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Συλλογικό Έργο

Επιµέλεια: Επίκουρος Καθηγητής Δελιάς Παύλος

Εκδόσεις ΤΕΙ Καβάλας

Οκτώβριος 2012, Καβάλα

6304187896039

ISBN 978-960-363-041-8

Χαιρετισµός του Προεδρείου του Συνεδρίου Αγαπητοί συνάδελφοι και φίλοι,

Η 9η Συνάντηση της Ελληνικής Οµάδας Πολυκριτήριας Ανάλυσης Αποφάσεων που

πραγµατοποιείται στην Καβάλα αποτελεί συνέχεια των αντίστοιχων συναντήσεων

προηγουµένων ετών. Εννέα χρόνια µετά την πρώτη συνάντηση η οποία πραγµατοποιήθηκε στα

Χανιά, το 2003, η φετινή συνάντηση αποδεικνύει ότι η συγκεκριµένη εκδήλωση αποτελεί πλέον

έναν πετυχηµένο θεσµό, ο οποίος υποστηρίζει σηµαντικά την επικοινωνία των Ελλήνων

ερευνητών του χώρου, συνεισφέρει στη διάδοση νέων ιδεών και αποτελεσµάτων και στην

ανάπτυξη νέων συνεργασιών, καθώς και στην περαιτέρω εδραίωση της πολυκριτήριας (ή

πολυκριτηριακής) ανάλυσης στην Ελληνική κοινότητα της επιχειρησιακής έρευνας.

Η Επιστηµονική Οµάδα της Πολυκριτήριας Ανάλυσης Αποφάσεων εµφανίζεται σαν η πλέον

δυναµική από το χώρο της Επιχειρησιακής Έρευνας στη χώρα µας, κάτι που φαίνεται από το

πλούσιο επιστηµονικό έργο των Ελλήνων ερευνητών και διεθνή περιοδικά υψηλού κύρους.

Η Ελληνική Εταιρεία Επιχειρησιακών Ερευνών σε συνεργασία µε το τµήµα Λογιστικής του ΤΕΙ

Καβάλας και το Κέντρο Τεχνολογικής Έρευνας Αν. Μακεδονίας και Θράκης έχουν καταβάλει

σηµαντικές προσπάθειες για τη διοργάνωση µιας πετυχηµένης Συνάντησης, η οποία αποσκοπεί

σε υψηλού επιπέδου επιστηµονικές προκλήσεις και δηµιουργεί µε σταθερό και εποικοδοµητικό

τρόπο νέους ερευνητικούς άξονες στο χώρο της επιχειρησιακής έρευνας και της διοικητικής

επιστήµης.

Ο αριθµός των ερευνητών που συµµετέχει στο συνέδριο ξεπερνά τους 90, ενώ έχει

προγραµµατιστεί η παρουσίαση 36 εργασιών. Οι εργασίες του συνεδρίου καλύπτουν ένα ευρύ

πεδίο θεωρητικών µεθοδολογιών της πολυκριτήριας ανάλυσης αποφάσεων αλλά και (κυρίως) µία

πληθώρα εφαρµογών σε τοµείς όπως τα πληροφοριακά συστήµατα διοίκησης, η διαχείριση

φυσικών πόρων και περιβάλλοντος, η παραγωγή και ο κατασκευαστικός τοµέας, η ποιότητα των

υπηρεσιών και η καινοτοµία, οι υπηρεσίες υγείας και τα χρηµατοοικονοµικά.

Πριν κλείσουµε το σύντοµο αυτό χαιρετισµό, θα θέλαµε να ευχαριστήσουµε τη Διοίκηση του ΤΕΙ

Καβάλας, η οποία στήριξε ποικιλοτρόπως τη διεξαγωγή του συνεδρίου, και χωρίς την οποία θα

ήταν αδύνατη η πραγµατοποίηση της συνάντησης. Επιπλέον, θα θέλαµε να ευχαριστήσουµε

τους πολύτιµους χορηγούς, τα Χρυσωρυχεία Θράκης και τις Εκδόσεις Κριτική. Τέλος, οφείλουµε

ένα µεγάλο ευχαριστώ στους εθελοντές του συνεδρίου για την αυταπάρνηση µε την οποία

βοηθήσανε στην πραγµατοποίηση της Συνάντησης.

Εκ µέρους τόσο της Επιστηµονικής όσο και της Οργανωτικής Επιτροπής σας καλωσορίζουµε για

άλλη µία φορά στη φιλόξενη πόλη της Καβάλας και σας ευχόµαστε καλή διαµονή

Παύλος Δελιάς, Πρόεδρος του Συνεδρίου

Νικόλαος Ματσατσίνης, Πρόεδρος της Ελληνικής Εταιρείας Επιχειρησιακών Ερευνών

Ιωάννης Σίσκος, Συντονιστής της Ελληνικής Οµάδας Εργασίας Πολυκριτήριας Ανάλυσης

9η Συνάντηση Πολυκριτήριας Οµάδας

iv

Περιεχόμενα

1η Συνεδρία

An integrated approach for Mutual funds Efficiency analysis and performance appraisal

(Vassilios Babalos, Michael Doumpos, Nikolaos Philippas and Constantin Zopounidis) ......................... 1

Supporting Financing Innovation for Green Energy Growth (Haris Doukas, Panos Xidonas and

John Psarras) ............................................................................................................................................... 2

Factors That Influence Customers to Switch Bank (Efstathios Dimitriadis and Maria

Xanthopoulou) ............................................................................................................................................ 3

Strategic decision making using multicriteria analysis: New service development in Greek

hotels (Fotis Kitsios, Konstantinos Giannikopoulos, Evangelos Grigoroudis, Michael Doumpos and

Constantin Zopounidis) ............................................................................................................................... 8

The Construction of Integrated Scenarios for Incorporation of Political Risk in Cash Flows and

The Valuation of Firms (Anagnostis Kipouros) ....................................................................................... 9


Strategic decision model for the evaluation of timber harvesting systems as applied in the

Forests (Vasiliki Dimou) .......................................................................................................................... 10

Multi-criteria analysis of planning decisions in mountainous areas with emphasis on land use

allocation (Konstantinos Tolidis and Efi Dimopoulou) ........................................................................... 14

Exploring Consumers Attitudes towards Paper Products that could derive from Genetic

Modified Trees (Lambros Tsourgiannis, Vasiliki Kazana, Anastasios Karasavvoglou, Christos

Antonios Tsourgiannis, Giannoula Florou and Persefoni Polychronidou) ............................................... 15

Πολυστοχικό Μοντέλο Γραµµικού Προγραµµατισµού για τη Βέλτιστη Σχεδίαση της

Εφοδιαστικής Αλυσίδας Καυσόξυλου (Γαρύφαλλος Αραµπατζής, Κωνσταντίνος Πετρίδης, Σπύρος

Γαλατσίδας και Δηµήτριος Δρόσος) ......................................................................................................... 16

SWOT Analysis on sustainable forest management policy and management. The Eastern

Macedonia-Thrace case (Vassiliki Kazana, Angelos Kazaklis, Dimitrios Fotakis, Christos

Stamatiou, Paraskevi Koutsona and Anastasia Boutsimea) ...................................................................... 17

9η Συνάντηση Πολυκριτήριας Οµάδας, Καβάλα, 11-13 Οκτωβρίου 2012

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Robust compromise programming of industrial scheduling jobs with variable criteria priorities

(Ioanna Makarouni, Yannis Psarras and Eleftherios Siskos) .................................................................... 18

A Simulation Methodology for Evaluating Dual Sourcing Strategies of a Discrete Part

Manufacturer (Dimitris Tsiolias, Christos Keramydas, Dimitrios Vlachos, Daniel Partsch and

Eleftherios Iakovou) .................................................................................................................................. 19

A synthesis of multi-criteria and cluster analysis approaches for the selection of the most

competent Construction Project Designer (Georgios Aretoulis, Christoforos Triantafillidis and

Jason Papathanasiou) ................................................................................................................................ 23

Πολυκριτήριος Χρονοπρογραµµατισµός Παραγωγής σε Συστήµατα Παραγωγής Job – Shop (Γ.

Π. Κουτσουβάλης, Α.Σ. Ξανθόπουλος και Δ. Ε. Κουλουριώτης) ............................................................ 24

Multicriteria route choice in road networks (Evangelos Mitsakis, Josep Maria Salanova Grau,

Evangelia Chrysohoou, Iraklis Stamos and Georgia Aifadopoulou) ........................................................ 25


Sustainable Energy for Rural Development: A Greek Case Study (Vangelis Marinakis,

Alexandra Papadopoulou, Haris Doukas and John Psarras) ..................................................................... 26

Integrated aquaculture – an old concept with new applications in Greece (Ioannis Vatsos,

Panagiotis Angelidis, Alexandros Theodoridis and Christos Batzios) ..................................................... 27

Assessing Scenarios on Maritime Transport Policies by means of Multicriteria Analysis: the

case of Greece (Eliza Gagatsi) ................................................................................................................. 31

Evaluation of investments in the field of renewable energy resources using MCDA (Ioannou

Konstantinos, Arabatzis Garyfallos and Zagkoumidou Vasiliki) ............................................................. 35

Assessment of the Rural Development Plan in Greece. A multicriteria analysis (Thomas

Bournaris, Christina Moulogianni, Basil Manos and Vassiliki Manthou) ................................................ 36

Ascendant Hierarchical Classification of individuals, who are determined by a number of

categorical, ordinal and quantative variables (Odysseas Moschidis and Vasileios Ismyrlis) ............. 37


Entropy measures to control robustness in ordinal regression models (Salvatore Greco, Yannis

Siskos and Roman Slowinski) .................................................................................................................. 38


vi

Robustness measures in criteria importance estimation based on Hamiltonian search

algorithms (Ch. Hurson, E. Siskos, N. Tsotsolas and N. Christodoulakis) ............................................. 40


Μια Αλγοριθµική Προσέγγιση Milp/Dea για το Βέλτιστο Σχεδιασµό Της Εφοδιαστικής

Αλυσίδας (Κωνσταντίνος Πετρίδης, Ευάγγελος Γρηγορούδης και Γαρύφαλλος Αραµπατζής) ............. 41

Μεθοδολογία Πολυκριτηριακής Ανάλυσης σε Συνδυασµό µε Υπολογιστικά Μοντέλα για

Αξιοποίηση Ανανεώσιµων Πηγών Ενέργειας σε Περιφερειακό Επίπεδο (I. Μουρµούρης και Κ.

Ποτόλιας) .................................................................................................................................................. 42

Using preference disaggregation to measure quality of life: A survey based approach (E.

Grigoroudis and C. Zopounidis) ............................................................................................................... 43

A Multicriteria Methodology for Non-Technical Skills Assessment of pilots at military aviation

(Krassadaki E., Tsifetakis Ε. and Matsatsinis Ν.) ..................................................................................... 44

Measuring health status using quality-of-life instruments: A multicriteria approach (Manolitzas

P., Grigoroudis E., Krasoudakis A., Archontakis G. and Matsatsinis N.) ................................................ 45


A multicriteria comparative analysis of cloud computing services from the user perspective

(Jason Papathanasiou, Vassilis Kostoglou and Dimitris Petkos) .............................................................. 46

A methodology for the assessment of online courses through Weighted Sum Model (Ioannis

Petasakis, Theodosios Theodosiou, Ioannis Kazanidis and Stavros Valsamidis) .................................... 47

Evaluation of heating systems in Greece using RetScreen software tool and Multi-Criteria

Analysis (Pantelis Antoniadis, Jacob Fantidis and Nikos Vordos) .......................................................... 51

Evaluating reorganization scenarios in an Emergency Department of a health care organization

using Multi criteria Analysis and simulation techniques (SIM-UTA) (Panagiotis Manolitzas,

Evangelos Grigoroudis, Petros Nikitakis, Maro Vlachopoulou, Nikolaos Matsatsinis) ........................... 56

A Comparison Study: E-Banking vs E-Commerce (Efstathios Dimitriadis, Despoina Kaltsidou and

Theoklitos Kaltsidis) ................................................................................................................................. 57

Authors’ List ........................................................................................................................................... 66

12ο Ειδικό Συνέδριο Ελληνικής Εταιρίας Επιχειρησιακών Ερευνών

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An Integrated Approach for Mutual Funds Efficiency Analysis and Performance Appraisal

Babalos Vassilios University of Piraeus

Department of Banking & Financial Management

80, Karaoli and Dimitriou Str, Piraeus, Greece

[email protected]

Zopounidis Constantin Technical University of Crete

Dept. of Production Engineering and Management

Financial Engineering Laboratory University Campus, 73100 Chania,

Greece [email protected]

Doumpos Michael Technical University of Crete

Dept. of Production Engineering and Management

Financial Engineering Laboratory University Campus, 73100 Chania,


Philippas Nikolaos University of Piraeus

Department of Business Administration

80, Karaoli and Dimitriou Str, Piraeus, Greece

[email protected]

ABSTRACT Mutual fund investors are concerned with the selection of the best fund in terms of performance among the set of alternative funds. This paper proposes an integrated approach for analyzing the efficiency and performance of mutual funds. The methodology combines data envelopment analysis (DEA) with a multicriteria decision aid (MCDA) methodology. DEA is employed to assess the relative efficiency of mutual funds in terms of their return, assets, gross expense ratio, turnover ratio, and risk. In a second stage, a multicriteria disaggregation method is employed to develop an overall performance measure on the basis of the DEA efficiency scores of the mutual funds. The resulting model

evaluates all mutual funds in a common basis and enables comparisons over time. The methodology is applied on a large sample of more than 500 US mutual funds over the period 2003-2010. The analysis is implemented under three different time-window periods (one, three, and five year evaluations) and the results are compared against the ratings of the mutual funds by Morningstar.

Keywords Mutual funds, Performance appraisal, Multicriteria analysis, Data envelopment analysis.


2

Supporting Financing Innovation for Green Energy Growth Doukas Haris

National Technical University of Athens

School of Electrical and Computer Engineering

9, Iroon Polytechniou str., 157 80 Athens, Greece

[email protected]

Xidonas Panos National Technical University of

Athens School of Electrical & Computer

Engineering 9 Heroon Polytechneiou Str., 15780,

Athens, Greece [email protected]

Psarras John National Technical University of

Athens School of Electrical and Computer

Engineering 9, Iroon Polytechniou str., 157 80


ABSTRACT From the current financial situation that many companies are facing in Greece emerges the opportunity for the transition from traditional economy to a “greener” economy. Renewables and energy efficiency are highly supported by the State, as an important mean to increase development. Indeed, green investments are currently attracting attention, since green projects are considered as a “top” priority.

Financing innovation is required, in terms of green banking strategies, to transform this opportunity to profitable investments.

In this respect, a proposed integrated decision support framework and corresponding prototype tools will be presented, aiming to support banks and FIs for:

1) Analyzing corporate environmental performance: Analysis of the environmental performance, both in the corporate and project level, in terms of measuring of the environmental footprint that derives from business activity as well as the provision of guidelines and interventions for improvement. The latter, in terms

of a targeted programme of strategic interventions, adapted to businesses’ environmental policy needs, is of significant importance for supporting enterprises, to become a driving force for the promotion of environmentally friendly practices.

2) Supporting banking organizations and institutions to select companies applying for financial support and credit granting: Incorporation of the companies’ environmental performance on the loan decision processes of banks and FI, fostering in this respect green energy growth. The critical point is that, besides budget constraints, additional credit policy constraints may impose bounds on the loan decision process and prevent from directly exploiting evaluations. A complex formulation is required, capable to effectively deal with the specific problem’s combinatorial character.

The proposed approach combines operational research and economic theory techniques, through web information technology.

Keywords Decision support, green energy, financing tools.


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Factors That Influence Customers to Switch Bank Efstathios Dimitriadis

Kavala Institute of Technology Agios Loukas 65 404, Kavala-Greece

+30 2510462304 [email protected]

Maria Xanthopoulou Kavala Institute of Technology

Agios Loukas 65 404, Kavala-Greece [email protected]

ABSTRACT In a severe and competitive market, many firms try to attract new customers and maintain the existing, through the creation of strong commitment and confidence. This theory is especially true when refers to financial institutions which efforts to connect their market strategies with new and advanced procedures, to succeed customers’ satisfaction and loyalty. The present study examines customers’ intention to switch bank, and the basic reasons causing such an action. Furthermore, it focuses to issues that can measure customers’ satisfaction according to the dimensions of a service. The results of a research, in a sample of 206 individuals indicate that the main reasons to switch bank are the banks’ staff and the reputation of the bank.

Keywords Bank Services, Customer Satisfaction, Loyalty.

1. INTRODUCTION In early 2011, 20 Greek banks with 3699 branches and 57970 employees operate in Greece. At the same time, 16 financial institutions and financial unions with 177 branches and 1293 employees there were. Moreover, 17 foreign banks with 287 branches and 5605 employees activate in Greece, while 6 Greek banks developed in Balkan countries, Turkey, Egypt, German and United Kingdom. However, the Greek banking system is concentrated around the largest Greek banks (Ethniki, Eurobank, Alpha, Piraeus, Attica, Emporiki and Geniki Bank) which have the largest market share. The increase in the number of Greek and foreign banks in combination with the relatively small increase in population has resulted in increased competition and the need to develop more and better marketing initiatives by the banks in order to maintenance their customers and moreover to attract new customers from other banks.

2. LITERATURE REVIEW Many researchers, focused on examining issues that influences the bank selection [1], market segmentation [2], banking relationship [3] and the satisfaction of bank customers [4]. Additionally, another research of Athanassopoulos [5], examines the quality of the provided services that reflects the satisfaction level, both on customers and business management. According to Mihelis and Grigoroudis [6], the satisfaction level of customers, on a variety of business, as well as to business on the financial sector, is the key component to success in the creation of an excellent organization. Furthermore, the satisfaction of customers reflects the ability of the staff to work efficiently, providing a sense of accomplishment that concentrates them to achieve higher levels of productivity [7]. Due to a research concerning the customers of banks in Australia and New Zealand, it was found that tree are the most important reasons for a customer to switch bank: “bank pricing”, the failure on servicing issues and services that cannot be satisfied [8]. The

results showed, that the most significant impact to switch bank is the pricing of bank. However the research focused on the relationship of the customer with its bank, measuring the dimension of them, such as the time of collaboration. It referred to the quality of the relationship and concluded to the strong link of relationship and intention to switch bank [9]. Another research made from Yavas et al. [10], was based to results that was coming out, comparing the type of relationship between characteristics of satisfaction and selected behavior, as well as the quality of service and secondary characteristics in Germany. It came out that the quality of provided service was of utmost importance for a customer to switch bank and it is accompanied with recommendations of individual. The research made clear that numerous “aspects of service quality” had a different impact on outcomes. Furthermore, the satisfaction of the quality of bank clients is examined separately in the research of Parasuraman et al [11], distinguishing the satisfaction of the quality of the provided services, to the satisfaction of the quality of the relationship with the bank. An important issue, introduced by Bejou and Palmer [12], suggests that customers defection, may occur from numerous transactions appears over time. Many researches which are focusing on single factors, seems to fail because they don’t manage to record multiple sections which can have a significant influence on clients intention to switch bank [8]. Another issue that has been examined in past researches is the cost of services, fair prices of them and the connection between prices and quality of services [13]. Furthermore, the location of the bank has been examined, testing the accessibility and security of the organization [14], [15]. Tangible assets, like the atmospherics and design of the building inside and outside, had a more controversial impact in a number of studies [16], [15]. Finally, a number of researches emphasise at the positive influence of controlling problems like potential conflicts, the ability of effectively solving the out coming problems and the speed of restoring those them [15], [13]. Manrai and Manrai [15], tested the switching behavior of bank customers, using six factors: the staff, the atmospherics, interest earnings, interest payments, ATMs and hours. Satisfaction level, importance and switching behavior of those factors were checked. In addition, the research of Mavri and Ioannou [17], tried to find predictions that reflects the intention of a customer to switch bank. Mihelis and Grigoroudis [6] measured the satisfaction level of banks’ clients in Greece. They examined how satisfied were the customers from the personnel, from the provided services and products, from the image of the bank and finally, from the access to the bank. The results showed that clients were more satisfied from the personnel and the access to the bank, that the other factors. It was also shown, that clients were not satisfied enough from the provided bank services and the information should be given in a more understandable way. Finally, Clemes et al. [18] based on the findings from literature review, as well as on the feedback of the focused group, tested the customers switching behavior in the Chinese retail banking industry. They examined


4

several factors that forces a client to switch bank; service quality, involuntary switching because of house changing, the affective advertising of a competitive bank, distance which means an inconvenient location of the bank, switching costs, demographic characteristics and the reputation of the institution. The last one is the factor that influences our research; the banks’ brand name. The reputation of the bank, gives positive signs to the public about the capability and reliability of the organization. They suggest that bank managers should investigate to build relationship of trust, increasing the loyalty of customers.

3. HYPOTHESES FORMULATIONT According to a research, done by Opinion Research Corporation (1984), the 25% of banks customers, transport at least one account from the existing institution to another. The reasons replying to why, are issues that have to do with charges for services, higher interest rates and better quality of services [15]. Mavri and Ioannou [17], argues that the service quality of a bank influences to the intention to switch bank. Studies in recent times are showing that the intention to switch bank now, is basically higher rates on credit cards, lower rates on accounts of saving money and the non-issuing of loans [19], especially during the latest years, when banks are experiencing the bank crisis. Except financial considerations, switching bank could be an action forced from other reasons such as service satisfaction and convenience [20], [21]. As a result, a customer could switch bank, due to one or more reasons dealing with financial considerations, servicing, and satisfaction level of servicing. Service quality could be a component of great importance. A research that has been done by Manrai and Manrai [15] indicates that customer satisfaction is a determinant of bank switching. So, a hypothesis connected to those reasons can be posed: Η1: The satisfaction level of a bank service could have a negative effect to the intention of switching bank. Manrai and Manrai [15] argue that all the customers do not have the same degree of sensitivity across the importance of a particular service and thus “importance of a particular service to a particular customer” is a crucial element in customers’ behavioral intention. Managers who are working on banks’ marketing sector know that different services do not have the same significance on different customers. A methodology called “Determinant Attributes” was introduced to measure that factor. This is a procedure that measures the reaction to attributes that are close to decisions or preferences made on purchases [22]. A research of Manrai and Manrai [15], indicates that the importance of the particular services offered by the banks, in addition to satisfaction, plays a serious role in the behavioral intention. H2: The importance given to a bank's particular service would mediate the influence of satisfaction on intention to switch bank, due to this service. Manrai and Manrai [15], note that the nature of competition for different banks’ services is a critical factor for the decision of the customers to switch bank. The dissatisfaction of a customer with a service of extreme importance does not drive the customer to change bank, if the competitive bank offers the same. This is true for financial dimensions of bank services but is not valid for non- financial services where the relationship between intention of switching and satisfaction is significantly affected by the importance of the service. As a result the tendency to change is caused from different factors meaning the average waiting time or staffs attitude. So, the hypotheses could be:

H3: The satisfaction of customers with financial considerations of a bank’s service could not vary from bank to bank, while the satisfaction with non-financial considerations could be different. H4: The change in the relationship between satisfaction and intention to change bank for one of its services is stronger for non-financial services than for financial when the service is of high importance. Through to literature review, it was found that many studies had as an object the effect of banks’ reputation to the customer. In fact, it was approved that banks are using their reputation to attach customers and increase profits [23]. Yue and Tom [24], proved that the procedure of selection bank, could be strongly influenced from the reputation of bank. This can happen because a good reputation of a bank increases the level of trust, in contrast of the bad reputation which causes negative effects on switching bank [18]. It would be useful then to examine: H5: There is a negative relationship between banks’ reputation and the intention of switching bank

4. RESEARCH METHODOLOGY 4.1 Sample and Data Collection In order to achieve the objectives of this study a survey, from May to September in 2011, was conducted. As research instrument a structured questionnaire was used, and the target population of our study was Greek customers of the banks. The sample was randomly selected and it is consisted of people having as a characteristic an existing relationship with a financial organization in Greece. The questionnaire was distributed through e-mails, social networks and via personnel interviews. The final sample size consists of 206 usable questionnaires where 51% of the respondents were women and the rest 49% men. The 47% of the answers were given from young people (26-35 years old), while the 31% were private employees, 22% businessmen/self employed, 15% were public servants, 14% were unemployed/housewife and students and the rest 6% of the respondents, were pensioners. The highest level of monthly income is noted on the <600€ scale with 27%, 15% of the sample earns 1001€-1300€, 19% of the respondents 801€-1000€, 22% has a monthly income >1300€ and finally 18% of the respondents earns 601€-800€. 41% of the sample uses bank services one to three times per month, 31% one to four times per week, 17% one to five times per six months, 7% daily and the rest 5% onetime per year.

4.2 Questionnaire’s Description The research instrument of this study consists of two parts. The first one refers to the demographic characteristics. The second and most important part of the questionnaire consists of 35 questions adopted from the works of Mihelis and Grigoroudis [6] and Manrai and Manrai [15] and is divided in four groups, based on the style of issues to consider. The first 13 questions are related with personnel related considerations. The second group of 7 questions deals with environmental related considerations. Another group of 9 questions analyses the financial related considerations and finally, the last group of 5 questions is related with convenience considerations. The respondents were asked to answer in the 34 questions three times. Firstly, based on the level of satisfaction on those characteristics, as they cooperate with the bank they chose. At the second level of the research, they were asked to focus to the importance of the same 34 questions and finally the questionnaire concluded to the intention of switching or not a bank according to those characteristics. The section that


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focuses on the satisfaction level of bank services is answered using a five point Likert scale, starting from 1= extremely dissatisfied, 2= dissatisfied, 3= neutral, 4= satisfied, and 5= extremely satisfied at the end. The same procedure is followed to the other sections measuring the importance and intention to switch bank. (1= Unimportant, 2= of little importance, 3= moderately, 4=important and 5=very important for the second part, and 1= extremely likely, 2= likely, 3= possible, 4= unlikely and 5= extremely unlikely for the last part). The last question asks the individuals to evaluate the reputation of the chosen bank of cooperation using a Likert scale starting from 1= Very bad to 5=Very good.

4.3 Reliability and Validity Analysis Before analyzing the data that have been collected, it is necessary the test of validity and reliability of the questionnaire. This procedure includes the following steps: Firstly, exploratory analysis of reliability and secondly, the validity analysis. According to Cronbach [25], the assessment of reliability is consisted of two steps. The first one is the calculation of Cronbach’s alpha index and the next one is the test of unidimensionality for each factor. Reliability measures the internal consistency of each factor and the measurement tool is the Cronbach’s alpha index. Values greater than 0,7 indicate reliable factors. After the exploratory analysis of reliability in our sample, we have Cronbach’s alpha index for each one of the four factors of our, related to the satisfactions level. The indices showed satisfying results on the second and third factor. On the other hand, the first factor that deals with the staff, outcome the result of a= 0,654. For this reason, three variables were removed. After the delete of those variables, the index became a= 0,887. Following the same procedure on the fourth factor, two were the variables that had to be removed. This change, replaced the initial outcome of a= 0,505, with an acceptable one a= 0,802. The unidimensionality of each factor was tested using exploratory factor analysis. The Principal Component Method of factors’ extraction and the Varimax method of orthogonal rotation of the axes were used in order to test the unidimensionality. The results that came out from the factor analysis that were performed for every one of the four factors, concerning the satisfaction, were good enough to be used. To be specific, the Measure of Sampling Adequacy (MSA) of Kaiser-Mayer-Olkin, which is widely known, outcomes results that ranges from 0,709 to 0,900. According to Sharma [26], the K.M.O. index of the total sample suitability, should be greater of 0,7. The loadings of the variables are enough satisfying and statistical significant, as they note prices greater in absolute value, of 0,50 for a sample bigger from 150 respondents that Hair et al. [27], do recommend. The total variance explained, gives measures that ranges from 54,90% to 72,23%. The validation of the research instrument is consisted from two tests: the first one is the test for content validity and the second the test for construct validity [28].Content validity describes if all possible items of the research are represented. A research has content validity if the entire range of the possible facets of the examined subject, are covered [29]. This research has content validity because it uses a questionnaire that was created from the combination of two familiar researches that examined the same topic in the past. Additionally, the questions were checked from expert judges of the sector, who confirmed its content validation. For the assessment of construct validity two tests are usually performed. The first one measures the convergent validity and the second the discriminant validity. According to Sanzo et al. [30], there is evidence for convergent validity if all the items used, have

loadings greater than 0,5 and are statistically significant. Evidence for discriminant validity exists, if all correlations between factors are lower than the a index. In this study all loadings cover the restricting that has been mentioned above.

