User Experience as a Predictor of E-commerce Continuation Intention in Indonesia: Examining the Role of Shopping Orientation as a Moderator
Downloads
Background: The integration of Stimulus-Organism-Response (SOR) framework and Technology Acceptance Model (TAM) is still in need of improvement, particularly in studies examining individual behavior in Indonesian e-commerce context. A common challenge in e-commerce adoption is individual willingness and intention to adopt, which is influenced by previous user experience. Consequently, there is a need for the establishment of standard to measure user experience in e-commerce.
Objective: This study aims to measure the post-adoption experience of e-commerce user, which will shape attitude and influence future continuance intention (CI).
Methods: This study integrated SOR and TAM frameworks, followed by the collection and analysis of data from 263 respondents using Structural Equation Modeling-Partial Least Squares (SEM-PLS). Among the four hypotheses proposed, two represented novel contributions to the existing literature.
Results: The results showed a positive and significant influence of Interaction Experience (IE), Sense Experience (SE), and Flow Experience (FE) on Attitude Toward Using (ATU). The data analysis also indicated a positive and significant effect of ATU on Continuance Intention (CI). However, the influence of ATU on CI became insignificant when moderated by Shopping Orientation (SO).
Conclusion: Based on the results, not all hypotheses proposed in this study are supported. However, the results provide both theoretical and practical contributions.
Keywords: SOR, TAM, User Experience, Continuance Intention, e-commerce
A. Bilgihan, “Gen y customer loyalty in online shopping: An integrated model of trust, user experience and branding,” Comput. Human Behav., vol. 61, pp. 103–113, 2016, doi: 10.1016/j.chb.2016.03.014.
Y. F. Chen and C. J. Wu, “Influence of website design on consumer emotion and purchase intention in travel websites,” Int. J. Technol. Hum. Interact., vol. 12, no. 4, pp. 15–29, 2016, doi: 10.4018/IJTHI.2016100102.
G. Van Noort, H. A. M. Voorveld, and E. A. van Reijmersdal, “Interactivity in Brand Web Sites: Cognitive, Affective, and Behavioral Responses Explained by Consumers’ Online Flow Experience,” J. Interact. Mark., vol. 26, no. 4, pp. 223–234, 2012, doi: 10.1016/j.intmar.2011.11.002.
S. Rose, M. Clark, P. Samouel, and N. Hair, “Online Customer Experience in e-Retailing: An empirical model of Antecedents and Outcomes,” J. Retail., vol. 88, no. 2, pp. 308–322, 2012, doi: 10.1016/j.jretai.2012.03.001.
V. D. Tran and Q. H. Vu, “Inspecting the relationship among e-service quality, e-trust, e-customer satisfaction and behavioral intentions of online shopping customers,” Glob. Bus. Financ. Rev., vol. 24, no. 3, pp. 29–42, 2019, doi: 10.17549/gbfr.2019.24.3.29.
G. Taher, “E-commerce: advantages and limitations,” Int. J. Acad. Res. Account. Financ. Manag. Sci., vol. 11, no. 1, pp. 153–165, 2021.
M. Yan, R. Filieri, and M. Gorton, “Continuance intention of online technologies: A systematic literature review,” Int. J. Inf. Manage., vol. 58, p. 102315, 2021.
J. M. Spector and C. Kim, “Technologies for intentional learning: Beyond a cognitive perspective,” Aust. J. Educ., vol. 58, no. 1, pp. 9–22, 2014.
P. Gallina, N. Bellotto, and M. Di Luca, “Progressive co-adaptation in human-machine interaction,” in 2015 12th International Conference on Informatics in Control, Automation and Robotics (ICINCO), 2015, vol. 2, pp. 362–368.
S. J. Barnes, A. D. Pressey, and E. Scornavacca, “Mobile ubiquity: Understanding the relationship between cognitive absorption, smartphone addiction and social network services,” Comput. Human Behav., vol. 90, pp. 246–258, 2019.
P. de Bérail, M. Guillon, and C. Bungener, “The relations between YouTube addiction, social anxiety and parasocial relationships with YouTubers: A moderated-mediation model based on a cognitive-behavioral framework,” Comput. Human Behav., vol. 99, pp. 190–204, 2019.
