International Journal of Research in Science and Technology Volume 2, Issue 3 (I) July - September...

International Journal of Research in Science and Technology Volume 2, Issue 3 (I): July - September 2015

Editor- In-Chief Dr. Pranjal Sharma

Members of Editorial Advisory Board

Dr. Nurul Fadly Habidin Faculty of Management and Economics, Universiti Pendidikan Sultan Idris, Malaysia

Dr. Marwan Mustafa Shammot Associate Professor, King Saud University, Riyadh, Saudi Arabia

Prof. P. Madhu Sudana Rao Professor of Banking and Finance, Mekelle University, Mekelle, Ethiopia

Dr. Amer A. Taqa Faculty, DBS Department, College of Dentistry, Mosul University

Dr.Agbo J.Madaki Lecturer, Catholic University of Eastern Africa, Kenya

Dr. Sunita Dwivedi Associate Professor, Symbiosis International University, Noida

Dr. D. K. Pandey Director, Unique Institute of Management & Technology, Meerut

Dr. Sudhansu Ranjan Mohapatra Director, Centre for Juridical Studies Dibrugarh University, Dibrugarh

Dr. Tazyn Rahman Dean ( Academics ) Jaipuria Institute, Ghaziabad

Dr. Neetu Singh HOD, Department of Biotechnology, Mewar Institute , Vasundhara, Ghaziabad

Dr. Teena Shivnani HOD, Department of Commerce, Manipal University, Jaipur

Dr. Anindita Associate Professor, Jaipuria School of Business, Ghaziabad

Dr. K. Ramani Associate Professor, K.S.Rangasamy College of Technology, Namakkal

Dr. S. Satyanarayana Associate Professor, KL University , Guntur

Dr. Subha Ganguly Scientist (Food Microbiology) University of Animal and Fishery Sciences, Kolkata

Dr. Gauri Dhingra Assistant Professor, JIMS, Vasant Kunj, New Delhi

Dr. V. Tulasi Das Assistant Professor, Acharya Nagarjuna University

Dr. R. Suresh Assistant Professor, Mahatma Gandhi University

Copyright @ 2014 Indian Academicians and Researchers Association, Guwahati All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, or stored in any retrieval system of any nature without prior written permission. Application for permission for other use of copyright material including permission to reproduce extracts in other published works shall be made to the publishers. Full acknowledgment of author, publishers and source must be given. The views expressed in the articles are those of the contributors and not necessarily of the Editorial Board or the IARA. Although every care has been taken to avoid errors or omissions, this publication is being published on the condition and understanding that information given in this journal is merely for reference and must not be taken as having authority of or binding in any way on the authors, editors and publishers, who do not owe any responsibility for any damage or loss to any person, for the result of any action taken on the basis of this work. All disputes are subject to Guwahati jurisdiction only.

International Journal of Research in Science and Technology Volume 2, Issue 3 ( I ): July - September 2015

CONTENTS

Research Papers

PORTFOLIOS OF CONTROL IN BUSINESS PROCESS OUTSOURCING

Dr. Rohtash Kumar Garg and Neha Solanki

1 13

INVENTORY MODELING FOR DETERIORATING ITEMS: FUNDAMENTAL VIEW

Hetal R. Patel

14 21

AN OVERVIEW OF DATA WAREHOUSING AND OLAP OPERATIONS

Chandrakant Dewangan, Dileshwar Dansena, Mili Patel and Pooja Khemka

22 28

FORMANT ESTIMATION FOR SPEECH RECOGNITION AND STRUCTURAL ANALYSIS OF ASSAMESE LANGUAGE IN ASSAM

Dr. Rashmi Dutta

29 37

CELLPHONE CLONING OVER (GSM & CDMA)

Mukesh Patel, Mili Patel and Pooja Khemka

38 40

CONVERSION OF METHANOL TO FORMALDEHYDE OVER Ag NANOROD CATALYST UNDER MICROWAVE IRRADIATION

Manish Srivastava, Aakanksha Mishra, Ashu Goyal, Anamika Srivastava and Preeti Tomer

41 43

DIGITAL SIGNATURE VERIFICATION WITH OTP GENERATION BASED ON HIDDEN MARKOV MODEL

A. Manoj, M. Ayyappan, T. Rajesh Kumar and Dr. S.Padmapriya

44 47

ENHANCED CERTIFICATE REVOCATION USING CLUSTERING SCHEME FOR MANETs

N. R. Vaishnavi , J. Omana, Sherinkaran Wisebell and I. M. Thaya

48 53

LOCATION PRIVACY IN UBIQUITOUS COMPUTING

Purnima Pradhan, Savita Singh, Mili Patel and Pooja Khemka

54 58

RESEARCH ISSUE IN: STUDY OF QUANTUM CRYPTOGRAPHY

Rupali Yadav, Neellima Manher, Mili Patel and Pooja Khemka

59 62

ARTIFICAL INTELLIGENCE

Amanjot Kaur

63 67

STUDY OF E -VOTING SYSTEM WITH MULTI SECURITY USING BIOMETRIC

Shashikala Khandey, Kavita Patel, Mili Patel and Pooja Khemka

68 75

STUDY OF QUANTUM COMPUTING

Alka Chandan, Ankita Panda, Mili Patel and Pooja Khemka

76 80

CONSIDERING ANY RELATION BETWEEN ORGANIZATIONAL CULTURE & SUGGESTIONS SYSTEM

Kiamars Fadaei

81 89

CORPORATE GOVERNANCE AND FINANCIAL STABILITY IN SUDANESE BANKING SECTOR

Dina Ahmed Mohamed Ghandour

90 98

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International Journal of Research in Science and Technology Volume 2, Issue 3 (I): July - September, 2015

ISSN 2394 - 9554

PORTFOLIOS OF CONTROL IN BUSINESS PROCESS OUTSOURCING

Dr. Rohtash Kumar Garg and Neha Solanki Assistant Professor, DIRD, New Delhi

ABSTRACT The three trends that seem certain to dominate the world, for some time to come, are globalization, technological advances and deregulation. They combine to make geographical dispersion an area of low concern in the planning of business strategy; as enterprises increasingly look for leveraging the cost or differentiation advantages available across the globe forging partnerships to create a value chain with the aim of accomplishing the most with the least. It is in this scenario that business process outsourcing (bpo') emerges as the latest buzz in management thinking as a global supply-chain of information and expertise that stretches from Mumbai to Manhattan is etched.

The greatest challenge in this management tool, however, is one of control. Managers are accustomed to having direct control over the resources to deliver the results for which theyre accountable. With BPO, these controls are in the hands of the provider. How this aspect of governance is handled can mean the difference between adequate results and high performing outsourcing that delivers beyond expectations. It is this control issue its practice and its structuring that is explored in this paper.

Keywords: business process outsourcing, control, management

INTRODUCTION In 1989 when CIO Katherine Hudson outsourced the management of Kodaks entire data centre to DEC-IBM she introduced a whole new paradigm in business administration that would soon transcend borders, go global and create havoc among the then existing ethics of business and exchange. The Kodak IBM deal changed the rules of the management game irreversibly. If a large Fortune 500 company such as this could do it to save costs and protect its core competency, would others allow themselves to lag behind?

Close to two decades later, the world, today, has moved onto outsourcing practically every business process including medical services to third party vendors. The global business process outsourcing sector is currently estimated to be over US$ 18 billion. Nasscom predicts the total exports for the Indian BPO sector to exceed USD 8.3 billion in FY 2006-07, growing by 32 percent over the previous year. Over FY2001-2006, Indias share in global process sourcing is estimated to have grown from 39 per cent to 45 percent. As a proportion of national GDP, the revenue aggregate of the Indian technology sector has grown from 1.2 percent in FY1998 to an estimated 5.4 percent in FY2007. Net value-added by this sector, to the economy, is estimated at 3-3.5 percent for FY2007. (All data from Nasscom strategic review 2007)

The increasing pervasiveness of outsourcing, the competitiveness and diversity of the market, and the consequent growing interest among researchers on various outsourcing issues provide the impetus for this study. In the last decade, a large number of studies have been conducted to address a variety of outsourcing research issues. Researchers have focused on various outsourcing issues such as motivation (Buchowicz 1991, Buck-Lew 1992), scope (Benko 1993, Gupta & Gupta 1992), performance (Arnett and Jones 1994, Loh and Venkatraman 1995), contract (Fitzgerald and Willcocks 1994, Richmond and Seidmann 1992) and partnership (Grover, Cheon and Teng 1996, Klepper 1995).