5. DATA ANALYSIS We begin with the test of the first hypothesis (H1) using a simple Pearson’s correlation analysis, between satisfaction and intention to switch bank. From the results shown on the table 1, arise that there is a negative and significant correlation between satisfaction and intention to switch bank, in the first and fourth factor (personnel, ATM’s). So, we can say that H1 is partially accepted.

Table 1. Hypothesis 1

Factors Correlation Coefficient Sig. Personnel -0.243 0.000 Environmental Cons. -0.024 0.737 Financial Cons. -0.076 0.277 ATM’s -0.384 0.000

For testing H2, a partial correlation analysis (Pearson) was used and the results are shown in the table 2. Here, we can see how the importance of an item could acts as an mediator between satisfaction and intention to switch or not the basic bank of cooperation, according to the banks’ staff, the environmental and financial considerations and the use of ATM’s. We notice a negative correlation, which is significant (sig.<0.05), between satisfaction and intention to switch bank, to the personnel and ATM’s categories. However, the correlation to the rest of the categories, meaning environmental and financial considerations, is positive and not significant. So, the significance and the intention to switch bank to each one of those four categories improves, when the importance of them can be controlled. The importance of the factor cannot independently influence the intention of switching bank but, as it was hypothesized, the importance has a mediating role. Thus H2 is partially supported.

Table 2. Hypothesis 2

Factors Partial Correlation coefficient

Sig.

Personnel -0.141 0.044 Environmental Cons. 0.048 0.498 Financial Cons. 0.097 0.166 ATM’s -0.400 0.000

To test the hypothesis 3, an Analysis of Variance (ANOVA) was performed and the results, shown in the table 3, indicates that non-financial factors do vary across different banks but the same result is out coming for the financial factors, also. So, we can say that the H3 is accepted for non-financial and rejected for financial related considerations.

Table 3. Hypothesis 3 F Sig.

Non-financial

Satisfaction-Personnel 5.804 0.000 Satisfaction-Environment 7.625 0.000

Satisfaction-ATM’s 4.877 0.000 Financial Satisfaction-Financial 3.837 0.000

For hypothesis 4, a simple correlation analysis was performed and the results are shown in the table 4. As we can see, the connection between the satisfaction level of a service and the intention to


6

switch bank because of that service, is still negative. Additionally, this outcome shows that the importance level of a service varies across different groups of services. The last column shows the difference between the absolute prices of simple and partial correlation. That difference tends to take the lowest price for the financial considerations and the greatest prices for the non-financial, suggesting that the satisfaction level of non-financial services, influenced from the factor of importance, has a greatest impact to the intention of switching bank, than of the financial. So, it can be said that H4 is partially supported.

Table 4. Hypothesis 4 Simple

Correlation Partia

l Dif.

Non-financial

Personnel -0.243 -0.141 0.102 Environment -0.024 0.048 0.024

ATM’s -0.384 -0.400 0.016 Financial Financial -0.076 0.097 0.021

The last hypothesis (H5), indicates that there is a negative relationship between the reputation of a bank and the intention to switch bank because of it. Here we tested the probability of switching bank because of its reputation, in the four categories we examine, staff, environment, financial and ATM’s. The results shown in the 5, indicates the accuracy and the significance of that hypothesis. So, the last hypothesis H5 is fully supported.

Table 5. Hypothesis 5 Reputation of

the bank Sig.

Pers. Env. Fin. ATM’s -0.717 (0.000)

-0.393 ( 0.000)

-0.268 ( 0.000)

-0.150 (0.033)

6. CONCLUSIONS The level of satisfaction from the banks’ staff is higher than the level of satisfaction from the environmental and financial considerations, as well as ATM’s. Additionally, the importance of the fourth factors insisting again on the first factor connected with the banks’ staff. Is unlikely for an individual, who is satisfied with the staff of the bank he/she cooperates to switch bank because of that factor. Generally, all four factors are significant and should be taken into consideration from a bank director. If a customer is satisfied from the staff, the environment, the ATMs machines of the bank and at the same time is partially satisfied from the financial considerations also, it is more unlikely to switch bank. Another factor that can make an individual to switch financial organization is the reputation of the bank. As the reputation of a bank tends to be high, there is lower intention for its customers to switch bank.

7. REFERENCES [1] Anderson, W.T and Fulcher, D.G. 1976. Bank Selection

Decisions and Market Segmentation, Journal of Marketing, 40, 40-45

[2] Hood, J.M. and Walters, C.G., 1985. Banking on established customers. Journal of Retail Banking 7 (1) (Spring), 35–40.

[3] Berry, L.L. and Thompson, T.W. 1982. Relationship banking: the art of turning customers into clients. Journal of Retail Banking 4 (2) (June), 64–73.

[4] Athanassopoulos, A. 2000. Customer Satisfaction Cues to Support Market Segmentation and Explain Switching Behavior’, Journal of Business Research, Vol. 47, pp. 191-207.

[5] Athanassopoulos, A. 1997. An Optimization Framework of the Triad: Capabilities, Service Quality, and Performance, in Efficiency of Financial Institutions (Special Issue), Cambridge University Press, Cambridge.

[6] Mihelis, G. and Grigoroudis, E. 2001. Customer satisfaction measurement in the private bank sector, European Journal of Operational Research, Vol. 130, pp. 347-360

[7] Gerson, R.F. 1993. Measuring Customer Satisfaction, Menlo Park, CA.

[8] Colgate, M and Hedge, R. 2001. An investigation into the switching process in retail banking services, International Journal of Bank Marketing, Vol.19 No 5,pp. 201-212

[9] Chakravarty, S., Feinberg, R. and Rhee, E. 2004. Relationships and individuals’ bank switching behavior, Journal of Economic Psychology, Vol.25, pp. 507

[10] Yavas U., Benkenstein M. and Stuhldreier U. 2004. Relationships between service quality and behavioral outcomes: A study of private bank customers in Germany, International Journal of Bank Marketing, Vol. 22, pp. 144-157.

[11] Parasuraman, A., Zeithaml, V.A. and Berry, L.L. 1985. A conceptual model of service quality and implications for future research, Journal of Marketing, 41–50.

[12] Bejou D. and Palmer A. 1998. Service failure and loyalty: an exploratory empirical study of airline customers, Journal of Services Marketing, Vol.12 pp. 7-22.

[13] Levesque, T. and McDougall, G.H. 1996. Determinants of customer satisfaction in retail banking, International Journal of Bank Marketing, 14 (7), 12–20.

[14] Oppewal H. and Vriens M. 2000. Measuring perceived service quality using integrated conjoint experiments, International Journal of Bank Marketing, Vol. 18, No 4, pp. 154–169.

[15] Manrai, L.A. and Manrai. A.K. 2007. A field study of customers’ switching behavior for bank services, Journal of Retailing and Consumer Services, Vol. 14 pg. 208-215.

[16] Jones C. 2004. Developing a scorecard for service quality, Management Services, Vol. 48, pp. 8–13.

[17] Mavri M. and Ioannou, G. 2008. Customers switching behavior in the Greek banking Services: a case studies , Managerial Finance Vol.34 pp.186-197

[18] Clemes M.D., Gan C. and Zheng L.Y. 2007. Customers switching behavior in the New Zealand banking industry, Banks and Banks System, Vol.2, pp50-66.

[19] Moutinho L. and Meidan A. 1989. Banks customers’ perceptions, innovations and new technology, International Journal of Marketing, Vol.7 pp. 22-27

[20] Gwin J.M. and Lindgren J.H. 1986. Reaching the service sensitive retail consumer’, Journal of Retail Banking, Vol.8 pp.36-42

[21] Manrai L.A. and Manrai A.K. 1995. Why do customers switch bank services: some managerial implications (Abstract), In: H. Timmermans (Eds.), Second recent advantages in retailing and services science’, The European Institute of Retailing and the Canadian Institute of Retailing and Services Studies


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[22] Alpert M.I. 1972. Identification of determinate attributes-a comparison of methods, Journal of Marketing Research, Vol.8, pp.184-191.

[23] Weigelt K.and Camerer C. 1988. Reputation and corporate strategy: a review of recent theory and application, Strategic Management Journal, Vol.9 pp.443-454.

[24] Yue H. and Tom G. 1995. How the Chinese select their banks, Journal of Retail Banking, Vol.4 pp.36-39.

[25] Cronbach, L. J. 1951. Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297–334.

[26] Sharma, S. 1996. Applied Multivariate Techniques, New York, Willey.

[27] Hair, J.F. Jr, Anderson, R.E., Tatham, D.L. and Black, W.C. 1995. Multivariate Data Analysis with Readings, 4th ed., Prentice-Hall, Upper Saddle River.

[28] Flavian, C. and Lozano, F. 200). Diseno de una escala para medir la orientacion al entorno de la nueva formacion profesional. Cuadernos de Economıa y Direccion de la Empresa, 15, 333–363.

[29] Golafshani, N. 2003. Understanding reliability and validity in qualitative research, The Qualitative Report, Vol. 8 No, 4, pp. 597-607

[30] Sanzo, M.J., Santos, M.L., Vazquez, R. and Alvarez, L.I. 2003. The effect of market orientation on Bayer-Seller Relationship satisfaction. Industrial Marketing Management, 32(4), 327-345.


8

Strategic Decision Making Using Multicriteria Analysis: New Service Development in Greek Hotels

Kitsios Fotis University of Macedonia, Department

of Technology Management Loggou-Tourpali, 59200, Naousa-GR

(+30) 23320 52467

[email protected]

Doumpos Michael Technical University of Crete,

Department of Production Engineering and Management

University Campus, 73100 Chania, GR (+30) 28210 37318

[email protected]

Giannikopoulos Konstantinos TEI Kavalas, Department of Business

Administration Ag. Loukas, Kavala, 654 04, GR

(+30) 2510 462177

[email protected]

Zopounidis Constantin Technical University of Crete,



[email protected]

Grigoroudis Evangelos Technical University of Crete,



[email protected]

ABSTRACT The importance of service development is particularly marked in developed countries, where the service sector accounts for more than 70% of economic activity. It is likely that the share of services will accelerate in the short and medium terms, taking into account the ongoing shift towards knowledge-based, service-oriented activities in many countries (OECD).

The economic crisis in Greece can be treated primarily by exploiting the competitive advantages of domestic production. Greek products and services are necessary to gain competitive features and increase their share in international markets. In this area Greek tourism and especially hotel services are mainly addressed international markets. The sector resists, despite intense competition from emerging tourism destinations, with more economic offers. What strategy should Greek hotels follow in an effort to maintain or improve market shares in domestic and international markets? How a service differentiation strategy can help give a competitive advantage?

This study is based on two previous studies. The first study focuses on a better understanding of how successful new hotel services are developed and investigates the factors, which have impact on success and failure in new service developments (NSD) in the hotel sector. The results of the exploratory study are concluded in a predictive model which can distinguish future success cases from failure. The predictive model conducted with multivariate statistical methods (Kitsios, 2005).

The second study used the same data collected via in depth structured interview with questionnaires from hotel managersand the results compared with multicriteria methodologies and specifically with UTADIS method which showed almost the same

critical success factors but in more accurate prediction (Kitsios et al 2009).

The purpose of this study is to gain insight only in factors that have emerged from previous studies as significant in contribution to the success or failure. Additionally it considered important to change the scale measuring the dependent variable that determined the success and failure using a five-point Likert-type point scale than a two-point. Finally, the overall customer satisfaction from services provided by the hotels measured also in a previous manner. The data collected by hotels in Eastern Macedonia via in depth structured interview with questionnaires from hotel managers.

Keywords Differentiated Service Innovation strategies, new service development, tourism and Hospitality services, critical success factors, Multicriteria analysis.

REFERENCES [1] Kitsios, F., Doumpos, M., Grigoroudis, E., Zopounidis, C.

(2009) Evaluation of new service development strategies using multicriteria analysis: Predicting the success of innovative hospitality services, Operational Research 9 (1), pp. 17-33.

[2] Kitsios, F., (2005) Innovation management in new service development, PhD dissertation, Technical University of Crete.


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The Construction of Integrated Scenarios for Incorporation of Political Risk in Cash Flows and The

Valuation of Firms Kipouros Anagnostis Accounting department,

Kavala Institute of Technology, 65404 Agios Loucas Greece [email protected]

ABSTRACT The technique of the incorporation of political risk in the Cash flows and for the computations of “risk premium”, shapes a "tripartite" or three phase scenario where are connected:

a) The national and international macroeconomic developments b) The effect s in the market sector and his own self-reliant course c) The corporate output/ performance that is shaped however in the dynamics of developments of macro and sector-based data.

The main macroeconomic variables that should make forecast are:

1) The rythm of increase of G.D.P. 2) The rythm of inflation and his future developments. 3) The rate of change of exchange rate parities and their

tendencies of change in the near and intermediary future. 4) The “running” interest-rates and the time structure of interest-

rates 5) The deficits of balance of payments and the fiscal debt and the

running budget deficit.

These work out or depicted the future economic reality.

We know also that the increase of GDP and the inflation are the most decisive forces, for the determination of exchange rate parities, for their revaluation or depreciation course and from this assessment depends the value of companies (valuation).

When therefore is selected a scenario of high inflation, the exchange rate parity will be moved proportionally in depreciatory direction in long- run, because of the adaptations with the "Purchasing power Parity" that is the regulator of parities between the various currencies.

In the second stage is determined, how each connected element of cash flows, is determined and defined, by the changes of macroeconomic variables, at a way that every rate of change, are automatically adapted positively or negatively the constitutive elements where have strong effects in the structure of cash flows.

EFFECTS IN SECTOR-BASED VARIABLES FROM POLITICAL DEVELOPMENTS IN EMERGING MARKETS.

The effects and results of “sector-based effects” are applying on this scenario with less variables as happens also for the developed markets, with the addition however, that here the sector-based variables are more influenced from the governmental practices and policies.

So here enters (in cash flows formation) more intensely the political element, concerning the Macroeconomic variables, with the addition however, that the sector-based variables are more influenced from the governmental practices and policies.

So here the political element enters more intensely in the cash flows, concerning the Macroeconomic variables.

The SECTOR-BASED INFLUENCE

For example some enterprises exclusively importation raw material or products) or exportation enters more intensely the political element concerning the Macroeconomic variables.

Therefore the income of them are determined by the economic urges of third person action, therefore they are not influenced substantially by the internal developments like of them of international environment.

Recent examples of classic SECTOR-BASED influence by the governmental practice are in Russia, where for example the sector of petroleum products, with the adventures of company YUKOS, not only fell rapidly her price in the stock Exchange of Moscow, but entered also in adventures and faced a shook, with events like the reduction of oil production, bad references about managerial executives and her stockholders, insolvency in the foreign markets and a serious loss in markets and sales, with negative evolutions which has serious repercussions in her viability.

For the calculation of cost of capital in the practice of real world the prices / values are more changeable, so we should use various approaches and finally we select "areas of prices" that is determined by the analysis of possibility-weighted within a completed scenarios, where the "discounted cash flows", e.g. with one of long-run “Risk Premium of country“, with factor from 1,5% 2,2% in the medium weighted “cost of capital” and the "indicators of efficiency" on the market prices.


10

Strategic Decision Model for the Evaluation of Timber Harvesting Systems as Applied in the Forests

Dimou Vasiliki Department of Forestry and Management of the Environment and Natural Resources

Demokrition University of Thrace, Department of Forestry-Geology-Hydrology

TU Dresden, Germany. 3 Cohran str. 65201 Kavala

+30 6947800872

[email protected]

ABSTRACT In the present study a strategic decision model was used in order to evaluate and classify timber harvesting systems for the forests of Northeastern Greece. Within the frame of this model, five systems were selected through literature review in terms of suitability for the afore-mentioned forests. The systems were subsequently evaluated against certain assessment criteria, which fell into three groups: financial, ecological and social. In accordance with the method developed at the Department of Forest-Technology, University of Dresden, the criteria had been customized to suit the specific needs of the Greek population and the given environmental conditions in which they were to be applied. The timber harvesting systems under investigation were at an initial stage rated by experienced foresters with the use of the Delphi method. Subsequently they were ranked by ten Forest Directorates according to goals and objectives set by each Directorate. Timber harvesting systems which employed low-level mechanized transportation methods occupied the last positions in the rank, whereas those that used full mechanization occupied first positions. It is of great interest that the partially mechanized harvesting system that uses log chutes reached one of the top positions in the rank in terms of ecological and social criteria, although it was rejected on the grounds of economic criteria

Keywords Decision theory, strategic decision model, timber harvesting systems, evaluation, ranking, assessment.

1. INTRODUCTION Efficient timber harvesting depends on a variety of factors such as road networks, equipment and machinery, skilled forest laborers etc and has a plethora of impacts: apart from the profits that it generates for the forest enterprise, it can also have positive effects on long-term ecological and social values [26]. It is clearly a complex set of operations and as a result the evaluation and analysis of timber harvesting systems should take into account stand and terrain data as well as ecological, economic and social consequences [18], [20], [22], [25], [12]. In addition, the development of new technologies and the increase in production costs necessitate the continuous review of the systems used [14]. Selecting the most suitable logging system that combines both cost effectiveness and minimal adverse

impact to the forest environment means taking all the above factors into consideration.

To estimate the effects of changes in management a decision support tool is helpful, especially for tactical and strategic goals [17], [19], [16].

When in decision making several factors are involved, it is essential to set rules with the help of a model in order to ensure that the decision making process becomes comprehensive and concise [9], [13], [6].

Decision theory (Entscheidungs theorie) enables the formulation of analytical techniques in order to lead to strategic decisions. All alternatives are rated according to rules and thus acquire a certain value of importance. The best alternative is the one that gains the highest importance value [9].

Generally speaking, the classification of alternatives is not difficult when there is a small number of a criterion involved. However, evaluation is usually performed with the use of more criteria, a fact that makes it a particularly demanding task. For this reason, various models of evaluation have been developed such as the Cost-Benefit Analysis or the Utility Analysis [5].

The present study investigates the possibility of applying low-level mechanized timber harvesting systems that have never been used in Greek forests. The relatively small cut that Greek forests yield and the selective timber felling practices that are dominant in Greece favor the use of small and maneuverable machinery with low investment costs. In total five harvesting systems were studied, of which only one had already been applied in the Greek context. The investigation of the systems as well as of their limitations focused on economic, ecological and social criteria.

2. STUDY AREA-METHODOLOGY The first stage of the study involved the selection of the logging systems. As mentioned above, all the systems were chosen from literature with the exception of the first one which is already applied in Greece. The systems selected are the following:

A. Long-length system – fully mechanized: All processing operations are performed in the harvest area, namely felling, delimbing, measurements and crosscutting. Prehauling and


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hauling take place in a single work phase using a tractor with a winch.

B. Short-wood system – medium-level mechanized: Processing takes place entirely at the tree stump. Prehauling is performed with a mini-tractor (sleigh). The wood is initially stacked in the skid road and then transported on a tractor towing a trailer.

C. Long-length system - partially mechanized: Entire processing takes place at the tree stump. Prehauling is done with a mini tracked tractor. Firstly timber is stockpiled in the skid road and then it is transported with a winch-equipped tractor.

D. Short-wood system - partially mechanized: Processing is finished at the tree stump. Prehauling is done with a mini winch. Logs are initially gathered in the skid road and then they are transported by tractor plus trailer.

E. Short-wood system - partially mechanized: Whole processing is finished at the tree stump. Timber is transported manually up to the top of the chutes. Prehauling is done with the chutes up to the forest road. Afterwards timber is transported with a trailer-equipped tractor.

The systems under consideration, of which there is no practical experience in the Greek context, had to be forecast with a certain probability, a procedure carried out by experienced “on the ground” foresters.

Τhe logging systems were evaluated with the aid of certain assessment criteria. According to the method developed in the Department of Forest Technology, Dresden University, a stratified system of ranking or hierarchy of goals is structured on the basis of a logically determined relation. In order for a goal to be clearly defined and comprehended it must be vertically branched downwards into more specific objectives. In the present study three goals - economic, ecological and social - were given on a first level. These three basic goals were then divided into six partial goals. Each partial goal was further divided into two or three assessment criteria, according to which the evaluation and rating of the systems were performed (Fig. 1) [4].

With the use of the afore-mentioned criteria the systems were rated by means of a structured interview [21]. The questions were answered by 10 experienced foresters and the whole procedure was based on the Delphi method [7], [3]. The Delphi method, which is a forecasting study, constitutes a strategy tool according to Ben R. Martin (1993). The expert is given the chance to formulate an opinion or revise it in three repeated questioning rounds influenced by the opinions of the other experts [7], [3].

The third stage of the study consisted of ranking the timber harvesting systems based on the results of the research into the individual goal system adopted by each of the ten Forest Directorates (Sidirokastro, Serres, Drama, Kavala, Thassos, Xanthi, Comotini, Alexandroupoli, Soufli, Orestiada and Didimotiho). The theory of goals (Zieltheorie) is based on the fact that every organization adopts its own goal system which functions as the main driving force in every decision making process [5]. According to [11], a hierarchy of alternatives can be constructed only after the compilation of a system of goals. Goal systems form the basis of an alternative appraisal [13].

1.Financial

Goals

1.1a 1.1b 1.1c 1.2a 1.2b 2.1a 2.1b 2.1c 2.2a 2.2b

1.1

3.1a 3.1b 3.2a 3.2b 3.2c

1.2 2.1 2.2 3.1 3.2

Assessment criteria

Partial goals

2.Ecological 3.Social1.Financial

Goals

1.1a 1.1b 1.1c 1.2a 1.2b 2.1a 2.1b 2.1c 2.2a 2.2b

1.1

3.1a 3.1b 3.2a 3.2b 3.2c

1.2 2.1 2.2 3.1 3.2

Assessment criteria

Partial goals

2.Ecological 3.Social

Figure 1: Assessment criteria 1.1a: Applicability, 1.1b: Productivity, 1.1c: Transportability, 1.2a: Profitability, 1.2b: Adaptability

2.1a: Vitality, 2.1b: Biodiversity, 2.1c: Soil & water protection 2.2a: Saving energy, 2.2b: Saving on indirect recourses

3.1a: Recreational compatibility, 3.1b: Respect of local cultures, 3.2a: Reduction of the crew’s fatigue, 3.2b: Prevention of accidents, 3.2c: Increase of the crew’s self-esteem.

In the present study a total of five timber harvesting systems were rated with the use of the Delphi method and the goal systems of 10 Forest Directorates were investigated. On the basis of the results of the rating process the systems under study were ranked in order of importance.

The five systems that were selected concern the forest complexes of Pageo-Kavala, Frakto and Elatia-Drama. The systems were selected in terms of functionality since they were considered technically functional. One of the systems (A) is already applied in the Drama and Kavala regions. The other four (B, C, D and E) are theoretical and not in use in Greece. The aim of the present study is to compare the traditional harvesting system (A) with the ones that have not been tried in the Greek harvesting context. The relatively small cut of the Greek forests coupled with the selection felling operations applied in Greece is a problem for the Greek forestry. For this reason, the logging systems that are included in the present study are applied with less technologically advanced transportation machinery. Their selection was made by taking into consideration their maneuverability in the felling site and the low initial investment costs.

3. RESULTS The rating results are presented in Table 1.

The lowest value of the fulfillment degree is 0 and denotes a ‘bad alternative’ and the highest value is 1 which denotes a ‘good alternative’ [1], [2]. Shows that each harvesting system is given a degree as far as each of the 15 criteria is concerned. A score equal to or lower than 0.4 is considered an unsatisfactory score [23].

The classification of the harvesting systems was carried out by means of crosschecking the goal systems of the 10 Forest Directorates with the results presented in [15], [3].

Of the four priorities structures presented above (Suppression of goals, lexicographic order of goals, Maximization of a goal at a given requirement level and gravity of goals) the Forest


12

Directorates of Xanthi and Comotini selected the lexicographic order (first goal of choice: ecological compatibility, second goal: social acceptability). According to this system of goals and the rating presented in, top position is occupied twice by harvesting system E (short-wood system with log chutes) due to its high ecological compatibility whereas second position is occupied twice by system D (short-wood system with mini-winch). Last position is occupied twice by system C (short-wood system with mini tracked tractor) due to its poor ecological compatibility.

The next four systems of goals (given by Didimotiho, Alexandroupoli, Drama and Kavala) were structured according to prioritization type c - maximization of a goal at a given requirement level, which was stated equal to 0.4. First position was occupied four times (Didimotiho, Alexandroupoli, Drama and Kavala) by system A (long-length-system with tractor plus winch) due to its high ecological compatibility. Second position was occupied three times (Didimotiho, Alexandroupoli, Drama) by system C (long-length system with mini tracked tractor). The other three systems (B, D and E) were rejected. For instance, they were rejected four times (by Didimotiho, Alexandroupoli, Drama and Kavala), whereas system C was rejected three times due to its low operational ability and financial efficiency.

Table. 1: Rating of the five harvesting systems Goals Financial Ecological Social

Part

ial g

oals

Ope

ratio

nal a

bilit

y

Fina

ncia

l eff

icie

ncy

Eco

logi

cal c

ompa

tibili

ty

Eco

logi

cal e

ffic

ienc

y

Soci

al a

ccep

tabi

lity

Soci

al e

ffic

ienc

y

1.1a

1.1b

1.1c

1.2a

1.2b

2.1a

2.1b

2.1c

2.2a

2.2b

3.1a

3.1b

3.2a

3.2b

3.2c

0,7 0,8 0,8 1 0,5 0,6 0,5 0,6 1 0,4 0,7 0 0,7 0,5 0,2

Sys

tem

A

0,8 0,8 0,6 0,7 0,6 0,50,4 0,4 0,4 0,4 0,3 0,6 0,3 0,6 1 0,6 0,6 1 0,6 0,5 0,1

Sys

tem

B

0,4 0,3 0,5 0,8 0,8 0,40,5 0,4 0,4 1 0,3 0,6 0,4 0,4 1 0,5 0,6 0,7 0,6 0,5 0,2

Sys

tem

C

0,4 0,7 0,5 0,8 0,7 0,40,4 0,3 0,3 0,4 0,2 0,6 0,6 0,6 1 0,6 0,7 0,9 0,6 0,5 0,1

Sys

tem

D

0,3 0,3 0,6 0,8 0,8 0,40,1 0,2 0,3 0,1 0,7 0,7 0,7 0,7 1 0,7 0,7 1 0,5 0,6 0,1

Sys

tem

E

0,2 0,4 0,7 0,8 0,9 0,4 The next four systems of goals (given by Thassos, Soufli, Sidirokastro and Serres) were structured according to priorities type d - gravity of goals. First position was occupied four times (Thassos, Soufli, Sidirokastro and Serres) by logging system A (long-length system), second position was occupied four times by system E (short-wood system with log chutes) and last position was occupied four times (Thassos, Soufli, Sidirokastro and Serres) by system B (short-wood system with mini tractor - sleigh).

The study yielded the following ranking:

Ø First position was occupied by harvesting system A (long-length, prehauling – hauling with a tractor).

Ø Second position was occupied by harvesting system E (short-wood, prehauling with log chutes – hauling with a tractor).

Ø Third position was occupied by harvesting system C (long-length, prehauling with a mini tracked tractor – hauling with a tractor).

Ø Fourth position was occupied by harvesting system D (short-wood, prehauling with a mini winch – hauling with a tractor), and

Ø Fifth position was occupied by harvesting system B (short-wood, prehauling with a mini tractor-sleigh – hauling with a tractor).

4. CONCLUSIONS The five harvesting systems investigated in the present study constituted alternative solutions for the forest complexes of Pageo (Kavala) and Frakto and Elatia (Drama). They were evaluated against certain financial, ecological and social criteria.

Harvesting systems in which prehauling is done with low mechanized machinery as is the case with systems B, C and D (employing a mini tractor - sleigh, a tracked mini-tractor and a mini-winch respectively) are not preferred; on the contrary they are the most frequently rejected harvesting systems.

The most dominant goals to be achieved were of ecological nature, such as the goal of ecological compatibility and ecological efficiency; besides financial goals played an important role.

