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Designing adaptive feedback mechanisms with text mining capabilities: An illustration on eBay

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Abstract

This research looks at current feedback mechanisms design at an electronic marketplace, notices the shortcomings of underutilized feedback comments, and proposes an alternative design that uses text mining to reveal latent service quality/customer satisfaction dimensions, otherwise potentially unnoticed. We observed the rigidity of many feedback mechanisms that confine users to leave feedback on a narrow palette of options, and we used adaptability theory principles to propose the design of a new feedback mechanism. The proposed feedback mechanism design draws on three studies: (1) the first study shows that feedback comments contain unobserved dynamically latent service quality/customer satisfaction dimensions, (2) the second study shows that some of the dynamically latent service quality/customer satisfaction dimensions are more important than the rigid a priori service quality/customer satisfaction dimensions existent at current electronic marketplaces, and (3) the third study shows that, when revealed, extracted service quality/customer satisfaction dimensions have the potential to change behavioral intentions formed on rigid a priori established service quality/customer satisfaction dimensions. We conclude our research by providing steps on how to implement an adaptive feedback mechanism using text mining.

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References

  • Aalst, W., & Kumar, A. (2003). XML-based schema definition for support of interorganizational workflow. Information Systems Research, 14(1), 23–46. https://doi.org/10.1287/isre.14.1.23.14768

  • Adam, M., Gregor, S., Hevner, A., & Morana, S. (2021). Design science research modes in human-computer interaction projects. AIS Transactions on Human-Computer Interaction, 13(1), 1–11. https://doi.org/10.17705/1thci.00139

    Article  Google Scholar 

  • Adomavicius, G., Gupta, A., & Yang, M. (2019). Designing real-time feedback for bidders in homogeneous-item continuous combinatorial auctions. MIS Quarterly, 43(3), 721–A11. https://doi.org/10.25300/MISQ/2019/14974

    Article  Google Scholar 

  • Almaliki, M., Ncube, C., & Ali, R. (2014). The design of adaptive acquisition of users feedback: An empirical study. IEEE Eighth International Conference on Research Challenges in Information Science, 2014, 1–12.

    Google Scholar 

  • Alter, S. (2014). The concept of “IT artifact” has outlived its usefulness and should be retired now. Information Systems Journal, 25(1), 47–60. https://doi.org/10.1111/isj.12048

  • Ba, S., & Pavlou, P. A. (2002). Evidence of the effect of trust building technology in electronic markets: Price premium and buyer behavior. MIS Quarterly, 26(3), 243–268. https://doi.org/10.2307/4132332

  • Baskerville, R., Baiyere, A., Gregor, S., Hevner, A., & Rossi, M. (2018). Design Science Research Contributions: Finding a Balance between Artifact and Theory. Journal of the Association for Information Systems, 19(5), 358–376. https://doi.org/10.17705/1jais.00495

  • Bauer, I., Parra-Moyano, J., Schmedders, K., & Schwabe, G. (2022). Multi-party certification on blockchain and its impact in the market for lemons. Journal of Management Information Systems, 39(2), 395–425. https://doi.org/10.1080/07421222.2022.2063555

    Article  Google Scholar 

  • Benbasat, I., & Zmud, R. W. (2003). The identity crisis within the is discipline: Defining and communicating the discipline’s core properties. MIS Quarterly, 27(2), 183–194. https://doi.org/10.2307/30036527

  • Benkler, Y. (2002). Coase’s penguin, or, linux and “the nature of the firm.” The Yale Law Journal, 112(3), 369. https://doi.org/10.2307/1562247

    Article  Google Scholar 

  • Berry, W., Dumais, S., & O’Brien, G. (1995). Using linear algebra for intelligent information retrieval. SIAM Review, 37(4), 573–595. https://doi.org/10.1177/002224299405800408

  • Bitner, M. J., Booms, B. H., & Mohr, L. A. (1994). Critical service encounters: The employee’s viewpoint. Journal of Marketing, 58, 95–104. https://doi.org/10.1177/002224299405800408

