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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.

During the supply chain disruptions caused by COVID-19, logistics service providers (LSPs) have invested heavily in innovations to enhance their supply chain resilience capabilities. However, only little attention has been given so far to the nature of these innovative capabilities, in particular to what extent LSPs were able to repurpose capabilities to build supply chain resilience. In response, using the concept of exaptation, this study identifies to what extent LSPs have discovered and utilized latent functions to build supply chain resilience capabilities during a disruptive event of high impact and low probability.

This conceptual paper uses a theory building approach to advance the literature on supply chain resilience by delineating the relationship between exaptation and supply chain resilience capabilities in the context of COVID-19. To do so, we propose two frameworks: (1) to clarify the role of exaptation for supply chain resilience capabilities and (2) to depict four different exaptation dimensions for the supply chain resilience capabilities of LSPs.

We illustrate how LSPs have repurposed original functions into new products or services to build their supply chain resilience capabilities and combine the two critical concepts of exploitation and exploration capabilities to identify four exaptation dimensions in the context of LSPs, namely impeded exaptation, configurative exaptation, transformative exaptation and ambidextrous exaptation.

As one of the first studies linking exaptation and supply chain resilience, the framework and subsequent categorization advance the understanding of how LSPs can build exapt-driven supply chain resilience capabilities and synthesize the current literature to offer conceptual clarity regarding the varied implications and outcomes linked to the repurposing of capabilities.

Stakeholder capitalism has gained attention among business practitioners and academia, often discussed within the context of corporate social responsibility, ethical practices and values-based leadership. Many societal institutions, including businesses and higher education institutions, have a role to play in the transition toward stakeholder capitalism. This study aims to discuss insights gained from a multiyear research and pedagogical project coordinated among a group of academics and an Israel-based holding company to study the implementation of a values-based leadership process focused on establishing a stakeholder-oriented model in a variety of organizations.

Conducted over a decadal period, this project relied on a qualitative case study methodology. The project was conceived as an exploratory and inductive study examining organizations that implemented a values-based leadership model and a university that used this model for curriculum and pedagogy. Semi-structured interviews, observations of leadership practices and operations, and substantive reviews of organizational documents informed the study’s iterative methodology.

The case studies presented explore the benefits of a stakeholder capitalism and values-based leadership transformation in organizations and highlight the importance of senior leadership engagement at the outset to set the tone and direction of implementation while also role modeling values-based behaviors for the organization. The utility of aligning the new values-based approach with existing elements of the organizational culture and priorities was also identified in addition to the benefit of individuals linking the new values initiative to their personal values and life. These practices, and a broader stakeholder dialogue on values, helped establish a transition that was inclusive within the organizational hierarchy and in its connections to the larger society. The cases also explored how stakeholder principles and values-based leadership models can be integrated into management education based on the outcomes of the organizational investigations.

These case studies offer insight into the implementation of a values-based leadership framework, which draws on stakeholder theory, in diverse organizations across a for-profit to non-profit spectrum. These studies also provide a unique opportunity to evaluate the implementation of a common values framework in different sectors. The cases further highlight the potential role of business-education sectoral partnerships in educating a workforce that is dedicated to business for good.

This study aims to investigate the manufacturing reshoring decision-making content from an Eclectic Paradigm perspective.

Data were collected through a six-step systematic literature review on factors influencing manufacturing reshoring decision-making. The review is based on 100 peer-reviewed journal papers discussing reshoring decision-making contents published from 2009 to 2022.

In total, 80 decision factors were extracted and then categorized into resource-seeking (8%), market-seeking (11%), efficiency-seeking (41%) and strategic asset-seeking (16%) advantages. Additionally, 24% of these were identified as hybrid, which means that they were classified into multiple categories. Some decision factors were further identified as reshoring influencing factors (i.e. drivers, enablers and barriers).

Scholars need to consider what other theories can be used or developed to identify and evaluate the decision factors (determinants) of manufacturing reshoring as well as how currently adopted theory can be further advanced to create clearer and comprehensive theoretical frameworks.

This research underscores the importance of developing clearer and more comprehensive theoretical frameworks. For practitioners, understanding the multifaceted nature of decision factors could enhance strategic decision-making regarding reshoring initiatives.

