Design is More Than Looks: Research on the Affordance of Review Components on Consumer Loyalty

References

• Guthrie C, Fosso-Wamba S, Arnaud JB. Online consumer resilience during a pandemic: An exploratory study of e-commerce behavior before, during and after a COVID-19 lockdown. J Retail Consum Serv. 2021;61(7):102570. doi:10.1016/j.jretconser.2021.102570
   Web of Science ®Google Scholar
• Wang HP, Du R, Li J, Fan WG. Subdivided or aggregated online review systems: which is better for online takeaway vendors? Electron Commer Res. 2020;20(4):915–944. doi:10.1007/s10660-018-9314-y
   Web of Science ®Google Scholar
• Lei F, Wei GW, Chen XD. Model-based evaluation for online shopping platform with probabilistic double hierarchy linguistic CODAS method. Int J Intell Syst. 2021;36(9):5339–5358. doi:10.1002/int.22514
   Web of Science ®Google Scholar
• Gibson JJ. The theory of affordances. Hilldale. 1977;1(2):67–82.
   Google Scholar
• Amazon.com, Wet n wild Disney lilo and stitch makeup set collection https://www.amazon.com/Wild-Disney-Stitch-Makeup-Collection/dp/B0B3C4DP88 Accessed 19 June 2022
   Google Scholar
• Dhaoui C, Webster CM. Brand and consumer engagement behaviors on Facebook brand pages: let’s have a (positive) conversation. Int J Res Mark. 2021;38(1):155–175. doi:10.1016/j.ijresmar.2020.06.005
   Web of Science ®Google Scholar
• Kuan KKY, Hui KL, Prasarnphanich P, Lai HY. What makes a review voted? An empirical investigation of review voting in online review systems. J Assoc Inf Syst. 2015;16(1):48–71 doi:10.17705/1jais.00386.
   Web of Science ®Google Scholar
• Pumawirawan N, Eisend M, De Pelsmacker P, Dens N. A meta-analytic investigation of the role of valence in online reviews. J Interact Mark. 2015;31:17–27. doi:10.1016/j.intmar.2015.05.001
   Web of Science ®Google Scholar
• Dong XY, Wang TN. Social tie formation in Chinese online social commerce: the role of IT affordances. Int J Inform Manage. 2018;42:49–64. doi:10.1016/j.ijinfomgt.2018.06.002
   Web of Science ®Google Scholar
• Lysonski S, Durvasula S, Zotos Y. Consumer decision-making styles: a multi-country investigation. Eur J Mark. 1996;30(12):10–21. doi:10.1108/03090569610153273
   Google Scholar
• Mitra S, Jenamani M. OBIM: a computational model to estimate brand image from online consumer review. J Bus Res. 2020;114:213–226. doi:10.1016/j.jbusres.2020.04.003
   Web of Science ®Google Scholar
• Karimi S, Wang F. Online review helpfulness: impact of reviewer profile image. Decis Support Syst. 2017;96:39–48. doi:10.1016/j.dss.2017.02.001
   Web of Science ®Google Scholar
• Davis FD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 1989;13:319–340. doi:10.2307/249008
   Web of Science ®Google Scholar
• Donovan RJ, Rossiter JR, Marcoolyn G, Nesdale A. Store atmosphere and purchasing behavior. J Retailing. 1994;70(3):283–294 doi:10.1016/0022-4359(94)90037-X
   Web of Science ®Google Scholar
• Eroglu SA, Machleit KA, Davis LM. Atmospheric qualities of online retailing - A conceptual model and implications. J Bus Res. 2001;54(2):177–184. doi:10.1016/S0148-2963(99)00087-9
   Web of Science ®Google Scholar
• Eroglu SA, Machleit KA, Davis LM. Empirical testing of a model of online store atmospherics and shopper responses. Psychol Market. 2003;20(2):139–150. doi:10.1002/mar.10064
