IDEAS home Printed from https://ideas.repec.org/a/inm/orisre/v24y2013i1p108-127.html
   My bibliography  Save this article

The Effect of Customers' Social Media Participation on Customer Visit Frequency and Profitability: An Empirical Investigation

Author

Listed:
  • Rishika Rishika

    (Mays Business School, Texas A&M University, College Station, Texas 77843)

  • Ashish Kumar

    (Department of Marketing, Aalto University School of Business, FI-00076 Aalto, Finland)

  • Ramkumar Janakiraman

    (Mays Business School, Texas A&M University, College Station, Texas 77843)

  • Ram Bezawada

    (School of Management, State University of New York, Buffalo, New York 14260)

Abstract

In this study we examine the effect of customers' participation in a firm's social media efforts on the intensity of the relationship between the firm and its customers as captured by customers' visit frequency. We further hypothesize and test for the moderating roles of social media activity and customer characteristics on the link between social media participation and the intensity of customer-firm relationship. Importantly, we also quantify the impact of social media participation on customer profitability. We assemble a novel data set that combines customers' social media participation data with individual customer level transaction data. To account for endogeneity that could arise because of customer self-selection, we utilize the propensity score matching technique in combination with difference in differences analysis. Our results suggest that customer participation in a firm's social media efforts leads to an increase in the frequency of customer visits. We find that this participation effect is greater when there are high levels of activity in the social media site and for customers who exhibit a strong patronage with the firm, buy premium products, and exhibit lower levels of buying focus and deal sensitivity. We find that the above set of results holds for customer profitability as well. We discuss theoretical implications of our results and offer prescriptions for managers on how to engage customers via social media. Our study emphasizes the need for managers to integrate knowledge from customers' transactional relationship with their social media participation to better serve customers and create sustainable business value.

Suggested Citation

  • Rishika Rishika & Ashish Kumar & Ramkumar Janakiraman & Ram Bezawada, 2013. "The Effect of Customers' Social Media Participation on Customer Visit Frequency and Profitability: An Empirical Investigation," Information Systems Research, INFORMS, vol. 24(1), pages 108-127, March.
  • Handle: RePEc:inm:orisre:v:24:y:2013:i:1:p:108-127
    DOI: 10.1287/isre.1120.0460
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/isre.1120.0460
    Download Restriction: no

    File URL: https://libkey.io/10.1287/isre.1120.0460?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
    ---><---

