Certification and Inspection Service Quality Applying the fuzzy SERVQUAL method

■2012 JSPS Asian CORE Program, Nagoya University and VNU University of Economics and Business Certification & Inspection Service Quality: Applying the fuzzy SERVQUAL method CUI Li-xin 1, ZENG Guang-feng 2, WU Hong-yan2, WANG Cheng-jie 2, LIU Ru ABSTRACT: This paper applied fuzzy set theory based on modified SERVQUAL model to analysis service quality in certification & inspection industry in China The study consists of 405 randomly selected participants who are customers of China Certification & Inspection Group (CCIC) The paper includes four parts: introduction, methodology, a case study of certification & inspection service quality and conclusions The results of this research show that among the five dimensions the feature of “tangible” has the biggest gap between the service quality expectations and perceptions So, the company we studied (CCIC) need to increase investment in tangible aspects in order to improve their service quality efficiently KEYWORDS: SERVQUAL certification & inspection Introduction fuzzy set theory Blesic et al., 2011), higher education(Ishfaq Ahmed et Service quality is more difficult to be evaluated al., 2010; Kashif Hussain, 2011), urban than commodity quality but it plays an especially transportation(Seyed Mohammad Mahmoudi et al., important role in firms to improve customer 2010; Anjali Awasthi et al., 2011), public or private satisfaction and customer loyalty For measuring the health care(Raymond Tempier et al., 2010; Tashonna R service quality, a 22-item questionnaire instrument Webster called SERVQUAL was proposed by Parasuraman et system(Narasimhaiah Gorla, 2011), e-learning(Godwin al in 1988 (A Parasuraman, V A Zeithaml, L L J Udo et al.,2011), hot spring industry(Shun-Hsing Berry, Chen 1988) Since then, the SERVQUAL et et al., al., 2011), 2011), information condominium questionnaire has been used to analyze service quality management(Yao-Chen Kuo et al., 2011), internet within diverse organizations, such as retailing service(Godwin J Udo et al., 2010;Gregory John Lee, organizations(Halil industry(James J Nadiri, H Liou 2011), airline 2011), et 2011), banking(Mina Beigi, Melika Shirmohammadi, 2011), al., supply chain(Gyan Prakash, 2011), restaurants(Jang-Hyeon Nam et al.,2011), hotel(Prabha and so on But the measurement of Ramseook-Munhurrun, Perunjodi Naidoo, 2010; Ivana hasn't been applied to certification & inspection School of Management and Economics, Beijing Institute of Technology, Beijing, China China Certification & Inspection Company, Beijing, China SERVQUAL Suppose A a, b, c is a triangular fuzzy number as Fig Then, suppose the membership function of A A is f A x LA RA fA x a x a b a a x b c x c b b x c c b Fig Triangular fuzzy number A LA x x a ，a b a x b, RA x c x ，b c b x c LA1 h a b a h， h 1, RA1 h a c a h， h industry so far Qin Su et al (2010) just mentioned that SERVQUAL maybe not suitable for certification industry and in their research they applied Indserv model which is a measurement designed specifically else for BtoB industry In previous researches, methods being used are various, including fuzzy set theory (Chien-Chang Chou, al., 2009), fuzzy AHP (Chen Guiyun et al., 2006), L A x and R A x are the left function and right function of the triangular fuzzy number A , grey-fuzzy DEMATEL approach (Tseng Ming-Lang, respectively While L A1 h 2008), Structural Equation Modeling (Lin Deng-Juin et and R A1 h are the inverse functions of the function L A x and the 