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Entrepreneurs are generally considered to be committed in order to strive for highly desirable goals, such as growth or commercial success. However, commitment is a multidimensional concept and may have asymmetric relationships with positive or negative entrepreneurial outcomes. This paper aims to provide a nuanced perspective to show under what conditions commitment may be detrimental for entrepreneurs and lead to overinvestment.

Using a sample of entrepreneurs from incubators in France (N = 437), this study employs a configurational perspective, fuzzy-set qualitative comparative analysis (fsQCA), to identify which commitment profiles lead entrepreneurs to overinvest different resources in their entrepreneurial projects.

The paper exposes combinations of conditions that lead to overinvestment and identifies five different commitment profiles: an “Affective profile”, a “Project committed profile”, a “Profession committed profile”, an “Instrumental profile”, and an “Affective project profile”.

The results show that affective commitment is a necessary condition for entrepreneurs to conduct overinvesting behaviors. This complements previous linear research on the interdependence between affect and commitment in fostering detrimental outcomes for nascent entrepreneurs.

The purpose of this study is to analyze state-of-the-art knowledge of artificial intelligence (AI) research in hospitality.

This study adopts the theory-context-methods framework to systematically review 100 AI-related articles recently published (i.e. from 2021 to April 2023) in three top-tier hospitality journals, namely, the International Journal of Contemporary Hospitality Management, International Journal of Hospitality Management and Journal of Hospitality Marketing and Management.

Findings suggest that studies of AI applications in hospitality are mostly theory-driven, whereas most AI methods research adopts a data-driven approach. State-of-the-art AI applications research exhibits the most interest in service robots. In AI methods research, little attention was paid to the amid-service/experience.

This study reveals inadequacies in theory, context and methods in contemporary AI research. More research from hospitality suppliers’ perspectives and research on generative AI applications are advocated in response to the unveiled research gaps and recent AI developments.

This study classifies the most recent AI research in hospitality into two main streams – AI applications research and AI methods research – and discusses the gaps in each research stream and latest AI developments. The paper then suggests future research directions to guide researchers in advancing AI research in hospitality.

In the rapidly evolving digital economy, businesses face formidable pressures to maintain their competitive standing, prompting a surge of interest in the intersection of artificial intelligence (AI) and digital transformation (DT). This study aims to assess the impact of AI technologies on corporate DT by scrutinizing 3,602 firm-year observations listed on the Shanghai and Shenzhen stock exchanges. The research delves into the extent to which investments in AI drive DT, while also investigating how this relationship varies based on firms' ownership structure.

To explore the influence of AI technologies on corporate DT, the research employs robust quantitative methodologies. Notably, the study employs multiple validation techniques, including two-stage least squares (2SLS), propensity score matching and an instrumental variable approach, to ensure the credibility of its primary findings.

The investigation provides clear evidence that AI technologies can accelerate the pace of corporate DT. Firms strategically investing in AI technologies experience faster DT enabled by the automation of operational processes and enhanced data-driven decision-making abilities conferred by AI. Our findings confirm that AI integration has a significant positive impact in propelling DT across the firms studied. Interestingly, the study uncovers a significant divergence in the impact of AI on DT, contingent upon firms' ownership structure. State-owned enterprises (SOEs) exhibit a lesser degree of DT following AI integration compared to privately owned non-SOEs.

This study contributes to the burgeoning literature at the nexus of AI and DT by offering empirical evidence of the nexus between AI technologies and corporate DT. The investigation’s examination of the nuanced relationship between AI implementation, ownership structure and DT outcomes provides novel insights into the implications of AI in the diverse business contexts. Moreover, the research underscores the policy significance of supporting SOEs in their DT endeavors to prevent their potential lag in the digital economy. Overall, this study accentuates the imperative for businesses to strategically embrace AI technologies as a means to bolster their competitive edge in the contemporary digital landscape.

This study aims to explore the connection between demographic traits and the choice of attraction patterns among international repeat tourists.

The study employed a questionnaire survey to collect data from 1550 international repeat tourists who visited Tanzania between November 2022 and July 2023. Convenient sampling was employed as tourists were selected from the three international airports of Tanzania, namely Kilimanjaro International Airport, Julius Nyerere International Airport, and Abeid Aman Karume International Airport. A multinomial logistic regression model was used to examine the impact of socio-demographic characteristics on the selection of attraction patterns among international repeat tourists.

