The Impact of Marketing-Induced versus Word-of-Mouth Customer Acquisition on Customer Equity Growth
By Julián Villanueva, Shijin Yoo, Dominique M. Hanssens. 2008
648 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/d291436a3045940cb6712e5188c4a576c7d5f8f6
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Xueming Luo
- Cait Lamberton
- Renana Peres
- Andrew T. Stephen
- Julián Villanueva
- David Godes
- Eitan Muller
- Jenny van Doorn
Citations in the corpus
- Quantifying the Long-Term Impact of Negative Word of Mouth on Cash Flows and Stock Prices (2009, methodology): “Note that because the white-noise residuals can still be contemporaneously correlated and thus generate misleading results, we apply an orthogonolising transformation to correct this bias (Hamilton 1994, Villanueva et al. 2008).”
- Sequential and Temporal Dynamics of Online Opinion (2012, methodology): “To summarize our analysis of sequential dynamics, we have established that the theory proposed by Wu and Huberman (2008) seems to explain some, but not all, of the variance in our data set.”
- Customer Satisfaction and Stock Returns Risk (2009, unknown): “Positive word of mouth engenders greater credibility among customers and serves as a low-cost channel for retaining customers (Villanueva, Yoo, and Hanssens 2008).”
- Good, better, engaged? The effect of company-initiated customer engagement behavior on shareholder value (2018, background): “Third, customer engagement behaviors resulting from a company’s initiatives are likely to have a different impact than customer engagement behaviors that occur naturally (i.e., without the company’s interference) (Villanueva et al. 2008).”
- Customer-to-Customer Interactions: Broadening the Scope of Word of Mouth Research (2010, unknown): “Online data have been also used to show that C2C acquired customers may create more long-term value to the firm (Villanueva, Yoo, and Hanssens 2008).”
- The effect of social networks structure on innovation performance: A review and directions for research (2019, background): “This might explain the findings of Watts and Dodds (2007), who simulated social hubs as having low susceptibility, which translates into late adoption, that is, these network members need a higher number of adopting neighbors to adopt themselves.”