International Journal of Information Technology and Business Management 29 th March, Vol.35 No JITBM & ARF. All rights reserved

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1 A STUDY ON THE INDICATOR-WEIGHT EVALUATION OF CITY COMPETITIVENESS IN THE SELECTION OF CONVENTION/EXHIBITION VENUE FOR MICE INDUSTRY DEVELOPMENT: USING TAIPEI CITY AS AN EXAMPLE Mei-Hsien Huang 1, Tracy Tsai 2, Yu-Je Lee 3, Ting-Chun Liu 4 1 National Taiwan University of Arts 2, 3, 4 Takming University of Science and Technology Abstract Being the largest city as well as the political, economic and cultural center in Taiwan, Taipei has always been chosen to host large-scale international conventions and exhibitions. The main purpose of this study is to evaluate the weight values of various dimensions of city competitiveness indicator in the selection of convention/exhibition venue in the Meetings, Incentives, Conventions and Exhibitions (MICE) industry by using Taipei City as the subject of study. The analytic network process (ANP) is applied to examine the correlations between the dimensions and identify the priority order of the important factors and weight values of the dimensions. The study outcome shows that the weight values determined by scholars and business operators for the eight dimensions all exceed 0.1. This means both scholars and business operators agree that convention/exhibition venue facilities, hospitality and dining facilities, scenic spots, costs, city image, professional service personnel, convenient transportation and government support are all important indicator dimensions that have influence on the competitiveness of cities in MICE industry development. However, scholars and business operators do hold different views toward the weight of each of these eight dimensions since scholars make their assessment from a more theoretic angle and regard transportation facilities/convenience as having the biggest influence on a city s MICE industry development whereas business operators adopt a more practical standpoint and think professional service personnel are the biggest influence. This outcome can serve as a reference for various sectors in development of Taipei s MICE industry to promote city competitiveness and image. Keywords: MICE Industry, Venue Selection, City Competitiveness, Analytic Network Process (ANP) 63

2 2. Foreword The four major convention/exhibition host cities in Taiwan are Taipei City, Taichung City, Tainan City and Kaohsiung City. As the largest city as well as the political, economic and cultural center in Taiwan, Taipei City is home to main government agencies, international associations and trade unions. In line with the government s effort to build the island into the Asia-Pacific Regional Operations Center, Taipei continues to make reinforcement in the financial, media and communications aspects to facilitate industrial and economic development. All major international conventions and exhibitions have been held in the city. According to statistics from Taipei World Trade Center, Taipei hosted 134 exhibitions in Meanwhile, the latest data from International Congress and Convention Association (ICCA) indicate that 122 association meetings were held in Taipei in 2013, making the city the No. 33 convention host city in the world and No. 7 in Asia. Taipei City s potential to develop the MICE industry is once again made evident (ICCA, 2014). Hosting international conventions and exhibitions can bring both invisible and visible benefits to a city; therefore, host city selection has become an important part of the convention or exhibition hosting process (Hsiao, 2005). For this reason, what a city has to offer to attract convention or exhibition organizers is an issue worth looking into. This study is intended to examine the convention/exhibition selection indicators proposed by domestic scholars in their studies. The objective is to understand how city competitiveness is evaluated in the selection of convention/exhibition venue in the MCIE industry. At the same time, it is hoped that the outcome of this study can serve as reference for various sector in developing Taipei s MICE industry to promote the city s competitiveness and image. This is the main purpose of this study. 3. Literature Review The indicators in this study for assessment of the influence of the selection of convention/exhibition venue on city competitiveness are established after examination of related literature. They include (1) convenient transportation; (2) professional service personnel; (3) convention/exhibition venue facilities; (4) government support; (5) costs; (6) city image; (7) hospitality and dining facilities; and (8) scenic spots. The more distinctive studies by domestic and foreign researchers suggesting different indicator dimensions in evaluating the influence of the selection of convention/exhibition venue on city competitiveness in MICE industry development are as follows: The American Society of Association Executives (ASAE, 1995) put forward 16 factors to be taken into account and studies conducted accordingly indicate that the most important ones are exhibition venue and convention center facilities, followed by service quality and efficiency, and then the number of hotel rooms available. Chen (1996) proposed 15 factors to be considered when surveying organization or 64