The study revealed that demographic factors, including age, marital status, income level, occupation, and education level, exhibit statistically significant correlations with preferences for distinct attraction patterns. This significance was established through a p-value of less than 0.05 for all the aforementioned variables.

This study is primarily focused on international repeat tourists, thereby limiting insights into the preferences of domestic tourists. To better inform strategies aimed at attracting a larger domestic tourist base, future research may prioritize the investigation of choice of attractions patterns among domestic tourists in relation to their demographic characteristics.

This study contributes to the nuanced understanding of international tourist behavior by unraveling the extent to which demographic traits impact tourists’ choices of attraction patterns, thereby providing insights crucial for effective marketing strategies, improved visitor experiences, and sustainable tourism development strategies.

This study aims to identify the groups of value cocreators in the context of social media in the retail banking industry and resources that predict customer membership among different groups of value cocreators.

This study reviewed the literature and developed measurement instruments for the constructs of interest. Data were collected from 406 customers in an emerging market in 2019 and analyzed using latent profile analysis.

This study identified three profiles of value cocreators on social media based on the actual practices of resource integration that enliven value cocreation. Second, this study explains the differences in the performance of resource integration practices to cocreate by the types of resources that customers integrate into social media. Third, this study fills the need for knowledge of value cocreation in different contexts and industries (e.g. banks).

This study analytically relates a set of resources to the variety and intensity of the value cocreation practices adopted by bank customers in interactive environments. The emphasis on how value cocreation practices in online environments combined with customer resources (e.g., a person-centered approach) allows to identify unique profiles of value cocreators on social media. The findings inform managers of the profiles of cocreators, which customers are more attractive as value cocreators on social media, and which resources managers should help customers develop to increase cocreation on social media.

This empirical study explores the intricate relationships between Industry 4.0 (I4), Lean practices and sustainable operational performance (SOP) within the dynamic context of the services sector. Rooted in the theoretical framework of Resource Orchestration Theory (ROT), the research investigates the nuanced interplay between these paradigms and their collective impact on firm performance.

The research methods included creation of a structural model, hypothesis formulation and advanced data analysis. Primary data were gathered through an online questionnaire distributed among service sector professionals. Analysis was completed using Partial Least Squares (PLS) Structural Equation Modeling (SEM) using the Smart-PLS software.

The results underscore the mediating role of Lean practices between I4 and SOP, emphasizing the imperative of harmonized integration to enhance overall firm performance. In alignment with ROT principles, the study illuminates the positive influence of Lean practices on sustainable operational outcomes.

The study contributes to the scholarly discourse on I4, Lean and Services, emphasizing the strategic necessity of integrating I4 capabilities with Lean practices. Practical insights guide practitioners in orchestrating a balanced adoption of I4 and Lean practices for SOP. This research offers actionable insights for industry leaders seeking to cultivate SOP within their organizational contexts.

This study contributes to the evolving understanding of the interplay between I4, Lean practices and SOP within the services sector, offering novel insights for both academia and industry practitioners.

Corporate Social Responsibility (CSR) reporting has been widely accepted as a vital tool for communicating with stakeholders on a range of social, environmental, and governance issues, but how companies define, interpret, apply, integrate, and communicate their CSR efforts and impacts in corporate reporting is anything but a straightforward task. The purpose of this chapter is to explore the concept of materiality in CSR reporting and demonstrate practical examples of good CSR and Sustainable Development Goals (SDGs) reporting practices. We chose the aviation industry because of its economic relevance, constant growth, and future expected changes in the aftermath of COVID-19. In addition, airlines affect many of the SDGs directly and indirectly with contending results. This chapter is timely because of the growing willingness by companies to integrate CSR and environmental, social, and governance (ESG) thinking into the corporate strategy and business operations using materiality assessment and enhancing their competitive advantage and ability to maintain long-term value and because ESG and ethical investing have become part of the mainstream investing. Thus, this chapter contributes to an understanding of the wide range of existing and new reporting frameworks and regulations and reinforces the importance of discussing how this diversity of approaches can affect the work toward worldwide comparability of CSR and sustainability reporting.

This study aims to explore how social media affects decision-making among tourists and whether there is a potential effect of age, which is studied through generations. For this purpose, baby boomers, Gen X, Gen Y and Gen Z tourists are studied and real-time implications are offered.

