An empirical study of customer satisfaction with marine products wholesale market

Indian Journal of Geo Marine Sciences Vol. 46 (07), July 2017, pp. 1470-1476 An empirical study of customer satisfaction with marine products wholesale market Sun Zhaoqun 1,2,3, Wan Rong 3, Ding Xiangqian 1,2, Zhu Yugui 3 * & Zhang Guangrui 1,2 * 1.College of Information Science and Engineering, Ocean University of China, Qingdao, 266003, China 2.Center of New Star Computer Engineering, Ocean University of China, Qingdao 266071, China 3.College of Fisheries, Ocean University of China, Qingdao, 266003, China. *[E-mail: zhuyugui66@aliyun.com, zhang.guangrui@outlook.com] Received 18 December 2015 ; revised 17 November 2016 Present study is to build an appropriate model of marine products wholesale markets customer satisfaction theory by studying and improving on some existing international mainstream satisfaction index models. This study also gives some advices to improve the customer satisfaction for marine products wholesale markets. The results show that the customer satisfaction of marine products wholesale markets is decided by the customer perceived service quality and the customer previous expectation. Most reasonable approaches to make the marine wholesale customers satisfied are to provide timely and high efficiency marine products transaction information, construct an excellent infrastructure environment, build fair transaction order and charging rules as well as offer the convenient surrounding services. [Keywords: marine products, customer satisfaction, wholesale markets, empirical study] Introduction Customer satisfaction is regarded as a very important concept for organizations of all types, such as firms, governments, non-governmental organizations and so on 1,2,3,4&5. In 1965, Cardozo first proposed the notion of customer satisfaction as well as conducted groundbreaking research 1. Since then, Customer satisfaction theory gradually developed into one of the centers of modern marketing practice theory 6,7&8. Over the past decades, more and more organizations have increasingly acknowledged the importance markets customer satisfaction 9,10,11&12. A key motivation for the increasing emphasis on customer satisfaction is that higher customer satisfaction can lead to have a stronger competitive position. In recent decades, many literatures about customer satisfaction research are emerged. Some research shows higher customer satisfaction may result in higher markets share and profitability 13,14&15, reduced price elasticity, lower business cost, reduced failure cost, and mitigated cost of attracting new customers 16,17,18&19. Markets research is the process of designing, gathering, analyzing, and reporting information that may be used to solve a specific marketing problem 20,21&22. Market research can help the organizations understand their customers so that they can modify their strategies to attract more customers 23,24,25&26. The marketing literature suggests that the long term success of a firm is clearly based on its ability to rapidly respond to changing customer needs and preferences 27,28,29&30. Marine products wholesale markets is a main carrier of marine products circulation, an important platform of carrying out marine products distribution business and an essential bridge of connecting manufacturers, wholesalers, retailers and consumers. In China, there are numerous marine products wholesale markets at present. As to the marine products wholesale markets, the battle for marine products dealers is the key to success. However, there are few studies in the marine products wholesale markets because of the special attributes of marine products. Customer satisfaction study about marine product wholesale markets has not yet seen. This study plans to use the concept of customer satisfaction to study marine products wholesale and establish a wholesale markets structure model between service quality, customer expectations and customer satisfaction by an empirical study of marine products wholesale markets in order to provide a theoretical and empirical basis for the