    Article  Google Scholar 

  • Brady, M. K., & Robertson, C. J. (2001). Searching for a consensus on the antecedent role of service quality and satisfaction: An exploratory cross-national study. Journal of Business Research, 51, 53–60. https://doi.org/10.1016/S0148-2963(99)00041-7

  • Cao, Q., Duan, W., & Gan, Q. (2011). Exploring determinants of voting for the “helpfulness” of online user reviews: A text mining approach. Decsion Support Systems, 50(2), 511–521. https://doi.org/10.1016/j.dss.2010.11.009

  • Chau, M., Li, W., Yang, B., Lee, A., & Bao, Z. (2021). Incorporating the time–order effect of feedback in online auction markets through a Bayesian updating model. MIS Quarterly, 45(2), 985–1006. https://doi.org/10.25300/MISQ/2021/15324

    Article  Google Scholar 

  • Chen, P. Y., Yoon, J., & WU, S. (2004). The impact of online recommendations and consumer feedback on sales. 711-724. Paper presented at International Conference on Information Systems, ICIS 2004, Washington, United States.

  • Cheung, C. M., & Lee, M. K. (2012). What drives consumers to spread electronic word of mouth in online consumer-opinion platforms. Decision Support Systems, 53(1), 218–225. https://doi.org/10.1016/j.dss.2012.01.015

  • Chia, K., Hsu, C., Lin, L., & Tseng, H. H. (2021). The identification of ideal social media influencers: Integrating the social capital, social exchange and social learning theories. Journal of Electronic Commerce Research, 22(1), 4–21.

  • Clemons, E. (2007). An empirical investigation of third-party seller rating systems in E-commerce: The case of buySAFE. Journal of Management Information Systems, 24(2), 43–71. https://doi.org/10.2753/MIS0742-1222240203

  • Coase, R. H. (1937). The nature of the firm. Economica, 4(16), 386–405. https://doi.org/10.2307/2626876

    Article  Google Scholar 

  • Conrad, M. (1983). Adaptability. Springer, US. https://doi.org/10.1007/978-1-4615-8327-1

    Article  Google Scholar 

  • Conrad, M. (2007). Adaptability theory as a guide for interfacing-computers and human society. Systems Research, 10(4), 1–23. https://doi.org/10.1002/sres.3850100402

  • Cronin, J. J., & Taylor, S. A. (1992). Measuring service quality: A reexamination and extension. Journal of Marketing, 56(3), 55. https://doi.org/10.1177/002224299205600304

  • Cross, N. (2001). Designerly ways of knowing: Design discipline versus design science. Design Issues, 17(3), 49–55. https://doi.org/10.1007/1-84628-301-9_1

  • Dellarocas, C., Dini, F., & Spagnolo, G. (2006). Designing reputation (feedback) mechanisms. In N. Dimitri, G. Piga, & G. Spagnolo (Eds.), Handbook of procurement. Cambridge University.

  • Dellarocas, C. (2003) The Digitization of Word of Mouth: Promise and Challenges of Online Feedback Mechanisms. Management Science, 49(10), 1407–1424. https://doi.org/10.1287/mnsc.49.10.1407.17308

  • DeLone, W. H., & McLean, E. R. (2004). Measuring e-Commerce success: Applying the DeLone & McLean information systems success model. International Journal of Electronic Commerce, 9(1), 31–47. https://doi.org/10.1080/10864415.2004.11044317

  • DeSanctis, G. (2003). The social life of information systems research. Journal of the Association of Information Systems, 4(7), 360–376. https://doi.org/10.17705/1jais.00043

  • Dimoka, A., Hong, Y., & Pavlou, P. A. (2012). On product uncertainty in online markets: Theory and evidence. MIS Quarterly, 36, 1–32. https://doi.org/10.2307/41703461

  • Drechsler, A. & Hevner, A. R. (2018). Utilizing, producing, and contributing design knowledge in DSR projects. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (10844 LNCS pp. 82–97). Springer International Publishing. https://doi.org/10.1007/978-3-319-91800-6_6

  • Dumais, T. (1991). Improving the retrieval of information from external sources. Behaviour Research Methods, 23(2), 229–236. https://doi.org/10.3758/BF03203370

  • eBay. (2024). eBay Feedback Profile. ebay Customer Service 06/20/2024. https://www.ebay.com/help/account/changing-account-settings/feedback-profiles?id=4204

  • Evangelopoulos, N., & Visinescu, L. (2012). Text-mining the voice of the people. Communications of the ACM, 55(2), 62–69.

