AIRCC's International Journal of Computer Science and Information Technology

Open Access Open Access  Restricted Access Subscription Access

Integration of Importanceperformance Analysis and Fuzzy Dematel


Affiliations
1 Department of Marine Leisure and Tourism, Taipei University of Maritime Technology, No. 150, Sec. 3, Binhai Rd., Tamsui District, New Taipei City 251, Taiwan, Province of China
2 Department of Physical Education Center, Hsiuping University of Science and Technology, No.11, Gongye Rd., Dali Dist., Taichung City 412-80, Taiwan, Province of China
3 Department of Office of Academic Affairs, China University of Technology, No. 16, Sec. 1, Shuang-Shih Road, Taichung, 404, Taiwan, Province of China
4 Department of Sport Information & Communication, National Taiwan University of Sport, No. 16, Sec. 1, Shuang-Shih Road, Taichung, 404, Taiwan, Province of China
 

The traditional Importance-Performance Analysis (IPA) assumes that quality attributes are independent variables, and presupposes that explicit customers’ response data is used for assessing the importance and performance of quality attributes. Under this supposition, when the quality attribute has explicit causation data, the traditional IPA cannot correctly provide importance and priority of improvement. Moreover, the influential degree of the traditional quality attributes is emphasized as maximum degree. This study employs regression analysis and the fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL), which consider the fuzziness of human thinking, to calculate the causal relationship and the influential degree among each quality attribute, and then proposes a new methodology of decision analysis, which modifies the traditional IPA and obtains the accurate importance and the improvement the quality attributes. In this study, a Taiwanese bank is an empirical case study, which illustrates the application and the effectiveness of integrating fuzzy DEMATEL and IPA.

Keywords

Importance-Performance Analysis, Multiple Regression Analysis, Decision Making Trial and Evaluation Laboratory, Fuzzy Theory.
User
Notifications
Font Size

  • Al-Najjar, B., & Alsyouf, I. “Selecting the most efficient maintenance approach using fuzzy multiple criteria decision making”. International Journal of Production Economics, vol. 84, no.1, 85–100, 2003.

  • Deng, W.J., Chen, W.C. and Pei, W., “Back-Propagation Neural Network Based ImportancePerformance Analysis for Determining Critical Service Attributes”, Expert Systems with Applications, vol. 34, pp. 1115-1125, 2008.

  • Fontela E. and Gabus A., “The DEMATEL Observer, DEMATEL 1976 Report. Switzerland, Geneva”, Battelle Geneva Research Prominence, 1976.

  • Gabus, A. and Fontela, E., “Perceptions of the World Problematique: Communication Procedure, Communicating with Those Bearing Collective Responsibility, DEMATEL Report No. 1”, Battelle Geneva Research Prominence, Geneva, Switzerland, 1973.

  • Goodman, R, “Introduction to Stochastic Models, Monlo Park”, California: Benjamin/Cummings Publishing Company., 1988.

  • Hajime, Y., Kenichi, I. and Hajime, M., “An Innovative Product Development Process for Resolving Fundamental Conflicts”, Journal of the Japan Society for Precision Engineering, vol. 71, no.2, pp.216-222, 2005.

  • Hess, P., & Siciliano, J.. “Management: Responsibility for performance”. New York: McGraw-Hill, 1996.

  • Hu, C.Y., Chiu, S.I., Ching-Chan Cheng, C.C, Yen, T.M. “Applying the IPA and DEMATEL models to improve the order-winner criteria: A case study of Taiwan’s network communication equipment manufacturing industry”, 2011.

  • Huang, C.Y., Shyu, J.Z. and Tzeng, G.H., “Reconfiguring the Innovation Policy Portfolios for Taiwan’s SIP Mall Industry”, Technovation, vol. 27, pp. 744-765, 2007.

  • Huang, Y.C., Wu, C.H. and Hsu, C.J., “Using Importance-Performance Analysis in Evaluating Taiwan Medium and Long Distance National Highway Passenger Transportation Service Quality”, The Journal of American Academy of Business, vol. 8, no.2, pp.98-104, 2006.