As it is shown from the results, classification of harvesting systems depends on the initial goals set by each Forest Directorate. In other words, there is a strong correlation between the individual system of goals adopted by a Forest Directorate and deciding which harvesting system to choose. In this sense the importance of the decision maker (the Forest Directorate) is enhanced.

5. DISCUSSION Decision making in timber harvesting has long-term consequences on the further development of forests. Decisions about harvesting activities are often based on intuition and the consequences of these actions cannot be determined exactly [14].

The harvesting systems under consideration were evaluated by experts in terms of five economic, five ecological and five social criteria. The great number of criteria rendered the classification of all the alternative timber harvesting systems difficult. Each system met certain criteria but did not meet others to a satisfactory extent. In such cases it is essential to use a model for directing decisions in order to select the most suitable system and avoid losing control during the decision making process [10].

Generally speaking, decision making in Greece concerning timber harvesting is not made with a concurrent evaluation of all


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factors involved or the study of relevant data. Most of the times it relies on tradition and random choices.

Timber harvesting systems are evaluated and classified for the first time in the present study, in an attempt to propose alternative systems and methods. The proposals included in this study concern methods that are based on low-mechanization machinery such as the mini tractor, the mini winch etc. As a result, the logging systems employing such machinery were not given top positions in the hierarchy; on the contrary, they were frequently rejected.

Another factor that must be taken into consideration is that forest laborers are not suitably trained; their work is mostly based on experience gained in the work-place and tradition. Consequently they are not familiar with modern machinery that is available on the market and in this sense they do not constitute “the agent of change” in harvesting practices.

6. REFERENCES [1] Bacher, J. 1994. Clusteranalyse, R Oldenbourg Verlg

GmbH [Hrsg], München, Wien. [2] Bock, H., H., 1974. Automatische Klassifikation

Theoretische und praktische Methoden zur Gruppierung und Strukturierung von Daten, Vandenhoek & Rupprecht [Hrsg], Göttingen.

[3] Dummel K., Forbig, A., 1996. Beurteilung der Verfahren, in Forsttechnik für naturnahe Waldwirtschaft, Tagungsführer zur 12 KWF Tagung 1996 Oberhof-Thüringen, KWF / Allgemeine Forst Zeitschrift / Der Wald [Hrsg], GroßUmstadt..

[4] Erler, J. 2000b. Forsttechnische Unterziele und Kriterien / Allgemeine Forst Zeitschrift / Der Wald [Hrsg. ], Groß-Umstadt 5/2000 S.231 – 233.

[5] Erler, J., 2000. Forsttechnik. Verfahrenbewertung, Eugen Ulmer GmgH / Co, Stuttgart.

[6] Erler, J., 2000c. Eine forsttechnologische Strategie / Allgemeine Forst Zeitschrift / Der Wald [Hrsg. ], Groß-Umstadt 9/2000 S.460 – 461.

[7] Grupp, H., Krüger, P., 1993. Deutscher Delphi-Bericht zur Entwicklung von Wissenschaft und Technik, im Auftrag des Bundesministeriums für Forschung und Technologie (BMFT), Heinz Neubert-Verlag GmbH [Hrsg. ], Bayreuth.

[8] Hauschildt, J., 1973. Die Struktur von Zielen in Entscheidungsprozessen – Bericht aus einem empirischen Forschungsprojekt. ZfbF 25, S. 709-738.

[9] Hauschilt, J., 1977. Entscheidungsziele, Tübingen.

[10] Hoheneck, F., 1993. Bewertungsmodelle als Entschaidungshilfe bei Umweltinvestitionen, Reihe Wirtschaftswissenschaften 79. Centaurus-Verlagsgesellschaft, Pfaffenweiler.

[11] Jischa, M., 1993. Herausforderung Zukunft, Technischer Fortschritt und ökologische Persektiven; Spektrum Akademischer Verlag [Hrsg. ], Stuttgart.

[12] Kangas, A., Kangas, J., Kurttila, M., 2008. Decision support for forest management. Berlin: Springer, XII, 222p.

[13] Koch 1998. Methodische Konzeption eines Modells zur komplexen, mehrdimensionalen Beurteilung forsttechnischer Produktionsverfahren; Diss. TU Dresden. Tharandt

[14] Kühmaier, M., Stampfer, K., 2010. Development of a Multi-Attribute Spatial Decision Support System in Selecting Timber Harvesting Systems. Croat. J. For. Eng., 32 (2): (p 75-88).

[15] Laux, H., 1995. Entscheidungstheorie, Springer-Verlag GmbH [Hrsg. ], Berlin Heidlberg.

[16] Lubello. D., 2008. Sviluppo di un modello per la pianificazione integrate dei sistemi di utilizzazione (A rule-based SDSS for integrated forest harvesting planning). Tesi di dottorato – Universitá degli Studi di Padova, Dipartimento Territorio e Sistemi Agro-Forestali, 213p

[17] Lüthy. D., 1998. Entwicklung eines »Spatial decision support« Systems (SDSS) für die Holzernteplanung in steilen Geländeverhältnissen (Development of a SPSS for timber harvesting in steep terrain). Zürich: Vdf, Hochschul – Verl. an der ETH. 260 p. ISBN 3-7281–2654–3.

[18] Mendoza, G., A., Sprouse, W., 1989. Forest planning and decision making under fuzzy environments: an overview and illustrations. Forest Science, 35 (2): 481-502.

[19] Meyer, T., Stückelberger, J., Hollenstein, K., Attenberger, M., Hänggli, T., 2001. effor2: Holzerntekonzept für die Untersuchungsbetriebe im Kanton schwyz (Timber harvesting concept for several areas in canton schwyz). Eidgenössiche Technische Hochschule Zürich. Interne Berichte Nr. 11. 98p.

[20] Naeesset, E., 1997. A spatial decision support system for long-term forest management plan by means of linear programming and a geographical information system. Scand. J. For. Res., 12 (1) 77-88.

[21] Schell, R., Hill, P. Esser, E., 1993. Methoden der empirischen Sozialforschung, R. Oldenbourg Verlag GmbH, München.

[22] Sheppard, S. R. J., Meitner, M., 2005. Using multi-criteria analysis and visualisation for sustainable forest management planning with stakeholder groups. Forest Ecology and Management, 207 (1-2): 171-187

[23] Simon, H. A., 1957. Models of Man. New York

[24] Stampfer, K., 2010. Forstliches Ingenieurwesen (Forst enginnering), Vorlesungsunterlagen Studienjahr 2010/ 11, Universität für Bodenkultur Wien.

[25] Wolfslehner, B., Vacik, H., 2008. Evalzation sustainable forest management strategies with the Analytic Network Process in a Pressure-State-Response framework, Journal of Environmental Management, 88 (1): 1-10.


14

Multi-criteria Analysis of Planning Decisions in Mountainous Areas with Emphasis on Land Use

Allocation Tolidis Konstantinos

School of Surveying Engineering, National Technical University of Athens (NTUA)

[email protected]

Dimopoulou Efi School of Surveying Engineering, National Technical

University of Athens (NTUA)

[email protected]

ABSTRACT Mountainous areas are characterized by inherent spatial problems due to their unique traits of geomorphology, socioeconomic reality, climate conditions etc. These particular characteristics are in most cases, directly associated with further local development constraints. Moreover, the multifactoral nature of these problems requires a Multi-Criteria Decision Analysis (MCDA) involving a set of alternatives that are evaluated and classified on the basis of different (possibly conflicting) criteria. The present research study focuses on multisite land use allocation (MLUAL) process, exploiting the advantages of using multi-criteria spatial decision support systems (MC SDSS). The main objective of the research is to propose a classification model for spatial decision making using the ELECTRE TRI method which will be the main sub system of an integrated MC SDSS for MLUAL planning procedures.

Regarding all the aforementioned, the paper is organised in three thematic axes: a) Justification of the adoption of the ELECTRE TRI method, b) Presentation of the structure and the content of both the classification model (ELECTRE TRI based) and the overall spatial decision support system and finally d) Simplified application example of MLUAL process in an Greek mountainous area combining GIS and ELECTRE TRI method.

The proposed model can be applied both in local and strategic level of spatial planning and has an added value when integrated into participatory systems of decision-making regarding MLUAL procedures.

Keywords Mountainous areas, multisite land use allocation, multi-criteria analysis, spatial planning, spatial decision support systems, GIS.


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Exploring Consumers Attitudes towards Paper Products that Could Derive from Genetic Modified Trees

Tsourgiannis Lambros Region of East Macedonia and Thrace

[email protected]

Kazana Vasiliki Kavala Institute of Technology

[email protected]

Karasavvoglou Anastasios Kavala Institute of Technology

[email protected]

Tsourgiannis Christos Antonios Ministry of Rural Development and

Food

[email protected]

Florou Giannoula Kavala Institute of Technology

[email protected]

Polychronidou Persefoni Kavala Institute of Technology

[email protected]

ABSTRACT This paper aims to explore consumers’ purchasing behaviour towards the potential paper products that could derive from genetic modified forest trees (GM Trees) and their attitudes regarding the use of biotechnology in this sector. More specifically this study aims to identify the main factors could affect people to buy paper products that could derive from transgenic forest trees, classify them into groups with similar buying behaviour and to profile each group of consumers according to their attitudes towards the use of biotechnology and their personal characteristics. Field interviews conducted in a random selected sample consisted of 418 consumers in November and December of 2011. Multivariate statistical analysis performed to a sample of 205 consumers who declared that would buy paper products that will derive from GM trees. More particular principal components analysis (PCA) was conducted in order to identify the main factors that affect consumers’ purchase behaviour towards GM Tree paper products which are: (a) Environmental impact of the use of biotechnology in forest trees, (b) marketing issues

relative to paper products, (d) product’s characteristics. Moreover, PCA performed to identify the main factors that affect consumers’ attitudes towards the use of biotechnology in forest tree sector that are: (a) Environmental impact and (b) Economic Issues. In the next stage hierarchical and non hierarchical cluster techniques employed to classify consumers with similar consumption behaviour and identified 3 groups of consumers: (a) opportunists, (b) those who are influenced by the impact of biotechnology in the environment (c) those who are interested in marketing issues. Discriminant analysis was performed to assess how the identified main factors affecting consumers’ buying behaviour derived from PCA, could predict cluster membership. Non parametric test was used to profile each group of consumer regarding their personal characteristics and to identify which main attitudes of consumers towards the use biotechnology in this sector affect each group.

Keywords Consumer behaviour, Paper products, Genetic Modified Trees.


16

Πολυστοχικό Μοντέλο Γραμμικού Προγραμματισμού για τη Βέλτιστη Σχεδίαση της Εφοδιαστικής Αλυσίδας

Καυσόξυλου Αραμπατζής Γαρύφαλλος

Τμήμα Δασολογίας και Διαχείρισης Περιβάλλοντος και Φυσικών

Πόρων Δημοκρίτειο Πανεπιστήμιο Θράκης

[email protected]

Δρόσος Δημήτριος Τμήμα Διοίκησης Επιχειρήσεων

ΤΕΙ Πειραιά

[email protected]

Πετρίδης Κωνσταντίνος Τμήμα Δασολογίας και Διαχείρισης

Περιβάλλοντος και Φυσικών Πόρων

Δημοκρίτειο Πανεπιστήμιο Θράκης [email protected]

Γαλατσίδας Σπύρος Τμήμα Δασολογίας και Διαχείρισης


Δημοκρίτειο Πανεπιστήμιο Θράκης

[email protected]

ΠΕΡΙΛΗΨΗ Σε αυτή την εργασία γίνεται η καταγραφή της εφοδιαστικής αλυσίδας καυσόξυλου όπως αυτή εφαρµόζεται στη Βόρεια Ελλάδα. Η εξεταζόµενη εφοδιαστική αλυσίδα αποτελείται από το δάσος από το οποίο οι Αγροτικοί Δασικοί Συνεταιρισµοί (ΑΔΣ) στέλνουν την ξυλεία είτε στους εµπόρους, είτε απευθείας στους εξυπηρετούµενους πελάτες, ενώ οι έµποροι απευθείας στους πελάτες. Η εφοδιαστική αλυσίδα εξετάζεται κάτω από τα κριτήρια της ελαχιστοποίησης του κόστους των διαφόρων διαδικασιών που συντελούνται καθώς του χρόνου απόκρισης στην θεωρούµενη στοχαστική ζήτηση και της ελαχιστοποίησης της εκποµπής αερίων (κυρίως CO2) κατά την µεταφορά από τους ΑΔΣ ή τους εµπόρους στους πελάτες. Το κριτήριο της

ελαχιστοποίησης των εκποµπών αερίων µοντελοποιείται µε την χρήση του προβλήµατος περιοδεύοντος πωλητή (TSP). Η προτεινόµενη λύση του εξεταζόµενου µοντέλου είναι η αποσύνθεση του προβλήµατος στα υπο-προβλήµατα της ελαχιστοποίησης των εκποµπών αερίων και της ελαχιστοποίησης του κόστους, χρόνου απόκρισης. Με αυτή την θεώρηση µειώνεται σηµαντικά η πολυπλοκότητα του αρχικού προβλήµατος. Τέλος θα παρουσιαστεί µια εφαρµογή της παραπάνω µεθόδου όπου µε την χρήση της ανάλυσης ευαισθησίας για διάφορα σενάρια παραµέτρων της στοχαστικής ζήτησης θα γίνει καταγραφή των λύσεων που ελαχιστοποιούν τα εξεταζόµενα κριτήρια.


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SWOT Analysis on Sustainable Forest Management Policy and Management. The Eastern Macedonia-Thrace Case

Kazana Vassiliki Department of Forestry and Natural Environment Management at Drama

Kavala Institute of Technology 1st km Drama-Mikrohori, 66100

Drama, GREECE +30 2521060435

[email protected]

Stamatiou Christos Kavala Institute of Technology

[email protected]

Kazaklis Angelos Centre for Integrated Environmental

Management, GREECE

[email protected]

Koutsona Paraskevi

Kavala Institute of Technology

[email protected]

Fotakis Dimitrios Kavala Institute of Technology

[email protected]

Boutsimea Anastasia


[email protected]

ABSTRACT A survey was carried out during a Workshop of the National Forest Governance Council to identify the Strengths, Weaknesses, Opportunities and Threats of sustainable forest policy and management. The National Forest Governance Council was established through the INFORM project financed through LIFE (LIFE08/ENV/GR/000574). Its main role is to support development of a knowledge base for national forest policy development and sustainable forest management and monitoring.

This paper presents the important internal and external factors identified in the four groups: Strengths, Weaknesses,

Opportunities and Threats for sustainable forest policy and management in Eastern Macedonia and Thrace region. It also discusses the strategy resulting in a good fit between the internal and external factors. SWOT provides a basic frame within which an analysis of the strategic decision situation towards sustainable forest policy and management can be performed.

Keywords Governance, forest sustainability, strategic decision support.


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Robust Compromise Programming of Industrial Scheduling Jobs with Variable Criteria Priorities

Makarouni Ioanna National Technical University of




Psarras Yannis National Technical University of




Siskos Eleftherios National Technical University of




ABSTRACT Scheduling problems consist of finding the sequence of a certain number of jobs to be carried out on different machines, so that technological constraints are satisfied and several performance criteria are optimized. This paper presents a mixed integer programming formulation to model a real world assembly line scheduling problem which includes four optimization criteria with unknown weights comprised in a convex polyhedral set: (1) maximize the number of job items produced; (2) maximize the just in time use of available resources; (3) minimize the absolute difference between the computed production date and the expected one; and (4) optimize a resource utilization index. The paper suggests the use of a labyrinth algorithm to compute all vertices-weights in the polyhedral set. Then it employs a repetitive

application of a classical compromise programming method for each different weighting vertex. The frequency of appearance of an optimal compromise solution to the job sequencing problem is interpreted as the probability this solution to be the best compromise solution. The robust compromise programming (RCP) approach proposed through this paper allows analysts to manage the variability of criteria priorities and to suggest robust solutions to the decision makers. The experience with a specific numerical example showed the efficiency and usefulness of the proposed methodology.

Keywords Multiple objective programming, Job scheduling, Pareto optimality, Mixed-model assembly line.


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A Simulation Methodology for Evaluating Dual Sourcing Strategies of a Discrete Part Manufacturer

Tsiolias D. Aristotle University of Thessaloniki

P.O. Box 461, 55124 0030 2310 995896

[email protected]

Partsch D. Aristotle University of Thessaloniki

P.O. Box 461, 55124 0030 2310 995896

[email protected]

Keramydas C. Aristotle University of Thessaloniki

P.O. Box 461, 55124 0030 2310 995896

[email protected]

Iakovou E. Aristotle University of Thessaloniki

P.O. Box 461, 55124 0030 2310 995970

[email protected]

Vlachos D. Aristotle University of Thessaloniki

P.O. Box 461, 55124 0030 2310 995969

[email protected]

ABSTRACT Globalization and technological evolution associated with critical socioeconomics changes altered the traditional supply chain (SC) nature, along with the corresponding risk forms. Modern SCs are multi-national, multi-echelon networks including complex relationships among stakeholders with conflicts of interests. Therefore, modern SCs are vulnerable to risks (e.g. natural disasters, financial crisis, etc.), and their consequences (delays and disruptions of product, money, and information flows). Thus far, academia and practitioners had mainly addressed the issues of identification and classification of supply chain risks, along with the relevant mitigation strategies that should be adopted to shield the organization against them. Whilst the nature of the overall supply disruption problem is quantitative, the vast majority of these efforts employs a qualitative approach. In this paper we focus on dual sourcing (DS) risk mitigation strategy employed by a discrete part manufacturer, in a quantitatively manner. More specifically, a discrete event simulation methodology is developed using the ArenaTM simulation software for the measurement of risk impacts on the organization’s performance, and the evaluation of alternative DS policies in terms of the premium cost paid to the alternative supplier. The insightful findings derived from the numerical analysis could support the relevant decision-making process in the direction of achieving significant cost savings in the long-term.

Keywords Supply Chain Risk Management, Supply Chain Disruption, Risk Mitigation Strategies, Dual Sourcing, Simulation.

1. INTRODUCTION Globalization and technological evolution together with socioeconomic changes contributed significantly to the transformation of traditional supply chains into multi-national, multi-echelon networks of partners and relationships. Concurrently, traditional risks that used to threaten SCs altered in their form and consequences (e.g. tsunami in Japan, earthquake in Iceland, etc.), while new threats were added to the already existing ones (e.g. Information Technologies systems collapse).

As a result and given the increased complexity and vulnerability of the modern SCs dynamic structure, the aforementioned risks have considerable impacts on the performance of the organizations, and thus have to be adequately and timely managed [1]. Therefore, several proactive risk mitigation strategies rose naturally in order to shield enterprises against these risk impacts and mitigate their results [2], [3]. Finally, managers have to decide on the appropriate one, which in turn should be further tailored to their company’s needs.

In this paper we focus on Dual Sourcing (DS) that proved to be an efficient and thus widely accepted mitigation strategy in real-world practice and literature [4], [5], [6], [7]. Complementary to the already existing qualitative papers, we extend the results of Partsch et al. [8] for the case of a discrete part manufacturer. Specifically, we tackle alternative DS strategies in a quantitative manner by evaluating their contribution in the company’s long-term cost savings. Moreover, this paper determines the optimal premium cost that should be paid to the alternative suppliers in order the adopted DS policy to be feasible. The fundamental paper objective is to provide a decision-making support methodology for the managers to decide on whether to implement a DS strategy or not, and the level of the reserved capacities.

The rest of the paper is organized as follows: The description of the system under study is presented in section 2. In section 3, the simulation methodology is introduced, while the associated numerical analysis is performed in section 4. Finally, we sum-up with conclusions in section 5.

2. SYSTEM DESCRIPTION We consider a simplified two-echelon supply chain that comprises of two suppliers/manufacturers (A and B) and one retailer. The supply process concerns a single Stock-Keeping-Unit (SKU)/final product that has two component parts (part A and part B), according to the relevant Bill of Material (BOM). The retailer faces a stochastic demand for the final product and implements periodic review (s, S) ordering policies for the replenishment of its components. The manufacturers implement a make-to-order strategy with limited production capacities that are, though, sufficient enough to fulfill the retailer’s orders.


20

The manufacturers’ production process is prone to disruptions, which further interrupts the subsequent distribution process. It is assumed that a disruption incident forces the manufacturers to completely shut down their production process for a stochastic time period (disruption duration). During this period, the manufacturers are unable to cover the demand, which is backordered and will be satisfied when adequate inventory is available.

In order to mitigate the effects of the disruption consequences, the retailer has the option to contract an alternative supplier for each component of the final product. The alternative suppliers have the same production time and unit price as the main ones, respectively. In this contracted partnership context, the retailer reserves a fraction of the alternative’s supplier capacity (“stand-by” capacity) which is promptly activated in case of main supplier’s breakdown. Figure 1 depicts the overall supply chain configuration.

The retailer decides on the reserved capacity level, which is determined as a fraction (percentage) of the main supplier’s capacity, and ranges from 0% (single sourcing) to 100% (full substitution of the main supplier). According to the contract, the retailer is obliged to pay a premium cost (reservation cost) to the supplier, which is assumed to be linearly proportional to the reserved capacity. In exchange for this charge, the alternative supplier is committed to release the agreed capacity (retailer’s backup option), exactly at the time that the retailer raises the relevant claim.

Furthermore, it is assumed that there is no delay in the alternative supplier’s response (instant switch from the main supplier to the alternative one), and that there is always an available supplier for delivering orders (the suppliers of a component cannot fail simultaneously). For research reasons and without loss of generality, in order to isolate each main supplier’s disruption effects, it is assumed that the main suppliers do not collapse in parallel (this assumption could be easily relaxed). At the end of the disruption period, the alternative supplier continues to deliver any pending orders, while new orders are directed to the main supplier.

Retailer

Main Supplier A

Alternative Supplier A

CustomerDemand

OrderDisruption Risk A

Supply Supp

ly

Orde

r

Pro-Active Strategiesü Dual Sourcing

Main Supplier B

Alternative Supplier B

Orde

r

Disruption Risk B

Supp

ly

Supply

Order

Component A

Component B

Figure 1. Supply chain system configuration. In the relevant decision-making framework, the retailer has to answer two critical successive questions:

• Is a Dual Sourcing strategy beneficial in the long term? • If the answer is “yes”, then which are the optimal alternative

suppliers’ capacities that should be reserved given the respective premium costs, or equivalently, which is the maximum acceptable premium cost to be paid given the reserved capacities?

The following alternative strategies are considered:

ü Single Sourcing strategy (SS): No action is undertaken from the retailer to mitigate the impact of a potential disruption.

ü Dual Sourcing strategy (DS): An additional capacity (RC% of the main supplier capacity) is reserved from the retailer to mitigate the impact of a potential disruption.

Additionally, another third strategy is employed, which acts as the reference strategy when evaluating the first two ones, namely: Basic Strategy (BS), where there is no disruption probability and no risk mitigation action is undertaken.

The performance indicator that is used for the alternative strategies evaluation is the total expected system cost, which is comprised of the following elements: ordering cost (OC), holding cost (HC), and backordering cost (BC). The purchase cost is the same for all options and therefore it is ignored.

3. SIMULATION MODEL The Dual Sourcing problem under study includes multiple decision variables (Emergency Suppliers’ capacities), stochasticity sources (Demand, Time and Duration of the Disruptions, Lead Times) and several parameters (Costs, Inventory Levels, etc.). Although the objective function (total cost) can be easily written, its analytical solution is mathematically intractable. For this reason, discrete event simulation techniques are employed.

The simulation model structure is comprised by the following modules: (i) The Demand Generator: the stochastic daily demand of the retailer is generated and then fed to the Inventory Level Calculator. (ii) The Inventory Level Calculator and Order Generator: this module represents the standard periodic review (s,S) policy with two suppliers. It emulates all the standard operational procedures that take place in such a system: incoming demand satisfaction, review of inventory levels, order placement where necessary and order delivery after a given lead time. The parameters of the module are altered in line with the system status (no disruption, disruption on Regular Supplier A or B, disruption on both Regular Suppliers). (iii) The Disruption Generator: a disruption occurs at a main supplier on a random date during the planning horizon for a stochastic duration with a specific probability, triggering the Order Generator to place new orders to the alternative supplier.

The model variables and their notation are summarized in the first two columns of Table 1.

All models were built, tested and run in the environment of the Rockwell Automation® Arena™ Simulation Software. The verification process was carried out utilizing numerous techniques including thorough examination of each individual element’s logic, a step by step run of the model with simultaneous observation of its variables and parameters through both spreadsheets and visual aids (graphs, flow diagrams), stress-tests (model behavior under extreme input settings) and a critical evaluation and comparison of the produced numerical results, to ensure that the model is an accurate representation of the real system under study.

The validation procedure presented with more difficulties, owing to the absence of a tangible functional equivalent in order to compare the outputs with actual data. Thus, experience and observation of fairly similar systems were employed in order to ensure that the model’s outputs are an accurate approximation of what a real-world system would produce under similar input values, within an


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acceptable range. Moreover, a comparative analysis of a wide range of different scenarios was carried out to ascertain that the model’s behavior shifted accordingly.

A run of 100 replications was executed for each set of input settings (184 in total), with a replication length of one year (365 days), which represents the time frame of the study. Results were extracted and analyzed using Microsoft’s® Excel™ Spreadsheet software. Each simulation run lasted on average one minute, including model set-up.

Table 1. Model variables and notation

Name Notation Value(s) Arrival rate [customers/day] λ Poisson(10)

Demand Size [units/customer] µ Poisson(10) Reorder Point for parts A and B

[units] sA , sB 900, 450

Base stock level [units] SA, SB 1500, 750 Capacity of Regular Suppliers

(RSA, RSB) [units] CRSA, CRSB 400, 800

Lead Time for each supplier RSA, RSB, ESA, ESB. [days] LT Triangular (1,2,3)

Ordering Cost for each supplier RSA, RSB, ESA, ESB [€ per

order] OC 3.5

Holding Cost for parts A and B and finished products P [€ per unit

and day]

HCA, HCB, HCP 1,1,2

Backordering Cost [€ per unit and day] BOC 100

Premium ESA, ESB [€ per unit of reserved capacity] PA, PB 4,1

Disruption Probability RSA RSB [%] pA, pB 20, 10

Disruption Duration [days] DtA, DtB

Triangular (25,30,35) Triangular (10,15,20

Capacity of Emergency Suppliers (ESA, ESB) as percentages of the Regular Suppliers Capacity [%]

cESA, cESB 0-100, 0-100

4. NUMERICAL ANALYSIS The parameters for the basic scenario are presented in the third column of Table 1. To study the effect of the emergency capacity levels on the system performance a number of experiments were conducted for a planning horizon of one year for various levels of CESA and CESB, while keeping the other parameters constant. To allow comparison for different values of the decision variables we assumed that the disruptions occur in specific dates (day 50 for Regular Supplier A and day 150 for Regular Supplier B).

Figure 2 depicts the cumulative expected Total Cost (solid curve) and its components across the planning horizon. These curves correspond to a scenario without emergency suppliers. In Figure 2, five areas of interest are observed:

Day 1-Day 50: The system functions normally (steady-state operation) and the slopes of all the components show no significant variation. Day 50 is the preset date the disruption on Regular Supplier A occurs.

Day 51~Day 100: A rapid ascent of the backorder cost appears, affecting in turn the total cost due to the disruption. With no way to replenish inventory, backorders pile up. Notice how, although the maximum stochastic duration of the disruption is 35 days, it takes the system approximately 50 days to fully recover and resume its steady-state operation. Day 101-Day 150: The system operates in steady-state. The slope of all cost components is the same to the first period. Day 150 is the preset date of the disruption on Regular Supplier B. Day 151~Day 180: The disruption on Regular Supplier B occurs, exhibiting similar effects as before (the difference in its magnitude depends only on the different cost and disruption probabilities of the suppliers of part B). The system recovery takes again more time than the maximum disruption duration. Day181-Day365: The system returns to a steady-state operation.

Figure 2. Total Cost Components

4.1 Adding Emergency Capacity The adoption of a dual sourcing strategy differentiates the system performance. Figure 3 depicts the evolution of cumulative expected Total Cost for various combinations of cESA and cESB.