2009), modified grey relation method (James J H Liou et al., 2011) and so on This paper applied fuzzy set theory based on function R A x , respectively modified SERVQUAL model to analysis service quality in certification & inspection industry in China method for one fuzzy number is proposed by Chen and Methodology The fuzzy set theory used in this paper was introduced by Zadeh (1965) firstly In fact, fuzzy set theory has been The graded mean integration representation applied in solving many decision-making problems In this paper, a combined Hsieh(1998) This method is based on the integral value of graded mean h-level of fuzzy number In detail, suppose the graded mean h-level value of fuzzy number A is h LA1 h RA1 h / (the graded mean fuzzy SERVQUAL method will be used to copy with the measurement of service quality in certification & inspection industry In this section, the basic definitions of fuzzy set theory are briefly presented as follows: 2.1 The concept of fuzzy number Because of the simplicity of the concept and computation for triangular fuzzy number set, it is widely used in practical applications (Pedrycz, 1994) h-level value of fuzzy number A as Fig 2.) During the research of the measurement of service quality in the certification & inspection industry, there A are steps involved They are questionnaire designing, h interview survey, calculation for collecting data LA RA 3.1 Questionnaire design In this research, the questionnaire designing is based on the previous literatures and the interview of the interviewees came from China Certification & LA1 h a Fig c R A1 h b Inspection Group (CCIC) In the questionnaire, there are major dimensions and 22 items The graded mean h-level value of 3.2 Interview survey LA1 h fuzzy number A All the interviewees are the customs of CCIC who The graded mean integration representation of A have already accepted the service provided by CCIC is P A Participants are randomly selected The survey spent P A h LA1 h R A1 h h a about weeks The size of the sample is 405 The dh b a h a c a h response rate is nearly 100% hdh 3.3 Calculation for collecting data dh Based on fuzzy set theory, the basic arithmetic operations of fuzzy numbers have been clearly triangular fuzzy a2，b2，c2 A2 is and a also is another triangular fuzzy a2，b1 b2，c1 A2 a1 c2，b1 b2，c1 c2 （2） service to customers There exist gaps between the responsiveness、reliability、empathy、assurance The Company we studied (CCIC) should give the most priority of increasing investment in the visual image of a2 （3） A case study of certification & inspection service quality conclusion that CCIC doesn’t provide satisfactory dimensions from high to low as following: tangible、 (2)Subtraction of fuzzy numbers A1 service quality can measure a company’s service dimensions We sort these gaps among different (1)Addition of fuzzy numbers a1 between the expectations and the perceptions of the expectations and the perceptions of all service quality fuzzy numbers as follow A2 The fuzzy SERVQUAL method is a combination quality level From the study, we can come to the number We present the basic arithmetic operations of A1 Conclusions and suggestions of SERVQUAL model and fuzzy set theory The gaps a1，b1，c1 number gap between expectation and perception are shown in Table and Table 2.2 The arithmetic operations on fuzzy numbers Suppose hdh The scores of expectations and perceptions for of the scores of expectations and perceptions, and the （1） described service quality are calculated, respectively The result a 4b c A1 the company in