    References listed on IDEAS

    as
    1. René Algesheimer & Sharad Borle & Utpal M. Dholakia & Siddharth S. Singh, 2010. "The Impact of Customer Community Participation on Customer Behaviors: An Empirical Investigation," Marketing Science, INFORMS, vol. 29(4), pages 756-769, 07-08.
    2. A. Smith, Jeffrey & E. Todd, Petra, 2005. "Does matching overcome LaLonde's critique of nonexperimental estimators?," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 305-353.
    3. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 605-654.
    4. Sourafel Girma & Holger Görg, 2016. "Evaluating the foreign ownership wage premium using a difference-in-differences matching approach," World Scientific Book Chapters, in: MULTINATIONAL ENTERPRISES AND HOST COUNTRY DEVELOPMENT Volume 53: World Scientific Studies in International Economics, chapter 2, pages 17-32, World Scientific Publishing Co. Pte. Ltd..
    5. Raj Chetty & Adam Looney & Kory Kroft, 2009. "Salience and Taxation: Theory and Evidence," American Economic Review, American Economic Association, vol. 99(4), pages 1145-1177, September.
    6. Sascha O. Becker & Marco Caliendo, 2007. "Sensitivity analysis for average treatment effects," Stata Journal, StataCorp LP, vol. 7(1), pages 71-83, February.
    7. Anjana Susarla & Jeong-Ha Oh & Yong Tan, 2012. "Social Networks and the Diffusion of User-Generated Content: Evidence from YouTube," Information Systems Research, INFORMS, vol. 23(1), pages 23-41, March.
    8. Marco Caliendo & Sabine Kopeinig, 2008. "Some Practical Guidance For The Implementation Of Propensity Score Matching," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 31-72, February.
    9. Rajeev H. Dehejia & Sadek Wahba, 2002. "Propensity Score-Matching Methods For Nonexperimental Causal Studies," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 151-161, February.
    10. Joshua D. Angrist & Jörn-Steffen Pischke, 2009. "Mostly Harmless Econometrics: An Empiricist's Companion," Economics Books, Princeton University Press, edition 1, number 8769.
    11. DiPrete, Thomas A. & Gangl, Markus, 2004. "Assessing bias in the estimation of causal effects: Rosenbaum bounds on matching estimators and instrumental variables estimation with imperfect instruments," Discussion Papers, Research Unit: Labor Market Policy and Employment SP I 2004-101, WZB Berlin Social Science Center.
    12. Eugene W. Anderson & Mary W. Sullivan, 1993. "The Antecedents and Consequences of Customer Satisfaction for Firms," Marketing Science, INFORMS, vol. 12(2), pages 125-143.
    13. Jonathan Gruber, 1994. "The Consumption Smoothing Benefits of Unemployment Insurance," NBER Working Papers 4750, National Bureau of Economic Research, Inc.
    14. Chris Forman & Anindya Ghose & Batia Wiesenfeld, 2008. "Examining the Relationship Between Reviews and Sales: The Role of Reviewer Identity Disclosure in Electronic Markets," Information Systems Research, INFORMS, vol. 19(3), pages 291-313, September.
    15. Marianne Bertrand & Esther Duflo & Sendhil Mullainathan, 2004. "How Much Should We Trust Differences-In-Differences Estimates?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 119(1), pages 249-275.
    16. Shuk Ying Ho & David Bodoff & Kar Yan Tam, 2011. "Timing of Adaptive Web Personalization and Its Effects on Online Consumer Behavior," Information Systems Research, INFORMS, vol. 22(3), pages 660-679, September.
    17. Michael Lechner, 2002. "Some practical issues in the evaluation of heterogeneous labour market programmes by matching methods," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 165(1), pages 59-82, February.
    18. Richard Blundell & Monica Costa Dias, 2000. "Evaluation methods for non-experimental data," Fiscal Studies, Institute for Fiscal Studies, vol. 21(4), pages 427-468, January.
    19. Janiszewski, Chris, 1993. "Preattentive Mere Exposure Effects," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 20(3), pages 376-392, December.
    20. David Godes & Dina Mayzlin, 2004. "Using Online Conversations to Study Word-of-Mouth Communication," Marketing Science, INFORMS, vol. 23(4), pages 545-560, June.
    21. Ruth N. Bolton, 1998. "A Dynamic Model of the Duration of the Customer's Relationship with a Continuous Service Provider: The Role of Satisfaction," Marketing Science, INFORMS, vol. 17(1), pages 45-65.
    22. Abadie, Alberto & Diamond, Alexis & Hainmueller, Jens, 2010. "Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California’s Tobacco Control Program," Journal of the American Statistical Association, American Statistical Association, vol. 105(490), pages 493-505.
