IDEAS home Printed from https://ideas.repec.org/a/gam/jjrfmx/v15y2022i10p440-d928166.html
   My bibliography  Save this article

Social Networks Marketing, Value Co-Creation, and Consumer Purchase Behavior: Combining PLS-SEM and NCA

Author

Listed:
  • Farzin Arbabi

    (Department of Economics, Central Tehran Branch, Islamic Azad University, Tehran 1955847781, Iran)

  • Seyed Mohammad Khansari

    (Department of Economics, Faculty of Administrative Sciences and Economics, Shahid Ashrafi Esfahani University, Isfahan 4999981799, Iran)

  • Aidin Salamzadeh

    (Department of Business Management, Faculty of Management, University of Tehran, Tehran 141556311, Iran)

  • Abbas Gholampour

    (The Innovation and Entrepreneurship Research Lab, London EC4N 7TW, UK)

  • Pejman Ebrahimi

    (Doctoral School of Economic and Regional Sciences, Hungarian University of Agriculture and Life Sciences (MATE), 2100 Gödöllő, Hungary)

  • Maria Fekete-Farkas

    (Institute of Agricultural and Food Economics, Hungarian University of Agriculture and Life Sciences (MATE), 2100 Gödöllő, Hungary)

Abstract

Given the mediating role of value co-creation, this paper tries to demonstrate how social network marketing (SNM) could influence consumer purchase behavior (CPB). The proposed hypotheses are empirically tested in this study using a PLS-SEM and Necessary Condition Analysis (NCA) method combination. The novel methodology adopted in this study includes the use of NCA, IPMA matrix, permutation test, CTA, and FIMIX. The assessment of the outer model, the inner model, the NCA matrix, and the IPMA matrix are the four steps that the paper takes. Instagram users with prior experience making purchases online made up the statistical population of the study. Four hundred twenty-seven questionnaires were analyzed by SmartPLS3 software. Based on the findings, SNM positively and significantly influenced economic, enjoyment, and relational values. Furthermore, these three types of values significantly and directly influenced CPB. For CPB, the model accounted for 73.8% of the variance. The model had high predictive power because it outperformed the PLS-SEM benchmark for all of the target construct’s indicators in terms of root mean square error (RMSE). According to the NCA’s findings, SNM, economic, recreational, and relational values are necessary conditions for CPB that are meaningful (d ≥ 0.1) and significant ( p < 0.05). Four prerequisites must be met for CPB to reach a 50% level: relational value at no less than 8.3%, enjoyment value at no less than 16.7%, economic value at no less than 33.3%, and SNM at no less than 31.1%. The highest importance score for SNM is shown to be 0.738, which means that if Instagram channels improve their SNM performance by one unit point, their overall SNM will also improve by 0.738.

