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Antecedents of E-Satisfaction in Online Retailing:An Empirical Study


Affiliations
1 BBAU, (A Central University), Lucknow-226025, Uttar Pradesh, India
2 Babasaheb Bhimrao Ambedkar University (A Central University), Lucknow, India
 

Purpose: the main purpose of the study was to examine the factors that affect customer satisfaction in online retailing in Indian context and identify the relative influence of factors. A theoretical model was derived in accordance with the literature and was tested empirically.

Methodology/Approach: the data was collected convenience through a structured questionnaire administered through both personal and online mode. Exploratory Factor Analysis was done to measure the latent constructs and establish the structure of factors. The proposed model and impact of each factor on e-satisfaction was tested through Multiple Linear Regression.

Findings: it was found that the antecedents of e-satisfaction can be measured with five underlying factors instead of proposed four factor model. The factors that were found to have significant impact on e-satisfaction are merchandising, product information, perceived value and financial transaction. Interestingly, convenience was found to have an insignificant impact. The strongest impact was that of merchandising followed by perceived value.

Practical implications: firstly the study contributes to the literature by establishing that scales developed to measure factors affecting satisfaction in e-retailing elsewhere can also employed in Indian context also. From e-marketing point of view it was brought forward that merchandising and perceived value are the most important factors that affect e-sat therefore marketers should strengthen their merchandising activities and enhance value perception of the customers.

Research limitations: use of non-probabilistic sampling technique due to non availability of sampling frame was the major limitation that restricts the generalization of the results.


Keywords

E-Satisfaction, Antecedents of E-Sat, Factors Affecting E-Sat., E-Retailing.
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  • Anderson, E. W., Claes, F., Lehmann, D. R. (1994). Customer satisfaction, market share, and profitability: Findings from Sweden. Journal of Marketing, 58, 53-66.

  • Anderson, R. E., and Srinivasan, S. S. (2003). E-satisfaction and e-loyalty: A contingency framework.

  • Psychology and Marketing, 20(2), 123-138.

  • Bhattacherejee, A. (2001). An empirical analysis of the antecedents of electronic commerce service continuance. Decision Support Systems, 32, 201-214.

  • Bitner, M. J., Brown, S. W., Meuter, M. L. (2000). Technology infusion in service encounters. Journal of the Academy of Marketing Science, 28(Winter), 138-149.

  • Burke, R. R. (2002). Technology and the customer interface: What consumers want in the physical and virtual store? Journal of the Academy of Marketing Science, 30(Fall), 411- 432.

  • Carlson, J., O’Cass, A., and Ahrholdt, D. (2015). Assessing customers’ perceived value of the online channel of multichannel retailers: A two country examination. Journal of Retailing and Consumer Services, 27(2015), 90–102.

  • Chang, H. H., and Wang, H. (2011). The moderating effect of customer perceived value on online shopping behavior. Online Information Review, 35(3), 333-359.

  • Crisil Research. (2014, Feb.). Crisil Opinion, e-tails eats into retail. Retrieved from http:// www.crisil.com/pdf/research/CRISIL-Research-Article-Online-Retail-Feb14.pdf.

  • Deloitte and ASSOCHAM, (2014). Future of e-Commerce: Uncovering Innovation. Retrieved from http://www.deloitte.com/in.

  • Evanschitzky, H., Iyer, G.R., Hesse, J., and Ahlert, D. (2004). E-satisfaction: a re-examination. Journal of Retailing, 80(2004), 239-247.

  • Field, A. P. (2009). Discovering statistics using SPSS. London, England: Sage.

  • Flipkart (n.d.). The E-Commerce Market in India. Retrieved from http://www.flipkartcareers.com/work-in-india.php.

  • How the Big Online Sales Fared. (2016, October 4). Ascent, Times of India, p. 24.

  • Jolliffe, I. T. (1972). Discarding variables in a principal component analysis, I: Artificial data. Applied Statistics, 21, 160-173.

  • Jolliffe, I. T. (1986). Principal component analysis. New York: Springer.

  • Kass, R. A., and Tinsley, H. E. A. (1979). Factor analysis. Journal of Leisure Research, 11, 120-138.

  • Kaiser, H. F. (1960). The application of electronic computers to factor analysis. Educational and Psychological Measurement, 20, 141-151.

  • Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39, 31-36.

  • Kim, J. H., Kim, M., & Kandampully, J. (2007). The impact of buying environment characteristics of retail websites. Service Industries Journal, 27(7), 865-880.

  • Kim, J. H., Kim, M., & Kandampully, J. (2011). Buying environment characteristics in the context of eservice. European Journal of Marketing, 43(9-10), 1188-1204.

  • Liu, X., He, M., Gao, F., and Xie, P. (2008). An empirical study of online shopping customer satisfaction in China: a holistic perspective. International Journal of Retail & Distribution Management, 36(11), 919-940.

  • Nunnally, J. C. (1978). Psychometric theory. New York: McGraw-Hill.

  • Oliver, R. L. (1981). Measurement and evaluation of satisfaction processes in retail settings. Journal of Retailing, 57, 25-48.

