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This study examines whether common directors are guilty of contagion of corporate frauds from the customer side and, if so, how contagion occurs. Moreover, it explores a way to mitigate it, which is the increased digital orientation of firms.

Secondary data analysis is applied in this paper. We extract supply chain relations from the China Stock Market and Account Research (CSMAR) database as well as corporate fraud data from the same database and the official website of the China Securities Regulatory Commission (CSRC). Digital orientations are estimated through text analysis. Poisson regression is conducted to examine the moderating effect of common directors and the moderated moderating effect of the firms’ digital orientations.

By analysing the 2,096 downstream relations from 2000 to 2021 in China, the study reveals that corporate frauds are contagious through supply chains, while only customers’ misconduct can contagion to upstream firms. The presence of common directors strengthens such supply chain contagion. Additionally, the digital orientation can mitigate the positive moderating effect of common directors on supply chain contagion.

This study highlights the importance of understanding supply chain contagion through corporate fraud by (1) emphasising the existence of the contagion effects of corporate frauds; (2) understanding the potential channel in the process of contagion; (3) considering how digital orientation can mitigate this contagion and (4) recognising that the effect of contagion comes only from the downstream, not from the upstream.

This study explores how customers' individual characteristics and perceptions affect acceptance of service robots as a hotel workforce. The Interactive Technology Acceptance Model (iTAM) has inspired us to investigate effects of customers' technological self-efficacy, perceived interactivity, sense of utility, and enjoyment-level of acceptance related to hotel-service robots as staff.

Data were collected from 224 customers via an online questionnaire conducted in the period April–June 2022 by convenience sampling, and then analyzed by using partial least squares – structural equation modeling (PLS-SEM).

The findings show that customers' technological self-efficacy and perceived interactivity with service robots enhances perceived usefulness and perceived enjoyment, serving as functional and emotional value components of service robots. They also demonstrate that robot's interactivity outweighs other robot's value components, such as perceived usefulness and perceived enjoyment for acceptance of service robots as employees in hotels.

While empirically validating the iTAM, this study emphasizes service robot interactivity as the most important aspect for customers' acceptance, and it adds a new perspective regarding the underexplored role of the customer-robot interface. Combining specific dimensions from different technology acceptance models (functional/socio-emotional/relational; utilitarian/hedonic) the study contributes to the service robot literature currently missing a more holistic understanding of consumers' experience and adoption drivers, and it provides managerial guidance on how to successfully implement service robots in hotel environments.

This paper aims to conduct an experiment that investigates the effect of the ambiguity present in international financial reporting standards (IFRS) on the judgments of auditors. This paper also examine the effects of the personality trait of ambiguity tolerance on judgments of auditors.

This paper conduct an experiment in which experienced Australian-based auditors are placed in hypothetical revenue recognition and lease classification decision contexts. The participants are members of the Australian accounting profession who are familiar with applying IFRS.

This paper find support for the perception that when the relevant IFRS are more ambiguous, auditors make less aggressive reporting judgments compared to when the IFRS are less ambiguous. The results also unveil a novel finding that auditors who are more tolerant of ambiguity are likely to choose the accounting treatment that best reflects the economic substance of a transaction when interpreting IFRS compared to those who are less tolerant of ambiguity.

These results would be of interest to policymakers and accounting researchers as they continue to contemplate a shift to more principles-based IFRS.

To the best of the authors’ knowledge, this study is the first to examine the influence of an individual’s ambiguity tolerance on financial reporting quality in jurisdictions that have adopted IFRS.

The purpose of this study is to ascertain service quality (halal values, assurance, meal quality, reliability, security, system and traceability) and perceived risks (financial, quality, environment, social, time, psychology and health) and its influence on satisfaction, as well as trust concerning online halal food delivery system (OHFDS).

This study uses quantitative methodology, through an online survey, by using purposive sampling across a sample size of 423 respondents. The analysis of data was conducted using SmartPLS.

