IDEAS home Printed from https://ideas.repec.org/a/inm/orisre/v25y2014i1p35-52.html
   My bibliography  Save this article

How to Attract and Retain Readers in Enterprise Blogging?

Author

Listed:
  • Param Vir Singh

    (Tepper School of Business and iLab, Heinz College, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213)

  • Nachiketa Sahoo

    (School of Management, Boston University, Boston, Massachusetts 02215; and iLab, Heinz College, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213)

  • Tridas Mukhopadhyay

    (Tepper School of Business and iLab, Heinz College, Carnegie Mellon University Qatar, Doha, Qatar)

Abstract

We investigate the dynamics of blog reading behavior of employees in an enterprise blogosphere. A dynamic model is developed and calibrated using longitudinal data from a Fortune 1,000 IT services firm. Our modeling framework allows us to segregate the impact of textual characteristics ( sentiment and quality ) of a post on attracting readers from retaining them. We find that the textual characteristics that appeal to the sentiment of the reader affect both reader attraction and retention. However, textual characteristics that reflect only the quality of the posts affect only reader retention. We identify a variety-seeking behavior of blog readers where they dynamically switch from reading on one set of topics to another. The modeling framework and findings of this study highlight opportunities for the firm to influence blog-reading behavior of its employees to align it with its goals. Overall, this study contributes to improved understanding of reading behavior of individuals in communities formed around user generated content.

