Investor's Intrinsic Motives and the Valence of Word-of-Mouth in Sequential Decision-Making. Issue 2 (3rd April 2021)

• Record Type: Journal Article
• Authors: Ahmad, Fawad; Oriani, Raffaele; De Angelis, Matteo
• Is Part Of: Journal of behavioral finance. Volume 22:Issue 2(2021)
• Page Start: 170
• Page End: 188
• Publication Date: 2021-04-03
• Subjects: Sequential decision-making -- Risk-attitude -- Word-of-mouth communication -- Self-motives -- Social motives -- Investor behavior; Capital market -- Psychological aspects -- Periodicals; Finance -- Psychological aspects -- Periodicals; 332.019
• DOI: 10.1080/15427560.2020.1751630
• Languages: English
• ISSNs: 1542-7560

Abstract

Abstract: An escalation of commitment refers to an individual's decision to engage in greater risk-taking following prior losses than gains. This behavior was found to be preeminent in situations framed as portfolio decisions. However, there is lack of evidence regarding the underlying mechanism behind an individual's decision to engage in later high (or low) risk-taking in a loss (or gain) domain. A model was developed based on the connections between prospect theory, self-determination theory and word-of-mouth to provide underlying mechanisms that activate investors' decisions to engage in later high (or low) risk-taking. We theorized that self- and/or social motives and negative word-of-mouth (NWoM) or positive word-of-mouth (PWoM) would double mediate the effect of prior low (high) risk-taking on later high (low) risk-taking in the loss (gain) domain. Results supported a double mediation effect and indicated that investors have different underlying self- and/or social motives, manifested in NWoM or PWoM, that activate later high (low) risk-taking in the loss (gain) domain. The findings have pertinent implications for advisors wishing to understand underlying self- and/or social motives in order to predict and manage client risk-attitude. The findings also help researchers and analysts to identify patterns in investor behavior that can predict market trends.