A distinct pattern emerges in the graph for each level of cESA. We remind that we assumed that the disruption may occur initially at the supplier of part B. Focusing on the top ensemble of curves (for cESA=0%) we can extract conclusions that remain valid for all the other cESA levels. The slopes differentiate after day 150 (as expected, due to the fact that only cESA dictates the system’s reaction to Disruption A), according to the level of cESB. The topmost curve (for cESB=0%) is in fact the same curve we observed in Figure 2 for Total Cost. As cESB increases, the slopes gradually decrease. For cESB > 20% the curve continues almost as a straight line and the system behaves (cost-wise) as if the disruption at the supplier of part B never occurred. By observing the graph as a whole it is evident that the same behavior is exhibited by the CESA slopes.

The very bottom line of the graph represents expected Total Cost when both Emergency Suppliers are contracted for the full Regular Suppliers Capacities, effectively acting as identical replacements (or, alternatively, as if the disruptions do not manifest themselves), leading to the notable conclusion that for cESA > 30% and cESB >


22

20% the financial effects of the disruptions on both regular suppliers are negated altogether.

Figure 3. Total Cost Under Different Settings

4.2 Premium Cost and Optimization Though very insightful, the analysis above ignores a key cost element: the reservation Premium the retailer pays the Emergency Suppliers in exchange for the ability to have their Production Capacity readily at his disposal, when and if the disruptions occur. Despite being a one-off payment, its amount can significantly impact the balance of the cESA/cESB mix. For this study we assumed a Premium for Emergency Supplier A of 4€ per reserved capacity unit (or 0.125% of additional capacity) and a Premium for Emergency Supplier B of 1€ per unit (or 0.25% of additional capacity) to resemble the dynamics behind the two parts and suppliers (part A is more sensitive and more risky, thus mitigating its risk costs more). These Premium costs were added to the Total Expected Cost calculated for numerous combinations of cESA and cESB and the iso-cost results are plotted in the contour graph of Figure 4. The graph shows that the optimal solution for the given problem parameters is obtained for cESA=25% and cESB= 20%.

Figure 4. Optimal Emergency Capacity Levels

5. CONCLUSIONS AND DISCUSSION This paper presents a simulation-driven numerical analysis of a supply chain risk mitigation strategy, namely dual sourcing. The complexity of modern multimodal supply chain networks was broken down to a manageable and robust model to enable the study of the financial impacts of disruptions and the evaluation of policies to alleviate that risk. Focusing on three alternative scenarios –no disruptions probability, potential disruptions with no countermeasures applied, potential disruptions with dual sourcing- we quantify the risk associated with disruptions and compare the outcome between them, in order to extract tangible and applicable managerial insights.

The results demonstrate the necessity of proactive risk evaluation and management that executives must implement, in order to safeguard their firms from potential pitfalls. Moreover, steps should be taken towards the integration of the risk mitigation strategies throughout the whole length of the supply network. “A chain is only as strong as its weakest link” and, as it is evident through this paper, the most sensitive segments of the system generate considerably higher impact on its overall functionality and resilience, should adversities occur.

Future research will attempt to further enhance the usefulness of the model by gradually detracting assumptions and conducting more tests to enable a more universal approach to a wider scope of management issues addressing risk and its effects on modern supply chains.

6. REFERENCES [1] Glendon, L. 2011. Supply Chain Resilience Survey 2011.

Financial Services Group and Business Continuity Institute, Zurich. DOI=http://www.techinsurance.zurichna.com/res/supply_chain/supply_chain_resilience_2011-1.pdf.

[2] Knemeyer, A. M., Zinn, W., and Eroglu, C. 2009. Proactive planning for catastrophic events in supply chains. J. Oper. Manag. 27, 2 (April 2009), 141-153.

[3] Sheffi, Y. 2007. The Resilient Enterprise: Overcoming Vulnerability for Competitive Advantage. MIT Press. Cambridge, Massachusetts, MA.

[4] Chopra, S., and Sodhi, M. S. 2004. Managing Risk to Avoid Supply-Chain Breakdown. MIT Sloan Manage. Rev. 46, 1 (Fall 2004), 53-61.

[5] Tang, C. S. 2006. Robust Strategies for Mitigating Supply Chain Disruptions. I. J. L.: R. A. 9, 1 (March 2006), 33-45.

[6] Yu, H., Zeng, A. Z., and Zhao, L. 2009. Single or Dual Sourcing: Decision-Making in the Presence of Supply Chain Disruption Risks. Omega – I. J. Manage. S. 37, 4 (August 2009), 788-800.

[7] Wang, Y., Gilland, W., and Tomlin, B. 2010. Mitigating Supply Risk: Dual Sourcing or Process Improvement?. M&SOM – Manuf. Serv. Op. 12, 3 (Summer 2010), 489-510.

[8] Partch, D., Keramydas, C., Vlachos, D., and Iakovou E. 2012. A Simulation-Based Risk Methodology to Calculate the Cost to Recuperate from a Supply Chain Disruption with a Dual-Sourcing Mitigation Strategy. In 2nd International Conference on Supply Chains (Katerini, Greece October 05-06, 2012). 2nd ICSC.


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A Synthesis of Multi-criteria and Cluster Analysis Approaches for the Selection of the Most Competent

Construction Project Designer Aretoulis N. Georgios School of Civil Engineering

Faculty of Engineering Aristotle University of Thessaloniki

Thessaloniki, Greece

[email protected]

Triantafillidis X. Christoforos School of Civil Engineering


Thessaloniki, Greece

[email protected]

Papathanasiou Jason Department of Marketing and

Operations Management University of Macedonia

Edessa, Greece

[email protected]

ABSTRACT Construction Project Designers (CPDs) are essential human resources for the construction enterprises. Their designs are the first step towards a successful project implementation and they are equipped with a number of cognitive skills and personality characteristics. International research has long been focusing on identifying these attributes. At the same time, the number of Construction Project Designers is continuously increasing and the choice of the most competent Designer for the construction project at hand has proven to be a challenge. This paper focuses on creating a novel approach for selecting the most efficient project designer. Firstly, the required attributes of a designer were identified and a questionnaire survey took place. The survey was conducted based on a structured questionnaire and led to 187 responses, originating from engineers and construction professionals throughout the Greek Construction Industry. The questionnaire’s content was based on the international literature and interviews with Greek professionals in the construction industry and recorded scores for each attribute on a Likert scale.

The first aim of the current research is to identify potential groups of Greek Engineers that share similar conceptions of the Greek CPDs’ required competencies. The Statistical Package of Social Sciences (SPSS) was used to implement cluster analysis and three distinct clusters of participants’ profiles were identified based on their responses. Descriptive statistics were also employed focusing on each identified group and a description of each cluster’s attributes is presented. The second aim is to propose an approach for ranking available project designers. The criteria were selected among the most dominant attributes of the survey. Goal programming techniques and the Simos method asserted the weighs of the selected criteria in order to implement the PROMETHEE multi-criteria methodology. Expected results will provide an opportunity to gain insights on the Designers’ selection procedure by various employers’ profiles.

Keywords Construction Project Designers, Competencies, Cluster Analysis, Perceptions, Simos Method, PROMETHEE multi-criteria methodology.


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Πολυκριτήριος Χρονοπρογραμματισμός Παραγωγής σε Συστήματα Παραγωγής Job – Shop

Κουτσουβάλης Γ. Π. Τμήμα Μηχανικών Παραγωγής και

Διοίκησης Δημοκρίτειο Πανεπιστήμιο Θράκης

[email protected]

Ξανθόπουλος Α. Σ. Τμήμα Μηχανικών Παραγωγής και


[email protected]

Κουλουριώτης Δ. Ε. Τμήμα Μηχανικών Παραγωγής και


[email protected]

ABSTRACT Τα συστήµατα τύπου job-shop προορίζονται για τη, σχετικά µικρού όγκου, παραγωγή µιας ευρείας γκάµας προϊόντων των οποίων οι προδιαγραφές καθορίζονται σε µεγάλο ποσοστό από τον πελάτη. Σε ένα σύστηµα job-shop χρησιµοποιείται ευέλικτος εξοπλισµός γενικής χρήσης, ενώ η όλη παραγωγική διαδικασία χαρακτηρίζεται από χαµηλό βαθµό αυτοµατοποίησης. Σηµείο κλειδί για την εύρυθµη και αποδοτική υλοποίηση του µεσοπρόθεσµου πλάνου παραγωγής είναι η λειτουργία του χρονοπρογραµµατισµού των εργασιών παραγωγής. Με το χρονοπρογραµµατισµό παραγωγής καθορίζεται η ανάθεση των εργασιών στους σταθµούς, καθώς και η αλληλουχία εκτέλεσης αυτών. Η χρήση κανόνων δροµολόγησης αποτελεί µια ευρέως διαδεδοµένη πρακτική σε περιπτώσεις όπου οι αποφάσεις χρονοπρογραµµατισµού λαµβάνονται σε πραγµατικό χρόνο, κυρίως λόγω των χαµηλών απαιτήσεών τους σε υπολογιστική ισχύ. Παρ’ όλα αυτά, η απόδοση ενός κανόνα δροµολόγησης εξαρτάται σε µεγάλο βαθµό από τις συνθήκες λειτουργίας του συστήµατος παραγωγής και τα αντικειµενικά κριτήρια που λαµβάνονται υπόψη.

Στην παρούσα εργασία, και µε τη βοήθεια µοντέλου προσοµοίωσης συστήµατος job-shop, µελετάται η συµπεριφορά εναλλακτικών κανόνων δροµολόγησης βάσει διαφόρων αντικειµενικών κριτηρίων σε πλήθος σεναρίων λειτουργίας του συστήµατος. Το σύστηµα παραγωγής που βρίσκεται υπό εξέταση αποτελείται από µία και µοναδική µηχανή που µπορεί να επεξεργαστεί παραγγελίες που ανήκουν σε m τύπους και µιας αποθήκης (buffer) άπειρης χωρητικότητας όπου αναµένουν (στοιβάζονται) οι εισερχόµενες παραγγελίες. Με την βοήθεια του παραπάνω συστήµατος προσοµοίωσης µελετώνται οι εξής δώδεκα κανόνες δροµολόγησης: FIFO, EDD, SPT, LS, CR, SPTNS, SPSU, SCT, LSSU, ED-DNS, LSNS, CRNS για

αντικειµενικά κριτήρια όπως ο µέσος χρόνος ροής, η µέση ενωρίτερη/βραδύτερη περάτωση, ο µέσος χρόνος αναµονής, η µέση καθυστέρηση και το ποσοστό αργοπορηµένων παραγγελιών. Τα αριθµητικά αποτελέσµατα από την εκτέλεση των µοντέλων προσοµοίωσης χρησιµοποιούνται για την διεξαγωγή στατιστικών αναλύσεων. Στα πλαίσια αυτής της ανάλυσης γίνεται µια γραφική ανάλυση των αποτελεσµάτων ενώ στη συνέχεια η ανάλυση και η ερµηνεία τους γίνεται µε τη βοήθεια της στατιστικής ανάλυσης ANOVA και της διαδικασίας του clustering. Τέλος, σχηµατίζονται µαθηµατικές εξισώσεις εισάγοντας ψευδοµεταβλητές για την εκπροσώπηση των πολλών διαφορετικών ανεξάρτητων µεταβλητών, όπως αυτές ορίζονται και στο σύστηµα της προσοµοίωσης έτσι ώστε να αξιοποιηθούν τα αποτελέσµατα των προσοµοιώσεων και οι οποίες θα ισχύουν και για περιπτώσεις που δεν έχει γίνει η αντίστοιχη προσοµοίωση, κάτι το οποίο ουσιαστικά έχει ως αποτέλεσµα όχι µόνο τεράστιο κέρδος σε χρόνο, αλλά και τη δυνατότητα στο µηχανικό να χρησιµοποιεί συνεχείς αλγεβρικές συσχετίσεις αντί για διακριτές τιµές. Τα τεχνητά νευρωνικά δίκτυα δίνουν πολλές φορές λύση στο συγκεκριµένο πρόβληµα και είναι και ο λόγος που χρησιµοποιήθηκαν.

Οι παραπάνω µεθοδολογίες προσέγγισης βοήθησαν στην τελική αξιολόγηση των διαφόρων κανόνων δροµολόγησης για τα αντικειµενικά κριτήρια που τέθηκαν. Έτσι δόθηκε η δυνατότητα να εξαχθούν ασφαλή συµπεράσµατα για την επίδοση τους σε διαφορετικές συνθήκες λειτουργίας του συστήµατος παραγωγής.

Λέξεις Κλειδιά Χρονοπρογραµµατισµός παραγωγής, συστήµατα παραγωγής κατά παραγγελία, βελτιστοποίηση, κανόνες δροµολόγησης, νευρωνικά δίκτυα, µετα-µοντέλα.


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Multicriteria Route Choice in Road Networks Mitsakis Evangelos

Centre for Research and Technology Hellas

Hellenic Institute of Transport +30 2310 498459

[email protected]

Stamos Iraklis Centre for Research and Technology

Hellas Hellenic Institute of Transport

[email protected]

Salanova Grau Josep Maria Centre for Research and Technology


[email protected]

Aifadopoulou Georgia

Centre for Research and Technology Hellas

Hellenic Institute of Transport

[email protected]

Chrysohoou Evangelia Centre for Research and Technology


[email protected]

ABSTRACT Road transport networks are primarily used for serving the daily travelers’ demand for trips. This demand has been increasing substantially, up to levels where the existing capacity offered by road transport networks cannot anymore satisfy it. The decisions of drivers regarding the choice of their preferred route, in order to execute their trips between given origin and destination points within the road transport network, may in reality vary from the distance or free-flow travel time based choices. This can be especially the case during congested traffic conditions. The drivers’ criteria for the route choice process usually include travel time or distance. Under congested traffic conditions, the behavior of all drivers regarding their route choices results to User

Equilibrium (UE) conditions. Under UE conditions, all routes used by drivers traveling between two points are equal and minimal, according to Wardrop’s first principle. In the present paper we investigate and discuss the effects of multiple route choice criteria, including emissions produced, emissions exposed to and fuel consumption, besides the commonly used distance and time. Our research effort is focusing on the investigation of actual multicriteria decisions taken by daily travelers when choosing their routes.

Keywords Route choice, multicriteria decisions, utility theory.


26

Sustainable Energy for Rural Development: A Greek Case Study

Marinakis Vangelis National Technical University of


Engineering Management & Decision Support

Systems Lab. (EPU-NTUA) 9, Iroon Polytechniou str. 157 80,

Athens, Greece

[email protected]

Psarras John National Technical University of




Athens, Greece

[email protected]

Papadopoulou G. Alexandra National Technical University of




Athens, Greece

[email protected]

Doukas Haris National Technical University of




Athens, Greece

[email protected]

ABSTRACT Nowadays, the Covenant of Mayors (CoM) counts more than 4,200 signatories. Although the CoM initiative embraces all regions and is not intended solely for large cities, fewer regions with rural characteristics have adhered to this initiative. Climate change policies and programmes in these communities are still in their infancy, in terms of putting real changes on the ground. In this respect, particular emphasis has to be laid on them towards “greening” rural communities economies [1]. The main objective of this paper is to present an interactive supportive framework for the formulation of the rural communities’ long term vision and overall strategy. The adopted approach is based on the general principles set out in the Covenant guidelines for Sustainable Energy Action Plan (SEAP), as well as existing methodologies and tools for the development and implementation of SEAPs (e.g. MODEL, MUSEC, PEPESEC, etc), properly adapted to the rural communities’ characteristics [2, 3]. Indeed, specific emphasis is given in the sectors of agriculture, forestry and fishery, taking into consideration that these sectors constitute an important part of the Baseline Emission Inventory of the rural communities. As a result of the community’s Baseline Emission Inventory, a number of profile and the Renewable Energy Sources (RES) and Rationale Use of Energy (RUE) actions are identified for each sector (public, tertiary, residential, transport, etc). In this context, alternative scenarios are developed based on the identified RES and RUE actions. The proposed approach contributes to the selection of the most appropriate RES and RUE actions at local regional level, using an existing multi-criteria decision-making (MCDM) method, namely the UTilités Additives (UTA) method [4].

The adopted approach was applied to a Greek municipality in the district of Lakonia, Peloponnese region. The results and the discussion of the main outcomes from the application are presented. It should be noted that a basic part of the current paper is based on the relevant activities conducted within the framework of the project “Rural Web Energy Learning Network for Action (eReNet), supported by the Intelligent Energy – Europe (IEE).

Keywords Decision Support, Sustainable Energy, Rural Development, Covenant of Mayors.

REFERENCES [1] European Commission. 2006. Communication from the

Commission to the Council and the European Parliament: Employment in Rural Areas: Closing the Jobs Gap. COM (2006) 857 final. Brussels, Belgium.

[2] European Union. 2010. How to Develop a Sustainable Energy Action Plan (SEAP) – Guidebook. Brussels, Belgium.

[3] Bertoldi, P., Cayuela, D. B., Monni, S. and Raveschootm R. P. 2009. Existing Methodologies and Tools for the Development and Implementation of Sustainable Energy Action Plans (SEAP). European Commission - Joint Research Centre (EC - JRC). Brussels, Belgium.

[4] Jacquet-Lagrèze, E. and Siskos, Y. 1982. Assessing a set of additive utility functions for multicriteria decision making: The UTA method, European Journal of Operational Research, 10 (2):151-164.


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Integrated Aquaculture – an Old Concept with New Applications in Greece

Ioannis N. Vatsos Laboratory of Ichthyology

Faculty of Veterinary Medicine Aristotle University of Thessaloniki

0030 2310 999880

[email protected]

Christos Batzios Laboratory of Animal Production

Economics Faculty of Veterinary Medicine

Aristotle University of Thessaloniki 0030 2310 999957

[email protected]

Panagiotis Angelidis Laboratory of Ichthyology


0030 2310 999822

[email protected]

Alexandros Theodoridis Laboratory of Animal Production

Economics Faculty of Veterinary Medicine

Aristotle University of Thessaloniki 0030 2310 999953

[email protected]

ABSTRACT The concept of integrated aquaculture is old, but in the last thirty years many authors have suggested various systems, in which different species are cultured together, in order to reduce the environmental impacts of aquaculture. In particular, people have attempted to integrate mussel and micro- or macroalgae culture into open-sea or land-based fish farming. When certain criteria are met, such production could increase the profit of the farms, mainly through the reduction of the waste treatment cost. In addition, the mussels or the algae could be used as ingredients in the diet of the fish. In Greece, up until now, monoculture was the prevailing fish and shellfish farming system. However, in the last few years, the farmers seek to develop alternative production patterns that could result in increased profit through the maximized utilization of the available resources.

Keywords Integrated aquaculture, fish, mussels, algae

1. INTRODUCTION The concept of raising together different animal species, or even animals and crops, with the purpose of utilizing the byproducts, or even the wastes, from the one activity to sustain the other activity is very old. For many centuries in China people reared together carp species of different feeding habits in ponds, in order to optimize the use of the available resources [1]. These mixed farming systems were an early form of the integrated systems which were developed later, where all the species involved (animal and/or plant) develop symbiotic relationships and the prosperity of one depends on the prosperity of the other. A good example of such integrated production systems is the rice-fish farming that has been taking place in many places in Asia for over 1200 years [2].

Someone might argue that in the intensive aquaculture systems that are applied today, such integrated farming methods are of little, if any, use. However, this is far from the truth. About thirty years ago, some authors suggested the co-culture of algae or mollusks with fish as a solution to minimize the impact of the fish farming wastes on the environment [3] and since then many integrated aquaculture systems have been developed.

Up until now, Greece, although a major marine fish producer in the Mediterranean area, has not made any progress in the direction of integrated aquaculture. It is believed that recent findings, concerning the potential of using integrated culture systems, combined with the necessity to maximize the use the available resources, will impose the development of novel farming methods. The present review focuses on the main advances in the integrated aquaculture systems in relation to Greek aquaculture and particularly to marine fish and mussel farming, as these are by far the most important sectors of aquaculture in the country.

2. AQUACULTURE SECTOR IN GREECE In the last 30 years, Greece, due to its strategic location and geographical characteristics (particularly the extended sheltered coastline) has become one of the leading fish and shellfish producers in Europe and particularly in the Mediterranean basin.

2.1 Fish Production Greece is the top producer of sea beam (Sparus aurata) and sea bass (Dicentrarchus labrax) in Europe. According to data from Food and Agriculture Organisation (FAO) and Federation of European Aquaculture Producers (FEAP) Greece produces approximately 130,000 tons of these species, which corresponds to 55 % and 40 % of the global sea bream and sea bass production respectively [4,5]. In addition to these fish species, Greece also produces more than fifteen other fish species, both marine and fresh water. Some of these species are: rainbow trout


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(Oncorhynchus mykiss), sharpsnout sea bream (Putazzo puntazzo), common pandora (Paguellus erythrinus), red porgy (Pagrus pagrus), white sea bream (Diplodus sargus), flathead grey mullet (Mugil cephalus) and brown meager (Sciaena umbra). The production of the fresh water species is quite low. For example, trout, which is the main fresh water species produced in Greece, is less than 3,000 tons [4]. Approximately 80 % of the marine fish production is exported to other countries, mainly Italy, France and Spain [5,8].

The farming of the marine fish species, such as sea bream and sea bass, takes place in land-based facilities (hatcheries and pre-growing units) and at open-sea sites (ongrowing stage) in cages, while the production of fresh water species takes place only in land-based facilities. There are about 370 marine fish farming sites (hatcheries and ongrowing units), throughout Greece and less than 100 fresh water fish farms, located mainly in northern Greece [5]. Most marine fish farms produce 250 - 500 tons annually (market size fish), while four ones produce ≥5,000 tons p.a. (this is more than 50% of the total national production) [6,8]. It should be noted that Greece is also a main sea bass and sea bream fingerling exporter, supplying fish to other countries such as Italy and Spain.

In 2001 and 2002, there was a major crisis in the marine aquaculture segment, which was caused by the imbalance between the production and the market demand, according to a technical report by the University of Stirling, UK [6]. Inefficient management strategies and inadequate promotion led to over-production, especially of sea bream. This crisis continued in the following years and the situation appeared to improve after 2006-2007. However the present financial crisis affected again severely the industry.

An important issue related to Greek marine fish aquaculture industry that should be stressed is its conflict with local societies due to its environmental impact. Indeed, the European Environmental Agency lists this activity among the main potential causes for serious environmental degradation if conducted uncontrolled [9]

In terms of production cost, the main factor that affects the production at the first stages of marine aquaculture (hatcheries and pre-growing unit) is labor cost (constituting about 35 % of the total production cost), while at the ongrowing stage is feed cost (constituting over 40 % of the total production cost) [7]. In relation to feeds, it is should be noted that the main ingredient that still greatly affects the cost is the use of high quality fishmeal, which is the main protein source. Thus, in the last 15 years a lot of research has been conducted in order to examine new cheaper raw materials that could replace fishmeal, such as soybean meal. However, there is still a lot of space for improvement in this area and integrated farming systems could provide some promising alternatives, as it will be discussed below.

2.2 Shellfish Production Shellfish farming is the second aquaculture segment, constituting about 25 % of the total national aquaculture production, after the sea bream and sea bass farming (constitutes about 70 % of the total national aquaculture production) [8]. The Mediterranean mussel (Mytilus galloprovincialis) is the main shellfish species that is extensively cultured in Greece, with an annual production of over 35,000 tons [10]. There are about 500 farms, most of them located at the Thermaikos gulf. There are two methods of production, the long-line (most common method) and the on-table

method. Over 80 % of mussel production is exported to other countries and mainly to Italy and France.

Mussel farming, in the form that is conducted in Greece, is a relatively simple and low-cost activity, utilizing the natural spawning that occurs in the environment. However, the industry faces many problems, mostly related to bad marketing, legislation framework (related mainly to re-organization of the culture sites) and various unpredictable environmental parameters, such as harmful algal blooms [10]. Concerning the operation cost, Theodorou et al. [10] concluded that although this cost is related to farm size, the depreciation appears to be the main parameter, followed by labor cost.

The mussels are sold either with their shells (live), or without their shells, in water. However, very often large quantities of mussels may remain unsold for long periods of time (e.g. due to algal blooms, or really low market prices). The consumption of shellfish by the Greek consumers is still relatively low [11] and development of new forms of products may offer solutions to farmers in the future and this is pursued at the moment.

3. INTEGRATED MARINE FISH FARMING 3.1 Global Experience In the literature, there are several examples worldwide that demonstrate how integrated farming systems can increase the efficient use of natural resources and hence their productivity and competitiveness [9]. In the present review only selected studies, with a potential use in Greece, will be presented.

As discussed above, there are two issues of particular significance for marine finfish aquaculture: a) the reduction of the production cost, mainly through the use of cheaper commercial diets and b) the reduction of the environmental impacts that often lead to conflicts with local societies. Several studies aimed to address these issues though the use of integrated aquaculture.

3.1.1 Minimizing the environmental impacts Troell et al. [12] calculated that about 180,000 Mt of uneaten feeds used in aquaculture are excreted in the sea in the form of ammonia-N. They also estimated that, theoretically, most of this could be used by shellfish and seaweed in integrated systems.

One representative study of how an integrated system can be designed to reduce the discharge of wastes from an open-sea fish farm into the environment is that by Bodvin et al. [13]. In that study, the water from fish cages, which was heavily loaded with organic materials, such as faeces and uneaten feeds, supplied floating units of mussels. The bivalves utilized the big particles in the water through their filtration activity. Finally, the water from the mussel units supported the growth of seaweeds (macroalgae). In this case, the seaweeds acted as natural bio-filters to clean the water that was released into the environment. Such a system, if properly designed, can lead to a significant reduction in the waste management cost and to a stable and sustainable activity [14]. Additionally, as the legislation on the protection of the environment is becoming quite strict, such production patterns will be easier to finance [14].

In land-based farming systems, fish and shrimp are reared in high stocking densities, in ponds or tanks. In intensive fish farming, where re-circulating water is used, commercially important seaweed species, such as Ulva and Gracilaria can be used as bio-filters to reduce the nutrients present in the water, increasing at the same time the oxygen levels in the water through photosynthesis [15]. An interesting example of integrated salmon and seaweed


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culture in commercial land facilities was presented by Buschmann et al. [16]. In that example, along with 92 tons of fish 500 tons of red seaweed (Gracilaria chilensis) was produced. At the same time, 50 % (in winter) up to 90 % (in summer) of the ammonium in the effluent water was removed by the seaweeds.

A major structural weakness of the integrated farming system is the critical design of the system, which needs to take into account many factors, particularly environmental, as many authors stressed in previous studies [17].

Another, equally important issue is the possibility of transferring and harbouring significant for the principle farmed species (e.g. fish) pathogens, as for example Vibrio anguillarum, [18] within the body of the other species and particularly the bivalves.

3.1.2 Reducing the feeding cost Up until now, only few trials have demonstrated the potential of using integrated culture systems to reduce the cost of feeds used in fish farming. Two of these studies, which were conducted in Europe, showed how micro- and macroalgae produced from in an integrated system can be used as fish feedstuff ingredients [19, 20]. According to the study by Borges et al. [19] the effluent water from turbot and sea bass rearing tanks was used to successfully culture various species of microalgae, which are commonly used as live feeds for fish larvae. The microalgae also reduced, to some extend, the nutrient levels in the water. In the second study by Valente et al. [19] showed that macroalgae species, which are often used in integrated systems, can be used as incidents in the diets of sea bass juveniles without compromising their growth.

3.2 Efficient Use of Integrated Aquaculture Systems Soto [9] in his extensive review on the global status of integrated aquaculture systems lists some criteria that can lead to an efficient application of these systems. These criteria are:

(a) Assessment of the economic value of each component as well as that of the overall system.

(b) Development of bio-economic models to assess the profitability of the systems.

(c) Estimation of the additional economic value of co-products.

(d) Use of the most appropriate species in a certain area or country.

(e) Consideration of the specific characteristics of an area/country/ society/market.

(f) Creation of an adequate and effective legislation framework.

(g) Establishment of continuous and effective research projects.

3.3 Our Experience The Laboratory of Ichthyology at the Faculty of Veterinary Medicine, A.U.Th is actively involved in many research projects related with fish and shellfish health. Of particular interest is the effect of the use of new raw materials, as ingredients in commercial feeds, on the health and growth performance of the cultured fish.

Maybe the top priority of the Greek marine aquaculture industry is the substitution of the fishmeal used in the commercial feeds with

other raw materials. So far attempts have been made to use plant proteins, such as rapeseed meal, various forms of soy bean meals and many other seed meals, such as legume, pea and caror seed germ meal. These trials have indicated that such substitution, especially at high levels, can have negative effects on the growth performance of the reared fish.