INDIAN J. MAR. SCI., VOL. 46, NO. 07, JULY 2017 1471 construction of marine products wholesale markets customer satisfaction model. Materials and Methods Through the studying and improving on some existing international mainstream satisfaction index models, the following six hypotheses are put forward: Assumption1, the higher the customer expectations to marine product wholesale markets, the lower customer satisfaction; Assumption 2, the higher the quality of customer perception to marine product wholesale service, the higher customer satisfaction; Assumption 3,the more reasonable the charges situation, the higher customer perception of service quality and customer satisfaction; Assumption 4, The better the infrastructure of marine product wholesale markets, the higher customer perception of service quality and customer satisfaction. Assumption 5, the timelier and high efficiency the marine product transaction information, the higher customer perception of service quality and customer satisfaction; Assumption 6, the more convenient the surrounding services, the higher customer perception of service quality and customer satisfaction; Assumption 7: The better the transaction order, the higher customer perception of service quality and customer satisfaction. According to designed principles and hypothesis, this study modifies and determines the main questionnaire items by Small-scale interviews with the marine products wholesale markets managers and customers. Finally, 18 variables were designed in this questionnaire and all the items were measured on 10-point scales, with anchors ranging from 1 denoting a very negative view and 10indicating a very positive view. Relying on 10-point scales enables customers to make better discriminations 31&32. In other words, all the respondents should give a value between 1 and 10 to the 18 variables according to their satisfaction to the marine products wholesale markets (Table 1). Variables x 11 x 12 x 13 x 21 x 22 x 23 x 31 x 32 x 33 x 41 x 42 x 43 x 51 x 52 x 53 x 54 x 61 x 62 y Table 1 Explanations of the variables Explanations The attitude of fee collectors The rationality of charging The phenomenon of unauthorized fees The infrastructure environment in the marine products wholesale markets The location of the marine products wholesale markets The internal environment in marine products wholesale markets The fairness degree of the markets transactions The safety level of markets transactions The punishments conditions for illegal transactions The methods to provide transaction information by the marine products wholesale markets The promptness of the transaction information provided by the marine products wholesale markets The operability of the online transaction information platform The convenient condition for accommodation The convenient condition for catering The convenient condition for banking The convenient condition for service station The expectations to the service quality of the marine products wholesale markets before entering The expectations to the condition of products sales in the marine products wholesale markets s before entering The overall satisfaction degree to the marine products wholesale markets The respondents visited in this study are customers of Chengyang marine products wholesale markets in Qingdao, China. Investigation date lasted from August 2015 to September 2015. During the investigation, 200 questionnaires were distributed totally and 152 of them were returned back, Valid Percent is 76%. Among them,there are 55 Fish dealers with the proportion of 38.18%, 49 Shellfish dealers,with the proportion of 32.37%, 36 Crustacean dealers with proportion of 23.68%, and 12 algae dealers with proportion of 7.89 %. Analysis of the collected survey data was conducted before carrying on the hypothesis testing, including the following two steps mainly: According to the scores of each variable gained through the questionnaires, we can calculate the mean score of each variable, and then analyze the approximate satisfaction degree of customers to each variable and the overall satisfaction degree in the marine products wholesale markets. The mean value indicate the overall attitude of the respondents. The essential information description of each variable's score is showed in table 1. We can see from table 2, nearly all the scores graded to each variable by the customers are higher than 7.5, even few of them are almost reach to 9.

1472 ZHAOQUN et al.: CUSTOMER SATISFACTION WITH MARINE PRODUCTS MARKET Table 2 Descriptive Statistics Variables N Minimum Maximum Mean Std. Deviation Variables N Minimum Maximum Mean Std. Deviation x 11 152 6 9 7.80 0.722 x 42 152 6 10 8.36 0.850 x 12 152 8 10 8.86 0.665 x 43 152 7 10 8.84 0.507 x 13 152 6 9 7.89 0.686 x 51 152 7 10 8.24 0.853 x 21 152 6 9 8.12 0.949 x 52 152 8 10 8.99 0.676 x 22 152 5 9 7.53 0.958 x 53 152 7 10 8.26 0.880 x 23 152 4 9 6.39 0.977 x 54 152 8 10 8.89 0.676 x 31 152 7 9 7.99 0.671 x 61 152 7 9 8.49 0.690 x 32 152 8 10 8.75 0.478 x 62 152 6 9 7.84 0.865 x 33 152 7 9 7.95 0.689 y 152 8 9 8.13 0.332 x 41 152 6 9 8.24 0.806 x 42 152 6 10 8.36 0.850 As a whole, the mean score of the item The overall satisfaction degree to the marine products wholesale markets is 8.13 which mean that the customers have a relatively high satisfaction degree to the marine products wholesale markets. In details, customers have a higher degree of satisfaction