Consumers response towards mobile commerce applications: S-O-R approach.

Prasanta Kr Chopdara, Janarthanan Balakrishnan, (2020).Consumers response towards mobile commerce applications: S-O-R approach, International Journal of Information Management.

Keywords: Mobile shopping application Impulsiveness; Perceived value Stimulus-organism-response (S-O-R) Repurchase intention; Satisfying experience

Pour une application sur smartphone, sa rentabilité se mesure à la fidélisation du client, et à l’utilisation quotidienne de celle-ci. Cet étude a pour but de comprendre les éléments de comportement envers les utilisateurs d’application. Afin de recueillir des données sur l’incitation aux application de m-commerce, un échantillon de 420 acheteurs de mobiles en Inde est interrogés.

Développement :

La recherche applique de manière transversale le cadre de la théorie stimulus-organisme-réponse (S-O-R), cette méthode permet de d’étudier le comportement de l’achat impulsif. Elle unifie le concept du comportement du consommateur, des systèmes d’informations (SI) et de la psychologie.

Le marché du m-commerce est présent dans le quotidien de tout utilisateurs de smartphone aujourd’hui. Les application permette a tout société de proposer des achats de biens ou de service personnalisé grâce une utilisation de la data via tous les canaux de distribution d’information.

Le secret de viabilité d’un application réside dans la fidélisation sur le long terme de son utilisateur, pour que celle-ci dégage un profit. Pour développer construire sa basé de donnée l’étude se base sur 14 hypothèses auprès d’un échantillon de 420 personnes consommateur de m-commerce en Inde.

Hypothèse 1. L’ubiquité perçue affecte positivement l’impulsivité des applications d’achat mobiles.

Hypothèse 2. L’ubiquité perçue affecte positivement la valeur perçue des applications d’achat mobile.

Hypothèse 3. L’offre contextuelle affecte positivement l’impulsivité avec les applications d’achat mobiles.

Hypothèse 4. L’offre contextuelle affecte positivement la valeur perçue des applications d’achat mobile.

Hypothèse 5. L’attractivité visuelle affecte positivement l’impulsivité avec les applications d’achat mobiles.

Hypothèse 6. L’attractivité visuelle affecte positivement la valeur perçue des applications d’achat mobiles.

Hypothèse 7. Les incitations liées aux applications affectent positivement l’impulsivité des applications d’achat mobiles.

Hypothèse 8. Les incitations liées aux applications affectent positivement la valeur perçue des applications d’achat mobiles.

Hypothèse 9. L’impulsivité affecte positivement une expérience satisfaisante avec les applications d’achat mobiles.

Hypothèse 10. L’impulsivité affecte positivement l’intention de rachat par le biais des applications d’achat mobiles.

Hypothèse 11. La valeur perçue affecte positivement l’expérience satisfaisante dans les applications d’achat mobiles.

Hypothèse 12. La valeur perçue affecte positivement l’intention de rachat par le biais des applications d’achat mobiles.

Hypothèse 13. Une expérience satisfaisante influe positivement sur l’intention de rachat via les applications d’achat mobiles.

Hypothèse 14a. L’impact de l’impulsivité sur une expérience satisfaisante est modéré négativement par l’âge.

Hypothèse 14b. L’impact de l’impulsivité sur l’intention de rachat est négativement modéré par l’âge.

Hypothèse 14c. L’impact de la valeur perçue sur une expérience satisfaisante est positivement modéré par l’âge.

Hypothèse 14d. L’impact de la valeur perçue sur l’intention de rachat est positivement modéré par l’âge.

Résultats :

 Les résultat de la recherche empirique et démontre H1 est plausible donc, l’ubiquité perçue affecte positivement l’impulsivité des applications d’achat mobiles. Puis H5 et H6 sont donc soutenu par le fait que l’attractivité visuelle joue un rôle dans la valeur perçue et joue positivement sur l’impulsivité d’achat.

Cela permet d’affirmer qu’il y effet sur l’impulsivité d’achat qui engendre une satisfaction auprès des utilisateurs, mais que contrairement à l’hypothèse 13 notre impulsivité joue un rôle négatif sur l’intention de fidélisation.