In a series of experiments, frozen mussels (M. galloprovincialis) were mixed with commercial diets for sea bream and sea bass. This pilot studies were conducted in view of integrating mussel culture in the sea bream and sea bass farming. The trials (unpublished data) indicated that mixing frozen mussels with commercial feeds at a level of approximately 30 % (wet weight) could significantly improve the feed and protein efficiency. The method of mixing was simple and could be used on-farm. Of course, more field trials are required to indicate the optimum way of incorporating such a procedure in the existing production cycle.

Although in Greece the mussels and to a mush smaller extent oysters, are farmed in the open sea, it is believed that under certain circumstances small-scale shellfish cultures in land-based facilities can be incorporated in the existing fish production systems, and used for the treatment of the effluent water, as well as to provide nutrient-rich medium for the culture of microalgae species that are used in the commercial sea bream and sea bass hatcheries. In this direction, in a preliminary study, the effluent water that originated from oyster culture was used as medium for the culture of microalgae. The results [21] indicated that such water can be incorporated in the standard culture medium and sustain the growth of Isochrysis galbana for up to three days using 50 % less nitrogen.

The first field trials of co-culturing mussels and fish, which will be conducted in the near future, are expected to provide important results on the feasibility of applying integrated aquaculture systems under the Greek conditions.

4. REFERENCES [1] Rabanal, H.R. 1988. History of Aquaculture. http://www.fao.

org/docrep/field/009/ag158e/AG158E00.htm#TOC [2] Halwart, M.and Gupta, M.V. 2004. Culture of fish in rice

fields. FAO and The WorldFish Center. ISBN 983-2346-33-9.

[3] Casalduero, F.G. 2000. Integrated systems: "Environmentally clean" aquaculture. In Proceedings of the seminar of the CIHEAM network on technology of aquaculture in the Mediterranean (TECAM), jointly organized by CIHEAM and FAO, Zaragoza (Spain), 17-21 January 2000. http://ressources.ciheam.org/om/pdf/c55/01600228.pdf

[4] http://www.feap.info/production/countries/greece/greekprod_ en.asp

[5] http://www.fao.org/fishery/en

[6] University of Stirling 2004. Study of the market for Aquaculture produced seabass and seabream species. Report to the European Commission DG Fisheries. http://ec.europa.eu/fisheries/documentation/studies/aquaculture_market_230404_en.pdf

[7] Moretti, A., Fernandez-Criado, M.P. and Vetillart, R. 2005. Manual on Hatchery Production of Seabass and Gilthead Seabream Volume 2. FAO, Rome. http://www.fao.org/docrep/008/y6018e/y6018e00.htm


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[8] Barazi-Yeroulanos, L. 2010. Regional synthesis of the Mediterranean marine finfish aquaculture sector and development of a strategy for marketing and promotion of Mediterranean aquaculture. FAO, Rome, 2010, Studies and Reviews No. 88. http://151.1.154.86/GfcmWebSite/GFCM/34/GFCM34_2010_Dma5.pdf

[9] Soto, D. 2009. Integrated mariculture - A global review. FAO Fisheries and Aquaculture Technical Paper. No. 529. http://www.fao.org/docrep/012/i1092e/i1092e00.htm

[10] Theodorou, J.A., Sorgeloos. P., Adams, C.M., Viaene, J., and Tzovenis, I, 2010. Optimal farm size for the production of the Mediterranean mussel (Mytilus galloprovincialis) in Greece. IIFET 2010 Montpellier (France) 13-16 July 2010. http://www.iraj.gr/IRAJ/253.pdf

[11] Batzios, Ch., Angelidis, P., Moutopoulos, D.K. Anastasiadou, Ch. and Chrisopolitou V. 2003. Consumer attitude towards shellfish in the Greek market: a pilot study. Medit. Mar. Sci. 4/2, 155-174.

[12] Troell, M., Halling, C., Neori, A., Chopin, T., Buschmann, A.H., Kautsky, N., Yarish C., 2003. Integrated mariculture: asking the right questions. Aquaculture 226, 69–90.

[13] Bodvin, T., Indergaard, M., Norgaard, E., Jensen, A., Skaar, A. 1996. Clean technology in aquaculture - a production without waste products? Hydrobiologia 326/327, 83-86.

[14] Chopin, T., Buschmann, A.H., Hulling, C., Troell, M., Kautsky, M., Neori, A., Kraemer, G.P., Zertuche-Gonzálrez, J.A., Yarish, C. and Neefus, C. 2001.Integrating seaweeds into marine aquaculture systems: a key toward sustainability. J Phycol. 37, 975-986.

[15] Neori, A., Chopin, T., Troell, M., Buschmanne, A.H., Kraemer, G.P., Halling C., Shpigel M. and Yarish, C. 2004.

Integrated aquaculture: rationale, evolution and state of the art emphasizing seaweed biofiltration in modern mariculture. Aquaculture 231, 361–391.

[16] Buschmann, A.H., Troell, M., Kautsky, N. and. Kautsky, L 1996. Integrated tank cultivation of salmonids and Gracilaria chilensis (Gracilariales, Rhodophyta). Hydrobiologia 326/327, 75-82.

[17] Cheshuk B.W., and Purser G.J., R. 2003. Integrated open-water mussel (Mytilus planulatus) and Atlantic salmon (Salmo salar) culture in Tasmania, Australia. Aquaculture 218, 357–378.

[18] Pietrak, M.R.; Molloy, S.D., Bouchard, D.A., Singer, J.T. and Bricknell, I. 2012. Potential role of Mytilus edulis in modulating the infectious pressure of Vibrio anguillarum 02β on an integrated multi-trophic aquaculture farm. Aquaculture 326-329, 36-39.

[19] Borges, M.T., Silva, P., Moreira, L.and Soares, R. 2005. Integration of consumer-targeted microalgal production with marine fish effluent biofiltration – a strategy for mariculture sustainability. J Appl. Phycol. 17, 187–197.

[20] Valente, L.M.P., Gouveia, A., Rema, P., Matos, J., Gomes, E.F. and Pinto I.S. 2006. Evaluation of three seaweeds Gracilaria bursa-pastoris, Ulva rigida and Gracilaria cornea as dietary ingredients in European sea bass (Dicentrarchus labrax) juveniles. Aquaculture 252, 85–91.

[21] Symeonidis, C., Angelidis, P., Kamarianos, A., Vatsos, I.N., Batzios, C. 2010. Use of the nitrogen of oyster culture effluent by the marine microalgae Isochrysis galbana (CLONE T-ISO). In Proceedings of Aquaculture Europe 2010, 5-8 October, Porto, Portugal. p. 128-129.


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Assessing Scenarios on Maritime Transport Policies by Means of Multicriteria Analysis: the Case of Greece

Eliza Gagatsi Aristotle University of Thessaloniki

541 24, Thessaloniki, Greece +30 2310 498464; +306976224371

[email protected]

ABSTRACT The importance of maritime transport in the world’s economy and employment sector along with its strong dependency on the worldwide macroeconomic conditions due to its globalised nature highlights the importance of clear as well as flexible policy structures able to cope with critical and unstable situations.

Although the world economic situation seems to have brightened in 2010, the situation in Greece, one of the most important players in the world’s maritime scene, is still extremely volatile.

Recent developments in operational research science have proved that the use of a tailor-made decision-support system can strongly support the policy making process by evaluating the effects of a series of policy scenarios in the under consideration area. The present paper reports on an going research that focuses on the application of multicriteria analysis techniques for the identification and evaluation of critical for the Greek maritime transport system parameters and how these can be utilized for formulating a maritime transport policy decision support tool.

Keywords Maritime transport policy, Multi-criteria analysis, Analytic Hierarchic Process, Greece

1. INTRODUCTION The Greek Maritime transport system and its respective policy framework has been formulated around 4 distinctive sub-areas based on the international and European legislation namely [1]:

• The ocean going sector • The short-sea sector • The cruise sector • The domestic ferries sector

All 4 areas are integral pieces of the Greek Maritime transport puzzle and are characterized by a variety of different needs and priorities calling at the same time for different policy measures.

The policy making process is becoming quite complex since it has to deal with different needs, interests, priorities, involved bodies and, above all, limited resources in a very critical for the country period. The actual evaluation of each policy effect is also a very complex task incorporating aspects that in most cases cannot be translated into cost elements. To this end, the use of qualitative research techniques such as the MCA is deemed necessary for the appraisal of policies dealing with the integrated approach of maritime transport. The appraisal of integrated transport policies is not straightforward, as these policies take different shapes [2]. Merging 4 different sectors in a common policy evaluation

framework is a challenge by definition. However, MCA comprises a strong technique for planning under uncertainty and is proposed for rationalizing complex decision problems and goal conflicting cases by “providing both a tool for communication between all actors involved and a rigorous analytical technique for examining (implicitly or explicitly) the implications of policy trade-offs.”[2]

2. KEY PRIORITIES OF THE GREEK MARITIME TRANSPORT SYSTEM: SETTING THE SCENE The methodology followed for the identification of the key priorities that affect each subsector of the Greek maritime transport system was based on a detailed bibliographical review. An analysis of the Greek Maritime Transport system took place prior to the priorities identification, aiming to capture:

• The key stakeholders’ participation in the Greek Maritime Transport System

• The main policy lines followed by the national policy makers over the past decades

• The future policy orientations of the sector according to the existing or proposed legislation

The Maritime Transport Sector in Greece was “mapped” in terms of individual types of ‘forces’ that participate in each subsector’s operation. The analysis was based on the Porter’s 5 competitive forces model [3] aiming to capture the type of actors that can be considered as the subsector’s supply and demand markets as well as internal and external competitors and also substitute where available.

To this end, the key actors and stakeholder in each subsector were identified along with their key priorities as stated in official policy reports, announcements and other relevant documents.

In parallel, the existing and foreseen policies set by the responsible authorities (Ministries) were identified and also allocated to the 4 subsectors.

This process was repeated also for the creation of a European Maritime Transport policy map.

The result of this work led to the creation of the first set of priorities for each sub sector summing up to 39 parameters that can be considered as key priorities of the maritime transport sector of Greece.


32

Table 1. Key competition forces in Greek Maritime Transport sector

Source, [3], adjusted for the research needs

3. GOALS, CRITERIA, EVALUATION SCENARIOS AND MAJOR CHALLENGES

The ultimate objective of this research work, implemented within the framework of a research grant under the HRAKLEITOS II scholarships program of the Hellenic Republic’s Ministry of Education, is to come up with a tool that will support the policy making process through the evaluation of a set of policies in the maritime transport sector.

As already noted in the introductory chapter, the use of MCA is considered the most appropriate method for the evaluation of such complex and non-easily quantified evaluation problems. The selected MCA technique is the Analytic Hierarchic Process, developed by Saaty in 1980[5]. AHP decomposes the decisional process in a hierarchy of criteria, sub-criteria, attributes and alternatives through a set of weights that actually reflect the relative importance of each examined alternative.

The method is structured around three major steps:

• Step 1: Definition of the hierarchy goal ( top level) • Step 2: Building of the hierarchy (definition of criteria

and sub-criteria). For the examined problem a bottom up approach was used.

• Step 3: Definition of the alternatives to be examined.

The intermediate levels that are built within step 2, are used for grouping similar issues that can be compared. The bottom level that is built in the third step (lower level of the hierarchy) is intended to ask the key questions that the AHP seeks to examine.

The application of the above methodology leads to the creation of the decision tree that captures the evaluation process and the key relations among the different criteria, sub-criteria attributes and alternatives to be examined.

The particularities of the specific evaluation problem are described in the next paragraphs along with the main research issues and questions that need to be addressed.

3.1 Key particularities of the multi-dimension evaluation problem The major challenge in the examined evaluation problem consists of the development of a single hierarchy structure that can “merge” the 4 examined sub-sectors of maritime transport. In order to capture the evaluation framework each sector was analyzed separately. Therefore, the 3 step of AHP structuring

process were applied for the creation of each subsector’s decision tree.

The first particularity encountered concerned the different type of hierarchy goals. This is due to the different characteristics of the examined sub-systems, their current status in terms of “economic performance” and contribution to the country’s economy, as well as the different trends foreseen for each subsector. The following Table summarizes the current situation, the foreseen trends and the key evaluation goals identified for each of the 4 sub-sectors.

Table 2: Economic Performance and Foreseen Trends of the 4 sub-sectors comprising the Greek maritime transport

S1: OCEAN GOING

S2: SSS S3: CRUISE

S4: COASTAL

Economic performance

Identified trend

AHP evaluation goals

Increase competitiveness



Secure viability

Different sources, elaborated by the author

The downtown trend of the coastal shipping sector that is shown above - – is attributed to a large extend to the economic crisis that led to the shrinking of the households’ purchasing power, thus decreasing the demand in coastal shipping- encountered since 2007 [6]. This trend is expected to even worsen in the next years bringing the viability at the top of the goals that the sub-sector needs to achieve. The economic performance of the Greek coastal shipping and its contribution to the country’s economy is negative, taking into consideration that the country has to finance the sector’s operation through the funding of the so-called unprofitable lines, a cost that steadily increased over the past decade.

As concerns the remaining three sub-sectors, their economic performance in terms of contribution to the country’s GDP and employment along with their developmental potential varies significantly. However for all three sectors, the ultimate targets of the country’s policies focus on increasing their competitiveness and contribution to GPD and employment.

The next research issue that needed to be addressed concerned the identification of the alternatives to be used for each sectors “performance” evaluation.

For the scope of the present analysis, three alternatives were identified as relevant to be examined. The first one concerns the “As is Situation” or “Do Nothing Scenario”. It will be used for assessing the hierarchy of the identified criteria towards each evaluation goal for the current situation.

Following the same logic, two additional alternatives/ scenarios were formulated: the “Medium – Long Term scenario” and the “Short Term Scenario”. Therefore, the actual evaluation question to be addressed is two-fold, covering the importance of each examined criterion (priority) to each sector’s evaluation goal in short and medium-long term. Within the scope of this analysis, the Short term alternative focuses on a 1-5 year period and the medium –long term on a 5-15 years period.


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Figure 2 provides an overview of the three step AHP application to the cruise sector.

As already stated, the major challenge of this research consists the evaluation of the whole maritime transport system of Greece.

Policies for making Greek ports more attractive to cruise destinations (especially for

homeporting)

Policies for strengthening Greek cruise sector (flag related

measures)

G3 : Competitiveness of Cruise Sector

CSF4.4:Establishment of training/education centres

CSF4.1:Minimum crew requirements(number,nationa

lity)

CSF4.2: Labor cost

CS4.3:Insurance, bureaucracy

Port infrastructure

related policies

Port services related policies

CSF1.1: Port expansion/

upgrade

CSF1.2: New ports

CSF2.1:Berth allocation

CSF2.2:Port service provision (pilotage,tendeservices, fresh

water..)

CSF2.3:Low cost

CSF2.4:Port facilities security, time spent for

security checks

Destination attractiveness related policies

CSF3.1: home port accessibility

CSF3.2:Access to combined transport

CSF3.3:Adverst. Campaign

CSF3.4:Coordination with attraction points

CSF3.5:Central info point for cruise (e-

cruise)

S1: Do Nothing Scenario

S2:Medium-Long Term Scenario

S3: Short Term/ soft scenario

GOAL

CRITERIA

ALTERNATIVES

`

SUB-CRITERIA

Figure 2: Example of the cruise sub-sector Decision Tree

Figure 3 provides an overview of the Greek Maritime Transport policy priorities “decision tree” that was developed for the scopes of the analysis.

S1: Do Nothing Scenario S2:Medium-Long Term Scenario S3: Short Term/ soft scenario

Policies for making Greek ports more attractive to cruise destinations (especially for

homeporting)

Policies for strengthening Greek cruise sector (flag related

measures)

G3 : Competitiveness of Cruise Sector

Greek Maritime Transport System

Greek flag attractiveness related policies

Policies for Greek ports attractiveness

(attract flows)

Policies for supporting/

attracting shipping cluster activities

G1 : Competitiveness of Shipping (ocean going and SSS)

Πολιτικές που στοχεύουν στην µείωση του κόστους

της ακτοπλοΐας

Πολιτικές που στοχεύουν στην βελτίωση των ποιοτικών

χαρακτηριστικών της παρεχόµενης υπηρεσίας

G3 : Viability of Inland maritime transport system (ferries)

CSF4.4:Establishment of training/education centres

CSF4.1:Minimum crew requirements(number,nationa

lity)

CSF4.2: Labor cost

CS4.3:Insurance, bureaucracy

Port infrastructure

related policies

Port services related policies

CSF1.1: Port expansion/

upgrade

CSF1.2: New ports

CSF2.1:Berth allocation

CSF2.2:Port service provision (pilotage,tendeservices, fresh

water..)

CSF2.3:Low cost

CSF2.4:Port facilities security, time spent for

security checks

Destination attractiveness related policies

CSF3.1: home port accessibility

CSF3.2:Access to combined transport

CSF3.3:Adverst. Campaign

CSF3.4:Coordination with attraction points

CSF3.5:Central info point for cruise (e-

cruise)

CSF5.1:Απλοποίηση/ επιτάχυνση διαδικασιών

(πχ e-Νηολόγιο, One stop-shop)

CSF5.2:security related legislation (0n board-for

confronting piracy..)

CSF5.3: Επιδοτήσεις για ναυπηγήσεις νέων πλοίων/ ανανέωση

στόλου

CSF5.4:Απλοποίηση απαιτήσεων νηολογίου (πχ ελάχιστος αριθµός µελών πληρώµατος)

CSF6.1:Ανταγωνιστικές υπηρεσίες (τελωνεία, περιβαλλοντικά θέµατα, χρόνοι εξυπηρετησης…)

CSF6.2: Εξειδικευµένο προσωπικό

CSF6.4: ενίσχυση Port-hinterland connections

(rail) for intermodal transport facilitation

CSF6.3: Ανταγωνιστικό κόστος υπηρεσιών

CSF7.2: ίδρυση φορέα οργάνωσης και διευκόλυνσης ναυτιλιακών επενδύσεων

CSF7.3: Invest in ship building ship repair..

CSF7.1: Ανάπτυξη Ελληνικού Shipping cluster..(νοµοθεσία)

CSF5.5: αναβάθµιση ναυτικής εκπαίδευσης και σχετικής υποδοµής

CSF5.6: Κοστος κοινωνικής ασφάλισης?

Κάλυψη από το κράτος??

CSF8.1: Μείωση ΦΠΑ εισιτηρίων

Μείωση κόστους

µετάβασης

CSF9.1: STCW

requirements for crew

Μείωση κόστους

µεταφοράς

CSF9.2: Δικαίωµα µείωσης ταχύτητας πλοίου

Πολιτικές µείωσης κόστους

επιδοτήσεων

CSF10.1: Αξιοποίηση Κοινοτικής

Χρηµατοδότησης

Εκσυγχρονισμός

υπηρεσιών ενημέρωσης χρηστών

Περιορισµός συµφόρησης λιµένων στις

περιόδους αιχµής

Βελτίωση προσβασιμότητας νησιών

CSF13.1:δίκτυο

µεταφορών, οµάδες µελέτης, παρατηρητήριο

CSF13.2:συνδυασµένες

νησιωτικές

συγκοινωνίες

CSF12.1Λειτουργία και άλλων κεντρικών λιµένων πέραν του Πειραιά

CSF12.2: Βελτίωση χώρων υποδοχής επιβατών

CSF5.3: Slot

allocation system στους λιµένες

CSF11.1 ΤΠΕ

τεχνολογίες σε λιµάνια

CSF11.2: Ηλεκτρονική διακυβέρνηση,

ΥΕΝ

Figure 3: AHP application to the Greek Maritime Transport System

3.2 AHP application: scoring and weighting Analytic Hierarchy Process is actually a method for converting subjective assessments of relative importance to a set of overall scores or weights [7]. To be able to apply scores and weights to the identified criteria and sub-criteria, a special questionnaire for each subsector was designed and will be addressed to a relevant experts’ group.

The questionnaire is based on the 1-5 rating scale proposed by Saaty [5] aiming to capture the relevant importance of each criterion towards the examined goal for each of the examined alternatives.

The experts’ team that will participate to the scoring and weighting process will include representatives from:

- Policy making bodies (eg relevant ministries, regional authorities etc)

- Industrial stakeholders (ports, shipping companies, port customers, labor organizations, ports associations etc)

- Academia-research (eg universities, research institutes etc)

Furthermore, the experts’ team will cover the key stakeholders that comprise each sub-sector’s supply and demand as recorded in Table 1.

The key experts that will support the scoring and weighting process will be contacted by personal or telephone interviews so that additional comments or proposals they might have will be effectively captured.

4. KEY RESEARCH QUESTIONS –DICSUSSION ISSUES This paper presents the key concept of an on-going research work that aims to examine the particularities of the Greek Maritime Transport System versus the European one, and to come up with a Decision Support Tool that will be used for supporting the policy making process through the evaluation of the effects of key policies to the country’s maritime transport system.

The particularities of the examined sector and the complex and controversial targets of the evaluation problem led to the selection of MCA (AHP) as the most appropriate evaluation technique. Still there are several issues to be addressed before stepping up to the actual application of the method.

The research questions can be grouped into two different categories:

- The first is related to the process followed for the selection of the evaluation criteria and sub-criteria. The methodology that has been presented in this paper focuses on a bottom –up approach. However, the author will examine also the top down approach, starting from the European policy framework

- The second group of questions concerns the actual application of the selected evaluation technique. The main problems that need to be addressed concern:

o The different first level goals of each subsector o The evaluation of each sub-sector’s contribution to

the country’s maritime transport sector o The selection of the alternatives to be examined o The identification of potential interactions among

the sectors The major challenge of this research work – and also the most interesting part of it- is the fact that it attempts to apply the holistic approach that the EU proposes for maritime policy making [8] into the formulation of a policy evaluation methodology. The unadoptable difficulty lies into the particularities of each sub-sector that comprise the national maritime transport system as well as the dynamic nature of maritime transport. However, the development of a policy decision support tool can become a very useful “weapon” for the


34

optimum exploitation of maritime transport for the country’s benefit in a very difficult and sensitive economic concurrence.

5. ACKNOWLEDGMENTS This research has been co-financed by the European Union

(European Social Fund – ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: Heracleitus II. Investing in knowledge society through the European Social Fund The author wishes to acknowledge the Heracleitus II scholarships program of the Hellenic Republic Ministry of Education for proving the unique opportunity of studying the very interesting and important for the country’s economic recovery sector of maritime transport.

6. REFERENCES [1] Alkis John Corres : Pallis A A (Editor): Maritime Transport:

The Greek Paradigm, Research in Transport Economics Series Νο 21,London: Elsevier. ISBN-978-0-7623-1449-2 “Greek maritime policy and the discreet role of shipowners’ associations.” Chapter 13, Elsevier Transport Series, London, 2007.

[2] Bakker, P, Koopmans, C, Nijkamp, P, Appraisal of integrated transport policies

[3] Michael E. Porter, “The Five Competitive Forces That Shape Strategy, HBR’s Must-Reads on Strategy”, p. 23, Harvard Business Review

[4] Porter, M., (1980). Competitive Strategy, New York: Free Press.

[5] Saaty, T. L, (1980). The Analytic Hierarchy Process, New York: McGraw-Hill

[6] National Statistical Service of Greece (N.S.S.G.)

[7] Multicriteria Analysis: A manual, Department for Communities and Local Government, London, January 2009, ISBN: 978-1-4098-1023-0

[8] Maritime Transport Strategy 2009-2018: Strategic goals and recommendation for the EU’s maritime transport policy until 2018, European Commission, DG for energy and Transport, 21 January 2009

[9] Review of Maritime Transport 2011, UNCTAD/RMT/2011

[10] XRTC, Annual Report on the Greek Ferry Sector (2010-2011)

[11] Decision Making Support Systems, Achievements and Challenges for the new decade, M. Mora, Guisseppi A, JatinderN. D., elSBN 1-59140-080-5.


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Evaluation of Investments in the Field of Renewable Energy Resources using MCDA

Ioannou Konstantinos Laboratory of F. Informatics

School of Forestry and Natural Environment

Aristotle University of Thessaloniki +30 6944798247,

[email protected]

Arabatzis Garyfallos Department of Forestry and

Management of the Environment and Natural Resources

Democritus University of Thrace +30 6944298499

[email protected]

Zagkoumidou Vasiliki +30 6974754885

[email protected]

ABSTRACT It is well known that the main part of human energy needs is covered by the use of fossil fuels, like oil, coal and natural gas. The reserves of fossil fuels are limited and their resources are depleted quickly, especially if we take into account the ever-increasing rate of consumption in the developing countries. Additionally, the use of such raw materials for energy production lead burden on the natural environment, because they produce a series of green house gases and other pollutants which contribute to the green house effect.

It is logical to assume that the decrease of conventional energy resources in conjunction with the environmental contamination caused by the use of these resources has led governments and companies to explore the possibility of increasing the exploitation of Renewable Energy Sources (RES), the use of which ensure that there will be limitless energy production, and that there will be no further burden to the environment.

Renewable Energy sources are energy sources that are continuously renewing based on a practically limitless energy source like the sun, or can be considered as limitless when used with proper management. Sources of this type are solar, wind, biomass and geothermal energy, the use of which is growing at a significant pace, due to the comparative advantages compared with conventional energy sources and due to the agreements for the protection of the environment.

As a result governments and companies around the world are continuously seeking ways to shift to the use of RES in a process that is called "Sustainable Development", which refers to the economic development designed taking into account the protection of the environment and implement green growth programs in an effort to spur economies and lead to new business opportunities opened for green technologies. Green technologies are developed based on increased environmental consciousness. Green economy is the economic activity, which is associated with reducing the use of fossil fuels, reducing air pollution-pollution and greenhouse gas emissions, recycling materials and the development and adoption of renewable energy sources.

This paper aims to the design, development and implementation of a functional and flexible model for recognition of the best forms of banking investments in the field of green economy. As a result the model will rank all the suggested investments in 4 different fields taking into account Environmental and Economic parameters, thus allowing managers to easily identify the most profitable. Additionally the model will be capable of recognizing problematic areas leading to improvements in the proposal and the capability to create what-if scenarios.

The main tool used for the creation of the model is a Multicriteria Decision Analysis method, called Analytic Hierarchy Process (AHP) which allows the use of quantitative and qualitative criteria during modeling.


36

Assessment of the Rural Development Plan in Greece. A Multicriteria Analysis

Bournaris Thomas Aristotle University of Thessaloniki

Department of Agricultural Economics Thessaloniki 54124, Greece

[email protected]

Moulogianni Christina Aristotle University of Thessaloniki


[email protected]

Manos Basil Aristotle University of Thessaloniki


[email protected]

Vassiliki Manthou University of Macedonia

Department of Applied Informatics Thessaloniki 54006, Greece

[email protected]

ABSTRACT The Rural Development Plan measures affect people living in rural areas and have impacts on agricultural income and rural employment, maintaining also the social fabric of rural areas. This paper aims to assess the direct and indirect economic, environmental and social impacts of the measure “Setting up Young Farmers” of the Rural Development Plan in the region of Thessaloniki in Greece. For this reason, a sample of young farmers who have participated in the “Setting up Young Farmers” measure during 2007-2010 from the Prefecture of Thessaloniki

was chosen. For the assessment of impacts and the simulation of the results, a multicriteria mathematical programming model was implemented.

Keywords Multicriteria mathematical programming, impact assessment, rural development.


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Ascendant Hierarchical Classification of Individuals, who are Determined by a Number of Categorical, Ordinal and

Quantative variables Odysseas Moschidis

Department of Marketing and Operations Management University of Macedonia Ethnikis Antistaseos 33

Moudania, 63200, Greece

[email protected]

Vasileios Ismyrlis Department of Marketing and Operations Management

University of Macedonia Agiou Dimitriou 49, 58200, Edessa, Greece

[email protected]

ABSTRACT The present research deals with the grouping of individuals, who are determined by a number of categorical and ordinal variables. This research applies the method of Ascendant Hierarchical Classification (CAH); using as criterion, the inertia and the distance metrics of X2. The usual dealing with this problem refers to the coding of the certain categorical and ordered data in a logical table (0-1) under the form: individuals x variables. However, the sub table of the table (0-1), which concerns the ordered variables, deducts information in advance as it deals with

the ordered variables as being simple categorical variables. The research suggest a new encoding of the quantitative variables and of the ordinal variables that leads to a new more detailed encoding of categorical and ordinal variables in a new general table of percentages, the analysis (CAH) of which provides more detailed conclusion.

