S. Field - Dissertation E-Copy.docx

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Sebastian Field

Rural MICE Event Impact Analysis: A case study investigation of the socio-economic impacts of MICE

events upon a rural host economy

2015/2016

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Rural MICE Event Impact Analysis: A case study investigation of the socio-economic impacts of MICE

events upon a rural host economy

Sebastian Field: G20614827

Event Management BA (HONS)

Date of submission: 11 April 2016

Name of supervisor: Phil Stone

Division of Sports Studies, Management

Word count: 11,125

This dissertation is an original and authentic piece of work produced in fulfilment of my degree

regulations. I have fully acknowledged and referenced all secondary sources. I have read and

understood the Academic Regulations and I am fully aware of any breach of them.

Signed:

Date: 09/04/2016

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Abstract

Much research has been conducted regarding the socio-economic impacts of MICE events in urban

areas, yet little is to be found regarding their impacts in rural locations. This deductive research

contributes toward the filling of this gap in the literature using MICE events held at the Birnam Arts

and Conference Centre in the rural Scottish town of Dunkeld & Birnam as a case study. After

reviewing various approaches to economic impact analysis, this research focuses on the direct

impact; also calculating direct leakage and switching costs. Social-economic frameworks developed

by Wood (2005) and EventIMPACTS (2010e) were combined to create a new framework in this

research which can be replicated for future research in other rural locations. Results showed rural

socio-economic impacts to largely mirror their urban counterparts and be of both social and economic

value to the host economy, although some significant social inconveniences were present.

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Acknowledgements

This dissertation has been some time in the making and comprises a significant part of my

undergraduate degree. Its completion would not have been possible without a great deal of

assistance from others, to whom I owe much credit. There are many whom I could thank, but some

individuals deserve particular recognition. I would first like to thank Dr Phil Stone, my dissertation tutor

at the University of Central Lancashire, for his ongoing assistance, insight, critique and support. Many

times I entered his office in a panic, and left feeling reassured. I would also like to thank Stuart Flatley

and the Birnam Arts and Conference Centre management for their assistance, cooperation, patience

and for allowing me to conduct research at their venue. Without their help, none of this research

would have been possible. Finally, I would like to thank my wife, Danielle, to whom I have been

happily married for 2 years. I am grateful for her ongoing patience, for the times she pushed me to

stay up till the early hours working when necessary, and for the belief she has in me. There are many

others friends, family members, colleagues, university lecturers and associates who have contributed

to my development and growth during the academic chapter of my life. They know who they are, and I

am grateful to all of them.

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Contents

List of Tables ix

List of Figures x

List of Appendices xii

List of Abbreviations xiii

Chapter 1: Introduction & Background 1

1.1 Introduction & Background

1

1.2 Research Rationale 2

1.3 Research Aims & Objectives

3

1.4 Research Design

3

1.5 Research Limitations

4

Chapter 2 - Literature Review: Economic Impact Analysis

5

2.1 Introduction

5

2.2 Economic Impacts of MICE Events

5

2.3 A Methodological Review of Economic Event Impacts Analysis

7

2.4 Chapter Summary

11

Chapter 3 - Literature Review: Social Impact Analysis

12

3.1 Social Impacts

12

3.2 MICE Event Impact Analysis as part of Tourism Planning & Destination Development

14

3.3 Chapter Summary

15

Chapter 4 - Research Methods & Methodology

16

4.1 Introduction

16

4.2 Review of Socio-Economic Impact Analysis Models

16

4.2.1 Underlying Methodological Trends within the Literature 17

4.3 Methodology 17

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4.4 Data Type: Qualitative vs Quantitative

18

4.5 Definition of Host Economy: Dunkeld & Birnam (D&B) & Birnam Arts & Conference Centre (BACC)

19

4.5.1 What is ‘Rural’? 20

4.6 Research Design: Data Collection & Questionnaire Surveys 21

4.6.1 Research Design: Questionnaire Survey 1 21

4.6.2 Research Design: Questionnaire Survey 2 22

4.6.3 Research Design: Questionnaire Survey 3

22

4.6.4 Research Design: BACC Financial Data Collection 22

4.7 Sampling Method

22

4.7.1 Questionnaire 1 - Sampling Method & Selection 23



4.8 Data Collection Period 24

4.9 Pilot Study 25

4.10 Analysis Methods 25

4.11 Reliability, Validity & Limitations 28

Chapter 5 - Results & Analysis 30

5.1 Introduction 30

5.2 Perceived Economic Impact on Local Business Owners

30

5.2.1 Perceived Economic Impact on Local Business Owners: Results

30

5.2.2 Perceived Economic Impact on Local Business Owners: Analysis

34

5.3 Economic Impact of Delegate Expenditure and BACC Revenue

35

5.3.1 Economic Impact: Results

36

5.3.2 Economic Impact: Analysis

45

5.4 Resident Attitudes Toward and Perceptions of BACC MICE Events

47

5.4.1 Resident Attitudes Toward and Perceptions of BACC MICE Events: Results

47

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5.4.2 Public Attitudes Toward and Perceptions of BACC MICE Events:

Analysis

52

5.5 Delegate Perceptions of the D&B Host Destination

53

5.5.1 Delegate Perceptions of the D&B Host Destination: Results

53

5.5.2 Delegate Perceptions of the D&B Host Economy: Analysis

55

5.6 Chapter Summary

55

Chapter 6 – Conclusion

56

6.1 Introduction

56

6.2 Summary of Main Finding

56

6.2.1 Objective 1 – Economic Impact Analysis

56

6.2.2 Objective 2 – Delegate Perceptions of D&B as a Tourist Destination

57

6.2.3 Objective 3 - Perceived Economic Impacts of BACC MICE Events on Local Business-Owners

57

6.2.4 Objective 4 - To investigate general public attitudes toward and perceptions of BACC MICE events

58

6.3 Research Contributions

58


58

6.5 Suggestions for Future Research

59

6.6 Chapter Summary

60

References 61 Appendices 69

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1.1 Research Objectives 3

3.1 A Selection of Possible Intangible Social & Economic Costs &

Benefits resulting from MICE events

13

4.1 Scottish Government Urban – Rural Classification (TSG, 2014) 20

4.2 Example Formula for Delegate Expenditure Calculations

26

4.3 Example Formula for BACC Financial Calculations

27

4.4 Total Economic Injection & Economic Injection Per Delegate

28

5.1 Business Owners’ Perception of BACC MICE Event Impact on

Short-Term Turnover

33

5.2 Business Owners’ Perception of Impact Event Impact Long-Term Turnover

33

5.3 BACC MICE Event Delegate Expenditure, Leakage & Switching (February

2016)

37

5.4 BACC Revenue & Leakage (February 2016)

40

5.5 Total February Economic Injection & Economic Injection Per Delegate

43

5.6 BACC MICE Events Monthly & Annual Economic Injection Estimates (2014 –

2015 tax year)

44

5.7 Resident Perceptions of BACC MICE Event Impact on Noise Levels, Crowding

Levels, Crime Levels and Property Value

47

5.8 The Extent to which Residents Perceive Social Benefits & Inconveniences to

be positively or negatively impacted by BACC MICE Events

52


56

6.2 Research Limitations 59

List of Tables

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List of Figures

2.1 How Event-Related Expenditure Filters through the Host Economy: The

Multiplier Effect

6

2.2 Types of Economic Impact

8

2.3 Direct Impact Factors for Calculation 9

2.4 Factors for Calculation in an Economic Multiplier

10

3.1 Maslow’s Hierarchy of Needs

14

4.1 Definition of Host Economy: Dunkeld & Birnam (D&B) & Birnam Arts &

Conference Centre (BACC)

19

5.1 Business Owners' Perceptions of the Impact of BACC MICE Events on their

Businesses

31

5.2 Businesses which perceive an impact on their business from BACCC MICE

events

31

5.3 Businesses which perceive no impact on their business from BACCC MICE

events

32

5.4 Business Owners’ Further Thoughts and Opinions Regarding the Relationship

between BACC MICE Events and Local Business

34

5.5 BACC MICE Event Delegate Accommodation & Non-Accommodation

Expenditure

38

5.6 BACC MICE Event Delegate Non-Accommodation Leakage, Switching and

D&B-Retained Expenditure

38

5.7 Total BACC MICE Event Delegate Leakage, Switching & D&B-Retained

Expenditure

39

5.8 Proportion of BACC Room hire Leakage to D&B-Retained Room hire Revenue

41

5.9 Proportion of BACC Room hire Leakage to D&B-Retained Room hire Revenue

41

5.10 Total Estimated D&B-Retained BACC Room hire & Catering Revenue

42

5.11 Total Estimated BACC Revenue: D&B-Retained Revenue & Leakage

42

5.12 Total Estimated BACC Revenue: D&B-Retained Revenue & Leakage 43

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5.13 Total Estimated BACC Revenue: D&B-Retained Revenue & Leakage

44

5.14 Average monthly High Season & Low Season D&B-Retained Economic

Injection

45

5.15 Resident Perceptions of the BACC MICE Event Impact on D&B Congestion

Levels

48

5.16 Resident Perceptions of the BACC MICE Event Impact on Quality of Life

48

5.17 Resident Perceptions of the BACC MICE Event Impact on Social and

Community Ties

49

5.18 Resident Perceptions of the BACC MICE Event Impact on Local Infrastructure

49

5.19 The Extent to which D&B Residents Agree that BACC MICE Events Support

Local Business

50

5.20 The Extent to which D&B Residents Agree that BACC MICE Events Support

Tourism in D&B

50

5.21 D&B Residents’ Further Thoughts, Feelings or Opinions regarding BACC

MICE Events

51

5.22 BACC MICE Event Delegate Free Responses: Impression of D&B

54

5.23 Number of BACC MICE Event Delegates who would Consider Returning to

D&B for a Personal Holiday

54

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List of Appendices

Appendix A: Dunkeld & Birnham

69

Appendix B: Birnam Arts & Conference Centre 70

Appendix C: Switching & Leakage 71

Appendix D: Input – Output Multiplier (I-O) Model

72

Appendix E: Computer-Generated Equilibrium (GCE) Model

73

Appendix F: Social Accounting Matrix (SAM)

74

Appendix G: Cost - Benefit Analysis (CBA) Model

75

Appendix H: EventIMPACTS Model Developers

76

Appendix I: Closed, Recall, Process & Open-Ended Questions (SYN, 2014) 77

Appendix J: Questionnaire Survey 1: Business Owners’ Perceptions

78

Appendix K: Questionnaire 2 - Delegate Expenditure & Perception of Host

Economy

79

Appendix L: Questionnaire 3 – Resident Perceived Social Impacts

81

Appendix M: Finite Population Correction Factor

82

Appendix N: BACC Delegate Numbers

83

Appendix O: Pilot Study

84

Appendix P: Questionnaire 1 Business Types

85

Appendix Q: Questionnaire Survey 2 Data Set

86

Appendix R: Questionnaire Survey 1 Economic Impact Data Set

89

Appendix S: Questionnaire Survey 3 Data Set

92

Appendix T: Delegate Perceptions of D&B - Data Set 100

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List of Abbreviations

ROI: Return on Investment

D&B: Dunkeld & Birnam

BACC: Birnam Arts & Conference Centre

DEA: Direct Expenditure Approach

EIA: Economic Impact Analysis

SET: Social Exchange Theory

B2B: Business to Business

MICE: Meetings, Incentives, Conferences, Exhibitions

I-O: Input–Output (multiplier model)

ENCORE: ENCORE Festival & Event Evaluation Toolkit

HMRC: Her Majesty’s Revenue & Customs

SME’s: Small – Medium Enterprises

VAT: Value Added Tax

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Chapter 1

Introduction & Background

1.1 Introduction & Background

Considerable research attention is paid to the economic, social, cultural and environmental

impacts of events worldwide due to their powerful and far-reaching effects upon

stakeholders and the local economy (Getz, 2007; Shone & Parry, 2013; Allen et al., 2008).

The majority of this research is concentrated upon sporting and other mega-events (e.g.,

Jackson, 2013; Burnes & Mules, 1986; Lilley & De Franco, 2003; Mair, 2012; Motorsport

Association, 2000; Jones, 2001; Giesecke & Madden, 2011; Jory & Boojiawon, 2011) with

considerably less research attention being paid to MICE events, the term under which

summits, meetings, conferences, assemblies, conventions, congresses, AGMs, briefings,

trainings and incentives, amongst others, can be included (Rogers, 2013). The past three

decades have seen a large global growth of the relatively young MICE events industry

(Rogers, 2013; Schlenker et al., 2010; Lee, 2006). It has become one of the fastest growing

(Bernini, 2009) and most economically valuable segments of the global tourism industry

(Van der Wagen & White, 2010).

This industry growth has prompted an increase in research attention, primarily directed at

larger-scale MICE events such as large conferences, conventions, exhibitions and meetings

in urban areas (e.g., Dwyer et al., 2000a; Dwyer et al., 2000b; Braun, 1992; Morris, 2014;

Grado et al., 1998; Kim et al., 2003; Kim et al., 2010; NEC Group, 1993; MPIFC, 2008) with

focus most concentrated upon economic impacts rather than environmental, social, cultural

and other aspects (Sherwood et al., 2005). This is usually due to stakeholders’ desire for

financial cost-benefit analysis (Lilley & De Franco, 2003). Such research demonstrates the

extreme value of MICE events to host regions, with a greater economic impact per event-

visitor than any other form of event tourism, resulting from the higher levels of expenditure by

business visitors than other tourists (Rogers, 2013). Indeed, Shone & Parry (2013) claim that

a 3-day international conference for dentists may produce greater economic impact than a

premier league soccer match.

Despite increasing MICE event-impact research, little is available regarding MICE event

impacts in rural locations. This may be because urban areas are often the most economically

valuable locations for MICE events (Bernini, 2009). Most authors agree, however, that

knowledge of MICE event-impacts provides important insight of value to stakeholders and

the host economy (Wood, 2005). Understanding the economic value of MICE events and

their influence on economic legacy, resident-perceptions of the local area and place-

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marketing may assist local stakeholders in their tourism and business strategic planning

(Kotler et al., 1999). This is applicable to both urban areas and rural host economies.

Academics and organisations have created multiple frameworks with which to analyse socio-

economic impacts of events generally (Wood, 2005; EventIMPACTS, 2010a; Schlenker et

al., 2010; Dwyer & Forsyth, 1996; Kim et al., 2003), many of which use an input-output (I-O)

model (EventIMPACTS, 2010a; Jago & Dwyer, 2006; Lee, 2006) (see Chapters 2.2 & 2.3).

These are subject to intense critical review within academic literature. This research

combines and applies frameworks by Wood (2005) and EventIMPACTS (2010d) to create a

framework for socio-economic impact analysis of MICE events at a purpose-built venue in

rural locations.

1.2 Research Rationale

This research contributes towards the filling of the gap in literature surrounding rural MICE

event impacts, allowing for greater understanding of the similarities and difference between

economic impact in urban and rural locations. It also provides a valuable framework to future

MICE event stakeholders for the investigation and calculation of the social and economic

value of rural MICE events to the host economy, as well as cost-benefit analysis of MICE

events within a local authority planning sphere. It may also be of use to rural MICE venue

management and local authorities to understand the impact of MICE events on rural host

economies.

The host economy for this research was Dunkeld & Birnam (D&B), a small, rural town in

Perthshire, Scotland (Appendix A). The impact of MICE events at Birnam Arts & Conference

Centre (BACC) (Appendix B) was the subject of the study. The town and venue were

selected due to their rural location and are further discussed later in the study (Chapter 4).

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This research aims to investigate the economic and social impacts of MICE events upon a

rural host economy using the objectives in Table 1.1

Table 1.1: Research Objectives

Objective

Number Objective

1

To calculate total direct economic injection of delegate expenditure as well as

the revenue and costs associated with hosting MICE events at the chosen venue

in a rural location. This investigates the nature and type of expenditure as well

as the amount which is leaked from the host region, contributing towards the

direct economic impact figure.

2 To investigate MICE event delegate perceptions regarding their impressions of

the venue’s host destination.

3 To investigate perceived economic impacts of MICE events at the chosen venue

upon local business-owners.

4 To investigate general resident attitudes toward, and perceptions of, MICE

events at the chosen venue within the host community.

1.4 Research Design

This research collected data through three questionnaire surveys focused on; 1) MICE event

delegate expenditure and perceptions of D&B; 2) local business owners’ perceived impacts

of MICE events on their business; and 3) social impacts of MICE events on D&B residents.

Questionnaire surveys were primarily quantitative, but some qualitative data were also

collected. BACC revenue figures were also obtained to calculate economic impact.

Results were analysed using univariate analysis. The EventIMPACTS (2010b) economic

calculator was also used to obtain an economic figure from the results (objective 1).

