IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i24p10619-d464807.html
   My bibliography  Save this article

Influences of Reference Group on Users’ Purchase Intentions in Network Communities: From the Perspective of Trial Purchase and Upgrade Purchase

Author

Listed:
  • Shuiping Ding

    (School of Economics and Management, Tongji University, Shanghai 200092, China
    School of Economics and Management, Yichun University, Yichun 336000, China)

  • Jie Lin

    (School of Economics and Management, Tongji University, Shanghai 200092, China)

  • Zhenyu Zhang

    (School of Economics and Management, Tongji University, Shanghai 200092, China
    School of Automation, Nanjing University of Science & Technology, Nanjing 210094, China)

Abstract

Reference group is an important factor influencing users’ purchase in the network communities. The reference group’s influences involve informative influence and normative influence, and users’ purchases are divided into the trial purchase and upgrade purchase. In different purchases, users have different product information, consumer experience, and purchase attitudes, making different responses to the reference group. Thus, a research model of reference groups’ influences on users’ purchase intentions from the perspective of trial purchase and upgrade purchase is constructed. The model and hypotheses are tested by analyzing 349 valid questionnaires. The results indicate that both informative and normative influences have significant positive effects on users’ trial purchase intentions. Informative influence has a significant positive effect on users’ upgrade intentions, while the normative influence on users’ upgrade purchase intentions is not significant. Both informative influence and normative influence have significant positive effects on trust in the product. Trust in the product has a significant positive effect on trial purchase intentions, but its effect on upgrade purchase intentions is not significant. Purchase involvement positively regulates the relationship between informative influence and trial purchase intentions and negatively regulates the relationship between informative influence and upgrade purchase intentions. The results further enrich the theoretical system of users’ purchase behaviors in a virtual environment. The research can also have important implications for network communities wishing to improve online marketing.

