IDEAS home Printed from https://ideas.repec.org/a/eee/jbrese/v64y2011i11p1190-1194.html
   My bibliography  Save this article

Effects of social influence on consumers' voluntary adoption of innovations prompted by others

Author

Listed:
  • Kim, Sang-Hoon
  • Park, Hyun Jung

Abstract

Research on innovation adoption focuses on voluntary adoption, although non-voluntary or prompted adoption decisions are prevalent in real life, especially for high-tech products and services. This study aims to investigate the effect of social influence on consumers' innovation adoption in the context of prompted adoption. In particular, the present paper models the duration of voluntary adoption as a function of social norms, attractiveness of the prompter, number of prompters, and so on. Prior knowledge is not only a control variable, but also a moderating variable for a few social factors. This paper validates models relying on the illustrative application of a mobile gift service called Gifticon. The results provide much insight for marketing practitioners on how to accelerate consumers' adoption behavior and therefore the diffusion of innovative products.

Suggested Citation

  • Kim, Sang-Hoon & Park, Hyun Jung, 2011. "Effects of social influence on consumers' voluntary adoption of innovations prompted by others," Journal of Business Research, Elsevier, vol. 64(11), pages 1190-1194.
    • Handle: RePEc:eee:jbrese:v:64:y:2011:i:11:p:1190-1194
    DOI: 10.1016/j.jbusres.2011.06.021
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0148296311002086
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jbusres.2011.06.021?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Madhavan Parthasarathy & Anol Bhattacherjee, 1998. "Understanding Post-Adoption Behavior in the Context of Online Services," Information Systems Research, INFORMS, vol. 9(4), pages 362-379, December.
    2. Fred D. Davis & Richard P. Bagozzi & Paul R. Warshaw, 1989. "User Acceptance of Computer Technology: A Comparison of Two Theoretical Models," Management Science, INFORMS, vol. 35(8), pages 982-1003, August.
    3. Kulviwat, Songpol & Bruner II, Gordon C. & Al-Shuridah, Obaid, 2009. "The role of social influence on adoption of high tech innovations: The moderating effect of public/private consumption," Journal of Business Research, Elsevier, vol. 62(7), pages 706-712, July.
    4. David Godes & Dina Mayzlin, 2004. "Using Online Conversations to Study Word-of-Mouth Communication," Marketing Science, INFORMS, vol. 23(4), pages 545-560, June.
    5. Kieran Mathieson, 1991. "Predicting User Intentions: Comparing the Technology Acceptance Model with the Theory of Planned Behavior," Information Systems Research, INFORMS, vol. 2(3), pages 173-191, September.
    6. McCracken, Grant, 1989. "Who Is the Celebrity Endorser? Cultural Foundations of the Endorsement Process," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 16(3), pages 310-321, December.
    7. Randolph B. Cooper & Robert W. Zmud, 1990. "Information Technology Implementation Research: A Technological Diffusion Approach," Management Science, INFORMS, vol. 36(2), pages 123-139, February.
    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. Bearden, William O & Etzel, Michael J, 1982. "Reference Group Influence on Product and Brand Purchase Decisions," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 9(2), pages 183-194, September.