The study adopts a descriptive and exploratory design where the conceptual model of social media-based decision-making is developed through a review of the literature. Quantitative analysis is conducted on primary data from 600 Indian tourists. This is done using a self-administered questionnaire adopted from Gulati (2022) after checking its validity and reliability. The statistical analysis for hypothesis testing is done using PLS-SEM path modelling on pooled data. To study the categorical moderating effect of generations, partial least squares multigroup analysis (PLS-MGA) is performed as a paired comparison on every successive generation.

After testing every successive younger generation with an older generation through PLS-MGA, none of the pairs found any significant differences in path coefficients, as the values obtained were 0.05 < p < 0.95 for all five paths (SM → NR, SM → IS, SM → E, SM → P, SM → PPB). This indicates all the generations behave in a similar manner irrespective of them being older or younger, and age does not moderate social media’s impact on decision-making among Indian tourists.

The study establishes India as a unique geographical market and suggests tourism marketers to treat all generations at par, irrespective of age, as they behave and interact with social media in a similar manner. But, because this study is restricted to a single geographical location, i.e. India, further regions can be explored for global generalisation. Future research can also explore other demographics for combined, moderated analysis. Findings from the study suggest that marketers should ensure that equal attention is given to all generations as they engage with social media in a similar manner. Targeted marketing using artificial intelligence can help in ensuring custom ads. Personalisation according to generations can also facilitate greater purchases.

The study fills a major population and knowledge gap by exploring a topic that has been highly under-researched. Also, the study adopts an inclusive approach by analysing all the generations, both younger and older, to understand the potential effect of age on moderating the impact that social media has on tourist decision-making. Further, real-time suggestions and implications are offered to tourism marketers with special reference to the Indian tourism industry.

Teleworking, working from home and flexible work have gained popularity over the last few years. A shift in policies and practices in the workplace is required owing to the COVID-19 pandemic accelerating current trends in work-from-everywhere (WFE) research. This article presents a systematic literature review of WFE research from 1990 to early 2023 to understand the transformation of the field.

The Web of Science database was used to conduct this review based on rigorous bibliometric and network analysis techniques. The prominence of the research studied using SPAR-4-SLR and a collection of bibliometric techniques on selected journal articles, reviews and early access articles. Performance and keyword co-occurrence analysis form the premise of cluster analysis. The content analysis of recently published papers revealed the driving and restraining forces that help define and operationalize the concept of WFE.

The major findings indicate that the five established and accelerated trends from cluster analysis are COVID-19 and the pandemic, telework(ing), remote working, work from home and well-being and productivity. Driving and restraining forces identified through content analysis include technological breakthroughs, work–life integration challenges, inequality in the distribution of jobs, gender, shifts in industry and sector preferences, upskilling and reskilling and many more have been published post-COVID in the restraining forces category of WFE.

A key contribution of this pioneering study of “work from everywhere” is the linking of the bibliometric trends of the past three decades to the influencing and restraining factors during the pandemic. This study illustrates how WFE could be perceived differently post-COVID, which is of great concern to practitioners and future researchers.

A wide range of publications on WFE and multiple synonyms can create confusion if a systematic and effective system does not classify and associate them. This study uses both bibliometric and scientometric analyses in the context of WFE using systematic literature review (SLR) methods.

This paper develops and tests a theoretical model that draws on the Diffusion Contingency Model and the Theory of Human Behavior to explain the factors influencing users’ acceptance of accrual accounting in terms of two distinct dimensions: behavioral intention and usage behavior.

Based on surveyed data from financial departments and directorates of different Greek general government entities, the paper uses factor analysis to build a theoretical model that assesses the factors influencing behavioral intention to adopt and usage behavior of accrual accounting. Then, it tests the relationship between behavioral intention and usage behavior through structural equation modeling.

The theoretical model suggests that the expected improvement of the quality of financial information and political and financial support are the most important determinants of behavioral intention. Usage behavior is mainly influenced by the compatibility between the existing legal framework and the new accounting system. The structural equation modeling identifies a statistically significant positive influence of behavioral intention on usage behavior.

The study provides valuable insights regarding the timing and focus of the actions taken by policymakers when designing accounting reforms. Special attention is drawn to the factors influencing behavioral intentions, as these are found to influence usage behavior significantly.

The study extends prior research on the diffusion of accounting innovations by breaking down the diffusion process into intentions-oriented actions aiming to promote accrual accounting and increase acceptance and implementation-oriented actions aiming to facilitate successful implementation.