However, there has been only limited attention to the form of control systems that are suited to strategic alliances, with calls to extend the domain of organizational control to cover inter-firm relationships (Otley, 1994; Hopwood, 1996; Spekl, 2001). Research that considers explicitly the design of control in outsourcing relationships has, however, begun to appear (van der Meer-Kooistra and Vosselman, 2000; Mouritsen et al., 2001; Chua and Mahama, 2002). A common feature, though, of all these studies has been its focus on the clients perspective. In fact, as Levina and Ross note, while the clients sourcing decisions and the client-vendor relationship have been examined in outsourcing literature, the vendor's perspective has hardly been explored (Levina & Ross, 2003). This near-total lack of vendor perspectives in outsourcing research has been also been highlighted by Dibbern et al., (2004).

This burgeoning impact of business process outsourcing coupled with the paucity of theoretical understanding on control from the vendors perspective has motivated this research. An attempt to understand critical outsourcing control issues and provide an integrative theoretical perspective to add new insights in the direction and focus of future outsourcing research has been the underlying rationale for this study; the intent being to explore how control modes are implemented in business process outsourcing relationships.

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Research provides evidence of controllers in inter-organizational settings structuring a portfolio of control modes in order to manage the complexities and subtleties of a task that involves people with various knowledge and skills across time (Boland 1979, Orlikowski 1991, Henderson and Lee 1992). Thus we expect that, even in the business process outsourcing context, firms will use a portfolio of controls. Thus, our research objective is to explore the mechanisms that constitute the portfolios of control in business process outsourcing relationships.

REVIEW OF LITERATURE Research on business process outsourcing has for the most part been driven by the practitioner community. Academics, largely, have demonstrated relatively lesser interest in researching this phenomenon leading to a virtual absence of academic publications on the topic" (Rouse and Corbitt, 2004). Other researchers such as Gewald et al (2006) and Whitaker et al. (2006) have also noted this lacuna. Also, business process outsourcing has often been treated as an extension of the concept of IT/IS outsourcing to IT intensive business processes (Hyder et al, 2002) or as a subset of IT/IS outsourcing (Sovie & Hansen, 2001; Michell & Fitzgerald, 1997). Hence for this paper, we have sourced information from the extensive body of work on IT/IS outsourcing research of the past two decades. As Dibbern et al. (2004) note research on . business process outsourcing would benefit from standing on the shoulders of what has already been accomplished in the field of IS outsourcing.

CONCEPTUALIZATION OF BUSINESS PROCESS OUTSOURCING The transaction cost approach to the theory of the firm hypothesizes that firms are organizational innovations born out of the costs involved in market transacting in order to reduce those costs. Coase (1937) has argued that, were the firm and the market alternatives for organizing the same set of transactions; a firm will substitute market transactions as long as management costs are less than transaction costs. Thanks to the convergence in corporate computing platforms and rapid advances made in communications technology it has become easy and inexpensive to seamlessly link together geographically dispersed information systems thus making market transactions for executing several activities previously done within the firm boundaries possible and preferable. This concept of remotely executing tasks was the genesis of business process outsourcing defined as the delegation of one or more IT-intensive business processes to an external provider that, in turn, owns, administrates and manages the selected process/processes, based upon defined and measurable performance metrics (Gartner 2004).

The key defining characteristics brought out by this definition are: The transfer of management and execution of one or more complete business processes or entire business

functions to an external service provider (vendor).

Nature of outsourced processes being essentially IT intensive. Such highly transactional, technology-intensive work lends itself easily to business process automation.

The vendor is part of the decision making structure surrounding the outsourced business function.

The client relinquishes control over the outsourced process in favor of monitoring through performance metrics tied to strategic business value.

In ascending order of value and level of expertise required, bpo can be classified as: Data entry and conversion, which includes medical transcription;

Rule-set processing, in which a worker makes judgments based on rules set by the customer. He might decide, for example, whether, under an airlines rules, a passenger is allowed an upgrade;

Problem-solving, in which the bpo provider has more discretionfor example, to decide if an insurance claim should be paid;

Direct customer interaction, in which the bpo provider handles more elaborate transactions with the clients customers. Collecting delinquent payments from credit-card customers is an example;

Expert knowledge services, which require specialists (with the help of a database). For example, a bpo provider may predict how credit-card users behavior will change if their credit rating improves.

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A business process outsourcing relationship typically progresses through the following four phases:

Figure 1

CONTROL PRACTICES: A SURVEY AND ANALYSIS OF LITERATURE The issue of control has received considerable attention in organizational literature. Anthonys (1965) contribution in particular is often referred to and well known for its distinction between strategic planning, management control and operational control. Child (1984), Eisenhardt (1985), Hofstede (1981) and Ouchi (1979) determine the context of control in organizations and determine a number of characteristics that lend themselves to define a typology. On the other hand Boland (1979) and Orlilowski (1991) reveal how control is applied in the context of information management. Looking at the existing theories, three common dimensions can be identified according to Fischer (1993) that describe a useful typology for analyzing control: focus of control (directed at whom or what), measures of control (degree of control), and process of control (means of enforcing control).

Control in this study is viewed in a behavioral sense, that is, as the organization's attempt to increase the probability that people will behave in ways that lead to the attainment of organizational goals (Flamholtz et al., 1985) and thus includes a range of mechanisms to monitor and execute operations. As Tannenbaum (1968) states it is the function of control to bring about conformance to organizational requirements and achievement of the ultimate goals of the organization. Taking this broad view allows for an examination of multiple approaches to control, and avoids problems associated with more narrow perspectives. For example, the practioner literature typically takes a cybernetic view of control, in which outputs are compared against standards and corrective actions are taken to address deviations; the PMI Standards Committee (1996) offers the following definition: the process of comparing actual performance with planned performance, analyzing variances, evaluating possible alternatives, and taking appropriate corrective action as needed (p.161, emphasis in original). This cybernetic view assumes that outcomes are known, standards can be set, and corrective action is possible (Markus and Pfeffer 1983, Merchant and Simons 1986, Jaworski 1988). However, desired outcomes, standards, and corrective actions are not always obvious in the outsourcing environment, rendering these assumptions problematic and suggesting the need for a broader interpretation of control (Kirsch 1997).

The behavioral view of control implies that the controller uses certain devices, or control mechanisms, to promote desired behavior by the controllee (Kirsch 1997). These control mechanisms help implement control modes, which may broadly be divided into formal controls, i.e., modes that rely on mechanisms that influence the controllees behavior through performance evaluation and rewards, and informal controls, i.e., modes that utilize social or people strategies to reduce goal differences between controller and controllee (Eisenhardt 1985; Kirsch 1996, 1997). Some researchers (e.g., Merchant 1988) view formal and informal controls not as a dichotomy, but as opposite ends of a continuum. Both formal and informal controls are exercised through mechanisms used to influence controllee behavior. Examples include target implementation dates (formal control) and socialization (informal controlKirsch 1997).

Two types of formal controls have been commonly considered in prior literature (e.g., Ouchi 1979, Eisenhardt 1985),behavior control and outcome control. In outcome control, the controller explicitly states desired outcomes or goals and rewards the controllee for meeting those goals (Kirsch 1997). In behavior control, the controller seeks to influence the process, or the means to goal achievement, by explicitly prescribing specific

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rules and procedures, observing the controllees behaviors, and rewarding the controllee based on the extent to which it follows stated procedures (Jaworski & Maclnnis 1989, Kirsch 1996).

Informal controls are also of two types: clan control and self-control. Clan controls operate by promulgating common values, beliefs, and philosophy within a clan, which is defined as a group of individuals who are dependent on one another and who share a set of common goals (Kirsch 1996). In self-control, the controllee determines both the goals and the actions through which they should be achieved (Henderson and Lee 1992). Several authors (e.g., Von Glinow 1983, Kirsch 1996) have noted, however, that the controller can also encourage or enable the controllee to exercise self-control.

Studies on intra-organizational control practices further suggest that, controllers often use the four modes (behavior, outcome, clan, self) in combination, creating a portfolio of controls (Kim 1984, Jaworski 1988, Jaworski et al. 1993, Kirsch 1997). Referring to information systems development projects, Kirsch (1997) noted that "In no instance did a controller in this study eliminate formal controls. .the controllers were not comfortable relying solely on informal modes of control ..they seemed to require a comfort zone of formal modes (Kirsch 1997, p. 235)."

