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

It is crucial for any organization to discover knowledge from ecosystem-specific sources of knowledge that are considered external to the organization. Since knowledge exploration is a resource-intensive task for organizations, untimely or excessive knowledge exploration have detrimental impacts on the innovativeness and competitiveness of organizations. The benefits of performance measurement and management tools for knowledge management in organizations have been known for many years now. Therefore, the application of similar tools in ecosystems may enable actors to have access to valuable external knowledge. However, there is a paucity of such tools in management scholarship. The purpose of this study is to bridge this gap by proposing a conceptual tool the Ecosystem Knowledge (EK) Explorer, which generates insightful knowledge for ecosystem actors using codified technical knowledge (e.g., scientific publications and patents). Not only does the EK Explorer reduce the uncertainty and fuzziness of the knowledge exploration phase for ecosystem actors, it also enables them to save resources and have access to strategic knowledge regarding competition, collaboration, technology management, and policy making in ecosystems. Bibliometric analysis, social network analysis, and text mining were used to conceptualize the constructs and measurable variables of the EK Explorer.

/pdf/the-ecosystem-knowledge-explorer-a-tool-to-systematically-1lebzd4mbk.pdf

The Ecosystem Knowledge Explorer: A Tool to Systematically Discover External Knowledge

Dieser Beitrag zeigt, wie Amazon denkt, diskutiert, wie das Amazon-Geschaftsmodell funktioniert und demonstriert die aktuellen Geschaftsfelder von Amazon und die damit einhergehenden Bedrohungen fur verschiedenste Branchen auf.

Die „Amazonisierung“ des Konsums – Game-Changer Amazon

Competition and cooperation in a platform-based business ecosystem within complementary partners

Increasingly, digital platforms are being introduced into existing markets to complement product customization, digitization, the embedding of software into existing business activities, the Internet of Things, and the ubiquitous availability of the Internet (Tiwana, 2014). Indeed, most companies with a large market capitalization, such as Apple and Alphabet, run platform business models (Parker et al., 2016). These business models are often eliminating existing market entry barriers and, due to unleashing network effects, are changing the existing business environment as well as the competition in these markets as a result of rapid growth (Choudary, 2015; Tiwana, 2014). Some impacts of a platform’s market entry on established companies are known based on case studies. However, there is no general understanding of these effects in current literature and practice.

/pdf/when-a-new-platform-enters-a-market-what-is-the-impact-on-51m864r9tv.pdf

When a New Platform Enters a Market, What Is the Impact on Incumbents?

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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When a New Platform Enters a Market, What Is the Impact on Incumbents?

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