3 association leaders to evaluate how these factors are valued in their selection of host city. The results show that convention facilities are the most important, transportation facilities come second and then city image. Oppermann (1999) examined the factors of that convention/exhibition association members consider since they have the liberty to decide whether to attend annual conventions or not. In the study, 16 factors are evaluated to determine their level of significance. The outcome reveals that the size of the venue and equipment are the most important, then the overall cooperativeness and supply capacity, and then the convenience and accessibility of air transport. Yeh (2000) conducted his study on the industrial, government and academic sectors and experts to analyze how the different factors in Taipei City s development of the MICE industry and tourism are valued. The study covers 36 elements in eight dimensions and the results show the capacity of convention venue is the most important. The professional capacity and service quality of organizers personnel come second, followed by the professional capacity and standards of the convention venue and service personnel. Lee (2003) performed a survey on international convention planners and users and marketing managers in Taipei and Seoul. The study includes seven major dimensions, namely (1) service quality; (2) convention energy; (3) city image; (4) venue; (5) culture; (6) convenience of transportation; and (7) others. However, the study only lists out the level of importance of the factors of each dimension without indicating the weight of each dimension. Tsai (2009) pointed out the factors of consideration in selection of convention/exhibition venue and evaluates the level of significance of eight factors or assessment indicators. The weight priority order is (1) convenient transportation; (2) professional service personnel; (3) convention/exhibition venue facilities; (4) costs; (5) government support; (6) city image; (7) hospitality and dining facilities; and (8) scenic spots. 4. Research Methods and Designs 3.1 A Theoretical Basis - Analytic Network Process (ANP) The ANP, derived from the AHP (Analytic Hierarchy Process), has the feedback mechanism added to AHP, using the feedback as a replacement, with a purpose to gain and estimate precisely internal relationship between all criteria, goals and options via ratio scales, and even make a way for best decision-making (Mohamed, 2002; Chen, 2004). Therefore, this study analyzes the relevance between green design criteria by ANP, and find out the important factors of the respective criteria and the dominance order of the weighting; hence, the results of analysis of this phase can serve as references for Taipei City in MICE industry development to promote city competitiveness and image. The ANP network consists of decision criteria, clusters, elements, nodes and links. The cluster s nodes among one specific and another one have a dependence or feedback relationship 65

4 that a link appears between these two clusters. The ANP assumes the permission to respective finally select another node to be a parent node; (4) draw a line based on the parent node elements mutual dependence or feedback affecting children nodes, that is, making a between the same and different decision criteria. The inner dependence will be called, if elements are mutually dependent or feeding back among the same decision criteria (nodes among mutual paired comparison between nodes; (5) complete each cluster connection accordingly when all linking lines of relevant nodes are drawn; (6) finally, make sure the affecting and the same criteria must only be a affected linking lines inside the network are all Paired Comparison with ones among another genuine and correct, mutually paired comparison criteria, if no inner dependence); will be made between nodes and nodes, clusters outer-dependence will be, if elements are mutually dependent or feeding back among different decision criteria (Satty, 1996). Thus, the and clusters. The ANP network calculation process includes three matrixes, separately un-weighted permission assumption of dependence or super-matrix, weighted super-matrix and limiting feedback between criteria can better conform with real occurrence of complex problems in the human society, particularly decision-making is super-matrix. The un-weighted super-matrix is the weights attained after the paired comparison inside the original network; the weighted still involved in uncertainty and risk super-matrix refers to the same component consideration (Sun, 1997; Liu, 2002; Tu and Hsu, 2008). A suitable structure for the ANP model is weights multiplied by related cluster weights inside the un-weighted super-matrix; if each vertical column of un-weighted super-matrix is likely to include one or multiple networks in added to be stochastic, which weighted order to build up a network for the ANP model, which must: (1) think the categories of elements in problems and whether such categories (clusters) are necessary for the problem solutions; (2) establish a cluster first, and which nodes (elements) are included in such a cluster; (3) select one of nodes (elements) to be a parent super-matrix makes un-weighted one; A limiting super-matrix is to make a weighted super-matrix squared to the power of multiple times until every number in vertical columns is equal; therefore, all weighting values of the nodes in the network can be obtained from any one of the vertical columns. Satty (1996) node, next check whether other nodes in the proposed the calculation method for the network clusters will be affected by the parent following ANP model, lim SV=[w,...,w] if an node or not; the affected nodes are called irreducible super-matrix, and all vertical children nodes, which will be mutually columns in the matrix will have the same vector compared in pairs, comparing how much the impact each from these two children nodes under the consideration of the parent node s impact; w attaining to convergence (Tu and Hsu, 2008). Briefly, the phases of ANP include: (1) application of the Delphi Method or expert 66