Suggested Citation

  • Param Vir Singh & Nachiketa Sahoo & Tridas Mukhopadhyay, 2014. "How to Attract and Retain Readers in Enterprise Blogging?," Information Systems Research, INFORMS, vol. 25(1), pages 35-52, March.
    • Handle: RePEc:inm:orisre:v:25:y:2014:i:1:p:35-52
    DOI: 10.1287/isre.2013.0509
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/isre.2013.0509
    Download Restriction: no
    File URL: https://libkey.io/10.1287/isre.2013.0509?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. Oded Netzer & James M. Lattin & V. Srinivasan, 2008. "A Hidden Markov Model of Customer Relationship Dynamics," Marketing Science, INFORMS, vol. 27(2), pages 185-204, 03-04.
    2. Yves Atchade, 2005. "An Adaptive Version for the Metropolis Adjusted Langevin Algorithm with a Truncated Drift," RePAd Working Paper Series LRSP-WP1, Département des sciences administratives, UQO.
    3. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    4. Rosen, Sherwin, 2007. "Studies in Labor Markets," National Bureau of Economic Research Books, University of Chicago Press, number 9780226726304, April.
    5. repec:ucp:bknber:9780226726281 is not listed on IDEAS
    6. B. P. S. Murthi & Sumit Sarkar, 2003. "The Role of the Management Sciences in Research on Personalization," Management Science, INFORMS, vol. 49(10), pages 1344-1362, October.
    7. Yingda Lu & Kinshuk Jerath & Param Vir Singh, 2013. "The Emergence of Opinion Leaders in a Networked Online Community: A Dyadic Model with Time Dynamics and a Heuristic for Fast Estimation," Management Science, INFORMS, vol. 59(8), pages 1783-1799, August.
    8. Yves F. Atchadé, 2006. "An Adaptive Version for the Metropolis Adjusted Langevin Algorithm with a Truncated Drift," Methodology and Computing in Applied Probability, Springer, vol. 8(2), pages 235-254, June.
    9. J. Miguel Villas-Boas & Russell S. Winer, 1999. "Endogeneity in Brand Choice Models," Management Science, INFORMS, vol. 45(10), pages 1324-1338, October.
    10. Param Vir Singh & Yong Tan & Nara Youn, 2011. "A Hidden Markov Model of Developer Learning Dynamics in Open Source Software Projects," Information Systems Research, INFORMS, vol. 22(4), pages 790-807, December.
    11. Andrews,Donald W. K. & Stock,James H. (ed.), 2005. "Identification and Inference for Econometric Models," Cambridge Books, Cambridge University Press, number 9780521844413, October.
    12. McAlister, Leigh, 1982. "A Dynamic Attribute Satiation Model of Variety-Seeking Behavior," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 9(2), pages 141-150, September.
    13. Rohit Aggarwal & Ram Gopal & Ramesh Sankaranarayanan & Param Vir Singh, 2012. "Blog, Blogger, and the Firm: Can Negative Employee Posts Lead to Positive Outcomes?," Information Systems Research, INFORMS, vol. 23(2), pages 306-322, June.
    14. McAlister, Leigh & Pessemier, Edgar, 1982. "Variety Seeking Behavior: An Interdisciplinary Review," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 9(3), pages 311-322, December.
    15. Sha Yang & Yuxin Chen & Greg Allenby, 2003. "Bayesian Analysis of Simultaneous Demand and Supply," Quantitative Marketing and Economics (QME), Springer, vol. 1(3), pages 251-275, September.
    16. James J. Heckman, 1981. "Heterogeneity and State Dependence," NBER Chapters, in: Studies in Labor Markets, pages 91-140, National Bureau of Economic Research, Inc.
    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. Sebastian Schötteler & Sven Laumer & Heidi Schuhbauer, 2023. "Consequences of Enterprise Social Media Network Positions for Employees," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 65(4), pages 425-440, August.
    2. Yi Yang & Kunpeng Zhang & Yangyang Fan, 2023. "sDTM: A Supervised Bayesian Deep Topic Model for Text Analytics," Information Systems Research, INFORMS, vol. 34(1), pages 137-156, March.
    3. Warut Khern-am-nuai & Karthik Kannan & Hossein Ghasemkhani, 2018. "Extrinsic versus Intrinsic Rewards for Contributing Reviews in an Online Platform," Information Systems Research, INFORMS, vol. 29(4), pages 871-892, December.
    4. Sheng, Jie & Amankwah-Amoah, Joseph & Wang, Xiaojun, 2017. "A multidisciplinary perspective of big data in management research," International Journal of Production Economics, Elsevier, vol. 191(C), pages 97-112.
    5. Naveen Kumar & Liangfei Qiu & Subodha Kumar, 2022. "A Hashtag Is Worth a Thousand Words: An Empirical Investigation of Social Media Strategies in Trademarking Hashtags," Information Systems Research, INFORMS, vol. 33(4), pages 1403-1427, December.
