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The purpose of this study is twofold: first, to identify the categories of artificial intelligence (AI) chatbot service failures in frontline, and second, to examine the effect of the intensity of AI emotion exhibited on the effectiveness of the chatbots’ autonomous service recovery process.

We adopt a mixed-methods research approach, starting with a qualitative research, the purpose of which is to identify specific categories of AI chatbot service failures. In the second stage, we conduct experiments to investigate the impact of AI chatbot service failures on consumers’ psychological perceptions, with a focus on the moderating influence of chatbot’s emotional expression. This sequential approach enabled us to incorporate both qualitative and quantitative aspects for a comprehensive research perspective.

The results suggest that, from the analysis of interview data, AI chatbot service failures mainly include four categories: failure to understand, failure to personalize, lack of competence, and lack of assurance. The results also reveal that AI chatbot service failures positively affect dehumanization and increase customers’ perceptions of service failure severity. However, AI chatbots can autonomously remedy service failures through moderate AI emotion. An interesting golden zone of AI’s emotional expression in chatbot service failures was discovered, indicating that extremely weak or strong intensity of AI’s emotional expression can be counterproductive.

This study contributes to the burgeoning AI literature by identifying four types of AI service failure, developing dehumanization theory in the context of smart services, and demonstrating the nonlinear effects of AI emotion. The findings also offer valuable insights for organizations that rely on AI chatbots in terms of designing chatbots that effectively address and remediate service failures.

Drawing on and extending the push-pull-mooring (PPM) framework, this paper aims to empirically explore the influencing mechanism of traveler switching intention from the hotel reservation platforms to the sharing accommodation platforms (SAPs).

This study adopts structural equation modeling to analyze the 543 responses collected among hotel reservation platforms and SAPs travelers.

The results support the positive effect of both push factors (e.g. dissatisfaction with product, service and information quality of hotels on the hotel reservation platform) and pull factors (e.g. price value, authenticity, interaction, home benefits and novelty of SAPs) on traveler switching intention. Except for the negative effect of switching cost, other mooring factors including prior switching experience and social influence positively affect traveler switching intention. The authors also found the switching cost negatively and prior switching experience positively moderated the push effects on traveler switching intention, while the social influence positively moderated the pull effects on traveler switching intention.

Recommendations of future SAP participation research to consider the competing platforms, the unique experiences of SAPs and mooring factors. Examining the factors of different sources is also useful for practitioners to better understand travelers’ demands and to improve the overall welfare of travelers.

This paper embraces an extended PPM framework to explore traveler switching intention in online travel platforms. Moreover, this paper provides unique insights into the switching behavior from the hotel reservation platforms to the SAPs.

Stock price reactions have often been used to evaluate the cost of data breaches in the current information systems (IS) security literature. To further this line of research, this study examines the impact of data breaches on stock returns, information asymmetry and unsystematic firm risk in the context of COVID-19.

This paper employs an event study methodology and examines data breach events released in public databases, spanning pre- and post-COVID settings. This study investigated 283 data breaches of the US publicly traded firms, and the economic cost was measured by cumulative abnormal returns (CARs), trading volume, bid-ask spread and unsystematic risk.

The authors observe that data breaches during the COVID pandemic make investors react more negatively to data breach announcements, as reflected in the significantly negative difference in CARs between breached firms before COVID and those after COVID. The findings also indicate that, after the disclosure of data breach incidents, information asymmetry is reduced to a lesser extent compared with that in the pre-COVID setting. The authors also find that data breach events lead to an increase in the unsystematic risk of breached companies in the pre-COVID era but no change in the post-COVID era.

This study is the first effort to examine the economic consequences of data breaches by investigating the effects in the form of trading activities and risk measurement in the COVID setting.

This study aimed to investigate the impact of e-commerce capabilities on agricultural firms’ performance gains through organizational agility.

A survey was used to collect data from 280 managers of agricultural firms. The proposed model was tested via structural equation modeling.

The empirical results indicated that organizational agility plays a mediating role in conveying the positive influences of e-commerce capabilities on agricultural firms’ performance gains. Specifically, managerial, talent and technical capabilities have different effects on market capitalization and operational adjustment agility, with talent capability performing the most important role. Market capitalization and operational adjustment agility have positive impacts on financial and nonfinancial performance gains, respectively.

This study provides a new framework to understand the relationships between e-commerce capabilities, organizational agility and agricultural firms’ performance gains.