5 interviews to establish a structure of network levels; (2) calculation of each level weighting, such as; establishment of the paired-comparison matrixes (dispatching questionnaires), obtainment of eigenvalues and eigenvectors, consistent test (<0.1) and super-matrix/ limiting super-matrix calculation; and (3) calculation of total level weighting-global (Hu and Wang, 2008). 3.2 Questionnaire Design and Sample Collection According to the study framework, the ANP model for evaluation of the influence of the selection of convention/exhibition venue in MICE industry on city competitiveness and the correlations between the criteria are established. Subsequently, as the ANP is an appropriate measure for handling small samples collected through expert interviews, a questionnaire for evaluating the competitiveness indicators in the selection of convention/exhibition venue and their correlations is designed based on the analytic chart from the ANP model. The following are the correlations between the city competitiveness indicators for the selection of convention/exhibition venue in the MICE industry and their weight values obtained after expert interviews with managerial personnel in the MICE industry and scholars in Taipei. Finally, according to related literature from in and outside Taiwan, the assessment indicator dimensions in this study are established: (1) convenient transportation; (2) professional service personnel; (3) convention/exhibition venue facilities; (4) government support; (5) costs; (6) city image; (7) hospitality and dining facilities; and (8) scenic spots. The focus of this study is set on the correlations between the dimensions and criteria and the weight values. 3.3 Research Subjects Questionnaires were given by the experts of this study: (1) Total eight sheets were dispatched to scholars, and eight responded, with a response rate up to 100%. (2) Total eight sheets were dispatched to business operators, and seven responded, with a response rate up to 87.5%. In view of the above high response rates, the Convenience Sampling is the reason. 3.4 Research Structure The following Tables 3-1 and 3-2 are individually (1) the formal structure for evaluating the weight values of competitiveness indicators in the selection of convention/ exhibition venue in the MICE industry; and (2) an explanatory Correlation Table of Respective Sub-Dimensions. Additionally, there is incomplete independence between respective sub-dimensions from the Table 3-2, and some of dimensions have the relevance; in other words, incomplete independence exists between respective nodes and nodes, or between clusters and clusters, after paired comparison of nodes toward nodes, and clusters toward clusters. Therefore, this study uses the ANP instead of AHP for analyzing (Hu and Wang, 2008). 67

6 Table 3-1 The Balanced Scorecard in the Formal Structure for Evaluating the Weight of Company Value Maximization Goal Main dimension Sub-dimension Criterion Convention/exhibiti on venue facilities (EE) Convention/exhibition venue capacity (EE 1 ) Convention/exhibition venue availability (EE 2 ) Audio-video and communications equipment at the convention/exhibition venue (EE 3 ) Government funding (GS 1 ) Government Attitude toward the MICE industry Government support (GS) (GS 2 ) Active government efforts to host international conventions/exhibitions (GS 3 ) Assistance from related government agencies in organization of conventions/exhibitions (GS 4 ) Promotion of city competitiveness in MICE industry development (PC) Convention/ exhibition venue selection indicator (MP) Professional Service personnel (PP) Quality and service standard of reception personnel (PP 1 ) Language abilities of service personnel (PP 2 ) Quality and service standard of convention/exhibition planners (PP 3 ) Quality and service standard of convention/exhibition facility and equipment personnel (PP 4 ) Quality and service standard of audio-video equipment engineers (PP 5 ) Quality and service standard of hospitality and dining service personnel (PP 6 ) Convenient transportation between airports and Convenient transportation (CC) the convention/exhibition host city (CC 1 ) Convenience and Availability of international flights (CC 2 ) Convenience of local transportation (CC 3 ) International image of city (CI 1 ) City image (CI) Local safety (CI 2 ) Local social and political stability (CI 3 ) (continue) 68

