Skip to main content
SpringerLink
Log in

Assessing and managing e-commerce service convenience

  • Published:
Information Systems Frontiers Aims and scope Submit manuscript

Abstract

Due to the burgeoning growth of electronic commerce (EC or e-commerce), online shopping has become a key competitive strategy for online retailers (e-retailers) to attract more customers, expand market boundaries, and create more benefits. Service convenience (SERVCON), a concept of benefit and related to customer satisfaction and retention, has received increasing attention and is now treated as an important factor in shopping behavior. Unfortunately, the literature on convenience has explored only traditional retailers. Thus, this research attempts to apply the results of marketing and information management (IM) research concerning customer service convenience with e-retailers. Based on a survey of 304 online shoppers (e-shoppers) in Taiwan, a 14-item e-commerce service convenience (EC-SERVCON) instrument was constructed. We then construct an EC-SERVCON managerial grid for managers to use in formulating strategy for improving service convenience. The instrument, findings, and implications of this study will be valuable to researchers and practitioners interested in designing, implementing, and managing e-commerce.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Abdul-Muhmin, A. G. (2011). Repeat purchase intentions in online shopping: the role of satisfaction attitude, and online retailers’ performance. Journal of International Consumer Marketing, 23(1), 5–20.

    Google Scholar 

  • Alba, J., & Lynch, J. (1997). Interactive home shopping: consumer, retailer, and manufacture incentives to participate in electronic marketplace. Journal of Marketing, 61(3), 38–53.

    Google Scholar 

  • Al-Natour, S., Benbasat, I., & Cenfetelli, R. (2006). The role of design characteristics in shaping perceptions of similarity: the case of online shopping assistants. Journal of the Association for Information Systems, 13(2), 821–861.

    Google Scholar 

  • Al-Rasheed, S., Zairi, M., & Ahmed, A. M. (2010). Getting in the mind of the customer: an empirical study of consumer behaviour in retailing. European centre for best practice management, 1–12.

  • Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: a review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423.

    Google Scholar 

  • Babakus, E., & Boller, G. W. (1992). An empirical assessment of the SERVQUAL scale. Journal of Business Research, 24(3), 253–268.

    Google Scholar 

  • Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94.

    Google Scholar 

  • Berry, L. L., Seiders, K., & Grewal, D. (2002). Understanding service convenience. Journal of Marketing, 66(3), 1–17.

    Google Scholar 

  • Bettman, J. R., Johnson, E. J., Luce, M. F., & Payne, J. W. (1993). Correlation, conflict, and choice. Journal of Experimental Psychology: Learning, Memory, and Cognition, 19(4), 931–951.

    Google Scholar 

  • Bhatnagar, A., Misra, S., & Rao, H. R. (2000). On risk, convenience, and internet shopping behavior. Communications of the ACM, 43(11), 98–105.

    Google Scholar 

  • Brown, T. J., Churchill, G. A., Jr., & Peter, J. P. (1993). Research note: improving the measurement of service quality. Journal of Retailing, 69(1), 127–139.

    Google Scholar 

  • Calder, B. J., Phillips, L. W., & Tybout, A. M. (1981). Designing research for application. Journal of Consumer Research, 8(2), 197–207.

    Google Scholar 

  • Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by multitrait-multimethod matrix. Psychological Bulletin, 56(2), 81–105.

    Google Scholar 

  • Capps, R. (2009). Kevin Maney’s trade off offers another look at quality vs. convenience. http://www.wired.com/epicenter/2009/09/kevin-maneys-trade-off-offers-another-look-at-quality-vs-convenience/. Accessed 22 September 2011.

  • Carman, J. M. (1990). Consumer perceptions of service quality: an assessment of the SERVQUAL dimensions. Journal of Retailing, 66(1), 35–55.

    Google Scholar 

  • Cavana, R., Delahaye, B. L., & Sekaran, U. (2001). Applied business research: Qualitative and quantitative methods (3rd ed.). New York: Wiley.

    Google Scholar 

  • Churchill, G. A., Jr. (1979). A paradigm for developing better measures of marketing constructs. Journal of Marketing Research, 16(1), 64–73.

    Google Scholar 

  • Copeland, M. T. (1923). Relation of consumers’ buying habits to marketing methods. Harvard Business Review, 1(April), 282–289.