    10. Park, C Whan & Lessig, V Parker, 1977. "Students and Housewives: Differences in Susceptibility to Reference Group Influence," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 4(2), pages 102-110, Se.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Loureiro, Sandra M.C. & Cavallero, Luisa & Miranda, Francisco Javier, 2018. "Fashion brands on retail websites: Customer performance expectancy and e-word-of-mouth," Journal of Retailing and Consumer Services, Elsevier, vol. 41(C), pages 131-141.
    2. Pabitra Chatterjee & Barthelemy Chollet & Olivier Trendel, 2017. "From conformity to reactance: Contingent role of network centrality in consumer-to-consumer influence," Post-Print hal-01589885, HAL.
    3. Pabitra Chatterjee & Barthelemy Chollet & Olivier Trendel, 2017. "From conformity to reactance: Contingent role of network centrality in consumer-to-consumer influence," Grenoble Ecole de Management (Post-Print) hal-01589885, HAL.
    4. Boeuf, Benjamin, 2019. "The impact of mortality anxiety on attitude toward product innovation," Journal of Business Research, Elsevier, vol. 104(C), pages 44-60.
    5. Bhukya, Ramulu & Paul, Justin, 2023. "Social influence research in consumer behavior: What we learned and what we need to learn? – A hybrid systematic literature review," Journal of Business Research, Elsevier, vol. 162(C).
    6. Chatterjee, Pabitra & Chollet, Barthélemy & Trendel, Olivier, 2017. "From conformity to reactance: Contingent role of network centrality in consumer-to-consumer influence," Journal of Business Research, Elsevier, vol. 75(C), pages 86-94.
    7. Willy, Daniel Kyalo & Holm-Müller, Karin, 2013. "Social influence and collective action effects on farm level soil conservation effort in rural Kenya," Ecological Economics, Elsevier, vol. 90(C), pages 94-103.
    8. Kawaljeet Kaur Kapoor & Yogesh K. Dwivedi & Michael D. Williams, 2015. "Examining the role of three sets of innovation attributes for determining adoption of the interbank mobile payment service," Information Systems Frontiers, Springer, vol. 17(5), pages 1039-1056, October.
    9. Elgaaied-Gambier, Leila & Monnot, Elisa & Reniou, Fanny, 2018. "Using descriptive norm appeals effectively to promote green behavior," Journal of Business Research, Elsevier, vol. 82(C), pages 179-191.
    10. Al-Qeisi, Kholoud & Dennis, Charles & Alamanos, Eleftherios & Jayawardhena, Chanaka, 2014. "Website design quality and usage behavior: Unified Theory of Acceptance and Use of Technology," Journal of Business Research, Elsevier, vol. 67(11), pages 2282-2290.
    11. Daniel Kyalo Willy & Arnim Kuhn, 2016. "Technology Adoption Under Variable Weather Conditions — The Case of Rain Water Harvesting in Lake Naivasha Basin, Kenya," Water Economics and Policy (WEP), World Scientific Publishing Co. Pte. Ltd., vol. 2(02), pages 1-25, June.
    12. Fosso Wamba, Samuel & Bhattacharya, Mithu & Trinchera, Laura & Ngai, Eric W.T., 2017. "Role of intrinsic and extrinsic factors in user social media acceptance within workspace: Assessing unobserved heterogeneity," International Journal of Information Management, Elsevier, vol. 37(2), pages 1-13.
    13. Yi, Jisu & Lee, Youseok & Kim, Sang-Hoon, 2019. "Determinants of growth and decline in mobile game diffusion," Journal of Business Research, Elsevier, vol. 99(C), pages 363-372.
    14. Julian M. Müller, 2019. "Comparing Technology Acceptance for Autonomous Vehicles, Battery Electric Vehicles, and Car Sharing—A Study across Europe, China, and North America," Sustainability, MDPI, vol. 11(16), pages 1-17, August.
    15. Xia, Feihong & Chatterjee, Rabikar & Venkatesh, R., 2022. "Clinching the deal: An empirical study of the drivers of diffusion of daily deals," Journal of Business Research, Elsevier, vol. 149(C), pages 824-832.