to the rationality of charging, the safety level of markets transactions, the convenient condition for catering and the appropriate condition for service station. Meanwhile,Customers are not very satisfied with the internal environment in marine products wholesale markets. Results The R software was used for conducting multiple regression analysis for the survey data, the results obtained are showed in Table 3 and Table 4: Table 3 Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 0.648 a 0.420 0.341 0.269 a. Predictors: (Constant), x62, x51, x41, x32, x13, x23, x54, x22, x61, x31, x43, x52, x11, x12, x42, x53, x21, x33 Table 4 ANOVA a Model Sum of Squares df Mean Square F Sig. Regression 6.980 18 0.388 5.348 0.001 b 1 Residual 9.645 133 0.073 Total 16.625 151 b. Predictors: (Constant), x62, x51, x41, x32, x13, x23, x54, x22, x61, x31, x43, x52, x11, x12, x42, x53, x21, x33 As can be seen from the above two tables, the overall model fits well, the test results indicate statistically significant (p=0.001). Table 5 Coefficients a Model Unstandardized Coefficients Standardized Coefficients B Std. Error Beta t Sig. (Constant) 2.600 0.910 2.856 0.005 x 11-0.049 0.058-0.107-0.844 0.400 x 12 0.093 0.072 0.186 1.298 0.196 x 13 0.093 0.065 0.192 1.424 0.157 x 21 0.052 0.089 0.148 0.578 0.564 x 22-0.003 0.086-0.008-0.031 0.975 x 23 0.064 0.030 0.190 2.165 0.032 x 31 0.138 0.119 0.280 1.165 0.246 x 32 0.010 0.079 0.014 0.123 0.902 x 33-0.023 0.126-0.047-0.182 0.856 x 41-0.013 0.069-0.032-0.192 0.848 x 42 0.146 0.059 0.375 2.481 0.014 x 43-0.059 0.070-0.090-0.846 0.399 x 51-0.086 0.079-0.220-1.088 0.278 x 52-0.022 0.055-0.045-0.398 0.691 x 53 0.174 0.075 0.461 2.303 0.023 x 54 0.092 0.043 0.187 2.121 0.036 x 61 0.017 0.046 0.036 0.379 0.705 x 62 0.057 0.036 0.147 1.591 0.114 The analysis results gained from the previous steps shows that the overall model fits well and were statistically significant. However, the results of each parameter estimate showed that the partial

INDIAN J. MAR. SCI., VOL. 46, NO. 07, JULY 2017 1473 regression coefficients were not statistically significant, and most of the significant values were greater than 0.05 or 0.1, which means the presence of co-linearity among these independent variables. Therefore, we should use the principal component analysis to extract the strong common factors from the correlation variables. Using the varimax rotation method and setting eigenvalues greater than 1 as the standard to extract several factors which affect marine products wholesale markets customer satisfaction by principal component analysis. Extracting factors of affecting marine products wholesale markets customer satisfaction by using principal component analysis Table 6 shows the eigenvalues in ascending order. We can know from table 5 that the eigenvalues of all the first six principal components are greater than one. Therefore, in this study, the first six principal components were extracted. Meanwhile the cumulative contribution rate has reached 84.031%. Table 6 Total Variance Explained Component Initial Eigenvalues Total Contribution rate (%) Cumulative contribution rate (%) 1 3.500 19.447 19.447 2 3.217 17.874 37.322 3 2.754 15.298 52.619 4 2.387 13.259 65.878 5 1.842 10.232 76.110 6 1.426 7.921 84.031 7 0.610 3.389 87.421 8 0.472 2.620 90.041 9 0.376 2.089 92.130 10 0.313 1.740 93.870 11 0.292 1.625 95.495 12 0.253 1.403 96.898 13 0.185 1.030 97.928 14 0.147 0.819 98.748 15 0.096 0.531 99.279 16 0.061 0.337 99.616 17 0.037 0.205 99.820 18 0.032 0.180 100.000 Extraction Method: Principal Component Analysis. From the above analysis, we have confirmed the number of factors affecting the marine products wholesale markets customer satisfaction is 6. Therefore, we set the number of principal components analysis as6 during the factor analysis process, and then we can obtain the factor loading matrix which is showed in Table 7. Table 7 Rotated Component Matrix a Variables Component 1 2 3 4 5 6 x 11-0.071-0.043 0.901-0.116-0.172-0.034 x 12-0.153 0.038 0.926-0.042-0.102 0.033 x 13-0.050 0.065 0.919 0.018-0.131 0.110 x 21-0.066-0.021-0.131 0.013 0.951 0.054 x 22-0.050 0.009-0.114-0.001 0.948 0.033 x 23-0.015 0.141-0.136-0.036 0.760 0.046 x 31-0.039 0.956 0.002-0.058 0.066 0.034 x 32-0.052 0.879 0.038 0.051 0.013 0.026 x 33-0.061 0.964 0.015-0.054 0.063 0.054 x 41-0.035-0.011-0.016 0.960-0.010-0.032 x 42-0.013-0.040-0.030 0.928 0.018-0.127 x 43-0.040-0.003-0.084 0.870-0.035 0.151 x 51 0.931-0.026-0.070 0.038-0.068 0.022 x 52 0.857-0.060-0.118-0.103-0.085 0.063 x 53 0.924-0.015-0.087 0.044-0.065 0.022 x 54 0.748-0.056-0.010-0.065 0.064-0.077 x 61 0.011 0.118 0.090-0.004-0.024 0.908 x 62 0.004-0.015 0.005-0.002 0.149 0.903 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 5 iterations.