    Google Scholar 

  • Cowles, D. L., Kiecker, P., & Little, M. W. (2002). Using key informant insights as a foundation for e-retailing theory development. Journal of Business Research, 55(8), 629–636.

    Google Scholar 

  • Cronbach, L. J., & Meehl, P. E. (1955). Construct validity in psychological tests. Psychological Bulletin, 52(4), 281–302.

    Google Scholar 

  • Cronin, J. J., Jr., & Taylor, S. A. (1992). Measuring service quality: a reexamination and extension. Journal of Marketing, 56(3), 55–68.

    Google Scholar 

  • Cronin, J. J., Jr., & Taylor, S. A. (1994). SERVPERF versus SERVQUAL: reconciling performance-based and perceptions-minus-expectations measurement of service quality. Journal of Marketing, 58(1), 125–131.

    Google Scholar 

  • Cronin, J. J., Jr., Brady, M. A., & Hult, G. T. M. (2000). Assessing the effects of quality, value, and customer satisfaction on consumer behavioral intentions in service environments. Journal of Retailing, 76(2), 193–218.

    Google Scholar 

  • Dahan, E., & Hauser, J. R. (2002). The virtual customer. Journal of Product Innovation Management, 19(5), 332–353.

    Google Scholar 

  • Dellaert, B., & Kahn, B. E. (1999). How tolerable is delay? Consumers’ evaluations of internet web sites after waiting. Journal of Interactive Marketing, 13(1), 41–54.

    Google Scholar 

  • Diamantopoulos, A., & Siguaw, J. (2000). Introducing LISREL. London: Sage.

    Google Scholar 

  • Douglas, A., Mills, J., & Kavanaugh, R. (2007). Exploring the use of emotional features at romantic destination websites. Information and Communication Technologies in Tourism, 8, 331–340.

    Google Scholar 

  • Featherman, M. S., & Pavlou, P. A. (2003). Predicting e-services adoption: a perceived risk facets perspective. Human-Computer Studies, 59(4), 451–474.

    Google Scholar 

  • Fick, G. R., & Ritchie, J. R. B. (1991). Measuring service quality in the travel and tourism industry. Journal of Travel Research, 30(2), 55–68.

    Google Scholar 

  • Finn, D. W., Baker, J., Marshall, G. W., & Anderson, R. (1996). Total quality management and internal customers: measuring internal service quality. Journal of Marketing Theory & Practice, 4(3), 36–51.

    Google Scholar 

  • Fornell, C. L., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.

    Google Scholar 

  • Forrester Research, I. (2008). US eCommerce forecast: 2008 To 2012. http://www.forrester.com/Research/Document/Excerpt/0,7211,41592,00.html. Accessed September 19 2009.

  • Frost, D., Goode, S., & Hart, D. (2010). Individualist and collectivist factors affecting online repurchase intentions. Internet Research, 20(1), 6–28.

    Google Scholar 

  • Gupta, S., & Kim, H. W. (2010). Shopping: the mental accounting theory perspective. Psychology and Marketing, 27(1), 13–35.

    Google Scholar 

  • Gupta, A., Su, B. C., & Walter, Z. (2004). An empirical study of consumer switching from traditional to electronic channels: a purchase-decision process perspective. International Journal of Electronic Commerce, 8(3), 131–161.

    Google Scholar 

  • He, W., & Chai, J. (2009). Study on mechanism and models of customer segmentation of C2C shopping. In 1st International Conference on Information Science and Engineering (ICISE). Nanjing, China, Dec 26–28

  • Herden, S., Mkrtchyan, A., Rautenstrauch, C., Zwanziger, A., & Schenk, M. (2003). Personal information guide-a platform with location based services for mobile powered e-commerce. In International Conference, Management and Technology in the New Enterprise. Havana, Cuba

  • Hertzum, M., Juul, N. C., Jørgensen, N., & Nørgaard, M. (2004). Usable security and e-banking: Ease of use vis-à-vis security. In OZCHI Conference. Wollongong, Australia, 22–24 November

  • Hirst, A., & Omar, O. E. (2007). Assessing women’s apparel shopping behaviour on the internet. The Journal of Retail Marketing Management Research, 1(1), 32–40.