    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. Bhukya, Ramulu & Paul, Justin, 2023. "Social influence research in consumer behavior: What we learned and what we need to learn? – A hybrid systematic literature review," Journal of Business Research, Elsevier, vol. 162(C).
    2. Banu Demirel & Ayça Kübra Hızarcı Payne, 2018. "Social Innovation Adoption Behavior: The Case of Zumbara," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 15(02), pages 1-19, April.
    3. Mauricio S. Featherman & Nick Hajli, 2016. "Self-Service Technologies and e-Services Risks in Social Commerce Era," Journal of Business Ethics, Springer, vol. 139(2), pages 251-269, December.
    4. Fernandes, Semila & Venkatesh, V.G. & Panda, Rajesh & Shi, Yangyan, 2021. "Measurement of factors influencing online shopper buying decisions: A scale development and validation," Journal of Retailing and Consumer Services, Elsevier, vol. 59(C).
    5. Semila Fernandes & V.G. Venkatesh & Rajesh Panda & Yangyan Shi, 2021. "Measurement of factors influencing online shopper buying decisions: A scale development and validation," Post-Print hal-04455597, HAL.
    6. Rajak, Manindra & Shaw, Krishnendu, 2021. "An extension of technology acceptance model for mHealth user adoption," Technology in Society, Elsevier, vol. 67(C).
    7. Peng, Zeyu & Sun, Yongqiang & Guo, Xitong, 2018. "Antecedents of employees’ extended use of enterprise systems: An integrative view of person, environment, and technology," International Journal of Information Management, Elsevier, vol. 39(C), pages 104-120.
    8. Kulviwat, Songpol & Bruner II, Gordon C. & Al-Shuridah, Obaid, 2009. "The role of social influence on adoption of high tech innovations: The moderating effect of public/private consumption," Journal of Business Research, Elsevier, vol. 62(7), pages 706-712, July.
    9. Jaeki Song & Fatemeh Mariam Zahedi, 2005. "A Theoretical Approach to Web Design in E-Commerce: A Belief Reinforcement Model," Management Science, INFORMS, vol. 51(8), pages 1219-1235, August.
    10. Cristopher Siegfried Kopplin, 2021. "Two heads are better than one: matchmaking tools in coworking spaces," Review of Managerial Science, Springer, vol. 15(4), pages 1045-1069, May.
    11. 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.
    12. Nistor, Cristian, 2013. "A conceptual model for the use of social media in companies," MPRA Paper 44224, University Library of Munich, Germany.
    13. Francisco Rejón-Guardia & Juán Sánchez-Fernández & Francisco Muñoz-Leiva, 2011. "Motivational Factors that influence the Acceptance of Microblogging Social Networks: The µBAM Model," FEG Working Paper Series 06/11, Faculty of Economics and Business (University of Granada).
    14. Kawsar Ahmad & Arifuzzaman Arifuzzaman & Abdullah Al Mamun & Junayed Md Khaled Bin Oalid, 2021. "Impact of consumer’s security, benefits and usefulness towards cashless transaction within Malaysian university student," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 10(2), pages 238-250, March.
    15. Muhammad Ali & Syed Ali Raza & Chin-Hong Puah & Mohd Zaini Abd Karim, 2017. "Islamic home financing in Pakistan: a SEM-based approach using modified TPB model," Housing Studies, Taylor & Francis Journals, vol. 32(8), pages 1156-1177, November.
    16. Rahman Ummeh Habiba Faria Benteh & Zafar Muhammad Khubaib, 2020. "Factors Influencing Uber Adoption In Bangladesh And Pakistan," Open Economics, De Gruyter, vol. 3(1), pages 86-97, January.
    17. Netsanet Haile & Jörn Altmann, 2016. "Structural analysis of value creation in software service platforms," Electronic Markets, Springer;IIM University of St. Gallen, vol. 26(2), pages 129-142, May.
    18. Müller-Seitz, Gordon & Dautzenberg, Kirsti & Creusen, Utho & Stromereder, Christine, 2009. "Customer acceptance of RFID technology: Evidence from the German electronic retail sector," Journal of Retailing and Consumer Services, Elsevier, vol. 16(1), pages 31-39.
    19. McLean, Graeme & Osei-Frimpong, Kofi & Al-Nabhani, Khalid & Marriott, Hannah, 2020. "Examining consumer attitudes towards retailers' m-commerce mobile applications – An initial adoption vs. continuous use perspective," Journal of Business Research, Elsevier, vol. 106(C), pages 139-157.
    20. Minseok Choi & Kyeongseok Han & Jeongil Choi, 2015. "The effects of product attributes and service quality of transportation card solutions on service user’s continuance and word-of-mouth intention," Service Business, Springer;Pan-Pacific Business Association, vol. 9(3), pages 463-490, September.

    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:eee:jbrese:v:64:y:2011:i:11:p:1190-1194. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jbusres .

    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.