Conclusion :

Enfin, cet étude qui pour objectif d’assimiler les comportement face aux expérience d’achat dans le m-commerce et les intentions de rachat de l’utilisateur, permet de démontrer que l’impulsivité est un facteur bloquant dans le processus de rachat, ce qui crée un frein à la fidélisation du client.

Références Bibliographiques :

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

Andrews, M., Goehring, J., Hui, S., Pancras, J., & Thornswood, L. (2016). Mobile pro- motions: A framework and research priorities. Journal of Interactive Marketing, 34, 15–24.

Ansari, M. S., Channar, Z. A., & Syed, A. (2012). Mobile phone adoption and appro- priation among the young generation. Procedia-Social and Behavioral Sciences, 41, 265–272.

Arpaci, I. (2016). Understanding and predicting students’ intention to use mobile cloud storage services. Computers in Human Behavior, 58, 150–157.

Atulkar, S., & Kesari, B. (2016). Shopping experience of hypermarket shoppers on weekends. Indian Journal of Marketing, 46(11), 36–49.

Beatty, S. E., & Ferrell, M. E. (1998). Impulse buying: Modeling its precursors. Journal of Retailing, 74(2), 169–191.

Bhandari, U., Neben, T., Chang, K., & Chua, W. Y. (2017). Effects of interface design factors on affective responses and quality evaluations in mobile applications. Computers in Human Behavior, 72, 525–534.

Bhattacherjee, A. (2001). Understanding information systems continuance: An expecta- tion-confirmation model. MIS Quarterly, 351–370.

Bilgihan, A., Kandampully, J., & Zhang, T. (2016). Towards a unified customer experience in online shopping environments: Antecedents and outcomes. International Journal of Quality and Service Sciences, 8(1), 102–119.

Bilro, R. G., Loureiro, S. M. C., & Ali, F. (2018). The role of website stimuli of experience on engagement and brand advocacy. Journal of Hospitality and Tourism Technology, 9(2), 204–222.

Boeck, H., Lamarre, A., & Galarneau, S. (2011). Mobile marketing and consumer behavior current research trends. International Journal of Latest Trends in Computing, 3(1).

Cai, S., & Xu, Y. (2011). Designing not just for pleasure: Effects of web site aesthetics on consumer shopping value. International Journal of Electronic Commerce, 15(4),159–188.

Chakraborty, T., & Balakrishnan, J. (2017). Exploratory tendencies in consumer behaviour in online buying across gen X, gen Y and baby boomers. International Journal of Value Chain Management, 8(2), 135–150.

Chan, T. K., Cheung, C. M., & Lee, Z. W. (2017). The state of online impulse-buying research: A literature analysis. Information & Management, 54(2), 204–217.

Chen, S. C. (2012). To use or not to use: Understanding the factors affecting continuance intention of mobile banking. International Journal of Mobile Communications, 10(5), 490–507.

Chen, C. F., & Chen, F. S. (2010). Experience quality, perceived value, satisfaction and behavioral intentions for heritage tourists. Tourism Management, 31(1), 29–35. Chen, C.

C., & Yao, J. Y. (2018). What drives impulse buying behaviors in a mobile auction? The perspective of the Stimulus-Organism-Response model. Telematics and Informatics, 35(5), 1249–1262.

Chih, W. H., Wu, C. H. J., & Li, H. J. (2012). The antecedents of consumer online buying impulsiveness on a travel website: Individual internal factor perspectives. Journal of Travel & Tourism Marketing, 29(5), 430–443.

Chiu, C. M., Wang, E. T., Fang, Y. H., & Huang, H. Y. (2014). Understanding customers’ repeat purchase intentions in B2C e‐commerce: The roles of utilitarian value, hedonic value and perceived risk. Information Systems Journal, 24(1), 85–114.

Choi, S., Cheong, K., Somera, B., & Hao, Q. (2014). Determinants of utilitarian value smartphone-based mobile commerce. JunePACIS151.

Chopdar, P. K., & Sivakumar, V. J. (2018). Understanding psychological contract violation and its consequences on mobile shopping applications use in a developing country context. Journal of Indian Business Research, 10(2), 208–231.