Delegate perceptions of D&B were analysed to investigate their impression of D&B and the

possibility this could have for increased future tourism (objective 2). Social impacts were

analysed to investigate the effects of MICE event on local business owners (objective 3) and

residents (objective 4) in rural locations.

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Despite every effort to ensure reliability and validity, the research was subject to some

limitations. As resources were not available to investigate the indirect or induced impacts

(Chapter 2), the EIA study focused only on direct impact which may show only basic, high-

level economic impact. Further, D&B has too few businesses to obtain equal proportions of

business types in the sample, which may increase bias in the data.

This dissertation now reviews literature surrounding socio-economic impacts of MICE

events, and how these may or may not apply in rural settings.

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Chapter 2

Literature Review: Economic Impact Analysis

2.1 Introduction

Global tourism, defined as the visitor economy (Hristov, 2015) or the movement of people

(Mathison & Wall, 1982), has experienced significant growth over recent decades to

become one of the fastest-growing economic sectors (UNWTO, 2015). Tourism revenue

strongly contribute toward destination diversification and economic development in

numerous sectors (Rogers, 1998), and have subsequently become a key driver for socio-

economic progress. Competition exists between locations globally to attract tourists and

subsequent socio-economic development (UNWTO, 2015; Baade et al., 2009).

MICE Events are a subdivision of the total visitor economy and are intrinsically linked to

tourism, becoming one of its pre-eminent development tools (Reic, 2012). Local authorities

frequently use MICE events as tourist attractions and crucial elements in destination

promotion. MICE events are well recognised within tourism for having both highly valuable

and damaging consequences upon host economies (Allen et al., 2011). As a result of this

young but growing industry, academic enquiry is widespread (Skinner, 2008; Mistilis &

Dwyer, 1999; Sherwood et al., (2005); Davies et al., (2013); Teller & Elms, 2012;

Hankinson, 2004). This review explores key themes within the extant literature surrounding

socio-economic impact analysis, by first discussing economic impact of MICE events, then

reviewing the methods by which it is conducted. Literature regarding social impact of MICE

events is discussed in the following chapter.

2.2 Economic Impacts of MICE Events

MICE economic impact is the net economic change within a defined geographical area or

community due to MICE event-related spending (Crompton & McKay, 1994; Rogers, 2013),

which occurs principally through attendee expenditure (EventIMPACTS, 2010a). Business

tourists spend approximately three times more than leisure tourists; often as business

expenditure, rather than personal (Bihari, 2004; Shone & Parry, 2013; Solberg et al., 2002).

Venue revenue also significantly contributes to economic injection (Lee, 2006). Expenditure

directly impacts hotels, entertainment venues, shops, public transport, and local business in

the host economy. It then filters and distributes throughout the rest of the economy as

indirect and induced impacts (Figure 2.1), ultimately reaching resident households through

employment remuneration. Cameron (2009) claims that MICE events have such significant

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economic benefits that they should be considered a means of economy development rather

than part of tourism.

The view that MICE events precipitate largely positive economic benefits is not uncontested.

Baade et al. (2009) and Boyle (1997) consider city council investments in MICE

infrastructure an opportunity cost for alternative sector investments. Jones & Li (2016)

challenge preferred investment in MICE infrastructure over leisure attractions and suggest

that high cost causes profitability of MICE facilities to be often marginal, focusing economic

benefits on delegate expenditure, and creating a similar situation to conventional leisure

tourism. Such criticism fails, however, to recognise the previously-discussed value of

business tourist expenditure over its leisure counterpart (Bihari, 2004; Solberg et al., 2002).

Further debate surrounds expenditure leakage into foreign economies through tax, supplier

costs, and chain businesses (Kim et al., 2003; Mistilis & Dwyer, 1999). Mehmetoglu (2002)

suggests the proportion of MICE expenditure leaked out can almost wholly counteract its

positive effects on host destinations. Buultjens & Cairncross (2015) suggest this applies

particularly to rural locations. However, many UK studies challenge Mehmetoglu’s claim,

identifying varying levels of leakage, but rarely indicating that leakage nullifies economic

benefits (Jones & Li, 2015; Weber & Ladkin, 2004).

Figure 2.1: How Event-Related Expenditure Filters through the Host Economy: The

Multiplier Effect (Rogers, 2013: 257).

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Concern also surrounds political capture of MICE infrastructure development by local and

political elites consumed by city boosterism and personal popularity. Many economists are

suspicious of EIA studies claimed by such event proponents (Chang et al., 2015; Crompton,

2006; Crompton & McKay, 1994; Jones & Li, 2015). Indeed Crompton, (2006) suggests few

EIA studies are truly independent due to bias of the commissioning organisation, often

aiming to persuade stakeholders of the costs or benefits of the event. This is supported by

Baade’s et al. (2008) evaluation of political conventions in the USA between 1972 and 2005,

finding them to provide no real municipal growth despite proponent and sponsor claims that

conventions provided valuable windfalls to host destinations. Baade’s et al. (2008) study,

however, may have been subject to similar bias as the conventions studied. Potential for EIA

studies to be political tools for event proponents highlights real risk to host destinations

which invest in MICE events (Flyvbjerg, 2008).

Literature regarding MICE event economic impacts on host economies remains inconclusive

and further research is necessary. Potential impacts, however, are as previously defined.

Most studies ignore Crompton’s (2006) claims of politicism of EIA studies, focusing on the

direct, indirect and induced impacts. Furthermore, the overwhelming majority of MICE event

EIA studies are limited to large-scale, urban conventions. Little research has been

conducted of rural events which could be less subject to large-scale political capture.

Equally, economic impacts of MICE events on UK rural locations, which Mehmetoglu (2002)

and Buultjens & Cairncross (2015) claim much more subject to leakage, are largely

unobserved in the research due to much higher economic figures in gateway cities (Wood,

2005). However, without accurate data local authorities and taxpayers will struggle to

properly understand economic value of such events to rural host destinations (Dwyer et al.,

2007). Further research is needed to address this gap in the literature. This review now

proceeds to examine key approaches to EIA.

2.3 A Methodological Review of Economic Event Impacts Analysis

Much debate surrounds the most accurate method of EIA (e.g. Davies et al., 2013; Tyrrell &

Johnston, 2006; Wood, 2005; EventIMPACTS, 2010a), with different methods producing

contrasting results (Morgan & Condliffe, 2006). Opinion is split between focus on direct

impact (initial spending stimulus), indirect impact (resultant inter-business transactions) and

induced impact approaches (consequent impact on household income and consumer

spending), the sum of which comprises the total impact (Saayman & Saayman, 2012)

(Figure 2.2). Many authors (e.g. Davies et al., 2015; Abelson, 2011; Wood, 2005; Chang et

al., 2015; Dwyer et al., 2000a; Getz, 2005; EventIMPACTS; 2010a; Chad; 2015, Bess &

Ambargis, 2011) debate the accuracy and true economic representation of each approach,

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yet most agree on the importance of quantifying delegate expenditure and venue revenue

and costs, as well as the need of a reliable research method.

Davies et al. (2013) considers the direct expenditure approach (DEA) the most pragmatic,

accurate, and cost-effective method for measuring small events, considering only direct

impact of retained event-related spending stimuli (Figure 2.3) (EventIMPACTS 2010c;

Davies et al., 2013; Faulkner, 1993; Jago & Dwyer, 2006). Further rounds of economic

activity generated by initial stimuli require more advanced indirect and induced impact

approaches, supported by multiplier analysis. Multiplier analysis examines how initial

spending stimuli filters through the economy (Figure 2.1 & 2.4), using complex economic

calculations to estimate further economic activity such as inter-business transactions

(indirect impact) and household income or consumer activity increases (induced impact)

(Saayman & Saayman, 2012; EventIMPACTS, 2010a). Leakage and switching costs

(Appendix C) are also accounted for (Shone & Parry, 2013). Multiplier approaches available

include the input-output (I-O) analysis (Appendix D), computer-generated equilibrium (CGE)

model (Appendix E), and social accounting matrix (SAM) (Appendix F). All are extremely

data intensive and may be impractical for resource-limited researchers (Davies et al., 2013).

The use of multiplier analysis is the source of much debate within the literature. While a

widely-accepted method of economic evaluation (Getz, 2007; Dwyer et al., 2000a; Bess &

Ambargis; 2011), tensions occur between economists, academics and organisers regarding

the need to achieve academic rigour while managing commonplace resource constraints.

This is due to their estimative, varied, and extremely resource-intensive nature, as well as

increased chance of statistical error (Abelson, 2011). EventIMPACTS (2010a) and Davies et

al. (2013) suggest that multiplier analysis should be reserved to professional organisations

and research groups for large-scale MICE event EIA.

Figure 2.2: Types of Economic Impact

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Academic opinion is split between advanced approaches and increasing support for the

DEA. Davies et al. (2013), argue that the research method should be proportionate to the

event’s scale and support views that the DEA is suited to smaller events and resource-

limited practitioners due to offering an academically credible and resource manageable

method. Abelson (2011), however, strongly criticises the DEA’s limited approach, arguing

that ignoring opportunity costs creates fundamental error. Dwyer et al. (2000a) and Lee

(2006) support the use of advanced studies such as I-O and CGE models, suggesting that

in-depth analysis provides better indication of economic value. Views exist within the

academic literature, however, that advanced approaches typically inflate positive economic

impacts and serve as a manipulative tool for public support (e.g. Baade, 2008; Crompton,

2006; Crompton & McKay, 1994; Raj, 2015). Crompton (2006) also suggests that many

advanced studies are flawed through the regular use of misrepresentative multiplier

coefficients, leading to inaccurate results. Abelson (2011) is equally dismissive of popular

advanced approaches such as I-O and CGE, instead offering persuasive argument for cost -

benefit analysis approach (CBA) (Appendix G). This approach, however, is most commonly

used for capital investment and may also be too data-intensive for small to medium event

EIA (Davies et al. 2013).

Leakage & Switching

Direct

Economic

Impact

Visitor Organiser &

Venue

Commercial-

Visitors

Day-Visitors

Leakage

Figure 2.3: Direct Impact Factors for Calculation (EventIMPACTS, 2010c)

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It should be noted that even within each category of EIA, the calculation of leakage is

contested (Crompton, 1995; EventIMPACTS, 2010a; Lee, 2006). Multiple authors

acknowledge that different leakage calculations produce varying results. A variety of

formulas are used, ranging from the use of univariate statistics (EventIMPACTS, 2010d) to

complex economic formulas and algorithms, (Crompton, 1995). I-O models are also regularly

used to calculate leakage. Authors argue each method’s accuracy and practicality in a

similar fashion to the debate surrounding previously-discussed EIA calculation elements.

It is clear from the literature that all methods possess both disadvantages and advantages.

Davies’ et al. (2013) recommendation that methods should be selected in proportion to the

given event and practitioner appears sensible. This, however, may frustrate authors who call

for a singular method to facilitate universal comparison of MICE event EIA (MPI, 2013; Jago,

2007). All approaches appear to contain elements of flaws and may therefore systematically

Figure 2.4: Factors for Calculation in an Economic Multiplier

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fail to identify true economic value. However, it could be suggested that each flawed

approach provides a valid indication of economic value relative to itself, comparable with

other impact studies of the same approach.

2.4 Chapter Summary

The literature indicates that resources are not readily available for the advanced EIA of rural

and small to medium MICE events for individual or resource-limited researchers.

Consequently, the DEA is increasingly used as a pragmatic and affordable approach to

measuring their economic activity which is also comparable across multiple events

(EventIMPACTS, 2010a; Wood, 2005; Gratton et al., 2006; Davies et al., 2013). Evidence

suggests that some organisations are interested primarily in direct impact as a measure of

ROI (ACE, 2012). Direct impact quantified through DEA can also be used as fundamental

data to begin modelling advanced economic impacts through I-O and GCE models in future

research. Raybould & Fredline (2012) highlight the overarching necessity of accurate data

for accurate results in the DEA, indirect and induced approaches, making each approach

only as reliable as the data obtained.

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Chapter 3

Literature Review: Social Impact Analysis

3.1 Social Impacts

Academics recognise that EIA alone is unable to measure intangible impacts of MICE events

in the community (Dwyer et al., 2000b; Bowdin et al., 2011; Wood, 2005). MICE events and

business tourism often influence social attitudes as a result of event-related benefits and

inconveniences (Schofield, 2011). Table 3.1 lists possible areas of social impact highlighted

by Dwyer et al. (2000b) and Shone & Parry (2013). Social impacts may not be felt

universally by residents within one community and there is strong evidence for heterogeneity

regarding social attitudes towards business tourism (Schofield, 2011). Multiple factors may

influence resident attitudes, such as proximity to MICE event venues (Sheldon & Var, 1984;

Wall, 1996), knowledge of tourism impact on the community (Lankford, 1994) and individual

economic dependency on MICE events (Lankford & Howard, 1994; Androitis & Vaughan,

2003). King et al. (1993) further claim that conflicts of interest regularly occur between

stakeholder and local resident objectives, suggesting that large events, though profitable to

the destination and proponents, often have negative social impacts on residents.

Rogers (2013) supports this negative correlation within the MICE sector, but argues social

inconveniences are frequently tolerated to reap the perceived wider economic benefits of

MICE event expenditure on the host economy. In contrast, numerous studies highlight

positive impacts of MICE events (Roche, 1994; Lin, 2012) such as community cohesion

(Ritchie, 1984), culture exchange (Yang et al., 2010), and improvement of local infrastructure

(Silvestre, 2009). This is particularly true of rural community and sport events (Wood, 2005;

Buultjens & Cairncross, 2015), highlighting the need to test the theory through further social

impact research of rural MICE events.

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Table 3.1: A Selection of Possible Intangible Social & Economic Costs & Benefits

Resulting from MICE Events

Ap’s (1992) examination of resident socio-economic relationships to tourism through the use

of social exchange theory (SET) supports Rogers’ (2013) & King’s et al. (1993) claim. In a

MICE event context, SET requires residents to evaluate social and economic impacts of

MICE events. If perceived benefits outweigh perceived costs, residents support tourism (or

vice-versa). Although this model has empirical support within the literature (Williams &

Lawson, 2001; Cavus & Tanrisevdi, 2003), Tomljenovic & Faulkner (2000) highlight that SET

fails to identify the reasoning behind why economic benefits are perceived to be of higher

value than social. Maslow (1987) suggests this may occur because social needs are less

fundamental to quality of life than economic needs (by way of association to physiological

needs), indicating why residents show tolerance of social inconveniences when faced with

conflicting social and economic interests (Figure 3.1). Such tolerance, however, could be

futile unless reliable and unbiased economic data can be obtained with which to justify it.

Wood (2005) and EventIMPATS (2010d) present a framework for the capture and

comparison of social impacts of community and sport events respectively. Both also provide

accompanying frameworks for EIA through DEA. The frameworks, though not initially

designed for MICE events, could easily be adapted to the business tourism sector and is

further discussed in the methodology chapter of this study (Chapter 4).

Costs Benefits

Social

Impacts

Disruption to resident’s lifestyles

Traffic congestion

Noise

Crowding

Crime

Property damage

Community destination destruction

Security

Cordoned-off areas

Resident Exodus

Interruption of normal business

Under-utilised infrastructure

Community development

Civic pride

Event product extension

Improvement of social ties

Long-term promotional benefits

Induced development and construction

expenditures

Business confidence

Additional trade and business

development

Increased property value

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3.2 MICE Event Impact Analysis as part of Tourism Planning & Destination

Development

Despite discussed debate, most research suggests that MICE events have a largely positive

effect on the economies and communities of host destinations, and it is accepted that MICE

events play one of the most popular and significant place-marketing strategy roles within

global tourism planning (Edizel, 2013; Rogers, 2013). Recent studies value the direct

contribution of MICE events to UK GDP at £22.5bn (MPI, 2013), supporting 423,455 full-time

employment positions. These figures, as well as numerous other EIA studies, indicate that

MICE events have a positive economic impact on destinations on a local, as well as national,

level. Tourist boards regularly aim to attract business tourists due to delegates’ higher levels

of purchasing power (Horvath, 2011; Callan & Hoyes, 2000; Davidson, 1994).

MICE events have further potential to benefit a destination through increased B2B

expenditure, employment opportunities within the host economy, and subsequent ‘knock-on’

effects throughout the region. This makes them highly valuable to a number of private and

public sector stakeholders (Rogers & Davidson, 2006). They also regularly attract tourists

during the low season of conventional tourism (Horvath, 2011), creating permanent, rather

than seasonal, trade and employment. Furthermore, Davidson (1994) claims that delegates

who leave MICE events with positive experiences of the location effectively become unpaid

ambassadors for the destination. These are commonly individuals who may be significant in

promoting the location to others. Demand for future MICE events in the region may

subsequently increase, as well as the possibility for relocation of businesses to the area.