    Google Scholar 

  • Hofacker, C. F. (2001). Internet marketing (3rd ed.). New York: Wiley.

    Google Scholar 

  • Hoffman, D. L., Novak, T. P., & Peralta, M. (1999). Building consumer trust on line. Communications of the ACM, 42(4), 80–85.

    Google Scholar 

  • Horrigan, J. B. (2008). Online shopping: Convenient but risky. http://pewresearch.org/pubs/733/online-shopping. Accessed 22 September 2011.

  • Jaehun, J. (2007). An empirical study on the relationship between customer value and repurchase intention in Korean internet shopping malls. Journal of Computer Information System, 48(1), 53–62.

    Google Scholar 

  • Jones, M. A., Mothersbaugh, D. L., & Beatty, S. E. (2003). The effects of locational convenience on customer repurchase intentions across service types. Journal of Services Marketing, 17(7), 701–712.

    Google Scholar 

  • Kelley, E. J. (1958). The importance of convenience in consumer purchasing. Journal of Marketing, 23(32–38).

    Google Scholar 

  • Khalifa, M., Limayem, M., & Liu, V. (2004). A contingency theory for consumer retention: The role of online shopping habit. In M. G. Hunter & F. B. Tan (Eds.), Advanced topics in global information management, vol. 3 (pp. 42–62). Hershey: Idea Group Publishing.

    Google Scholar 

  • Kim, B. C., & Park, Y. W. (2011). Security verses convenience? An experimental study of user misperception of wireless internet security quality. Decision Support Systems, In press.

  • King, A. A. (2009). Usability study: men need speed. http://www.websiteoptimization.com/speed/tweak/usability-criteria/. Accessed 22 September 2011.

  • Kwek, C. L. (2010). Investigating the shopping orientations on online purchase intention in the e-commerce environment: a Malaysian study. Journal of Internet Banking and Commerce, 15(2), 1–22.

    Google Scholar 

  • Li, N., & Zhang, P. (2005). What makes customers shop online. In J. Fjermestad & N. Romano (Eds.), Customer relationship management (Series of advances in management information systems). Armonk: M.E. Sharpe, Inc.

    Google Scholar 

  • Li, Y. N., Tan, K. C., & Xie, M. (2002). Measuring web-based service quality. Total Quality Management, 13(5), 685–700.

    Google Scholar 

  • Lin, C. S., Tzeng, G. H., Chin, Y. C., & Chang, C. C. (2010). Recommendation sources on the intention to use e-books in academic digital libraries. The Electronic Library, 28(6), 844–857.

    Google Scholar 

  • Lohse, G. L., Bellman, S., & Johnson, E. J. (2000). Consumer buying behavior on the internet: findings from panel data. Journal of Interactive Marketing, 41(1), 15–29.

    Google Scholar 

  • Lorenzo, C., Constantinides, E., & Angel, M. (2009). Effects of web experience factors on virtual retail purchase preferences. International Retail and Marketing Review, 5(1), 1–14.

    Google Scholar 

  • Luo, X., Li, H., Zhang, J., & Shim, J. P. (2010). Examining multi-dimensional trust and multi-faceted risk in initial acceptance of emerging technologies: an empirical study of mobile banking services. Decision Support Systems, 49(2), 222–234.

    Google Scholar 

  • MacCallum, R. (1986). Specification searches in covariance structure modeling. Psychological Bulletin, 100(1), 107–120.

    Google Scholar 

  • Marsh, H. W., & Hocevar, D. (1985). Applications of confirmatory factor analysis to the study of self-concept: first- and higher-order factor models and their invariance across groups. Psychological Bulletin, 97(3), 562–582.

    Google Scholar 

  • Marsh, H. W., & Hocevar, D. (1988). A new more powerful approach to multitrait-multimethod analysis: application of second-order confirmatory analysis. Journal of Applied Psychology, 73(1), 107–117.

    Google Scholar 

  • Matthew, A. (2011). Online consumers are driving economy. http://www.swissinfo.ch/eng/business/Online_consumers_are_driving_economy.html?cid=298661282011.