   Web of Science ®Google Scholar
• Floh A, Madlberger M. The role of atmospheric cues in online impulse-buying behavior. Electron Commer R A. 2013;12(6):425–439. doi:10.1016/j.elerap.2013.06.001
   Web of Science ®Google Scholar
• Lorenzo-Romero C, Alarcon-del-Amo MD, Gomez-Borjal MA. Analyzing the user behavior toward electronic commerce stimuli. Front Behav Neurosci. 2016;10:224. doi:10.3389/fnbeh.2016.00224
   PubMed Web of Science ®Google Scholar
• Lin JB, Luo ZM, Cheng XS, Li L. Understanding the interplay of social commerce affordances and swift guanxi: an empirical study. Inform Manage-Amster. 2019;56(2):213–224. doi:10.1016/j.im.2018.05.009
   Web of Science ®Google Scholar
• Volkoff O, Strong DM. Critical realism and affordances: theorizing it-associated organizational change processes. MIS Q. 2013;37(3):819–834. doi:10.25300/MISQ/2013/37.3.07
   Web of Science ®Google Scholar
• Leonardi PM. When does technology use enable network change in organizations? A comparative study of feature use and shared affordances. MIS Quarterly. 2013;37(3):749–775. doi:10.25300/MISQ/2013/37.3.04
   Web of Science ®Google Scholar
• Hutchby I. Technologies, texts and affordances. Sociology. 2001;35(2):441–456. doi:10.1177/S0038038501000219
   Google Scholar
• Koroleva K, Kane GC. Relational affordances of information processing on Facebook. Inform Manage-Amster. 2017;54(5):560–572. doi:10.1016/j.im.2016.11.007
   Web of Science ®Google Scholar
• Faraj S, Jarvenpaa SL, Majchrzak A. Knowledge collaboration in online communities. Organ Sci. 2011;22(5):1224–1239. doi:10.1287/orsc.1100.0614
   Web of Science ®Google Scholar
• Treem JW, Leonardi PM. Social media use in organizations: exploring the affordances of visibility, editability, persistence, and association. Ann Int Commun Assoc. 2013;36(1):143–189 doi:10.1080/23808985.2013.11679130.
   Google Scholar
• Majchrzak A, Faraj S, Kane GC, Azad B. The contradictory influence of social media affordances on online communal knowledge sharing. J Comput-Mediat Comm. 2013;19(1):38–55. doi:10.1111/jcc4.12030
   Web of Science ®Google Scholar
• Sutherland W, Jarrahi MH. The sharing economy and digital platforms: a review and research agenda. Int J Inform Manage. 2018;43:328–341. doi:10.1016/j.ijinfomgt.2018.07.004
   Web of Science ®Google Scholar
• De Rivera J, Gordo Á, Cassidy P, Apesteguía A. A netnographic study of P2P collaborative consumption platforms’ user interface and design. Environ Innov Soc Tr. 2017;23:11–27. doi:10.1016/j.eist.2016.09.003
   Web of Science ®Google Scholar
• Califf CB, Brooks S, Longstreet P. Human-like and system-like trust in the sharing economy: the role of context and humanness. Technol Forecast Soc. 2020;154:119968. doi:10.1016/j.techfore.2020.119968
   Web of Science ®Google Scholar
• Yang W, Liu Y. Research on purchase intention of fresh agricultural products based on TAM model in pre-sale mode. Proceedings of the 2nd International Conference on E-Commerce and Internet Technology. Hangzhou, China; 2021.
   Google Scholar
• Pozzi G, Pigni F, Vitari C. Affordance theory in the IS discipline: a review and synthesis of the literature. Proceedings of AMCIS Savannah, GA, USA. ; 2014.