  • Evangelopoulos, N., Zhang, X., & Prybutok, V. R. (2012). Latent Semantic Analysis: five methodological recommendations. European Journal of Information Systems, 21(1), 70–86. https://doi.org/10.1057/ejis.2010.61

  • Foltz, W., Kintsch, W., & Landauer, K. (1998). Analysis of text coherence using latent semantic analysis. Discourse Processes, 25, 285–307. https://doi.org/10.1080/01638539809545029

  • Forman, C., Ghose, A., & Wiesenfeld, B. (2008). Examining the relationship between reviews and sales: The role of reviewer identity disclosure in electronic markets. Information Systems Research, 19(3), 291–313. https://doi.org/10.1287/isre.1080.0193

  • Gai, T., Cao, M., Chiclana, F., Wu, J., Liang, C., & Herrera-Viedma, E. (2022). A decentralized feedback mechanism with compromise behavior for large-scale group consensus reaching process with application in smart logistics supplier selection. Expert Systems with Applications, 204, 117547. https://doi.org/10.1016/j.eswa.2022.117547

    Article  Google Scholar 

  • Gavish, B., & Gerdes, J. H. (1998). Anonymous mechanisms in group decision support systems communication. Decision Support Systems, 23(4), 297–328. https://doi.org/10.1016/S0167-9236(98)00057-8

  • Gefen, D. (2002). Customer loyalty in E-commerce. Journal of the Association for Information Systems, 3, 27–51.

  • Ghose, A., & Ipeirotis, P. G. (2011). Estimating the helpfulness and economic impact of product reviews: Mining text and reviewer characteristics. IEEE Transactions on Knowledge and Data Engineering, 23(10), 1498–1512. https://doi.org/10.1109/TKDE.2010.188

  • Ghose, A., Ipeirotis, P. G., & Sundararajan, A. (2014). The dimensions of reputation in electronic markets. NYU Center for Digital Economy Research Working Paper, CeDER-06–02.

  • Ghose, A. (2009). Internet exchanges for used goods: an empirical analysis of trade patterns and adverse selection. MIS Quarterly, 33(2), 263–291. https://doi.org/10.2307/20650292

  • Godin, M. (2017). Everything We did to Increase Our eBay Feedback and win more sales. Retrieved 06/20/2023. https://crazylister.com/blog/improve-ebay-feedback/

  • Gregor, S., & Hevner, A. R. (2013). Positioning and presenting design science research for maximum impact. MIS Quarterly, 37(2), 337–355. https://www.jstor.org/stable/43825912

  • Hesse, M., & Teubner, T. (2020). Reputation portability – quo vadis? Electronic Markets, 30(2), 331–349. https://doi.org/10.1007/s12525-019-00367-6

    Article  Google Scholar 

  • Hevner, A., March, S., Park, J., & Ram, S. (2004). Design science in information systems research. MIS Quarterly, 28(1), 75–105. https://doi.org/10.2307/25148625

  • Huang, Q., Davison, R. M., & Liu, H. (2014). An exploratory study of buyers’ participation intentions in reputation systems: The relationship quality perspective. Information & Management, 51(8), 952–963. https://doi.org/10.1016/j.im.2014.09.003

    Article  Google Scholar 

  • Huang, N., Burtch, G., Gu, B., Hong, Y., Liang, C., Wang, K., Fu, D., & Yang, B. (2019). Motivating user-generated content with performance feedback: Evidence from randomized field experiments. Management Science, 65(1), 327–345. https://doi.org/10.1287/mnsc.2017.2944