B. Zhu, S. Kowatthanakul, and P. Satanasavapak, “Generation Y consumer online repurchase intention in Bangkok: Based on Stimulus-Organism-Response (SOR) model,” Int. J. Retail Distrib. Manag., vol. 48, no. 1, pp. 53–69, 2020.
J. U. Islam, S. Shahid, A. Rasool, Z. Rahman, I. Khan, and R. A. Rather, “Impact of website attributes on customer engagement in banking: a solicitation of stimulus-organism-response theory,” Int. J. Bank Mark., vol. 38, no. 6, pp. 1279–1303, 2020.
A. Mehrabian and J. A. Russell, “A measure of arousal seeking tendency,” Environ. Behav., vol. 5, no. 3, pp. 315–333, 1973, doi: 10.1177/001391657300500303.
C. L. Hsu, K. C. Chang, and M. C. Chen, “The impact of website quality on customer satisfaction and purchase intention: Perceived playfulness and perceived flow as mediators,” Inf. Syst. E-bus. Manag., vol. 10, no. 4, pp. 549–570, 2012, doi: 10.1007/s10257-011-0181-5.
F. Ali, “Hotel website quality, perceived flow, customer satisfaction and purchase intention,” J. Hosp. Tour. Technol., vol. 7, no. 2, pp. 213–228, 2016, doi: 10.1108/JHTT-02-2016-0010.
L. Seonjeong Ally, J. Miyoung, and J. Myunghee Mindy, “Effects of experiential stimuli on customers’ responses: An example of bed and breakfast websites,” J. Hosp. Tour. Technol., vol. 7, no. 4, 2016, doi: 10.1108/JHTT-08-2016-0039.
S. H. Chang, W. H. Chih, D. K. Liou, and Y. T. Yang, “The mediation of cognitive attitude for online shopping,” Inf. Technol. People, vol. 29, no. 3, pp. 618–646, 2016, doi: 10.1108/ITP-08-2014-0172.
J. Li et al., “Sustainability of China’s singles day shopping festivals: Exploring the moderating effect of fairness atmospherics on consumers’ continuance participation,” Sustain., vol. 12, no. 7, pp. 1–25, 2020, doi: 10.3390/su12072644.
Y. Liu, Q. Li, T. Edu, L. Jozsa, and I. C. Negricea, “Mobile shopping platform characteristics as consumer behavior determinants,” Asia Pacific J. Mark. Logist., vol. 32, no. 7, pp. 1565–1587, 2020, doi: 10.1108/APJML-05-2019-0308.
N. Ligaraba, B. Nyagadza, D. Dӧrfling, and Q. M. Zulu, “Factors influencing re-usage intention of online and mobile grocery shopping amongst young adults in South Africa,” Arab Gulf J. Sci. Res., vol. 41, no. 3, pp. 389–415, 2023, doi: 10.1108/AGJSR-06-2022-0088.
S. Kumar, A. Jain, and J. K. Hsieh, “Impact of apps aesthetics on revisit intentions of food delivery apps: The mediating role of pleasure and arousal,” J. Retail. Consum. Serv., vol. 63, p. 102686, 2021, doi: https://doi.org/10.1016/j.jretconser.2021.102686.
F. D. Davis, “Perceived usefulness, perceived ease of use, and user acceptance of information technology,” MIS Q., pp. 319–340, 1989.
S. Liao, J.-C. Hong, M.-H. Wen, and Y.-C. Pan, “Applying technology acceptance model (TAM) to explore users’ behavioral intention to adopt a performance assessment system for E-book production,” EURASIA J. Math. Sci. Technol. Educ., vol. 14, no. 10, p. em1601, 2018.
J. Ranellucci, J. M. Rosenberg, and E. G. Poitras, “Exploring pre‐service teachers’ use of technology: The technology acceptance model and expectancy–value theory,” J. Comput. Assist. Learn., vol. 36, no. 6, pp. 810–824, 2020.
