Factors influencing consumer's intention towards e-grocery shopping: An extended technology acceptance model approach

Main Article Content

Winda Trisna Ryadi Florentina Kurniasari Kristianus Ade Sudiyono

Abstract

The e-grocery industry in Indonesia is multiplying and is expected to become one of the most important markets in the world. Massive amount of funding for e-grocery start-ups, the high desire of Indonesian consumers to buy grocery products online, and COVID19 are increasing the growth of e-grocery services in Indonesia. Although the desire to use e-grocery services in Indonesia is high, data shows that e-grocery adoption is still far below other e-commerce product categories such as fashion and electronics. Previous research and surveys also show that consumers will return to shopping for wholesale products offline and stop/reduce the use of e-grocery after the COVID19 pandemic. Therefore, this research is interested in examining the factors that can increase the adoption of e-grocery in Indonesia. Quantitative research was conducted using the purposive sampling method and obtained 135 respondents who have ever used e-grocery service/shopping in the JABODETABEK area. Data were analyzed using PLS-SEM (Partial Least Square – Structural Equation Model). The results of this study indicate that perceived risk has a negative effect on Trust. Social Influence, Perceived Usefulness, and Perceived Ease of Use have a positive effect on Trust. Social Influence and Perceived Ease of Use have a positive effect on Perceived Usefulness. However, it turns out that Trust in this study was not proven to affect the intention to use e-grocery services/shopping for grocery products online.

Article Details

How to Cite
RYADI, Winda Trisna; KURNIASARI, Florentina; SUDIYONO, Kristianus Ade. Factors influencing consumer's intention towards e-grocery shopping: An extended technology acceptance model approach. Economics, Management and Sustainability, [S.l.], v. 6, n. 2, p. 146-159, nov. 2021. ISSN 2520-6303. Available at: <https://jems.sciview.net/index.php/jems/article/view/144>. Date accessed: 21 may 2022. doi: https://doi.org/10.14254/jems.2021.6-2.11.
Section
Articles

