Personalized managerial response and negative inconsistent review helpfulness: The mediating effect of perceived response helpfulness

Abstract Analyzing textual data by means of AI models has been recognized as highly relevant in information systems research and practice, since a vast amount of data on eCommerce platforms, review portals or social media is given in textual form. Here, language models such as BERT, which are deep learning AI models, constitute a breakthrough and achieve leading-edge results in many applications of text analytics such as sentiment analysis in online consumer reviews. However, these language models are “black boxes”: It is unclear how they arrive at their predictions. Yet, applications of language models, for instance, in eCommerce require checks and justifications by means of global reconstruction of their predictions, since the decisions based thereon can have large impacts or are even mandatory due to regulations such as the GDPR. To this end, we propose a novel XAI approach for global reconstructions of language model predictions for token-level classifications (e.g., aspect term detection) by means of linguistic rules based on NLP building blocks (e.g., part-of-speech). The approach is analyzed on different datasets of online consumer reviews and NLP tasks. Since our approach allows for different setups, we further are the first to analyze the trade-off between comprehensibility and fidelity of global reconstructions of language model predictions. With respect to this trade-off, we find that our approach indeed allows for balanced setups for global reconstructions of BERT’s predictions. Thus, our approach paves the way for a thorough understanding of language model predictions in text analytics. In practice, our approach can assist businesses in their decision-making and supports compliance with regulatory requirements. 

/pdf/global-reconstruction-of-language-models-with-linguistic-1p8n4bi9.pdf

Global reconstruction of language models with linguistic rules – Explainable AI for online consumer reviews


Purpose
This paper aims to evaluate and structure the basic heuristics consumers use in evaluating word-of-mouth (WOM) about luxury hotel brands while analyzing the impact of deception in online consumer reviews.


Design/methodology/approach
The research used a two-study mixed-methods approach, using interpersonal deception theory and social proof theory as lenses to conduct our analysis. For the first study, a qualitative conceptual mapping analysis was conducted, examining online consumer reviews to identify key concepts and their relationships in the context of luxury hotel brands. In the second study, the themes were further examined using a fuzzy-set qualitative comparative analysis to analyze their causal complexity and association between variables to determine how they influence the perceived helpfulness of online reviews for luxury hotel brands.


Findings
The results underline the importance of functional, objective variables, such as the number of reviews and stars, as social proof heuristics and other factors, including clout, authenticity and analytic tone, as interpersonal communication heuristics. Therefore, consumers use a combination of social and interpersonal communication heuristics to extract information from reviews and manage deception risk.


Research limitations/implications
The paper contributes to the consumer–brand relationship literature by assessing the heuristics consumers use in evaluating online reviews and provides additional information for research in online reputation management.


Practical implications
This study’s results can help marketing practitioners and brand managers manage their online reputations better. It can also aid managers in improving their messaging on hotel websites to entice consumers to complete bookings. Heuristics play an essential role in such messaging and understanding them can help marketers appeal directly to their target market.


Originality/value
This study contributes to the literature on consumer–brand relationships by providing a framework of heuristics that consumers use when evaluating luxury service brands and contributes to WOM and online reputation research by highlighting factors that may make online reviews more helpful.


Consumer-brand heuristics in luxury hotel reviews

/pdf/electronic-markets-on-platform-culture-3cls0uye.pdf

Electronic Markets on platform culture

Phase 4: Verhaltenssteuerung

Abstract Consumer-generated reviews play a decisive role in creating trust and facilitating transactions on digital platforms. However, prior research shows various problems, e.g., only a small number of consumers providing reviews, fake reviews, and inconsistent reviews. We use an experiment in the context of a restaurant booking platform to examine the impact of inconsistent reviews on the duration of consumers’ transaction decisions. In a second experiment, we investigate the relative importance of the review components in the case of inconsistent reviews. Drawing on the dual-process theory and media richness theory, we predict that inconsistent reviews result in a longer time required for consumers’ transaction decisions (H1) and lead to users’ transaction decisions being predominantly based on the qualitative component (H2). Although we do not find general support that inconsistent restaurant reviews negatively determine the duration of transaction decisions, we find evidence that in the case of inconsistent restaurant reviews, the polarity of the qualitative component is crucial for both the duration of the transaction decision and the decision itself. 

/pdf/its-all-about-the-text-an-experimental-investigation-of-2p58dx67.pdf

It’s all about the text: An experimental investigation of inconsistent reviews on restaurant booking platforms

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It’s all about the text: An experimental investigation of inconsistent reviews on restaurant booking platforms