Disconfirmation effect on online review credibility: An experimental analysis

Jha, Ashish Kumar; Shah, Snehal

doi:10.1016/j.dss.2021.113519

Cited by 28 publications

(21 citation statements)

References 54 publications

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“…The study models have been evaluated based on the calculated scores of adjusted R 2 and root mean square error (RMSE) for both the training and test data sets, as shown in Table 4. Existing literature has guided that these measures are commonly used to compare and detect the goodness of fit of machine learning models (Jha and Shah, 2021). Thus, we followed the same.…”

Section: Methodsmentioning

confidence: 99%

“…Digital economic developments have prompted a large section of consumers to share their experiences on different online review platforms (Jha and Shah, 2021). These text reviews are tremendously significant and informative to potential customers who rely on them when making a purchase decision (Duan and Whinston, 2008).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Thus, the COVID-19 pandemic has created financial uncertainty for every sector especially the banking industry (Elnahass et al, 2021). Given the growing importance of a stay-at-home culture, online shopping and digital transactions have now increased across the globe (Jha and Shah, 2021). Eventually, all kinds of online buying activities are being supported by online banking services (Jebarajakirthy and Shankar, 2021;Kaur et al, 2020b).…”

Section: Introductionmentioning

confidence: 99%

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Determining banking service attributes from online reviews: text mining and sentiment analysis

Mittal

Agrawal

2022

IJBM

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PurposeThe current study employs text mining and sentiment analysis to identify core banking service attributes and customer sentiment in online user-generated reviews. Additionally, the study explains customer satisfaction based on the identified predictors.Design/methodology/approachA total of 32,217 customer reviews were collected across 29 top banks on bankbazaar.com posted from 2014 to 2021. In total three conceptual models were developed and evaluated employing regression analysis.FindingsThe study revealed that all variables were found to be statistically significant and affect customer satisfaction in their respective models except the interest rate.Research limitations/implicationsThe study is confined to the geographical representation of its subjects' i.e. Indian customers. A cross-cultural and socioeconomic background analysis of banking customers in different countries may help to better generalize the findings.Practical implicationsThe study makes essential theoretical and managerial contributions to the existing literature on services, particularly the banking sector.Originality/valueThis paper is unique in nature that focuses on banking customer satisfaction from online reviews and ratings using text mining and sentiment analysis.

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Section: Methodsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Determining banking service attributes from online reviews: text mining and sentiment analysis

Mittal

Agrawal

2022

IJBM

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“…For instance, Xie and Lee (2015) have established that both earned as well as owned exposure of firms on social media lead to a positive impact on the consumer's purchase likelihood. Extant research also finds the impact of user generated content on influencing future user review behaviour (Jha & Shah, 2019)and review credibility (Jha & Shah, 2021). However, a close study of extant literature also informs us that there are only a few that analyse the impact of user or firm generated content on the firm value (Chung et al, 2020).…”

Section: Firm Communication On Social Mediamentioning

confidence: 99%

Social Media Sustainability Communication: An Analysis of Firm Behaviour and Stakeholder Responses

Jha

Verma

2022

Inf Syst Front

Self Cite

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Social media communication, and its impact on individuals and firms, is becoming increasingly important in today’s age. Firms are utilizing social media channels for communicating their sustainability-related initiatives. The role of social media as a mode for sustainability-related communication by firms has not been widely analyzed in the extant information systems literature. Given the increasingly important role of social media for information diffusion as well as increasing awareness for sustainability practices, this is a critical area of research. In this paper, we use an analytic model to theorize, coupled with empirical analysis to test the impact of firms’ sustainability practices. We have validated our proposed hypotheses using an empirical model based on panel data of firms’ sustainability performance and their Twitter communication over a 3-year period. Through our unique mixed-method study, we add additional methodological rigour to extant social media-based research in the information systems domain. Our research has significant theoretical and managerial significance as we identify how firms utilize social media for sustainability-related communication and its corresponding impact on customer response. Our research provides actionable insights for policymakers, firms as well as investors and consumers on understanding and managing sustainability-related communications on social media.

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“…However, with the emergence of the internet, people, especially millennials, not only prefer writing comments or reviews online nowadays but also like to refer to online information and opinions before making decisions ( Hong & Park, 2019 ; Siering et al, 2018 ). When elaborating on online comments, expressing emotions and using emotional words can make a significant difference in customers' disconfirmation level in the e-business context ( Jha & Shah, 2021 ; Liao et al, 2011 ). Meanwhile, as indicated in the EDT by Westbrook (1987) , people's emotions arise, and emotional fluctuations are caused when facing the disconfirmation of expectation and perceived performance outcome in purchasing activities.…”

Section: Introductionmentioning

confidence: 99%

Recommend or not? The influence of emotions on passengers’ intention of airline recommendation during COVID-19

et al. 2023

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Disconfirmation effect on online review credibility: An experimental analysis

Cited by 28 publications

References 54 publications

Determining banking service attributes from online reviews: text mining and sentiment analysis

Determining banking service attributes from online reviews: text mining and sentiment analysis

Social Media Sustainability Communication: An Analysis of Firm Behaviour and Stakeholder Responses

Recommend or not? The influence of emotions on passengers’ intention of airline recommendation during COVID-19

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