    Article  Google Scholar 

  • Huang, E. Y., Lin, S.-C., & Hsieh, I.-T. (2023). Online marketplace sellers’ influence on rating scores and comment orientation. Electronic Commerce Research, 23(2), 1241–1270. https://doi.org/10.1007/s10660-021-09511-x

    Article  Google Scholar 

  • Huifang, L., Yulin, F., Youwei, W., Kai, H. L., & Liang, L. (2015). Are all signals equal? Investigating the differential effects of online signals on the sales performance of e-marketplace sellers. Information Technology & People, 28(3), 699–723. https://doi.org/10.1108/ITP-11-2014-0265

  • Iivari, J. (2016). Information system artefact or information system application: That is the question. Information Systems Journal, 27(6), 753–774. https://doi.org/10.1111/isj.12121

  • Indulska, M., Hovorka, D. S., & Recker, J. (2012). Quantitative approaches to content analysis: identifying conceptual drift across publication outlets. European Journal of Information Systems, 21(1), 49–69. https://doi.org/10.1057/ejis.2011.37

  • James, T. L., Calderon, E. D., & Cook, D. F. (2017). Exploring patient perceptions of healthcare service quality through analysis of unstructured feedback. Expert Systems with Applications, 71, 479–492. https://doi.org/10.1016/j.eswa.2016.11.004

  • Jang, W., Kim, J., & Park, Y. (2014). Why the online customer reviews are inconsistent? Textual review vs. scoring review. In P. Benghozi, D. Krob, A. Lonjon, & H. Panetto (Eds.), Digital enterprise design & management. Advances in Intelligent Systems and Computing (Vol. 261, p. 151). Springer.

  • Josang, A., Ismail, R., & Boyd, C. (2007). A survey of trust and reputation systems for online service provision. Decision Support Systems, 43(2), 618–644. https://doi.org/10.1016/j.dss.2005.05.019

  • Kozlowski, S. W. J., Toney, R. J., Mullins, M. E., Weissbein, D. A., Brown, K. G., & Bell, B. S. (2001). 2. Developing adaptability: A theory for the design of integrated-embedded training systems. In Advances in human performance and cognitive engineering research (Vol. 1, pp. 59–123). Emerald (MCB UP ). https://doi.org/10.1016/S1479-3601(01)01004-9

  • Kuechler, W. (2007). Business applications of unstructured text. Communications of the ACM, 50(10), 86–93.

  • Kumar, C., & Chowdary, C. R. (2023). A study on the role of uninterested items in group recommendations. Electronic Commerce Research, 23(4), 2073–2099. https://doi.org/10.1007/s10660-021-09526-4

    Article  Google Scholar 

  • Lackermair, G., Kailer, D., & Kanmaz, K. (2013). Importance of online product reviews from a consumer’s perspective. Advances in Economics and Business, 1(1), 1–5. https://doi.org/10.13189/aeb.2013.010101

  • Lallana, E., Quimbo, R., & Andam, Z. R. (2000). ePrimer: An Introduction to eCommerce 2 (Philippines: DAI-AGILE, 2000), United Nations Development Program Report.

  • Landauer, K. T. (2002). On the computational basis of learning and cognition: Arguments from LSA. Psychology of Learning and Motivation, 41, 43–84. https://doi.org/10.1016/S0079-7421(02)80004-4

  • Larsen, K. R., & Bong, C. H. (2016). A tool for addressing construct identity in literature reviews and meta-analyses. MIS Quarterly, 40(3), 1–23. https://www.jstor.org/stable/26629026

  • Larsen, K. R., & Monarchi, D. E. (2004). A mathematical approach to categorization and labeling of quantitative data: The latent categorization method. Sociological Methodology, 34(1), 349–392. https://doi.org/10.1111/j.0081-1750.2004.00156.x

  • Lee, G., & Lin, H. (2005). Customer perceptions of e-service quality in online shopping. International Journal of Retail & Distribution Management, 33(2), 161–176. https://doi.org/10.1108/09590550510581485