The results of the findings indicate that assurance and halal values have an influence on satisfaction, as well as trust; nonetheless, only reliability has an impact on satisfaction. On the other hand, perceived health and financial risks have negative influence on trust and satisfaction toward OHFDS. In addition, perceived psychological and financial risks are found to have negative impacts on trust of OHFDS.

The theoretical value of this study is the testing of perceived service quality and risks concerning OHFDS in the same model, thereby contributing to a deeper understanding of its impact on trust and satisfaction toward the online food service delivery industry. The results of this study may appear as a starting point for researchers who wish to conduct further studies on the same topic.

This study suggests that the service providers need to boost their efforts in establishing high quality service and, simultaneously, reduce perceived risks, to develop satisfaction and trust toward OHFDS.

The long-term consequence of the business's achievement is that it makes it simpler for customers to have confidence in, be satisfied with and recommend the service providers to others.

A number of research investigations have been conducted among Muslims, specifically in the Asian region, which have yielded crucial data regarding consumer behavior toward halal products, such as food and tourism. This study, nonetheless, remains close with other studies on halal food, except that it adds together the knowledge of perceived quality and risks, as to gain a deeper understanding of the experience customers have on food, through online service delivery.

This study aims to identify motivations for visiting Kyoto's prominent religious attractions using latent Dirichlet allocation (LDA) text analysis of online reviews; establish linkages between push motivational factors and pull factors of the religious sites, forming distinct tourist typologies; and suggest strategies for Kyoto's destination marketing based on the findings.

This study analyzed 37,772 TripAdvisor reviews for Kyoto's top 25 religious sites from the pre-pandemic period (March 2020). LDA topic modeling extracts 18 underlying thematic dimensions from the review texts. Axial coding of these dimensions revealed five distinct tourist motivation typologies.

Five motivation typologies emerged: cultural seekers drawn to Japan's unique heritage, nature lovers attracted by scenic landscapes, chrono-seasonal experiencers seeking distinct seasonal views, crowd-avoiders prioritizing less congested visits and city wanderers engaging in local activities.

The findings offer valuable guidance for destination marketers and managers in Kyoto, enabling the development of targeted strategies to enhance visitor experiences and manage overcrowding at popular religious sites.

This research provides novel insights into nonreligious tourists' motivations for visiting religious sites in a crowded destination. By identifying distinct motivation-based tourist typologies, the study informs strategies for enhancing visitor experiences tailored to diverse needs, contributing to tourism literature and practical destination management.

This study aims to investigate the effects of IFRS convergence on market liquidity and to analyze the firm-level heterogeneity in liquidity effects based on reporting incentive, firm size, ownership structure and firm leverage.

The empirical analysis is based on firm-fixed effect regression using several proxies of market liquidity as dependent variables. The sample consists of 337 firms listed on the National Stock Exchange (NSE) who shifted to IFRS from the financial year 2016–2017.

The empirical findings indicate that IFRS convergence has contributed to the significant increase in market liquidity in a weaker enforcement country, i.e. India. Additionally, when the study performs the heterogeneity test of IFRS impact, the results indicate the presence of significant cross-sectional differences in such liquidity effects across firms. Thus, altogether the findings suggest that both accounting convergence and firm-level factors are likely to be the mechanism underlying the observed improvement in market liquidity.

In the current literature, there is an ongoing debate about whether the observed post-IFRS effects are driven by the change in accounting standard per se or by other related factors. Therefore, by studying the liquidity effects of IFRS convergence in India, this study provides evidence regarding the sources of the documented IFRS effects. Moreover, the study indicates the significance of firm-level factors in determining the observed liquidity outcomes around IFRS adoption, which is unique to the literature.

This research investigates the differential impact of information technology (IT) investments based on their features, such as investment in data management capability, security improvement, IT outsourcing or new IT infrastructure. The Long-Horizon Event Study (LHES) is essential for providing a more appropriate measure of the value of IT investments because firms' strategic decisions often set long-horizon and large-scale organizational goals, and there is inherent uncertainty regarding future cash flows resulting from these investments. Therefore, the authors aim to analyze how announcements of IT investments affect the firm's abnormal stock returns over the long term and to compare the differential impact of different features of IT investment.