7 Table 3-1(continue) Level of advancement of business functions (CI 4 ) Local climate (CI 5 ) Friendliness of local people (CI 6 ) History and cultural background (SS 1 ) Diversity of leisure activities (SS 2 ) Promotion of city competitiveness in MICE industry development (PC) Convention/ exhibition venue selection indicator (MP) Scenic spots (SS) Cost (CT) Scenic spots nearby (SS 3 ) Festive activities during the convention/exhibition (SS 4 ) Airfares or local transportation expenses (CT 1 ) Commodity prices (CT 2 ) Hotel rates and food prices (CT 3 ) Convention/exhibition facility prices (stall rentals) (CT 4 ) Ease of room (table) reservation (HB 1 ) Hospitality and dining facilities (HB) Hotel and restaurant facilities and quality (HB 2 ) Diversity of hotels and restaurants (HB 3 ) Number of hotel rooms (HB 4 ) Audio-video and communications equipment in hotels (HB 5 ) Table 3-2 Correlations between the Sub-dimensions of Indicators for the selection of Convention/Exhibition Venue Dimension Dimension EE GS PP CC CI SS CT HB EE V V V V V X V V GS V V V V V V X V PP V V V V X X V V CC V V V V V V V X CI V V X V V V X V SS X V X V V V V X CT V X V V X V V V HB V V V X V X V V Remarks: (1) Please read vertically when entering something into the system. (2) Please read horizontally when drawing something in WORD. (3) EE: convention/exhibition venue facilities; GS: government support; PP: professional service personnel; CC: convenient transportation; CI: city image; SS: scenic spots; CT: costs; HB: hospitality and dining facilities 69

8 3.5 The ANP Analysis Steps This study used the Analytic Network Process to implement each step as shown in the Figure 3-1. Identification of Decision Problems Control Level Network Level Paired Comparison made between Groups and Criteria Establishment of Super-matrix Calculation of Limiting Super-matrix for Decision Problems Important Criteria for Ordering and Strength Analysis *Goal *Criteria *Sub-Criteria Network Structure for Sub-Criteria Figure 3-1 Analysis Steps 70

9 (1)Construction of Decision Making Problems System The ANP application primarily divides the system into two major parts, the first called Control Level including Goal, Decision Criteria and Sub-criteria. All criteria are regarded as mutually independent and only dominated by goal elements. There is no decision criteria within control factors but with at least one goal, and every criterion weighting can be obtained by the traditional AHP among the Control Level. The second part is the Network Level composed of Clusters or Components dominated by the Control Level, which affect each other inside the network structure. (2)Paired Comparison made between Respective Groups and Criteria The step (1) has the Groups, Criteria and Groups and Criteria with the feedback relationship compared in pairs after constructing the decision-making problem system and feedback relationship, using the same comparison as the AHP. (3)Establishment of Super-matrix A paired comparison of groups and criteria in the step (2), same as the AHP, leads to a calculation of every criterion s eigenvector among the Control Level. All eigenvectors are expressed by matrix, that is, Super-matrix. Make the super-matrix row vectors normalized to have their sum equal to 1, which is named as Stochastic Matrix. Non-Stochastic Super-Matrix is known as Un-weighted Super-matrix, and Weighted Super-matrix will be after the stochastic process. The advantage of Stochastic Matrix is the respondent maximum eigenvalue 1, which can make an easier matrix calculation. (4)Calculation of Limiting Super-matrix for Decision Problems The step (3) classifies the types and characteristics of super-matrix from the eigenvalue types; next, makes the weighted super-matrix continually multiplied to obtain a Limiting Super-matrix. Different system structures will have different super-matrix types (Decomposable, Indecomposable, Basic, Non-Basic), converting the super-matrix operation expression. (5)Important Criteria for Ordering and Strength Analysis The final step is to follow Important Criteria for Weight Ordering and Strength Analysis of indicator dimensions for the city competitiveness in MICE industry development. 4. Research Results and Discussions According to the above descriptions, the value of each row and column of the limiting super-matrix (Table 4-1) of the decision problems calculated in this study is nearly the same, which indicates that the results are stable. 71