    Article  Google Scholar 

  • Lee, H. G. (1998). Do electronic marketplaces lower the price of goods? Communications of the ACM, 41(1), 73–80. https://doi.org/10.1145/268092.268122

  • Liang, T.-P., & Huang, J.-S. (1998). An empirical study on consumer acceptance of products in electronic markets: A transaction cost model. Decision Support Systems, 24(1), 29–43. https://doi.org/10.1016/S0167-9236(98)00061-X

    Article  Google Scholar 

  • Loiacono, E. T. (2000). WebQual™: A Web site quality instrument, Dissertations & Theses, 24. https://www.proquest.com/dissertations-theses/webqual™-web-site-quality-instrument/docview/304593400/se-2

  • Luca, M. (2017). Designing online marketplaces: Trust and reputation mechanisms. Innovation Policy and the Economy, 17, 77–93. https://doi.org/10.1086/688845

    Article  Google Scholar 

  • Makino, S., Hashimoto, K., & Gold, P. W. (2002). Multiple feedback mechanisms activating corticotropin-releasing hormone system in the brain during stress. Pharmacology Biochemistry and Behavior, 73(1), 147–158. https://doi.org/10.1016/S0091-3057(02)00791-8

  • Markey, R., Reichheld, F., & Dullweber, A. (2009). Closing the customer feedback loop. Harvard Business Review, 87(12), 43–47.

  • McKay, J., Marshall, P., & Hirschheim, R. (2012). The design construct in information systems design science. Journal of Information Technology, 27(2), 125–139. https://doi.org/10.1057/jit.2012.5

  • Merton, K. (2022). The World’s Top Online Marketplaces 2022. WebRetailer Retrieved 09/12/2022. https://www.webretailer.com/b/online-marketplaces/

  • Miller, G. A. (1956). The magical number seven, plus minus two: Some limits on our capacity for processing information. The Psychological Review, 63, 81–97. https://doi.org/10.1037/h0043158

  • Mou, J., Ren, G., Qin, C., & Kurcz, K. (2019). Understanding the topics of export cross-border e-commerce consumers feedback: An LDA approach. Electronic Commerce Research, 19(4), 749–777. https://doi.org/10.1007/s10660-019-09338-7

    Article  Google Scholar 

  • Mudambi, S. M., Schuff, D., & Zhang, Z. (2014). Why aren’t the stars aligned? An analysis of online review content and star ratings. Hawaii International Conference on System Sciences (HICSS), 2014 47th, 3139–3147. https://doi.org/10.1109/HICSS.2014.389

  • Nayyar, P. R. (1990). Information asymmetries: A source of competitive advantage for diversified service firms. Strategic Management Journal, 11, 513–519. https://doi.org/10.1002/smj.4250110703

  • Orlikowsky, W. J., & Iacono, C. S. (2001). Research commentary: Desperately seeking the “IT” in IT research—A Call to theorizing the IT artifact. Information Systems Research, 12(2), 121–222.

  • Parasuraman, A., Zeithaml, V. A., & Malhotra, A. (2005). E-S-QUAL a multiple-item scale for assessing electronic service quality. Journal of Service Research, 7(3), 213–233. https://doi.org/10.1177/1094670504271156

  • Pavlou, P., & Dimoka, A. (2006). The nature and role of feedback text comments in online marketplaces: Implications for trust building, price premiums, and seller differentiation. Information Systems Research, 17(4), 392–414. https://doi.org/10.1287/isre.1060.0106

  • Pavlou, P., & Gefen, D. (2004). Building effective online marketplaces with institution-based trust. Information Systems Research, 15(1), 37–59. https://doi.org/10.1287/isre.1040.0015

  • Pavlou, P., & Gefen, D. (2005). Psychological contract violation in online marketplaces: Antecedents, consequences, and moderating role. Information Systems Research, 16(4), 372–399. https://doi.org/10.1287/isre.1050.0065

  • Pillet, J. C., Pigni, F., & Vitari, C. (2017). Learning about ambiguous technologies: Conceptualization and research agenda. 25th European Conference on Information Systems (ECIS) (pp. 674–690).