   Google Scholar
• Huang LY, Hsieh YJ. Predicting online game loyalty based on need gratification and experiential motives. Internet Res. 2011;21(5):581–598. doi:10.1108/10662241111176380
   Web of Science ®Google Scholar
• Novak TP, Hoffman DL, Yung Y-F. Measuring the customer experience in online environments: a structural modeling approach. Market Sci. 2000;19(1):22–42. doi:10.1287/mksc.19.1.22.15184
   Web of Science ®Google Scholar
• Liaw -S-S, Huang H-M. An investigation of user attitudes toward search engines as an information retrieval tool. Comput Hum Behav. 2003;19(6):751–765. doi:10.1016/S0747-5632(03)00009-8
   Web of Science ®Google Scholar
• Kandampully J, Suhartanto D. Customer loyalty in the hotel industry: the role of customer satisfaction and image. Int J Contemp Hosp M. 2000;12(6):346–351. doi:10.1108/09596110010342559
   Google Scholar
• Cachero-Martínez S, Vázquez-Casielles R. Building consumer loyalty through e-shopping experiences: the mediating role of emotions. J Retail Consum Serv. 2021;60:102481. doi:10.1016/j.jretconser.2021.102481
   Web of Science ®Google Scholar
• Ameen N, Hosany S, Paul J. The personalisation-privacy paradox: consumer interaction with smart technologies and shopping mall loyalty. Comput Hum Behav. 2022;126:106976. doi:10.1016/j.chb.2021.106976
   Web of Science ®Google Scholar
• Prakasam N, Huxtable-Thomas L. Reddit: affordances as an enabler for shifting loyalties. Inform Syst Front. 2021;23(3):723–751. doi:10.1007/s10796-020-10002-x
   Web of Science ®Google Scholar
• Azinuddin M, Hanafiah MH, Mior Shariffuddin NS, Kamarudin MKA, Mat Som AP. An exploration of perceived ecotourism design affordance and destination social responsibility linkages to tourists’ pro-environmental behaviour and destination loyalty. J Ecotourism. 2022;1–24. doi:10.1080/14724049.2022.2085283
   Web of Science ®Google Scholar
• Kim J. Platform quality factors influencing content providers’ loyalty. J Retail Consum Serv. 2021;60:102510. doi:10.1016/j.jretconser.2021.102510
   Web of Science ®Google Scholar
• Kim J, Lennon SJ. Effects of reputation and website quality on online consumers’ emotion, perceived risk and purchase intention. J Res Interact Mark. 2013;7(1):33–56. doi:10.1108/17505931311316734
   Google Scholar
• Tuncer I. The relationship between IT affordance, flow experience, trust, and social commerce intention: an exploration using the S-O-R paradigm. Technol Soc. 2021;65:101567. doi:10.1016/j.techsoc.2021.101567
   Web of Science ®Google Scholar
• Fang Y-H, Li C-Y, Bhatti ZA. Building brand loyalty and endorsement with brand pages: integration of the lens of affordance and customer-dominant logic. Inform Technol Peopl. 2020;34(2):731–769. doi:10.1108/ITP-05-2019-0208
   Web of Science ®Google Scholar
• Dong X, Wang T, Benbasat I. IT affordances in online social commerce: conceptualization validation and scale development. Proceedings of AMCIS. San Diego, CA, USA: ; 2016.
   Google Scholar
• Xiao B, Benbasat I. Product-related deception in E-commerce: a theoretical perspective. MIS Q. 2011;35(1):169–195. doi:10.2307/23043494
   Web of Science ®Google Scholar
• Wagner D, Vollmar G, Wagner H-T. The impact of information technology on knowledge creation: an affordance approach to social media. J Enterp Inf Manag. 2014;27(1):31–44. doi:10.1108/JEIM-09-2012-0063
   Web of Science ®Google Scholar
• Choi W, Stvilia B. Web credibility assessment: conceptualization, operationalization, variability, and models. J Am Soc Inf Sci Tec. 2015;66(12):2399–2414. doi:10.1002/asi.23543
   Web of Science ®Google Scholar
• Dennis AR, Kinney ST. Testing media richness theory in the new media: the effects of cues, feedback, and task equivocality. Inf Syst Res. 1998;9(3):256–274. doi:10.1287/isre.9.3.256
   Web of Science ®Google Scholar
• Lu Y, Kim Y, Dou XY, Kumar S. Promote physical activity among college students: using media richness and interactivity in web design. Comput Hum Behav. 2014;41:40–50. doi:10.1016/j.chb.2014.08.012
   Web of Science ®Google Scholar
• Minkler AP. Why firms franchise: a search cost theory. J Inst Theor Econ. 1992;148:240–259.
   Web of Science ®Google Scholar
• Toufaily E, Ricard L, Perrien J. Customer loyalty to a commercial website: descriptive meta-analysis of the empirical literature and proposal of an integrative model. J Bus Res. 2013;66(9):1436–1447. doi:10.1016/j.jbusres.2012.05.011
   Web of Science ®Google Scholar
• Petty RE, Cacioppo JT. The elaboration likelihood model of persuasion. Adv Exp Soc Psychol. 1986;1986:123–205 doi:10.1016/S0065-2601(08)60214-2.
   Google Scholar
• Malthouse EC, Calder BJ, Kim SJ, Vandenbosch M. Evidence that user-generated content that produces engagement increases purchase behaviours. J Market Manag. 2016;32(5–6):427–444. doi:10.1080/0267257X.2016.1148066
   Web of Science ®Google Scholar
• Armstrong A, Hagel J. The real value of on-line communities. Harvard Bus Rev. 1996;74:134–141.