CONTROL IN THE OUTSOURCING CONTEXT Business process outsourcing is not just a technical process of managing a business function but also a social process involving stakeholders from multiple organizational units. This set of stakeholders possesses critical and complementary skills and knowledge that will be called upon during the course of the relationship. Successful outsourcing arrangements, therefore, require effective management of relationships among these stakeholders to elicit their contributions and cooperation, while, at the same time, maintaining progress in conformance with the business value propositions and proposed schedules and budgets. Exercising control is one powerful approach that managers can use to ensure progress by fusing together the complementary roles and capabilities of the outsource participants, motivating individuals to work in accordance with organizational goals and objectives. Research suggests a natural link between how an outsourcing arrangement is structured and managed, and the subsequent outcomes (Dibbern et al., 2004). As Clark et al. state .the truly critical success factors associated with successful outsourcing are those associated with vendor governance (Clark et al., 1998). The practitioner literature has also noted the critical role that control plays in effective outsourcing management (Linder and Sawyer, 2003).

RESEARCH METHODOLOGY This section presents the methodological elements and the research design of this study. The first section discusses the unit of analysis. The second section describes the stages of our case study. We then address the issue of research quality.

UNIT OF ANALYSIS The focus of this study is the outsourcing relationship between a service receiver and a service provider. An individual client-vendor- outsourced function relationship commonly referred to as a queue embedded within the vendor organization is regarded as the unit of analysis. Most of the prior research in outsourcing has used the methodology of collecting data from either the customers or the vendors (Levina and Ross 2003). In this study we adopt a more comprehensive and balanced approach by collecting data from both clients and vendors- this research design significantly reduces the risks of common source bias in this study (Zmud and Boynton 1991).

Our cases were of business process outsourcing relationships with durations in excess of one year. Establishing this criterion of duration ensured that the client and vendor have had sufficient opportunity to work with each other and developed a degree of maturity in the relationship reflected in the establishment of the control structures. A degree of outsourcing success was also inherent as contract durations in business process outsourcing relationships are typically of one year, hence a relationship in excess of one year would have witnessed at least one contract renewal / extension.

THE CASE STUDY APPROACH The case study is a research strategy which focuses on understanding the dynamics present within single settings. (Eisenhardt 1989). This research method is preferred when how or why questions are being posed, when the investigator has little control over events, and when the focus is on a contemporary phenomenon within some real-life context (Yin 1984). The investigation of how clients and vendors control to ensure that business process outsourcing relationships progress in conformance with the business value propositions, proposed schedules and budgets satisfied all of these criteria. The case study method is well established in outsourcing research especially with reference to governance issues (Kirsch 1997, Kern and Willcocks 2000).

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The procedure we followed for our exploratory case study was as per the steps outlined by Eisenhardt, 1989. We started with a definition of the research question How do stakeholders control to manage business process outsourcing relationships? Our attempt was to go into organizations with a well defined focus to collect specific kinds of data systematically (Mintzberg 1979)

SITE SELECTION We then proceeded to select our cases based on the concept of theoretical sampling so that we could best answer the question posed (Glaser and Strauss 1967). Since our goal was to understand how controls are structured and enforced, we needed cases where a) the vendor provided extensive access to individuals at multiple levels who could describe control practices and how they are enforced; b) the client acknowledged the relationship as successful; c) the client was willing to share perceptions as to efficacy of the control structure; and d) the contract had been active long enough to demonstrate a degree of stability of processes. The cases we studied satisfied all of these criteria. Our sites presented a rare opportunity for broad access to successful outsourcing engagements. These cases were revelatory (Yin 1984: 48) or exemplar in the sense that we had an opportunity to study something previously not researched, but not unique.

To strengthen the generalizability of this study, to produce enough data to suggest additions to control theories, and to provide empirical grounding, four case studies were conducted (Yin 1984, Eisenhardt 1989). Balancing the principles of similarity and variation, four business process outsourcing relationships in three vendor organizations were identified. All three vendor firms are established bpo firms with dominant positions in this sector on a global basis. Two are the bpo arms of premier IT companies, with annual revenues in excess of US$ 2 billion and the third is purely into bpo provision with annual revenues close to US$1 billion. The relationships differed along several dimensions, including outsourced function category, client firm industry and employee headcount. They were however, similar in terms of organization, revenue size and lifetime.

DATA SOURCES The first vendor organization (VO1) is a global leader in IT outsourcing providing services to more than 620 global customers across 53 countries. It employs 68,000 people from 42 different nations. This organizations full-service integrated portfolio offers industry focused solutions and spans across the entire spectrum of IT services application development and maintenance, business process outsourcing, technology infrastructure, consulting, package implementation, product engineering services, systems integration and R & D.

The second vendor organization (VO2) provides consulting and IT services to clients globally - as partners to conceptualize and realize technology driven business transformation initiatives. With over 80,000 employees worldwide, the company uses a low-risk Global Delivery Model (GDM) to accelerate schedules with a high degree of time and cost predictability.

The third vendor organization (VO3) manages business processes for companies around the world. The company combines process expertise, information technology and analytical capabilities with operational insight and experience in diverse industries to provide a wide range of services using its global delivery network of more than 25 locations in nine countries in multiple geographic regions with a headcount of over 29,000.

One of the world's leading financial firms with services including wealth management, global investment banking and securities, asset management, mutual funds and estate planning is our first client organization (CO1). This US$50 billion (approx.) company has offices in some 50 nations and employs over 70,000 people. The company services about 3.5 million corporate and about 140,000 corporate clients, as well as 3,000 financial institutions worldwide. The second client organization is one of the world's largest airline by revenue-passenger-miles and total passengers transported. UK's leading internet service provider, with more than 2 million subscribers, including more than 1.4 million on broadband is our third client organization (CO3).

The business processes outsourced included two instances of a financial analytics process which involved updation of various accounting and financial statements for various companies on the client terminal; adjustments to information received so as to facilitate company comparison; publishing of data for end user reception and error correction of reports as and when required. A voice queue for customer acquisition and retention and a non-voice queue for billing and technical help for an UK ISP comprised the other outsourced function. The last relationship studied involved the outsourcing of the order processing and related information technology services by an US airlines. The functions outsourced included processing inbound end-user pre-sale and post-sale inquiries and orders and providing and maintaining hardware and software supporting the information systems for these processes.

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The four cases are summarized below in Table 1.

* size depicted in terms of employee strength (Emp) and approx. revenues (Rev) in US$ bn.

DATA COLLECTION Data collected included both qualitative and quantitative types. This synergistic combination had advantages described by Mintzberg (1979) as: For while systematic data create the foundation for our theories, it is the anecdotal data that enable us to do the building..We uncover all kinds of relationships in our hard data, but it is only through the use of this soft data that we are able to explain them. Data collection involved a variety of techniques including unstructured and semi-structured interviews; documentation; archival records; direct observations; published sources; physical artifacts such as manuals, forms, and project archives; and follow-up emails and telephone interviews. The rationale was that the triangulation made possible by multiple data collection methods provides stronger substantiation of constructs (Yin 1984).

It was critical, during data collection, to identify and elicit information about particular incidents of control. Consequently, a specific interviewing technique was designed. Recognizing that control is purposive (Green and Welsh 1988), three common goals of outsourced relationships were identified: (1) maximizing speed in which things are done from the customers perspective (2) doing things accurately at the first attempt and (3) optimizing efficiency and the cost per unit incurred by the vendor (ref.: COPC-2000 CSP Standard, June 2005). A series of interview questions focused on mechanisms controllers used in order to meet each of these three goals.

Other general set of questions sought to uncover additional critical incidents and how they were handled. To uncover such incidents, respondents were asked to recall events that caused problems for which the organization had no ready solution, or events that challenged existing norms and solutions , or anything interpersonal that was unusual or tension provoking and required some kind of response (Schein 1987, p.120).

The interviews of the team/group leaders, operations managers and service delivery leaders/ queue heads generally lasted between one and two hours. The interview questions, primarily open-ended, were informed by the literature on control (Kirsch 1997, Rustagi 2004) and designed to elicit data about theoretical constructs of interest.

DATA ANALYSIS Data analysis frequently overlapped with data collection. An important means of analysis used by this researcher was the usage of field notes. Van Maanen (1988) described field notes as an ongoing stream-of-consciousness commentary about what is happening in the research, involving both observation and analysis. This overlap also allowed us to take advantage of flexible data collection. Adjustments to the interview protocol to probe emergent theme to improve resultant theory were thus made. Detailed case study write-ups for each relationship were made from these field notes as a next step with the overall objective to become intimately familiar with each case as a stand alone entity and accelerate cross case comparison (eisenhardt 1989).