To the best of the authors’ knowledge, this is the first study to investigate the value and practicality of the Eclectic Paradigm in categorizing factors in manufacturing reshoring decision-making content and presents in-depth theoretical classifications. In addition, it bridges the gap between decision factors and influencing factors in the decision-making content research realm.

This paper aims to explore the implications of algorithmic management on careers and employment relationships in the Nigerian gig economy. Specifically, drawing on labour process theory (LPT), this study provides an understanding of the production relations beyond the “traditional standard” to “nonstandard” forms of employment in a gig economy mediated by digital platforms or digital forms of work, especially on ride-hailing platforms (Uber and Bolt).

This study adopted the interpretive qualitative approach and a semi-structured interview of 49 participants, including 46 platform drivers and 3 platform managers from Uber and Bolt.

This study addresses the theoretical underpinnings of the LPT as it relates to algorithmic management and control in the digital platform economy. The study revealed that, despite the ultra-precarious working conditions and persistent uncertainty in employment relations under algorithmic management, the underlying key factors that motivate workers to engage in digital platform work include higher job flexibility and autonomy, as well as having a source of income. This study captured the human-digital interface and labour processes related to digital platform work in Nigeria. Findings of this study also revealed that algorithmic management enables a transactional exchange between platform providers and drivers, while relational exchanges occur between drivers and customers/passengers. Finally, this study highlighted the perceived impact of algorithmic management on the attitude and performance of workers.

The research presents an interesting case study to investigate the influence of algorithmic management and labour processes on employment relationships in the largest emerging economy in Africa.

This study aims to describe the m-learning experience of school students and teachers during the COVID-19 pandemic and explores the factors influencing the continuance intention of m-learning.

Semistructured interviews of 24 students and 09 teachers of schools in national capital territory (NCT) Delhi, India were conducted over 03 months and transcribed verbatim. A hermeneutic phenomenological design was used to interpret the text and bring out the “lived experiences” of m-learning.

The following 15 themes or factors influencing continuance intention emerged through the hermeneutic circle: (1) actual usage, (2) attitude, (3) context, (4) extrinsic motivation, (5) facilitating conditions, (6) intrinsic motivation, (7) perceived compatibility, (8) perceived content quality, (9) perceived mobile app quality, (10) perceived teaching quality, (11) perceived usefulness, (12) satisfaction, (13) self-efficacy, (14) self-management of learning and (15) social influence.

The study offers insightful recommendations for school administrators, mobile device developers and app designers. In addition, suggestions for effectively using m-learning during disasters such as COVID-19 have been provided. Several future research directions, including a nuanced understanding of m-assessment and online discussions, are suggested to enhance the literature on m-learning continuance.

The study enriches the literature on m-learning continuance. A qualitative approach has been used to identify relevant factors influencing m-learning continuance intention among secondary and higher secondary level (Grades 9 to 12) school students and teachers in India. In addition, a conceptual framework of the relationships among the factors has been proposed. Further, an analysis of the lived experiences of m-learning during the COVID-19 pandemic indicated several issues and challenges in using m-learning during disasters.

The study aims to provide a critical review of the extent to which digital technologies are likely to replace human labour, the exponential rise in the amount of work to be done and how far distinctively human skills are future-proofed and therefore likely to be in short supply. It reviews the evidence for a permanent switch to home and remote working enabled by emerging technologies. It assesses the business, digital and labour strategies of work organisations and the promise and challenges from a dominant trend towards a digitally enabled flexible labour model.

A critical review of 1020 plus case studies and the extant literature was carried out.

The relationship between emerging technologies and work is widely misunderstood, and there are major qualifiers to the idea of an overwhelming tsunami of technology drastically reducing headcounts globally. Distinctive human skills remain valuable, the amount of work to be done is increasing exponentially and automation is becoming more a coping than a labour replacement mechanism. Moves to a hybrid digitalised flexible labour model are promising but not if short-term, and if the challenges they represent are not managed well.

The main limitation is that we are making projections into the future, though we are drawing on a lot of different sources and evidence and past data projected into the future.

The problem is not labour displacement but large skills shortages that will slow down the speed of technology adoption. Skills development is vital, as is the taking of long-term perspectives towards the management of hybrid, flexible working based on human-machine interactions.