Chopdar, P. K., & Sivakumar, V. J. (2019). Impulsiveness and its impact on behavioural intention and use of mobile shopping apps: A mediation model. International Journal

of Business Innovation and Research, 19(1), 29–56.

Clement, J. (2007). Visual influence on in-store buying decisions: An eye-track experi-

ment on the visual influence of packaging design. Journal of Marketing Management,

23(9–10), 917–928.

Clements, J. A., & Boyle, R. (2018). Compulsive technology use: Compulsive use of mobile

applications. Computers in Human Behavior, 87, 34–48.

Dai, H., Hu, T., & Zhang, X. (2014). Continued use of mobile technology mediated ser-

vices: A value perspective. Journal of Computer Information Systems, 54(2), 99–109. Dale, L. P., White, L., Mitchell, M., & Faulkner, G. (2019). Smartphone app uses loyalty

14

P.K. Chopdar and J. Balakrishnan

International Journal of Information Management 53 (2020) 102106

point incentives and push notifications to encourage influenza vaccine uptake.

Vaccine, 37(32), 4594–4600.

Davis, R., & Sajtos, L. (2009). Anytime, anywhere: Measuring the ubiquitous consumer’s

impulse purchase behavior. International Journal of Mobile Marketing, 4(1).

Deng, L., Turner, D. E., Gehling, R., & Prince, B. (2010). User experience, satisfaction, and

continual usage intention of IT. European Journal of Information Systems, 19(1),

60–75.

Ebrahim, R., Ghoneim, A., Irani, Z., & Fan, Y. (2016). A brand preference and repurchase

intention model: The role of consumer experience. Journal of Marketing Management,

32(13–14), 1230–1259.

El-Adly, M. I. (2019). Modelling the relationship between hotel perceived value, customer

satisfaction, and customer loyalty. Journal of Retailing and Consumer Services, 50,

322–332.

Fang, J., Zhao, Z., Wen, C., & Wang, R. (2017). Design and performance attributes driving

mobile travel application engagement. International Journal of Information

Management, 37(4), 269–283.

Farah, M. F., & Ramadan, Z. B. (2017). Disruptions versus more disruptions: How the

Amazon dash button is altering consumer buying patterns. Journal of Retailing and

Consumer Services, 39, 54–61.

Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to

theory and research. Reading, MA: Addison-Wesley.

Floh, A., & Madlberger, M. (2013). The role of atmospheric cues in online impulse-buying

behavior. Electronic Commerce Research and Applications, 12(6), 425–439.

Floh, A., Zauner, A., Koller, M., & Rusch, T. (2014). Customer segmentation using un-

observed heterogeneity in the perceived-value–loyalty–intentions link. Journal of

Business Research, 67(5), 974–982.

Forbes (2017). Forbes. Available at: https://www.forbes.com/sites/quora/2017/12/19/

why-many-online-shopping-sites-are-becoming-mobile-shopping-apps/#

5f29e62f62c2 (Accessed 11 June 2018).

Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable vari-

ables and measurement error: Algebra and statistics. Journal of Marketing Research,

382–388.

Gao, L., Waechter, K. A., & Bai, X. (2015). Understanding consumers’ continuance in-

tention towards mobile purchase: A theoretical framework and empirical study–A

case of China. Computers in Human Behavior, 53, 249–262.

Ghani, U., & Kamal, Y. (2010). The impact of in-store stimuli on the impulse purchase

behaviour of consumers in Pakistan. Interdisciplinary Journal of Contemporary Research

in Business, 2(8), 155–162.

Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., & Thiele, K. O. (2017). Mirror,

mirror on the wall: A comparative evaluation of composite-based structural equation

modeling methods. Journal of the Academy of Marketing Science, 45(5), 616–632. Hair, J. F., William, C. B., Barry, J. B., & Rolph, E. A. (2010). Multivariate data analysis.

Englewood Cliffs, NJ: Prentice Hall.

Helkkula, A., & Kelleher, C. (2010). Circularity of customer service experience and cus-

tomer perceived value. Journal of Customer Behaviour, 9(1), 37–53.

Henseler, J., Ringle, C. M., & Sarstedt, M. (2016). Testing measurement invariance of

composites using partial least squares. International Marketing Review, 33(3),

405–431.

