Benchmarking model for factors influencing creation of negative electronic word of mouth. Issue 9 (29th November 2018)

• Record Type: Journal Article
• Authors: Kumar, Sushant; Purbey, Shankar
• Is Part Of: Benchmarking. Volume 25:Issue 9(2018)
• Page Start: 3592
• Page End: 3606
• Publication Date: 2018-11-29
• Subjects: Electronic word of mouth -- Interpretive structural modelling -- Negative electronic word of mouth -- Structural framework; Benchmarking (Management) -- Periodicals; Total quality management -- Periodicals; 658.562
• DOI: 10.1108/BIJ-08-2017-0222
• Languages: English
• ISSNs: 1463-5771

Abstract

Abstract : Purpose: The purpose of this paper is to develop a structural framework for factors influencing the creation of negative electronic word of mouth (WOM) at online forums, review portals, social networking sites or any other internet-based platform. Consumers frequently talk about consumption through WOM. With the unprecedented progress in digitalization of world, consumers usually tell stories about a product or service experience online. The study aims to identify the antecedents for negative electronic WOM (EWOM) and develop a structural model with different levels of factors. Design/methodology/approach: Literature review and group judgment techniques are used to identify the factors responsible for negative WOM. The study uses interpretive structural modeling approach to develop a structural model representing interrelationships among factors. The model also represents the factors at different levels along with most and least dominant factors responsible for EWOM. Findings: Seven factors responsible for negative electronic WOM are identified which are spread over three levels. First level of factors includes anxiety reduction, advice seeking, exertion of power (over companies) and social benefits (received), whereas the second level of factors includes altruism (negative WOM) and economic rewards. The most dominant factor identified is vengeance, which is at level three. Practical implications: The study identified three levels of factors responsible for negative EWOM. Companies can strategies their resources to ensure that no consumer reaches beyond level one. Beyond level one, the involved factors may jeopardize the brand value and brand image of the company. Originality/value: The study contributes to the literature by providing a structural model for negative EWOM. This model identifies the most and least dominant factors and guides managers to take necessary action to prevent negative EWOM.