References

Alalwan, A. A., Baabdullah, A. M., Rana, N. P., Tamilmani, K., & Dwivedi, Y. K. (2018). Examining adoption of mobile internet in Saudi Arabia: Extending TAM with perceived enjoyment, innovativeness and trust. Technology in Society, 55, 100–110. https://doi.org/10.1016/j.techsoc.2018.06.007
Amin, M., Rezaei, S., & Tavana, F. S. (2015). Gender differences and consumer’s repurchase intention: The impact of trust propensity, usefulness and ease of use for implication of innovative online retail. International Journal of Innovation and Learning, 17(2), 217–233. https://doi.org/10.1504/IJIL.2015.067409
Bezirgani, A., & Lachapelle, U. (2020). Qualitative Study on Factors Influencing Aging Population’s Online Grocery Shopping and Mode Choice When Grocery Shopping in Person. Transportation Research Record, 2675(1), 79–92. https://doi.org/10.1177/0361198120964790
Chakraborty, D. (2019). Indian Shoppers’ Attitude Towards Grocery Shopping Apps: A Survey Conducted on Smartphone Users. Metamorphosis: A Journal of Management Research, 18(2), 83–91. https://doi.org/10.1177/0972622519885502
Chaouali, W., Ben Yahia, I., & Souiden, N. (2016). The interplay of counter-conformity motivation, social influence, and trust in customers’ intention to adopt Internet banking services: The case of an emerging country. Journal of Retailing and Consumer Services, 28, 209–218. https://doi.org/10.1016/J.JRETCONSER.2015.10.007
Chen, Y., Yan, X., Fan, W., & Gordon, M. (2015). The joint moderating role of trust propensity and gender on consumers’ online shopping behavior. Computers in Human Behavior, 43, 272–283. https://doi.org/10.1016/j.chb.2014.10.020
Crawford, S. Y. (2003). Internet Pharmacy: Issues of Access, Quality, Costs, and Regulation. Journal of Medical Systems, 27(1), 57–65. https://doi.org/10.1023/A:1021009212905
Daily Social. (2020). Menakar Masa Depan Startup “Online Grocery” di Indonesia. Retrieved from https://dailysocial.id/post/online-grocery-startup-indonesia
Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, Vol. 13(No. 3), 319-340 (22 pages). Retrieved from https://doi.org/10.2307/249008
Dhagarra, D., Goswami, M., & Kumar, G. (2020). Impact of Trust and Privacy Concerns on Technology Acceptance in Healthcare: An Indian Perspective. International Journal of Medical Informatics, 141(April), 104164. https://doi.org/10.1016/j.ijmedinf.2020.104164
Dick, A. S., & Basu, K. (1994). Customer loyalty: Toward an integrated conceptual framework. Journal of the Academy of Marketing Science, 22(2), 99–113. https://doi.org/10.1177/0092070394222001
Driediger, F., & Bhatiasevi, V. (2019). Online grocery shopping in Thailand: Consumer acceptance and usage behavior. Journal of Retailing and Consumer Services, 48(February), 224–237. https://doi.org/10.1016/j.jretconser.2019.02.005
Droogenbroeck, E. Van, & Van Hove, L. (2021). Adoption and usage of E-grocery shopping: A context-specific UTAUT2 model. Sustainability (Switzerland), 13(8). https://doi.org/10.3390/su13084144
Focused, C. (2020). Shopper Sentiments: A September 2020 Global Mood Survey. Retrieved from https://us.moodmedia.com/2020-shopper-sentiment/
Gefen, D., Benbasat, I., & Pavlou, P. A. (2008). A research agenda for trust in online environments. Journal of Management Information Systems, 24(4), 275–286. https://doi.org/10.2753/MIS0742-1222240411
Gutama, W. A., & Dewi Intan, A. P. (2017). Consumer Acceptance Towards Online Grocery Shopping in Malang, East Java, Indonesia. Agricultural Social Economic Journal, 17(1), 23–32. https://doi.org/10.21776/ub.agrise.2017.017.1.4
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (Second Edi). SAGE Publications Ltd.
Jagani, K., Oza, F. V., & Chauhan, H. (2020). Customer Segmentation and Factors Affecting Willingness to Order Private Label Brands: An E-Grocery Shopper’s Perspective. https://doi.org/10.4018/978-1-7998-0257-0.ch011
Kian, T. P., Loong, A. C. W., & Fong, S. W. L. (2019). Customer Purchase Intention on Online Grocery Shopping. International Journal of Academic Research in Business and Social Sciences, 8(12). https://doi.org/10.6007/ijarbss/v8-i12/5260
Kim, J., Ma, Y. J., & Park, J. (2009). Are US consumers ready to adopt mobile technology for fashion goods?: An integrated theoretical approach. Journal of Fashion Marketing and Management, 13(2), 215–230. https://doi.org/10.1108/13612020910957725
Kurniasari, F., & Ryadi, W. T. (2021). Determinants of Indonesian E-Grocery Shopping Behavior After Covid-19 Pandemic Using the Technology Acceptance Model Approach. United International Journal for Research & Technology (UIJRT), 03(01), 12–18. Retrieved from https://uijrt.com/paper/determinants-indonesian-egrocery-shopping-behavior-after-covid19-pandemic-using-technology-acceptance-model-approach
L.E.K Consulting. (2021). Covid-19 a catalyst for growth in Indonesia’s e-grocery market. Retrieved from https://www.consultancy.asia/news/3941/covid-19-a-catalyst-for-growth-in-indonesias-e-grocery-market
