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Negative Blogs, Positive Outcomes: When should Firms Permit Employees to Blog Honestly?

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Abstract

Weblogs or blogs have recently received a lot of attention, especially in the business community, with a number of firms encouraging their employees to publish blogs to reach out and connect to a wider audience. It is beginning to be recognized that employee blogs can cast a firm in either a positive or a negative light, thereby enhancing or harming the firm’s reputation. Paradoxically, under certain conditions negative postings by employees can actually help the overall reputation of the firm. The rationale for this is that negative posts raise the credibility of an employee blog and attract more readers, who then will also be exposed to the positive posts on the blog. Drawing from the literature on customer advocacy and the stage model theory of information processing in cognitive psychology, we develop a model to decipher the relationship between the extent of negative posts and the overall positive Word of Mouth (WOM) generated by the employee blogs for the firm. An empirical model is developed to account for the inherent non-linearities, endogeneity and unobserved heterogeneity concerns, and potential alternative specifications. Our results suggest that negative posts act as a catalyst to increase the readership of an employee blog, with readership increasing exponentially in the initial stages and then stabilizing. The empirical findings are used to generate an analytical framework that firms can use to formulate employee blogging policies. We illustrate the application of the framework using blogging data from Sun Microsystems.

Suggested Citation

  • Rohit Aggarwal & Ram Gopal & Ramesh Sankaranarayanan, 2007. "Negative Blogs, Positive Outcomes: When should Firms Permit Employees to Blog Honestly?," Working Papers 07-32, NET Institute, revised Sep 2007.
  • Handle: RePEc:net:wpaper:0732
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    References listed on IDEAS

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    1. Vijay Mahajan & Eitan Muller & Roger A. Kerin, 1984. "Introduction Strategy for New Products with Positive and Negative Word-of-Mouth," Management Science, INFORMS, vol. 30(12), pages 1389-1404, December.
    2. Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119.
    3. Lynch, John G, Jr & Srull, Thomas K, 1982. " Memory and Attentional Factors in Consumer Choice: Concepts and Research Methods," Journal of Consumer Research, Oxford University Press, vol. 9(1), pages 18-37, June.
    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. Dina Mayzlin, 2006. "Promotional Chat on the Internet," Marketing Science, INFORMS, vol. 25(2), pages 155-163, 03-04.
    6. Brown, Jacqueline Johnson & Reingen, Peter H, 1987. " Social Ties and Word-of-Mouth Referral Behavior," Journal of Consumer Research, Oxford University Press, vol. 14(3), pages 350-362, December.
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    More about this item

    Keywords

    blog; employee blogs; bloggers; blogging policies; word-of-mouth; customer advocacy; information processing theory; non-linear models;

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software
    • D78 - Microeconomics - - Analysis of Collective Decision-Making - - - Positive Analysis of Policy Formulation and Implementation
    • L10 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - General
    • M50 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics - - - General
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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