Suggested Citation

  • Shuiping Ding & Jie Lin & Zhenyu Zhang, 2020. "Influences of Reference Group on Users’ Purchase Intentions in Network Communities: From the Perspective of Trial Purchase and Upgrade Purchase," Sustainability, MDPI, vol. 12(24), pages 1-18, December.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:24:p:10619-:d:464807
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/24/10619/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/12/24/10619/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Raghuram Iyengar & Christophe Van den Bulte & Thomas W. Valente, 2011. "Opinion Leadership and Social Contagion in New Product Diffusion," Marketing Science, INFORMS, vol. 30(2), pages 195-212, 03-04.
    2. 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.
    3. Rex P. Bringula & Shirley D. Moraga & Annaliza E. Catacutan & Marilou N. Jamis & Dionito F. Mangao, 2018. "Factors influencing online purchase intention of smartphones: A hierarchical regression analysis," Cogent Business & Management, Taylor & Francis Journals, vol. 5(1), pages 1496612-149, January.
    4. Bilgicer, Tolga & Jedidi, Kamel & Lehmann, Donald R. & Neslin, Scott A., 2015. "Social Contagion and Customer Adoption of New Sales Channels," Journal of Retailing, Elsevier, vol. 91(2), pages 254-271.
    5. Ravi Bapna & Akhmed Umyarov, 2015. "Do Your Online Friends Make You Pay? A Randomized Field Experiment on Peer Influence in Online Social Networks," Management Science, INFORMS, vol. 61(8), pages 1902-1920, August.
    6. Hans Baumgartner, 2012. "Repetitive Purchase Behavior," Springer Books, in: Adamantios Diamantopoulos & Wolfgang Fritz & Lutz Hildebrandt (ed.), Quantitative Marketing and Marketing Management, edition 127, chapter 2, pages 269-286, Springer.
    7. Heidi R. STALLMAN & Harvey S. JAMES Jr, 2017. "Farmers’ Willingness To Cooperate In Ecosystem Service Provision: Does Trust Matter?," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 88(1), pages 5-31, March.
    8. Zaichkowsky, Judith Lynne, 1985. "Measuring the Involvement Construct," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 12(3), pages 341-352, December.
    9. Sinan Aral & Dylan Walker, 2014. "Tie Strength, Embeddedness, and Social Influence: A Large-Scale Networked Experiment," Management Science, INFORMS, vol. 60(6), pages 1352-1370, June.
    10. Lu (Lucy) Yan & Jianping Peng & Yong Tan, 2015. "Network Dynamics: How Can We Find Patients Like Us?," Information Systems Research, INFORMS, vol. 26(3), pages 496-512, September.
    11. Sharad Goel & Daniel G. Goldstein, 2014. "Predicting Individual Behavior with Social Networks," Marketing Science, INFORMS, vol. 33(1), pages 82-93, January.
    12. Jeong-Yeon Lee & Daniel G. Bachrach & Kyle Lewis, 2014. "Social Network Ties, Transactive Memory, and Performance in Groups," Organization Science, INFORMS, vol. 25(3), pages 951-967, June.
    13. Yansong Hu & Christophe Van den Bulte, 2014. "Nonmonotonic Status Effects in New Product Adoption," Marketing Science, INFORMS, vol. 33(4), pages 509-533, July.
    14. Liye Ma & Ramayya Krishnan & Alan L. Montgomery, 2015. "Latent Homophily or Social Influence? An Empirical Analysis of Purchase Within a Social Network," Management Science, INFORMS, vol. 61(2), pages 454-473, February.
    15. Arif, Imtiaz & Aslam, Wajeeha, 2014. "Students' dependence on smart phone and its effect on purchase behavior," MPRA Paper 58919, University Library of Munich, Germany.
    16. Shuiqing Yang, 2016. "Role of transfer-based and performance-based cues on initial trust in mobile shopping services: a cross-environment perspective," Information Systems and e-Business Management, Springer, vol. 14(1), pages 47-70, February.
    17. Wynne W. Chin & Abhijit Gopal & W. David Salisbury, 1997. "Advancing the Theory of Adaptive Structuration: The Development of a Scale to Measure Faithfulness of Appropriation," Information Systems Research, INFORMS, vol. 8(4), pages 342-367, 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. Sarah Gelper & Ralf van der Lans & Gerrit van Bruggen, 2021. "Competition for Attention in Online Social Networks: Implications for Seeding Strategies," Management Science, INFORMS, vol. 67(2), pages 1026-1047, February.
    2. Shan Huang & Sinan Aral & Yu Jeffrey Hu & Erik Brynjolfsson, 2020. "Social Advertising Effectiveness Across Products: A Large-Scale Field Experiment," Marketing Science, INFORMS, vol. 39(6), pages 1142-1165, November.
    3. Chen, Zhen-Yu & Fan, Zhi-Ping & Sun, Minghe, 2019. "Individual-level social influence identification in social media: A learning-simulation coordinated method," European Journal of Operational Research, Elsevier, vol. 273(3), pages 1005-1015.
    4. Tianshu Sun & Sean J. Taylor, 2020. "Displaying things in common to encourage friendship formation: A large randomized field experiment," Quantitative Marketing and Economics (QME), Springer, vol. 18(3), pages 237-271, September.
    5. Yuho Chung & Yiwei Li & Jianmin Jia, 2021. "Exploring embeddedness, centrality, and social influence on backer behavior: the role of backer networks in crowdfunding," Journal of the Academy of Marketing Science, Springer, vol. 49(5), pages 925-946, September.
    6. Che-Wei Liu & Guodong (Gordon) Gao & Ritu Agarwal, 2019. "Unraveling the “Social” in Social Norms: The Conditioning Effect of User Connectivity," Information Systems Research, INFORMS, vol. 30(4), pages 1272-1295, April.
    7. Zhang, Honghong & Fam, Kim-Shyan & Goh, Tiong-Thye & Dai, Xin, 2018. "When are influentials equally influenceable? The strength of strong ties in new product adoption," Journal of Business Research, Elsevier, vol. 82(C), pages 160-170.
    8. Tingting Song & Qian Tang & Jinghua Huang, 2019. "Triadic Closure, Homophily, and Reciprocation: An Empirical Investigation of Social Ties Between Content Providers," Information Systems Research, INFORMS, vol. 30(3), pages 912-926, September.
    9. Li, Feng & Du, Timon Chih-ting & Wei, Ying, 2019. "Offensive pricing strategies for online platforms," International Journal of Production Economics, Elsevier, vol. 216(C), pages 287-304.
    10. Rishika Rishika & Jui Ramaprasad, 2019. "The Effects of Asymmetric Social Ties, Structural Embeddedness, and Tie Strength on Online Content Contribution Behavior," Management Science, INFORMS, vol. 65(7), pages 3398-3422, July.
    11. Muller, Eitan & Peres, Renana, 2019. "The effect of social networks structure on innovation performance: A review and directions for research," International Journal of Research in Marketing, Elsevier, vol. 36(1), pages 3-19.
    12. Park, Minjung, 2019. "Selection bias in estimation of peer effects in product adoption," Journal of choice modelling, Elsevier, vol. 30(C), pages 17-27.
    13. Wang, Le & Luo, Xin (Robert) & Li, Han, 2022. "Envy or conformity? An empirical investigation of peer influence on the purchase of non-functional items in mobile free-to-play games," Journal of Business Research, Elsevier, vol. 147(C), pages 308-324.
    14. Plé, Loïc & Demangeot, Catherine, 2020. "Social contagion of online and offline deviant behaviors and its value outcomes: The case of tourism ecosystems," Journal of Business Research, Elsevier, vol. 117(C), pages 886-896.
    15. Gandal, Neil & Bar-Gill, Sagit, 2017. "Online Exploration, Content Choice & Echo Chambers: An Experiment," CEPR Discussion Papers 11909, C.E.P.R. Discussion Papers.
    16. Valente, Thomas W. & Dyal, Stephanie R. & Chu, Kar-Hai & Wipfli, Heather & Fujimoto, Kayo, 2015. "Diffusion of innovations theory applied to global tobacco control treaty ratification," Social Science & Medicine, Elsevier, vol. 145(C), pages 89-97.
    17. Gupta, Reetika & Mukherjee, Sourjo & Jayarajah, Kasthuri, 2021. "Role of group cohesiveness in targeted mobile promotions," Journal of Business Research, Elsevier, vol. 127(C), pages 216-227.
    18. Pinar Yildirim & Yanhao Wei & Christophe Bulte & Joy Lu, 2020. "Social network design for inducing effort," Quantitative Marketing and Economics (QME), Springer, vol. 18(4), pages 381-417, December.
    19. Kosuke Uetake & Nathan Yang, 2020. "Inspiration from the “Biggest Loser”: Social Interactions in a Weight Loss Program," Marketing Science, INFORMS, vol. 39(3), pages 487-499, May.
    20. Lianren Wu & Jinjie Li & Jiayin Qi & Deli Kong & Xu Li, 2021. "The Role of Opinion Leaders in the Sustainable Development of Corporate-Led Consumer Advice Networks: Evidence from a Chinese Travel Content Community," Sustainability, MDPI, vol. 13(19), pages 1-20, October.

    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:12:y:2020:i:24:p:10619-:d:464807. 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.