Figure 3.1: Maslow’s Hierarchy of Needs (BBC, 2013)

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Indeed, Davidson (1994) suggests that one meeting of important delegates may indirectly

boost a destination’s exposure more than years of promotion by development authorities.

3.3 Chapter Summary

Although abundant MICE impact analysis studies exist, there remains very limited research

regarding their socio-economic impacts in rural locations. Due to the overwhelming majority

of meetings taking place in gateway cities and urban areas (Bernini, 2009; Wood, 2005), the

majority of studies also focus on such locations. 36% of UK MICE events take place in

London, Cardiff, Edinburgh, Belfast and Liverpool alone (MPI, 2013), 41% in the South East

of England, and a large majority in urban areas. In contrast, only 0.6% of MICE events occur

in the Scottish Highlands (MPI, 2013; BTS, 2013). Some social and economic impact

research in rural and less-urban locations does exist (Wood, 2005; Lankford, 1994; Buultjens

& Cairncross, 2015; Mehmetoglu, 2002); however, they are usually limited to sport or

community, rather than MICE, events.

The lack of literature may suggest that rural MICE event impact evaluation is not valued

within academia. However, despite rural MICE events being fewer and smaller than urban, it

may be of value to stakeholders and local residents to understand the socio-economic

impacts of MICE events on the community and local business. Destination development

planners and local government may equally benefit from an understanding of the impact of

business tourism on the local area (Lee, 2006). Research in this area would contribute

towards better understanding of these questions. This dissertation now proceeds in the

methodology to discuss a selection of research methods, as well as the framework used by

this study, in an effort to fill the identified gaps in research.

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Chapter 4

Research Methods & Methodology

4.1 Introduction

This chapter discusses the methods selected for this research, taking into account strengths,

weaknesses, limitations, and how they contribute to meeting the research aims and

objectives. Three research models for socio-economic impact analysis are initially reviewed

to assess methodological trends in the literature. The selected research methodology and

research design are then discussed, followed by an explanation of research and analysis

methods as well as a definition of the host economy. Finally, limitations of the study are

highlighted as part of a review of the overall reliability and validity of the research.

4.2 Review of Socio-Economic Impact Analysis Models

Wood (2005) developed a framework to collect social and economic data of local community

events in Blackburn, Lancashire. The method involves collecting both qualitative and

quantitative data regarding delegate expenditure, resident perceptions and perceived effects

on local business using survey-questionnaires. No multipliers are used in the framework,

although Wood acknowledges their potential to produce further-reaching economic

estimations. Although not specifically designed for MICE events, Wood’s method is

adaptable to rural MICE event research. It lacks, however, focus on factors of EIA such as

leakage and venue revenue and costs.

Such factors are a larger focus of the EventIMPACTS (2010a) model, created by multiple UK

governing bodies (Appendix H) to better evaluate triple bottom line impacts of sporting and

cultural events. This framework is adaptable to small, medium and very large scale events,

and offers direct, indirect and total economic impact approaches. The basic framework

(EventIMPACTS, 2010d), feeds data into a web-based calculator to produce an economic

impact figure through the assessment of attendee expenditure, organiser expenditure, and

leakage. The intermediate framework (EventIMPACTS, 2010c) builds upon this by

accounting for further economic transactions, and the advanced framework estimates

further-reaching effects through the use of a multiplier. EventIMPACTS (2010e) also

provides five thorough frameworks for the analysis of social event impacts by focusing on; 1)

satisfaction; 2) identity, image and place; 3) participation; 4) volunteering and skills; and 5)

children & young people. These are, however, intended for large sporting events and are

likely to be difficult to adapt to small rural MICE events.

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Though effective, the EventIMPACTS frameworks are not peer-reviewed and hold little

significance within academia. EventIMPACTS has, however, the added value of being

endorsed by many influential UK governing bodies, indicating applicability to UK events. Its

step-by-step guide for basic to advanced economic impact research makes it practical to

most individuals and organisations, versatile and easily adaptable to MICE events.

Furthermore, Wood’s economic shortcomings could be recompensed by combining her

method with aspects of the EventIMPACTS (2010d) basic framework.

The ENCORE Festival & Event Evaluation Toolkit (Jago, 2007) was developed by

Sustainable Tourism CRC (Jago, 2007) and is a comprehensive, computerised toolkit for the

purely economic evaluation of large-scale community events (Bowdin et al., 2011). This

relies heavily on a GCE or I-O model to calculate MICE event economic impact (Bowdin,

2011). ENCORE is widely accredited by leading academics (e.g., Bowdin et al., 2011; Jago,

2007; Schlenker et al., 2010), and has also been adopted by Australian state government

treasuries (Bowdin et al., 2011). However, its difficulty in accessibility, focus on large-scale

events, and required use of multipliers may be impractical for resource-limited research.

4.2.1 Underlying Methodological Trends within the Literature

The three methods have a similar approach to economic and social impact data, taking a

positivist approach. Each deductively and descriptively identifies how MICE events impact

host economies without attempting to explain why this phenomenon occurs or evaluate the

effectiveness of its management. Research focuses on quantitative data, which is collected

using survey questionnaires. Wood (2005) uses interval data measurement in her efforts to

evaluate social impacts. Little secondary data is used, however some is used in the

ENCORE and advanced EventIMPACTS studies in order to calculate the appropriate

multiplier.

4.3 Methodology

This study combined Wood’s (2005) small-scale, social impacts research design with

EventIMPACTS’ (2010d) direct economic impact data calculation methods and focus on

economic leakage and event organiser cost. Wood’s (2005) approach to social impact data

collection was adaptable to this research’s aim and was also applied. Given the finite nature

of resources available for the study as well as its small scale, these methods were selected

over advanced methods to be most appropriate to achieve the aims and objectives of the

study.

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This descriptive, case-study research adopts a post-positivist, deductive approach to data,

knowledge and research by collecting and analysing primary, quantitative data, then

deducing conclusions in relation to research aims and objectives (Veal, 2011).

4.4 Data Type: Qualitative vs Quantitative

Allen et al. (2008) consider quantitative data most effective when identifying the economic

impact of events upon a host economy because they are measurable and subject to

statistical analysis, whilst able to be used on a large scale. This is supported by the

overwhelming majority of authors who approach EIA using questionnaire surveys. Coles et

al. (2013) alternatively suggest that a mixed-method approach may be of value in tourism-

based studies. This is reinforced by Finn et al. (2011), who claim that qualitative data provide

more information about the research subject through the use of words, rather than quantities.

Interviews and focus groups would be useful to meet the objective of investigating perceived

social impacts, although this research’s finite resources caused the use of purely qualitative

research methods to be difficult. Veal (2011), however, claims that qualitative data can be

presented in quantitative form, such as the collection of numerical data thorough the use of

Likert scales or through open response questions (Wood, 2005).

This research adopts a primarily quantitative, but somewhat mixed methods approach to

achieve the research aim and objectives (Figure 4.1). The majority of data was purely

quantitative and numerical. Some qualitative data was quantitatively presented using Likert

scales, as suggested by Veal, (2011). A small number of qualitative, open-ended questions

were also used, which were not pre-coded. Individual survey design and actual methods

used are discussed below (Chapter 4.6). In order to achieve the aims and objectives, only

primary data were collected. Secondary data were not required since no economic multiplier

was applied.

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4.5 Definition of Host Economy: Dunkeld & Birnam (D&B) & Birnam Arts & Conference

Centre (BACC)

D&B (Appendix A) has a population of 1,287 (ScotlandCensus, 2011) which classifies it as

rural according to Scottish classifications (Table 4.1) (TSG, 2013). A 3-kilometre radius from

D&B town centre was used as the host economy for this research. Once the country’s

capital, D&B is one of the best preserved historic towns in Scotland (Dunkeld and Birnam,

2015) and is a popular tourist destination. It lies approximately 30 miles south of the

Cairngorms National Park and offers a variety of tourist attractions including museums, a

cathedral, highland nature and wildlife, a Beatrix Potter exhibition, a variety of riverside and

woodland walks, traditional highland shops, and multiple hotels. It is also a location from

which other tourist destinations in rural and highland Scotland can be easily accessed, and

only a 27 minute drive from the nearest significant urban town of Perth (Apendix A ). This

location meets the objective requirements for the study because; 1) it is a rural location; 2) it

has a purpose-built conference centre with MICE event-specific facilities; and 3) tourism

plays an important role in its economy.

BACC in D&B is the venue selected for this research. BACC offers professional MICE

facilities and is used frequently by organisations across Scotland for MICE events (Appendix

B). BACC was built in 2001 and its nearly £2,000,000 capital investment was achieved

through both public-funding and grants from local governing bodies, organisations and its

largest financial stakeholder, Perth & Kinross Council (BACC, 2015). BACC experiences a

Quantitative Data Qualitative Data

Aim: investigate the economic and social impacts of MICE events held at a

purpose-built venue in a rural host economy

Objective 1 Economic Impact

Objective 2 Delegate

Perceptions

Objective 3 Business Owner

Perceptions

Objective 4 D&B Residents

Social Impacts

Figure 4.1 How Quantitative & Qualitative Data Address Aim & Objectives. Bold

arrows show the qualitative form in which data was presented. Thinner arrows indicate an

element of qualitative data within data required to address the respective objective (e.g.

open-response questions).

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Table 4.1: Scottish Government Urban – Rural Classification (TSG, 2014)

conventional MICE high-season between September and May, excluding December. This

venue meets the research aims and objectives by hosting MICE events in a rural area.

4.5.1 What is ‘Rural’?

The definition of rural is widely debated. Multiple authors and organisations contest the TSG

(2014) urban – rural classification. The ONS (2004) classifications differ depending on the

type of geographical definition, and any output area with a population less than 10,000 is

considered rural. The U.S. Census Bureau (USCB, 2015) and Department of Agriculture

Economic Research Services (USDAERS, 2015) consider any settlement with less than

2,500 residents as rural. This research accepts that the Scottish rural classification may differ

from that from other more remote countries. However, for the purpose of this research, the

Classification Type

Classifications (Number of Residents)

2 Fold Urban-Rural

Classification

Urban

>3,000 residents

Rural

<3,000 residents

3 Fold Urban-Rural

Classification

Urban

>3,000 residents

Accessible Rural

<3,000 residents & <30 minute drive time to a >10,000 settlement

Remote Rural

<3,000 residents & >30 minute drive to >10,000 settlement

8 Fold Urban-Rural

Classification

Large Urban

>125,000 residents

Other Urban

10,000 – 124,999 residents

Accessible Small Town

3,000 – 9,999 residents & <30 minute drive to

10,000 resident settlement

Remote Small Town

3,000 – 9,999 residents & >30 minute drive to 10,000 resident

settlement

Very Remote Small Town

3,000 – 9,999 residents & >60 minute drive to 10,000 resident

settlement

Accessible Rural

<3,000 residents & <30 minute

drive to 10,000 resident

settlement

Remote Rural

<3,000 residents & >30 minute


settlement

Very Remote Rural

<3,000 residents & >60 minute


settlement

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Scottish classification was considered appropriate as it is the governing authority, and was

used.

4.6. Research Design: Data Collection & Questionnaire Surveys

Primary data were collected using three quantitative questionnaire surveys which included

closed, recall, process and open-ended questions (Appendix I). Questionnaire surveys were

applicable to the specific context of this research due to effectively yielding the required

sample size within time resources, as well as providing adequate data validity (Veal et al.,

2011). Questionnaire surveys are an ideal means of quantifying multifaceted data in a

concise manner within a tourism context (Veal, 2011). However, Coles et al. (2013) claim

that the often prevalent view that questionnaire surveys are always most appropriate for

deductive studies is a false binary, and qualitative research methods may be equally

effective to test theory. Indeed, interviews and focus groups may have produced greater

insight, particularly relating to social impacts. Qualitative methods are, however, often more

resource–intensive (Ritchie et al., 2005), hence questionnaire surveys were selected as an

efficient way to collect varied data.

Closed questions were primarily used as they are easily understood and quick to answer,

potentially increasing the response rate (Finn et al., 2000). However, respondents may be

restricted to give answers which only loosely match their opinions, posing potential threat of

negative impact on data quality. Alternatively, open questions can be particularly effective to

more accurately identify respondent opinions, or reasons for those opinions, which may be

hidden from a pre-coded list. However, verbatim answers can be both difficult and time-

consuming to process and code (Finn et al., 2000). Both question types are present in this

research, and the advantages and limitation of both are acknowledged. All questions were

properly audited to maximise the inclusion of only relevant questions. Individual

questionnaire design is discussed below.


A short face-to-face questionnaire survey regarding local business owners’ perception of

MICE event economic impact upon the turnover of their business was conducted, addressing

objective 3. This used closed questions, a 5-point Likert response scale and open, multiple

response questions. See Appendix J for an example. Face-to-face, interviewer-completed

questionnaires were selected for this study due to the wide acceptance that they generate a

relatively high response rate (Allen et al., 2011; Bowdin, 2011; Coles et al., 2013) and higher

22 G20614827

accuracy compared with other quantitative survey methods, also allowing for a less ‘user-

friendly’ design.


A questionnaire survey was conducted amongst MICE event delegates to investigate; 1)

delegate expenditure, leakage and switching cost; and 2) delegate perceptions of Dunkeld &

Birnam as a tourist destination. An example is found in Appendix K. Some nominal data was

obtained to calculate leakage and switching costs. Questions were primarily numerical and

not-coded, or simple, pre-coded and factual. One open-response question was included.

Despite the benefits of face to face questionnaire surveys (Ritchie et al., 2005) they were not

used with business delegates due to possible inaccuracy when listing personal expenditure

should the respondent have felt rushed by the interviewer. It should be noted that diary

methods have been seen to be more accurate than recall methods for gathering delegate

expenditure data, providing means for delegates to record expenditure as it is spent. Diary

methods, however, were not employed as they are accepted to have a notoriously-low

response rate (Wood, 2005; Faulkner & Raybould, 1995).


A short, face-to-face survey questionnaire regarding the perceived social impacts on D&B

residents was conducted (Appendix L) using Likert response scales. Likert scales were

selected to easily present qualitative data in a quantitative form through coding (Veal, 2011).

One open-response question was included for respondents to express additional information

if required. The social impact categories were adapted from Wood’s (2005) framework for

social impact evaluation of local community events, and are considered applicable for rural

locations such as D&B.

4.6.4 Research Design: BACC Financial Data Collection

BACC financial data were provided by BACC management. These data were provided for

MICE events within the same time period as the collection of delegate expenditure data.

Data included; 1) room hire revenue and costs per event; 2); catering revenue and costs

(broken down by supplier, including their locations to account for leakage); and 3) tax and

other relevant financial information.

4.7 Sampling Method

Including every MICE event delegate or local business in questionnaire surveys is seldom

feasible or effective (Finn et al., 2000). Consequently, it is necessary that a smaller sample

23 G20614827

of the survey population is drawn which can represent the survey population as a whole

(Champion, 1976). All questionnaires adopt random probability sampling principals to

minimise bias and maximise representativeness (Veal, 2011). This study would ideally use a

95% confidence level and 5 per cent margin of error, producing a sample size of 384 for

each questionnaire survey (calculated assuming that p = 0.5). However, resource limitations

required a greater margin of error in some cases.

4.7.1 Questionnaire 1 - Sampling Method & Selection

It is estimated that there are around 150 businesses within D&B (Visit Dunkeld, 2015;

D&BNEWS, 2015; TripAdvisor, 2016), although this figure is hard to verify. A sample

population of 150 is significantly smaller than the suggested sample size of 385, requiring

the use of a finite population correction factor (Appendix M ) (McDaniel & Gates, 1998; Veal,

2011; Wood, 2005) which brings the sample size to 109 in order to achieve a 5% margin of

error (Pivotal Research, 2011). Although this number of responses would be ideal, this was

too many considering this research’s limited resources. A smaller sample population of 59

and a 10% margin of error were therefore accepted, slightly reducing the validity and

reliability of the research.

Of the 150 business in Dunkeld & Birnam, 59 were selected using a random number table.

10 businesses were randomly selected and ranked as contingencies should original

businesses have not cooperated. Two contingencies were used. It should be noted that the

small number of businesses in D&B did not allow for an equal number of each business type

in the sample, which may increase data bias.