   Web of Science ®Google Scholar
• Liu Z, Lei S-H, Guo Y-L, Zhou Z-A. The interaction effect of online review language style and product type on consumers’ purchase intentions. Palgr Commun. 2020;6(1):1–8 doi:10.1057/s41599-020-0387-6.
   Web of Science ®Google Scholar
• Christodoulides G, Michaelidou N. Shopping motives as antecedents of e-satisfaction and e-loyalty. J Market Manag. 2010;27(1–2):181–197. doi:10.1080/0267257X.2010.489815
   Google Scholar
• Sun Y, Shao X, Li X, Guo Y, Nie K. How live streaming influences purchase intentions in social commerce: an IT affordance perspective. Electron Commer R A. 2019;37:100886. doi:10.1016/j.elerap.2019.100886
   Web of Science ®Google Scholar
• Shao Z, Zhang L, Chen K, Zhang C. Examining user satisfaction and stickiness in social networking sites from a technology affordance lens: uncovering the moderating effect of user experience. Ind Manage Data Syst. 2020;120(7):1331–1360. doi:10.1108/IMDS-11-2019-0614
   Web of Science ®Google Scholar
• Lim KH, Benbasat I. The effect of multimedia on perceived equivocality and perceived usefulness of information systems. MIS Quart. 2000;24:449–471. doi:10.2307/3250969
   Web of Science ®Google Scholar
• Gilal NG, Zhang J, Gilal FG. Linking product design to consumer behavior: the moderating role of consumption experience. Psychol Res Behav Ma. 2018;11:169. doi:10.2147/PRBM.S161384
   PubMed Web of Science ®Google Scholar
• Lai J, Chang C. User attitudes toward dedicated e‐book readers for reading: the effects of convenience, compatibility and media richness. Online Inf Rev. 2011;35(4):558–580. doi:10.1108/14684521111161936
   Web of Science ®Google Scholar
• Kim J, Ahn K, Chung N. Examining the factors affecting perceived enjoyment and usage intention of ubiquitous tour information services: a service quality perspective. Asia Pac J Tour. 2013;18(6):598–617. doi:10.1080/10941665.2012.695282
   Web of Science ®Google Scholar
• Jiang B, Zou T. Consumer search and filtering on online retail platforms. J Mark Res. 2020;57(5):900–916. doi:10.1177/0022243720928367
   Web of Science ®Google Scholar
• Chuttur M. Overview of the technology acceptance model: origins, developments and future directions. All Sprouts Content; 2009:290.
   Google Scholar
• Wang P, Li H. Understanding the antecedents and consequences of the perceived usefulness of travel review websites. Int J Contemp Hosp M. 2019;31(3):1086–1103. doi:10.1108/IJCHM-06-2017-0380
   Web of Science ®Google Scholar
• Woolley K, Sharif MA. Incentives increase relative positivity of review content and enjoyment of review writing. J Marketing Res. 2021;58(3):539–558. doi:10.1177/00222437211010439
   Web of Science ®Google Scholar
• Karahanna E, Straub DW. The psychological origins of perceived usefulness and ease-of-use. Inform Manage-Amster. 1999;35(4):237–250. doi:10.1016/S0378-7206(98)00096-2
   Web of Science ®Google Scholar
• Song K, Fiore AM, Park J. Telepresence and fantasy in online apparel shopping experience. J Fash Mark Manag. 2007;11(4):553–570 doi:10.1108/13612020710824607.
   Google Scholar
• Moon JH, Kim E, Choi SM, Sung Y. Keep the social in social media: the role of social interaction in avatar-based virtual shopping. J Interact Advert. 2013;13(1):14–26. doi:10.1080/15252019.2013.768051
   Google Scholar
• Koo D-M. The fundamental reasons of e-consumers’ loyalty to an online store. Electron Commer R A. 2006;5(2):117–130. doi:10.1016/j.elerap.2005.10.003
   Web of Science ®Google Scholar
• Suryaningsih IB, Farida L, Revanica O, Mawardi AAK. The effect of coupon sales promotion, online customer review and perceived enjoyment on repurchase intention in e-commerce shopee. Int J Sci Technol Res. 2019;2019:435.