REACHING CLOSURE In the subsequent step we tabulated the focus of and typical mechanisms used in the four control modes from our background literature study on control and then by comparing the description of the observed control mechanisms in business process outsourcing relationships attempted to classify them into the four control categories.

ADDRESSING QUALITY OF RESEARCH During data collection, construct validity and reliability issues were addressed. Construct validity, which is concerned with establishing that the correct measures are used, can be increased by using multiple sources of data (Yin 1984). In this research, multiple sources of data were tapped to ensure that responses converged. Inconsistencies were resolved by consulting control related documentation or other individuals for clarification.

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A typical example of documentation referred to would be a metrics checklist used by the process audit / compliance teams in vendor organizations.

Reliability is concerned with consistency (Yin 1984): if the study is repeated, would the same results follow? One of the primary means of establishing reliability is to build a case study database in order to be as explicit as possible about the way in which observations were made and recorded (Kirk and Miller 1986, Yin 1984). Several techniques were used in this study to improve reliability. First, all interviews were transcribed yielding approximately two hundred pages of transcripts. All transcriptions and related documentation were filed by case by individual. Second, the sources of all documents and data were recorded though an assurance of confidentiality was made. Finally, an individual write-up of each relationship was prepared where the data were sorted and organized by construct. The purpose of this last step was to reduce the raw data to a more manageable and meaningful structure.

RESULTS Control, in this research, refers to a range of mechanisms to monitor and execute operations to increase the probability of conformance to organizational (both client and vendor) requirements in the outsourcing relationship. A brief description of these mechanisms are given here as observed in the case study conducted involving four discrete business process outsourcing relationships.

1. Process metrics The term metrics in the bpo sector represents measurements that quantify results with respect to the outsourcing relationship and are the key focus of outsourcing contracts variously referred to as service level agreement (SLA) or statement of work (SOW). Various categories of metrics were observed with different objectives and target populations. These included people metrics (attrition, absenteeism targets); support function metrics (technology metrics such as network uptime) and process metrics.

As in this research, the first two have been categorized under different headings we deal here with only with the last. Process metrics are used to measure the service provider's performance and determine whether the service provider is meeting its commitments and can be differentiated into (i) volume metrics (ii) quality metrics (iii) responsiveness metrics and (iv) efficiency metrics.

Volume of work is typically the key sizing determinant of an outsourcing relationship, specifying the exact level of effort to be provided by the service provider within the scope of the relationship for instance number of transactions processed per period. Any effort expended outside of this scope will usually be separately charged to the client, or will require re-negotiation of the terms of the contract.

Quality metrics are the most diverse of all of the metrics covering a wide range of work products, deliverables and requirements and seeking to measure the conformance of those items to certain specifications or standards. These metrics include (i) Counts or percentages that measure the errors in major deliverables (ii) Standards compliance (iii) Service availability (iv) Service satisfaction especially end-user satisfaction assessment.

Responsiveness metrics measure the amount of time that it takes for an outsourcer to handle a client request and include metrics to measure the (i) the elapsed time from the original receipt of a request until the time when it is completely resolved (ii) time taken to acknowledge a request, and accessibility of status information (iii) the size of the backlog, typically expressed as the number of requests in the queue or the number of hours needed to process the queue.

Efficiency metrics measure the engagement's effectiveness at providing services at a reasonable cost. Examples include (i) cost/effort efficiency (ii) cost / employee efficiency

2. Transaction monitoring A structured approach is used to monitor all types of end-user transactions (e.g., calls, faxes, mail, web-based, e-mail, etc.) wherein all information given and received are monitored. The approach includes: Details of performance attributes to be monitored for both accuracy and quality A monitoring frequency A monitoring method (e.g., side-by-side or remote). Specific performance thresholds and a clear, objective scoring system. A plan for communicating the findings of all transactions monitored to the individuals monitored,

including both negative and positive feedback. Another usage of this mechanism is identifying (using Pareto analysis) reasons contributing to customer satisfaction / dissatisfaction at agent, team and process level.

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3. Staff Skill control Recruitment guidelines Vendors have clear, written definitions of the minimum skills and knowledge required for customer related jobs, provided by the client. Recruiting and hiring approaches are geared to identify and successfully recruit individuals with these minimum requirements.

Training For all staff, training is provided for all the minimum skills and knowledge defined, unless staff has been hired with these minimum skills and knowledge. The approach to training and development is formally defined and includes a listing of the specific skills and knowledge required for each minimum skill; the personnel authorized to provide the training and a desired or required outcome that can be verified. The document detailing the training approach requires a sign-off by the client before the training schedule can be initiated.

Staff testing The verification process for all staff in customer related jobs includes: Objective performance thresholds that are linked to the minimum requirements (including all minimum

skills and knowledge) of the position.

Documentation (e.g., tests, scores, dates) that can be audited.

Action plans for staff that fail to demonstrate the required skills and knowledge.

Annual re-verification of skills and knowledge.

Re-verification of skills and knowledge following changes in program, procedures, systems, etc.

4. Staff Performance Management This is done at two levels: Annual performance appraisal

The vendor employees performance appraisal includes the findings from skills and knowledge verification and transaction monitoring. Employee evaluations are structured to support the outsourcing relationships business performance targets.

Continuous monitoring Vendor employees who fail transaction monitoring are: (i) Individually (one-on-one) coached on all transactions that do not meet target.

(ii) Monitored more frequently in order to determine if their performance is statistically below target.

(iii) Advised on corrective actions using a structured approach for identifying and resolving the root cause(s) of poor performance. This action plan necessarily provides for removing employees who repeatedly perform fatal errors from handling end-user transactions

5. Financial controls One or more of these financial controls were observed in our cases embedded in the relationships pricing structure: Incentives are given to vendor as a percentage of invoice amount based on volumes handled at pre-

specified quality levels

A percentage of the savings or revenue improvement based on achieving or exceeding targets is given to the vendor; this is commonly referred to as gain-share. A variation of this mechanism is the risk/reward pricing method wherein the provider risks losing money if the agreed-on improvements are not achieved.

Tying the providers revenue to level of improvement of the performance of the outsourced function based on business metrics. Commonly, referred to as value pricing or business benefit pricing this arrangement generally involves changing the customers business processes.

Defining the potential for future business, motivating the provider to maintain a keen performance edge.

6. Process work-flow documentation A major concern among outsourcing and especially offshoring clients is the possibility of disruption of outsourcing workflow and hence the insistence on the presence of documented policies and procedures by the vendors for allocating transactions in the most likely scenarios including:

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a) Normal operations with forecasted transaction levels.

b) Abnormal conditions which may arise for a number of reasons including: i) Transaction volumes significantly above or below forecasted levels.

ii) Site, telecommunications, or system reduced availability/slowness or outage.

iii) Staffing levels well above or below scheduled levels (e.g., bad weather).

This documentation has three major components: (i) methodology for assessment of business risk impact (ii) back-up and recovery strategies and (iii) key personnel and supplies required.

7. Task work-flow documentation The objective of this control mechanism is to control variation within the performance of the individual tasks comprising the outsourced function across all shifts and work teams. Diagrammatic flow-charts are made during process transition itself and for every change in working made during the outsourcing lifetime detailing each step of the work to be carried out at. Commonly referred to as SIPOC (supplier-input-process-output-customer) charts these are made for various levels thus assuming a tree like structure. (an example of a typical SIPOC tree is given in the appendices). These flow-charts may be made by either party but necessarily require sign offs from each and very stringent procedures exist for making any changes in them.

8. Regular reporting This mechanism refers to the vendor reporting performance information as required by clients. Commonly referred to as daily, weekly, or monthly reports, key areas covered by these reports are:

tracking the timeliness of the implementation milestones

compliance accuracy regarding appropriate legal requirements

reports on status of adherence to targets regarding process metrics

A key observation here was the level of automation involved. Almost all the regular reports were automatically generated and sent to the clients email id by the software tools in the information system.

9. Regular meetings Both parties to the outsourcing relationship initiated frequent meetings or conference calls to discuss the performance status, issues and resolutions. Though mostly done following a pre-decided structure and schedule, impromptu meetings to resolve one-off escalations or incidents were not uncommon. During these meetings significant feedback was provided to the vendor team regarding their performance.

