Introduction Strategy for New Products with Positive and Negative Word-of-Mouth

Mahajan, Vijay; Muller, Eitan; Kerin, Roger A.

doi:10.1287/mnsc.30.12.1389

Cited by 317 publications

(174 citation statements)

References 16 publications

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“…Clearly, the effect on success would depend on the valence of the information communicated, positive or negative (e.g., Mahajan et al 1984), where the valence depends on the reputation of the developers. As in the case of corporate reputation (e.g., Fombrun and Shanley 1990), reputation in the open source environment should be a multidimensional construct.…”

Section: Hypothesis 3b (H3b) the Likelihood That Project Manager Embmentioning

confidence: 99%

Location, Location, Location: How Network Embeddedness Affects Project Success in Open Source Systems

2006

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T he community-based model for software development in open source environments is becoming a viable alternative to traditional firm-based models. To better understand the workings of open source environments, we examine the effects of network embeddedness-or the nature of the relationship among projects and developers-on the success of open source projects. We find that considerable heterogeneity exists in the network embeddedness of open source projects and project managers. We use a visual representation of the affiliation network of projects and developers as well as a formal statistical analysis to demonstrate this heterogeneity and to investigate how these structures differ across projects and project managers. Our main results surround the effect of this differential network embeddedness on project success. We find that network embeddedness has strong and significant effects on both technical and commercial success, but that those effects are quite complex. We use latent class regression analysis to show that multiple regimes exist and that some of the effects of network embeddedness are positive under some regimes and negative under others. We use project age and number of page views to provide insights into the direction of the effect of network embeddedness on project success. Our findings show that different aspects of network embeddedness have powerful but subtle effects on project success and suggest that this is a rich environment for further study.

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Section: Hypothesis 3b (H3b) the Likelihood That Project Manager Embmentioning

confidence: 99%

Location, Location, Location: How Network Embeddedness Affects Project Success in Open Source Systems

2006

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“…Research in marketing generally supports the claim that WOM is more influential on behavior than other marketer-controlled sources (Day, 1971;Sheth, 1971;Mahajan, Muller, & Kerin, 1984). WOM has been shown to influence a variety of conditions: awareness, expectations, perceptions, attitudes, and behavior (Richins & Root-Shaffer, 1988;Hogan et al, 2004).…”

Section: Word Of Mouthmentioning

confidence: 87%

“…Mahajan et al (1984) showed that when there is a negative rumor in the release of a certain product, the most appropriate strategy is to increase and change the level of consumers' awareness through advertising as soon as possible.…”

Section: Positive and Negative Wommentioning

confidence: 99%

The Effect of Word of Mouth in Customer Equity and Brand Equity

2011

CBR

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In this paper the author examines the extent to which word of mouth (WOM) impact on customer equity and brand equity, two of the most popular metrics of marketing productivity. WOM is the most ancient and effective communication tool because its low cost affects the efficiency in the allocation of marketing resources. After an extensive literature review, the author proposes several propositions to be tested in the future concerning how WOM might affect each element of brand equity and customer equity.

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“…1 Especially when they have already ordered the product and know for sure that they will be delivered before the consumers ordering it later on 2 Some diffusion models have reported negative word-of-mouth effect for new products [38,39]. However, we do not believe this is likely to occur in this first phase of the model since committed consumers have not experienced the product yet.…”

Section: Credibility Factormentioning

confidence: 98%

A Diffusion Model for Preannounced Products

Manceau

Eliashberg

Rao

et al. 2013

Cust. Need. and Solut.

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Strategic preannouncement of a new product launch by a firm creates a pent-up demand (or consumers committed to purchase prior to launch) for the new product. The level of the pent-up demand depends, among other factors, on the timing and the reputation of the firm announcing the new product; it is critical in shaping up the diffusion process of the new product after launch. In this paper, we develop a two-phase diffusion model that describes both the impact of the announcement on consumers' purchase commitments and the diffusion process since launch starting with a strictly positive number of new product orders. We illustrate the empirical performance of the model with an old but classic dataset that captures both advance purchase orders as well as sales after launch for a new audio CD. We discuss how our model can guide a firm's decision on when to preannounce the introduction of its new product or technology, relative to the time of launch, so as to maximize the total benefit during the planning horizon.

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Introduction Strategy for New Products with Positive and Negative Word-of-Mouth

Cited by 317 publications

References 16 publications

Location, Location, Location: How Network Embeddedness Affects Project Success in Open Source Systems

Location, Location, Location: How Network Embeddedness Affects Project Success in Open Source Systems

The Effect of Word of Mouth in Customer Equity and Brand Equity

A Diffusion Model for Preannounced Products

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