Based on the 2014 – 2015 tax year figures, BACC traditionally hosts an average of 719

MICE event delegates per month (Flatley, 2016). However, actual figures vary dramatically

between high and low season months. The average number of delegates during the BACC

high season (September to May, excluding December) is 995, against only 168 in the low

season (Appendix N). This research used the actual number of delegates in February 2015

(1,020) as a sample population. In order to achieve a 95% confidence level and 5% margin

of error, 280 questionnaire responses were required. It should be noted that the actual

February 2016 number of MICE delegates could differ from that of February 2015, further

affecting the margin of error. 300 questionnaires were delivered to BACC staff to be

distributed to and completed by delegates. Event delegates were given hard-copies of the

questionnaire upon arrival to the event (or the last day of the event if a multi-day event),

24 G20614827

which were collected upon event-adjournment, allowing respondents time to consider

expenditure. Questionnaires which were not completed were redistributed to maximise the

sample size whilst reducing wastage. Wood (2005) stressed the need for the questionnaires

to be completed during the event period to avoid delegates forgetting expenditure details. A

cover sheet was included to ensure anonymity.


The questionnaire 3 sample population is 1,300 (the population of D&B). To obtain a 5%

margin of error, the required sample size was 297. However, limited time and resources, as

well as few people on the street, demanded a smaller sample population of 105 responses,

which were successfully obtained, increasing the margin of error to 9.17%. Though not as

reliable and valid as a 5% margin of error, it is felt that a margin of error of <10% is

acceptable and provides enough research confidence for the purposes of this study.

Street surveys for questionnaire 3 were conducted on Dunkeld High Street, the centre of

Dunkeld & Birnam. The High Street was representative of all D&B residents. Other areas of

the town may have increased bias by being representative of only the residents that lived in

that specific area and their (potentially localised) perceived impacts. The researcher walked

repeatedly from one end of the High Street to the other, inviting each member of the

community that passed by to take part in the questionnaire survey. Further

representativeness may have been achieved had the use of quotas been employed, but

given the resource limitations and small population of D&B, this was not practical.

4.8 Data Collection Period

Questionnaires 1 and 3 were undertaken over a period of 3 days during the third week in

January. The data collection period was not deemed as important as the number of

responses obtained. Data were, however, intentionally collected toward the end of January

so to obtain an accurate representation of D&B on a ‘day-to-day’ level, avoiding the festive

period.

Questionnaire 2 was undertaken over a 1 month period (February) during a normal operating

period of the year to reduce risk of bias in the data (Veal, 2011). Busier or quieter months

may distort economic impacts upon the host economy. If other months experience half or

double the number of MICE events and delegates, the resultant figure for economic impact

can be halved or doubled respectively.

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4.9 Pilot Study

A small pilot study was carried out to test data collection methods. Purposes of the pilot

included (Veal, 2011):

1- Testing questionnaire wording

2- Testing questionnaire sequencing

3- Estimating response rate

4- Gaining familiarity with respondents

Further details of the pilot study can be found in Appendix O.

4.10 Analysis Methods

Data regarding D&B business owners’ perceptions of the BACC MICE events economic

impact on their businesses and resident perceptions of social MICE event impacts were

analysed through univariate analysis in Microsoft Excel. Businesses were grouped into

business types (Appendix P) to allow for identification of business-types which experience

greatest benefits. All open-response questions were analysed by grouping responses into

categories and identifying most commonly-expressed categories.

Analysis of BACC revenue and MICE event delegate expenditure was conducted through

univariate analysis based upon various EventIMPACTS (2010c) economic calculator

formulas. It should be noted that SPSS was considered but not required for the analysis due

to Excel sufficiency. Delegate expenditure data was calculated using the formula

demonstrated in Table 4.2 in order to calculate total delegate accommodation expenditure

(F), delegate non-accommodation expenditure (H), total delegate expenditure leakage (J),

total delegate switching (L), and the total D&B-retained delegate expenditure (M).

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Table 4.2: Example Formula for Delegate Expenditure Calculations (1 month period)

Example MICE Event Delegate Expenditure Calculator Figures Calculation

Actual BACC monthly delegates 1,000 N

Actual BACC sample delegates 100 n

Sample Delegate Expenditure: Accommodation

Sample delegates using D&B accommodation 50 A

Estimated total delegates using D&B accommodation in month

500 B = (A ÷ n) x N

Average number of nights spent in host economy 1.5 C

Number of commercial bed nights 750 D = B x C

Average cost per bed-night £55 E

Estimated total revenue in month for D&B accommodation sector

£41,250 F = D x E

Delegate Expenditure: Event-Related Non-Accommodation Expenditure

Average individual delegate expenditure on non-accommodation items during entire visit

£25.00 G

Estimated total delegate expenditure on non-accommodation items in month

£25,000 H = G x N

Delegate Non-Accommodation Leakage

Leakage: Average individual delegate non-accommodation expenditure with non-local traders

£12 I

Total estimated non-accommodation expenditure with non-local traders in month

£12,000 J = I x N

Delegate Non-Accommodation Switching

Switching: Average individual delegate switching costs £5 K

Total estimated delegate switching costs in month £5,000 L = K x N

Total D&B-retained delegate expenditure in month £24,250 M = F + H – J - L

BACC financial data was calculated using a further EventIMPACTS-based formula to

calculate the total BACC revenue which was retained by D&B, as well as BACC leakage. An

example calculator is shown in Table 4.3

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Table 4.3: Example Formula for BACC Financial Calculations (1 month period)

BACC February Revenue & Leakage Figure Calculation

BACC Room hire Revenue & Leakage (1 Month)

Total BACC room hire revenue £10,000 O

Total BACC room hire VAT £2,000 P = O x 0.2

Total D&B-retained room hire revenue £8,000 Q = O – P

BACC MICE Event Catering Revenue & Leakage (1 Month)

Total BACC MICE event catering revenue £12,000 R

BACC Catering VAT £2,400 S = R x 0.2

Total BACC non-local supplier costs £3,500 T

Total D&B-Retained BACC February MICE event catering revenue

£6,100 U = R – S - T

Total D&B-retained BACC February MICE event revenue £14,100 V = Q + U

From the above calculations, the total D&B-retained economic injection resulting from BACC

MICE events during any given month can be calculated using the formula in Table 4.4, as

well as the total economic injection per individual delegate. This individual delegate figure

can then be multiplied by estimated or actual numbers of delegates to provide economic

impact estimation.

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Table 4.4: Total Economic Injection & Economic Injection per Delegate (1 Month)

Figure Calculation

Total D&B-retained economic injection resulting from BACC MICE events

£38,350 W = M + V

Average D&B-retained economic injection resulting from BACC MICE events per individual delegate

£38.35 X = W ÷ N

It should be noted that this research calculates leakage using a formula based on the

EventIMPACTS (2010c) calculator. The leakage calculation for each individual area of

economic event impact is found in the above formulas. However, the formula to calculate an

estimation of total leakage for any number of delegates is as follows (based on above

calculations):

Leakage = (J + P + S + T)

4.11 Reliability, Validity & Limitations

Research methods employed in this study provided a robust framework for data collection

with acceptable levels of both reliability and validity. However, some threats to validity exist.

These are summarised in Table 4.5.

N

x number of delegates

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Table 4.5 Potential Threats to Validity

Threat Description

Questionnaire

design

Respondents may find questions confusing. If present in the

questionnaire, leading questions could influence respondent decision.

Accuracy of

Recall

Lack of ability for delegates to accurately recall expenditure over a

period of a day or multiple days.

Data

Sensitivity

Respondents may be unwilling to share personal expenditure

information.

Respondent

Patience

Respondents may be impatient, leading to incomplete or inaccurate

responses. This is especially possible when delegates are asked to

recall much expenditure before travelling home after a day of meetings.

Respondent

Distraction

Distractions may cause respondents to rush the interviews or not give it

his or her full attention, leading to inaccurate results.

High margin of

Error

Questionnaires 1 and 3 both possessed around 10% margin of error.

Decreasing this to 5% would increase both research reliability and

validity.

30 G20614827

Chapter 5

Results & Analysis

5.1 Introduction

This chapter presents and discusses results of research conducted through all questionnaire

surveys as well as BACC financial information. These results are displayed and discussed in

separate sections which each relate to a different research objective.

5.2 Perceived Economic Impact on Local Business Owners

This section presents and discusses the results of questionnaire survey 1 which addresses

research objective 3; to investigate the perceived economic impact of BACC MICE events

upon D&B business owners. A full data set is in Appendix Q.

5.2.1 Perceived Economic Impact on Local Business Owners: Results

Within the sample of D&B businesses, perceptions regarding the impact of BACC MICE

events on local business were split. 53% of the sample perceived BACC MICE events to

have some impact on their business (Figure 5.1). Of these, hospitality business made up the

most significant proportion (32%) (Figure 5.2). 91% of hospitality business perceived an

impact. Other significantly-impacted business types included retail shops and cafés, each

comprising 16% of total impacted businesses (Figure 5.2). These business types alone

totalled 64% of all businesses to perceive an impact.

Although retail businesses comprised a significant proportion of the total businesses to

perceive an impact, 64% perceived MICE events to have no impact on their business. This

was the most significant contributor to businesses perceiving no impact (32%). Other

significant business types which expressed no perceived impact included automotive and

adventure businesses. This is further highlighted in Figures 5.2 and 5.3.

31 G20614827

Figure 5.1: Business Owners' Perceptions of the Impact of BACC MICE Events

on their Businesses

3% 7%

16%

3%

7%

3% 3%

3% 7%

16%

32%

Businesses which perceive an impact on their business from BACCC MICE events

Automotive & Mechanical

Building / Trade

Café / Deli

Finance / Professional

Grocery / Markets

Medical & Vetinary

Music & Music Production

Newagents & Post Office

Restaurant

Retail & Tourist Shops

Hospitality

Figure 5.2: Businesses which Perceive an Impact on their Business from

BACCC MICE Events

0

5

10

15

20

25

30

35

No Yes

Nu

mb

er o

f B

usi

nes

ses

Business Owners' Perceptions of the Impact of BACC MICE Events on their Business

Hospitality


Restaurant


Music & Music Production

Medical & Vetinary

Grocery / Markets


Café / Deli

Building / Trade

Barber / Hair Salon


Adventure / Sports

32 G20614827

11%

14%

7%

3% 7%

7% 4%

4%

7%

32%

4%

Businesses which perceive no impact on their businesses from BACC MICE events

Adventure / Sports


Barber / Hair Salon

Building / Trade

Café / Deli


Grocery / Markets

Medical & Vetinary



Hospitality

Figure 5.3: Businesses which Perceive no Impact on their Business from

BACCC MICE Events

Half of respondents perceived no impact to short-term turnover by MICE events (Table 5.1).

These were similar business to those which perceive no overall impact. Some business

types (e.g. cafes & hospitality) perceived a majority increase (71% & 54% respectively).

Three additional hotels (27%) perceived a large increase, which were also 75% of all

businesses to perceive a large increase (Table 5.1). No businesses perceived a large

decrease to short-term turnover; however one hotel and one newsagent perceived a

decrease. Hotel management explained that BACC MICE events compete with the hotel’s

MICE activity.

MICE events impact on long-term turnover mirrored that of short-term turnover to a large

extent. Half the respondents perceived no impact to long-term turnover (Table 5.2). These

were similar businesses to those which perceive no impact to short-term turnover. Business

types which perceived an increase or large increase include cafés (57%) and hospitality

(91%). Only two businesses (3%) perceived a large increase to long-term turnover. No

businesses perceived a decrease or large decrease to long-term turnover.

33 G20614827

Table 5.1: Business Owners’ Perception of BACC MICE Event Impact on Short-Term

Turnover

Table 5.2: Business Owners’ Perception of Impact Event Impact Long-Term Turnover

Business Type Large

Increase

Increase No

impact

Decrease Large

Decrease

Automotive & Mechanical 0 0 5 0 0

Adventure / Sports 0 0 3 0 0

Barber / Hair Salon 0 0 2 0 0

Building / Trade 0 2 1 0 0

Café / Deli 1 3 3 0 0

Finance / Professional 0 1 2 0 0

Grocery / Markets 0 1 2 0 0

Medical & Vetinary 0 0 2 0 0

Music & Music Production 0 1 0 0 0

Newsagents & Post Office 0 1 2 0 0

Restaurant 0 1 1 0 0

Retail & Tourist Shops 1 4 9 0 0

Hospitality 0 10 1 0 0

Grand Total 2 24 33 0 0

Row Labels Large

increase Increase

No

impact Decrease

Large

Decrease

Automotive & Mechanical 0 0 5 0 0

Adventure / Sports 0 1 2 0 0

Barber / Hair Salon 0 0 2 0 0

Building / Trade 0 2 1 0 0

Café / Deli 0 5 2 0 0

Finance / Professional 0 0 3 0 0

Grocery / Markets 0 0 3 0 0

Medical & Vetinary 0 0 2 0 0

Music & Music Production 0 1 0 0 0

Newsagents & Post Office 0 1 1 1 0

Restaurant 0 2 0 0 0

Retail & Tourist Shops 1 5 8 0 0

Hospitality 3 6 1 1 0

Total 4 23 30 2 0

34 G20614827

22%

15%

7%

10%

1% 2%

5% 2%

34%

2%

Business owners’ further thoughts and opinion regarding the relationship between BACC MICE events and

local business Business opportunity

Cause parking issues

Could work better with localbusiness.Generates business throughtourism legacyGood for all ages

Good for building relationships

Good for the community

Inconvenience

None

Ugly / Poor Design

One in three businesses expressed no further thoughts or feelings regarding the relationship

between MICE events and their businesses (Figure 5.4). However, the most common of the

comments which were given was that BACC MICE events create business opportunity (22%

of total responses). Hospitality, retail and café businesses comprised 70% of this proportion.

15% of respondents expressed that BACC MICE events cause parking issues. Other

significant comments included that BACC MICE events generate business through tourism

legacy and could work better with local business (Figure 5.4).

5.2.2 Perceived Economic Impact on Local Business Owners: Analysis

D&B business owners’ perceptions support previously-discussed claims in the literature that

some business types have greater exposure to direct impacts of MICE events than others

(Rogers, 2013; Bowdin et al., 2011, EventIMPACTS 2010a). Although business owners

appear to be almost equally divided regarding BACC MICE event impact on their

businesses, different business types perceived varying exposure to impact of BACC MICE

events (Rogers, 2013). Results in this section indicate that hospitality businesses have the

greatest exposure to MICE event impacts in rural locations, closely followed by cafés and

delis, as well as retail shops. Urban EIA studies have also found these business types to be

Figure 5.4: Business Owners’ Further Thoughts and Opinions Regarding the

Relationship between BACC MICE Events and Local Business

35 G20614827

the most exposed to urban MICE events (EventIMPACTS, 2010a; Getz, 2007), indicating

similarities between urban and rural MICE event trends.

As well as supporting literature that some businesses have more exposure to MICE event

impacts (Rogers, 2013; Bowdin et al., 2011), results indicate that although some business

owners perceived no impact from BACC MICE events, few businesses perceived a negative

impact or reduction in turnover (Tables 5.1 & 5.2). Results further highlight that some

businesses recognised an indirect positive link between MICE events and business turnover,

such as building and trade businesses which indicated that MICE events increase turnover

perceiving no direct impact.

The results also indicate that the presence of BACC MICE events in D&B develop business

confidence in a significant proportion of businesses. 22% of businesses indicated that MICE

events provided a business opportunity for them (Figure 5.4). However, a large proportion of

businesses felt MICE events cause parking issues (15%), and 7% felt that MICE events

could work better with local businesses. This indicates that not all businesses see MICE

events as good for business, and some businesses also experience inconveniences as a

result of BACC MICE events.

In summary, these results indicate that certain business types (particularly hotels, cafés and

restaurants) experience greater positive impacts from BACC MICE events than many others.

Very few businesses perceived a large increase to turnover due to MICE events, which is

expected given D&B’s focus on leisure tourism activity (VisitDunkeld, 2015). Though some

increase exists to businesses, D&B businesses are in stark contrast to businesses in urban

environments which often target MICE event delegates (Rogers, 2013). Some business

owners perceived that BACC MICE events cause parking issues and should be better

coordinated with local business.

5.3 Economic Impact of Delegate Expenditure and BACC Revenue

This section presents and discusses economic impact data collected through questionnaire

survey 2 and BACC financial data. This data addresses research objective 1; to calculate

total direct economic injection of delegate expenditure, as well as the revenue and costs

associated with hosting MICE events in rural areas. These results analyse the nature and

type of expenditure as well as the amount which is leaked from the host economy, to

calculate the total direct economic impact figure. A full data set is in Appendix R.

36 G20614827

5.3.1 Economic Impact: Results

Of the 300 surveys distributed only 62 (20.66%) were completed, increasing the margin of

error to 11.99%. The actual response rate is not known since uncompleted questionnaire

surveys were redistributed to increase sample size. The actual sample population in

February 2016 was 1,070. This is 50 greater than in 2015 and further increases the margin

of error to 12.09%. This has obvious negative implications on data reliability and validity

which is discussed later in this dissertation (Chapter 6).