10. Site visits Both parties made arrangements for team members at the managerial levels to travel to each others sites not just for process training or transition but also to engender camaraderie and cooperation. This was considered a necessity during the initial stage of the relationship and at least annually. As one interviewee observed, I dont think theres any better measure of the relationship than seeing the guy and his peer sitting side by side at a meeting. You can tell from their body language that they are two members of the same team. Besides the client outsourcing manager or vendor manager who is often located at the outsourcing site, other members of the client team responsible for or users of the outcome of the outsourced process also make regular site visits. Often at these visits, client team members walk around the vendor site to informally gather first hand information about the tasks, activities, progress and issues in the outsourcing arrangement.

11. Business reviews In all four cases this was a quarterly incident. While reviews were done at a weekly/ monthly basis at different hierarchical levels of the client-vendor governance structure a QBR was the high point of the relationship. Reviewing performance to the required performance targets and plans, discussing anticipated program changes and communicating business strategies were the objectives of this exercise which saw top management representation from both sides.

A description from one of the interviewees summed up this control mechanism as: "At our quarterly business review sessions, we spend an entire day just going through the numbers. In addition, part of the evaluation is going through an analysis of a healthy relationship -- what's working and what's not working. We are very, very candid with the executives as well as with the operations people at about what our thoughts and views are, and we invite them to be just as candid back to us."

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12. Process audits All the three vendor sites we studied had a separate (outside the operations set-up) entity variously labeled as process excellence; compliance and quality control in their governance structures which was aimed at taking an unbiased external view of the operational capabilities. A major deliverable of this team was performing a comprehensive annual compliance audit of each process metrics performance relative to each of the requirements in the contract and related documents as well as industry benchmarks. Another objective of this process is the replication of best practices across the organization.

13. Process milestones Each business process outsourcing relationship goes through certain stages viz. transition, pilot, stabilization, ramp-up and continuous improvement, the last two being iterative. Each stage has an attached time frame, adherence to which controls the progress of the relationship.

14. Staffing and scheduling Aligning staff capacity with historical and forecasted future transaction arrival patterns is a key service deliverable of the vendor team. The mechanism used for this is a staffing plan that minimizes variation between arrival patterns and staff capacity made using workflow management (WFM) software such as IEX and Aspect.

15. Shrinkage management Shrinkage refers to the amount of scheduled time that is not realized because of absenteeism, sick/late time, training, coaching, team meetings, etc. that are not included in the work schedule. Vendors measure this time by staff category (e.g., by job type, organization level, etc.) at the entity level and at the program level for staff in customer related jobs to estimate the costs and impact of each on service, quality, and end-user satisfaction. The tactical management has targets established for minimizing shrinkage based on an understanding of these implications, other business requirements (e.g., internal transfers), and labor conditions. Attrition (employees being fired or resigning) levels are also tracked and minimized to ensure consistency in service quality offered to end users.

16. Ensuring data security Protection of patented or end-user details and other sensitive and proprietary data is a key component of the outsourcing service quality. Hence data security is ensured by (i) having a documented security policy that defines how access enterprise sensitive and proprietary data is to be protected (ii) implementation of a number of mechanisms such as using proprietary lines and encryption to transmit data; making removable computer drives, email capabilities or printers unavailable to non-managerial employees; disallowing visitor tours during working hours and having armed guards to protect the work area (iii) physical separation of work areas and employees serving different clients and (iv) conducting periodic checks to identify and prevent opportunities for security breaches.

17. Free gifts Vendor employees receive free client merchandise, and the workspace is decorated with colorful client memorabilia. This mechanism is aimed at creating belonging through direct links to an organizations (client) culture. As a senior manager from the vendor side mentioned these freebies create a sense of dual citizenship so that vendor employees remain deeply committed to their new team.

18. Special events Clients regularly fund and/or organize special events to mark important milestones in the organizations or relationships growth where the outsource vendor employees (including the ground level workforce) are given a chance to interact with and understand the employee culture of the client. For instance, an US based ISP in one of the sites of our study organized a five day workshop for the top ten performers of each outsourced process in both its captive and outsourced center in Goa. Such events are aimed at fostering clan control.

19. Certifications Both the vendors we studied had also acquired external quality assurance / performance management certifications such as BS 7799, ISO 9001:2000, COPC and eSCM and used their annual audits as a measure of the efficacy of the control systems set up.

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All of the above lead to the matrix shown in Table 2, which classifies the mechanisms identified as per the control modes identified through our literature review:

Control mode

Focus of control (identified from previous literature)

Typical mechanisms

(identified from previous literature)

Relevant control mechanisms observed in case study

Outcome control

Outputs (both final and interim) of a process

(Kirsch 1997)

Performance targets (Snell 1992, Eisenhardt 1985)

Interim milestones for a particular activity (Henderson and Lee 1992)

Specific project goals (Kirsch 1996)

Business reviews Financial controls Process metrics Process milestones

Behavior control

Process, or the means to goal achievement and controllees behaviors

(Jaworski and Maclnnis 1989, Kirsch 1996)

Specification of appropriate behaviors (e.g., development methodology)

Evaluation of behavior (Kirsch 1997) such as direct observation (e.g., placing client personnel on vendor premises) and other information systems (e.g., weekly progress reports, periodic meetings, or conference calls) (Eisenhardt 1985)

Ensuring data security

Process work-flow documentation

Regular meetings Regular reporting Site visits Staff skill control Staffing and

scheduling Task work-flow

documentation Transaction

monitoring

Clan control Promulgating common values, beliefs, and philosophy within group of individuals who share a set of common goals (Kirsch 1996)

Carefully selecting and socializing members (Boland 1979, Ouchi 1979, Orlikowski 1991)

Shared experiences, rituals, and ceremonies (Kirsch 1996, Ouchi 1980)

Business reviews Free gifts Regular meetings Site visits Special events Staff skill control

Self control The controllee determines both the goals and the actions through which they should be achieved (Henderson and Lee 1992)

The controllee sets standards for its own behavior, self-set project milestones and monitoring progress against these milestones

(Kirsch 1997)

Certifications Process audits Shrinkage

management Staff performance

management Staff skill control Staffing and

scheduling Transaction

monitoring

The above table throws up two significant conclusions. One is the multiplicity of mechanisms used to implement various control modes. Each mode is effected through more than one mechanism. For instance, business reviews, financial controls, process metrics and process milestones are used to implement outcome control. Conversely the same mechanism is used to implement more than one mode. Staff skill control defines acceptable behaviors to be followed by the client, restricts the entry of employees into the relationship and is an

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internal control mechanism for the vendor. Hence, this mechanism forms part of behavior, clan and self-control modes.

The other key finding is the multiplicity of controllers of the relationship. Not just the clients and vendors are involved in the structure, but also end-users (through user satisfaction measurement), external quality agencies (through provision of certification) and industry bodies (through insistence on particular levels of data protection done to maintain the image of the sector).

CONCLUSIONS This study makes a couple of substantive contributions to outsourcing literature. The first is an articulation of the mechanisms used by stake holders to implement behavior, clan, outcome and self control in business process outsourcing relationships. This articulation is important because it speaks to the issue of how multiple mechanisms constitute a portfolio of control modes. In addition, it aids future research by providing guidance for operationalizing modes of control. The second contribution is an understanding of the critical roles played by different stakeholders to control business process outsourcing relationships. The implication to practice is that managers need to cultivate a broad view of control. Successful BPO clients would need to go beyond direct, constraining control mechanisms to achieve their objectives and incorporate indirect and particularly enabling controls to instill their provider with the incentive to deliver high performance.

Avenues for future research include seeking clarity on the sufficient amount of control needed and what decides the appropriateness of a particular mechanism. Secondly, business process outsourcing relationships face a complex, dynamic environment, and the multiplicity of controllers and control modes contributes to that complexity. Future work could examine how various stakeholders structure their control portfolios to manage this complexity.

REFERENCES Academic literature 1. Anthony, R.N. (1965). Planning and control systems- A framework for analysis, Harvard Business School

Press, Boston.