Based on signaling theory, this paper aims to explore the impact of supply chain transparency (SCT) on firms' bank loan (BL) and supply chain financing (SCF) in the context of voluntary disclosure of supplier and customer lists.

Based on panel data collected from Chinese-listed firms between 2012 and 2021, fixed-effect models and a series of robustness checks are used to test the predictions.

First, improving SCT by disclosing major suppliers and customers promotes BL but inhibits SCF. Specifically, customer transparency (CT) is more influential in SCF than supplier transparency (ST). Second, supplier concentration (SC) weakens SCT’s positive impact on BL while reducing its negative impact on SCF. Third, customer concentration (CC) strengthens the positive impact of SCT on BL but intensifies its negative impact on SCF. Last, these findings are basically more pronounced in highly competitive industries.

This study contributes to the SCT literature by investigating the under-explored practice of supply chain list disclosure and revealing its dual impact on firms' access to financing offerings (i.e. BL and SCF) based on signaling theory. Additionally, it expands the understanding of the boundary conditions affecting the relationship between SCT and firm financing, focusing on supply chain concentration. Moreover, it advances signaling theory by exploring how financing providers interpret the SCT signal and enriches the understanding of BL and SCF antecedents from a supply chain perspective.

The purpose of this study is to demonstrate that Strategic Enterprise Management (SEM) and Business Intelligence (BI) have the potential to integrate management decisions vertically through an organization’s hierarchy. This study also aims to present a design theory framework and build a model dimension using eight principles serving as mid-range theories.

This study uses a design science perspective to posit how organizations can successfully implement SEMBI (a union of SEM and BI). This study then completes the design theory by building the method dimension using two principles. Finally, the study presents testable hypotheses for the theory and an evaluation using stakeholder attitudes and judgments as proxies for objective measures.

In the search for a prescription for SEMBI success, this study finds that the notion of the Capability Maturity Model (CMM) is a good artifact with which to organize the principles the authors are seeking. CMM has since been adapted to suit different contexts by incorporating relevant principles from those domains. Hereafter, this study refers to SEMBI–CMM as the adapted solution for SEMBI's success.

This study coins and uses the term SEMBI to represent the union of SEM and BI. This term retains its distinct identities and principles and forms a holistic and integrated view of SEM and BI implementation strategies. In an effort to advance this line of research, this study employs a design science perspective to address the question of how an organization can successfully implement SEMBI.

The purpose of this paper is twofold: first, to clarify what specific behaviors are involved in consumers' partial switching in mobile application (app) usage, and, second, to explore the common and differential motivations of these behaviors.

This paper specified two behaviors in consumers' partial switching in mobile app usage, trialing and combining behaviors, and conceptualized them as different types of variety seeking behaviors. A theoretical model contrasting intrinsic motivations and extrinsic motivations on the two behaviors was developed and tested with a sample of 561 mobile app users in China.

The findings showed that both trialing and combining behaviors could be motivated by intrinsic individual-related and extrinsic technology-related factors. Besides, intrinsic individual-related factors were more effective in motivating trialing behavior, whereas extrinsic technology-related factors were more effective in motivating combining behavior. All these findings are applicable and consistent in both hedonic and utilitarian apps.

This study extends and advances the literature on information technology switching by investigating consumer use behaviors from a new perspective of partial switching and multiple competing apps usage. This study also contributes to variety seeking literature by extending the understanding of variety seeking to the context of mobile app usage. Finally, by investigating the associations and distinctions of trialing and combining behavior, this study not only helps to fully understand the partial switching but also enriches the understanding of different types of variety seeking behaviors.

Since China began its market-oriented economic reform in 1979, government budget deficits have been a fact of life. On one hand, the share of resources owned or controlled by the government must be shrunk in order to create a favorable environment for the development of the market economy. On the other hand, the government still performs many responsibilities required by the traditional planed economy. After calculating government budget deficits and analyzing their causes, the article assesses the impacts of government budget deficits and predicts the future of deficits in China.

Since China began its market-oriented economic reform in 1979, government budget deficits have been a fact of life. On one hand, the share of resources owned or controlled by the government must be shrunk in order to create a favorable environment for the development of the market economy. On the other hand, the government still performs many responsibilities required by the traditional planed economy. After calculating government budget deficits and analyzing their causes, the article assesses the impacts of government budget deficits and predicts the future of deficits in China.