B. Foroughi, M. Iranmanesh, and S. S. Hyun, “Understanding the determinants of mobile banking continuance usage intention,” J. Enterp. Inf. Manag., vol. 32, no. 6, pp. 1015–1033, 2019, doi: 10.1108/JEIM-10-2018-0237.
S. H. Jung, J. H. Kim, H. N. Cho, H. W. Lee, and H. J. Choi, “Brand personality of korean dance and sustainable behavioral intention of global consumers in four countries: Focusing on the technological acceptance model,” Sustainability, vol. 13, no. 20, 2021, doi: https://doi.org/10.3390/su132011160.
D. Morales, A. A. Cotas, and I. Esteban-Millat, “The effect of flow experience in the adoption of online supermarkets applying the technology acceptance model (TAM),” Quest. Public., vol. 6, no. 32, pp. 41–54, 2023.
A. Aggarwal and M. Rahul, “Impact of perceived usability and perceived information quality on Indian consumer purchase intentions in online shopping: implication of TAM and SOR theory,” Int. J. Technol. Transf. Commer., vol. 15, no. 2, pp. 160–183, 2017.
S.-H. Jeong and J.-Y. Chung, “Integrated technology acceptance model (TAM) of sports team smartphone application (STSA) in the stimulus organism response (SOR) framework,” J. Phys. Educ. Sport, vol. 22, no. 9, pp. 2152–2161, 2022.
V. Arghashi and C. A. Yuksel, “Interactivity, Inspiration, and Perceived Usefulness! How retailers’ AR-apps improve consumer engagement through flow,” J. Retail. Consum. Serv., vol. 64, p. 102756, 2022.
D. Scarpi and D. Scarpi, “A literature review of hedonic and utilitarian shopping orientation,” Hedonism, Util. Consum. Behav. Explor. Consequences Cust. Orientat., pp. 7–40, 2020.
C. Flavián, S. Ibáñez-Sánchez, and C. Orús, “The impact of virtual, augmented and mixed reality technologies on the customer experience,” J. Bus. Res., vol. 100, pp. 547–560, 2019.
J. He et al., “The first high-resolution meteorological forcing dataset for land process studies over China,” Scientific data. nature.com, 2020.
G. A. Lucas, G. L. Lunardi, and D. B. Dolci, “From e-commerce to m-commerce: An analysis of the user’s experience with different access platforms,” Electron. Commer. Res. Appl., vol. 58, p. 101240, 2023.
B. Taneja, “The digital edge for M-commerce to replace E-commerce,” in Emerging challenges, solutions, and best practices for digital enterprise transformation, IGI Global, 2021, pp. 299–318.
T. Haryanti and A. P. Subriadi, “Factors and theories for E-commerce adoption: A literature review,” Int. J. Electron. Commer. Stud., vol. 11, no. 2, pp. 87–106, 2020.
F. D. Davis, R. P. Bagozzi, and P. R. Warshaw, “User acceptance of computer technology: A comparison of two theoretical models,” Manage. Sci., vol. 35, no. 8, pp. 982–1003, 1989.
R. A. Westbrook and W. C. Black, “A motivation-based shopper typology,” Retail. Crit. concepts. Environ. Retail., vol. 2, p. 82, 2002.
S. Purchase and T. Volery, “Marketing innovation: a systematic review,” J. Mark. Manag., vol. 36, no. 9–10, pp. 763–793, 2020.
P. Kotler, W. Pfoertsch, U. Sponholz, P. Kotler, W. Pfoertsch, and U. Sponholz, “The new paradigm: H2H marketing,” H2H Mark. Genes. Human-to-Human Mark., pp. 29–90, 2021.
P. K. Sinha, “Shopping orientation in the evolving Indian market,” Vikalpa, vol. 28, no. 2, pp. 13–22, 2003, doi: 10.1177/0256090920030202.
Büttner, Oliver & Florack, Arnd & Goeritz, “Shopping Orientation as a Stable Consumer Disposition and Its Influence on Consumers’ Evaluations of Retailer Communication,” Eur. J. Mark., vol. 48, pp. 1–39, 2013.
T. Ahn, Y. Ik Suh, J. K. Lee, and P. M. Pedersen, “Understanding purchasing intentions in secondary sports ticket websites,” Int. J. Sport. Mark. Spons., vol. 16, no. 1, pp. 35–49, 2014.