    6. Son, Jaebong & Lee, Hyung Koo & Jin, Sung & Lee, Jintae, 2019. "Content features of tweets for effective communication during disasters: A media synchronicity theory perspective," International Journal of Information Management, Elsevier, vol. 45(C), pages 56-68.
    7. Rohit Aggarwal & Michael J. Lee & Vishal Midha, 2023. "Differential Impact of Content in Online Communication on Heterogeneous Candidates: A Field Study in Technical Recruitment," Information Systems Research, INFORMS, vol. 34(2), pages 609-628, June.
    8. Angela Aerry Choi & Daegon Cho & Dobin Yim & Jae Yun Moon & Wonseok Oh, 2019. "When Seeing Helps Believing: The Interactive Effects of Previews and Reviews on E-Book Purchases," Information Systems Research, INFORMS, vol. 30(4), pages 1164-1183, December.
    9. Shaohui Wu & Yong Tan & Yubo Chen & Yitian (Sky) Liang, 2022. "How Is Mobile User Behavior Different? A Hidden Markov Model of Cross-Mobile Application Usage Dynamics," Information Systems Research, INFORMS, vol. 33(3), pages 1002-1022, September.
    10. Yicheng Song & Nachiketa Sahoo & Elie Ofek, 2019. "When and How to Diversify—A Multicategory Utility Model for Personalized Content Recommendation," Management Science, INFORMS, vol. 65(8), pages 3737-3757, August.
    11. Zhao, Lu & Zhang, Mingli & Ming, Yaxin & Niu, Tao & Wang, Yu, 2023. "The effect of image richness on customer engagement: Evidence from Sina Weibo," Journal of Business Research, Elsevier, vol. 154(C).
    12. Yue Jin & Yong Tan & Jinghua Huang, 2022. "Managing contributor performance in knowledge‐sharing communities: A dynamic perspective," Production and Operations Management, Production and Operations Management Society, vol. 31(11), pages 3945-3962, November.
    13. Sandeep Khurana & Liangfei Qiu & Subodha Kumar, 2019. "When a Doctor Knows, It Shows: An Empirical Analysis of Doctors’ Responses in a Q&A Forum of an Online Healthcare Portal," Information Systems Research, INFORMS, vol. 30(3), pages 872-891, September.
    14. Wenjuan Fan & Qiqi Zhou & Liangfei Qiu & Subodha Kumar, 2023. "Should Doctors Open Online Consultation Services? An Empirical Investigation of Their Impact on Offline Appointments," Information Systems Research, INFORMS, vol. 34(2), pages 629-651, June.
    15. Sheng, Jie & Amankwah-Amoah, Joseph & Wang, Xiaojun, 2019. "Technology in the 21st century: New challenges and opportunities," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 321-335.
    16. Mengke Qiao & Ke-Wei Huang, 2021. "Correcting Misclassification Bias in Regression Models with Variables Generated via Data Mining," Information Systems Research, INFORMS, vol. 32(2), pages 462-480, June.
    17. Hyelim Oh & Khim-Yong Goh & Tuan Q. Phan, 2023. "Are You What You Tweet? The Impact of Sentiment on Digital News Consumption and Social Media Sharing," Information Systems Research, INFORMS, vol. 34(1), pages 111-136, March.
    18. Mariia Petryk & Michael Rivera & Siddharth Bhattacharya & Liangfei Qiu & Subodha Kumar, 2022. "How Network Embeddedness Affects Real-Time Performance Feedback: An Empirical Investigation," Information Systems Research, INFORMS, vol. 33(4), pages 1467-1489, December.
    19. Vilma Todri & Anindya Ghose & Param Vir Singh, 2020. "Trade-Offs in Online Advertising: Advertising Effectiveness and Annoyance Dynamics Across the Purchase Funnel," Information Systems Research, INFORMS, vol. 31(1), pages 102-125, March.
    20. Kawaljeet Kaur Kapoor & Kuttimani Tamilmani & Nripendra P. Rana & Pushp Patil & Yogesh K. Dwivedi & Sridhar Nerur, 2018. "Advances in Social Media Research: Past, Present and Future," Information Systems Frontiers, Springer, vol. 20(3), pages 531-558, June.
    21. Yan Huang & Param Vir Singh & Anindya Ghose, 2015. "A Structural Model of Employee Behavioral Dynamics in Enterprise Social Media," Management Science, INFORMS, vol. 61(12), pages 2825-2844, December.
    22. Michael Rivera & Liangfei Qiu & Subodha Kumar & Tony Petrucci, 2021. "Are Traditional Performance Reviews Outdated? An Empirical Analysis on Continuous, Real-Time Feedback in the Workplace," Information Systems Research, INFORMS, vol. 32(2), pages 517-540, June.
    23. Mochen Yang & Gediminas Adomavicius & Gordon Burtch & Yuqing Rena, 2018. "Mind the Gap: Accounting for Measurement Error and Misclassification in Variables Generated via Data Mining," Information Systems Research, INFORMS, vol. 29(1), pages 4-24, March.
    24. Jingchuan Pu & Yuan Chen & Liangfei Qiu & Hsing Kenneth Cheng, 2020. "Does Identity Disclosure Help or Hurt User Content Generation? Social Presence, Inhibition, and Displacement Effects," Information Systems Research, INFORMS, vol. 31(2), pages 297-322, June.