Organisations need to revitalise their training and development and labour management models. Governments and intermediary institutions need to manage transition states if the skills required to gain economic growth are to be available, and to ensure that large labour pools do not get bypassed from not having requisite skills.

The study offers a more subtle and complex perspective on the emerging evidence about the future of technology and work.

This study aims to investigate the antecedents of behavioral intention and actual usage of mobile payment (m-payment) services during the COVID-19 pandemic among Indian consumers.

The proposed research model of this study is based on the extended framework of the Unified Theory of Acceptance and Use of Technology (UTAUT2) by using two additional variables, namely, perceived security (PS) and perceived trust (PT). In total, 436 sample respondents are chosen from Indian consumers with experience using m-payment services through the online survey method. The data analysis and proposed hypothetical relationships were tested using confirmatory factor analysis and structural equation modeling techniques.

The results confirm that performance expectancy, effort expectancy, facilitating conditions, PS, PT, habit and price value are antecedents of consumer intention toward adopting m-payment services. Furthermore, behavioral intention significantly influences the actual usage of m-payment services during the COVID-19 pandemic.

Though the impact of COVID-19 has been observed during the research period in getting responses from m-payment service users, the constructs used in the study are confined to the UTAUT2 model, and dimensions related to COVID-19 are not directly included in the measurement scale. The study’s findings propose valuable insights for service providers and policymakers.

This study’s results offer valuable insights to the service providers and policymakers to achieve the Government of India digital India objective of “Faceless, Paperless and Cashless” transactions.

This study’s results contribute to extending the empirical research literature on m-payment as antecedents of behavioral intention toward the adoption of m-payment services during the COVID-19 pandemic. Furthermore, this study assumes important interrelationships among UTAUT2 constructs with the additional incorporation of PS and PT.

This study employs firm-level data to evaluate how the knowledge economy impacts the financing constraints of businesses across 106 low- and middle-income nations, focusing on the influence of technological transformation on corporate financing choices.

The research centers on privately held, unlisted firms and examines the distinct effects of knowledge at both the within-country and between-country levels using a panel dataset. Rigorous sensitivity and endogeneity analyses are conducted to ensure the reliability of the findings.

The findings indicate that greater levels of the knowledge economy correlate with reduced financing constraints for firms. However, this effect varies depending on the location within a country and across different geographical regions. Firms situated in larger urban centers and more innovative regions reap the most significant benefits from the knowledge economy when seeking external funding. Conversely, firms in smaller cities, rural areas and regions characterized by structural and institutional inefficiencies in knowledge generation experience fewer advantages.

The impact of knowledge exhibits variability not only within and among countries but also between poor and affluent developing nations, as well as between larger and smaller countries. The knowledge effect on firms' access to external finance is influenced by factors such as financial openness and development, educational quality, technological absorption capabilities and agglomeration conditions within each country.

Due to changing consumer thinking patterns and market dynamics, the quick service restaurant (QSR) industry has changed dramatically in the past few years. Considering this, this study aims to examine the influence of perceived brand globalness and perceived brand localness on consumer word of mouth through brand attitude by considering consumer ethnocentrism and perceived brand origin as moderators.

This study obtained 750 responses from Turkish consumers through a survey and analyzed the data using the maximum-likelihood estimation technique with structural equation modeling.

This study discovered that perceived brand globalness and perceived brand localness are critical components that drive brand attitude, influencing consumers' WOM toward global and local QSR brands. Similarly, perceived brand globalness and perceived brand localness are important brand attributes influencing consumer WOM. Importantly, this study found the significant effects of perceived brand origin on brand attitude mainly toward perceived local brands compared to global QSR brands. Although this study did not uncover the influence of consumer ethnocentrism as expected. However, these insights may assist global and local managers to rethink their strategies toward Turkish consumer settings.

This study was conducted exclusively in Turkey. However, additional studies in other countries, such as the comparative Asian versus European consumers' perspectives, may be considered to generalize the findings.

This study provides recommendations to global and local managers to support them in designing and executing several brand positioning strategies in the QSR industry.

This novel study contributes to the accessibility diagnostic theory and signaling theory by examining consumers' perceptions of local and global brands.