1474 ZHAOQUN et al.: CUSTOMER SATISFACTION WITH MARINE PRODUCTS MARKET We can see from the factor loadings matrix, the first principal component includes the main information of originalvariablex 51, variable x 52, variable x 53 and variable x 54. In other words, the first principal component can be seen as the convenience index of impacting the marine product wholesale markets customer satisfaction; the second principal component includes the main information of the original variable x 31, variable x 32 and variable x 33.In other words, the second principal component can be seen as the order index of impacting the marine product wholesale markets customer satisfaction; the third principal component includes the main information of the original variablex 11, variable x 12 and variable x 13. In other words, the third principal component can be seen as the price index of impacting the marine product wholesale customer satisfaction; the fourth principal component includes the main information of the original variablex 41, variable x 42 and variable x 43. In other words, the fourth principal component can be seen as the information index of impacting the marine product wholesale customer satisfaction; the fifth principal component includes the main information of the original variable x 21, variable x 22 and variable x 23. In other words, the fifth principal component can be seen as the infrastructure index of impacting the marine product wholesale customer satisfaction; the sixth principal component includes the main information of the original variables x 61 andx 62. In other words, the fifth principal component can be seen as the expectation index of impacting the marine product wholesale customer satisfaction; Above analysis reveals that, there are six common factors (X 1, X 2, X 3, X 4, X 5 and X 6 ) extracted from the 18 variables designed in the questionnaire, which can prove that the model constructed in the above is reasonable. After confirming the six principal components, the principal component regression analysis was carried out on the six principal components for getting the regression coefficients of each principal component, and then we could know how each principal component affects the marine products wholesale markets customer satisfaction including the direction and degree. The correlation coefficients of the principal component regression analysis are shown in Table 8: Table 8 Coefficients a Model Unstandardized Coefficients Standardized Coefficients B Std. Error Beta t Sig. (Constant) 8.125 0.022 364.942 0.000 REGR factor score 1 for analysis 2 0.019 0.022 0.057 0.841 0.402 REGR factor score 2 for analysis 2 0.057 0.022 0.171 2.534 0.012 REGR factor score 3 for analysis 2 0.044 0.022 0.132 1.961 0.052 REGR factor score4 for analysis 2 0.116 0.022 0.349 5.178 0.000 REGR factor score5 for analysis 2 0.109 0.022 0.328 4.873 0.000 REGR factor score6 for analysis 2-0.084 0.022 0.253 3.758 0.000 Table 9 Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 0.586 a 0.343 0.316 0.274 a. Predictors: (Constant), REGR factor score 6 for analysis 2, REGR factor score 5 for analysis 2, REGR factor score 4 for analysis 2, REGR factor score 3 for analysis 2, REGR factor score 2 for analysis 2, REGR factor score 1 for analysis 2 ANOVA a Model Sum of Squares df Mean Square F Sig. Regression 5.700 6 0.950 12.610 0.000 b 1 Residual 10.925 145 0.075 Total 16.625 151 b. Predictors: (Constant), REGR factor score 6 for analysis 2, REGR factor score 5 for analysis 2, REGR factor score 4 for analysis 2, REGR factor score 3 for analysis 2, REGR factor score 2 for analysis 2, REGR factor score 1 for analysis 2 The results show that the analysis was statistically significant(table 9,table 10), there are six principal components(x 1, X 2, X 3, X 4, X 5 and X 6 )affecting the dependent variable Y. The linear regression equation is: Y = 8.125 + 0.019X 1 + 0.057X 2 + 0.044X 3 + 0.116X 4 + 0.109X 5 0.084X 6 We can elaborate from the above equation that the coefficients of X 1, X 2, X 3, X 4, X 5 are positive, which indicating that the five factors