Suggested Citation

  • Farzin Arbabi & Seyed Mohammad Khansari & Aidin Salamzadeh & Abbas Gholampour & Pejman Ebrahimi & Maria Fekete-Farkas, 2022. "Social Networks Marketing, Value Co-Creation, and Consumer Purchase Behavior: Combining PLS-SEM and NCA," JRFM, MDPI, vol. 15(10), pages 1-21, September.
  • Handle: RePEc:gam:jjrfmx:v:15:y:2022:i:10:p:440-:d:928166
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1911-8074/15/10/440/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1911-8074/15/10/440/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ali Moghadamzadeh & Pejman Ebrahimi & Soodabeh Radfard & Aidin Salamzadeh & Datis Khajeheian, 2020. "Investigating the Role of Customer Co-Creation Behavior on Social Media Platforms in Rendering Innovative Services," Sustainability, MDPI, vol. 12(17), pages 1-20, August.
    2. Arora, Anuja & Bansal, Shivam & Kandpal, Chandrashekhar & Aswani, Reema & Dwivedi, Yogesh, 2019. "Measuring social media influencer index- insights from facebook, Twitter and Instagram," Journal of Retailing and Consumer Services, Elsevier, vol. 49(C), pages 86-101.
    3. Mor Naaman & Hila Becker & Luis Gravano, 2011. "Hip and trendy: Characterizing emerging trends on Twitter," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(5), pages 902-918, May.
    4. Casper Ferm, Lars-Erik & Thaichon, Park, 2021. "Value co-creation and social media: Investigating antecedents and influencing factors in the U.S. retail banking industry," Journal of Retailing and Consumer Services, Elsevier, vol. 61(C).
    5. Weismueller, Jason & Harrigan, Paul & Wang, Shasha & Soutar, Geoffrey N., 2020. "Influencer endorsements: How advertising disclosure and source credibility affect consumer purchase intention on social media," Australasian marketing journal, Elsevier, vol. 28(4), pages 160-170.
    6. Sheth, Jagdish & Kellstadt, Charles H., 2021. "Next frontiers of research in data driven marketing: Will techniques keep up with data tsunami?," Journal of Business Research, Elsevier, vol. 125(C), pages 780-784.
    7. Buchak, Greg & Matvos, Gregor & Piskorski, Tomasz & Seru, Amit, 2018. "Fintech, regulatory arbitrage, and the rise of shadow banks," Journal of Financial Economics, Elsevier, vol. 130(3), pages 453-483.
    8. Mor Naaman & Hila Becker & Luis Gravano, 2011. "Hip and trendy: Characterizing emerging trends on Twitter," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(5), pages 902-918, May.
    9. Sambashiva Rao Kunja & Acharyulu GVRK, 2018. "Examining the effect of eWOM on the customer purchase intention through value co-creation (VCC) in social networking sites (SNSs)," Management Research Review, Emerald Group Publishing Limited, vol. 43(3), pages 245-269, March.
    10. Gustafsson, Veronika & Khan, Mohammad Saud, 2017. "Monetising blogs: Enterprising behaviour, co-creation of opportunities and social media entrepreneurship," Journal of Business Venturing Insights, Elsevier, vol. 7(C), pages 26-31.
    11. Shmueli, Galit & Ray, Soumya & Velasquez Estrada, Juan Manuel & Chatla, Suneel Babu, 2016. "The elephant in the room: Predictive performance of PLS models," Journal of Business Research, Elsevier, vol. 69(10), pages 4552-4564.
    12. L. G. Pee, 2016. "Customer co-creation in B2C e-commerce: does it lead to better new products?," Electronic Commerce Research, Springer, vol. 16(2), pages 217-243, June.
    13. Zhu, Yu-Qian & Chen, Houn-Gee, 2015. "Social media and human need satisfaction: Implications for social media marketing," Business Horizons, Elsevier, vol. 58(3), pages 335-345.
    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. Nour El Houda Ben Amor & Mohamed Nabil Mzoughi, 2023. "Do Millennials’ Motives for Using Snapchat Influence the Effectiveness of Snap Ads?," SAGE Open, , vol. 13(3), pages 21582440231, July.
    2. Jan Dul & Sven Hauff & Ricarda B. Bouncken, 2023. "Necessary condition analysis (NCA): review of research topics and guidelines for good practice," Review of Managerial Science, Springer, vol. 17(2), pages 683-714, February.