  • Oliver, Richard L. (1997). Satisfaction: A behavioral perspective on the consumer. New York: McGraw-Hill.

  • Oliver, R.L. (1999). Whence consumer loyalty? Journal of Marketing, 63(Special Issue), 33-44.

  • Parasuraman, A., Zeithaml, Valerie A., Berry, Leonard L. (1988). SERVQUAL: A multi-item scale for measuring consumer perception of service quality. Journal of Retailing, 64(1), 12–40.

  • Parasuraman A., Zeithaml V. A. and Malhotra, A. (2005). E-S-QUAL: A Multiple-Item Scale for Assessing Electronic Service Quality. Journal of Service Research, 7(X), 1-21.

  • PwC India. (2015, Feb.). e-Commerce in India: Accelerating growth. Retrieved from http://www.pwc.in.

  • Ribbink, D., VanRiel, A. C. R., Liljander, V., and Streukens, S. (2004). Comfort your online customer: quality, trust and loyalty on the inter¬net. Managing Service Quality, 14(6), 446-456.

  • Schaupp, L. C., and Bélanger, F. (2005). A Conjoint Analysis of Online Consumer Satisfaction. Journal of Electronic Commerce Research, 6(2), 95-111.

  • Shwu-Ing, W. (2003). The relationship between consumer characteristics and attitude toward online shopping. Marketing Intelligence and Planning, 21(1), 37-44.

  • Siddiqui, U. A., and Khan, M. S. (2014). E-Tailing in India: Prospects and Challenges. İn Gera, N. ( Eds.), Managing Organizations of Tomorrow by Capitalizing Generation Next (Vol. 1, pp. 159-172). New Delhi, India: Bharti Publications.

  • Siddiqui, U. A., and Khan, M. S. (2016). Antecedents of E-Satisfaction in Online Retailing: A Conceptual Framework. Ottoman: Journal of Tourism and Management Research, Vol 1(1/2016), 155-165.

  • Sweeney, J. C. and Soutar, G. N. (2001). Consumer-Perceived Value: The Development of a Multiple Item Scale. Journal of Retailing, 77(2), 203-220.

  • Srinivasan, S. S., and Anderson, R. E., (2002). Customer Loyalty in e-commerce: an exploration of its antecedents and consequences. Journal of Retailing, 78, 41-50.

  • Stevens, J. P. (2002). Applied multivariate statistics for the social sciences. NJ: Hillsdale.

  • Winer, R. S. (2001). A framework for customer relationship management. California Management Review, 43, 89-105.

  • Wolfinbarger, M. and Gilly, M.C. (2003). Etailq: dimensionalising, measuring and predicting, etail quality. Journal of Retailing, 79(3), 183-98.

  • Yang, Z., & Peterson, R. T. (2004). Customer per¬ceived value, satisfaction, and loyalty: The role of switching costs. Psychology and Marketing, 21(10), 79-822.

  • Yoo, B. and Donthu, N. (2001). Developing a scale to measure the perceived quality of an internet shopping site. Quarterly Journal of Electronic Commerce, 2(1), 31-46.

  • Zeithaml, V. A., Berry, L. L., and Parasuraman, A. (1996). The Behavioral Consequences of Service Quality. Journal of Marketing, 60(April), 31-46.

  • Zeithaml, V.A. and Bitner, M.J. (1996). Customer Expectations of Services: Services Marketing. New York: McGraw Hill.


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  • Antecedents of E-Satisfaction in Online Retailing:An Empirical Study

Abstract Views: 315  |  PDF Views: 181

Authors

Urooj Ahmad Siddiqui
BBAU, (A Central University), Lucknow-226025, Uttar Pradesh, India
M. S. Khan
Babasaheb Bhimrao Ambedkar University (A Central University), Lucknow, India

Abstract


Purpose: the main purpose of the study was to examine the factors that affect customer satisfaction in online retailing in Indian context and identify the relative influence of factors. A theoretical model was derived in accordance with the literature and was tested empirically.

Methodology/Approach: the data was collected convenience through a structured questionnaire administered through both personal and online mode. Exploratory Factor Analysis was done to measure the latent constructs and establish the structure of factors. The proposed model and impact of each factor on e-satisfaction was tested through Multiple Linear Regression.

Findings: it was found that the antecedents of e-satisfaction can be measured with five underlying factors instead of proposed four factor model. The factors that were found to have significant impact on e-satisfaction are merchandising, product information, perceived value and financial transaction. Interestingly, convenience was found to have an insignificant impact. The strongest impact was that of merchandising followed by perceived value.

Practical implications: firstly the study contributes to the literature by establishing that scales developed to measure factors affecting satisfaction in e-retailing elsewhere can also employed in Indian context also. From e-marketing point of view it was brought forward that merchandising and perceived value are the most important factors that affect e-sat therefore marketers should strengthen their merchandising activities and enhance value perception of the customers.

Research limitations: use of non-probabilistic sampling technique due to non availability of sampling frame was the major limitation that restricts the generalization of the results.


Keywords


E-Satisfaction, Antecedents of E-Sat, Factors Affecting E-Sat., E-Retailing.

References