2. Arnett, K. P. and Jones, M. C., Firms that Choose Outsourcing: A Profile, Information & Management, 2` (4), 1994, pp.179~188

3. Benko, C., If Information System Outsourcing is the Solution, What is the Problem ?, Journal of Systems Management, November 1992, pp.32~35

4. Boland, R.J. (1979). Control, Causality and Information System Requirements, Accounting, Organizations and Society, 259-272

5. Buchowicz, B. S., A Process Model of Make vs. Buy Decision Making: The Case of Manufacturing Software, IEEE Transactions on Engineering Management, 38 (1), 1991, pp.24~32

6. Buck-Lew, M., To Outsource or Not ?, International Journal of Information Management, 12 (1), 1992, pp.3~20

7. Carmel, E. 1999. Global Software Teams. Prentice-Hall, Englewood Cliffs, NJ.

8. Child, J., Information Technology, Organization, and the Response to Strategic Challenges, California Management Review, 30 (1), 1987, pp.33~50

9. Choudhury and Sabherwal, Portfolios of Control in Outsourced Software Development Projects, Information Systems Research Vol. 14, No. 3, September 2003, pp. 291314

10. Chua, W.F. 1988. Interpretive sociology and management accounting research: a critical review, Accounting, Auditing & Accountability Journal, 1: 59-79

11. Clark, T. D., Jr., Zmud, R. W. and McCray, G. E. (1995) "The Outsourcing of Information Services: Transforming the Nature of Business in the Information Industry," Journal of Information Technology, Vol. 10, pp. 221-237.

12. Coase, R. H. (1937). "The Nature of the Firm," Economica, Vol. 4, No. November, pp. 386-405.

13. Fitzgerald and Willcocks (1994). Contracts and Partnerships in the outsourcing of IT. 15th International Conference on Information Systems, Vancouver, Canada, ICIS

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14. Flamholtz, E.G. 1983. Accounting, budgeting and control systems in their organizational context: theoretical and empirical perspectives. Accounting, Organizations and Society, 8: 153-169.

15. Gewald, H., K. Wllenweber and T. Weitzel (2006). "The Influence of Perceived Risks on BankingManagers' Intention to Outsource Business Processes - A Study of the German Banking and finance Industry." Journal of Electronic Commerce Research 7(2): 78-96.

16. Glaser, B. and Strauss, A. (1967). The discovery of grounded theory. Chicago: Aldine.Green and Welsh 1988)

17. Grover, V.; Cheon, M. J.; and Teng, J.T.C., The Effect of Service Quality and Partnership on The Outsourcing of Information Systems Functions, Journal of Management Information System, 12 (4), 1996, pp.89~116

18. Gupta, U. G. and Gupta, A., Outsourcing The IS Function: Is It Necessary for Your Organization?, Information Systems Management, Summer 1992, pp.44~50

19. Henderson, J. C., S. Lee. 1992. Managing I/S design teams: A control theories perspective. Management Sci. 38(6) 757777.

20. Hofstede, G. 1981. Management Control of Public and Nor-for-Profit Activities.Accounting, Organizations and Society 6 (3):193 - 211.

21. Hopwood, A.G. 1983. On trying to study accounting in the contexts in which it operates, Accounting, Organizations and Society, 8: 287-305.

22. Hopwood, A. G. 1996. Looking across rather than up and down: on the need to explore the lateral processing of information. Accounting, Organizations and Society, 21: 589-590.

23. Kalakota, R. and Robinson, M. 2004. Offshore Outsourcing: Business Models, ROI and Best Practices. Mivar Press.

24. Kern, T., Lacity, M. and Willcocks, L. (2001). Application Service Provision, Englewood Cliffs: Prentice Hall.

25. Kern, T., Lacity, M. C. and Willcocks, L. (2002). Net Sourcing: Renting Business Applications and Services Over a Network, Upper Saddle River, NJ: Prentice-Hall..

26. Kim, J. S. 1984. Effect of behavior plus outcome goal setting and feedback on employee satisfaction and performance. Acad. Management J. 27 139149.

27. Klepper, R. (1995). "The Management of Partnering Development in I/S Outsourcing," Journal of Information Technology, Vol. 10, pp. 249-258.

28. Klepper, R. and Hoffmann, N. (2000). "Assimilation of New Information Technology and Organized Culture: A Case Study," WIRTSCHAFTSINFORMATIK, Vol. 42, No. 4, pp. 339-346.

29. Levina, N. and Ross, J. (2003). "From the Vendor's Perspective: Exploring the Value Proposition in IT Outsourcing," MIS Quarterly, Vol. 27, No. 3, pp. 331- 364.

30. Loh, L. and Venkatraman, N. (1995). "An Empirical Study of Information Technology Outsourcing: Benefits, Risks, and Performance Implications," Proceedings of the 16th International Conference on Information Systems, Amsterdam, The Netherlands, pp. 277-288.

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INVENTORY MODELING FOR DETERIORATING ITEMS: FUNDAMENTAL VIEW

Hetal R. Patel Assistant Professor, Mathematics Department, U. V. Patel College of Engineering, Ganpat University, Gujarat

ABSTRACT This article derives an inventory model for deteriorating items with known and continuous demand and no shortages allowed. Optimal ordering quantity and cycle time is computed. Three numerical examples were also solved. Moreover, the derived model was subject to sensitivity analysis. The sensitivity analysis is performed by changing each of the parameters by -75%, -50%, -25%, +25%, +50% and +75% taking one parameter at a time to understand the behavior of the model.

Key words: EOQ, deteriorating, demand, cycle time, shortages

INTRODUCTION General trends in globalization and fierce competition in todays business world forces businesses, irrespective of size, to endeavor towards more effective methods for handling inventory. In fact, inventory modeling is one of the most developed fields of operations research. Monks (1987) put inventory as idle resources that possess economic value. An inventory is a list of items held in stock (Waters, 2003, p. 4). Looking at various product characteristics, products perishability is an important aspect of inventory control.

Perishable goods are classified as (a) Amelioration and (b) deterioration. More simply, obsolescence is a loss of value of a product due arrival of new and better product (Goyal and Giri, 2001). While, deterioration is decay, spoilage, loss of utility with finite shelf life and start to deteriorate once they are produced (Shah and Shukla, 2009). Moreover, Decay, change or spoilage that prevent the items from being used for its original purpose are usually termed as deterioration (Moon, Giri and Ko, 2005) and included Food items, pharmaceuticals, photographic film, chemicals and radioactive substances as deteriorating products.

Practically, stocks related decisions in inventory management for perishable goods are complex. It is influenced by deterioration rate and allied cost and resulting backlogging due to deterioration (Abad, 2003). Padmanabhan and Vrat (1995) considered an EOQ model for perishable items with stock-dependent demand. Furthermore, Chang and Dye (1999) developed an inventory model in which the proportion of customers who would like to accept backlogging is the reciprocal of a linear function of the waiting time.

In inventory literature, many studies are available considering deterioration. Moreover, in the literature itself, many scholars have classified the inventory research for deteriorating products into two major categories (a) decay modes and (b) finite lifetime models (Ghare and Schrader, 1963; Raafat, 1991; Weatherford et al., 1992; Liu et al., 1999; Panda et al., 2009). Decay models consider the products which deteriorate from the very beginning and finite lifetime models consider the products which start to deteriorate after a certain time.

In this chapter, an inventory model is developed considering deteriorating items. The model also assumes constant demand and known lead time. This means inventory available is exactly sufficient to cover the demand during the lead time after that an order is placed. The inventory model for deteriorating items is different from basic inventory model on only one point: inventory is assumed to deteriorate at a constant rate. In addition to this, this model also assumes the situation wherein no demand is unsatisfied. Simply, this model does not allow any shortages. Section 2 covers assumptions and notations followed by mathematical derivation in section 4. Numerical analysis is presented in section 5 followed by sensitivity analysis in last section.

ASSUMPTIONS AND NOTATIONS In inventory modeling literature, it has been noted that there is no standard set of notations that creates significant difficulties. Henceforth, this study will use notation here that makes it easier to remember what the different symbols represent.

Notations D the demand per year

s the unit selling price

A the fixed cost of placing and receiving an order

P the cost of purchasing a unit

h the cost of holding a unit in inventory for a year

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the rate of deterioration

Q the order quantity

T the time between orders or the length of an order cycle (replenishment time)

I the maximum inventory level if Q is the order quantity; with being an average inventory level over the year

ASSUMPTIONS The essence of the assumptions is to make the complexity of the inventory system malleable to mathematical modeling. The assumptions are selected to give accurate approximation of real life inventory system for product. The following assumptions are used in developing the model:

(1) The inventory system under consideration deals with single item. This assumption ensures that a single item is isolated from other items and thus preventing item interdependencies.

(2) The demand rate is known, constant and continuous.

(3) The time horizon is infinite and a typical cycle length of T for planning schedule is considered.

(4) A constant fraction of the on hand inventory deteriorates per unit time. is rate of deterioration.

(5) The lead time is zero.

(6) The replenishment is instantaneous.