Laukkanen, T. (2016). Consumer adoption versus rejection decisions in seemingly similar service innovations: The case of the Internet and mobile banking. Journal of Business Research, 69(7), 2432–2439. https://doi.org/10.1016/j.jbusres.2016.01.013
Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information and Management, 40(3), 191–204. https://doi.org/10.1016/S0378-7206(01)00143-4
Liébana-Cabanillas, F., Sánchez-Fernández, J., & Muñoz-Leiva, F. (2014). Antecedents of the adoption of the new mobile payment systems: The moderating effect of age. Computers in Human Behavior, 35(December), 464–478. https://doi.org/10.1016/j.chb.2014.03.022
Loketkrawee, P., & Bhatiasevi, V. (2018). Elucidating the Behavior of Consumers toward Online Grocery Shopping: The Role of Shopping Orientation. Journal of Internet Commerce, 17(4), 418–445. https://doi.org/10.1080/15332861.2018.1496390
Ma, L. (2021). Understanding non-adopters’ intention to use internet pharmacy: Revisiting the roles of trustworthiness, perceived risk and consumer traits. Journal of Engineering and Technology Management - JET-M, 59(December 2020). https://doi.org/10.1016/j.jengtecman.2021.101613
Mou, J., Shin, D. H., & Cohen, J. F. (2017). Trust and risk in consumer acceptance of e-services. Electronic Commerce Research, 17(2), 255–288. https://doi.org/10.1007/s10660-015-9205-4
Nurhayati-Wolff, H. (2021). Market share of online grocery retail in Indonesia in 2020 with a forecast for 2022. Retrieved from https://www.statista.com/statistics/1227268/indonesia-online-grocery-retail-market-share/
Park, J., Amendah, E., Lee, Y., & Hyun, H. (2019). M-payment service: Interplay of perceived risk, benefit, and trust in service adoption. Human Factors and Ergonomics In Manufacturing, 29(1), 31–43. https://doi.org/10.1002/hfm.20750
Pavlou, P. A. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International Journal of Electronic Commerce, 7(3), 101–134. https://doi.org/10.1080/10864415.2003.11044275
Schepers, J., & Wetzels, M. (2007). A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects. Information & Management, 44(1), 90–103. https://doi.org/10.1016/J.IM.2006.10.007
Seetharaman, A., Kumar, N. K., Palaniappan, S., & Weber, G. (2017). Factors Influencing Behavioural Intention to Use the Mobile Wallet in Singapore. Journal of Applied Economics and Business Research JAEBR, 7(2), 116–136.
Shukla, A., & Sharma, S. K. (2018). Evaluating Consumers’ Adoption of Mobile Technology for Grocery Shopping: An Application of Technology Acceptance Model. Vision SAGE Publications, 22(2), 185–198. https://doi.org/10.1177/0972262918766136
Singh, N., & Sinha, N. (2020). How perceived trust mediates merchant’s intention to use a mobile wallet technology. Journal of Retailing and Consumer Services, 52(June 2019), 101894. https://doi.org/10.1016/j.jretconser.2019.101894
Singh, R., & Rosengren, S. (2020). Why do online grocery shoppers switch? An empirical investigation of drivers of switching in online grocery. Journal of Retailing and Consumer Services, 53(June 2019), 101962. https://doi.org/10.1016/j.jretconser.2019.101962
Suebtimrat, P., & Vongai, R. (2021). An Investigation of Behavioral Intention Towards QR Code Payment in Bangkok, Thailand. Journal of Asian Finance, Economics and Business, 8(1), 939–950. https://doi.org/10.13106/jafeb.2021.vol8.no1.939
The Jakarta Post. (2020). Online grocery shopping to drive e-commerce growth as PSBB reimposed: Experts. Retrieved from https://www.thejakartapost.com/news/2020/09/14/online-grocery-shopping-to-drive-e-commerce-growth-as-psbb-reimposed-experts.html
Vedamani, G. G. (2017). Retail Management (5th editio). Pearson India Education Services Pvt. Ltd.
Venkatesh, V. (2000). Determinants of perceived ease of use : integrating control , intrinsic motivation , acceptance model. Inorganic Chemistry Communications, 11(3), 319–340.
Ventre, I., & Kolbe, D. (2020). The Impact of Perceived Usefulness of Online Reviews, Trust and Perceived Risk on Online Purchase Intention in Emerging Markets: A Mexican Perspective. Journal of International Consumer Marketing, 32(4), 287–299. https://doi.org/10.1080/08961530.2020.1712293
Wu, W. Y., & Ke, C. C. (2015). An online shopping behavior model integrating personality traits, perceived risk, and technology acceptance. Social Behavior and Personality, 43(1), 85–98. https://doi.org/10.2224/sbp.2015.43.1.85
Yang, Q., Pang, C., Liu, L., Yen, D. C., & Michael Tarn, J. (2015). Exploring consumer perceived risk and trust for online payments: An empirical study in China’s younger generation. Computers in Human Behavior, 50, 9–24. https://doi.org/10.1016/J.CHB.2015.03.058
Yousafzai, S. Y., Foxall, G. R., & Pallister, J. G. (2007). Technology acceptance: a meta-analysis of the TAM: Part 1. In Journal of Modelling in Management (Vol. 2). https://doi.org/10.1108/17465660710834453
Zheng, Q., Chen, J., Zhang, R., & Wang, H. H. (2020). What factors affect Chinese consumers’ online grocery shopping? Product attributes, e-vendor characteristics and consumer perceptions. China Agricultural Economic Review, 12(2), 193–213. https://doi.org/10.1108/CAER-09-2018-0201