INDIAN J. MAR. SCI., VOL. 46, NO. 07, JULY 2017 1475 affect the satisfaction positively. Meanwhile, the X 6 s coefficient is negative which indicating that this factor has a negative impact on satisfaction. In other words, this conclusion is consistent with the previous assumptions. Discussion It can be observed according to the coefficients showed in table 8 that the timeliness of information provided by the marine products wholesale markets and the infrastructure environment of the marine products wholesale markets rank in the top 2 position among the five factors, and both of them have a positive effect on customer satisfaction. It means that the timelier and high efficiency the marine product transaction information and the better the infrastructure environment of marine product wholesale markets will lead to a higher customer perception of service quality and customer satisfaction dramatically; the customer expectations in advance to the marine products wholesale markets ranked in the third position, and it has a negative effect on customer satisfaction. It shows that, to some extent the higher the customer expectations to marine product wholesale markets will lead to a lower customer perception of service quality and customer satisfaction; the transaction order and the condition of charges in the marine products wholesale markets ranked in the fourth and fifth position separately. The values of these two coefficients are relatively low, but both of them have a positive effect on customer satisfaction. It means that the better the transaction order and the more reasonable the charges situation will lead to a higher customer perception of service quality and customer satisfaction slightly; the convenience of the marine products wholesale markets ranked in the fifth position. It has a positive effect on the customer satisfaction, although the coefficient is relatively low. It means that that the more convenient of the surrounding services will lead to a higher customer perception of service quality and customer satisfaction. Conclusions We can conclude from the above analysis that the theoretical model which the customer satisfaction is determined by both the customer perception of service quality and the customer expectations in advance is established. And all hypotheses about the impacts of all kinds of factors to the marine products wholesale markets are confirmed and supported by this empirical study. In terms of the managers of marine products wholesale markets, they should manage to improve the competitiveness of the marine products wholesale markets by using the previous conclusion. However, although the lower of the customer expectations to marine product wholesale markets can improve the customer satisfaction to marine product wholesale markets, it is impossible to change the customers expectations in advance. So if the markets managers want to get the sustainable competitive advantage, they must stand on the customers' position, understand customers' needs and enhance the service quality such as providing timely transaction information, excellent infrastructure, well transaction order, reasonable charges situation and convenient surrounding services. Only in this way, marine products dealers can achieve comprehensively higher customer satisfaction. Acknowledgements This research is fully supported by a grant from the Fisheries College, Ocean University of China. References 1. Cardozo R N. An experimental study of consumer effort, expectation, and satisfaction. Journal of Marketing Research, 2(3)(1965): 244-249. 2. Webster, F. E.. The changing role of marketing in the corporation. Journal of Marketing, 56(4) (1992), 1 17. 3. Athanasso Poulos, Antreas D.. Customer satisfaction cues to support market segmentation and explain switching behavior. Journal of Business Research, (8)( 2000):191-207. 4. Banting RM.. Dion P.A. Industrial supplier-buyer negotiations, Industrial Marketing Management. (17)(1988):43-48. 5. Bharadwaj N.. Investigating the decision criteria used in electronic components procurement. Industrial Marketing Management, (33) (2004):317-323. 6. Sun Q.L.. The Surrey on Customer Satisfaction in agricultural products wholesale market, Business Research. (07)(2008):181-186. 7. Cardozo, Richard. An experimental study of consumer effort: expectation and satisfaction, Journal of Marketing Research, (8)(1965):244-249. 8. Ellinge Alexander E., Patrieia J. Customer satisfaction and loyalty in supply chain: the role of communication, Logistics and Transportation Review, (35)(1999): 121-134. 9. Bayraktar E, Tatoglu E. Measuring the efficiency of customer satisfaction and loyalty for mobile phone brands with DEA. Expert Systems with Applications, 39(1)(2012):99-106. 10. Frazier G. Speknian R.E., O'Neal C. Just-in-time exchange relations in industrial markets, Journal of Marketing, (52)(1988):52-67. 11. Gordon G L., Calantone R J., Di Benedetto CA. Business-to-business service marketing, Journal of Business and Marketing. (81)(1983):45-57.