Hew, T. S., & Kadir, S. L. S. A. (2016). Understanding cloud-based VLE from the SDT and

CET perspectives: Development and validation of a measurement instrument.

Computers & Education, 101, 132–149.

Hew, T. S., Leong, L. Y., Ooi, K. B., & Chong, A. Y. L. (2016). Predicting drivers of mobile

entertainment adoption: A two-stage SEM-artificial-neural-network analysis. Journal

of Computer Information Systems, 56(4), 352–370.

Ho, Y. C., Ho, Y. J., & Tan, Y. (2017). Online cash-back shopping: Implications for con-

sumers and e-businesses. Information Systems Research, 28(2), 250–264.

Homburg, C., Jozić, D., & Kuehnl, C. (2017). Customer experience management: Toward

implementing an evolving marketing concept. Journal of the Academy of Marketing

Science, 45(3), 377–401.

Hsiao, C. H., Chang, J. J., & Tang, K. Y. (2016). Exploring the influential factors in

continuance usage of mobile social Apps: Satisfaction, habit, and customer value

perspectives. Telematics and Informatics, 33(2), 342–355.

Hsu, M. H., Chang, C. M., & Chuang, L. W. (2015). Understanding the determinants of

online repeat purchase intention and moderating role of habit: The case of online group-buying in Taiwan. International Journal of Information Management, 35(1), 45–56.

Huang, L. T. (2016). Flow and social capital theory in online impulse buying. Journal of Business Research, 69(6), 2277–2283.

Hubert, M., Hubert, M., Linzmajer, M., Riedl, R., & Kenning, P. (2018). Trust me if you can–neurophysiological insights on the influence of consumer impulsiveness on trustworthiness evaluations in online settings. European Journal of Marketing, 52(1/2), 118–146.

Hübner, A., Holzapfel, A., & Kuhn, H. (2016). Distribution systems in omni-channel re- tailing. Business Research, 9(2), 255–296.

Hult, G. T. M., Sharma, P. N., Morgeson III, F. V., & Zhang, Y. (2019). Antecedents and consequences of customer satisfaction: Do they differ across online and offline pur- chases? Journal of Retailing, 95(1), 10–23.

Jain, R., Aagja, J., & Bagdare, S. (2017). Customer experience–a review and research agenda. Journal of Service Theory and Practice, 27(3), 642–662.

Johnson, V. L., Kiser, A., Washington, R., & Torres, R. (2018). Limitations to the rapid adoption of M-payment services: Understanding the impact of privacy risk on M- Payment services. Computers in Human Behavior, 79, 111–122.

Khakimdjanova, L., & Park, J. (2005). Online visual merchandising practice of apparel e- merchants. Journal of Retailing and Consumer Services, 12(5), 307–318.

Khalifa, M., & Liu, V. (2007). Online consumer retention: Contingent effects of online shopping habit and online shopping experience. European Journal of Information

Systems, 16(6), 780–792.

Kim, S., & Labroo, A. A. (2011). From inherent value to incentive value: When and why

pointless effort enhances consumer preference. The Journal of Consumer Research,

38(4), 712–742.

Kim, M., Kim, J., Choi, J., & Trivedi, M. (2017). Mobile shopping through applications:

Understanding application possession and mobile purchase. Journal of Interactive

Marketing, (39), 55–68.

Kim, S., Kim, S., Baek, T. H., Baek, T. H., Kim, Y. K., Kim, Y. K., Yoo, K., & Yoo, K. (2016).

Factors affecting stickiness and word of mouth in mobile applications. Journal of

Research in Interactive Marketing, 10(3), 177–192.

Kim, Y. H., Kim, D. J., & Wachter, K. (2013). A study of mobile user engagement (MoEN):

Engagement motivations, perceived value, satisfaction, and continued engagement

intention. Decision Support Systems, 56, 361–370.

Kim, E., Lin, J. S., & Sung, Y. (2013). To app or not to app: Engaging consumers via

branded mobile apps. Journal of Interactive Advertising, 13(1), 53–65.

Klaus, P. (2013). The case of Amazon. com: Towards a conceptual framework of online customer service experience (OCSE) using the emerging consensus technique (ECT).