  • Pool, J. (2023). The world’s top online marketplaces 2023. Webretailer Retrieved 08/08/2023. https://www.webretailer.com/marketplaces-worldwide/online-marketplaces

  • Rindfleisch, A. (2020). Transaction cost theory: Past, present and future. AMS Review, 10(1–2), 85–97. https://doi.org/10.1007/s13162-019-00151-x

    Article  Google Scholar 

  • Rita, P., Oliveira, T., & Farisa, A. (2019). The impact of e-service quality and customer satisfaction on customer behavior in online shopping. Heliyon, 5(10), e02690. https://doi.org/10.1016/j.heliyon.2019.e02690

    Article  Google Scholar 

  • SAS Institute Inc. (2012). Getting Started with SAS® Text Miner 12.1. SAS Institute Inc., Cary, NC, USA.

  • Sampson, S. E. (1996). Ramifications of monitoring service quality through passively solicited customer feedback. Decison Sciences, 27(4), 601–622. https://doi.org/10.1111/j.1540-5915.1996.tb01828.x

  • Shao, Z., Li, X., Guo, Y., & Zhang, L. (2020). Influence of service quality in sharing economy: Understanding customers’ continuance intention of bicycle sharing. Electronic Commerce Research and Applications, 40, 100944. https://doi.org/10.1016/j.elerap.2020.100944

    Article  Google Scholar 

  • Simon, H. A. (1988). The science of design: Creating the artificial. Design Issues, 4(1/2), 67–82.

    Article  Google Scholar 

  • Simon, H. A. (1996). The Sciences of the Artificial (3rd ed.). MIT Press. Cambridge, Massachusetts, London, England.

  • Soleimani, M. (2022). Buyers’ trust and mistrust in e-commerce platforms: A synthesizing literature review. Information Systems and E-Business Management, 20(1), 57–78. https://doi.org/10.1007/s10257-021-00545-0

    Article  Google Scholar 

  • Standage, T. (1998). The victorian internet: The remarkable story of the telegraph and the nineteenth century’s on-line pioneers, Bloomsbury New York, USA.

  • Steur, A. J., & Seiter, M. (2021). Properties of feedback mechanisms on digital platforms: An exploratory study. Journal of Business Economics, 91(4), 479–526. https://doi.org/10.1007/s11573-020-01009-6

    Article  Google Scholar 

  • Taherdoost, H. (2023). E-Business Essentials: Building a successful online enterprise. Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-39626-7

  • Thoms, B. (2011). A dynamic social feedback system to support learning and social interaction in higher education. IEEE Transactions on Learning Technologies, 4(4), 340–352. https://doi.org/10.1109/TLT.2011.9

  • Tirunillai, S., & Tellis, G. J. (2014). Mining marketing meaning from online chatter: Strategic brand analysis of big data using latent Dirichlet allocation. Journal of Marketing Research, 51(4), 463–479. https://doi.org/10.1509/jmr.12.0106

  • Tong, Y., Wang, X., Tan, C.-H., & Teo, H.-H. (2013). An empirical study of information contribution to online feedback systems: A motivation perspective. Information & Management, 70(7), 562–570. https://doi.org/10.1016/j.im.2013.02.009

  • Vasilyeva, E., Pechenizkiy, M., & De Bra, P. M. E. (2007). Adaptation of feedback in e-learning systems at individual and group level. In P. Brusilovsky, M. Grigoriadou, & K. Papanikolou (Eds.), Proceedings of the Workshop on Personalisation in E-Learning Environments at Individual and Group Level (PING 2007, in conjunction with the 11th International Conference on User Modeling), June 25-29 2007, Corfu, Greece (pp. 49–56). University of Athens.