    23. Halvorsen, Robert & Palmquist, Raymond, 1980. "The Interpretation of Dummy Variables in Semilogarithmic Equations," American Economic Review, American Economic Association, vol. 70(3), pages 474-475, June.
    24. Kietzmann, Jan H. & Hermkens, Kristopher & McCarthy, Ian P. & Silvestre, Bruno S., 2011. "Social media? Get serious! Understanding the functional building blocks of social media," Business Horizons, Elsevier, vol. 54(3), pages 241-251, May.
    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. Liane Faltermeier & Awudu Abdulai, 2009. "The impact of water conservation and intensification technologies: empirical evidence for rice farmers in Ghana," Agricultural Economics, International Association of Agricultural Economists, vol. 40(3), pages 365-379, May.
    2. Luis Aranda, 2013. "Doubling Up: A Gift or a Shame? Multigenerational Households and Parental Depression of Older Europeans," Working Papers 2013:29, Department of Economics, University of Venice "Ca' Foscari", revised 2013.
    3. Marco Caliendo & Sabine Kopeinig, 2008. "Some Practical Guidance For The Implementation Of Propensity Score Matching," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 31-72, February.
    4. Feddersen, Arne & Maennig, Wolfgang, 2012. "Sectoral labour market effects of the 2006 FIFA World Cup," Labour Economics, Elsevier, vol. 19(6), pages 860-869.
    5. Bagnoli, Lisa, 2019. "Does health insurance improve health for all? Heterogeneous effects on children in Ghana," World Development, Elsevier, vol. 124(C), pages 1-1.
    6. Riccardo Turati, 2020. "Network-based Connectedness and the Diffusion of Cultural Traits," LIDAM Discussion Papers IRES 2020012, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
    7. Duvendack, Maren, 2010. "Smoke and Mirrors: Evidence of Microfinance Impact from an Evaluation of SEWA Bank in India," MPRA Paper 24511, University Library of Munich, Germany.
    8. Ashimwe, Olive, 2016. "An Economic Analysis Of Impact Of Weather Index-Based Crop Insurance On Household Income In Huye District Of Rwanda," Research Theses 265675, Collaborative Masters Program in Agricultural and Applied Economics.
    9. Kodjo Adandohoin & Vigninou Gammadigbe, 2022. "The revenue efficiency consequences of the announcement of a tax transition reform: The case of WAEMU countries," African Development Review, African Development Bank, vol. 34(S1), pages 195-218, July.
    10. Abebaw, Degnet & Fentie, Yibeltal & Kassa, Belay, 2010. "The impact of a food security program on household food consumption in Northwestern Ethiopia: A matching estimator approach," Food Policy, Elsevier, vol. 35(4), pages 286-293, August.
    11. Tommaso Nannicini, 2007. "Simulation-based sensitivity analysis for matching estimators," Stata Journal, StataCorp LP, vol. 7(3), pages 334-350, September.
    12. Candon, David, 2018. "The effect of cancer on the labor supply of employed men over the age of 65," Economics & Human Biology, Elsevier, vol. 31(C), pages 184-199.
    13. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    14. D. Mark Anderson, 2013. "The Impact Of Hiv Education On Behavior Among Youths: A Propensity Score Matching Approach," Contemporary Economic Policy, Western Economic Association International, vol. 31(3), pages 503-527, July.
    15. Anupam Nanda, 2005. "Property Condition Disclosure Law: Does 'Seller Tell All' Matter in Property Values?," Working papers 2005-47, University of Connecticut, Department of Economics, revised Jul 2006.
    16. Sourafel Girma & Holger Görg, 2016. "Multinationals’ Productivity Advantage: Scale Or Technology?," World Scientific Book Chapters, in: MULTINATIONAL ENTERPRISES AND HOST COUNTRY DEVELOPMENT Volume 53: World Scientific Studies in International Economics, chapter 1, pages 3-15, World Scientific Publishing Co. Pte. Ltd..
    17. Falk, Martin, 2017. "Gains from horizontal collaboration among ski areas," Tourism Management, Elsevier, vol. 60(C), pages 92-104.
    18. Johar, Meliyanni, 2009. "The impact of the Indonesian health card program: A matching estimator approach," Journal of Health Economics, Elsevier, vol. 28(1), pages 35-53, January.
    19. Becerril, Javier & Abdulai, Awudu, 2010. "The Impact of Improved Maize Varieties on Poverty in Mexico: A Propensity Score-Matching Approach," World Development, Elsevier, vol. 38(7), pages 1024-1035, July.
    20. Wendimu, Mengistu Assefa & Henningsen, Arne & Gibbon, Peter, 2016. "Sugarcane Outgrowers in Ethiopia: “Forced” to Remain Poor?," World Development, Elsevier, vol. 83(C), pages 84-97.

    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:inm:orisre:v:24:y:2013:i:1:p:108-127. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.