  • Morganosky, M. A. (1986). Cost- versus convenience- orientated consumers: demographic, lifestyle, and value perspectives. Psychology and Marketing, 3(1), 35–46.

    Google Scholar 

  • Mowen, J. C., & Grove, S. J. (1983). Search behavior, price paid and the consumption other: An equity theory analysis of post-purchase satisfaction. In R. L. Day & H. K. Hunt (Eds.), International fare in consumer satisfaction and complaining behavior (pp. 57–63). Bloomington: Indiana University Press.

    Google Scholar 

  • Mullen, M. R. (1995). Diagnosing measurement equivalence in cross-national research. Journal of International Business Studies, 26(3), 573–596.

    Google Scholar 

  • Mulpuru, S. (2008). US eCommerce forecast: 2008 To 2012. http://www.forrester.com/rb/Research/us_ecommerce_forecast_2008_to_2012/q/id/41592/t/2. Accessed 29 September 2011.

  • Negash, S., Ryan, T., & Igbaria, M. (2003). Quality and effectiveness in web-based customer support systems. Information Management, 40(8), 757–768.

    Google Scholar 

  • O’Cornor, S. J., Shewchuk, R. M., & Carney, L. W. (1994). The great gap. Journal of Health Care Marketing, 14(2), 32–39.

    Google Scholar 

  • Ofir, C., Simonson, I., & Yoon, S. (2009). The robustness of the effects of consumers’ participation in market research: the case of service quality evaluations. Journal of Marketing, 73(6), 105–114.

    Google Scholar 

  • Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1985). A conceptual model of service quality and its implications for future research. Journal of Marketing, 49(4), 41–50.

    Google Scholar 

  • Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1988). SERVQUAL: a multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64(1), 12–40.

    Google Scholar 

  • Parasuraman, A., Berry, L. L., & Zeithaml, V. A. (1991a). Refinement and reassessment of the SERVQUAL scale. Journal of Retailing, 67(4), 420–450.

    Google Scholar 

  • Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1991b). Refinement and reassessment of the SERVQUAL scale. Journal of Retailing, 64(4), 420–450.

    Google Scholar 

  • Parasuraman, A., Berry, L. L., & Zeithaml, V. A. (1993). Research note: more on improving quality measurement. Journal of Retailing, 69(1), 140–147.

    Google Scholar 

  • Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1994). Reassessment of expectations as a comparison standard in measuring service quality: implications for further research. Journal of Marketing, 58(1), 111–124.

    Google Scholar 

  • Park, I., Bhatnagar, A., & Rao, H. R. (2010). Assurance seals, on-line customer satisfaction, and repurchase intention. International Journal of Electronic Commerce, 14(3), 11–34.

    Google Scholar 

  • Reilly, M. D. (1982). Working wives and convenience consumption. Journal of Consumer Research, 8(March), 407–418.

    Google Scholar 

  • Rose, G. M., & Straub, D. (2001). The effect of download time on consumer attitude toward the e-service retailer. e-Service Journal, 1, 55–76.

    Google Scholar 

  • Rose, G. M., Meuter, M. L., & Curran, J. M. (2005). On-line waiting: the role of download time and other important predictors on attitude toward E-retailers. Psychology and Marketing, 22(2), 127–151.

    Google Scholar 

  • Rosenberg, L. J., & Hirschman, E. C. (1980). Retailing without stores. Harvard Business Review, 58(4), 103–112.

    Google Scholar 

  • Sangwan, S., Siguaw, J. A., & Guan, C. (2009). A comparative study of motivational differences for online shopping. ACM SIGMIS Database, 40(4), 28–42.

    Google Scholar 

  • Schaninger, C. M., & Allen, C. T. (1981). Wife’s occupational status as a consumer behavior construct. Journal of Consumer Research, 8(2), 189–196.

    Google Scholar 

  • Schneider, G. P. (2006). Electronic commerce (6th ed.). Boston: Course Technology.

    Google Scholar 

  • Seiders, K., Berry, L. L., & Gresham, L. G. (2000). Attention, retailers! how convenient is your convenience strategy? Sloan Management Review, 41(3), 79–89.

    Google Scholar 

  • Seiders, K., Voss, G. B., Grewal, D., & Godfrey, A. L. (2005). Do satisfied customers buy more? Examining moderating influences in a retailing context. Journal of Marketing, 69(4), 26–43.