Inner and outer fences for data were calculated to identify outliers using the interquartile

range and upper and lower quartiles. Delegate hospitality expenditure data possessed no

major or minor outliers. Delegate non-hospitality expenditure possessed one major outlier

(the simple maximum) of an abnormally large amount. This was included in the data due to

the possibility of a business manager or owner paying for a business dinner for employees in

the evening which would be an important factor in EIA (Solberg et al, 2002, Shone & Parry,

2013). BACC catering data, BACC room hire data and delegate switching costs data all

possessed no major or minor outliers.

Both delegate accommodation and non-accommodation expenditure results were first

inputted into the adapted EventIMPACTS (2010c) calculator, discussed in the methodology.

Results are displayed in Table 5.3 and indicate that total D&B-retained estimated economic

injection from February BACC MICE event delegate expenditure after switching and leakage

costs was £39,810.52. It should be noted that 28 delegates used hospitality accommodation.

However, one delegate used accommodation outside D&B which was not considered as the

money never entered the D&B economy, resulting in 27 delegates using hospitality within

D&B (44% of total respondents).

Figure 5.5 shows the proportion of estimated total delegate accommodation expenditure to

non-accommodation expenditure to be 59% and 41% respectively. The proportion of total

estimated D&B-retained non-accommodation delegate expenditure was 40% of total non-

accommodation expenditure, with leakage and switching at 43% and 17% respectively

(Figure 5.6). Finally, Figure 5.7 shows that 76% of total estimated delegate expenditure

(accommodation and non-accommodation) was retained by D&B, as opposed to 17%

leakage and 7% switching.

37 G20614827

Table 5.3: BACC MICE Event Delegate Expenditure, Leakage & Switching (February

2016)

Figures Calculation

Actual BACC monthly delegates 1,070 N

Actual BACC sample delegates 62 n

Sample Delegate Expenditure: Accommodation

Sample delegates using D&B accommodation 27 A

Estimated total February delegates using D&B accommodation 466 B = (A ÷ n) x

N

Average number of nights spent in host economy 1.11 C

Number of commercial bed nights 517.26 D = B x C

Average cost per bed-night £60.25 E

Estimated total February revenue for D&B accommodation sector

£31,164.92 F = D x E

Delegate Expenditure: Event-Related Non-Accommodation Expenditure

Average individual delegate expenditure on non-accommodation items

£19.97 G

Estimated total February delegate expenditure on non-accommodation items

£21,367.90 H = G x N

Delegate Non-Accommodation Leakage

Leakage: Average individual delegate non-accommodation expenditure with non-local traders

£8.55 I

Total estimated February non-accommodation expenditure with non-local traders

£9,148.50 J = I x N

Delegate Non-Accommodation Switching

Switching: Average individual delegate switching costs £3.34 K

Total estimated February delegate switching costs £3,573.80 L = K x N

Total February D&B-retained delegate expenditure £39,810.52 M = F + H – J

- L

38 G20614827

£31,164.92 59%

£21,367.90 41%

BACC MICE Event Delegate Accommodation & Non-Accommodation Expenditure

Accommodation Expenditure

Non-AccommodationExpenditure

£8,645.60 40%

£9,148.50 43%

£3,573.80 17%

BACC MICE Event Delegate Non-Accommodation Leakage, Switching and D&B-Retained Expenditure

D&B-Retained Non-Accommodation Expenditure

Non-Accommodation Leakage

Non-AccommodationSwitching

Figure 5.5 BACC MICE Event Delegate Accommodation & Non-Accommodation

Expenditure

Figure 5.6: BACC MICE Event Delegate Non-Accommodation Leakage,

Switching and D&B-Retained Expenditure

39 G20614827

£39,810.52 76%

£9,148.50 17%

£3,573.80 7%

Total BACC MICE Event Delegate Leakage, Switching & D&B-Retained Expenditure

Total D&B-Retained DelegateExpenditure

Total Delegate Leakage

Total Delegate Switching

Organiser revenue was calculated using revenue and costs of BACC catering and room hire.

All MICE events were held by companies from outside the host economy, meaning that all

were included in the research. Table 5.4 shows total D&B-retained economic injection

through BACC revenue for the month of February after leakage to be £10,070.68.

Figure 5.7: Total BACC MICE Event Delegate Leakage, Switching & D&B-

Retained Expenditure

40 G20614827

Table 5.4: BACC Revenue & Leakage (February 2016)

Figure Calculation

BACC Room hire Revenue & Leakage

Total BACC February room hire revenue £6,853.34 O

Total BACC room hire VAT £1370.67 P = O x 0.2

Total D&B-retained room hire revenue £5,482.67 Q = O – P

BACC MICE Event Catering Revenue & Leakage

Total BACC February MICE event catering revenue £8436.33 R

BACC Catering VAT £1687. 27 S = R x 0.2

Total BACC non-local supplier costs £2,161.05 T

Total D&B-Retained BACC February MICE event catering revenue

£4,588.01 U = R – S - T

Total D&B-retained BACC February MICE event revenue £10,070.68 V = Q + U

Figures 5.8 and 5.9 show the proportions of leakage to D&B-retained BACC room hire and

catering revenue to be 20% against 80%, and 46% against 54% respectively. Figure 5.10

shows the proportions of D&B-retained room hire revenue and catering revenue to be

relatively even (54% and 46% respectively). Figure 5.11 shows total BACC leakage to be

34% of total BACC revenue, with 66% being retained by D&B. Graphs are for the month of

February 2016 only.

41 G20614827

£5,482.67 80%

£1,370.67 20%

BACC Room Hire Leakage & D&B-Retained Room Hire Revenue

Retained BACC Room HireRevenue

VAT Leakage

£4,588.01 54%

£1,687.27 20%

£2,161.05 26%

BACC catering revenue, VAT and supplier figures

Retained BACC CateringRevenue

VAT Leakage

Supplier Leakage

Figure 5.8: Proportion of BACC Room hire Leakage to D&B-Retained Room

hire Revenue

Figure 5.9: Proportion of BACC Room hire Leakage to D&B-Retained Catering

Revenue

42 G20614827

£4,588.01 , 46%

£5,482.67 , 54%

Total Estimated D&B-Retained BACC Room hire & Catering Revenue (February 2016)

Catering

Room Hire

£10,070.68 , 66%

£5,218.99 , 34%

Total Estimated BACC Revenue: D&B-Retained Revenue & Leakage

D&B-Retained BACCRevenue

BACC Leakage

Figure 5.10: Total Estimated D&B-Retained BACC Room hire & Catering

Revenue

Figure 5.11: Total Estimated BACC Revenue: D&B-Retained Revenue &

Leakage

43 G20614827

BACC revenues and the delegate expenditure were combined to produce total estimated

D&B-retained economic injection for the month of February, which was then divided by the

sample population to produce an estimated D&B-retained economic injection figure per

delegate (Table 5.5). Delegate expenditure comprised 80% of the total D&B-retained

economic injection, against 20% from BACC revenue (Figure 5.12). A summary including

total leakage and switching is shown in Figure 5.13.

The figure-per-delegate was then multiplied by actual delegate figures for individual months,

years, high seasons and low season. These results are shown in Table 5.6, as well as the

comparison of high season monthly D&B-retained economic injection against that of the low

season (Figure 5.14).

Table 5.5: Total February Economic Injection & Economic Injection per Delegate

Figure Calculation

Total D&B-retained economic injection resulting from BACC MICE events during February

£49,881.20 W = M + V

Average D&B-retained economic injection resulting from BACC MICE events per individual delegate

£46.62 X = W ÷ N

£10,070.68 20%

£39,810.52 80%

Total D&B-Retained Februrary 2016 Economic Injection & Leakage

BACC

Delegate Expenditure

Figure 5.12: Total Estimated BACC Revenue: D&B-Retained Revenue & Leakage

44 G20614827

Table 5.6: BACC MICE Events Monthly & Annual Economic Injection Estimates (2014 –

2015 tax year)

Figure Calculation

Annual BACC MICE delegates 8,628 Y

Average monthly BACC MICE delegates 719 Z

Average high season monthly BACC MICE delegates 995 a

Average low season monthly BACC MICE delegates 168 b

Annual D&B-retained economic injection resulting from BACC MICE events

£402,237.36 c = X x Y

Average monthly D&B-retained economic injection resulting from BACC MICE events

£33, 519.78 d = X x Z

Average high season monthly D&B-retained economic injection resulting from BACC MICE events

£46,386.90 e = X x a

Average low season monthly D&B-retained economic injection resulting from BACC MICE events

£7, 832.16 f = X x b

£49,881.20 74%

£14,367.49 21%

£3,573.80 5%

Total Estimated BACC Revenue: D&B-Retained Revenue & Leakage

Total D&B-RetainedEconomic Injection

Total Leakage

Total Swtiching Costs

Figure 5.13: Total Estimated BACC Revenue: D&B-Retained Revenue & Leakage

45 G20614827

5.3.2 Economic Impact: Analysis

The results support and contest a number of key theories discussed in the literature review.

First, the results strongly contest both Mehmetoglu’s (2002) and Buultjens & Cairncross’s

(2015) claims of such high leakage from events in rural areas that economic benefits may be

lost. Figure 5.13 shows total leakage was only 21% of the total money injected into the D&B

economy as a result of BACC MICE events. 75% was retained by D&B. Further, only 34% of

gross BACC revenue was leakage (Figure 5.11), and only 17% of total delegate expenditure

(Figure 5.7). This indicates that D&B is a rural town which is able to retain much of its direct

economic injection from MICE events, which may also be true of other rural areas. Since this

study employed the DEA approach, leakage in further business transactions was not

quantified and could only be identified through future advanced EIA.

Second, the results supports EventIMPACTS’ (2010a) previously-discussed claim that

economic impact occurs principally through delegate expenditure, indicating that this is also

the case in rural areas. Figure 5.12 shows delegate expenditure to comprise 80% of total

D&B-retained economic injection. However, BACC revenue is also a significant contributor

with 20%; supporting the literature that venue revenue is an important factor in EIA (Lee,

2006). This indicates that rural MICE events mirror their urban counterparts regarding the

dominant channel of MICE economic injection.

£-

£5,000.00

£10,000.00

£15,000.00

£20,000.00

£25,000.00

£30,000.00

£35,000.00

£40,000.00

£45,000.00

£50,000.00

High Season Low Season

Average monthly High Season & Low Season D&B-Retained Economic Injection

Average monthly D&B-Retained Economic Injection

Figure 5.14: Average monthly High Season & Low Season D&B-Retained

Economic Injection

46 G20614827

Third, results support the literature that the accommodation sector is one of the largest direct

beneficiaries of MICE event economic injection. Figure 5.12 shows that 80% of D&B retained

February economic injection was through delegate expenditure. Figure 5.5 shows that 59%

of D&B-retained delegate expenditure was on accommodation, making accommodation

expenditure 47% of total D&B-retained economic injection. Most research in the literature

has been in urban areas, meaning that little was known regarding whether this was also the

case in rural areas. This research indicates that rural areas are similar to urban areas in this

way.

Fourth, it is clear that BACC MICE events have a significant positive impact on the D&B host

economy. Economic injection as a result of BACC MICE events totals £402,237.36 annually

and is likely to have a significant effect on the many hotels and other businesses (of which

the majority in D&B are SME’s) through which it passes. The economic impact of BACC

MICE events is, however, significantly greater in high season months than in low season,

which may cause problems for businesses that do not experience an even spread of annual

revenue as a result. However, the BACC MICE low season coincides with the leisure tourism

high season, which is likely to counteract this imbalance somewhat. The disparity between

high and low season economic impact is a widely accepted trend of urban MICE events

(Getz, 2007), and indicates that rural MICE events are subject to similar sectoral trends as

their urban counterparts.

Finally, the literature review in this dissertation highlighted a claim by Jones & Li (2015), that

high venue cost causes profitability of MICE facilities to be often marginal, focusing

economic benefits on delegate expenditure. The results agree with this to an extent, since

the greatest proportion of D&B-retained economic impact was through delegate expenditure.

However, BACC revenue did comprise a significant proportion of the total economic impact.

Furthermore, it may be incorrect to label BACC MICE revenue as marginal, since its

February MICE event revenue (£10,070.86) may be significant for a rural MICE event venue

of its relatively small size.

It should be noted that although the BACC MICE events economic impact figure is significant

to D&B, this figure is likely to be smaller than figures produced by many other urban

economic impact analyses. Relevance to the host economy may, however, be relative and

equal or even surpass that of urban areas. This, however, is an area for future research and

is not discussed in or claimed by this dissertation.

47 G20614827

5.4 Resident Attitudes Toward and Perceptions of BACC MICE Events

This section presents and describes data and results obtained through questionnaire 3. This

addresses research objective 4; to investigate general public attitudes toward, and

perceptions of, BACC MICE events within D&B. A full data set is in Appendix S.

5.4.1 Resident Attitudes Toward and Perceptions of BACC MICE Events: Results

105 D&B resident questionnaires were successfully completed with no complications.

Residents perceived that BACC MICE events had largely little or no impact on noise levels,

crowding levels, crime levels, and property value (see Table 5.7).

Table 5.7: Resident Perceptions of BACC MICE Event Impact on Noise Levels,

Crowding Levels, Crime Levels and Property Value

Noise

Levels

Crowding

Levels Crime Levels Property Value

Strongly

Increased 0% 1% 0% 0%

Increased 10% 12% 1% 17%

No Impact 90% 87% 96% 81%

Reduced 0% 0% 1% 2%

Strongly

Reduced 0% 0% 2% 0%

Figure 5.15 shows that 31% of respondents perceived BACC MICE events to cause

increased congestion, and 22% perceived it to have a strong increase. 47% perceived no

impact to congestion and no respondents perceived any congestion decrease. This is

supported by questionnaire 1’s final question (Figure 5.4) in which a quarter of respondents

freely expressed a similar perception.

48 G20614827

Two thirds of respondents perceived no impact to quality of life as a result of BACC MICE

events (Figure 5.16). However, one third perceived that quality of life was either improved or

strongly improved. Only 3% perceived that quality of life was worsened.

22%

31%

47%

Resident Perceptions: Impact of BACC MICE Events on D&B Congestion Levels

Strongly Increased

Increased

No Impact

Reduced

Strongly Reduced

7%

28%

62%

3%

Resident Perceptions of the BACC MICE Event Impact on Quality of Life

Strongly Improved

Improved

No Impact

Worsened

Strongly Worsened

Figure 5.15: Resident Perceptions of the BACC MICE Event Impact on D&B

Congestion Levels

Figure 5.16: Resident Perceptions of the BACC MICE Event Impact on Quality

of Life

49 G20614827

80% of respondents perceived an improvement or strong improvement to social and

community ties due to BACC MICE events (Figure 5.17), leaving only 20% perceiving no

impact.

37% of respondents perceived an improvement to local infrastructure, as well as 4% which

perceived a strong improvement. 56% of respondents perceived no impact to local

infrastructure, and 3% perceived that local infrastructure was worsened due to BACC MICE

events (Figure 5.18).

33%

47%

20%

Resident Perceptions of the BACC MICE Event Impact on Social and Community Ties

Strongly Improved

Improved

No Impact

Worsened

Strongly Worsened

4%

37%

56%

3%

Resident Perceptions of BACC MICE Event Impact on Local Infrastructre

Strongly Improved

Improved

No Impact

Worsened

Strongly Worsened

Figure 5.17: Resident Perceptions of the BACC MICE Event Impact on Social

and Community Ties

Figure 5.18: Resident Perceptions of the BACC MICE Event Impact on Local

Infrastructure

50 G20614827

77% of respondents agreed or strongly agreed that BACC MICE events support local

business (Figure 5.19); a statement against which only 13% disagreed or strongly disagreed.

A further 10% perceived no impact. 88% agreed or strongly agreed that BACC MICE events

support tourism in D&B (Figure 5.20) whilst only 9% perceived no impact and only 3%

disagreed. None strongly disagreed.

30%

47%

10%

9% 4%

The Extent to which D&B Residents Agree that BACC MICE Events Support Local Business

Strongly Agree

Agree

Neither Agree nor Disagree

Disagree

Strongly Disagree

39%

49%

9%

3% 0%

The Extent to which D&B Residents Agree that BACC MICE Events Support Tourism in D&B

Strongly Agree

Agree

Neither Agree nor Disagree

Disagree

Strongly Disagree

Figure 5.19: The Extent to which D&B Residents Agree that BACC MICE Events

Support Local Business

Figure 5.20: The Extent to which D&B Residents Agree that BACC MICE Events

Support Tourism in D&B

51 G20614827

44% of respondents had no further thoughts or opinions. Of opinions given, the most

frequent was that BACC MICE events cause parking issues, expressed by 26% of

respondents (Figure 5.21). 8% perceived that BACC MICE events unite the community and

7% that that they improve D&B as a tourist destination. All response percentages are shown

in Table 5.8.