  • Kenichi, F. and Yoshihiro, N., “Study on Function and Failure Analysis of Snow Melting Machines”, Transactions of the Japan Society of Mechanical Engineers, vol. 68, no.675, pp. 3447-3455, 2002.

  • Kim, Y.H., “Study on Impact Mechanism for Beef Cattle Farming and Importance of Evaluating Agricultural Information in Korea Using DEMATEL”, PCA and AHP, Agricultural Information Research, vol. 15, no. 3, pp. 267-280, 2006.

  • Lee, Y.C., Yen, T.M. and Tsai, C.H., “Using Importance-Performance Analysis and Decision Making Trial and Evaluation Laboratory to Enhance Order-Winner Criteria ~ A study of Computer Industry”, Information Technology Journal, vol. 7, no. 3,pp.396-408, 2008.

  • Lee, Y.C., Lee, M.L.,Yen, T.M. & Huang, T.H., “Analysis of adopting an integrated Decision Making Trial and Evaluation Laboratory on a technology acceptance model”. Expert System with Applications, vol. 37, no. 2, 1745-1754, 2010.

  • Lee, Y.C., Lee, M.L.,Yen, T.M. & Huang, T.H., “Analysis of Fuzzy Decision Making Trial and Evaluation Laboratory on Technology Acceptance Model”. Expert System with Applications, vol. 38, no. 12, pp. 14407-14416, 2011.

  • Levenburg, N.M. and Magal, Simha R., “Applying Importance-Performance Analysis to Evaluate Ebusiness Strategies Among Small Firms”, E-Service Journal, vol. 3, no.3, pp.29-48, 2005.

  • Lin, C.J. and Wu, W.W., “A Causal Analytical Method for Group Decision-Making under Fuzzy Environment”, Expert System with Applications, vol. 34, pp. 205-213, 2008.

  • Martilla, J.A. and James, J.C., “Importance-Performance Analysis”, Journal of Marketing, vol. 41, pp.77-79, 1977.

  • Matzler, K., Bailom, F., Hinterhuber, H.H.,Renzl, B. and Pichler, J., “The Asymmetric Relationship Between Attribute-level Performance and Overall Customer Satisfaction: A Reconsideration of The Importance-Performance Analysis”, Industrial Marketing Management, vol. 33, pp.271-277, 2004.

  • Matzler, K., Sauerwein, E., “The Factor Structure of Customer Satisfaction: An Empirical Test of Importance Grid and The Penalty-Reward-Contrast Analysis”, International Journal of Service Industry Management, vol. 13, no. 4, pp.321-332, 2002.

  • Matzler, K., Sauerwein, E. and Heischmidt, K.A., “Importance-Performance Analysis Revisited: The Role of The Factor Structure of Customer Satisfaction”, The Service Industries Journal, vol. 23, no. 2, pp.112-129, 2003.

  • Nanayo, F. and Toshiaki, T., “A New Method of Paired Comparison by Improved Dematel Method: Application to the Integrated Evaluation of a Medical Information Which has Multiple Factors”, Japan Journal of Medical Informatics, vol. 22, no. 2, pp.211-216, 2002.

  • Opricovic, S., & Tzeng, G.H., “Defuzzification within a multicriteria decision model”, International Journal of Uncertainty. Fuzziness and Knowledge-Based Systems, vol. 11, no. 5, 635-652, 2003.

  • Seyed-Hosseini, S.M., Safaei, N. and Asgharpour, M.J., “Reprioritization of Failures in a System Failure Mode and Effects Analysis by Decision Making Trial and Evaluation Laboratory Technique”, Reliability Engineering and System Safety, vol. 91, pp. 872-881, 2006.

  • Tamura, H., Okanishi, H. and Akazawa, K., “Decision Support for Extracting and Dissolving Consumers’ Uneasiness over Foods Using Stochastic DEMATEL”, Journal of Telecommunications and Information Technology, vol. 4, pp. 91-95, 2006.