10 Table 4-1 The Limiting Super-matrix Dimension Dimension EE GS PP CC CI SS CT HB EE GS PP CC CI SS CT HB Additionally, according to the research structure, a relevance between the ANP model and intertextuality criteria for the indicator-weight evaluation of city competitiveness in the selection of convention/exhibition venue for MICE industry development was set up, using the ANP model analysis diagram to stipulate intertextuality questionnaires for the indicator-weight evaluation of city competitiveness in the selection of convention/exhibition venue for MICE industry development. Focused on the expert interviews of scholars and managers from companies in MICE industry of Taipei is to comprehend the relevance and weights between every dimension and criterion of the indicator of city competitiveness in the selection of convention/exhibition venue for MICE industry development. Furthermore, the circled results of questionnaires were calculated to get geometric means between each criterion that the ANP analysis software (Super Decisions) was finally used to obtain the priority ordering between each criterion. The obtained priority ordering would be effectively applied in the assessment of the city competitiveness in the selection of convention/exhibition venue for MICE industry development. The list below accounts for the research results in the perspectives of scholars and business operators with the focus on the CI values, weights and rankings of main constructs and criteria for the weight evaluation of city competitiveness in the selection of convention/exhibition venue for MICE industry development, shown as the Tables 4-2 and

11 Table 4-2 CI Values, Weights and Rankings of Financial Performance for Scholars and Business Operators Main dimension CI value Business Scholars operators Sub-dimension Scholars CI value Weight Ranking Business operators Scholars Business operators Scholars Business operators Convention/Exhibition Venue Facilities (EE) Government Support (GS) MP Professional Service Personnel (PP) Convenient Transportation (CC) City Image (CI) Scenic Spots (SS) Costs (CT) Hospitality And Dining Facilities (HB) For scholars or business operators, the Tables 4-2 and 4-3 shows the CI values of mainand sub-dimensions all fit Satty's criterion, less than 0.1 (Hu and Wang, 2008); for the eight sub-dimensions, all weight values from scholars and business operators exceed 0.1 that fit the consistency test, statistically. The results indicate that the weight values scholars and business operators have come up with for the eight sub-dimensions are close to balanced. For scholars, the priority order of the sub-dimensions is (1) convenient transportation (weight value.521); (2) professional service personnel (weight value.507); (3) convention/exhibition venue facilities (weight value.493); (4) costs (weight value.481); (5) government support (weight value.472); (6) city image (weight value.469); (7) hospitality and dining facilities (weight value.462); and (8) scenic spots (weight value.456). In comparison, the priority order for business operators is (1) convenient transportation (weight value.522); (2) convention/exhibition venue facilities (weight value.513); (3) costs (weight value.494); (4) professional service personnel (weight value.486); (5) city image (weight value.476); (6) government support (weight value.471); (7) hospitality and dining facilities (weight value.462); and (8) scenic spots (weight value.457). Scholars and business operators above had different perspectives for the former 73

12 held a more theoretical viewpoint, while the latter held a more practical one. 5. Research Conclusions and Following Research Directions 5.1 Research Conclusions With the abovementioned combined, the conclusions of the analysis of weight values of the indicators for evaluation of city competitiveness in the selection of convention/ exhibition venue in the MICE industry development are as follows: (1) After performing ANP analysis, we learn that the CI values of general dimensions and sub-dimensions from both the scholars and business operators are less than 0.1, which is consistent with the criteria proposed by Satty. This fact proves that the CI values of general dimensions and sub-dimensions obtained by using ANP approach meet the criteria of consistency testing. In addition the values of columns and rows calculated from the limit matrix are all the same, hence stable, which also means that the weight calculation of factors of all levels is reasonable. (2) It can be known from the results that the weight values among eight sub-dimensions between scholars and business operators are approaching "balanced". Besides, for sub-dimensions, scholars believe top three important ordering: A. Convenient Transportation (weight value.521); B. Professional Service Personnel (weight value.507); C. Convention/Exhibition Venue Facilities (weight value.493). Business operators believe top three important ordering: A. Convenient Transportation (weight value.522); B. Convention/Exhibition Venue Facilities (weight value.513); C. Costs (weight value.494). Scholars and business operators above had different perspectives for the former held a more theoretical viewpoint, while the latter held a more practical one. According to the above, the weight values from scholars and business operators for the eight dimensions of city competitiveness in MICE industry development that have influence on the selection of convention/exhibition venue all exceed 0.1. This is an indication that both scholars and business operators believe convention/exhibition venue facilities, hospitality and dining facilities, scenic spots, costs, city image, professional service personnel, convenience transportation and government support are important indicators for evaluation of city competitiveness in MICE industry development. Despite that business operators hold a different view toward the weight of the said eight dimensions, the difference is because scholars assess from a theoretic angle and think convenient transportation has the biggest influence on competitiveness of a city in MICE industry development, whereas business operators evaluate from a more practical viewpoint and believe professional service personnel have the biggest influence. This 74

