The effects of harm directions and service recovery strategies on customer forgiveness and negative word-of-mouth intentions

Casidy, Riza; Shin, Hyunju

doi:10.1016/j.jretconser.2015.07.012

Cited by 135 publications

(113 citation statements)

References 81 publications

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“…This model explained 28.9% (Nagelkerke R 2 ) of the variance in customer satisfaction. Importantly, the effect of the sentiment scores 6 We also found a significant effect of the section number variable (F (9, 1271502) = 16409.76, p < 0.001), fully supporting Hypothesis 1. 7 We conducted two analyses, one defined responses of five (5) in the latter sections of customers who reach higher level of satisfaction are significantly larger than the effects of early sections (Beta=.895 and 1.10 of sections 9 and 10, vs. Beta=-1.71 and -1.27 of sections 1 and 2).…”

Section: Relating Customer Emotion To Service Qualitysupporting

confidence: 74%

“…The interaction between the two factors in this model indicates whether the evolution in emotion scores differs for different FCR customer groups. We found a significant interaction between section number and customer FCR (F (9, 1271502) = 2229.12, p < 0.001), which supports that emotions develop differently for customers with different FCR values 6 . Customers who say their issue was resolved have a steeper climb from initial negative emotion, and end with higher levels of positive emotions.…”

Section: Relating Customer Emotion To Service Qualitysupporting

confidence: 62%

“…Better service quality is evident in the (positive) emotions customers express in the latter part of their interactions. Thus, automated emotion assessment, conducted in real-time during service interactions, can be used to evaluate service quality, and to intervene toward better service recovery [6]. Identifying customers whose emotions do not improve towards the end of the interaction can help managers intervene before a service situation escalates.…”

Section: Contributionsmentioning

confidence: 99%

See 2 more Smart Citations

Customer Sentiment in Web-Based Service Interactions

Yom-Tov

Ashtar

Altman

et al. 2018

Companion of the the Web Conference 2018 on the Web Conference 2018 - WWW '18

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We adjust sentiment analysis techniques to automatically detect customer emotion in on-line service interactions of multiple business domains. Then we use the adjusted sentiment analysis tool to report insights into the dynamics of emotion in on-line service chats, using a large dataset of telecommunications customer service interactions. Our analyses show customer emotions start out negative and evolve into positive feelings, as the interaction unfolds. Also, we identify a close relationship between customer emotion dynamics during the service interaction and the concepts of service failure and recovery. This connection manifests itself in customer service quality evaluations after the interaction ends. Our study highlights the connection between customer emotion and service quality as service interactions unfold, and suggests the use of sentiment analysis tools for real-time monitoring and control of web-based service quality.

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Section: Relating Customer Emotion To Service Qualitysupporting

confidence: 74%

Section: Relating Customer Emotion To Service Qualitysupporting

confidence: 62%

Section: Contributionsmentioning

confidence: 99%

See 1 more Smart Citation

Customer Sentiment in Web-Based Service Interactions

Yom-Tov

Ashtar

Altman

et al. 2018

Companion of the the Web Conference 2018 on the Web Conference 2018 - WWW '18

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show abstract

“…This notwithstanding, dissatisfaction brings about different kinds of intentions. In the research of Casidy and Shin (2015), they emphasized that people who are explicitly involved in dissatisfaction have substantial motives of negative WOM. In effect, when people are not treated fairly or dissatisfied, it can lead to certain attitudes whether or not the person is directly involved in the situation Colquitt (2004).Several researchers like (Buttle, 1998, G Nejad et al, 2015, Xia et al, 2004, Balaji et al, 2016, Casidy and Shin, 2015, Colquitt, 2004 have delved into the subject of Negative WOM…”

Section: Negative Word Of Mouth (Wom)mentioning

confidence: 99%

A Critique of the Impact of Consumer Dissatisfaction

Boadi¹,

Li²,

Sai³

et al. 2017

Proceedings of the International Conference on Transformations and Innovations in Management

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Research into consumer satisfaction levels have gone far enough for several years now, however, much has not been done to reiterate how consumers will react and deal with their dissatisfaction and the effect it has on the companies. The main objective of this paper was to review literature that depicts the impact that dissatisfaction has on consumers based on existing theoretical literature. The focus of this study is mainly to know how far a consumer is willing to go when dissatisfied with a product or service, in effect, weighing all the pros and cons of consumer dissatisfaction. This review paper combines the results of previous studies conducted on consumer dissatisfaction. The major consequences of consumer dissatisfaction discussed in this paper include negative Word-of-mouth, switch, complaints and no co-creation intentions. One major finding of this study is that all literature on consumer satisfaction relates it with consumer dissatisfaction by using several theories to explain a consumer's judgement after consuming a product or service.

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“…Empirical studies indicated that satisfactory service recovery not only eliminates potential negative word-of-mouth intention (Casidy and Shin, 2015) but also improves overall satisfaction (Boshoff, . Service recovery could be defined as the strategy undertaken by an organisation to identify and correct the service failure in order to retain customer satisfaction and loyalty (El-Helaly, 2013).…”

Section: Service Recovery (Sr)mentioning

confidence: 99%

The Role of Customer Knowledge Management Process in Service Recovery Performance: An Applied Study to the Egyptian National Railways

El-Helaly¹,

Ebeid²,

El-Menbawey³

2015

IJMAR

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Abstract:Customer knowledge represents an important organisational asset that organisations would utilize and manage to gain a competitive advantage. The purpose of this study is to develop and test a model to explain the role of customer knowledge management in service recovery performance; through examining the impact of Customer Knowledge Management (CKM) process on Service Recovery Performance (SRP), based on the perspective of the Egyptian National Railways' employees. It also attempts to measure how employees and customers evaluate the Egyptian National Railways' actual performance of service recovery. This paper has demonstrated the value of managing customer knowledge effectively in order to achieve a higher performance on service recovery. The empirical results indicated that organisations need to capture, share, acquire, and apply customer knowledge successfully in order to improve their service recovery performance. The results also demonstrated that employees evaluate their performance regarding the service recovery more positively than what customers do.

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The effects of harm directions and service recovery strategies on customer forgiveness and negative word-of-mouth intentions

Cited by 135 publications

References 81 publications

Customer Sentiment in Web-Based Service Interactions

Customer Sentiment in Web-Based Service Interactions

A Critique of the Impact of Consumer Dissatisfaction

The Role of Customer Knowledge Management Process in Service Recovery Performance: An Applied Study to the Egyptian National Railways

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