K. M. Chu and B. J. C. Yuan, “The effects of perceived interactivity on e-trust and e-consumer behaviors: The application of fuzzy linguistic scale,” J. Electron. Commer. Res., vol. 14, no. 1, pp. 124–136, 2013.
T. Ahn, M. Hong, and P. M. Pedersen, “Effects of perceived interactivity and web organization on user attitudes,” Eur. Sport Manag. Q., vol. 14, no. 2, pp. 111–128, 2014, doi: 10.1080/16184742.2014.880496.
D. L. Xu-Priour and G. Cliquet, “In-store shopping experience in China and France: The impact of habituation in an emerging country,” Int. J. Retail Distrib. Manag., vol. 41, no. 9, pp. 706–732, 2013, doi: 10.1108/IJRDM-05-2013-0108.
J. Ai, L. Yan, Y. Hu, and Y. Liu, “An investigation into the effects of destination sensory experiences at visitors’ digital engagement: empirical evidence from sanya, China,” Front. Psychol., vol. 13, p. 942078, 2022.
Y.-M. Chen, T.-H. Hsu, and Y.-J. Lu, “Impact of flow on mobile shopping intention,” J. Retail. Consum. Serv., vol. 41, pp. 281–287, 2018.
N.-H. Chen and Y.-W. Hung, “Online shopping orientation and purchase behavior for high-touch products,” Int. J. Electron. Commer. Stud., vol. 6, no. 2, pp. 187–202, 2015.
N. S. Terblanche, “Revisiting the supermarket in-store customer shopping experience,” J. Retail. Consum. Serv., vol. 40, no. June 2017, pp. 48–59, 2018, doi: 10.1016/j.jretconser.2017.09.004.
M. M. Luo, J. S. Chen, R. K. H. Ching, and C. C. Liu, “An examination of the effects of virtual experiential marketing on online customer intentions and loyalty,” Serv. Ind. J., vol. 31, no. 13, pp. 2163–2191, 2011, doi: 10.1080/02642069.2010.503885.
K. Yang, H. J. M. Kim, and J. Zimmerman, “Emotional branding on fashion brand websites: harnessing the Pleasure-Arousal-Dominance (P-A-D) model,” J. Fash. Mark. Manag., vol. 24, no. 4, pp. 555–570, 2020, doi: 10.1108/JFMM-03-2019-0055.
A. V. S. Madhav and A. K. Tyagi, “The World with Future Technologies (Post-COVID-19): Open Issues, Challenges, and the Road Ahead,” Intell. Interact. Multimed. Syst. e-Healthcare Appl., pp. 411–452, 2021.
J. W. Creswell and J. D. Creswell, Research design: Qualitative, quantitative, and mixed methods approaches. Sage publications, 2017.
P. S. Levy and S. Lemeshow, Sampling of populations: methods and applications. John Wiley & Sons, 2013.
A. Joshi, S. Kale, S. Chandel, and D. K. Pal, “Likert scale: Explored and explained,” Br. J. Appl. Sci. Technol., vol. 7, no. 4, p. 396, 2015.
H. Taherdoost, “Validity and reliability of the research instrument; how to test the validation of a questionnaire/survey in a research,” How to test Valid. a Quest. a Res. (August 10, 2016), 2016.
L. Cohen, L. Manion, and K. Morrison, “Validity and reliability,” in Research methods in education, Routledge, 2017, pp. 245–284.
K. Hamacher and R. Buchkremer, “Measuring online sensory consumer experience: introducing the Online Sensory Marketing Index (OSMI) as a structural modeling approach,” J. Theor. Appl. Electron. Commer. Res., vol. 17, no. 2, pp. 751–772, 2022.
Copyright (c) 2025 The Authors. Published by Universitas Airlangga.
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
All accepted papers will be published under a Creative Commons Attribution 4.0 International (CC BY 4.0) License. Authors retain copyright and grant the journal right of first publication. CC-BY Licenced means lets others to Share (copy and redistribute the material in any medium or format) and Adapt (remix, transform, and build upon the material for any purpose, even commercially).