13 outcome can serve as a reference for various sectors in development of the MICE industry in Taipei City to promote city competitiveness and image. Meanwhile, the outcome is not entirely the same as the results of studies by the researchers mentioned earlier, namely Chen (1996), Oppermann (1999), Lee (2003) and Tsai (2009), probably due to the fact that Taipei has a complete transportation system and facilities while its being the largest city and the political, economic and cultural center in Taiwan is beneficial to its MICE industry development to promote the city s competitiveness and image. 5.2 Research Contributions or Meanings of Management In this study, ANP is applied to evaluate the weight values of city competitiveness indicators for the selection of convention/exhibition venue in the MICE industry. This is a theoretically innovative application in the realm of management science. In practice, the results can also serve as references for various sectors in MICE industry development to promote city competitiveness and image. 5.3 Research Restrictions (1)Because this study used the ANP approach, a Convenience Sampling method was applied to process the survey interviews with a high response rate. Moreover, the research results may cause the subjective biases due to a small sampling applied in the ANP approach. (2)This study used the MICE industry as the research subjects. Different business 75 operators or venues are very likely to make different results. 5.4 Following Research Directions (1)Future researchers may compare evaluation weights based on different business operators or venues. (2)This study only discusses the relationships between dimensions and criteria. Future studies may add proposal evaluations, or other research techniques such as gray correlation analysis. (3)Research conducted by past scholars indicates that the ANP approach requires the use of Super Decisions software to process data collected from small samples of expert interviews; hence, future researchers should continue to use the ANP approach to manage proposals of assessment research. References 1.ASAE (American Society of Association Executives) (1992). Association Meeting Trends, Washington, D. C.: ASAE. 2.Chen, Chien-liang (1996), A Study on Regional MICE Industry Development Strategies-Using Kaohsiung as an Example, Taiwan: Master s degree thesis, Institute of Public Affairs Management, national Sun Yat-sen University 3.Chen, Wan Ching (2004), Development of Green design process Within Concurrent Engineering By Using Analytic Hierarchy Process (AHP) Method - Commercial Electronically Product As Example, Taiwan: Master s degree thesis, Graduate School of Industrial Design, Da-Yeh University.

14 4.Hsiao, Yu-hua (2005), The Evaluation Model of International Convention Site Selection: A Fuzzy-AHP Approach, Taiwan: Master s degree thesis, Department of Tourism Management, Nanhua University. 5.Hu, Yi-zhong and Wang, Jen-hung (2008), Discuss the Service Quality by AHP-Take the International Tourist Hotel for Example, Taiwan: Issue 2, Collection of Papers from 2008 Symposium on Sports & Leisure Industry Management. 6.ICCA statistics released in May 2014: Case Study on Taichung City, Taiwan: Master s degree thesis, Department of Hospitality Management, Tunghai University 14.Tu, Jui-che and Hsu, Chuan-ying (2008), Strategy for Sustainable Design from Application of Product Service System, Taiwan: Journal of Design Environment, Issue 9, pp Yeh, Tai-min (2000), A Study on the Potential of Taipei City in Development of the MICE Industry and Tourism, Taiwan: Master s degree thesis, Department of Tourism Management, Chinese Culture University. 7.Lee, Sang-eun (2003), A Comparative Study on Taipei and Seoul as Hosts for International Conventions, Taiwan: Master s degree thesis, Department of Tourism Management, Chinese Culture University. 8.Liu, Jason (2002), Application of AHP Method in Evaluation of Product Ecosystem Benefits in the Case of Desktop Monitors, Taiwan: Master s degree thesis, National Cheng Kung University. 9.Mohamed, Mirghani (2002). Points of the triangle, Intelligent Enterprise, San Mateo, Vol. 5, Iss. 14, pp. 32~37 10.Oppermann, M. (1999). Convention destination images: analysis of association meeting planners perceptions. Tourism Management, 17(3), Satty, T.L. (1996), Decision making with dependence and feedback: The analytic network process, RWS Publication. 12.Sun, Pei-yu (1997), Application of AHP in the Establishment of Screening Criteria, Taiwan Hsinchu: Master s degree thesis, Graduate School of Business Management, Chung Hua University. 13.Tsai, Bo-huei (2009), Application of AHP on the Research of the Venue The selection for MICE-A 76