Journal of Services Marketing, 27(6), 443–457.

Kleijnen, M., De Ruyter, K., & Wetzels, M. (2007). An assessment of value creation in

mobile service delivery and the moderating role of time consciousness. Journal of

Retailing, 83(1), 33–46.

Koenigstorfer, J., & Groeppel-Klein, A. (2012). Consumer acceptance of the mobile

Internet. Marketing Letters, 23(4), 917–928.

Köster, A., Matt, C., & Hess, T. (2016). Carefully choose your (payment) partner: How

payment provider reputation influences m-commerce transactions. Electronic

Commerce Research and Applications, 15, 26–37.

Kukar-Kinney, M., Scheinbaum, A. C., & Schaefers, T. (2016). Compulsive buying in

online daily deal settings: An investigation of motivations and contextual elements.

Journal of Business Research, 69(2), 691–699.

Kumar, A., & Lim, H. (2008). Age differences in mobile service perceptions: Comparison

of generation Y and baby boomers. Journal of Services Marketing, 22(7), 568–577. Kuo, Y. F., Wu, C. M., & Deng, W. J. (2009). The relationships among service quality,

perceived value, customer satisfaction, and post-purchase intention in mobile value-

added services. Computers in Human Behaviour, 25(4), 887–896.

Lai, F., Griffin, M., & Babin, B. J. (2009). How quality, value, image, and satisfaction

create loyalty at a Chinese telecom. Journal of Business Research, 62(10), 980–986. Law, D., Wong, C., & Yip, J. (2012). How does visual merchandising affect consumer

affective response? An intimate apparel experience. European Journal of Marketing,

46(1/2), 112–133.

Lee, T. (2005). The impact of perceptions of interactivity on customer trust and trans-

action intentions in mobile commerce. Journal of Electronic Commerce Research, 6(3),

165.

Lee, S., & Rao, V. S. C. (2010). Color and store choice in electronic commerce: The ex-

planatory role of trust. Journal of Electronic Commerce Research, 11(2), 110–126. Lee, T., Park, C., & Jun, J. (2014). Two faces of mobile shopping: Self-efficacy and im-

pulsivity. International Journal of E-Business Research (IJEBR), 10(1), 15–32. Lemon, K. N., & Verhoef, P. C. (2016). Understanding customer experience throughout

the customer journey. Journal of Marketing, 80(6), 69–96.

Leong, L. Y., Hew, T. S., Ooi, K. B., & Lin, B. (2012). The determinants of customer loyalty

in Malaysian mobile telecommunication services: A structural analysis. International

Journal of Services, Economics and Management, 4(3), 209–236.

Leong, L. Y., Jaafar, N. I., & Sulaiman, A. (2017). Understanding impulse purchase in

Facebook commerce: does big five matter? Internet Research, 27(4), 786–818. Leong, L. Y., Hew, T. S., Ooi, K. B., Lee, V. H., & Hew, J. J. (2019). A hybrid SEM-neural

network analysis of social media addiction. Expert Systems with Applications, 133,

296–316.

Leong, L. Y., Hew, T. S., Ooi, K. B., & Lin, B. (2019). Do electronic word-of-mouth and

elaboration likelihood model influence hotel booking? Journal of Computer

Information Systems, 59(2), 146–160.

Li, Y. (2015). Impact of impulsive buying behavior on postimpulsive buying satisfaction.

Social Behavior and Personality an International Journal, 43(2), 339–351.

Li, M., Dong, Z. Y., & Chen, X. (2012). Factors influencing consumption experience of

mobile commerce: A study from experiential view. Internet Research, 22(2), 120–141. Liao, S. L., Shen, Y. C., & Chu, C. H. (2009). The effects of sales promotion strategy,

product appeal and consumer traits on reminder impulse buying behaviour.

International Journal of Consumer Studies, 33(3), 274–284.

Liebana-Cabanillas, F., & Alonso-Dos-Santos, M. (2017). Factors that determine the

adoption of Facebook commerce: The moderating effect of age. Journal of Engineering

and Technology Management, 44, 1–18.