  • Tarrant, M.A. and Smith, E.K., “The Use of a Modified Importance-Performance Framework to Examine Visitor Satisfaction with Attributes of Outdoor Recreation Settings”, Managing Leisure, vol.

  • , pp.69-82, 2002.

  • Tonge, J. and Moore, S.A., “Importance-Satisfaction Analysis for Marine-Park Hinterlands: A Western Australian Case Study”, Tourism Management, vol. 28, pp.768-776, 2007.

  • Tzeng, G.H., Chiang, C.H. and Li, C.W., “Evaluating Intertwined Effects in E-Learning Programs: A Novel Hybrid MCDM Model Based on Factor Analysis and DEMATEL”, Expert Systems with Applications, vol. 32, pp. 1028-1044, 2007.

  • Wu, W.W. and Lee, Y.T., “Developing Global Managers’ Competencies Using Fuzzy DEMATEL Method”, Expert Systems with Applications, vol. 32, pp. 499-507, 2007.

  • Xiuli Geng, Xuening Chu, “A new importance–performance analysis approach for customer satisfaction evaluation supporting PSS design”, Expert Systems with Applications, vol. 39, pp. 14921502, 2012.

  • Zadeh, L. A., “Fuzzy sets”, Information and Control, vol. 8, no. 2, 338–353, 1965.

  • Kuei-Hu Chang, Yung-Chia Chang, Yu-Tsai Lee, “Integrating TOPSIS and DEMATEL Methods to Rank the Risk of Failure of FMEA”, International Journal of Information Technology & Decision Making, Vol. 13, No. 06, pp. 1229-1257, 2014

  • PAO-LIEN WEI, JEN-HUNG HUANG, GWO-HSHIUNG TZENG, SHWU-ING WU, “CAUSAL MODELING OF WEB-ADVERTISING EFFECTS BY IMPROVING SEM BASED ON DEMATEL

  • TECHNIQUE”, International Journal of Information Technology & Decision Making, Vol. 09, No. 05, pp. 799-829 (2010)


Abstract Views: 318

PDF Views: 171




  • Integration of Importanceperformance Analysis and Fuzzy Dematel

Abstract Views: 318  |  PDF Views: 171

Authors

Chin-Yi Chen
Department of Marine Leisure and Tourism, Taipei University of Maritime Technology, No. 150, Sec. 3, Binhai Rd., Tamsui District, New Taipei City 251, Taiwan, Province of China
Tung-Shen Wu
Department of Physical Education Center, Hsiuping University of Science and Technology, No.11, Gongye Rd., Dali Dist., Taichung City 412-80, Taiwan, Province of China
Mei-Lan Li
Department of Office of Academic Affairs, China University of Technology, No. 16, Sec. 1, Shuang-Shih Road, Taichung, 404, Taiwan, Province of China
Ching-Tang Wang
Department of Sport Information & Communication, National Taiwan University of Sport, No. 16, Sec. 1, Shuang-Shih Road, Taichung, 404, Taiwan, Province of China

Abstract


The traditional Importance-Performance Analysis (IPA) assumes that quality attributes are independent variables, and presupposes that explicit customers’ response data is used for assessing the importance and performance of quality attributes. Under this supposition, when the quality attribute has explicit causation data, the traditional IPA cannot correctly provide importance and priority of improvement. Moreover, the influential degree of the traditional quality attributes is emphasized as maximum degree. This study employs regression analysis and the fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL), which consider the fuzziness of human thinking, to calculate the causal relationship and the influential degree among each quality attribute, and then proposes a new methodology of decision analysis, which modifies the traditional IPA and obtains the accurate importance and the improvement the quality attributes. In this study, a Taiwanese bank is an empirical case study, which illustrates the application and the effectiveness of integrating fuzzy DEMATEL and IPA.

Keywords


Importance-Performance Analysis, Multiple Regression Analysis, Decision Making Trial and Evaluation Laboratory, Fuzzy Theory.

References