    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. Fendel Tanja, 2016. "Migration and Regional Wage Disparities in Germany," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 236(1), pages 3-35, February.
    2. Martijn G. de Jong & Donald R. Lehmann & Oded Netzer, 2012. "State-Dependence Effects in Surveys," Marketing Science, INFORMS, vol. 31(5), pages 838-854, September.
    3. Lu Yan & Yong Tan, 2014. "Feeling Blue? Go Online: An Empirical Study of Social Support Among Patients," Information Systems Research, INFORMS, vol. 25(4), pages 690-709, December.
    4. Yonezawa, Koichi & Richards, Timothy J., 2016. "Competitive Package Size Decisions," Journal of Retailing, Elsevier, vol. 92(4), pages 445-469.
    5. Peter Ebbes & Rajdeep Grewal & Wayne DeSarbo, 2010. "Modeling strategic group dynamics: A hidden Markov approach," Quantitative Marketing and Economics (QME), Springer, vol. 8(2), pages 241-274, June.
    6. Liang Guo, 2006. "—Removing the Boundary Between Structural and Reduced-Form Models," Marketing Science, INFORMS, vol. 25(6), pages 629-632, 11-12.
    7. Child, Travers Barclay, 2019. "Conflict and counterinsurgency aid: Drawing sectoral distinctions," Journal of Development Economics, Elsevier, vol. 141(C).
    8. Shuai Liu & Xiao-Yu Xu & Kai Zhao & Li-Ming Xiao & Qi Li, 2021. "Understanding the Complexity of Regional Innovation Capacity Dynamics in China: From the Perspective of Hidden Markov Model," Sustainability, MDPI, vol. 13(4), pages 1-22, February.
    9. B. P. S. Murthi & Sumit Sarkar, 2003. "The Role of the Mangement Sciences in Research on Personalization," Review of Marketing Science Working Papers 2-2-1025, Berkeley Electronic Press.
    10. Pradeep Chintagunta & Tülin Erdem & Peter E. Rossi & Michel Wedel, 2006. "Structural Modeling in Marketing: Review and Assessment," Marketing Science, INFORMS, vol. 25(6), pages 604-616, 11-12.
    11. John C. Ham & Daniela Iorio & Michelle Sovinsky, 2013. "Caught in the Bulimic Trap?," Journal of Human Resources, University of Wisconsin Press, vol. 48(3), pages 736-767.
    12. Shaohui Wu & Yong Tan & Yubo Chen & Yitian (Sky) Liang, 2022. "How Is Mobile User Behavior Different? A Hidden Markov Model of Cross-Mobile Application Usage Dynamics," Information Systems Research, INFORMS, vol. 33(3), pages 1002-1022, September.
    13. Wesley Hartmann, 2006. "Intertemporal effects of consumption and their implications for demand elasticity estimates," Quantitative Marketing and Economics (QME), Springer, vol. 4(4), pages 325-349, December.
    14. Oded Netzer & James M. Lattin & V. Srinivasan, 2008. "A Hidden Markov Model of Customer Relationship Dynamics," Marketing Science, INFORMS, vol. 27(2), pages 185-204, 03-04.
    15. Yue Jin & Yong Tan & Jinghua Huang, 2022. "Managing contributor performance in knowledge‐sharing communities: A dynamic perspective," Production and Operations Management, Production and Operations Management Society, vol. 31(11), pages 3945-3962, November.
    16. Ribeiro, Ricardo, 2010. "Consumer demand for variety: intertemporal effects of consumption, product switching and pricing policies," MPRA Paper 25812, University Library of Munich, Germany.
    17. Jonathan Z. Zhang & Oded Netzer & Asim Ansari, 2014. "Dynamic Targeted Pricing in B2B Relationships," Marketing Science, INFORMS, vol. 33(3), pages 317-337, May.
    18. Param Vir Singh & Corey Phelps, 2013. "Networks, Social Influence, and the Choice Among Competing Innovations: Insights from Open Source Software Licenses," Information Systems Research, INFORMS, vol. 24(3), pages 539-560, September.
    19. Henry S. Farber, 1992. "Evaluating Competing Theories of Worker Mobility," Working Papers 1992-1, Princeton University. Economics Department..
    20. Andreas Herrmann & Michael D. Johnson, 1999. "Die Kundenzufriedenheit als Bestimmungsfaktor der Kundenbindung," Schmalenbach Journal of Business Research, Springer, vol. 51(6), pages 579-598, June.

    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:25:y:2014:i:1:p:35-52. 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.