Figure 5.21: D&B Residents’ Further Thoughts, Feelings or Opinions regarding

BACC MICE Events

D&B Residents’ Further Thoughts, Feelings or

Opinions regarding BACC MICE Events

26%

2%

2% 1%

1%

1% 7%

6% 4%

2% 1% 1%

1%

44%

1%

Resident's Free-Response Questions Parking problems

The facility is underused

MICE events contribute to unsightlyinfrastructure (BACC)Divides the Community

Too many MICE events

MICE events are too politically biased

MICE events unite the community

MICE events improve D&B as touristdestinationMICE events are well supported in thecommunityGood location / venue for MICE events

Impressive level of MICE activity

MICE events bring revenue to localresidents & businessesMICE events are well managed

No Comments

Not aware of MICE events

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Table 5.8: The Extent to which Residents Perceive Social Benefits & Inconveniences

to be positively or negatively impacted by BACC MICE Events. E.g. 54% of respondents

perceive increased inconveniences through congestion. Each respondent could express up

to three further thoughts.

Inconveniences Benefits

Increased

(%)

Decreased

(%)

Increased

(%)

Decreased

(%)

Congestion 54% 0% Social Ties 82% 0&

Noise

Levels 10% 0%

Property

Value 17% 2%

Crowding

levels 13% 0%

Quality of Life 35% 3%

Crime

levels 1% 3%

Local

Infrastructure 41% 3%

Local

Business

Support

79% 13%

D&B Tourism

Support 88% 3%

5.4.2 Public Attitudes Toward and Perceptions of BACC MICE Events: Analysis

The results of questionnaire 3 strongly support Schofield’s (2011) claim that MICE events

and subsequent business tourism may influence social attitudes as a result of event-related

benefits and inconveniences. Many of Dwyer’s et al. (2000b) and Shone & Parry’s (2013)

suggested areas of social impacts listed in Table 3.1 were areas of particular benefit or

inconvenience for D&B residents.

Despite a significant proportion of respondents perceiving BACC MICE events to cause

increased congestion (Figure 5.15) or parking problems (Table 5.8), there is significantly

more agreement with their benefits than inconveniences within Likert-scale response data.

Only 10% of all combined Likert-scale responses were negative, against 35% positive. This

supports King’s et al. (1993) and Roger’s (2013) claims, discussed in the literature review

(Chapter 3), that residents may experience conflicts of interest regarding social impacts of

events, and may tolerate some inconveniences (in this case, congestion and parking) to

reap greater social and economic rewards. It also supports Maslow’s (1987) theory that

53 G20614827

economic needs (by way of association with physiological needs) are more fundamental to

human life than social needs, and social inconveniences may therefore be tolerated to reap

economic or physiological benefits.

However, a greater proportion of free-response questions (31%) highlighted negative

impacts than positive impacts (22%) (Figure 5.21). 82% of these negative free-response

questions were focused on parking problems associated with the MICE events, indicating

that parking is a significant inconvenience for D&B residents. Yet, of the respondents which

highlighted parking problems, 67% agreed that BACC MICE events support local business,

and 85% agreed that they support D&B tourism. This conflict of negative and positive

impacts of MICE events adds further support to King’s et al (1993) and Roger’s (2013)

claims.

5.5 Delegate Perceptions of the D&B Host Destination

This section presents and discusses data and results collected through questionnaire 2

relating to delegate perceptions of D&B. This addresses research objective 2; to investigate

MICE event delegate perceptions regarding their impression of D&B. A full data set is in

Appendix T.

5.5.1 Delegate Perceptions of the D&B Host Destination: Results

Delegate perceptions of D&B were calculated by grouping the free-response adjectives

given by delegates into categories, then ranking the categories by frequency. Delegate

perceptions of D&B were overwhelmingly positive. 99% of delegates expressed positive

perceptions of D&B which are displayed in Figure 5.22. The most common perception was

that D&B was ‘quiet’, followed by ‘beautiful’, ‘quaint’ ‘rural’ and ‘friendly’. Positive perceptions

were supported by 85% of delegates who, when questioned, stated that they would consider

returning for a personal holiday. Only 3% stated that they would not consider this, and 12%

answered ‘maybe’ (Figure 5.23).

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85%

3% 12%

Number of BACC MICE Event Delegates who would Consider Returning to D&B for a Personal Holiday

Yes

No

Maybe

14%

9%

8%

8%

7% 6%

6%

6%

6%

5%

5%

5%

5%

4% 4%

4%

BACC MICE Event Delegate Free Responses: Impression of D&B Quiet

Beautiful

Quaint

Rural

Friendly

Convenient

Historic

Pretty

Scenic

Central

Peaceful

Pleasant

Attractive

Accessible

Pretty

Small

Figure 5.22: BACC MICE Event Delegate Free Responses: Impression of D&B

Figure 5.23: Number of BACC MICE Event Delegates who would Consider

Returning to D&B for a Personal Holiday

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5.5.2 Delegate Perceptions of the D&B Host Economy: Analysis

These results support Davidson’s (1994) suggestion that MICE events may boost local

tourism in the host economy through delegates who leave with a positive impression and

promote the location to other colleagues and associates. D&B, already a popular tourist

destination, may further increase popularity amongst tourists through MICE events in this

way as well as through tourism legacy from the return visit of MICE delegates. This,

however, may not apply to all rural locations. D&B is an already-popular and famously

beautiful destination. Other rural locations may not leave the same positive impression on

MICE delegates.

5.6 Chapter Summary

This chapter presented the results from the research conducted in D&B, and discussed them

in relation to theory presented in the literature review to address the research aims and

objectives. The economic impact of BACC MICE events on the D&B host economy were,

both socially and economically, overwhelmingly positive. Results showed a significant

positive economic impact to D&B, a largely positive impact on businesses, evidence of MICE

delegates leaving D&B with a positive impression, and awareness amongst residents of the

predominantly positive benefits to D&B. However, a significant number of businesses

perceived no impact on their business, and a large number of residents noted a significant

parking inconvenience. Final conclusions, as well as scope for future research and

limitations of the study will be addressed in the next chapter.

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Chapter 6

Conclusion

6.1 Introduction

This chapter summarises the main findings of this research and highlights how the study’s

aims and objectives were addressed. Key contributions of the research to the wider

academic community are highlighted, followed by a discussion of research limitations and

constraints. Finally, potential future research areas that grow from this study are identified.

6.2 Summary of Main Findings

Main findings in this chapter are summarised below according to the aims and objectives of

the study, presented in Table 6.1.

Table 6.1: Research Aims & Objectives

Aim To investigate the economic and social impacts of MICE events upon a rural

host economy (D&B)

Objective

1

To calculate total direct economic injection of delegate expenditure as well as

the revenue and costs associated with hosting MICE events at the chosen venue

(BACC) in a rural location (D&B). This investigates the nature and type of

expenditure as well as the amount which is leaked from the host region,

contributing towards the direct economic impact figure.

Objective

2

To investigate MICE event delegate perceptions regarding their impressions of

the venue’s host destination (D&B).

Objective

3

To investigate perceived economic impacts of BACC MICE events upon local

business-owners.

Objective

4

To investigate general public attitudes toward, and perceptions of, BACC MICE

events within D&B.

6.2.1 Objective 1 – Economic Impact Analysis

Objective 1 was achieved through EIA using the DEA based on a combination of the Wood

(2005) and EventIMPACTS (2010b) models. Delegate spending was calculated and found to

be the most significant economic stimulus resulting from MICE events. Of delegate

spending, hotel and accommodation spending comprised the largest area of delegate

expenditure, followed by expenditure in local businesses, and finally in chain businesses.

57 G20614827

This research adapted the EventIMPACTS (2010c) calculation to create a formula for the

calculation of leakage (Chapter 4.10). Leakage and switching costs were significant (17%

and 7% of total delegate expenditure respectively) but over 75% of delegate expenditure

was retained by the D&B host economy. The combined economic stimuli of delegate

expenditure and BACC revenue were calculated to produce an economic injection figure of

£48.98 per delegate. Based on the number of delegates for the 2014 – 2015 tax year, this

produces an annual economic injection estimate of £402,237.36.

The significant economic stimulus retained by D&B, a rural area, indicates that MICE events

in rural areas do have an important economic impact on local business, particularly hotels.

This supports the preponderance of literature around the positive direct impact of MICE

events in urban areas (Cooper et al., 1993; Cameron, 2009; Lee, 2006) and suggests that

rural MICE events have a similar impact, albeit on a smaller scale. However, it discredits

claims that economic stimulus of rural MICE events is so significantly leaked that its positive

impact is lost (Mehmetoglu, 2002; Buultjens & Cairncross, 2015).

Finally, suggestions that DEA is the most practical EIA approach (Davies et al., 2013; Wood,

2005) for resource-limited practitioners were supported by this theory, as complicated and

resource-intensive indirect and induced EIA would have been impractical in this resource-

limited research.

6.2.2 Objective 2 – Delegate Perceptions of D&B as a Tourist Destination

Objective 2 was achieved and found that Cameron’s (2009) claim, that MICE events have

such significant positive impacts on host destinations that they should be considered a

means of economy development, was greatly supported by the results of this study. 99% of

delegates expressed positive perceptions of D&B, and 85% stated they would consider a

personal holiday in the area, showing significant potential for tourism legacy. Since D&B’s

economy is largely based on tourism (D&B, 2015), increased tourist activity would have a

positive economic impact.

6.2.3 Objective 3 - Perceived Economic Impacts of BACC MICE Events on Local

Business-Owners.

Objective 3 was achieved and found that business owners’ perceptions of the impact of

BACC MICE events on their businesses add further support to the positive economic

impacts of MICE events in rural areas. Business owners were relatively evenly divided

regarding whether MICE events impacted their business, but those who perceived an impact

primarily perceived an increase or large increase to business turnover as a result of BACC

58 G20614827

MICE events. These were primarily hospitality, retail and café businesses. Delegate

expenditure results supported this and indicated that hotels received the largest proportion of

delegate expenditure. This also supports Cooper’s et al. (1993) claim that such businesses

are amongst those most positively impacted by MICE events. However, one hotel manager

perceived a reduction in turnover due to MICE event competition from BACC.

6.2.4 Objective 4 - To investigate general public attitudes toward, and perceptions of,

BACC MICE events

Objective 4 was achieved and found that resident perceptions largely supported Roger’s

(2013) and King’s et al. (1993) suggestion that conflicts of interest occur regarding social

impacts of MICE events. Although the majority of responses were generally positive,

residents also strongly expressed that parking problems due to BACC MICE events are a

significant inconvenience. App’s (1992) use of SET is also supported by the results. The

majority of residents in the sample acknowledged the positive economic impacts of BACC

MICE events on local business and D&B tourism, which appear to outweigh the negative

social inconveniences of parking issues. Other positive impacts such as am improvement of

community ties, local infrastructure and quality of life also existed.

6.3 Research Contributions

This research contributes to filling the gap within the literature regarding the socio-economic

impact of MICE events in rural locations. The research may be of use to academics wishing

to investigate the difference in delegate expenditure or retained economic stimulus between

urban and rural MICE events. The research may also be of importance to local authorities

and investors who are considering developing MICE event facilities in rural locations and

want cost-benefit analysis. Finally, MICE event organisers and BACC management may use

this research to understand the impact of MICE events on the D&B host economy.


This research was subjected to a number of limitations which are detailed in Table 6.2.

These limitations impact the reliability and validity of the data and, if removed, would provide

more reliable results.

59 G20614827

Table 6.2: Research Limitations

1 Questionnaire 2: Skipping questions regarding hotel cost if the respondent stayed outside

B&D does not allow for the calculation of the amount of money lost to D&B by delegates

who book accommodation outside D&B. This could have provided further information to

see how much money was lost from D&B.

2 Questionnaire 1: Although a random number table was used, D&B has too few businesses

to question an equal number of each businesses type and maintain an acceptable margin

of error. For example, eleven hotels were questioned but only three trade businesses. This

created bias within the data and meant more businesses were questioned which are more

likely to be exposed to MICE event impacts (e.g. hotels) than those which are less likely to

be exposed (e.g. banks). However, this is representative of D&B’s tourism focus.

3 Since BACC is not exclusively a MICE event venue, only BACC expenses which were

directly attributed to MICE events were accounted for. General costs (e.g. heating,

electricity) were not considered. This has negative impacts on the BACC financial data

reliability and validity.

4 The small delegate sample size meant the EIA research had a 12.09% margin of error.

This could have been reduced by distributing more survey questionnaires to BACC

management. Obtaining 280 responses from 300 questionnaires would require a 93%

response rate and is highly unlikely (Veal, 2011). However, it should be noted that the

exact response rate is unknown due to the redistribution of –not-completed questionnaire

surveys.

5 The accuracy and actual representativeness of delegate expenditure is unknown. The use

of diary methods in addition to recall questionnaire surveys may provide more accurate

results regarding delegate expenditure.

6.5 Suggestions for Future Research

There are a number of areas for future research which grow from this study. First, the study

and its calculation formula could be replicated in other UK rural locations to test the results of

this research and investigate whether similar trends occur in other rural locations. This would

provide a more reliable indication of rural MICE event trends. Second, as suggested by

Jones & Li (2015), this DEA study could provide the first stages for further research into the

indirect and induced impacts of BACC mice events in D&B using an economic multiplier.

This would investigate the deeper economic impacts of BACC MICE events upon the D&B

60 G20614827

host community on a micro- and macro-economic scale and would provide more accurate,

long-term and inter-sectoral estimates. Finally, further research could be conducted to

investigate the ongoing impact of BACC development costs and investment which may have

been taken from the D&B economy to invest in the facility. This, as well as ongoing service,

maintenance and running costs, may further influence economic impact.

6.6 Chapter Summary

This research investigated the socio-economic impacts of BACC MICE events in D&B, a

rural town, and found both social and economic impacts to be largely positive, although

some negative social impacts were also present. Direct economic stimulus was largely

retained by D&B and has a positive impact on local business, particularly D&B’s hospitality

sector. This research contributes to filling the gap in literature regarding socio-economic

impacts of rural MICE events and suggests that many themes of extant urban MICE EIAs

also apply to rural MICE events. Replication of this research in other rural towns and areas is

needed to more reliably and accurately understand the socio-economic impacts of rural

MICE events.

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Appendices

Appendix A: Dunkeld & Birnham

Situated on the river Tay, a short journey from the Cairngorms, and surrounded by historic

towns and forests, D&B attracts significant summer leisure tourism (D&BTA, 2015). Once the

ecclesiastical capital of medieval Scotland and a ‘second home’ to Beatrix Potter, D&B is

visited by many heritage tourists. Birnam Wood, featured in Shakespeare’s Macbeth, is a

further tourist attraction in the area.

The above images show the location of Dunkeld, Scotland. The image on the left shows the

3-mile radius which is the chosen geographical location for the host economy. The image on

the right shows Dunkeld’s location in Scotland.

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Appendix B: Birnam Arts & Conference Centre

The BACC is a multi-purpose event venue, providing facilities for a range of community and

MICE events, as well as offering a library, council office space, a café, gift shop, art

exhibitions, and Beatrix Potter World (a popular leisure tourist attraction). It is overseen and

owned by the community through voluntary trustees and directors, and run by Birnam Arts

Ltd (the organisation responsible for operations at BACC), which donates all profit from the

venue in the form of Gift Aid to its charity arm, the Birnam I. BACC was built as a community,

leisure and event venue, and expanded into MICE events to become more financial

sustainable. This now generates much, if not most, of BACC’s revenue (Flatley, 2016).

BACC receives little in the way of government support or grants and is limited to £15,000 per

year from the local authority.

BACC provides state of the art facilities for meetings and exhibitions, hosting events for

businesses within D&B and in surrounding areas. A large number of national groups hold

MICE events at the venue such as the British Horse Society, RICS Scotland, Planning Aid

for Scotland and The Scottish Stammering Association, Transport for Scotland, the Scottish

Forestry Commission and the Hutton Institute.

It should be noted that BACC has been known by a number of names since its establishment

in 2001 such as Birnam Arts, the Birnam Institute, and Birnam Arts and Conference Centre.

At the time of starting this research the venue was known as the latter, which is the term that

is used throughout this research.

The above image shows the Birnham Arts & Conference Centre

Undiscovered Scotland [Online] Birnham Arts & Conference Centre. Available at:

http://www.undiscoveredscotland.co.uk/dunkeld/birnaminstitute/. (Accessed: 05 November 2015).