    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. Zia, Syeda Hamna & Muneer, Naima & Siddiqui, Amna & Huda, Rozmeen, 2022. "The Impact of Perceived Social Media Activities On Consumer-Based Brand Equity: A Perspective from Emerging Economy," MPRA Paper 112346, University Library of Munich, Germany.
    2. Yong Wang & Shamim Chowdhury Ahmed & Shejun Deng & Haizhong Wang, 2019. "Success of Social Media Marketing Efforts in Retaining Sustainable Online Consumers: An Empirical Analysis on the Online Fashion Retail Market," Sustainability, MDPI, vol. 11(13), pages 1-27, June.
    3. Godey, Bruno & Manthiou, Aikaterini & Pederzoli, Daniele & Rokka, Joonas & Aiello, Gaetano & Donvito, Raffaele & Singh, Rahul, 2016. "Social media marketing efforts of luxury brands: Influence on brand equity and consumer behavior," Journal of Business Research, Elsevier, vol. 69(12), pages 5833-5841.
    4. Elvin Sheak & Sham Abdulrazak, 2023. "The Influence of Social Media Marketing Activities on TikTok in Raising Brand Awareness," Tržište/Market, Faculty of Economics and Business, University of Zagreb, vol. 35(1), pages 93-110.
    5. Pejman Ebrahimi & Datis Khajeheian & Maria Fekete-Farkas, 2021. "A SEM-NCA Approach towards Social Networks Marketing: Evaluating Consumers’ Sustainable Purchase Behavior with the Moderating Role of Eco-Friendly Attitude," IJERPH, MDPI, vol. 18(24), pages 1-21, December.
    6. Abdulla H. Fetais & Raed S. Algharabat & Abdullah Aljafari & Nripendra P. Rana, 2023. "Do Social Media Marketing Activities Improve Brand Loyalty? An Empirical Study on Luxury Fashion Brands," Information Systems Frontiers, Springer, vol. 25(2), pages 795-817, April.
    7. Meimona Abdelrhim Bushara & Ahmed Hassan Abdou & Thowayeb H. Hassan & Abu Elnasr E. Sobaih & Abdullah Saleh Mohammed Albohnayh & Waleed Ghazi Alshammari & Mohammed Aldoreeb & Ahmed Anwar Elsaed & Moha, 2023. "Power of Social Media Marketing: How Perceived Value Mediates the Impact on Restaurant Followers’ Purchase Intention, Willingness to Pay a Premium Price, and E-WoM?," Sustainability, MDPI, vol. 15(6), pages 1-22, March.
    8. Faseeh Amin Beig & Mohammad Furqan Khan, 2022. "Romancing the Brands on Social Media," Global Business Review, International Management Institute, vol. 23(3), pages 841-862, June.
    9. Shuo Xu & Liyuan Hao & Xin An & Hongshen Pang & Ting Li, 2020. "Review on emerging research topics with key-route main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 607-624, January.
    10. Huan-Kai Peng & Hao-Chih Lee & Jia-Yu Pan & Radu Marculescu, 2016. "Data-Driven Engineering of Social Dynamics: Pattern Matching and Profit Maximization," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-21, January.
    11. Jiayin Pei & Guang Yu & Xianyun Tian & Maureen Renee Donnelley, 2017. "A new method for early detection of mass concern about public health issues," Journal of Risk Research, Taylor & Francis Journals, vol. 20(4), pages 516-532, April.
    12. Guan, Jiancheng & Liu, Na, 2015. "Invention profiles and uneven growth in the field of emerging nano-energy," Energy Policy, Elsevier, vol. 76(C), pages 146-157.
    13. Chen, Long & Huang, Jiahui & Jing, Peng & Wang, Bichen & Yu, Xiaozhou & Zha, Ye & Jiang, Chengxi, 2023. "Changing or unchanging Chinese attitudes toward ride-hailing? A social media analytics perspective from 2018 to 2021," Transportation Research Part A: Policy and Practice, Elsevier, vol. 178(C).
    14. Huan-Kai Peng & Radu Marculescu, 2015. "Multi-Scale Compositionality: Identifying the Compositional Structures of Social Dynamics Using Deep Learning," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-28, April.
    15. Tyler H. McCormick & Hedwig Lee & Nina Cesare & Ali Shojaie & Emma S. Spiro, 2017. "Using Twitter for Demographic and Social Science Research: Tools for Data Collection and Processing," Sociological Methods & Research, , vol. 46(3), pages 390-421, August.
    16. Aw, Eugene Cheng-Xi & Chuah, Stephanie Hui-Wen, 2021. "“Stop the unattainable ideal for an ordinary me!” fostering parasocial relationships with social media influencers: The role of self-discrepancy," Journal of Business Research, Elsevier, vol. 132(C), pages 146-157.
    17. Xiaodong Cao & Piers MacNaughton & Zhengyi Deng & Jie Yin & Xi Zhang & Joseph G. Allen, 2018. "Using Twitter to Better Understand the Spatiotemporal Patterns of Public Sentiment: A Case Study in Massachusetts, USA," IJERPH, MDPI, vol. 15(2), pages 1-15, February.
    18. Yuheng Hu & Yili Hong, 2022. "SHEDR: An End-to-End Deep Neural Event Detection and Recommendation Framework for Hyperlocal News Using Social Media," INFORMS Journal on Computing, INFORMS, vol. 34(2), pages 790-806, March.
    19. Cheung, Man Lai & Leung, Wilson K.S. & Aw, Eugene Cheng-Xi & Koay, Kian Yeik, 2022. "“I follow what you post!†: The role of social media influencers’ content characteristics in consumers' online brand-related activities (COBRAs)," Journal of Retailing and Consumer Services, Elsevier, vol. 66(C).
    20. Pejman Ebrahimi & Khadija Aya Hamza & Eva Gorgenyi-Hegyes & Hadi Zarea & Maria Fekete-Farkas, 2021. "Consumer Knowledge Sharing Behavior and Consumer Purchase Behavior: Evidence from E-Commerce and Online Retail in Hungary," Sustainability, MDPI, vol. 13(18), pages 1-20, 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:gam:jjrfmx:v:15:y:2022:i:10:p:440-:d:928166. 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.