Keywords Ascendant Hierarchical Classification, distance metrics of X2, inertia, ordinal and quantitative variables.


38

Entropy Measures to Control Robustness in Ordinal Regression Models

Greco Salvatore Department of Economics and Business, University of Catania

Corso Italia 55, 95129 Catania, Italy [email protected]

Siskos Yannis University of Piraeus

80, Karaoli & Dimitriou Street GR-18534 Piraeus, Greece

[email protected]

Slowinski Roman Institute of Computing Science and

Systems Research, Poznan University of Technology 60-965 Poznan

Polish Academy of Sciences, 01-447 Warsaw, Poland

[email protected]

ABSTRACT Within Multiple Criteria Decision Aiding (MCDA), ordinal regression methods build a preference model in the form of a value function or an outranking relation on the basis of some preference information provided by the Decision Maker (DM). The first method using this approach was UTA in which one looks for a piecewise additive value function representing DM preference information in a ranking decision problem. The same methodology has been used in the UTADIS method for decision sorting problems. Ordinal regression has also been used for outranking methods, both for ranking and sorting decision problems. Recently, ordinal regression has been reconsidered in light of the following observation: very often there exists not only one instance of a preference model of a given type (e.g., additive value function or binary outranking relation), but there exists a plurality of instances that represent equally well the preference information given by the DM. However, each one of these compatible instances of the preference model may express different preferences when applied to pairs of alternatives different from those considered in the preference information. On the basis of this observation, Robust Ordinal Regression (ROR) has been proposed. ROR considers the whole set of compatible instances of a chosen preference model representing the preference information given by the DM, and it provides a recommendation of the MCDA procedure in terms of possible and necessary preferences. For example, considering a set of alternative A and a family of criteria G={gi, i=1,… ,n} (without loss of generality we suppose gi: A→R increasing with respect to the preference, i=1,… ,n), if the considered decision model is an additive value function, ROR considers the whole set U of additive value functions U: A→R such that for any ar∈A, U(ar)= u1(g1(ar))+…+ un(gn(ar)), compatible with the preference information given by the DM, and for any pair of alternatives a and b, we say that

• a is necessarily preferred to b, if U(a)≥U(b) for all U∈U, and we denote this as a N b,

• a is possibly preferred to b, if U(a)≥U(b) for at least one U∈U, and we denote this as a P b.

Consideration of the whole set of instances of some preference model compatible with the preference information of the DM permits to avoid an arbitrary choice of only one of its compatible instances. ROR has been first proposed in the UTAGMS method, and after it was generalized in the GRIP method. UTAGMS and GRIP consider a ranking decision problem using the preference model in the form of an additive value function. ROR has been

applied also to decision sorting problem in the UTADISGMS

method. Moreover, ROR has been extended on outranking methods (ELECTREGKMS, PROMETHEEGKS) and on non-additive value functions having the form of Choquet integral (Non Additive Robust Ordinal Regression – NAROR). It has also been successfully applied to group decision problems (UTAGMS-GROUP, UTADISGMS-GROUP, ELECTREGKMS-GROUP, and so on).

Let us observe that even if the idea of considering the whole set of compatible instances of a chosen preference model compatible is appealing, there is a risk that the results obtained in terms of necessary and possible preferences are too vague because the set of these compatible instances is in some sense “too large”. In order to control this aspect of the ROR methodology, we propose to measure the set of compatible instances of the considered preference model. In fact, each compatible instance of the preference model is defined by a set of preferential parameters (for example, in case of additive value functions, the preferential parameters are the values assigned by marginal value functions to the evaluations of the reference alternatives considered by the DM in her preference information). Thus, we propose to measure the set of compatible instances of the considered preference model as the hypervolume of the set of corresponding preferential parameters. This hypervolume can be approximated using a Monte Carlo approach, i.e. randomly generating a set of vectors of preferential parameters. For the sake of simplicity, we present this methodology in the context of the UTAGMS method only.

The set of constraints COMP to be satisfied by a compatible additive value function are:

U(a)≥U(b)+ε for all ab, and U(a)=U(b) for all a∼b, a,b∈AR,

uj( xrj 1+ )≥uj( xrj ), where xrj ∈Xj={gj(a), a∈AR}, such that

x j1 < x j2 <…< ( )x jXcardj for all gj∈G,

uj( x j1 )=0, for all gj∈G, u1(( )x Xcard 1

1 )+…+um( ( )x mXcardm )=1,

where ε is a small positive value. Of course the “larger” is COMP the “smaller” is N and the “larger” is P. In other words, taking into consideration that always N ⊆ P, the “larger” is COMP the “larger” is Δ() = P − N, such that a measure of Δ, for example its cardinality |Δ()|, can be considered as a measure of the uncertainty due to ambiguous representation of DM’s preferences by the adopted preference model. Another coarse measure of this uncertainty is


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given by a measure of COMP. It can be obtained in different ways. One possible way is the following. First we compute the volume of the feasible set of preferential parameters when there is no preference information. It can be done as follows.

Let us consider the set of constraints MON:

uj( xrj 1+ )≥uj( xrj )+ εrj , where xrj ∈Xj−{ ( )x jXcardj } and Xj ={gj(a),

a∈AR}, such that x j1 < x j2 <…< ( )x jXcardj for all gj∈G

uj( x j1 )=0, for all gj∈G, u1(( )x Xcard 1

1 )+…+um( ( )x mXcardm )=1,

εrj ≥0 for all (r,j)∈RJ.

A measure of COMP can be obtained generating randomly points within MON using the ‘hit and run’ method. The ratio between the number of the points generated within MON which satisfy COMP and the total number of points generated within MON gives an approximate measure of the hypervolume of COMP, considering as unitary the hypervolume of MON. This measure is denoted by V().

Using the same methodology we can compute a credibility of the preference of alternative a over alternative b, a,b∈A. This can be obtained as a ratio between the number of random points generated within MON that satisfy the constraints of COMP for which U(a)>U(b) and the total number of the same random points that satisfy only COMP. Such credibility, denoted by P(ab), can be interpreted as a probability that, picking randomly a compatible value function, alternative a is better than alternative b. Analogously, one can compute P(ab), having the interpretation that picking randomly a compatible value function, alternative a is at least as good as alternative b. Credibility P(ab) and P(ab) gives us another finer measure of the uncertainty due to ambiguous representation of DM’s preferences. In fact, with respect to the alternative a,b∈A the closer P(ab) is to 0 or to 1 and the closer P(ba) is to 1 or to 0, respectively, the more certain is the truth or falsity of the statement ab, i.e. the statement “a is at least as good as b”. The certainty about the truth or falsity of ab can be modeled through P(ab) using the concept of Shannon entropy given by H(a,b)=−P(ab) log2 P(ab). A global measure of the uncertainty can be obtained taking the average of all H(a,b) for all (a,b)∈A[2], where A[2] =A2−{(a,a): ∈A}, i.e.

H()=( )

( ) [ ]

( )1

,2,

−×

∑∈

nn

baHAba

where n=|A|. H() is a measure ranging between 0 and 1 and, more precisely, H()=1 in case P(ab)=1 or P(ab)=0 for all (a,b)∈A[2] and H()=0 in case P(ab)=0.5 for all (a,b)∈A[2]. Instead of the Shannon index, other entropy indices can considered such as the Renyi entropy index and the Tsallis entropy index.

Using random points that satisfying COMP it is possible to compute the probability fk(a) that picking randomly a compatible value function alternative a∈A is in the k-th rank, k=1,…,n, from the best to the worst. The Shannon entropy can be applied also to compute the entropy relative to the ranking of alternative a, to the k-th ranking position and to the whole matrix F=[ fk(a)], obtaining, respectively:

H(a)= ( ) ( )∑−=

n

kkk afaf

1log , Hrank(k)= ( ) ( )∑−

∈Aakk afaf log ,

Hrank(F)=( ) ( )n

afafn

k Aakk∑ ∑

− = ∈1log

.

It is also possible to use the Renyi and Tsallis entropy to the probability fk(a) obtaining the analogous of the three above index obtained using the Shannon entropy index.

Measures Δ(), V(), H() and Hrank(F) can be used to assist the process of elicitation of preferences by the DM. In fact, at each step of preference elicitation, one can evaluate the tradeoff between the decreasing confidence of the preference information given by the DM and the improvement of the measures Δ(), V(), H() and Hrank(F). The process of preference elicitation is stopped when the advantage in terms of improvement of Δ(), V(), H() and Hrank(F) does not compensate the lack of confidence of the DM in the intended preference information.

Of course, properly adapted, the same methodology can be applied to other ROR methods, such as UTADISGMS, ELECTREGKMS, PROMETHEEGKS, NAROR, UTAGMS-GROUP, UTADISGMS-GROUP, ELECTREGKMS-GROUP, and so on.

Keywords

Robustness analysis; Multicriteria analysis; Entropy.


40

Robustness Measures in Criteria Importance Estimation Based on Hamiltonian Search Algorithms

Hurson Ch. IAE, Université de Rouen, 3, Avenue

Pasteur, F-76186 Rouen Cedex, France

([email protected]

N. Christodoulakis University of Piraeus

80, Karaoli & Dimitriou str., GR-18534 Piraeus, Greece

[email protected]

Siskos E. National Technical University of

Athens Decision Support Systems Laboratory,

School of Electrical & Computer Engineering


Tsotsolas N. University of Piraeus

80, Karaoli & Dimitriou str., GR-18534 Piraeus, Greece

[email protected];

ABSTRACT Generally, robustness in OR appears as a tool of resistance of decision analysts against the phenomena of approximations and ignorance zones. More specifically, robustness is a tool to analyze the gap between the “true” DM’s model and the one resulting from a computational mechanism. Consequently robustness should be measured and controlled in any decision-aid activity. This paper presents a methodology to control robustness in two popular methods that are used to estimate the criteria importance or weights, i.e. a pairwise comparison inference technique and the Simos method. Both the methods use special linear programming techniques to infer the criteria weights. Two kinds of measures are proposed: (1) an average stability index (ASI) per criterion and

globally, and (2) a visualization measure. All these measures are based on the post-optimality analysis results, and especially on the form and the extent of the polyhedron of multiple/near optimal weighting vectors. The set of criteria weighting vectors are composed from all the edges of the polyhedron which is explored by means of the Manas-Nedoma Hamiltonian search algorithm (labyrinth algorithm). Two numerical examples are used to illustrate the methodology. Finally an outranking relation is constructed through the ELECTRE method based on a set of criteria weights.

Keywords Multicriteria analysis; criteria weights; inference techniques.


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Μια Αλγοριθμική Προσέγγιση Milp/Dea για το Βέλτιστο Σχεδιασμό Της Εφοδιαστικής Αλυσίδας

Πετρίδης Κωνσταντίνος Τμήμα Δασολογίας και Διαχείρισης



[email protected]

Γρηγορούδης Ευάγγελος Τμήμα Μηχανικών Παραγωγής και

Διοίκησης Πολυτεχνείο Κρήτης

[email protected]

Αραμπατζής Γαρύφαλλος Τμήμα Δασολογίας και Διαχείρισης



[email protected]

ΠΕΡΙΛΗΨΗ Σε αυτήν την εργασία προτείνεται µια αλγοριθµική προσέγγιση του προβλήµατος της βέλτιστης σχεδίασης της εφοδιαστικής αλυσίδας. Η βέλτιστη σχεδίαση της εφοδιαστικής αλυσίδας αντιµετωπίζεται χρησιµοποιώντας µοντέλα µικτού ακέραιου γραµµικού προγραµµατισµού (MILP) από τα οποία εξάγονται διάφορες αποφάσεις σχετικά µε την σχεδίαση και τον προγραµµατισµό της εφοδιαστικής αλυσίδας. Οι αποφάσεις αυτές συνήθως θα πρέπει να ικανοποιούν ένα ή περισσότερα κριτήρια που αφορούν στην ελαχιστοποίηση του κόστους ή αντίστοιχα στην µεγιστοποίηση του κέρδους, στην µείωση του χρόνου απόκρισης της λειτουργίας της εφοδιαστικής αλυσίδας µέχρι και σε περιβαλλοντικά ζητήµατα. Στην συγκεκριµένη εργασία προτείνεται η επιλογή της βέλτιστης σχεδίασης µε την µεγαλύτερη τεχνική αποδοτικότητα και προκύπτει από την µέθοδο DEA. Oι εισροές και οι εκροές βάση των οποίων γίνεται η επιλογή των βέλτιστων λύσεων, θα πρέπει να οριστούν εκ των

προτέρων και µε τέτοιο τρόπο ώστε να εκφράζουν την παραγωγικότητα της κάθε µιας εγκατάστασης (αποθήκη, κέντρο διανοµής). Ο προτεινόµενος αλγόριθµος αναπροσαρµόζει την σχεδίαση του δικτύου ανάλογα µε τις εισροές και εκροές για τον καθορισµό της παραγωγικότητας κάθε εγκατάστασης. Ως µέτρο για την επιλογή της κάθε µιας εγκατάστασης επιλέγεται να είναι η τεχνική αποδοτικότητα (ΤΕ), για τον λόγο ότι λαµβάνει τιµές στο διάστηµα [0, 100]%. Έτσι µια εγκατάσταση επιλέγεται αν είναι πλήρως αποδοτική (ισχύει δηλαδή ότι TE=100%) και µε αυτό τον τρόπο µειώνεται το κόστος κεφαλαίου, το σταθερό κόστος µεταφοράς ενώ το κριτήριο τερµατισµού ταυ

προτεινόµενου αλγόριθµου ορίζεται να είναι το 2IN OUT+ όπου ΙΝ, OUT είναι το πλήθος των εισροών και εκροών αντίστοιχα. Τέλος παρατίθεται η λύση ενός προβλήµατος σχεδίασης όπου µε την εφαρµογή της µεθόδου προκύπτει σηµαντική µείωση τόσο του κόστους κεφαλαίου όσο και του συνολικού κόστους λειτουργίας της εφοδιαστικής αλυσίδας.


42

Μεθοδολογία Πολυκριτηριακής Ανάλυσης σε Συνδυασμό με Υπολογιστικά Μοντέλα για Αξιοποίηση Ανανεώσιμων

Πηγών Ενέργειας σε Περιφερειακό Επίπεδο Ιωάννης Κ. Μουρμούρης

Τμήμα Διεθνών Οικονομικών Σχέσεων και Ανάπτυξης

Δημοκρίτειο Πανεπιστήμιο Θράκης [email protected]

Κων/νος Δ. Ποτόλιας Τμήμα Διεθνών Οικονομικών Σχέσεων και

Ανάπτυξης Δημοκρίτειο Πανεπιστήμιο Θράκης

[email protected]

ΠΕΡΙΛΗΨΗ Οι Ανανεώσιµες Πηγές Ενέργειας (ΑΠΕ) αποτελούν πηγές ενέργειας φιλικές προς το περιβάλλον και συνιστούν ειδικότερη έκφανση αλλά και βασική συνιστώσα ανάπτυξης.

Η παρούσα εργασία εστιάζει το ενδιαφέρον της στην παρουσίαση µεθοδολογίας αξιολόγησης εναλλακτικών σεναρίων αξιοποίησης ΑΠΕ σε περιοχή, µε χρήση µεθόδων πολυκριτήριας ανάλυσης σε συνδυασµό µε υπολογιστικά µοντέλα. Ο σκοπός της εργασίας είναι η ενίσχυση της δυνατότητας εκτίµησης της βέλτιστης επιλογής αξιοποίησης ΑΠΕ συνδυάζοντας µεθοδολογίες που περιλαµβάνουν υποκειµενική προτίµηση µε υπολογιστικά µοντέλα αξιολόγησης ΑΠΕ.

Η διαδικασία λήψης απόφασης σχετικά µε την αξιοποίηση ανανεώσιµων πηγών ενέργειας για συµβολή στον εθνικό ενεργειακό εφοδιασµό είναι πολυδιάστατη, δοµηµένη σε διάφορες πτυχές και επίπεδα – οικονοµικά, περιβαλλοντικά, τεχνικά και κοινωνικά. Κατά συνέπεια η επίτευξη «σαφών» λύσεων είναι δύσκολη. Η δυσκολία αυτή οδηγεί στην ανάγκη ανάπτυξης, εργαλείων και µεθοδολογιών για το σχεδιασµό πολιτικών αξιολόγησης και αξιοποίησης των ανανεώσιµων πηγών ενέργειας για παραγωγή ηλεκτρικής ενέργειας ειδικότερα σε περιφερειακό επίπεδο.

Η ραγδαία εξέλιξη στην υιοθέτηση πολιτικών αξιοποίησης των ΑΠΕ τα τελευταία χρόνια οδηγεί συχνά σε λανθασµένες επιλογές και αποτελέσµατα λόγω των σύνθετων και λάθος καθορισµένων προβληµάτων ενός συνόλου σχέσεων µεταξύ των διάφορων εναλλακτικών λύσεων.

Οι εναλλακτικές λύσεις (σενάρια) χρησιµοποιούνται για να αξιολογήσουν επιπτώσεις και να προβλέψουν µελλοντική εξέλιξη και αντίκτυπο διαφορετικών ενεργειακών µιγµάτων και τεχνολογίας στον τύπο και την ένταση αυτών των επιπτώσεων.

Ο κύριος στόχος των µεθοδολογιών πολυκριτήριας ανάλυσης (MCDA) είναι η ενίσχυση απόφασης κριτηρίων µε σκοπό να δηµιουργηθεί ένα εργαλείο υποστήριξης για τους ιθύνοντες που προσαρµόζεται στους στόχους και τις προτεραιότητές τους (µια εποικοδοµητική ή δηµιουργική προσέγγιση).

Στην παρούσα εργασία αναπτύσσεται µεθοδολογία που στηρίζεται στην πολυκριτήρια ανάλυση µε σκοπό την, µέγιστη αξιοποίηση των ΑΠΕ που διαθέτει περιοχή. Η νέα πρόταση που εισάγει εστιάζεται στο συνδυασµό της πολυκριτήριας ανάλυσης για λήψη αποφάσεων πολλαπλών κριτηρίων µε υπολογιστικά εργαλεία αξιολόγησης- αξιοποίησης ΑΠΕ.

Τα υπολογιστικά εργαλεία ανάπτυξης ΑΠΕ δίνουν περιορισµένη δυνατότητα διαµόρφωσης ενεργειακής σχεδίασης που δεν µπορεί να ικανοποιήσει την πολυδιαστατικότητα και πολυπλοκότητα των κοινωνικοοικονοµικών και περιβαλλοντικών ζητηµάτων.

Η ανάλυση MCDA δίνει αποδοτικότερη και περισσότερο ικανοποιητική λύση στον ενεργειακό σχεδιασµό. Ο συνδυασµός των ανωτέρω δύο µεθοδολογιών σκοπό έχει την πληρέστερη προσέγγιση στο ζήτηµα της αξιοποίησης των ΑΠΕ σε περιφερειακό επίπεδο.


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Using Preference Disaggregation to Measure Quality of Life: A Survey Based Approach

Grigoroudis E. Technical University of Crete

Department of Production Engineering and Management University Campus, 73100 Chania, Greece

[email protected]

Zopounidis C. Technical University of Crete

Department of Production Engineering and Management University Campus, 73100 Chania, Greece

[email protected]

ABSTRACT The main aim of the paper is to measure QOL and analyze citizens satisfaction according to a set of major factors that affect wellbeing perceptions. Based on an extensive literature review and a qualitative preliminary survey, these QOL performance dimensions include: (a) Cost of living and employment opportunities, (b) safety, (c) public infrastructures (roads, parking, parks and green areas, etc.), (d) pollution and cleanliness, (e) public transportation, (f) services and infrastructures for education, health, and social care provision, (g) immigration services, and (h) culture and entertainment. A total of 20 QOL criteria have been considered in the questionnaire, which also includes the overall satisfaction of citizens from their place of living and their perception about the change in the QOL level during the last two years. All these factors and performance criteria have been evaluated using a predefined ordinal scale. The citizen satisfaction survey took place in two major cities of Crete (Greece) during May 2011. The survey was conducted through telephone interviews, while a random sampling procedure was applied. Final input data consist of 461 questionnaires from both cities. The analysis of the collected data is based on the MUSA (MUlticriteria Satisfaction Analysis) method, which is a preference disaggregation analysis technique. The results show

that the overall QOL performance is rather low in both cities, since the overall average satisfaction indices vary from 38% to 40%, although there are several satisfaction criteria with higher performance. These results are justified by the current Greek debt crisis and the relatively high importance estimated for economic-related criteria. However, it should be noted that citizens’ satisfaction from their place of living is also affected by their expectations. Thus, lower (higher) expectations may lead to higher (lower) satisfaction, without having a change in the real QOL level. For this reason, the results of the MUSA method have been compared with other non-survey based sustainability indicators. The necessity of establishing a permanent QOL barometer is justified by the dynamic nature of citizens’ satisfaction. In such case, local government and municipal authorities will have the ability to monitor QOL performance, perform a benchmarking analysis, and evaluate development plans. Moreover, a QOL barometer may help policymakers to adopt a continuous improvement philosophy.

Keywords Qualityoflife, MUSAmethod, Citizen satisfaction, Preference disaggregation.


44

A Multicriteria Methodology for Non-Technical Skills Assessment of Pilots at Military Aviation

Krassadaki E. Technical University of Crete


Decision Support Systems Laboratory University Campus, 73100, Chania,

Crete [email protected]

Tsifetakis Ε. Technical University of Crete




Matsatsinis Ν. Technical University of Crete




ABSTRACT The assessment of experienced pilots especially in military aviation refers to both Technical and Non-Technical Skills. Technical Skills refer to the technique of flying the aircraft and the use of avionics and weapons. Non-Technical Skills cover the social and cognitive side of the pilot. These are the attitudes and behaviors not directly related to aircraft control, systems control and standard operating procedures (SOPs), which can explain why someone is better than another, why someone is considered to be the best, and why someone is more capable than others at an extreme demanding environment. However, after one hour of flight, during the debriefing process, the assessment of both Technical and Non-Technical Skills of pilots may result on subjective decisions depending on the mission commander. The main reason for this problem is that there are no guidelines for the assessment of Non-Technical Skills, as opposed to Technical Skills, where technical manuals, protocols and standard operating procedures can be used. Although Technical and Non-Technical Skills are interconnected and should be assessed in parallel, we propose a methodology for Non-Technical skills, which can be part of an overall assessment process. Therefore, the aim of this paper is the structuring of a specific assessment procedure for

Non-Technical Skills by building a multi-criteria value system, which is as consistent as possible with the judgmental policy of a decision maker (commander of a mission-evaluator). The proposed methodology is illustrated by a real-world data set consisting of 15 pilots of a combat squadron. Seven criteria (leadership, situation awareness, tactical skills, planning skills, communication skills, decision making skill, team-working skill) are taken into consideration, which are analysed in a set of sub-criteria. A combination of the Analytic Hierarchy Process (AHP) and the UTASTAR multicriteria method is utilized. Using extrapolation techniques, a final ranking of all pilots can be achieved, while the use of the proposed methodology in combination with Technical Skills assessment can be a powerful tool for an overall assessment procedure at a specific time period. In this sense, the systematic use of the methodology (or the overall assessment procedure) can reveal the progress of each pilot and furthermore the uniform assessment procedure ensures for the validity of the results.

Keywords Assessment, non-technical skills of pilots, generic skills, military aviation, multicriteria analysis, AHP, UTASTAR.


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Measuring Health Status Using Quality-of-life Instruments: A Multicriteria Approach

Manolitzas P. Decision Support Systems Laboratory

Technical University of Crete Chania, Greece,

Grigoroudis E. Decision Support Systems Laboratory

Technical University of Crete Chania, Greece

Krasoudakis A. General Hospital of Chania

Chania, Greece

Archontakis G. General Hospital of Chania

Chania, Greece

Matsatsinis N. Decision Support Systems Laboratory


ABSTRACT The main aim of this paper is to develop a new approach for analyzing EQ-5D data based on the principles of multicriteria analysis. A data set of 73 patients after lumbar discectomy has been used in order to illustrate the applicability of the model. The proposed approach is an ordinal regression model for measuring and analyzing EQ-5D data. The main objective of the method is the aggregation of individual judgments into a collective value function. The proposed approach provides a series of normalized average indices for each one of the dimensions of the EQ-5D instrument, as well as a set of perceptual maps. These results include: average satisfaction, demanding, and improvement indices, as well as action and improvement diagrams. The analysis of the sample revealed a relatively high satisfaction level (84.65%) for the general health status (VAS). Furthermore, the analysis of the EQ-5D questions shows that patients are very satisfied regarding the dimensions of self-care (95.67%) and

pain/discomfort (95.63%). On the other hand, the lowest health status score refers to the dimension of mobility (78.24%). The weights of these five dimensions are additional results of the proposed method. Based on this particular sample, the results show that the most important factor is the anxiety/depression (32.11%), following by the dimensions of mobility (21.23%) and usual activities (19.16%). Combing these results, the action diagram reveals a gap regarding the perceptions of these particular patients and proposes mobility and anxiety/depression as critical health status dimensions. The main advantage of the method is the ability to consider the qualitative (ordinal) nature of the input information. In addition, the provided results are rich enough to give a clearer view about the patient’s health status.

Keywords Multicriteria analysis, satisfaction, EQ5D, quality of life.


46

A Multicriteria Comparative Analysis of Cloud Computing Services from the User Perspective

Jason Papathanasiou Department of Marketing and

Operations Management University of Macedonia

49 Ag. Dimitriou Str. Edessa, 58200, Greece

[email protected]

Vassilis Kostoglou Department of Informatics,

Alexander Technological Educational Institute of Thessaloniki

P.O. Box 141 Thessaloniki, 57400, Greece

[email protected]

Dimitris Petkos Department of Informatics,

Alexander Technological Educational Institute of Thessaloniki,

P.O. Box 141 Thessaloniki, 57400, Greece

[email protected]

ABSTRACT Cloud computing is changing rapidly the way users perceive the use of computer functions and resources as well as business models. A lot of new issues emerged by this ongoing trend, especially by privacy advocates as regards to the way cloud services providers control totally the communication and data exchanged between them and the users. The security status of the stored data offers another reason for concern, because as this new model is gaining popularity rapidly, so does the threat level increase. Cloud computing is however generally considered a reliable way to add features to the existing technical capabilities and increase business capacity on the fly without making costly investments in new IT infrastructures. It also encompasses subscription-based or pay-per-use services, but at the same time offers an extensive variety of free services as well. Currently, there is a wide range of cloud computing services providers available in the IT market. This paper focuses on the users’ perspectives towards the 11 most popular free services providers, chosen after a thorough literature review. A questionnaire survey

was conducted among the research and teaching staff of the Departments of Information Technology and Automation of the Alexander Institute of Technology, who are specialised users on the topic, in order to determine their provider selection criteria and the relationships among these criteria. Goal programming techniques and the Simos method asserted the weighs of the selected criteria in order to implement the PROMETHEE multi-criteria methodology. Expected results will provide an opportunity to gain insights on users’ demands and expectations and evaluate the level of trust towards these new services. In addition, the usefulness and applicability of cloud computing in the modern educational procedure will also be evaluated.

Keywords Multicriteria decision making, cloud computing, PROMETHEE, user perspective, goal programming.


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A Methodology for the Assessment of Online Courses through Weighted Sum Model

Petasakis Ioannis Department of Accountancy


Ag. Loukas, 65404, Greece

[email protected]

Theodosiou Theodosios

Department of Accountancy Kavala Institute of

Technology Ag. Loukas, 65404, Greece

[email protected]

Kazanidis Ioannis Department of Accountancy



[email protected]

Valsamidis Stavros Department of Accountancy



[email protected]

ABSTRACT E-learning courses evaluation is an ongoing topic of research and it involves the use of several criteria. The Multicretiria Decision Analysis (MCDA) method Weighted Sum Model (WSM) is applied in this paper in order to evaluate online courses uploaded in the Learning Management System (LMS) of the Accountancy Department of Kavala Institute of Technology. Four criteria are used in the analysis, namely, TAM, Quality, Quantity and Utilization of e-learning platform utilities. The results indicate that the TAM criterion is considered as the most important one, whereas the utilization of the least one. Furthermore, the ranking of a sample of ten LMS courses based on the four criteria facilitates the tutors to indicate possible weaknesses of their courses and improve their on-line material.