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Appendix C: Switching & Leakage

Switching: Information must be gathered about switching which occurs when a person

spends money at a MICE event which he or she would still otherwise have spent in the same

host economy had the MICE event not taken place. This may occur, for example, if a

resident of the host community attended an event in his or her own home town on a

Saturday. If the resident spent £100 on event-related costs but usually spent £80 within the

host economy on a normal Saturday, the £80 would be classes as switching costs and would

not count towards the direct economic impact of the event. Only the remaining £20 would be

considered, because it is the only money that would otherwise not have been spent, had the

event not taken place.

Leakage: Leakage is money that is spent by visitors to the host economy which then leaves

the host economy (also known as ‘direct leakage’). An example of this is if a business visitor

purchases an Apple Laptop for £1,000 from an Apple Store in Dunkeld (there is no Apple

Store in Dunkeld – this example of purely just to explain the concept of leakage). Since

Apple is not from the rural Scottish highlands, the large majority, if not all that money, will

immediately leave the host economy and go elsewhere. This would result in a business

visitors spending £1,000 but actually contributing very little to the host economy.

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Hypothetical Input – Output Table (Miernyk, 1965)

Appendix D: Input – Output Multiplier (I-O) Model

Regional I-O’s use detailed industry data to quantify each industry’s output, as well as the

use of this output by other companies and end users (Bess & Ambargis, 2011). The I-O then

measures the impact of event-related revenue on other sectors within the host economy, as

well as the sectoral consequence of industry-specific vicissitudes in final demand.

Exogenous injection of expenditure in one industry causes increased inputs supplied to other

industries. The I-O model does, however, have many disadvantages such as the ridged

assumption of fixed co-efficient production (in reality, factor substitution over a long period of

time is highly likely) as well as the unrealistic assumption that increases in outputs of one

industry will always lead to input increase in another (Bess & Ambargis, 2011; Chad, 2015).

Abelson (2011) further highlights that I-O multipliers measure only changes in output,

ignoring welfare and possible price increased as a result of increased economic activity.

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Appendix E: Computer-Generated Equilibrium (GCE) Model

The CGE model is an extremely rigorous and highly-complex evaluation method of economic

shock and injection within a defined economy, often containing many thousands of economic

equations (Abelson, 2011). GCE aims to reproduce the economy structure as realistically as

possible, as well as existing economic transaction between industry sectors, governments

and households (IADB, 2015).

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Appendix F: Social Accounting Matrix (SAM)

A SAM measures an area’s accounts and identifies relationships between sectoral supply

and demand. Using fixed prices, it measures inter-sectoral impacts by simulating changes to

the economy. SAMs are most commonly used to measure a national economy through the

measurement of national accounts, but can also be created for areas or whole regions.

CGE’s are based on SAMs (WorldBank, 2011).

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Appendix G: Cost - Benefit Analysis (CBA) Model

Cost - Benefit Analysis (CBA) is a method of evaluating the economic costs and benefits of

(usually) large scale investment projects. All internal and external perceived costs and

benefits are estimated, as well as those of alternative projects. The option with the highest

net benefits is selected. It is often very expensive to undertake, and it can also be very

difficult to place a value on benefits and costs (EO, 2016).

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Appendix H: EventIMPACTS Model Developers

The Events IMPACTS model was developed by a number of UK governing bodies. These

included UK Sport, Visit Britain, EventScotland, London Development Agency, the North

West Development Agency, Yorkshire Forward and Glasgow City Marketing Bureau.

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Appendix I: Closed, Recall, Process & Open-Ended Questions (SYN, 2014)

Closed questions: Invite a brief one word answer; ‘yes’ or ‘no’.

Recall questions: Recall questions are used when the questions required something

to be remembered, such as how much business visitors have spent and on what

during their event-related stay in the host economy.

Process questions: Usually require some deeper thought and/or analysis. Process

questions were used to ask business owners how BACC events affect their turnover.

They will answer in a 4 point Likert scale.

Open-ended questions: These present a question to which the respondent must give

an answer that involves multiple words or explanation. It is designed to encourage a

full, meaningful answer.

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Appendix J: Questionnaire Survey 1: Business Owners’ Perceptions

Interviewer should tick only 1 answer for each question

Question 1

Do you feel that business events at Birnam Arts & Conference Centre have an impact upon your

business?

Yes No

Question 2

Do business events at Birnam Arts & Conference Centre, and / or the delegate expenditure

thereof, have an impact on your turnover on the day of the event?

Large Increase

Increase No Impact

Decrease Large decrease

Question 3

Do business events at Birnam Arts & Conference Centre, and / or the delegate expenditure

thereof, have an impact on the long-term turnover of your business?

Large Increase

Increase No Impact

Decrease Large decrease

Question 4

Please briefly describe any other thoughts or feelings you have about the relationship between

business events at Birnam Arts and the profitability of your business.

………………………………………………..………………………………………………..………………………………………………..…

……………………………………………..………………………………………………..………………………………………………..……

…………………………………………..………………………………………………..………………………………………………..………

………………………………………..……………………………………………………………………………..

Interviewer should note the business type of the business in questions

Business Type & Sector:………………………………………………………………………………….

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Appendix K: Questionnaire 2 - Delegate Expenditure & Perception of Host Economy

Event Management BA (Hons) Dissertation Research

To what Extent do Rural Business (MICE) Events at Purpose-Built Venues have a

Direct Social & Economic Impact on the Rural Host Economy?

Sebastian F. Field

[email protected]

University of Central Lancashire

Thank you for your participation.

Please fold with this face on the outside and return to

Birnam Arts staff upon completion.

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Town of residence (e.g. ‘Dunkeld’ or ‘Perth’)…………………………………………….

1. Are you staying overnight away from home in order to attend this meeting / conference at

Birnam Arts? (please circle)

Yes

No

2. Are you staying in Dunkeld & Birnam, or within approximately 3 miles of the town centre)?

(please circle)

Yes

No (If no, please go to question 6)

3. How much are you spending on accommodation per night?

£……………………………………………………..

4. Upon leaving, how many nights will you have stayed in Dunkeld & Birnam because of the

event? …………………………………………………………….

5. Upon leaving to return home, approximately how much will you have spent within Dunkeld

& Birnam or an approximately 3k radius only on items in the following categories:

Chain Stores (e.g. Tesco Local Businesses (e.g. local,

Shell, Pizza Express) restaurants, bars, gift shops)

Food & Drink £…………………….. £…………………….

Entertainment £…………………….. £…………………….

Travel £…………………….. £…………………….

Shopping £…………………….. £…………………….

Other £……………………… £……………………..

6. Approximately how much would you have spent in Dunkeld & Birnam had this

meeting/conference not taken place?

£…………………………………………………………..

7. Please list 3 key words to describe your impression of Dunkeld & Birnam as a location

-------------------------------- -------------------------------- --------------------------------

Would you consider return to Dunkeld & Birnam on a personal visit or holiday?

Yes / No / Maybe (Please circle)

Thank you for your participation. Pease fold this paper and return to conference centre staff.

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Appendix L: Questionnaire 3 – Resident Perceived Social Impacts

What do you feel the impacts of business events (Meetings, Conferences, Exhibitions etc.) held at Birnam Arts and Conference Centre are on the following in Dunkeld & Birnam? Please state to what extent you agree with the following statements:

Business events at BACC cause …………. to be ………..

1 – Level of Congestion:

Strongly Increased Increased No Impact Decreased Strongly Decreased

2 – Noise Levels:


3 – Crowding Levels:


4 – Quality of Life:

Strongly improved Improved No Impact Worsened Severely Worsened

5 – Crime:

Strongly Increased Increased No Impact Lessened Severely Lessened

6 - Social and Community Ties:

Strongly Improved Improved No Impact Worsened Severely Worsened

8 – Local Infrastructure:

Strongly Improved Improved No Impact Worsened Severely Worsened

9 - Property Valuations:

Strongly increased Increased No Impact Decreased Severely Decreased

7 – Business Events at BACC support local business. Do you:

Strongly Agree Agree Neither Agree or Disagree Disagree Strongly Disagree

10 - Business Events at BACC support tourism in Dunkeld & Birnam. Do you:

Strongly Agree Agree Neither Agree or Disagree Disagree Strongly Disagree

Do you have any other thoughts, feelings or opinions about business events at BACC?

..................................................................................................................................................................

........................................................................................................................................................................................................................

........................................................................................................................................................................................................................

.......................................................................................................................................................................................................................

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Appendix M: Finite Population Correction Factor

When a sample size is greater than 5% of the sample population from which it is being

chosen, a finite population correction factor can be used. The finite population correction

factor would cause the sample size to sample population ratio to become larger than if a

finite population factor need not to used. The increase in sample ratio size shows extra

precision since the standard deviation (margin of error) as the sample size increases

(Pieniazek, 2007). Sample size for this study has been calculated using a sample size

calculator developed by Pivotal Research (2011).

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Appendix N: BACC Delegate Numbers

The total number of MICE event delegates which attended BACC MICE events during the

2014 – 2015 tax year was 8,420. The chart below shows this figure broken down into the

figures for each month.

0

200

400

600

800

1000

1200

1400

JUL AUG SEP OCT NOV DEC JAN FEB MAR APR MAY JUN

Number of Delegates in the Month

Number ofDelegates in theMonth

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Appendix O: Pilot Study

Questionnaire 1 was piloted in Boughton-Lees, a small rural village in Kent in the immediate

vicinity of a luxury 4-star hotel and conference venue (Eastwell Manor, 2016). Small-

businesses owners were approached regarding perceived impacts of Eastwell Manor MICE

events on their businesses. Respondents reacted well to the questionnaire and no changes

were made to question sequencing. Of the 10 businesses questioned, a 100% response rate

was achieved. Small changes were made to the initial questionnaire-survey wording.

Questionnaire 2 was piloted at a small financial services seminar in London. Questionnaires

were distributed to each of the 16 delegates. A 69% response rate was achieved. Small

changes were also made to questionnaire wording and a cover sheet was added.

Questionnaire 3 was piloted amongst residents of Ashford, Kent, regarding perceived social

impacts of MICE events at a well-known 4-star hotel in the town. Respondents were

approached in Ashford High Street. 15 responses were obtained. Small changes were made

to questionnaire wording as a result, as well as a change in questionnaire sequencing.

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Appendix P: Questionnaire 1 Business Types

The table below shows the business types into which businesses owners’ businesses were

group in questionnaire 1.

1 Adventure / Sports

2 Retail & Tourist Shop

3 Café / Deli

4 Barber / Hair Salon

5 Grocery / Markets

6 Newsagent & Post Offices

7 Hospitality / Accommodation

8 Finance / Professional

9 Medical & Vetinary

10 Music & Music Production

11 Automotive & Mechanical

12 Building / Trade

13 Restaurants

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Appendix Q: Questionnaire Survey 2 Data Set

The table below shows the data set for questionnaire 2 regarding business owners’

perceptions BACC MICE event impacts on their businesses.

Business Type

Q1 - Impact

on Business

Q2 - Impact on Turnover (on day of

event)

Q3 - Impact on Turnover (long-term)

Q4 - Thoughts or feelings about the relationship

between business events at BACC and business

profitability

Adventure / Sports No No impact No impact Cause parking issues


Yes Increase Increase None

Café / Deli Yes Increase Large Increase

Good for building relationships


Yes Large increase

Large Increase


Café / Deli No No impact No impact Business opportunity


No No impact No impact None

Barber / Hair Salon No No impact No impact None


No No impact No impact None

Grocery / Markets Yes No impact Increase None

Newsagents & Post Office

No Increase Increase None

Hospitality Yes Increase Increase Business opportunity

Barber / Hair Salon No No impact No impact None

Café / Deli Yes Increase No impact None

Finance / Professional No No impact No impact None

Medical & Vetinary Yes No impact No impact Cause parking issues

Music & Music Production Yes Increase Increase Business opportunity

Finance / Professional Yes No impact Increase Business opportunity

Hospitality Yes Large increase Increase Business opportunity

Automotive & Mechanical Yes No impact No impact Cause parking issues

Automotive & Mechanical No No impact No impact None

Medical & Vetinary No No impact No impact None

Hospitality Yes Decrease No impact Cause parking issues

Newsagents & Post Office Yes Decrease No impact Cause parking issues

Retail & Tourist Shops Yes No impact Increase

Generates business through tourism legacy

Automotive & No No impact No impact None

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Mechanical

Retail & Tourist Shops No No impact No impact Cause parking issues

Retail & Tourist Shops No No impact Increase

Generates business through tourism legacy

Building / Trade Yes No impact Increase Could work better with local business.

Retail & Tourist Shops No No impact No impact None

Grocery / Markets No No impact No impact None

Building / Trade Yes Increase Increase Generates business through tourism legacy

Hospitality Yes Increase Increase Could work better with local business.

Hospitality Yes Increase Increase Generates business through tourism legacy

Automotive & Mechanical No No impact No impact None


Café / Deli Yes Increase No impact Business opportunity

Hospitality Yes Increase Increase Business opportunity

Café / Deli No Increase Increase Could work better with local business.

Hospitality Yes Increase Increase Generates business through tourism legacy

Restaurant Yes Increase Increase Business opportunity

Automotive & Mechanical No No impact No impact Good for the community

Building / Trade No Increase No impact Generates business through tourism legacy

Newsagents & Post Office No No impact No impact None


Café / Deli Yes Increase Increase Cause parking issues

Finance / Professional No No impact No impact

Could work better with local business.

Retail & Tourist Shops No Increase No impact None

Hospitality Yes No impact Increase Inconvenience

Retail & Tourist Shops No Increase No impact Business opportunity

Retail & Tourist Shops Yes No impact No impact Business opportunity

Adventure / Sports No No impact No impact Cause parking issues

Retail & Tourist Shops no No impact No impact None

Retail & Tourist Shops Yes Increase Increase Good for all ages

Retail & Tourist Shops No Increase No impact None

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Hospitality no Increase Increase Good for the community

Restaurant Yes Increase No impact Business opportunity

Grocery / Markets Yes No impact No impact Cause parking issues

Adventure / Sports No Increase No impact None

Café / Deli Yes No impact Increase Ugly / Poor Design

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Appendix R: Questionnaire Survey 1 Economic Impact Data Set

Accommodation Expenditure Non-Accommodation Expenditure

Dunkeld &

Birnam Resident? (Y/N)

Overnight Stay Required? (Y/N)

Hotel in

Dunkeld &

Birnam? (Y/N)

Hotel cost per

night (£)

Number of

nights

Food & Drink –

Chain

(£)

Food & Drink –

Local

(£)

Entertain

ment - Chain

(£)

Entertainment - Local

(£)

Travel

– Chain

(£)

Travel

– Local

(£)

Shoppi

ng - Chain

(£)

Shoppi

ng – Local

(£)

Other -

Chain (£)

Other –

Local (£)

Total (£)

Total Chain

(£)

£ Spent in D&B had

no conferenc

e taken place

(£)

N Y Y 45 1 0 12 0 0 0 0 0 0 0 0 12 0 0

N Y Y 50 1 0 6 0 0 0 0 0 0 0 0 6 0 0

N Y Y NA 1 0 1.3 0 0 0 0 0 0 0 0 1.3 0 0

N N NA NA 0 0 0 0 0 0 0 0 0 0 0 0 0 0

N Y Y 70 1 0 10 0 0 0 0 0 0 0 0 10 0 0

N Y Y 35 1 8 0 0 0 8 0 0 0 12 0 28 28 0

N Y Y 80 1 0 0 0 0 0 0 0 0 0 0 0 0 0

N Y Y 80 1 15 10 5 0 0 0 0 0 0 0 30 20 1

N Y Y 80 1 0 0 0 0 0 0 0 0 0 0 0 0 0

N Y Y 25 1 0 0 0 0 0 0 0 20 0 0 20 0 0

N Y Y 50 1 0 80 0 0 0 0 0 0 0 0 80 0 0

N Y Y 60 1 5 10 0 0 0 0 0 0 0 0 15 5 0

N Y Y 40 1 0 30 0 0 0 0 0 0 0 0 30 0 0

N Y Y 50 1 0 0 0 0 0 0 0 0 0 0 0 0 0

N N N NA 0 0 0 0 0 0 0 0 0 0 0 0 0 0

N Y Y 50 ` 0 0 0 0 0 0 0 15 30 0 45 30 0

N Y Y 80 1 0 20 0 0 0 20 0 0 0 0 40 0 0

N y Y 54 1 0 40 0 0 0 0 0 0 0 0 40 0 0

Y Y Y 90 2 70 0 0 0 0 0 0 0 0 0 70 70 0

N Y Y 59 1 20 0 0 0 0 0 0 0 0 0 20 20 0

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N Y Y 80 1 0 20 0 0 0 0 0 0 0 0 20 0 0