Limayem, M., Hirt, S. G., & Cheung, C. M. (2007). How habit limits the predictive power

of intention: The case of information systems continuance. MIS Quarterly, 31(4). Lin, T. T., & Bautista, J. R. (2018). Content-related factors influence perceived value of

location-based mobile advertising. Journal of Computer Information Systems, 1–10. Lin, H., Fan, W., & Chau, P. Y. (2014). Determinants of users’ continuance of social

networking sites: A self-regulation perspective. Information & Management, 51(5),

595–603.

Lin, K. Y., & Lu, H. P. (2015). Predicting mobile social network acceptance based on

mobile value and social influence. Internet Research, 25(1), 107–130.

Lin, H. H., & Wang, Y. S. (2006). An examination of the determinants of customer loyalty

in mobile commerce contexts. Information & Management, 43(3), 271–282.

Liu, F., Zhao, X., Chau, P. Y., & Tang, Q. (2015). Roles of perceived value and individual differences in the acceptance of mobile coupon applications. Internet Research, 25(3),

471–495.

Liu, Y., Li, H., & Hu, F. (2013). Website attributes in urging online impulse purchase: An

empirical investigation on consumer perceptions. Decision Support Systems, 55(3), 829–837.

15

 

P.K. Chopdar and J. Balakrishnan

International Journal of Information Management 53 (2020) 102106

MacCallum, R. C., & Austin, J. T. (2000). Applications of structural equation modeling in psychological research. Annual Review of Psychology, 51(1), 201–226.

Magrath, V., & McCormick, H. (2013). Marketing design elements of mobile fashion retail apps. Journal of Fashion Marketing and Management: An International Journal, 17(1), 115–134.

McLean, G., & Wilson, A. (2016). Evolving the online customer experience… is there a role for online customer support? Computers in Human Behavior, 60, 602–610.

McLean, G., Al-Nabhani, K., & Wilson, A. (2018). Developing a mobile applications customer experience model (MACE)-implications for retailers. Journal of Business Research, 85, 325–336.

Mehrabian, A., & Russell, J. A. (1974). An approach to environmental psychology. Cambridge, MA: MIT Press.

Merisavo, M., Kajalo, S., Karjaluoto, H., Virtanen, V., Salmenkivi, S., Raulas, M., et al. (2007). An empirical study of the drivers of consumer acceptance of mobile adver- tising. Journal of Interactive Advertising, 7(2), 41–50.

Natarajan, T., Balasubramanian, S. A., & Kasilingam, D. L. (2018). The moderating role of device type and age of users on the intention to use mobile shopping applications. Technology in Society, 53, 79–90.

Naylor, R. W., Raghunathan, R., & Ramanathan, S. (2006). Promotions spontaneously induce a positive evaluative response. Journal of Consumer Psychology, 16(3), 295–305.

Ng, M. (2016). Examining factors affecting mobile commerce adoption of Chinese con- sumers. International Journal of Electronic Business, 13(1), 98–115.

Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). New York: McGraw-Hill.

Okazaki, S., & Mendez, F. (2013). Perceived ubiquity in mobile services. Journal of Interactive Marketing, 27(2), 98–111.

Ozen, H., & Engizek, N. (2014). Shopping online without thinking: Being emotional or rational? Asia Pacific Journal of Marketing and Logistics, 26(1), 78–93.

Ozturk, A. B., Bilgihan, A., Nusair, K., & Okumus, F. (2016). What keeps the mobile hotel booking users loyal? Investigating the roles of self-efficacy, compatibility, perceived ease of use, and perceived convenience. International Journal of Information Management, 36(6), 1350–1359.

Parboteeah, D. V., Valacich, J. S., & Wells, J. D. (2009). The influence of website char- acteristics on a consumer’s urge to buy impulsively. Information Systems Research, 20(1), 60–78.

Park, M., & Lennon, S. J. (2009). Brand name and promotion in online shopping contexts. Journal of Fashion Marketing and Management: An International Journal, 13(2), 149–160.

Park, H. H., Jeon, J. O., & Sullivan, P. (2015). How does visual merchandising in fashion retail stores affect consumers’ brand attitude and purchase intention? The International Review of Retail, Distribution and Consumer Research, 25(1), 87–104.