Keywords Online courses assessment , TAM, Weighted Sum Model.

1. INTRODUCTION E-learning is the delivery and management of teaching, training and learning by electronic means [1]. According to [2] e-learning describes the ability to electronically transfer, manage, support, and supervise learning and learning materials. E-learning systems, such as Learning Management System (LMS) are used in both training and education, resulted in their adoption by academia as well as industry. The fact that there is not physical contact between the educator and the learner is an obstacle to the quality and the quantity of the information which is usually provided to the educators about learners' progress. They do not track and assess all the activities performed by learners and they do not fully evaluate the effectiveness of the learning process.

In any information system, the attitudes of the users toward the system are pivotal and should be regarded thoroughly. This is evidenced by the fact that user satisfaction is often seen as a key antecedent to predict the success of a particular information system [3]. However, e-learners is a special group of users, who hold a unique view regarding satisfaction [4]. This means that traditional information system measures for assessing user satisfaction and for assessing learner satisfaction in the context of classroom teachings are not generally suitable for e-learning.

Study on e-learning evaluation is an ongoing topic of research. The paper written by [5] might be regarded among the complete approaches for evaluating e-learning. A case of e-learning evaluation was reported by [6]. In this paper, they present a systematic qualitative approach to consistently evaluating quality of software or web applications by actual users in real con-texts of use. Many researchers use Technology Acceptance Model (TAM) [7] for assessing LMSs and their courses [8, 9, 10, 11]. This kind of evaluation may indicate potential problems on their usage and help authors and developers to improve them.

On the other hand, multi-criteria analysis has been an active area of research since the 1970s [12]. There are many multi-criteria methods but the weighted sum model (WSM) is the best known and simplest [13].

The purpose of this paper is to propose a step-based, multi-criteria methodology from the perspective of e-learner satisfaction in order to support the evaluation of online courses. Questionnaires are used for course evaluation. These were properly designed according to TAM factors (perceived usefulness and perceived ease of use), quality, quantity and utilization of LMS features, and completed by students.

The rest of the paper is organized as follows. Section 2 describes the approach used. Results of the experimental evaluation are reported in Section 3. Section 4 presents discussion about the approach and the results. We also draw some conclusions together with directions in the future.

2. METHODOLOGY The proposed methodology involves the use of the multicriteria decision analysis (MCDA) method called Weighted Sum Model (WSM) in order to rank the courses of the Accountancy Department of Kavala Institute of Technology (DAKIT) based on their e-class content and usage. The WSM is a simple multicriteria method for evaluating a number of alternatives in terms of a number of criteria [14]. Let n denote the number of courses (alternatives) and m the number of decision criteria then WSM is formally written as

∑=

− =m

jijj

scoreWSMi wA

1α (1)


48

for ni ,,1…= . jw denotes the relative weight of importance of

the criterion jC and ija is the performance value of course

(alternative) iA when it is evaluated in terms of criterion jC . In

our case the number of criteria is four ( 4=m ), namely Technology Acceptance Model (TAM) factors, quality of educational content, quantity of online material and utilization of e-learning platform utilities.

TAM was developed in order to explain the acceptance of information systems, as well as to predict he value of related factors to the spread of these systems [7]. According to the TAM, there are two determinants of new technology acceptance: perceived usefulness, and perceived ease of use. As far as quality and quantity of educational content is concerned, both are important factors for a successful learning experience. If course quality is not adequate, learners have problems in understanding the course domain. On the other hand, problems in learning may arise in cases where content quantity is either too low or more than it should be for a specific type of learner. Utilization refers to the various tools of the LMS platform that are being used by the course, i.e. forums, quizzes, wikis, etc. The performance of each course is evaluated based on these four criteria calculated from their content on the LMS Open eClass [15]. It must be noted that the higher the values of the criteria the better they are.

The proposed approach can be distinguished in two distinct phases (Figure 1). In the first phase the weights ( jw ) for each of the four criteria are being calculated. A questionnaire was distributed to a sample of 87 students of the DAKIT in order to score each of the four criteria between 1 and 10, according to how important they consider it for the electronic material of the

courses. The weight for each criterion is the ratio of each ones

mean score divided by the sum of all four means scores. The four criteria used in our analysis have already been used successfully in [16] in order to evaluate the use of e-learning material for organization employees. In this study, the students were asked to fill a questionnaire with the same structure as the one depicted in figure 2 but with slightly different questions e.g “how important factor do you think that the usefulness of an online course is?” The proposed marking was in the scale from 1 to 10.

In the second phase the courses are ranked based on the WSM and the weights produced from phase one. The WSM is applied in ten different courses. The performance value ( ija ) for each criterion is calculated using another questionnaire consisting of eighteen questions. Six questions are refereeing to the TAM criterion, another six to the Quality, three to the Quantity and another three to the Utilization criterion (Figure 2). 266 students replied to each questions with a score of 1 to 5 (Likert scale, 1=strongly disagree and 5=strongly agree). Based on [17] the performance value ( ija ) is calculated as the mean of these scores for each course using for each criterion the relevant questions.

3. RESULTS The results of the first phase of our approach are based on a sample of 87 students and are used in order to calculate the weights for each criterion. Using the WSM and the weights from phase I, 10 courses of the Department of Accountancy that have e-learning material were ranked.

3.1 Phase I The weights calculated at Phase I for each one of the criteria are shown in Table 1. The TAM criterion has the largest weight,

while the utilization of the e-learning platform utilities is

Note: Cj denotes criterion j and wj denotes weight of criterion j. Ai denotes WSM score of course i, aij denotes the performance score of

Ai under criterion Cj.

Figure 1. Proposed approach diagram

Figure 2. The hierarchy structure for evaluating online courses


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considered by the students of our sample as the least important. Nevertheless, it must be noted the differences in the weights of the criteria our small.

Table 1. Criteria’s weights

Criterion Mean score Weight

TAM 9.105 0.27

Quality of educational content 8.865 0.26

Quantity of online material 7.970 0.24

Utilization of e-learning platform utilities 7.725 0.23

3.2 Phase II The number of students who completed the phase II questionnaire ranged from thirteen to fifty depending on the course. Table 2 presents for each course the calculated performance score of the four criteria, namely the TAM, Quality of educational content, Quantity of online material and Utilization of e-learning platform utilities.

In order to rank the courses we use the WSM method multiplying the performance score with the corresponding weight from phase I, separately for each one of the courses. As a result we produce the ranking score for each course (Table 3). This ranking score can range between one and five, where one means that the electronic material of the corresponding course was not important and five means that it was very important according to students’ perceptions.

Table 2. Performance values per course

Courses Frequency TAM Quality Quantity Utilization AD2103 49 3.89 3.24 3.62 3.42

AD6102 30 3.89 3.40 3.66 3.60

AD6100 16 3.87 3.38 3.72 3.57

AD6107 19 3.88 3.37 3.67 3.48

AD6108 35 3.88 3.67 3.75 3.64

AD2105 50 4.03 3.46 3.77 3.64

AD5106 13 3.77 2.90 3.39 3.26

AD1101 19 3.67 3.26 3.49 3.39

AD3108 14 3.76 3.35 3.45 3.30

AD2107 21 3.73 3.79 3.92 3.84

Table 3. Ranking score

Course Ranking score

AD6108 3.738

AD2105 3.733

AD6102 3.645

AD6100 3.641

AD3108 3.637

AD6107 3.607

AD2107 3.593

AD2103 3,553

AD1101 3.473

AD5106 3.341

4. CONCLUSIONS - DISCUSSION Multicriteria decision analysis can support decision making process and can be applied successfully in many domains. This paper presents the application of MCDA to an e-learning system in order to evaluate the e-learning material and their use by the students of the DAKIT. This evaluation can help tutors adjust accordingly their on-line material. Furthermore, can help them pinpoint the most important criteria based on the students opinion for evaluating the e-learning platform.

The evaluation is based on four criteria, namely the TAM, Quality, Quantity and Utilization of the e-learning platform utilities. The TAM criterion combines the perceived usefulness and the perceived ease of use of the platform in one criterion and is considered by the students as the most important one. On the other hand utilization has the least weight, meaning that the students consider the use of the relevant utilities, such wikis, forums, etc. by the platform to be not that much important.

The ranking of the 10 courses based on the WSM model show that the course AD6108 which is a laboratory course is considered to have the most complete on-line presence based on the four criteria. The performance scores for the four criteria are among the highest ones. The second most important course AD2105 has a ranking score very close to the first one. The next three courses have quite similar scores. It is noteworthy that the course AD6107 which is the theory of AD6108 is the sixth course in the ranking, whereas the laboratory (AD6108) on-line material are as already mentioned number one in the ranking list. The last in the ranking course is AD5106 and has low performance scores for the Quality and Utilization criteria.

Two important limitations are worth bearing in mind when interpreting the current findings. Firstly, was the sample size which was from a specific Institute of Technology in Greece and secondly the number of the examined online courses was relatively small. Since the students’ characteristics may differ from other universities, the results of this study cannot be generalized beyond the education program at the specific university department.

Future research needs to address and illuminate the following questions (a) how a high ranked online course may improve students’ performance and (b) how this ranking results could enhance an e-learning platform with the ability to provide suggestions on course improvements to the authors. A suggestion


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algorithm could be implemented which after analyzing the course ranking in each of the four criteria, would provide useful suggestions, from a pool database, that help authors to improve their online educational material and consequently students in their study.

5. REFERENCES [1] Wentling, T., Waight, C., Gallaber, J., Fleur, J., Wang, C.,

and Kanfer, A. 2000. E-learning--a review of literature (Report No. ED-RR-89-3). Urbana-Champaign, Il: Knowledge and Learning Systems Group. (ERIC Document Reproduction Service No. ED450394).

[2] Normark, O. R. and Cetindamar, D. 2005. E-learning in a competitive firm setting. Innovations in Education & Teaching International, 42, 4, 325-335.

[3] DeLone, W.H. and McLean, E.R. 2003. The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19, 4, 9–30.

[4] Wang, Y.-S. 2003. Assessment of learner satisfaction with asynchronous electronic learning systems. Information and Management, 41, 1, 75–86.

[5] Valsamidis, S., Kontogiannis, S., Kazanidis, I., and Karakos, A. 2011., "E-Learning Platform Usage Analysis“, Interdisciplinary Journal of E-Learning and Learning Objects (IJELLO), 7, 185-204.

[6] Covella, G., and Olsina, L. 2006. Assessing quality in use in a consistent way. Proceedings of the 6th International Conference on Web Engineering, ICWE'06, Palo Alto, California, USA, 1-8.

[7] Davis, F.D. 1989. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13, 3, 319–340.

[8] Abdalla, I. 2007. Evaluating effectiveness of e-blackboard system using TAM framework: A structural analysis approach. AACE Journal, 15, 3, 279-287.

[9] Martin, L., Martínez, D.R., Revilla, O., Aguilar, M. J., Santos, O.C. and Boticario, JG. 2008. Usability in e-Learning Platforms: Heuristics Comparison between Moodle, Sakai and dotLRN. Available from: http://www.oerafrica.org/ResourceDownload.aspx?id=36662&userid=-1 [Accessed 20 June 2012].

[10] Alsabawy, A. Y., Cater-Steel, A. & Soar, J. 2011. Measuring E-Learning System Success (Research In Progress). Proc. Of PACIS, Available from: http://aisel.aisnet.org/pacis2011/15 [Accessed 10 June, 2012].

[11] Kazanidis, I. and Satratzemi, M. 2011. Restrictions and abilities of SCORM: a path to adaptive course development. In A. Jimoyiannis, (ed.), Research on e-Learning and ICT in Education, 295-308, Springer.

[12] Köksalan, M., Wallenius, J., and Zionts, S. 2011. Multiple Criteria Decision Making: From Early History to the 21st Century. Singapore: World Scientific.

[13] Triantaphyllou, E. 2000. Multi-Criteria Decision Making: A Comparative Study. Dordrecht, The Netherlands: Kluwer Academic Publishers. ISBN 0-7923-6607-7. http://www.csc.lsu.edu/trianta/Books/DecisionMaking1/Book1.htm. [Accessed 20 July, 2012].

[14] Fishburn, P.C. 1967. Additive Utilities with Incomplete Product Set: Applications to Priorities and Assignments. Operations Research Society of America (ORSA), Baltimore, MD, U.S.A.

[15] GUNet. 2012. Open Eclass. http://www.openeclass.org/. [Accessed 20 August, 2012].

[16] Kazanidis, I., Petasakis, I., Valsamidis, S., and Karakos, A. LMS Contribution to a Better Business Education, 3rd International Conference EBEEC 2011, “The Economies of Balkan and Eastern Europe Countries in the Changed world”, May 5-8, 2011, Pitesti, Romania

[17] Knapp TR. (1990). Treating ordinal scales as interval scales: an attempt to resolve the controversy. Nursing Research 1990;39:121–3.


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Evaluation of Heating Systems in Greece using RetScreen Software tool and Multi-Criteria Analysis

Pantelis Antoniadis Dept. of Electrical Engineering,

Kavala Institute of Technology, 65404 Agios Loucas Greece

+30 2510 462276

[email protected]

Jacob G. Fantidis Dept. of Electrical Engineering


+30 2510 462315

[email protected]

Nikolaos Vordos Dept. of Electrical Engineering


+30 2510 462 247

[email protected]

ABSTRACT Financial crisis in Greece brought new taxes in the Greek citizens and in the fossil heating fuels and have changed the data on the field of the heating cost. The significantly increased prices for oil over the last few years motivate many building owners with oil heating systems to convert their heating systems. However, this problem is multidimensional in nature, requiring an integrated approach to problem solving which takes into account, economic, social, environmental, and other aspects. In order to face this complex problem a suitable multi-criteria decision analysis system was used.

The originality of the present study is that the evaluation of house heating systems based not only on techno-economical criteria, which derived from a RetScreen software tool, but also on environmental and social criteria using Multi-Criteria Analysis for their evaluation. Natural gas, heat pumps, pellet and wood was used as alternatives to heating diesel oil. Four cities namely Rhodes, Athens, Kavala, and Kozani, used as representative samples from each of the four climatic zones in which can be divided the Greece, are considered.

Keywords MCDA, RetScreen, Heating systems, Greece.

1. INTRODUCTION In Greece there are a large number of small heating units operating with heating diesel. However the acute financial crisis has brought new taxes in the heating diesel. Greek consumers are seeking out alternative ways of heating their homes as, at 1.30 to 1.40 € per liter, the price of heating oil has become prohibitive for many following the increase of the special consumption tax to 80 percent of that on diesel. The objectives of this work are to evaluate the alternative method of heating in different areas in Greece.

The evaluation of the house heating systems is a complex issue. The aim of this paper is the analysis and development of a multilevel decision-making structure, utilising multiple criteria with intention to find the most efficient and satisfactory solution. For this reason we used multi-criteria decision analysis (MCDA) techniques based on the REGIME method. The economic analysis and the environmental considerations calculated using the RETScreen software [1-3].

2. MULTI-CRITERIA ANALYSIS Multi-Criteria Analysis (MCA) is a decision-making tool developed for complex problems with numerous practical applications in a wide range of fields such as mathematics, economics, computer technology, software engineering, and information systems. A full application of MCA normally involves eight steps

1. Problem identification and initial data collection 2. Institutional analysis and stakeholder identification 3. Creation of alternatives 4. Establishing evaluation criteria 5. Criteria evaluation and preference elicitation 6. Selection of the MCDA technique 7. Model application 8. Stakeholder analysis of the results and feedback

There are several methods that might be applied to heating evaluation, the most suitable are: (i) Analytic Hierarchy Process, (ii) Analytic Network Process, (iii) REGIME, (iv) ELECTRE family, (v) Multi Attribute Utility approach, (vi) ADAM type. In this work, the Regime Method has been chosen to evaluate different heating systems in Greece [4].

2.1 Regime Analysis Regime Analysis is a discrete multi-assessment method with main advantage that it is capable of working with mixed data (ordinal, scale, ratios and categorical data). The fundamental framework of this method is based on two parts: the input matrix and a set of weights. Evaluation is applied on both the criteria and their corresponding weights or priority values as it was suggested by Nijkamp et al. [5].

Regime is a concordance method. Pair wise comparison between the set of alternatives according to each criterion are carried out. For each pair of alternatives i and k, the criteria are selected, for which alternative i is better or equal to alternative j. We call the set of these the criteria concordance set. The criteria in accordance with which an alternative j is worse or equal to alternative i is called the discordance set. Then, the alternatives i and j are ranked by means of the concordance index Cij, that is, the sum of the weights attached to the criteria according to which alternative i is better or equal to alternative j. Then the concordance index Cji is calculated, which is obtained by summing up the weights of the criteria according to which alternative j is better or equal to alternative i.

In the end, the net concordance index is calculated subtracting Cji from Cij (ìij = Cij−Cji), which is positive if alternative i is preferred


52

to alternative j. It must be noted that, since in most cases only ordinal information is available on the weights, but not trade−offs the net concordance index only indicates whether an alternative is preferred to another, but not by how much. Since sometimes it is not possible to obtain a complete ranking of the alternatives using only ìij’s sign, a performance indicator pij is formulated for the criterion i with respect to the criterion j, which indicates the probability that an alternative is preferred to another one, that is, that the net concordance index is positive: pij=prob (ìij>0). Using the performance indicator, an aggregate probability index can be defined, which indicates the performance score: Next, we define an aggregate probability measure, which represents the performance score:

11i ijj i

p pI ≠

=− ∑ (1)

where i is the number of chosen alternatives. pij and of pi are estimated using a specific probability distribution of the set of feasible weights. Regime is a relatively easy method to use, provided that one can have access to user−friendly software [6].

3. RETSCREEN SOFTWARE The RetScreen Clean Energy Project Analysis Software is an advanced mathematical model to evaluate the energy production and savings costs, emission reductions, financial viability and risk for various types of Renewable-energy and Energy-efficient Technologies. The RetScreen makes use of heating degree-days (DD) to calculate the building (or buildings) heating requirements. Heating degree-days are defined as the difference between a set temperature (in Greece 18°C) and the average daily temperature and described by the equation:

( ),1

iN

i set a kk

DD T T=

= −∑ (2)

where DDi is the monthly degree-days for month i, Ni is the number of days in month i, Tset is the set temperature, and Ta,k is the average daily temperature for day k of month i. The model calculates also the equivalent DD for domestic hot water heating as a percentage (d) of the total heating needs (DDDHW) using the following equation:

( )1DHWdDD DDd

=−

(3)

According to the RETScreen manual the hot water demand is supposed steady throughout the year and is expressed by the user as a fraction d of the annual total demand [7-8].

4. DESCRIPTION OF EVALUATION CRITERIA The input matrix in the present study is composed by the indicators selected in order to evaluate the different systems. In this case, the multi-criteria analysis is based on the assumption that input matrix are composed by four main criteria:

A. Economic criteria B. Environmental criteria C. Technical - technological criteria D. Others criteria

These criteria include both qualitative and quantitative measures and the objective of maximization or minimization depends on the

particular criterion. Each one of these groups refers to a type of attributes that plays a relevant role in the selection of the best heating system. Twelve sub-criteria have been defined on the bases of the main macro-group that have been exposed:

A. Economic criteria A1. Investment cost A2. Operation cost

B. Environmental criteria B1. Land consumption B2. Atmospheric pollution B3. Impact on flora/fauna

C. Technical - technological criteria C1. Lifespan of the system C2. Availability-Fuel Distribution C3. Automatic feeding fuel C4. Cleaning requirements C5. Maintenance requirements

D. Others criteria D1. Security of supply D2. Safety

5. CASE STUDY (GREECE) The financial crisis in Greece has brought new taxes in the Greek citizens. In accordance with the data from the Hellenic Minister of development [9], on 2009 the heating diesel price in Greece was around 0.56 €/L, on April 2012 the price was approximately 1.05 €/L. However, with the increase of the special consumption tax to 80 percent of that on diesel the new price will be 1.30 to 1.40 €/L. For these reasons many building owners search for alternatives to heating diesel. Heating systems based on natural gas, pellet, wood and heat pumps was evaluated.

The climate of Greece is primarily Mediterranean with average annual temperature ranges from +10 to +19.7 °C, however, due to the country's unique geography, Greece has a significant range of micro-climates and considerable local variations. According to the Greek statute for the building energy performance the Greece can be divided in 4 climatic zones which is related to the annual heating DD [10]. In the zone A the annual DD are between 450 – 1000. During the summer, the weather is almost always sunny and dry, winters are wet and the snowfalls occur rarely if ever. The zone B has similar climate with hot dry summers, winters are mild and wet, and any snow that falls does not last too long. The typical range of values for yearly DD is 1000 – 1500. In the climatic zone C the climate is wetter than the zone B and has cooler winters and not so hot summers. There are more snowfalls and the annual DD range from 1500 up to 2000. In the zone D the winter is harsh with abundant snowfalls, while the summers are cool with frequent thunderstorms, the annual DD are more than 2000.

In the present study four cities (Kavala, Athens, Rhodes, and Kozani), representative samples from each climatic zone, are considered (Fig. 1). Technical and financial information of the systems are shown in Table 1. The performance from each heating systems is strongly dependent on the climatic conditions and accurate weather data in a targeted location is essential. The required weather data for each of the four cities were obtained from the Hellenic National Meteorological Service [11].

Rhodes, which is located in the first climatic zone, is the largest of the Dodecanese islands in terms of both land area and population. The city of Rhodes had 54000 inhabitants. Athens is the capital of Greece, with 4 million people population and is positioned in the second climatic zone. Kavala is the second largest city in northern


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Greece with 61000 inhabitants and is positioned in the third climatic zone. Finally, Kozani is a city in northern. Its population is estimated at about 50000. The long-term monthly averaged air temperatures for each of the 4consider cities and the corresponding heating DD values are presented in Fig. 2. The technical and the financial parameters of the investigated systems are listed in Table 1.

Figure 1. Climatic zones in Greece.

Figure 2. Monthly heating degree-days and variation of air temperature for each of the 4 consider cities.

5.1 RETScreen calculation Given the meteorological data at a certain site, the RetScreen calculates the operating cost and the GHG emission reduction. The operating cost for different heating systems for each of the four investigated cities is shown in Fig. 3. In Rhodes there isn't and doesn't expect to obtain a natural gas distribution network and for this reason we leave out this scenario. In all circumstances the heating diesel has the higher operating cost and the heat pump has the minimum but with the higher investment cost.

Replacing heating generated by alternatives such as pellet, wood or heat pump could provide further benefits to Greece in the form of reduced emissions of priority air pollutants and Green Houses Gases (GHG). The RetScreen software is capable of estimating the amount of GHG which could be avoided as a result of usage of these alternative methods. The amounts of GHG reduction for the 4 locations are presented in Fig. 4. As expected the highest GHG emissions mitigation of 5.5 tons/year was observed at Kozani and the lowest reduction was observed at Rhodes with a value of 3 tons/year.

5.2 Application of the REGIME multiple criteria evaluation method The present section elaborates on the application of the above methodological framework in the problem at hand. With respect to the fact that alternatives have been already defined, evaluation criteria are considered. The evaluation criteria are shown in Table 2. Based on the alternatives criteria proposed, the impact matrix has been constructed (Table 3-6). The benefit matrix is the main input into the REGIME multiple-criteria evaluation method.

2D Graph 4

Area

Kavala Rhodes Athens Kozani

Year

ly c

ost o

h he

atin

g (€

)

0

500

1000

1500

2000

2500

3000Heating dieselPelletWoodHeat pumpNatural gas

Figure 3. The yearly heating cost for each of the 4 consider cities for the different investigated heating systems

Figure 4. GHG reduction due to usage of alternatives fuels.

Table 1. Technical and financial information of the investigated systems Parameter Heating Diesel

system Natural gas system

Wood system Pellet system Heat pump system

Initial Costs (€) 1300 1300 1700 2500 6000


54

Fuel price 1.4 €/L (Rhodes) 1.3 €/L (Athens) 1.35 €/L (Kavala) 1.33 €/L (Kozani)

0.08 €/kwh 150 €/t (Rhodes, Athens) 120 €/t (Kavala) 110 €/t (Kozani)

320 €/t (Rhodes) 300 €/t (Athens, Kavala, Kozani)

0.13 €/kwh

Rated Capacity (kW) 12.9 12.9 12.9 12.9 15

Efficiency (%) 90 90 75 85 420

Heated floor area (m2) 90 Heating load for building (w/m2) 90 Domestic hot water heating demand (%) 10

Table 2. Evaluation criteria a/a Criterion Criterion description Measurement scale Criterion direction

Κ1 Investment cost Manifest of all costs, such as purchasing equipment, installations, technician services, and unforeseen work.

Ordinal Cost

Κ2 Operation cost The variable costs include fuel and variable O&M costs for new and previously installed power plants

Ordinal Cost

Κ3 Land consumption Land which used for the operation of heating systems - - - / + + + Benefit Κ4 Atmospheric pollution CO2 mitigation potential Ratio Benefit

Κ5 Impact on flora/fauna Impacts related to heating system operation - - - / + + + Cost

Κ6 Lifespan of the system The life time of the major components of the system Ordinal Benefit

Κ7 Availability-Fuel Distribution The presence of well-organized distribution network - - - / + + + Cost Κ8 Automatic feeding fuel The presence of automatic feeding fuel mechanism - - - / + + + Benefit

Κ9 Cleaning requirements The frequency of the cleanliness - - - / + + + Benefit

K10 Maintenance requirements The frequency of the necessary maintenance - - - / + + + Benefit

K11 Security of supply Express the import dependency of the fuel Ratio Benefit K12 Safety Public safety Ordinal Benefit

Results obtained by the multi-criteria evaluation are shown in Fig. 5. According to these results, in Rhodes the best heating system based on the use of wood, while in Athens the best solution for heating is the heat pump. In the third and fourth climatic zones in Greece, where placed Kavala and Kozani, the most prominent system is the heat pump system, though, wood and pellet are good alternatives. Last but not least, owing to the new taxes, in all circumstances the heating system which based on diesel is by far the worst heating system in Greece.

6. CONCLUSIONS The dramatically increased prices for heating diesel over the last three years in Greece encourage many house owners with diesel heating system to convert their heating systems. In the present job, a techno-economic evaluation of different heating systems was realized. RetScreen was used for the financial evaluation of the systems for 4 different cities in Greece, which belong in 4 different climatic zones. From this study, it is clear that the heat pump has the minimum operation cost but the maximum investment cost.

Table 3. Impact matrix for Rhodes case. Alternatives Criteria Diesel Wood Pellet Heat pump Κ1 5 4 3 1 Κ2 2 3 3 4 Κ3 -- -- - ++

Κ4 1 4 3 2 Κ5 -- -- + + Κ6 4 3 4 4 Κ7 +++ ++ ++ +++ Κ8 ++ --- - +++ Κ9 + --- -- + K10 ++ + + +++ K11 1 4 3 3 K12 3 3 4 4

In this study, we used a MCDA technique, which is based on the REGIME method, because of the fact that the choice of the

Table 4. Impact matrix for Athens case. Alternatives Criteria

Diesel Natural gas

Wood Pellet Heat pump

Κ1 5 4 4 3 1 Κ2 1 2 3 3 4 Κ3 -- + -- - ++ Κ4 1 2 4 4 3 Κ5 -- + -- + +


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Κ6 4 4 3 4 4 Κ7 +++ ++ + + +++ Κ8 ++ +++ --- - +++ Κ9 + ++ --- -- + K10 ++ + + + +++ K11 1 1 3 3 3 K12 3 2 3 4 4

Table 5. Impact matrix for Kavala case. Alternatives Criteria

Diesel Natural gas


Κ1 5 4 4 3 1 Κ2 1 1 4 3 4 Κ3 -- + -- - ++ Κ4 1 2 4 4 3 Κ5 -- + -- + + Κ6 4 4 3 4 4 Κ7 +++ + +++ ++ +++ Κ8 ++ +++ --- - +++ Κ9 + ++ --- -- + K10 ++ + + + +++ K11 1 1 4 3 3 K12 3 2 3 4 4

Table 6. Impact matrix for Kozani case. Alternatives Criteria

Diesel Natural gas


Κ1 5 4 4 3 1 Κ2 1 1 4 2 4 Κ3 -- + -- - ++ Κ4 1 1 4 3 3 Κ5 -- + -- + + Κ6 4 4 3 4 4 Κ7 +++ - ++ ++ +++ Κ8 ++ +++ --- - +++ Κ9 + ++ --- -- + K10 ++ + + + +++ K11 1 1 4 3 3 K12 3 2 3 4 4

Figure 5. Results by use of the REGIME method.

optimum heating system is complex issue. In such a framework, multi-criteria evaluation has proved to be a useful tool, as such studies need to take into consideration both quantitative and qualitative aspects.