   Google Scholar
• Parasuraman A, Grewal D. The impact of technology on the quality-value-loyalty chain: a research agenda. J Acad Market Sci. 2000;28(1):168–174. doi:10.1177/0092070300281015
   Web of Science ®Google Scholar
• Hamari J, Sjoklint M, Ukkonen A. The sharing economy: why people participate in collaborative consumption. J Assoc Inf Sci Technol. 2016;67(9):2047–2059. doi:10.1002/asi.23552
   Web of Science ®Google Scholar
• Yang S, Ahn S. Impact of motivation in the sharing economy and perceived security in attitude and loyalty toward Airbnb. Adv Sci Lett. 2016;129:180–184.
   Google Scholar
• Oktarini MAS, Wardana IM. Peran customer satisfaction memediasi pengaruh perceived ease of use dan perceived enjoyment terhadap repurchase intention. E-Jurnal Manajemen Unud. 2018;7(4):2041–2072 doi:10.24843/EJMUNUD.2018.v07.i04.p12.
   Google Scholar
• Sheth JN, Newman BI, Gross BL. Why we buy what we buy: a theory of consumption values. J Bus Res. 1991;22(2):159–170. doi:10.1016/0148-2963(91)90050-8
   Web of Science ®Google Scholar
• Yan J, Ali I, Ali R, Chang Y. The power of affection: exploring the key drivers of customer loyalty in virtual reality-enabled services. Front Psychol. 2022;13:850896. doi:10.3389/fpsyg.2022.850896
   PubMed Web of Science ®Google Scholar
• Burton-Jones A, Hubona GS. The mediation of external variables in the technology acceptance model. Inform Manage-Amster. 2006;43(6):706–717. doi:10.1016/j.im.2006.03.007
   Web of Science ®Google Scholar
• Dishaw MT, Strong DM. Extending the technology acceptance model with task–technology fit constructs. Inform Manage-Amster. 1999;36(1):9–21. doi:10.1016/S0378-7206(98)00101-3
   Web of Science ®Google Scholar
• Karahanna E, Straub DW, Chervany NL. Information technology adoption across time: a cross-sectional comparison of pre-adoption and post-adoption beliefs. Mis Quart. 1999;23:183–213. doi:10.2307/249751
   Web of Science ®Google Scholar
• Venkatesh V, Davis FD. A model of the antecedents of perceived ease of use: development and test. Decision Sci. 1996;27(3):451–481. doi:10.1111/j.1540-5915.1996.tb01822.x
   Web of Science ®Google Scholar
• Venkatesh V, Davis FD. A theoretical extension of the technology acceptance model: four longitudinal field studies. Manage Sci. 2000;46(2):186–204. doi:10.1287/mnsc.46.2.186.11926
   Web of Science ®Google Scholar
• Legris P, Ingham J, Collerette P. Why do people use information technology? A critical review of the technology acceptance model. Inform Manage-Amster. 2003;40(3):191–204. doi:10.1016/S0378-7206(01)00143-4
   Web of Science ®Google Scholar
• Sussman SW, Siegal WS. Informational influence in organizations: an integrated approach to knowledge adoption. Inform Syst Res. 2003;14(1):47–65 doi:10.1287/isre.14.1.47.14767.
   Web of Science ®Google Scholar
• So KKF, Kim H, Oh H. What makes Airbnb experiences enjoyable? The effects of environmental stimuli on perceived enjoyment and repurchase intention. J Travel Res. 2021;60(5):1018–1038. doi:10.1177/0047287520921241
   Web of Science ®Google Scholar
• Brislin RW. The Content and Evaluation of Cross-Cultural Training Programs. In: Bibliographies. Cambridge University Press; 1970.
   Google Scholar
• Faul F, Erdfelder E, Lang A-G, Buchner A. G* Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods. 2007;39(2):175–191. doi:10.3758/BF03193146
   PubMed Web of Science ®Google Scholar
• Cochran WG. Sampling Techniques. 3th ed. NJ: John Wiley & Sons; 1977.
   Google Scholar
• Number of online shoppers in China from 2011 to 2021; 2022. Available from: https://www.statista.com/statistics/277391/number-of-online-buyers-in-china/. Accessed September 20, 2022.
   Google Scholar
• Bhattacherjee A. Understanding information systems continuance: an expectation-confirmation model. MIS Quart. 2001;25(3):351–370. doi:10.2307/3250921
   Web of Science ®Google Scholar
• Mäntymäki M, Salo J. Teenagers in social virtual worlds: continuous use and purchasing behavior in Habbo Hotel. Comput Hum Behav. 2011;27(6):2088–2097. doi:10.1016/j.chb.2011.06.003
   Web of Science ®Google Scholar
• Webster J, Ho H. Audience engagement in multimedia presentations. Acm Sigmis Database. 1997;28(2):63–77. doi:10.1145/264701.264706
   Web of Science ®Google Scholar
• Distribution of online buyers in China in 2019, by age group; 2019. Available from: https://www.statista.com/statistics/1172011/china-age-group-distribution-of-online-shoppers/. Accessed September 20, 2022.
