Service Attribute Decision Making Based on Revised Importance Performance Analysis

Abstract

Abstract:
In order to represent the individuation difference and subjective uncertainty in customer evaluation adequately, multigranularity and multisemantic fuzzy number which is translated into uniform decision information by conversion function was adopted to express service attribute’s performance value. Considering the affection to decision result arisen from the connection relations between importance degree of service attribute, analytic network process was adopted to identify the service attribute importance degree; consequently a revised importance performance analysis came into being to determine the priority in service attribute’s improvement effectively. A maintenance service of horizontal directional drilling machine was given to demonstrate the efficiency and feasibility of the revised method. The results show that the revised importance performance analysis is consistent with objective situation, which can be used to better guide business decisions.

Key words: service attribute, importance performance analysis (IPA), analytic network process

CLC Number:

TH17
C934

TAN Yuan-Ling, CHU Xue-Ning, ZHANG Zai-Fang. Service Attribute Decision Making Based on Revised Importance Performance Analysis[J]. Journal of Shanghai Jiaotong University, 2011, 45(09): 1281-1287.

References

［1］Deng Weijaw. Fuzzy importanceperformance analysis for determining critical service attributes［J］. International Journal of Service Industry Management, 2008, 19 (2): 252270.

［2］Ostrom A, Iacobucci D. Consumer tradeoffs and the evaluation of services［J］. Journal of Marketing, 1995, 59(1): 1728.

［3］Danaher P J. Using conjoint analysis to determine the relative importance of service attributes measured in customer satisfaction surveys［J］. Journal of Retailing, 1997, 73(2): 235260.

［4］Matzler K, Sauerwein E. The factor structure of customer satisfaction: An empirical test of the importance grid and the penaltyrewardcontrast analysis［J］. International Journal of Service Industry Management, 2002, 13(4): 314332.

［5］Matzler K, Fuchs M, Schubert A K. Employee satisfaction: Does Kano’s model apply?［J］. Total Quality Management and Business Excellence, 2004, 15(9/10): 11791198.［6］Oh H. Revisiting importanceperformance analysis［J］. Tourism Management, 2001, 22(6):617627.

［7］Matzler K, Bailom F, Hinterhuber, et al. The asymmetric relationship between attributelevel performance and overall customer satisfaction: A reconsideration of the importanceperformance analysis［J］. Industrial Marketing Management, 2004, 33(4): 271277.

［8］张在房，褚学宁，程辉，等. 基于模糊加权最小二乘的多粒度语言决策信息集成［J］. 上海交通大学学报，2009，43(9):13781382.

ZHANG Zaifang, CHU Xuening, CHENG Hui, et al. Multigranularity linguistic infoangrmation decision integration based on fuzzy weighted least squares［J］. Journal of Shanghai Jiaotong University, 2009, 43(9): 13791382.

［9］Herreraa F, HerreraViedmaa E, Martinez L. A fusion approach for managing multigranularity linguistic term sets in decision making［J］. Fuzzy Sets and Systems, 1998, 114(1):4358.

［10］杨明顺，林志航，陈琨，等. 模糊质量功能配置中多粒度多语义语言信息的处理［J］. 信息与控制，2003，32(1):913.

YANG Mingshun, LIN Zhihang, CHEN Kun, et al. Multigranularity multisemantic language information processing in fuzzy quality function deployment［J］. Information and Control, 2003, 32(1):913.

[1]	WANG Ruichang，CHEN Zhihua，MING Xinguo. Life Cycle Assessment of Marine Power System’s Green Design [J]. Journal of Shanghai Jiaotong University, 2020, 54(3): 256-264.
[2]	WANG Dan-Qi, WANG Long-Chang. Study on Implementing Derivative Problems of Design-Build Construction Projects in Taiwan [J]. Journal of Shanghai Jiaotong University, 2011, 45(04): 539-546.