    Google Scholar 

  • Seiders, K., Voss, G. B., Godfrey, A. L., & Grewal, D. (2007). SERVCON: development and validation of a multidimensional service convenience scale. Journal of the Academy of Marketing Science, 35(1), 144–156.

    Google Scholar 

  • Szajna, B., & Scamell, R. W. (1993). The effect of information system user expectation on their performance and perceptions. MIS Quarterly, 17(4), 493–516.

    Google Scholar 

  • Tan, K. C., & Kek, S. W. (2004). Service quality in higher education using an enhanced SERVQUAL approach. Quality in Higher Education, 10(1), 17–24.

    Google Scholar 

  • Teas, R. K. (1993a). Consumer expectations and the measurement of perceived service quality. Journal of Professional Services Marketing, 8(2), 33–54.

    Google Scholar 

  • Teas, R. K. (1993b). Expectations, performance evaluation, and consumers’ perceptions of quality. Journal of Marketing, 57(4), 18–34.

    Google Scholar 

  • Teas, R. K. (1994). Expectations as a comparison standard in measuring service quality: an assessment of a reassessment. Journal of Marketing, 58(4), 132–139.

    Google Scholar 

  • Torkzadeh, G., & Dhillon, G. (2002). Measuring factors that influence the success of internet commerce. Information Systems Research, 13(2), 187–120.

    Google Scholar 

  • Tsai, C. H., Chih, W. H., & Hsu, W. L. (2007). Using tam to study the personal motivations and social context factors influence the acceptance of knowledge management systems-based on high technology firms’ samples. Electronic Commerce Studies, 5(1), 81–108.

    Google Scholar 

  • Verhagen, T., Nes, J. G. v., Feldberg, J. F. M., & Dolen, W. M. v. (2011). Virtual customer service agents: using social presence and personalization to shape online service encounters. http://econpapers.repec.org/RePEc:dgr:vuarem:2011–10.

  • Verhoef, P. C., & Langerak, F. (2001). Possible determinants of consumers’ adoption of electronic grocery shopping in Netherland. Journal of Retailing and Consumer Services, 8(5), 275–285.

    Google Scholar 

  • Wang, P. A., & Nyshadham, E. (2011). Knowledge of online security risks and consumer decision making: an experimental study. In 44th Hawaii International Conference on System Sciences. Kauai, Hawaii, 4–7 Jan.: IEEE Society.

  • Watson, R. T., Pitt, L. F., & Kavan, C. B. (1998). Measuring information systems service quality: lessons from two longitudinal case studies. MIS Quarterly, 22(1), 61–79.

    Google Scholar 

  • Wong, L. A., & Fong, V. H. I. (2011). Development and validation of the casino service quality scale: CASERV. International Journal of Hospitality Management, 31(1), 209–217.

    Google Scholar 

  • Xia, L., Kukar-Kinney, M., & Monroe, K. B. (2010). Effects of consumers’ efforts on price and promotion fairness perceptions. Journal of Retailing, 86(1), 1–10.

    Google Scholar 

  • Xie, L., Peng, J., & Shen, W. (2010) Customer’s perceived service convenience and customers’ service evaluations of the bank’s outlets. In 7th International Conference on Service Systems and Service Management (ICSSSM), Tokyo, Japan, Jun 28–30 (pp. 1–6). IEEE Society.

  • Yang, Z., & Jun, M. (2002). Consumer perception of e-service quality: from internet purchaser and non-purchaser perspectives. Journal of Business Strategies, 19(1), 19–41.

    Google Scholar 

  • Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: a means-end model and synthesis of evidence. Journal of Marketing, 52(2), 2–22.

    Google Scholar 

  • Zeithaml, V. A., Parasuraman, A., & Berry, L. L. (1990). Delivering quality service: Balancing customer perceptions and expectations. New York: Free Press.

    Google Scholar 

  • Zo, H., & Ramamurthy, K. (2009). Consumer selection of e-commerce websites in a B2C environment: a discrete decision choice model. System and Humans, IEEE, 39(4), 819–839.