order to improve customers’ perception of its services Table Scores of fuzzy perceptions and expectations Dimensions Fuzzy perception Fuzzy expectation Fuzzy gap Responsiveness (6.139,8.134,8.883) (6.422,8.422,8.963) (-2.824,-0.288,2.46) (6.107,8.102,8.840) (6.421,8.421,8.956) (-2.849,-0.319,2.419) (6.197,8.192,8.905) (6.421,8.421,8.972) (-2.775,-0.229,2.484) (6.152,8.147,8.925) (6.436,8.436,8.978) (-2.826,-0.289,2.489) (6.156,8.151,8.899) (6.415,8.415,8.950) (-2.794,-0.264,2.484) (6.084,8.078,8.843) (6.417,8.417,8.961) (-2.878,-0.338,2.426) Assurance (6.239,8.246,8.983) (6.470,8.470,8.985) (-2.746,-0.223,2.513) (6.217,8.212,8.935) (6.5,8.5,8.989) (-2.772,-0.289,2.435) (6.289,8.284,8.960) (6.482,8.482,8.978) (-2.689,-0.198,2.478) (6.344,8.39,9.16) (6.490,8.490,8.989) (-2.645,-0.1,2.67) (6.105,8.1,8.875) (6.407,8.407,8.983) (-2.878,-0.307,2.468) Reliability (6.224,8.219,8.924) (6.489,8.489,8.982) (-2.758,-0.271,2.435) 10 (6.09,8.085,8.895) (6.459,8.459,8.967) (-2.877,-0.374,2.436) 11 (6.199,8.194,8.925) (6.504,8.504,8.989) (-2.79,-0.31,2.421) 12 (6.264,8.259,8.92) (6.492,8.492,8.989) (-2.725,-0.233,2.429) 13 (6.342,8.337,8.955) (6.503,8.503,8.983) (-2.642,-0.166,2.452) Tangibles (5.782,7.775,8.8) (6.308,8.308,8.949) (-3.166,-0.533,2.491) 14 (5.809,7.799,8.769) (6.3,8.3,8.939) (-3.13,-0.501,2.469) 15 (5.875,7.87,8.832) (6.335,8.335,8.961) (-3.086,-0.465,2.497) 16 (5.645,7.639,8.77) (6.294,8.294,8.950) (-3.305,-0.655,2.476) 17 (5.777,7.77,8.806) (6.345,8.345,8.955) (-3.178,-0.572,2.461) 18 (5.806,7.796,8.821) (6.268,8.268,8.939) (-3.132,-0.472,2.553) Empathy (6.251,8.246,8.913) (6.494,8.494,8.989) (-2.738,-0.249,2.419) 19 (6.368,8.363,8.95) (6.506,8.506,8.989) (-2.621,-0.142,2.445) 20 (6.147,8.142,8.885) (6.481,8.481,8.989) (-2.842,-0.3392.405) 21 (6.284,8.279,8.92) (6.515,8.515,8.994) (-2.711,-0.237,2.405) 22 (6.206,8.201,8.894) (6.475,8.4745,8.983) (-2.777,-0.274,2.42) Table Scores of perceptions and expectations Dimensions Perception Expectation Gap Responsiveness 7.926[4] 8.179[4] -0.253[2] 7.893[15] 8.177[14] -0.284[9] 7.978[10] 8.180[13] -0.202[18] 7.944[11] 8.193[12] -0.249[11] 7.943[12] 8.171[16] -0.228[15] 7.873[17] 8.174[15] -0.301[7] Assurance 8.034[1] 8.222[3] -0.188[5] 8.000[7] 8.248[5] -0.248[13] 8.064[4] 8.231[9] -0.167[19] 8.177[1] 8.240[7] -0.063[22] 7.897[14] 8.170[17] -0.273[10] Reliability 8.004[3] 8.238[2] -0.234[3] 10 7.888[16] 8.210[11] -0.322[6] 11 7.983[9] 8.252[3] -0.268[11] 12 8.036[6] 8.241[6] -0.205[17] 13 8.107[3] 8.250[4] -0.142[20] Tangibles 7.614[5] 8.082[5] -0.468[1] 14 7.629[20] 8.073[20] -0.444[3] 15 7.698[18] 8.106[19] -0.408[5] 16 7.495[22] 8.070[21] -0.575[1] 17 7.612[21] 8.113[18] -0.501[2] 18 7.635[19] 8.047[22] -0.411[4] Empathy 8.025[2] 8.243[1] -0.218[4] 19 8.129[2] 8.253[2] -0.124[21] 20 7.933[13] 8.232[8] -0.299[8] 21 8.053[5] 8.262[1] -0.209[7] 22 7.984[8] 8.226[10] -0.242[14] ACKNOWLEDGMENTS This research was 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SERVQUAL model to analysis service quality in certification & inspection industry in China method for one fuzzy number is proposed by Chen and Methodology The fuzzy set theory used in this paper... company’s service dimensions We sort these gaps among different (1)Addition of fuzzy numbers a1 between the expectations and the perceptions of the expectations and the perceptions of all service quality. .. quality fuzzy numbers as follow A2 The fuzzy SERVQUAL method is a combination quality level From the study, we can come to the number We present the basic arithmetic operations of A1 Conclusions and