N y Y 60 1 0 0 0 0 0 0 0 5 0 0 5 0 0

N Y Y 70 1 0 30 0 0 0 0 0 0 0 0 30 0 0

N N N NA 0 0 0 0 0 0 0 0 0 0 0 0 0 0

N Y N NA 0 0 0 0 0 0 0 0 0 0 0 0 0 0

N N N NA 0 0 0 0 0 0 0 0 0 0 0 0 0 0

N N N NA 0 0 0 0 0 0 0 0 0 0 0 0 0 0

N N N NA 0 0 0 0 0 0 0 0 0 0 0 0 0 0

N N N NA 0 0 0 0 0 0 0 0 0 0 0 0 0 0

N N N NA 0 0 0 0 0 0 0 0 0 0 0 0 0 0

N N N NA 0 0 0 0 0 0 0 0 3 0 0 2.5 0 0

N N N NA 0 0 0 0 0 0 0 0 0 0 0 0 0 0

N Y Y 55 1 0 0 10 0 0 0 0 0 0 0 10 10 30

N Y Y 60 1 35 60 10 0 100 0 20 0 0 0 225 165 150

N Y N NA 0 37 0 0 0 0 0 0 0 0 0 37 37 0

N N N NA 0 0 0 0 0 0 0 0 0 0 0 0 0 1.2

N N N NA 0 0 0 0 0 0 0 0 0 0 0 0 0 0

N N N NA 0 0 0 0 0 0 0 0 0 0 0 0 0 20

N N N NA 0 0 0 0 0 0 0 0 0 0 0 0 0 0

N N N NA 0 0 5 0 0 0 0 0 2 0 0 7 0 0

N N N NA 0 0 0 0 0 0 0 0 0 0 0 0 0 0

N N N NA 0 0 0 0 0 0 0 0 0 0 0 0 0 5

N N N NA 0 0 0 0 0 0 0 0 0 0 0 0 0 0

N N N NA 0 0 1.2 0 0 0 0 0 12 0 0 13.2 0 0

N N N NA 0 0 1.2 0 0 0 0 0 0 0 0 1.2 0 0

N Y Y 90 2 0 20 0 0 50 0 0 0 0 0 70 50 0

N Y Y 50 1 0 50 0 0 0 0 0 0 0 0 50 0 0

N N N NA 0 0 0 0 0 0 0 0 0 0 0 0 0 0

N Y Y 54 1 0 50 0

0 0 10 0 50 0 110 60 0

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N Y Y 60 1 0 0 0 0 0 0 0 0 0 10 10 0 0

N N N NA 0 0 10 0 0 5 0 0 0 0 0 15 5 0

N N N NA 0 0 13 0 10 0 0 0 0 0 0 23 0 0

N N N NA 0 0 1 0 0

3 0 0 0 0 4 0 0

N N N NA 0 0 10 0 0 0 0 0 0 0 0 10 0 0

N N N NA 0 10 0 0 0 10 0 0 0 0 0 20 20 0

N N N NA 0 0 10 0 0 0 0 10 0 0 5 25 10 0

N N N NA 0 0 0 0 0 0 0 0 0 0 0 0 0 0

N N N NA 0 0 7 0 0 0 0 0 25 0 0 32 0 0

n n N NA 0 0 0 0 0 0 0 0 0 0 0 0 0 0

N N N NA 0 0 10 0 0 0 0 0 0 0 0 10 0 0

N N N NA 0 0 10 0 0 0 0 0 0 0 0 10 0 0

N Y Y 50 2 0 10 0 0 0 20 0 10 0 0 40 0 0

92 G20614827

Appendix S: Questionnaire Survey 3 Data Set

Business events at BACC cause … to be...

Business events at BACCC…..

Other Thoughts

Q1 - Congestion Levels

Q2 - Noise Levels

Q3 - Crowding Levels

Q4 - Quality of Life

Q5 - Crime

Q6 - Social &

Community Ties

Q7 - Local Infrastructu

re

Q8 - Property Valuatio

ns

Q9 - Support

local business

Q10 - Support Tourism in D&B

Other Thoughts

Strongly increased

No impact

No impact

Improved No impact

Strongly improved

Improved No impact

Disagree Strongly agree

Parking problems

No impact No impact

No impact

No impact

No impact

Improved No impact No impact

Strongly agree

Agree None

No impact No impact

No impact

No impact

No impact

Strongly improved

Improved No impact

Disagree Agree Parking problems

No impact No impact

No impact

No impact

No impact


Strongly agree

Agree None

Strongly increased

No impact

No impact

No impact

No impact

Strongly improved

No impact No impact

Agree Strongly agree

None

No impact No impact

No impact

No impact

No impact


Strongly agree

Agree None

No impact No impact

No impact

Improved No impact


Strongly agree

Strongly agree

None

No impact No impact

No impact

Worsened

No impact

Strongly improved

No impact No impact


None

No impact Increased

No impact

No impact

No impact

Strongly improved

No impact No impact

Strongly agree

Strongly agree

Parking problems

Increased No Impact

No Impact

No Impact

No Impact

Strongly Improved

No Impact No Impact

Strongly Disagree

Agree Nice Café

No impact No impact

No impact

Strongly improved

No impact

Strongly improved

No impact No impact

Agree Agree None

Increased No Impact

No Impact

No Impact

No Impact

No Impact Improved No Impact

Strongly Agree

Agree None

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Increased No Impact

No Impact

No Impact

No Impact


Strongly Agree

Strongly Agree

Parking Problems

No impact No impact

No impact

Improved No impact

Strongly improved

Improved No impact

Strongly agree

Agree None

No impact No impact

No impact

No impact

No impact


Agree Agree None

Increased No Impact

No Impact

Improved No Impact

Strongly Improved

No Impact No Impact

Strongly Agree

Disagree Parking Problems

Strongly increased

No impact

Increased

No impact

No impact


Agree Agree None

No impact No impact

No impact

No impact

No impact

Strongly improved

No impact No impact


Facility not used enough

No impact No impact

No impact

Strongly improved

No impact

Strongly improved

No impact No impact

Neither agree nor disagree

Agree None

Increased No Impact

No Impact

Strongly Improved

No Impact

Strongly Improved

No Impact No Impact

Neither Agree Nor Disagree

Agree Division Between The Two Sides Of The River

No impact No impact

No impact

Worsened

No impact

Strongly improved

No impact No impact

Agree Agree None

Strongly increased

No impact

Strongly increased

No impact

No impact

No impact No impact No impact


Agree There should be more sporting & youth events

Strongly increased

No impact

No impact

Improved No impact

Improved Improved No impact

Agree Agree None

Increased No Impact

Increased

No Impact

No Impact

Improved Improved No Impact

Strongly Agree

Strongly Agree

None

Increased No Impact

Increased

No Impact

No Impact


Strongly Agree

Strongly Agree

Positive Contributor

No impact No impact

No impact

Improved No impact

Strongly improved

Improved Increased Neither agree nor disagree

Agree None

Strongly increased

No impact

No impact

Improved No impact


Agree Agree Nice facility

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Strongly increased

No impact

Increased

No impact

No impact


Strongly agree

Strongly agree

None

No impact No impact

No impact

No impact

No impact



Agree None

No impact No impact

No impact

Improved No impact

Strongly improved

No impact No impact

Strongly agree

Strongly agree

Brings the community together

No impact No impact

No impact

No impact

No impact

Strongly improved

No impact No impact


None

No impact No impact

No impact

No impact

No impact

No impact Improved No impact


Strongly agree

Parking problems

No impact No impact

No impact

Improved No impact



None

No impact No impact

No impact

Improved No impact


Strongly agree

Strongly agree

Nice facility

Strongly increased

No impact

No impact

No impact

No impact


Agree Agree Parking problems

Increased No Impact

No Impact

No Impact

No Impact

Improved No Impact No Impact

Agree Agree Parking Problems

Increased No Impact

No Impact

No Impact

No Impact

Strongly Improved

No Impact No Impact

Agree


None

No impact No impact

No impact

Strongly improved

No impact


Agree Agree None

Strongly increased

Increased

No impact

No impact

No impact

Strongly improved

Improved Increased Neither agree nor disagree

Agree None

Increased No Impact

No Impact

Improved No Impact

Strongly Improved

Improved No Impact

Strongly Agree

Strongly Agree

Too politically geared toward The Scottish national party

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No impact No impact

No impact

Improved No impact


Disagree Strongly agree

Nice facility

No impact Increased

No impact

No impact

No impact


Agree Agree Good for the community

No impact No impact

No impact

No impact

No impact


Strongly agree

Strongly agree


No impact Increased

No impact

Improved No impact

Strongly improved

No impact Increased Disagree Strongly agree

Not aware of level of mice use

Strongly increased

No impact

No impact

Improved No impact



Agree None

No impact No impact

No impact

Improved No impact

Strongly improved

Improved Increased Agree Strongly agree

Impressed with level if mice activity

Increased No Impact

Increased

No Impact

No Impact


Agree Agree

Brings Income To BACC. Benefits To Locals

No impact No impact

No impact

No impact

No impact


Agree


None

No impact No impact

No impact

No impact

No impact


Agree


None

Strongly increased

No impact

No impact

Strongly improved

No impact

Strongly improved

Improved Increased Strongly agree

Strongly agree

Very important. Good thing. Well supported

No impact No impact

No impact

Improved No impact

Strongly improved

No impact No impact

Disagree Disagree Would miss it if BACC wasn't there.

No impact No impact

No impact

Strongly improved

Lessened


Agree Agree None

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No impact No impact

No impact

No impact

No impact


Agree Agree None

No impact No impact

No impact

Improved Increased

Improved No impact Increased Agree Agree Facility not used enough

Strongly increased

No impact

No impact

No impact

No impact


Strongly agree

Strongly agree

Parking problems

Increased No Impact

No Impact

No Impact

No Impact

No Impact No Impact No Impact

Agree Agree None

Increased Increased

Increased

No Impact

No Impact


Disagree Agree Parking Problems

No impact No impact

No impact

No impact

No impact

Improved Strongly improved

Increased Agree Strongly agree

Positive contributor

Strongly increased

Increased

No impact

No impact

Severely lessened

Strongly improved

Improved No impact

Agree Agree Parking problems

Strongly increased

Increased

Increased

No impact

No impact

No impact Improved Increased Agree Agree Good for the community

Increased No Impact

No Impact

No Impact

No Impact

Improved Improved Increased Disagree Agree Parking Problems

Strongly increased

No impact

No impact

Worsened

No impact

Improved No impact Decreased

Strongly disagree


Ugly. Some people benefit

No impact No impact

No impact

No impact

No impact


Agree Agree Hope there are more

No impact No impact

No impact

No impact

No impact

Strongly improved

Improved No impact

Agree Agree Ugly. Some people benefit

Strongly increased

Increased

No impact

No impact

Severely lessened

Strongly improved

Strongly improved

Increased Agree Strongly agree

Hope there are more

No impact No impact

No impact

Improved No impact


Strongly agree

Agree Parking problems

No impact No impact

No impact

No impact

No impact



None

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Strongly increased

No impact

No impact

No impact

No impact

No impact Strongly improved

No impact



Parking problems

No impact No impact

No impact

Improved No impact


Strongly agree

Strongly agree

None

No impact No impact

No impact

No impact

No impact


Agree Agree Good for the community

Strongly increased

No impact

No impact

Improved No impact



Parking problems

Increased No Impact

No Impact

No Impact

No Impact


Disagree Agree We Don't See Money. Parking

Increased Increased

Increased

No Impact

No Impact



No impact No impact

No impact

No impact

No impact


Agree


Parking problems

Increased No Impact

No Impact

Improved No Impact


Strongly Agree

Agree Parking Problems

Strongly increased

Increased

Increased

No impact

No impact

No impact Improved Increased Disagree Agree None

Increased No Impact

No Impact

No Impact

No Impact

Improved Improved Increased Agree Agree Parking Problems

Increased No Impact

No Impact

No Impact

No Impact


Strongly Agree

Strongly Agree

Good For The Community

Strongly increased

No impact

No impact

Improved No impact



Agree Parking problems

Strongly increased

No impact

Increased

Improved No impact


Agree Agree None

Strongly increased

Increased

No impact

No impact

No impact

Improved Strongly improved

No impact

Agree Agree None

No impact No impact

Increased

No impact

No impact

Strongly improved

No impact No impact

Strongly agree

Strongly agree

None

98 G20614827

No impact No impact

No impact

No impact

No impact

Strongly improved

No impact Decreased

Agree Disagree None

Increased No Impact

No Impact

No Impact

No Impact

Improved No Impact Increased Strongly Agree

Strongly Agree

Parking Problems

Increased No Impact

No Impact

No Impact

No Impact

Improved No Impact Increased Strongly Agree

Strongly Agree


Increased No Impact

No Impact

No Impact

No Impact

Improved No Impact Increased Agree Agree None

Increased No Impact

No Impact

No Impact

No Impact

No Impact No Impact Increased Strongly Agree

Strongly Agree

Good MGMT. Benefit 2 Area

Increased No Impact

No Impact

No Impact

No Impact

Improved Worsened No Impact

Agree Strongly Agree

Unique

Increased No Impact

No Impact

Improved No Impact

Strongly Improved

Worsened No Impact


None

Increased No Impact

No Impact

No Impact

No Impact

Improved Worsened No Impact


None

Increased No Impact

No Impact

Improved No Impact

Strongly Improved

Improved Increased


Strongly Agree

None

No impact No impact

No impact

Strongly improved

No impact

Strongly improved

Improved No impact

Strongly agree

Strongly agree

Good place for mice events

Increased No Impact

No Impact

No Impact

No Impact


Agree Agree None

Increased No Impact

No Impact

Improved No Impact



Increased No Impact

No Impact

No Impact

No Impact


Strongly Agree

Strongly Agree

Parking Problems

No impact No impact

No impact

No impact

No impact


Agree Agree None

Increased No Impact

No Impact

Improved No Impact

Strongly Improved

No Impact No Impact

Strongly Agree

Strongly Agree


Strongly increased

No impact

No impact

Improved No impact

Strongly improved

Improved Increased Strongly agree

Strongly agree

Parking problems

99 G20614827

No impact No impact

No impact

Improved No impact


Agree Agree None

No impact No impact

No impact

No impact

No impact


Agree Agree None

No impact No impact

No impact

No impact

No impact


Strongly disagree


Positive for area. Tourism legacy

No impact No impact

No impact

No impact

No impact


Strongly disagree


Parking problems

Increased No Impact

No Impact

Improved No Impact

Strongly Improved

Improved No Impact

Disagree


None

No impact No impact

Increased

No impact

No impact

Strongly improved

Improved No impact

Strongly agree

Strongly agree

None

Increased No Impact

Increased

No Impact

No Impact



100 G20614827

Appendix T: Delegate Perceptions of D&B - Data Set

Delegate Perception

Word 1 Word 2 Word 3

Consider Holiday in

D&B? (Y/N/M)

Architecture Quirky Appealing Y

Rural Beautiful Peaceful Y

Beautiful Rural Friendly Y

Beautiful Central Accessible Y

Scenic Historic Beautiful Y

Nice Cultural Culturally Rich Y

Peaceful Pleasant Quiet Y

NA NA NA Y

NA NA NA Y

Quaint Pretty NA Y

Quiet Quaint Restful Y

Charming Beautiful Friendly Y

NA NA NA Y

NA NA NA Y

NA NA NA Y

Quaint Beautiful Cosy Y

Friendly Convenient Focused Y

Relaxing Quiet Beautiful Y

NA Like NA Y

Scenic Historic Beautiful Y

Authentic Nature Quiet Y

NA NA NA Y

Scenic Peaceful Independent Y

Attractive Well cared for Well located Y

Quiet Rural Serene Y

Pretty Rural Quiet M

Quiet Rural Scenic Y

Quaint Historic Rural Y

Expensive Quaint Not obvious from road N

Nice Central NA Y

Pretty

M

Pleasant

M

Natural Environment Accessible

Y

Small Place Medieval Buildings Nice bars Y

101 G20614827

Quaint Handy Highland M

Pretty Surreal Quiet N

Small Central

Y

Convenient Attractive

Y

Quiet Pleasant

Y

Lovely Pretty Unexpected Y

Peaceful Scenic A9 Y

Cherishable

Y

Lovely

Y

Cute Wee Village M

Pretty Small Quaint M

Convenient Traditional Quiet Y

Quiet Walkable Relaxing Y

Y

Cute Friendly Traditional Y

Neat Pretty Quiet Y

Good Music Centre Entertainment Y

Convenient Charming Good Facilities Y

Good Picturesque Highland Y

Central Attractive Lots of restaurants Y

Historic Individual Shops Good walks M

Y

Pleasant Lovely Styling Rural Y

Friendly Pretty Convenient Y

Good visitor location

Y

Y

Attractive Historic Hub for art & music Y

Picturesque Accessible Friendly Y

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