1476 ZHAOQUN et al.: CUSTOMER SATISFACTION WITH MARINE PRODUCTS MARKET 12. Homburg Christian, Claus Garbe. Does Customer Interaction Enhance new Product Success, Journal of Business Research, (49)(1999):1-14. 13. Fornell, C.. A national satisfaction barometer: the swedish experience. Journal of Marketing, 56(1992), 6 21. 14. Howard.and J.N. Sheth. The theory of industrial buyer behavior, Newyork: Wiley, 1971:125-136. 15. Iacobueei Dawn, Amy Ostrom. Commercial and interpersonal relationships. Intemational Journal of Research in Marketing, 1996(6):53-72. 16. Chien, T. K., Chang, T. H., & Su, C. T.. Did your efforts really win customers satisfaction? Industrial Management and Data Systems, 103(4) (2003), 253 262. 17. Minna M. Buyer-seller Customer Satisfaction: the Influence of the Environment and Customer Service, Journal of Business and Industrial Marketing, (4)(2004):403-415. 18. Mndambi S.M., Doyle P, Wong V. An Exploration of Branding in industrial markets, Industrial Marketing Management, (26)(1997):433-446. 19. Nguyen Nha,Gaston Leblanc. Corporate image and corporate reputation in customers' retention decisions in sendees. Journal of Retailing and Consumer services, 2001(8):227-236. 20. Yi,Y. The Determinants of Consumer Satisfaction: The moderating role of ambiguity. Advances in Consumer Research, (20)(1993):502-506. 21. Bitner MJ, Booms BH, Tetreault MS. The service encounter: diagnosing favorable and unfavorable incidents. Journal of Marketing, 54(1)(1990):71-84. 22. Youngdahl, William E., et al. Revisiting customer participation in service encounters: does culture matter?. Journal of Operations Management, 21(1)(2003):109-120. 23. Ahmad, Amir, L. Dey, and S. M. Halawani. A rule-based method for identifying the factor structure in customer satisfaction. Information Sciences, 198.3(2012):118 129. 24. P.A.Dion, R.M. Bnating, Buyer Reactions to Product Stockouts in Business to Business Markets, Industrial Marketing Management, (24)( 1995):341-350. 25. Parasuraman. A,.Valarie A.,Zeithaml and Leonard L. Berry. A1ternative scales for measuring service quality: A comparative assessment based on psychometric and diagnostic criteria. Journal of Retailing, 19 (8)(1994):201-230. 26. Philip Kotler. Marketing Management, Newyork: prentice Hall,2000:215-218. 27. Narver, J. C., & Slater, S. F.. The effect of a market orientation on business profitability. Journal of Marketing, 54(4) (1990), 20 35. 28. Verhoed C.W.. Post-Purehase Strategy: A key to successful industrial marketing and customer satisfaetion, Industrial Marketing Management, (24)(2001):91-98. 29. WestbrookR.A.,M.D.Reilly. An alternative to the Disconfirmation of Expectation Theory of Consumer Satisfaction, Consumer Research, (10)(1983):256-261. 30. Andrews, F. M.. Construct validity and error components of survey measures: A structural modeling approach. The Public Opinion Quarterly, 48(2) (1984), 409 442. 31. Qualls W.J., Rosa J.A. Assessing industrial buyers, Perceptions of quality and their effects on satisfaction. Industrial Marketing Management, (24)(1995):359-368. 32. Oliver,R.L., Conceptual issues in the structural analysis of consumption emotion, satisfaction and quality: Evidence in a service setting. Advances in Consumer Research, 21(1)(1997):203-210.