   Google Scholar
• Chin WW. The partial least squares approach to structural equation modeling. In: Marcoulides GA, editor. Modern Methods for Business Research. Hillsdale, New Jersey: Lawrence Erlbaum Associates Publishers; 1998:295–336.
   Google Scholar
• Nunnally JC. An overview of psychological measurement. In: Benjamin BW, editor. Clinical Diagnosis of Mental Disorders. New York: Springer; 1978:97–146.
   Google Scholar
• Henseler JR, Ringle CM, Sarstedt M. A new criterion for assessing discriminant validity in variance-based structural equation modeling. J Acad Market Sci. 2015;43(1):115–135. doi:10.1007/s11747-014-0403-8
   Web of Science ®Google Scholar
• Diamantopoulos A, Siguaw JA. Formative versus reflective indicators in organizational measure development: a comparison and empirical illustration. Brit J Manage. 2006;17(4):263–282. doi:10.1111/j.1467-8551.2006.00500.x
   Web of Science ®Google Scholar
• Preacher KJ, Hayes AF. Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behav Res Methods. 2008;40(3):879–891. doi:10.3758/BRM.40.3.879
   PubMed Web of Science ®Google Scholar
• Guo J, Li Y, Xu YJ, Zeng K. How live streaming features impact consumers’ purchase intention in the context of cross-border E-commerce? A research based on SOR theory. Front Psychol. 2021;12:767876. doi:10.3389/fpsyg.2021.767876
   PubMed Web of Science ®Google Scholar
• Vivek SD, Beatty SE, Morgan RM. Customer engagement: exploring customer relationships beyond purchase. J Market Theory Prac. 2012;20(2):122–146. doi:10.2753/MTP1069-6679200201
   Google Scholar
• Massey BL, Levy MR. Interactivity, online journalism, and English-language web newspapers in Asia. J Mass Commun Q. 1999;76(1):138–151 doi:10.1177/107769909907600110.
   Web of Science ®Google Scholar
• Cao HH. Online review manipulation by asymmetrical firms: is a firm’s manipulation of online reviews always detrimental to its competitor? Inform Manage-Amster. 2020;57:6 doi:10.1016/j.im.2019.103244.
   Web of Science ®Google Scholar
• Le LT, Ly PTM, Nguyen NT, Tran LTT. Online reviews as a pacifying decision-making assistant. J Retail Consum Serv. 2022;64:102805. doi:10.1016/j.jretconser.2021.102805
   Web of Science ®Google Scholar
• Wang XH, Goh DHL. Components of game experience: an automatic text analysis of online reviews. Entertain Comput. 2020;33:100338. doi:10.1016/j.entcom.2019.100338
   Web of Science ®Google Scholar
• Erkan I, Evans C. The influence of eWOM in social media on consumers’ purchase intentions: an extended approach to information adoption. Comput Hum Behav. 2016;61:47–55. doi:10.1016/j.chb.2016.03.003
   Web of Science ®Google Scholar
• Huang AH, Chen KC, Yen DC, Tran TP. A study of factors that contribute to online review helpfulness. Comput Hum Behav. 2015;48:17–27. doi:10.1016/j.chb.2015.01.010
   Web of Science ®Google Scholar
• Tversky A, Kahneman D. Advances in prospect theory: cumulative representation of uncertainty. J Risk Uncertainty. 1992;5(4):297–323. doi:10.1007/BF00122574
   Web of Science ®Google Scholar
• Fang Y-H. An app a day keeps a customer connected: explicating loyalty to brands and branded applications through the lens of affordance and service-dominant logic. Inform Manage-Amster. 2019;56(3):377–391. doi:10.1016/j.im.2018.07.011
   Web of Science ®Google Scholar
• Gao L, Waechter KA, Bai X. Understanding consumers’ continuance intention towards mobile purchase: a theoretical framework and empirical study–A case of China. Comput Hum Behav. 2015;53:249–262. doi:10.1016/j.chb.2015.07.014
   Web of Science ®Google Scholar