IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i23p15813-d986514.html
   My bibliography  Save this article

Factors of the Adoption of O2O Service Platforms: Evidence from Small Businesses in Korea

Author

Listed:
  • Sangho Lee

    (Gwangsan Business Support Center, Gwangju 62274, Republic of Korea)

  • Cheolho Yoon

    (Department of Business Administration, Mokpo National University, Muan 58554, Republic of Korea)

Abstract

O2O service platforms, which combine online and offline channels to provide more convenient services, are drawing attention as a new way of commerce that can revitalize small businesses that are losing competitiveness and struggling due to the coronavirus disease 2019 pandemic. In this study, we investigated and empirically analyzed the factors affecting the adoption of O2O service platforms in small businesses. We developed a research model that combines the technology acceptance model (TAM), an individual-level theory of IT acceptance, and the technology-organization-environment (TOE) framework, an organizational-level theory of information systems adoption. Data from 279 valid questionnaires were collected from small business owners and analyzed using structural equation modeling. The results show that the technical characteristics of the TOE framework, namely, relative advantage, compatibility, and trialability, and small business owners’ characteristics, namely, innovativeness, risk-taking tendency, and IT knowledge, affect the adoption of O2O service platforms through perceived usefulness and perceived ease of use. The environmental variables of the TOE framework, namely, government support, digital environment change, and competitive pressure, affect the adoption of O2O service platforms through subjective norms. We identify practical implications for the adoption of O2O service platforms by small businesses.