7. REFERENCES [1] Mourmouris, J. C., Potolias, C. and Fantidis, J. G. 2012.

Evaluation of Renewable Energy Sources Exploitation at Remote Regions, using Computing Model and Multi-Criteria Analysis: A Case-Study in Samothrace, Greece, International Journal of Renewable Energy Research 2 (2), 307-316.

[2] Browne, D., Bernadette, O. and Moles R. 2010. Use of multi-criteria decision analysis to explore alternative domestic energy and electricity policy scenarios in an Irish city-region, Energy 35, 518–528.

[3] Ghafghazi, S., Sowlati T., Sokhansanj S. and Melin S. 2010. A multicriteria approach to evaluate district heating system options. Applied Energy 87, 1134–1140.

[4] Beria, P., Maltese, I. and Mariotti, I. 2011. Comparing cost benefit and multi-criteria analysis: the evaluation of neighborhoods' sustainable mobility, Società Italiana degli Economisti dei Trasporti - XIII Riunione Scientifica –Messina 2011.

[5] Nijkamp, P., Rietveld, P. and Voogd, H. 1990. Multicriteria Evaluation in Physical Planning, Elsevier, Amsterdam.

[6] Hinloopen, E., Nijkamp, P. and Rietveld, P. 1983. The regime method: a new multi-criteria technique, in P. Hansen (ed.) Essays and Surveys on Multiple Criteria Decision Making, Springer Verlag, Berlin.

[7] Clean Energy Project Analysis, 2005. RETScreen® Engineering & Cases Textbook, Third Edition, Minister of Natural Resources Canada 2001 - 2005.September 2005.

[8] ASHRAE Handbook “Fundamentals”, 2005. American Society of Heating Refrigeration and Air-Conditioning Engineering, Atlanta, Georgia, Edition 2005.

[9] Hellenic ministry of development (http://www.ypeka.gr). [10] Technical Chamber of Greece, 2010. Climatic data on

Greece, First edition, Τ.Ο.Τ.Ε.Ε. 20701-3/2010. [11] Hellenic National Meteorological Service (www.hnms.gr).


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Evaluating Reorganization Scenarios in an Emergency Department of a Health care Organization Using Multi

criteria Analysis and Simulation Techniques (SIM-UTA) Μanolitzas Panagiotis


Technical University of Crete Kounoupidiana-Chania, 73100

[email protected]

Vlachopoulou Maro Department of Applied Informatics

University of Macedonia Tessaloniki, 54006

[email protected]

Grigoroudis Evangelos Department of Production Engineering

and Management Technical University of Crete

Kounoupidiana-Chania, 73100

[email protected]

Matsatsinis Nikolaos Department of Production Engineering

and Management Technical University of Crete

Kounoupidiana-Chania, 73100

[email protected]

Nikitakis Petros General Hospital of Chania

Emergency Department Mournies- Chania

Postal Code 73300

ABSTRACT The scope of a health organization is to provide high quality services at the lowest possible cost. An important characteristic of the hospital as an organization is its inability to precisely estimate the number of users/patients. This characteristic is common at the emergency department of a health care organization and as a result the hospital managers can not estimate the cost of the department or the optimal number of physicians, nurses, lab technicians etc. The most common problems that an emergency department faces during its operation are the waiting times, the lack of staff and the lack of proper planning procedures for dealing the increased flow of patients. During the last years simulation technologies gave the ability to examine ‘what if’ scenarios in order to reduce the problems that an emergency department faces. In this paper a methodology which combines simulation with multicriteria analysis is developed. The

simulation model has been developed using the Simul8 software in order to represent the current operation of the emergency department. In the next stage the decision maker evaluates alternative scenarios in order to measure the responsiveness of the system. These scenarios take into account alternatives like changes in processes, personnel, as well as their combinations. The evaluation criteria are based on costs, use of services and waiting times. Using the simulation results the decision maker expresses his/her preferences and the UTA method is applied. The combination of simulation and multicriteria analysis can be a valuable tool for managing the processes of an emergency department and improving the quality of the offered services.

Keywords Multicriteria Analysis, Reengineering, Simulation.


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A Comparison Study: E-Banking vs E-Commerce Dimitriadis Efstathios

Kavala Institute of Technology Agios Loukas 65 404, Kavala-Greece


Kaltsidou Despoina Democritus University of Thrace

Komotini - Greece [email protected]

Kaltsidis Theoklitos Cyprus Bank

Kavala- Greece

ABSTRACT

The rapid diffusion of the internet had as result a significant impulse in the development of electronic banking and electronic commerce. Nowadays, about two billion peoples are internet users. However, Greece ranks last among the 25 members of the European Union in terms of its use of the Internet even if 87% of the Greek businesses use the Internet which is close to the EU average of 89%. The results of a research, in a sample of 524 Greek customers, indicate that they still face with prejudice both e-commerce and e-banking.

Keywords E-Banking, E-Commerce, Familiarity, Risk, Trust, Intention to use.

1. INTRODUCTION Among the main applications of the internet are e-banking and e-commerce. Banking industry has gone through important operational differences over the last decades. The rapid spread of the internet, has transformed the delivery channels used by the financial services industry. Worldwide, the number of consumers that use Internet banking (IB) has increased steadily from 360.985.492 users in 2000 to 1.668.870.408 users in 2009, with most users being from Western Europe. The significance of internet in nowadays competitive and progressively worldwide banking environment has been globally acknowledged, and an increasing body of literature now occurs on important characteristics of online banking. Factors that influence consumer’s acceptance and adoption of e-banking have been at the vanguard of academic attention [1], [2], [3], [4], [5]. Internet has become also an essential business platform for trading, distributing and selling products between organizations, among organizations and consumers, and even between customers [6]. For many consumers e-commerce is a familiar mode to shopping and it growths 19% per year [7]. According to recently published research of Observatory for the Society of Information, in 2007 almost 31% of Greek users had made some purchase via Internet in last 12 months, while an additional 5% of users had purchased in the past.

2. LITERATURE REVIEW Many studies have tried to determine the factors that influence the intention to use e-banking and e-commerce. The most important and common factors for both, e- commerce and e-banking, are familiarity, risk and trust. From a functional point of view trust can be seen as a mechanism that reduces the complexity of human conduct in situations of uncertainty [8]. Trust is central to any economic transaction, whether conducted in a retail outlet in the real offline world or over the internet, by means of a web site. However, trust is even more important in an online situation [9], [10, [11], [12]. Crosby et al. [13], approached trust in terms of

customers trust and estimated that trust is the confidence that the customer feels for his/her supplier. Furthermore, Gefen [14] reported that trust could be characterized by previous interactions but the previous behavior of a supplier cannot guarantee that someone will act as he is supposed to. Mayer et al. [15], has divided trust in 3 parts: benevolence, ability and integrity. Risk is the potential that a chosen action or activity (including the choice of inaction) will lead to a loss (an undesirable outcome). The notion implies that a choice having an influence on the outcome exists (or existed). Potential losses themselves may also be called "risks". Almost any human endeavor carries some risk, but some are much more risky than others [16]. Perceived risk receives attention from both practitioners [17] and academics [18] and has been applied in a wide range of areas including banking [19] and apparel catalogue shopping [20]. According to Hoyer and MacInnis [21] there are hypothetical risks that are linked with e-banking. These risks are: Financial risk, Performance risks, Time risk, Social risk, Psychological Risk and Security risk. Alba and Hutchinson [22] define familiarity as ‘‘the number of product related experiences that have been accumulated by the consumer.’’ Consumer familiarity with a product or service is a key component of consumer knowledge [22,], [23]. It is only recently that familiarity (often referred to as user experience) has received attention in the context of Internet and electronic commerce.

3. RESEARCH HYPOTHESES Bauer [24] argues that once a risk has been taken in a purchase situation, there seems to be evidence that subsequent consumer behaviour is shaped by this risk perception. Consumer’s perceived risk could have a negative relationship with their attitudes toward the purchasing behaviour. Recent research has established that risk perception and attitudes are closely related. For example, Ruyter et al. [25] empirically verified that perceived risk has an influence on consumers’ attitudes toward e-service. McKnight et al. [26] stated that trusting intention is likely to be very fragile if the perceived risk is high. Consequently, purchase likelihood tends to be low. Perceived risk can also be regarded as a situational belief about the likelihood of gains and losses [27], [28]. Perceived risk is commonly thought of as an uncertainty regarding possible negative consequences of using a product or service. It has formally been defined as the combination of uncertainty plus seriousness of outcome involved [24]. Therefore, we hypothesize that:

H1: Consumers’ perceived risk is negatively related to consumers’ intention to purchase.

H2: Consumers’ perceived risk is negatively related to the intention to use e-banking. Existing empirical research has revealed that trust is significantly linked to attitude, and attitude positively signifies people’s purchase intention [29], [30]. Gefen and Straub [10] have proved


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that all the dimensions of trust positively affect the purchase intentions. Crespo et al. [31] proved that subjective norm, innovativeness, attitude and perceived trust have a positive effect on purchase intention. Attitude has been proven to influence behavioral intentions and actual behavior [32]. Attitude toward e- banking is defined as an individual’s overall affective reaction to using the internet for his/her banking activities. The closeness of trust and attitude draws on the apprehension of perceived consequences [12]. The trust that user have in the internet enables them to expect reliability and predictability and that no damaging. Therefore, can be formulated the below Hypotheses.

H3: Consumers trust is positively related to the purchase intention

H4: Consumers trust is positively related to the intention to use e-banking.

4. RESEARCH METHODOLOGY 4.1 Sample and Data Collection In order to achieve the objectives of this study a survey was conducted during the months of July and August in 2009. A structured questionnaire was used as research instrument. The target population of our study was the Greek internet users that did not carry out purchases and banking transactions via internet up to the moment of research. The choice of internet users only, is imposed by the nature of the research, because without internet online purchases or banking transactions are impossible. The sampling method that was used is the random sampling method, and the collection of the data has been done in two different ways. In the first one the questionnaire was supplemented with personal interviews and in the second via internet. Especially, a site was created, the respondents were visiting this site and after the completion of the questionnaire they submitted the answers by just clicking in the submit button. The total sample size consists of 524 usable questionnaires from which 142 (27%) from personal interviews and the rest 382 (73%) from the internet site.

The gender of the respondents were almost equal (50,4% males; 49,6% females). The majority of the individuals are very young (-24 years old) or young (25-40 years old), something which is natural as they are the main ages that are familiarized and have access to the internet. Almost half of the respondents (53,6%) are highly educated but mainly with low income (-800 € a month). Finally, 23,2% work in the public sector, 35,5% in the private sector, 18,4% are self employed or businessmen while an important percentage (15,4%) are students. More details about the samples composition in table 1.

4.2 Measurement The questionnaire that was used for the needs of the research is based on similar questionnaires and the most of the variables were measured using multi- items scales tested in previous studies. The first part of the questionnaire refers to the demographic characteristics and to level of familiarity in the use of the internet. For measuring users experience three variables were used: (1) length of use, (2) frequency and (3) time spend connected. The second and third part of the questionnaire refers to the two factors that influence the use of internet banking and to purchase goods or services via internet. These factors are “perceived trust” and “perceived risk”. In the case of e- banking, for the measurement of trust and risk 5 and 4 items respectively were used, adopted by the study of Thomson and Jing [33]. In the case of e-commerce, for the measurement of trust 5 items are adopted by the study of

Thomson and Jing [33], while for the measurement of risk 4 items are adopted by the work of Houghton et al. [34] and Simon et al. [35].

Table 1. Demographic Characteristics

Characteristics Percent Gender Male 50,4

Female 49,6 Age -24 30,6

25-40 60,0 41-55 7,3 55+ 2,1

Education Primary school 10,9 Secondary school 8,4 College 10,7 University/Tech. Institution 53,6 MS/Dr 16,3

Income -800 euro 45,4 801-1200 euro 29,0 1201-1400 euro 10,6 over 1400 euro 15,1

Occupation Public servant 23,2 Private employee 35,5 Student 15,4 Freelancer/ Self Employed 18,4 Housewife/Unemployed 6,5 Pensioner 1,0

Collection Methods

Via Internet 73,0% Personal Interviews 27,0%

Finally, in the fourth part it was attempted to determine the intention to use e-banking or to purchase via internet, using 4 items adopted from the work of Crespo et al [31]. All items, in the second, third and fourth part, were statements and the respondents were asked to indicate on a 5- point Likert scale, ranging from 1=strongly disagree to 5=strongly agree, the degree to which they agreed with the statements.

4.3 Validation of Proposed Constructs Several tests were performed to establish Content Validity, Construct Validity and Reliability of the measures. These tests are needed in order to ensure the appropriateness of the research instrument. Content Validity refers on the extent to which a measurement reflects the specific intended domain of content [36]. To ensure content validity primary a review of the literature on the subject of the study was made and secondly a pilot test in a panel of experts (professors and professionals) was conducted.

The next step in the validation procedure was the construct validity test. The construct validity seeks on agreement between a theoretical concept and a specific measuring device or procedure. Cao and Dowlatshahi [37] suggest three ways to assess construct validity: (1) a test of Unidimensionality, (2) a test of Discriminant validity and (3) a test of Convergent validity.

Unidimensionality gives evidence of a single latent construct [38]. In this study for evaluating the unidimentionality, exploratory factor analysis (EFA) was used. For the extraction of the factors, a Principal Component Analysis with Varimax rotation was used. For testing the appropriateness of the data for factor analysis,


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Bartlett’s test of sphericity was performed. Moreover, the Measure of Sampling Adequacy (M.S.A) of Kaiser-Mayer-Olkin (K.M.O), which is the most popular diagnostic measure [39], was used. According to Sharma (1996) K.M.O should be greater than 0,7. As factors all these with Eigenvalue greater than 1 were determined. Finally, as far as the test of significance of items is concerned the factor loadings were checked. In a sample of more than 250 individuals, a loading of 0.35 is considered as significant [40].

In this study two factor analyses were performed for both e-commerce and e-banking items. All the results were very satisfying as they cover the restrictions which were mentioned above.

Discriminant validity copes with the concept that differing constructs should be dissimilar [41]. An indicator of discriminant validity can be found if the correlation coefficients between the pairs of the variables are less than the Cronbach’s alpha [42]. The findings from the test were very satisfactory.

Convergent validity correlates with the degree to which multiple methods of measuring a variable provide the same results [43], [42]. Convergent validity is believed to be acceptable when all item loadings are more than 0,5 [44] and the items for all construct load onto one factor with an eigenvalue greater than 1. All items have load greater than 0,5 and the eigenvalue for all factors were greater than 1.

Finally, a reliability test, which measures the internal consistency, was performed using Cronbach's alpha coefficient. Nunally [45] suggests that Cronbach’s alpha should be more than 0,7 so as to be characterized a construct reliable. In this study all the indices were greater than 0,7.

5. DATA ANALYSIS- RESULTS In order to test the hypotheses of this study two regression analyses were performed. In both of them, the dependent variable was the “intention” and independent variables the “familiarity”, “trust” and “risk”. From the analyses resulted that in the case of e-commerce the three independent variables explain the 30% of the variance of the dependent variable. In the case of e-banking the explained percentage is more than 50%.

Table 2: Regression Analysis R2 F Sig. e- commerce 30% 73,616 0,000 e- banking 53% 191,467 0,000

Furthermore, as we can see in the table 3, in the case of e-commerce all coefficients are significant. Especially risk, with a value of -0,319, affect negatively the intention to purchase online. Similar, but positive is the effect of trust on the intention to purchase online. In the case of e-banking, trust with a value of 0,650 is the factor which affects more than the other the intention to use e-banking. Risk has a negative and significant affect but is not as strong as in the case of e-commerce. All these results support the fourth hypotheses mentioned above.

Table 3. Regression Coefficients Independent

Variables Beta t Sig.

e- commerce Familiarity 0,223 5,995 0,000 Risk -0,319 -8,566 0,000 Trust 0,305 8,113 0,000

e- banking

Familiarity 0,118 3,765 0,000 Risk -0,094 -2,913 0,004 Trust 0,650 19,424 0,000

Additionally, in order to investigate the behaviour of the customers towards e-commerce and e-banking, an analysis of variance was performed. The results indicate that the customers feel less risk in the e-commerce than in e-banking and they have more trust on it than on e-banking.

Table 4: ANOVA. Mean

RISK TRUST INTENTION e- commerce 2,8 3,2 3,3 e- banking 3,3 2,8 3,1 t-value -10,533 8,823 3,521 Sig. 0,000 0,000 0,000

6. CONCLUSIONS From the analysis of the results of the present study becomes perceptible that the respondents are, on average, sufficiently familiar with the use of internet as most of them use it many years, almost daily and for many hours. However, the Greeks are still very cautious and obviously want to feel more confident and safe, less danger and higher comfort in order to adopt the e-banking and e-commerce transactions. Additionally, “familiarity”, “trust” and “risk” affect more the intention to use e-banking than the intention to use e-commerce and is more probably to purchase via internet than to use e-banking.

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Authorsʼ List Aifadopoulou Georgia

Centre for Research and Technology Hellas Hellenic Institute of Transport

[email protected]

Christodoulakis N. University of Piraeus

80, Karaoli & Dimitriou str., GR-18534 Piraeus, Greece [email protected]

Angelidis Panagiotis Laboratory of Ichthyology


0030 2310 999822 [email protected]

Chrysohoou Evangelia Centre for Research and Technology Hellas

Hellenic Institute of Transport [email protected]

Antoniadis Pantelis Dept. of Electrical Engineering,


+30 2510 462276 [email protected]

Dimitriadis Efstathios Kavala Institute of Technology

Agios Loukas 65 404, Kavala-Greece +30 2510462304

[email protected]

Arabatzis Garyfallos Department of Forestry and Management of the

Environment and Natural Resources Democritus University of Thrace


Dimopoulou Efi School of Surveying Engineering, National Technical

University of Athens (NTUA) [email protected]

Archontakis G. General Hospital of Chania

Chania, Greece

Dimou Vasiliki Department of Forestry and Management of the

Environment and Natural Resources Demokrition University of Thrace,

Department of Forestry-Geology-Hydrology TU Dresden, Germany.

3 Cohran str. 65201 Kavala +30 6947800872

[email protected]

Aretoulis N. Georgios School of Civil Engineering


Thessaloniki, Greece [email protected]

Doukas Haris National Technical University of Athens

School of Electrical and Computer Engineering 9, Iroon Polytechniou str., 157 80


Babalos Vassilios University of Piraeus

Department of Banking & Financial Management 80, Karaoli and Dimitriou Str, Piraeus, Greece

[email protected]

Doumpos Michael Technical University of Crete

Dept. of Production Engineering and Management Financial Engineering Laboratory

University Campus, 73100 Chania, Greece [email protected]

Batzios Christos Laboratory of Animal Production Economics



Fantidis Jacob Dept. of Electrical Engineering



Bournaris Thomas Aristotle University of Thessaloniki

Department of Agricultural Economics

Florou Giannoula Kavala Institute of Technology

[email protected]


62

Thessaloniki 54124, Greece [email protected]

Boutsimea Anastasia Kavala Institute of Technology

[email protected]

Fotakis Dimitrios Kavala Institute of Technology [email protected]

Gagatsi Eliza Aristotle University of Thessaloniki 541 24, Thessaloniki,

Greece +30 2310 498464; +306976224371

[email protected]

Karasavvoglou Anastasios Kavala Institute of Technology

[email protected]

Giannikopoulos Konstantinos TEI Kavalas, Department of Business Administration

Ag. Loukas, Kavala, 654 04, GR (+30) 2510 462177

[email protected]

Kazaklis Angelos Centre for Integrated Environmental Management,

GREECE [email protected]

Greco Salvatore Department of Economics and Business, University of

Catania 95129 Catania, Italy

[email protected]

Kazana Vassiliki Department of Forestry and Natural Environment

Management at Drama Kavala Institute of Technology

1st km Drama-Mikrohori, 66100 Drama, GREECE +30 2521060435

[email protected] Grigoroudis Evangelos

Technical University of Crete, Department of Production Engineering and Management


[email protected]

Kazanidis Ioannis Department of Accountancy

Kavala Institute of Technology Ag. Loukas, 65404, Greece

[email protected]

Hurson Ch. IAE, Université de Rouen, 3, Avenue Pasteur, F-76186

Rouen Cedex, France [email protected]

Keramydas C. Aristotle University of Thessaloniki

P.O. Box 461, 55124 0030 2310 995896 [email protected]

Iakovou E. Aristotle University of Thessaloniki


Kipouros Anagnostis Accounting department,


[email protected]

Ioannou Konstantinos Laboratory of F. Informatics

School of Forestry and Natural Environment Aristotle University of Thessaloniki

+30 6944798247, [email protected]

Kostoglou Vassilis Department of Informatics,

Alexander Technological Educational Institute of Thessaloniki P.O. Box 141

Thessaloniki, 57400, Greece [email protected]

Ismyrlis Vasileios Department of Marketing and Operations Management

University of Macedonia Agiou Dimitriou 49, 58200, Edessa, Greece

[email protected]

Koutsona Paraskevi Kavala Institute of Technology

[email protected]

Kaltsidis Theoklitos Cyprus Bank

Kavala- Greece

Krasoudakis A. General Hospital of Chania

Chania, Greece

Kaltsidou Despoina Democritus University of Thrace

Komotini - Greece [email protected]

Krassadaki E. Technical University of Crete

Department of Production Engineering and Management Decision Support Systems Laboratory


-63-

University Campus, 73100, Chania, Crete [email protected]

Lakiotaki Kleanthi Technical Univ. of Crete

Dept. of Production & Management Engineering Decision Support Systems Lab.

Chania, Crete, Greece [email protected]

Moulogianni Christina Aristotle University of Thessaloniki


[email protected]

Lemontzoglou Xanthippe Technical Univ. of Crete

Dept. of Production & Management Engineering Decision Support Systems Lab.

Chania, Crete, Greece [email protected]

Nikitakis Petros General Hospital of Chania

Emergency Department Mournies- Chania

Postal Code 73300

Makarouni Ioanna National Technical University of Athens



Papadopoulou G. Alexandra National Technical University of Athens

School of Electrical & Computer Engineering Management & Decision Support Systems Lab. (EPU-

NTUA) 9, Iroon Polytechniou str. 157 80, Athens, Greece

[email protected]

Manolitzas P. Decision Support Systems Laboratory


Papathanasiou Jason Department of Marketing and Operations Management

University of Macedonia Edessa, Greece [email protected]

Manos Basil

Aristotle University of Thessaloniki Department of Agricultural Economics

Thessaloniki 54124, Greece [email protected]

Partsch D. Aristotle University of Thessaloniki


Manthou Vassiliki University of Macedonia

Department of Applied Informatics Thessaloniki 54006, Greece

[email protected]

Petasakis Ioannis Department of Accountancy


[email protected]

Marinakis Vangelis National Technical University of Athens

School of Electrical & Computer Engineering Management & Decision Support Systems Lab. (EPU-

NTUA) 9, Iroon Polytechniou str. 157 80, Athens, Greece

[email protected]

Petkos Dimitris Department of Informatics,

Alexander Technological Educational Institute of Thessaloniki, P.O. Box 141

Thessaloniki, 57400, Greece [email protected]

Mitsakis Evangelos Centre for Research and Technology Hellas

Hellenic Institute of Transport +30 2310 498459

[email protected]

Philippas Nikolaos University of Piraeus

Department of Business Administration 80, Karaoli and Dimitriou Str, Piraeus, Greece

[email protected] Moschidis Odysseas

Department of Marketing and Operations Management University of Macedonia Ethnikis Antistaseos 33

Moudania, 63200, Greece [email protected]

Polychronidou Persefoni Kavala Institute of Technology

[email protected]


64

Psarras John National Technical University of Athens



Triantafillidis X. Christoforos School of Civil Engineering


Thessaloniki, Greece [email protected]

Salanova Grau Josep Maria Centre for Research and Technology Hellas

Hellenic Institute of Transport [email protected]

Tsifetakis Ε. Technical University of Crete

Department of Production Engineering and Management Decision Support Systems Laboratory

University Campus, 73100, Chania, Crete [email protected]

Siskos Eleftherios

National Technical University of Athens School of Electrical and Computer Engineering

9, Iroon Polytechniou str., 157 80 Athens, Greece

[email protected]

Tsiolias D. Aristotle University of Thessaloniki

P.O. Box 461, 55124 0030 2310 995896

[email protected]

Siskos Yannis University of Piraeus

80, Karaoli & Dimitriou Street GR-18534 Piraeus, Greece

[email protected]

Tsotsolas N. University of Piraeus

80, Karaoli & Dimitriou str., GR-18534 Piraeus, Greece [email protected];

Slowinski Roman

Institute of Computing Science and Systems Research, Poznan University of Technology

60-965 Poznan Polish Academy of Sciences, 01-447 Warsaw, Poland

[email protected]

Tsourgiannis Christos Antonios Ministry of Rural Development and Food

[email protected]

Spyridakos Athanasios Department of Mathematics

TEI of Piraeus 0030 210 5381544

[email protected]

Tsourgiannis Lambros Region of East Macedonia and Thrace

[email protected]

Stamatiou Christos Kavala Institute of Technology

[email protected]

Valsamidis Stavros Department of Accountancy


[email protected]

Theodoridis Alexandros Laboratory of Animal Production Economics



Vatsos Ioannis Laboratory of Ichthyology



Theodosiou Theodosios

Department of Accountancy Kavala Institute of Technology Ag. Loukas, 65404, Greece

[email protected]

Vlachopoulou Maro

Department of Applied Informatics University of Macedonia

Tessaloniki, 54006 [email protected]

Tolidis Konstantinos

School of Surveying Engineering, National Technical University of Athens (NTUA)

Vlachos D. Aristotle University of Thessaloniki

P.O. Box 461, 55124


-65-

[email protected] 0030 2310 995969 [email protected]

Vordos Nikolaos Dept. of Electrical Engineering


+30 2510 462 247 [email protected]

Κουλουριώτης Δ. Ε. Τµήµα Μηχανικών Παραγωγής και Διοίκησης

Δηµοκρίτειο Πανεπιστήµιο Θράκης [email protected]

Kitsios Fotis University of Macedonia, Department of Technology

Management Loggou-Tourpali, 59200, Naousa-GR

(+30) 23320 52467 [email protected]

Κουτσουβάλης Γ. Π. Τµήµα Μηχανικών Παραγωγής και Διοίκησης


Xidonas Panos National Technical University of Athens

School of Electrical & Computer Engineering 9 Heroon Polytechneiou Str., 15780, Athens, Greece

[email protected]

Κων/νος Δ. Ποτόλιας Τµήµα Διεθνών Οικονοµικών Σχέσεων και Ανάπτυξης


Yannacopoulos Dennis Technological Education Institute of Piraeus

Marketing Laboratory [email protected]

Μourmouris Ι. Department of International Economic Relations and

Development Democritus University of Thrace


Zagkoumidou Vasiliki +30 6974754885

[email protected]

Νikolaidis Κ. Department of International Economic Relations and

Development Democritus University of Thrace


Zopounidis Constantin Technical University of Crete

Dept. of Production Engineering and Management Financial Engineering Laboratory

University Campus, 73100 Chania, Greece [email protected]

Xanthopoulou Maria Kavala Institute of Technology

Agios Loukas 65 404, Kavala-Greece [email protected]

Αραµπατζής Γαρύφαλλος Τµήµα Δασολογίας και Διαχείρισης Περιβάλλοντος

και Φυσικών Πόρων Δηµοκρίτειο Πανεπιστήµιο Θράκης

[email protected]

Ξανθόπουλος Α. Σ. Τµήµα Μηχανικών Παραγωγής και Διοίκησης


Γαλατσίδας Σπύρος Τµήµα Δασολογίας και Διαχείρισης Περιβάλλοντος


[email protected]

Πετρίδης Κωνσταντίνος Τµήµα Δασολογίας και Διαχείρισης Περιβάλλοντος


[email protected]

Δρόσος Δηµήτριος Τµήµα Διοίκησης Επιχειρήσεων

ΤΕΙ Πειραιά [email protected]

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