    Google Scholar 

Download references

Acknowledgements

The authors thank the editor and anonymous reviewers for their assistance in editing the paper. Also, the authors would like to thank the National Science Council of Taiwan for financially supporting this research under Contract No.: NSC 99-2416-H-005-039-MY2.

Author information

Authors and Affiliations

  1. Graduate Institute of Technology Management, National Chung Hsing University, No. 250, Kuo Kuang Road, Taichung, 402, Taiwan

    Jung-Yu Lai, Khire Rushikesh Ulhas & Jian-Da Lin

Authors
  1. Jung-Yu Lai
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Khire Rushikesh Ulhas
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jian-Da Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jung-Yu Lai.

Appendices

Appendix A: The initial EC-SERVCON 17-item instrument

1.1 Expected service convenience section

Directions: The purpose of this study is to obtain a better understanding of a customer’s expected and perceived service convenience delivered by e-retailers. There are two sections in this survey. In this expected service convenience section, we would like your opinions on the service convenience delivered by an “excellent” e-retailer. Based on your experiences as an e-shopper, please think about the kind of excellent e-retailer that will deliver excellent service convenience. Please indicate the extent to which you think such an e-retailer will possess the features described by each statement. If you strongly agree that a feature is absolutely essential for an excellent e-retailer, circle 5. Conversely, if you strongly disagree that a feature is essential for an excellent e-retailer, circle 1. If your feeling is less strong, circle one of the numbers in the middle.

figure a

1.2 Perceived service convenience section

Directions: The following statements relate to your feelings about XYZ, an e-retailer you shopped at or experienced. For each statement, please show the extent to which you believe your e-retailer XYZ has the features described by the statement. Once again, circling 5 means that you strongly agree, and circling 1 means that you strongly disagree. You may circle any of the numbers in the middle that show how strong your feelings are.

figure b

Appendix B: Nomological validity measurement items

Product category involvement

PCI1.

I have a strong personal interest in e-stores like XYZ.

1

2

3

4

5

PCI2.

E-stores like XYZ are very important to me.

1

2

3

4

5

Satisfaction

SAT1.

Overall, I am very pleased with the service at XYZ.

1

2

3

4

5

SAT2.

Overall, shopping at XYZ is a delightful experience.

1

2

3

4

5

SAT3

Overall, I am very satisfied with the XYZ shopping experience.

1

2

3

4

5

Re-purchase

RP1.

After purchase at XYZ, I will re-visit it in the future.

1

2

3

4

5

RP2.

After purchase at XYZ, I will continuously shop at it in the future.

1

2

3

4

5

RP3.

After purchase at XYZ, I will purchase more products from XYZ in the future.

1

2

3

4

5

Recommendation to others

O1.

I will recommend others to shop at XYZ.

1

2

3

4

5

O2.

I will encourage others to shop at XYZ.

1

2

3

4

5

Appendix C: Original SERVCON instrument (Seiders et al. 2007)

Decision

P1.

I can easily determine prior to shopping whether SR will offer what I need.

P2.

Deciding to shop at SR is quick and easy.

P3

I can quickly find information before I shop to decide if SR has what I’m looking for.

Access

P4.

I am able to get to SR quickly and easily.

P5.

SR offers convenient parking.

P6.

SR offers convenient locations.

P7.

SR offers convenient store hours.

Transaction

P8.

SR makes it easy for me to conclude my transaction.

P9.

I am able to complete my purchase quickly at SR.

P10.

It takes little time to pay for my purchase at SR.

Benefit

P11.

The merchandise I want at SR can be located quickly.*

P12.

It is easy to find the products I am looking for at SR.

P13.

I can easily get product advice at SR.

P14.

It is easy to evaluate the merchandise at SR.

Post-benefit

P15.

It is easy to take care of returns and exchanges at SR.*

P16.

SR takes care of product exchanges and returns promptly.

P17.

Any after-purchase problems I experience are quickly resolved at SR.

*SR: specialty retailer’s brand name

Rights and permissions

Reprints and permissions

About this article

Cite this article

Lai, JY., Ulhas, K.R. & Lin, JD. Assessing and managing e-commerce service convenience. Inf Syst Front 16, 273–289 (2014). https://doi.org/10.1007/s10796-012-9344-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10796-012-9344-2

Keywords

Search

Navigation