(7) Deteriorated unit is not repaired or replaced during a given cycle.

(8) Costs involved (such as holding cost, ordering cost etc.) are remaining constant over a period of time.

(9) Shortages are not allowed.

Motivated by the on-going research on inventory models for deteriorating items, purpose in this study is to provide optimal inventory policy for the EOQ model with constant demand and no shortages.

MATHEMATICAL FORMULATIONS A typical one time-inventory cycle is developed based on following computations:

Let be the inventory level of the system at . The inventory level decreases owing to demand as well as deterioration. Thus, the change of inventory level can be represented by the following differential equation over the period

The solution of the above differential equation is given as per following:

Above equations can be written as where

Now

Where and

Hence using equation (2.2.2), one get

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Here one has initial condition, Byputting these values in equation (2.2.3), one has

Henceinventory level at any instant of time t is

Also at boundary condition

By equation (2.2.4),

In order to calculate economic order quantity, first of all, total cost is computed. For EOQ model of deteriorating products, following costs are considered:

(1) Order cost, (2) Purchase cost, (3) Holding cost during the time period 0 to and to T,

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Hence the total cost of an inventory system is given by

Total cost = Ordering cost + Purchase cost + Holding cost. Using equations (3.6) to (3.8),

Differentiating this equation w. r. to Q results into;

To check whether the cost is minimum or not, it is required to take second order differential w.r.to Q which gives;

From the equation (3.11), it is visible that the second order differential equation gives positive value. Hence, the equation is minimum at the given point. To determine equation (3.10) is equating with zero. Hence, one gets;

NUMERICAL ANALYSIS To solve different scenarios of assumptions, three examples have been solved to demonstrate the application of approach. The variable part is the different situations of the deterioration rates ( ). Example 1 is based on situation consisting . Example 2 is based on situation consisting and example 3 is based on the situation consisting

Example 1:for numerical experiment, is considered. Let the values of other parameters for his inventory model be fixed cost per order A= $ 300; annual demand D=700 units; Unit cost of producing an item P= $ 5; annual holding cost per dollar value h=35% of purchase value ($). Under the given parameter values and according to the equation (3.12 and 3.5), respective optimal values of Q* and T* are obtained.

Q*= 623.89 units and T*=0.737 years

Example 2: for numerical experiment, is considered. Let the values of other parameters for his inventory model be fixed cost per order A= $ 300; annual demand D=700 units; Unit cost of producing an item P= $ 5; annual-0 holding cost per dollar value h=35% of purchase value ($). Under the given parameter values and according to the equation (3.12 and 3.5), optimal values of Q* and T* are obtained.

Q*= 559.03 units and T*=0.783 years

Example 3: for numerical experiment, is considered. Let the values of other parameters for his inventory model be fixed cost per order A= $ 300; annual demand D=700 units; Unit cost of producing an item P= $ 5; annual holding cost per dollar value h=35% of purchase value ($). Under the given parameter values and according to the equation (3.12 and 3.5), optimal values of Q* and T* are obtained.

Q*= 551.89 units and T*= 0.788 years

SENSITIVITY ANALYSIS Next step is to investigate the effect of changes in parameter values in model such as A, D, P, h, and on model decision variables such as economic order quantity (Q*) and optimal cycle time (T*). For this, except , all the parameter values are kept constant in this model. The sensitivity analysis is performed by changing each

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of the parameters by -75%, -50%, -25%, +25%, +50% and +75% taking one parameter at a time. The results are presented in table 5.1.

Table 5.1: Effects of changes in parameter values in inventory model (=0.5)

Parameters PCPV (%) Change in decision variables

Q* T*

A

-75% 376.32 0.476

-50% 483.46 0.593

-25% 560.91 0.674

+25% 677.92 0.789

+50% 726.00 0.840

+75% 769.46 0.876

D

-75% 264.10 1.120

-50% 404.67 0.912

-25% 520.94 0.806

+25% 718.04 0.687

+50% 805.59 0.649

+75% 888.30 0.618

P

-75% 1056.25 1.12

-50% 809.15 0.91

-25% 694.6 0.80

+25% 574.43 0.687

+50% 537.14 0.65

+75% 507.63 0.62

-75% 569.81 0.77

-50% 587.95 0.76

-25% 605.96 0.75

+25% 641.71 0.73

+50% 659.36 0.71

+75% 676.80 0.70

Based on the results of Table 5.1, the conclusions are briefly stated as follows:

(1) It is observed from table 5.1 that increase in ordering cost A increasesoptimal quantity Q*. Increase in ordering cost also increases optimal cycle time T*. The obtained results show thatquantity function is very sensitive to the ordering cost when decreasing and less sensitive to the ordering cost when it is increasing. Simply, it is reflective that small negative change in A results into large change in Q*; while small positive change in A results into not so large change in Q*. For cycle time, it is sensitive to the changes when A decreases and less sensitive when A increases.

(2) Similarly as D increases, the economic order quantity Q* increases and cycle time T* decreases. When reducing the demand, the change in Q* is very high showing higher sensitivity while less sensitive when increasing the value of demand. For cycle time T*, it is sensitive to the changes when D decreases and less sensitive when D increases.

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(3) Considering the dependency of holding cost per unit on unit price of item, purchase price is considered for sensitivity analysis.It is observed that an increase in purchase price results into decrease in Q* and also decrease in T*. It is reflective that small negative change in P results into large change in Q*; while small positive change in P results into not so large change in Q*. So, it is highly sensitive when P decreases and less sensitive when P increases. Similar pattern is displayed in T*.

(4) Table also reflects that an increase in rate of deterioration (), there is an increase in Q* and decrease in T*. For sensitization, the proportion change in Q* and T* is equivalent to the proportion change in . Thus, optimal quantity function and cycle time function is less sensitive to the changes in rate of deterioration ().



Q* T*

A

-75% 350.46 0.49

-50% 442.51 0.62

-25% 507.31 0.71

+25% 602.75 0.84

+50% 641.13 0.89

+75% 675.46 0.94

D

-75% 223.50 1.24

-50% 353.35 0.98

-25% 462.00 0.86

+25% 648.00 0.73

+50% 731.19 0.68

+75% 809.96 0.65

P

-75% 894.00 1.24

-50% 706.64 0.98

-25% 616.25 0.86

+25% 518.50 0.73

+50% 487.60 0.68

+75% 462.88 0.65

-75% 553.53 0.79

-50% 555.43 0.785

-25% 557.24 0.784

+25% 560.87 0.781

+50% 562.68 0.780

+75% 564.49 0.779


(1) It is observed from table 5.2 that increases in ordering cost A increases optimal quantity Q*. Increase in ordering cost also increases optimal cycle time T*. The obtained results show that quantity function is very sensitive to the ordering cost when decreasing and less sensitive to the ordering cost when it is increasing. Simply, it is reflective that small negative change in A results into large change in Q*; while Q* is less sensitive to positive change in A. The pattern is same in case on cycle time function too.

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(2) Similarly as D increases, the economic order quantity Q* increases and cycle time T* decreases. When reducing the demand, the change in Q* is very high showing higher sensitivity while less sensitive when increasing the demand. For cycle time T*, it is sensitive to the changes when D decreases and less sensitive when D increases.

(3) It is observed that an increase in purchase price results into decrease in Q* and also decrease in T*. It is reflective that small negative change in P results into large change in Q*; while small positive change in P results into not so large change in Q*. So, it is highly sensitive when P decreases and less sensitive when P increases. Similar pattern is displayed in T*.

(4) Table also reflects that an increase in rate of deterioration (), there is a very stiff increase in Q* and decrease in T*. For sensitization, the proportion change in Q* and T* is equivalent to the proportion change in indicating in-sensitive nature.



Q* T*

A

-75% 347.68 0.50

-50% 438.03 0.63

-25% 501.45 0.72

+25% 594.5 0.85

+50% 631.82 0.90

+75% 665.15 0.95

D

-75% 219.1 1.25

-50% 347.71 0.99

-25% 455.58 0.867

+25% 640.44 0.73

+50% 723.21 0.688

+75% 801.4 0.65

P

-75% 876.22 1.25

-50% 695.37 0.99

-25% 607.45 0.867

+25% 512.4 0.73

+50% 482.14 0.688

+75% 457.98 0.65

-75% 551.89 0.7883

-50% 551.89 0.7882

-25% 551.89 0.7881

+25% 551.89 0.7880

+50% 552.00 0.7880

+75% 552.00 0.7880


(1) Table 5.3reveals that increases in ordering cost A increases optimal quantity Q*. Increase in ordering cost also increases optimal cycle time T*. The obtained results show that quantity function is very sensitive to the ordering cost when decreasing and less sensitive to the ordering cost when it is increasing. Simply, it is

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reflective that small negative change in A results into large change in Q*; while Q* is less sensitive to positive change in A. The pattern is same in case on cycle time function too.