Peng, C., & Kim, Y. G. (2014). Application of the stimuli-organism-response (SOR) fra- mework to online shopping behavior. Journal of Internet Commerce, 13(3-4), 159–176.

Phang, C. W., Sutanto, J., Kankanhalli, A., Li, Y., Tan, B. C., & Teo, H. H. (2006). Senior citizens’ acceptance of information systems: A study in the context of e-government services. IEEE Transactions on Engineering Management, 53(4), 555–569.

Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. The Journal of Applied Psychology, 88(5), 879.

Prashar, S., Parsad, C., & Vijay, T. S. (2017). Segmenting young Indian impulsive shoppers. Journal of International Consumer Marketing, 29(1), 35–47.

Ritch, E. L., & Schröder, M. J. (2012). Accessing and affording sustainability: The experience of fashion consumption within young families. International Journal of Consumer Studies, 36(2), 203–210.

Rodríguez-Torrico, P., Cabezudo, R. S. J., & San-Martín, S. (2017). Tell me what they are like and I will tell you where they buy. An analysis of omnichannel consumer behavior. Computers in Human Behavior, 68, 465–471.

Rodríguez-Torrico, P., San-Martín, S., & San José-Cabezudo, R. (2019). What drives M-shoppers to continue using mobile devices to buy? The Journal of Marketing Theoryand Practice, 27(1), 83–102.

Rook, D. W., & Fisher, R. J. (1995). Normative influences on impulsive buying behavior.

The Journal of Consumer Research, 22(3), 305–313.

Rose, S., Clark, M., Samouel, P., & Hair, N. (2012). Online customer experience in e-

retailing: An empirical model of antecedents and outcomes. Journal of Retailing,

88(2), 308–322.

San-Martín, S., Prodanova, J., & Jiménez, N. (2015). The impact of age in the generation

of satisfaction and WOM in mobile shopping. Journal of Retailing and Consumer

Services, 23, 1–8.

Seo, Y. (2013). Electronic sports: A new marketing landscape of the experience economy.

Journal of Marketing Management, 29(13–14), 1542–1560.

Shang, D., & Wu, W. (2017). Understanding mobile shopping consumers’ continuance

intention. Industrial Management & Data Systems, 117(1), 213–227.

Shobeiri, S., Mazaheri, E., & Laroche, M. (2018). Creating the right customer experience

online: The influence of culture. Journal of Marketing Communications, 24(3),

270–290.

Soares, R. R., Zhang, T. T. C., Proença, J. F., & Kandampully, J. (2017). Why are

Generation Y consumers the most likely to complain and repurchase? Journal of

Service Management, 28(3), 520–540.

Song, J. H., & Zinkhan, G. M. (2008). Determinants of perceived web site interactivity.

Journal of Marketing, 72(2), 99–113.

Srivastava, M., & Kaul, D. (2016). Exploring the link between customer experi-

ence–loyalty–consumer spend. Journal of Retailing and Consumer Services, 31,

277–286.

Statista. Available at: https://www.statista.com/statistics/557951/mobile-commerce-

transaction-value-worldwide/ (Accessed 18 October 2019).

Tak, P., Tak, P., Panwar, S., & Panwar, S. (2017). Using UTAUT 2 model to predict mobile

app based shopping: Evidences from India. Journal of Indian Business Research, 9(3),

248–264.

Tojib, D., & Tsarenko, Y. (2012). Post-adoption modeling of advanced mobile service use.

Journal of Business Research, 65(7), 922–928.

Vazquez, D., Dennis, C., & Zhang, Y. (2017). Understanding the effect of smart retail

brand–consumer communications via mobile instant messaging (MIM)–an empirical

study in the Chinese context. Computers in Human Behavior, (77), 425–436. Verhoef, P. C., Lemon, K. N., Parasuraman, A., Roggeveen, A., Tsiros, M., & Schlesinger, L. A. (2009). Customer experience creation: Determinants, dynamics and management

strategies. Journal of Retailing, 85(1), 31–41.

Vinayak, S., & Malhotra, M. (2017). Impact of impulsiveness on mobile phone addiction.

Indian Journal of Health & Wellbeing, 8(10).