  • Visinescu, L. L., & Evangelopoulos, N. (2014). Orthogonal rotations in latent semantic analysis: An empirical study. Decision Support Systems, 62, 131–143. https://doi.org/10.1016/j.dss.2014.03.010

    Article  Google Scholar 

  • vom Brocke, J., Winter, R., University of St. Gallen, Switzerland, Hevner, A., University of South Florida, USA, Maedche, A., & Karlsruhe Institute of Technology, Germany. (2020). Special issue editorial –Accumulation and evolution of design knowledge in design science research: A journey through time and space. Journal of the Association for Information Systems, 21(3), 520–544. https://doi.org/10.17705/1jais.00611

  • Wareham, J., Zheng, J. G., & Straub, D. (2005). Critical themes in electronic commerce research: A meta-analysis. Journal of Information Technology, 20(1), 1–19. https://doi.org/10.1057/palgrave.jit.2000034

  • Wei, K., Li, Y., Zha, Y., & Ma, J. (2018). Trust, risk and transaction intention in consumer-to-consumer e-marketplaces: An empirical comparison between buyers’ and sellers’ perspectives. Industrial Management & Data Systems, 119(2), 331–350. https://doi.org/10.1108/IMDS-10-2017-0489

    Article  Google Scholar 

  • Wells, J. D., Valacich, J. S., & Hess, T. J. (2011). What signals are you sending? How website quality influences perceptions of product quality and purchase intentions. MIS Quarterly, 35(2), 373–396. https://doi.org/10.2307/23044048

  • Whinston, A. B., & Xianjun, G. (2004). Operationalizing the essential role of the information technology artifact in information systems research: Gray area, pitfalls, and the importance of strategic ambiguity. MIS Quarterly, 28(2), 149–159. https://doi.org/10.2307/25148631

  • Wild, F. (2022). lsa: Latent Semantic Analysis. Retrieved from https://CRAN.R-project.org/package=lsa

  • Williamson, O. E. (1981). The economics of organization: The transaction cost approach. American Journal of Sociology, 87(3), 548–577. https://doi.org/10.1086/227496

    Article  Google Scholar 

  • Wolfinbarger, M. F., & Gilly, M. C. (2001). Shopping online for freedom, control and fun. California Management Review, 43(2), 34–55. https://doi.org/10.2307/41166074

  • Wolfinbarger, M., & Gilly, M. C. (2003). eTailQ: dimensionalizing, measuring and predicting etail quality. Journal of Retailing, 79, 183–198. https://doi.org/10.1016/S0022-4359(03)00034-4

  • Wu, P. H., Huang, G. J., Milrad, M., Ke, H. R., & Huang, Y. M. (2011). An innovative concept map approach for improving students’ learning performance with an instant feedback mechanism. British Journal of Educational Technoogy, 43(2), 217–232. https://doi.org/10.1111/j.1467-8535.2010.01167.x

  • Ye, S., Gao, G. (Gordon), & Viswanathan, S. (2014). Strategic behavior in online reputation systems: Evidence from revoking on eBay. MIS Quarterly, 38(4), 1033–1056. https://doi.org/10.25300/MISQ/2014/38.4.05

  • Zeithaml, V. A., Parasuraman, A., & Malhorta, A. (2002). Service quality delivery through web sites: A critical review of extant knowledge. Journal of the Academy of Marketing Science, 30(4), 362–375. https://doi.org/10.1177/009207002236911

  • Zhang, P., Scialdone, M., & Ku, M. C. (2011). IT artifacts and the state of IS research. International Conference on Information Systems 2011, ICIS 2011, 5, 4369–4382. https://aisel.aisnet.org/icis2011/proceedings/generaltopics/14

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  1. Texas State University, 601 University Drive, San Marcos, TX, 78666-4684, USA

    Lucian Visinescu

  2. 7-Eleven Inc, Dallas/Fort Worth, TX, USA

    Nicholas Evangelopoulos

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  1. Lucian Visinescu
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  2. Nicholas Evangelopoulos
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Correspondence to Lucian Visinescu.

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Visinescu, L., Evangelopoulos, N. Designing adaptive feedback mechanisms with text mining capabilities: An illustration on eBay. Electron Markets 34, 40 (2024). https://doi.org/10.1007/s12525-024-00719-x

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