(2) Similarly as D increases, the economic order quantity Q* increases and cycle time T* decreases. When increasing or reducing the demand, the change in Q* is very high showing higher sensitivity. For cycle time T*, it is sensitive to the changes when D decreases and less sensitive when D increases.

(3) It is observed that an increase in purchase price results into decrease in Q* and also decrease in T*. It is reflective that small negative change in P results into large change in Q*; while small positive change in P results into not so large change in Q*. So, it is highly sensitive when P decreases and less sensitive when P increases. Similar pattern is displayed in T*.

(4) Table also reflects that an increase in rate of deterioration (), there is a negligible increase in Q* and negligible decrease in T*. the change is negligible reflecting no effect of change in . For sensitization, the proportion change in Q* and T* is equivalent to the proportion change in indicating almost in-sensitive relationship.

CONCLUSION The inventory model for deteriorating products with constant demand is studied here. It is meant for decision maker to plan the stocking of inventory. The sensitivity analysis refers that the model is sensitive to rate of change of demand, ordering cost and less sensitive to the very low rate of deterioration i.e. 0.001 value. Utilization of this model offers great insights relating to optimal quantity which is sensitive to inventory cost elements used in this study.

REFERENCES 1. Abad, P. L. (2003),Optimal pricing and lot-sizing under conditions of perishability, finite production and

partial backordering and lost sale European Journal of Operational Research, 144: 677-685.

2. Chang, H. J. and Dye, C. Y. (1999), An EOQ model for deteriorating items with time varying demand and partial backlogging, Journal of the Operational Research Society, 50: 11761182.

3. Ghare, P. M. and Schrader, G. P. (1963), A model for an exponentially decaying inventory, Journal of Industrial Engineering, 14(5).

4. Goyal, S. K. and Giri, B. C. (2001), Recent Trends in Modelling of Deteriorating Inventory, European Journal of Operational Research, 134: 1, 1-16.

5. Liu, L. and Shi, D. (1999): An (S.S) model for inventory with exponential lifetimes and renewal demands. Naval Research Logistic, 46, 3956.

6. Monks, J.G., (1987), Operations Management. 3rd Edn., McGraw-Hill Book Co., New York, pp: 236-334.

7. Moon, I., Giri, B. C. and Ko, B. (2005), Economic order quantity models for ameliorating/deteriorating items under inflation and time discounting, European Journal of Operational Research, 162:773-785.

8. Padmanabhan, G. and Vrat, P. (1995), EOQ models for perishable items under stock dependent selling rate, European Journal of Operational Research, 86:281292.

9. Panda, S., Saha, S. and Basu, M. (2009), An EOQ model for perishable products with discounted selling price and stock dependent demand, CEJOR. 17: 31-53.

10. Raafat, E. (1991), Survey of Literature on continuously deteriorating inventory model, Journal of Operational Research Society, 42:27-37.

11. Shah, N.H. and Shukla, K.T. (2009), Deteriorating inventory model for waiting time partial backlogging, Applied Mathematical Sciences, 3(9): 421-428.

12. Waters, D. (2003),Inventory control and management, John Wiley and Sons Ltd, Replika Press Pvt. Ltd., India.

13. Weatherford, L. R. and Bodily, S. E. (1992), A taxonomy and research Overview of Perishable asset revenue management: yield management, overbooking, and pricing. Operations Research, 40: 831-844.

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ISSN 2394 - 9554

AN OVERVIEW OF DATA WAREHOUSING AND OLAP OPERATIONS

Chandrakant Dewangan1, Dileshwar Dansena2, Mili Patel3 and Pooja Khemka4 Student1,2 and Faculty3,4 Kirodimal Institute of Technology, Raigarh (C.G.)

ABSTRACT Data-driven decision support systems, such as data warehouses can serve the requirement of extraction of information from more than one subject area. Data warehouses standardize the data across the organization so as to have a single view of information. Data warehouses can provide the information required by the decision makers. Developing a data warehouse for educational institute is the less focused area since educational institutes are non-profit and service oriented organizations. In present day scenario where education has been privatized and cut throat competition is prevailing, institutes needs to be more organized and need to take better decisions. Institutes enrollments are increasing as a result of increase in the number of branches and intake. Now a day, any reputed Institutes enrollments count in to thousands. In view of these factors the challenges for the management are meeting the diverse needs of students and facing increased complexity in academic processes. The complexity of these challenges requires continual improvements in operational strategies based on accurate, timely and consistent information. The cost of building a data warehouse is expensive for any educational institution as it requires data warehouse tools for building data warehouse and extracting data using data mining tools from data warehouse. The present study provides an option to build data warehouse and extract useful information using data warehousing and data mining open source tools. In this paper we have explored the need of data warehouse / business intelligence for an educational institute, the operational data of an educational institution has been used for experimentation. The study may help decision makers of educational institutes across the globe for better decisions.

Keywords: Data warehouse architecture, Types of OLAP Servers, LAP Operations, OLAP vs. OLTP

INTRODUCTION According to W. H. Inman A data warehouse is a subject-oriented, integrated, time-variant, and nonvolatile collection of data in support of managements decision-making process.

Subject Oriented - The Data warehouse is subject oriented because it provide us the information around a subject rather the organization's ongoing operations. These subjects can be product, customers, suppliers, sales, revenue etc. The data warehouse does not focus on the ongoing operations rather it focuses on modeling and analysis of data for decision making.

Integrated - Data Warehouse is constructed by integration of data from heterogeneous sources such as relational databases, flat files etc. This integration enhance the effective analysis of data.

Time-Variant - The Data in Data Warehouse is identified with a particular time period. The data in data warehouse provide information from historical point of view.

Non Volatile - Non volatile means that the previous data is not removed when new data is added to it. The data warehouse is kept separate from the operational database therefore frequent changes in operational database are not reflected in data warehouse.

Metadata - Metadata is simply defined as data about data. The data that are used to represent other data is known as metadata. For example the index of a book serves as metadata for the contents in the book. In other words we can say that metadata is the summarized data that lead us to the detailed data.

DATA WAREHOUSE ARCHITECTURE

Fig.1 Architecture of Warehouse

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ISSN 2394 - 9554

Architecture is the proper arrangement of the components. You build a data warehouse with software and hardware components. To suit the requirements of your organization you arrange these building blocks in a certain way for maximum benefit. We also want to review specific issues relating to each particular component.

1. SOURCE DATA COMPONENT Source data coming into the data warehouse may be grouped into four broad categories, as discussed here.

(a) Production Data. This category of data comes from the various operational systems of the enterprise. Based on the information requirements in the data warehouse, you choose segments of data from the different operational systems. While dealing with this data, you come across many variations in the data formats. You also notice that the data resides on different hardware platforms. Further, the data is supported by different database systems and operating systems. This is data from many vertical applications and integrates the pieces into useful data for storage in the data warehouse.

(b) Internal Data. In every organization, users keep their private spreadsheets, documents, customer profiles, and sometimes even departmental databases. This is the internal data, parts of which could be useful in a data warehouse. If your organization does business with the customers on a one-to-one basis and the contribution of each customer to the bottom line is significant, then detailed customer profiles with ample demographics are important in a data warehouse Although much of this data may be extracted from production systems, a lot of it is held by individuals and departments in their private files. You cannot ignore the internal data held in private files in your organization. It is a collective judgment call on how much of the internal data should be included in the data warehouse.

(c) Archived Data. Operational systems are primarily intended to run the current business. In every operational system, you periodically take the old data and store it in archived files. The circumstances in your organization dictate how often and which portions of the operational databases are archived for storage. Some data is archived after a year. Sometimes data is left in the operational system databases for as long as five years. Many different methods of archiving exist. There are staged archival methods. At the first stage, recent data is archived to a separate archival database that may still be online.

(d) External Data. Most executives depend on data from external sources for a high percentage of the information they use. They use statistics relating to their industry produced by external agencies. They use market share data of competitors. They use standard values of financial indicators for their business to check on their performance. For example, the data warehouse of a car rental company contains data on the current production schedules of the leading automobile manufacturers. This external data in the data warehouse helps the car rental company plan for their fleet management.

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