Suggested Citation

  • Sangho Lee & Cheolho Yoon, 2022. "Factors of the Adoption of O2O Service Platforms: Evidence from Small Businesses in Korea," Sustainability, MDPI, vol. 14(23), pages 1-18, November.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:23:p:15813-:d:986514
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/23/15813/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/23/15813/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Cheolho Yoon & Dongsup Lim, 2020. "An empirical study on factors affecting customers’ acceptance of internet-only banks in Korea," Cogent Business & Management, Taylor & Francis Journals, vol. 7(1), pages 1792259-179, January.
    2. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    3. Bang Nam Jeon & Kyeong Seok Han & Myung Jin Lee, 2006. "Determining factors for the adoption of e-business: the case of SMEs in Korea," Applied Economics, Taylor & Francis Journals, vol. 38(16), pages 1905-1916.
    4. Kevin Zhu & Kenneth L. Kraemer, 2005. "Post-Adoption Variations in Usage and Value of E-Business by Organizations: Cross-Country Evidence from the Retail Industry," Information Systems Research, INFORMS, vol. 16(1), pages 61-84, March.
    5. Yunji Moon & Deborah J. Armstrong, 2020. "Service quality factors affecting customer attitudes in online-to-offline commerce," Information Systems and e-Business Management, Springer, vol. 18(1), pages 1-34, March.
    6. Ruivo, Pedro & Oliveira, Tiago & Neto, Miguel, 2014. "Examine ERP post-implementation stages of use and value: Empirical evidence from Portuguese SMEs," International Journal of Accounting Information Systems, Elsevier, vol. 15(2), pages 166-184.
    7. One-Ki (Daniel) Lee & Mo (Winnie) Wang & Kai H. Lim & Zeyu (Jerry) Peng, 2009. "Knowledge Management Systems Diffusion in Chinese Enterprises: A Multistage Approach Using the Technology-Organization-Environment Framework," Journal of Global Information Management (JGIM), IGI Global, vol. 17(1), pages 70-84, January.
    8. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
    9. Nurdan Ozaralli & Nancy K. Rivenburgh, 2016. "Entrepreneurial intention: antecedents to entrepreneurial behavior in the U.S.A. and Turkey," Journal of Global Entrepreneurship Research, Springer;UNESCO Chair in Entrepreneurship, vol. 6(1), pages 1-32, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hart O. Awa & Ojiabo Ukoha & Bartholomew C. Emecheta, 2016. "Using T-O-E theoretical framework to study the adoption of ERP solution," Cogent Business & Management, Taylor & Francis Journals, vol. 3(1), pages 1196571-119, December.
    2. Afsay, Akram & Tahriri, Arash & Rezaee, Zabihollah, 2023. "A meta-analysis of factors affecting acceptance of information technology in auditing," International Journal of Accounting Information Systems, Elsevier, vol. 49(C).
    3. Vu Linh Toan Le & Tien Hoang Nguyen & Khanh Duy Pham, 2023. "What Drives Industry 4.0 Technologies Adoption? Evidence from a SEM-Neural Network Approach in the Context of Vietnamese Firms," Sustainability, MDPI, vol. 15(7), pages 1-32, March.
    4. Debora Bettiga & Lucio Lamberti & Emanuele Lettieri, 2020. "Individuals’ adoption of smart technologies for preventive health care: a structural equation modeling approach," Health Care Management Science, Springer, vol. 23(2), pages 203-214, June.
    5. Yu Wang & Shanyong Wang & Jing Wang & Jiuchang Wei & Chenglin Wang, 2020. "An empirical study of consumers’ intention to use ride-sharing services: using an extended technology acceptance model," Transportation, Springer, vol. 47(1), pages 397-415, February.
    6. Paul Juinn Bing Tan, 2013. "Applying the UTAUT to Understand Factors Affecting the Use of English E-Learning Websites in Taiwan," SAGE Open, , vol. 3(4), pages 21582440135, October.
    7. Peter Mantello & Manh-Tung Ho & Minh-Hoang Nguyen & Quan-Hoang Vuong, 2023. "Machines that feel: behavioral determinants of attitude towards affect recognition technology—upgrading technology acceptance theory with the mindsponge model," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-16, December.
    8. Fox, Stephen & Groesser, Stefan N., 2016. "Reframing the relevance of research to practice," European Management Journal, Elsevier, vol. 34(5), pages 457-465.
    9. Mäntymäki, Matti & Salo, Jari, 2013. "Purchasing behavior in social virtual worlds: An examination of Habbo Hotel," International Journal of Information Management, Elsevier, vol. 33(2), pages 282-290.
    10. Fatima Zahra Barrane & Gahima Egide Karuranga & Diane Poulin, 2018. "Technology Adoption and Diffusion: A New Application of the UTAUT Model," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 15(06), pages 1-19, December.
    11. Farida Saleem & Ahmad Adeel & Rizwan Ali & Shabir Hyder, 2018. "Intentions to adopt ecopreneurship: moderating role of collectivism and altruism," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 6(2), pages 517-537, December.
    12. Joan Torrent-Sellens & Cristian Salazar-Concha & Pilar Ficapal-Cusí & Francesc Saigí-Rubió, 2021. "Using Digital Platforms to Promote Blood Donation: Motivational and Preliminary Evidence from Latin America and Spain," IJERPH, MDPI, vol. 18(8), pages 1-17, April.
    13. Garima Malik & A. Sajeevan Rao, 2019. "Extended expectation-confirmation model to predict continued usage of ODR/ride hailing apps: role of perceived value and self-efficacy," Information Technology & Tourism, Springer, vol. 21(4), pages 461-482, December.
    14. Wang, Guoqiang & Tan, Garry Wei-Han & Yuan, Yunpeng & Ooi, Keng-Boon & Dwivedi, Yogesh K., 2022. "Revisiting TAM2 in behavioral targeting advertising: A deep learning-based dual-stage SEM-ANN analysis," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    15. Riffat Ara Zannat Tama & Md Mahmudul Hoque & Ying Liu & Mohammad Jahangir Alam & Mark Yu, 2023. "An Application of Partial Least Squares Structural Equation Modeling (PLS-SEM) to Examining Farmers’ Behavioral Attitude and Intention towards Conservation Agriculture in Bangladesh," Agriculture, MDPI, vol. 13(2), pages 1-22, February.
    16. Scott, Stephanie & Hughes, Paul & Hodgkinson, Ian & Kraus, Sascha, 2019. "Technology adoption factors in the digitization of popular culture: Analyzing the online gambling market," Technological Forecasting and Social Change, Elsevier, vol. 148(C).
    17. Pan Gong & Ningshuang Zeng & Kunhui Ye & Markus König, 2019. "An Empirical Study on the Acceptance of 4D BIM in EPC Projects in China," Sustainability, MDPI, vol. 11(5), pages 1-19, March.
    18. Cabrera-Sánchez, Juan-Pedro & Villarejo-Ramos, à ngel F., 2020. "Acceptance and use of big data techniques in services companies," Journal of Retailing and Consumer Services, Elsevier, vol. 52(C).
    19. Alfiero, Simona & Battisti, Enrico & Ηadjielias, Elias, 2022. "Black box technology, usage-based insurance, and prediction of purchase behavior: Evidence from the auto insurance sector," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    20. Cowan, Kelly R. & Daim, Tugrul U., 2011. "Review of technology acquisition and adoption research in the energy sector," Technology in Society, Elsevier, vol. 33(3), pages 183-199.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:23:p:15813-:d:986514. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.