Voropanova, E. (2015). Conceptualizing smart shopping with a smartphone: Implications

of the use of mobile devices for shopping productivity and value. The International

Review of Retail, Distribution and Consumer Research, 25(5), 529–550. Wang, C. (2014). Antecedents and consequences of perceived value in Mobile

Government continuance use: An empirical research in China. Computers in Human

Behavior, 34, 140–147.

Wang, C., & Teo, T. S. (2020). Perceived value and continuance intention in mobile

government service in China. Telematics and Informatics101348.

Wang, R. J. H., Malthouse, E. C., & Krishnamurthi, L. (2015). On the go: How mobile

shopping affects customer purchase behavior. Journal of Retailing, 91(2), 217–234. Wells, J. D., Parboteeah, V., & Valacich, J. S. (2011). Online impulse buying:

Understanding the interplay between consumer impulsiveness and website quality.

Journal of the Association for Information Systems, 12(1), 32.

Wolf, E. J., Harrington, K. M., Clark, S. L., & Miller, M. W. (2013). Sample size require-

ments for structural equation models: An evaluation of power, bias, and solution

propriety. Educational and Psychological Measurement, 73(6), 913–934.

Wong, C. H., Tan, G. W. H., Tan, B. I., & Ooi, K. B. (2015). Mobile advertising: The

changing landscape of the advertising industry. Telematics and Informatics, 32(4),

720–734.

Xu, Y., & Huang, J. S. (2014). Effects of price discounts and bonus packs on online im-

pulse buying. Social Behavior and Personality an International Journal, 42(8),

1293–1302.

Xu, Z., & Yuan, Y. (2009). The impact of context and incentives on mobile service

adoption. International Journal of Mobile Communications, 7(3), 363–381.

Xu, C., Peak, D., & Prybutok, V. (2015). A customer value, satisfaction, and loyalty per-

spective of mobile application recommendations. Decision Support Systems, 79,

171–183.

Yadav, R., Sharma, S. K., & Tarhini, A. (2016). A multi-analytical approach to understand

and predict the mobile commerce adoption. Journal of Enterprise Information

Management, 29(2), 222–237.

Yang, Y., Liu, Y., Li, H., & Yu, B. (2015). Understanding perceived risks in mobile payment

acceptance. Industrial Management & Data Systems, 115(2), 253–269.

Young Kim, E., & Kim, Y. K. (2004). Predicting online purchase intentions for clothing

products. European Journal of Marketing, 38(7), 883–897.

Yumurtacı Hüseyinoğlu, I. Ö, Galipoğlu, E., & Kotzab, H. (2017). Social, local and mobile

commerce practices in omni-channel retailing: Insights from Germany and Turkey.

International Journal of Retail & Distribution Management, 45(7/8), 711–729. Zarmpou, T., Saprikis, V., Markos, A., & Vlachopoulou, M. (2012). Modeling users’ ac-

ceptance of mobile services. Electronic Commerce Research, 12(2), 225–248. Zhang, J., & Mao, E. (2012). What’s around me?: Applying the theory of consumption values to understanding the use of location-based services (LBS) on smart phones.

International Journal of E-Business Research (IJEBR), 8(3), 33–49.

Zhang, X., Prybutok, V. R., & Strutton, D. (2007). Modeling influences on impulse pur-

chasing behaviors during online marketing transactions. The Journal of Marketing

Theory and Practice, 15(1), 79–89.

Zhao, X., Lynch, J. G., Jr., & Chen, Q. (2010). Reconsidering Baron and Kenny: Myths and

truths about mediation analysis. The Journal of Consumer Research, 37(2), 197–206. Zheng, X., Men, J., Yang, F., & Gong, X. (2019). Understanding impulse buying in mobile

commerce: An investigation into hedonic and utilitarian browsing. International

Journal of Information Management, 48, 151–160.

Zhou, T. (2013). An empirical examination of the determinants of mobile purchase.

Personal and Ubiquitous Computing, 17(1), 187–195.

Zhou, T., Lu, Y., & Wang, B. (2010). Exploring user acceptance of WAP services from the

perspectives of perceived value and trust. International Journal of Information Technology and Management, 9(3), 302–316.