The authors gathered IT investment announcements and stock data of listed firms in Korea between 2000 and 2018, and the monthly stock market returns over the 5 years after the announcements. To measure the differential impact of IT investments based on the investment features, the authors separate announcements data into five groups. A LHES is used to estimate the long-term effects of IT investment announcements.

The results indicate that announcements of IT investments had a long-term positive effect on firm performance. Additionally, the findings reveal differential effects of IT investments across industries and investment features. Notably, news of self-developed IT investments and IT investments in the manufacturing industry had significantly positive effects. However, contrary to common belief, announcements of investments in so-called essential IT areas such as data, security, or new IT infrastructure did not yield significant effects.

Although the need for LHES has been emphasized in information systems research, few follow-up studies have been conducted since Barua and Mani (2018). This is primarily due to the challenges associated with collecting large-scale abnormal stock returns data over a long horizon. This research represents the first LHES to investigate the differential impact of IT investments based on their features. By doing so, this study can provide valuable insights for decision-makers within firms, helping them understand the time horizon of market outcomes of IT investments based on their features. Furthermore, this work extends the scope of LHES to comprehend the differential impacts of investment features. For instance, managers need to grasp that so-called essential IT investments, such as data management, security enhancements or new IT infrastructure, may not necessarily generate long-term market value.

The purpose of this study is to examine how the pandemic impacted on business-to-business (B2B) cooperation and coordination, as well as on firms' financial and operational performance, from the B2B context in the era of knowledge economy.

With the help of social network theory, coordination theory and existing literature, a theoretical model was developed conceptually. Later, the conceptual model was validated using structural equation modelling technique with consideration of 712 respondents from different firms who are engaged in managing B2B relationships on behalf of their firms.

The study found that the COVID-19 pandemic has had a considerable moderating impact on the relationship between B2B cooperation and coordination with B2B relationship satisfaction. The study also highlighted that there is a degradation of financial and operational performance of firms due to the impact of COVID-19 pandemic on their B2B relationship management.

There is a challenging and ever-evolving global economy caused by the COVID-19 pandemic. Although it is argued that the pandemic has accelerated the growth of some online firms, it has also had a catastrophic effect, culminating in many firms failing. This study has developed a new business model which helps in improving financial as well as operational performance of the firms in post COVID-19 scenario, especially in the era of knowledge economy.

This is a unique study as this study (1) develops a unique theoretical model with high explanative power, (2) demonstrates how digital reliance and new business model help the firms in post COVID-19 pandemic and (3) adds to the body of literature in the domain of digital reliance, knowledge economy and B2B relationship management.

The COVID-19 pandemic was a shock to the food supply chain without modern precedent. Challenges in production, manufacturing, distribution and retailing led to the highest rates of food price inflation in the US since the 1970s. The major goal of this paper is to describe statistically the impact of the pandemic of food price inflation and volatility in the US and to discuss implications for industry and for policymakers.

We use Bureau of Labor Statistics data to investigate food prices in the US, 2020–2021. We apply 16 statistical approaches to measure price changes and volatility and three regression approaches to measure counterfactuals of food prices, had the pandemic not occurred.

Food price inflation and volatility increased substantially during the early months of the pandemic, with a great deal of heterogeneity across food products and geographic regions. Food price inflation was most pronounced for meats, and contrary to expectations, highest in the western US Forecasting approaches demonstrate that grocery prices were about 7% higher than they would have been without the pandemic as of the end of 2021.

The research on COVID-19 and the food system remains in its nascent stage. As findings on food loss and waste, employment and wages, food insecurity and more proliferate, it is vital to understand how food prices were connected to these phenomena and affected. We also motivate several ideas for future work.