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The literature on knowledge management in sustainable supply chain (KMSSC) has witnessed significant growth in the past two decades. However, a scientometric review that consolidates the primary trends and clusters within this topic has been notably absent. This paper aims to scrutinize recent advancements and identify the intellectual underpinnings of KMSSC research conducted between 2002 and 2022.

The present review employs a scientometric analysis approach via visualization maps of prolific contributions, co-citation, co-occurrence and thematic networks to examine a total of 114 articles and conference papers on KMSSC.

Emerging research frontiers and hotspots are revealed and a state-of-the-art framework of KMSSC research structure is developed.

The review provides significant implications that guide KMSSC research and better inform sustainability decisions in the supply chain context.

To the best of the authors' knowledge, this is the first review to thoroughly synthesize the intersected domain of KMSSC using scientometric analysis.

This study aims to predict the impact of utilitarian and hedonic motivations on using enterprise social network (ESN) systems for sharing internal and external knowledge, as well as their effects on employee productivity.

Responses of 115 ESN system users from a wide spectrum of firms have been validated and analysed by means of structural equation modelling using partial least squires (PLS-SEM) method.

The results indicate that using ESN to share internal and external knowledge has a positive significant impact on employee productivity. Surprisingly, empirical analysis reveals that using ESN tends to be significantly influenced by hedonic rather than utilitarian motivations.

The study is an early empirical attempt that examines using ESN for knowledge sharing, emphasizing its upstream motivational influence and downstream business impact. It also offers managers and ESN vendors a frame of reference to maximize the use of ESN in the workplace to boost employees’ productivity within various contexts.

The purpose of this paper is to predict Twitter satisfaction by healthcare professionals through integrating constructs of Csikszentmihalyi’s flow theory, quality dimensions and usefulness.

Survey responses of 108 physicians from a variety of specialisations in the United Arab Emirates have been validated and analysed by means of partial least squares-based structural equation modelling method using smartPLS software.

Service quality has emerged as the most influential quality dimension that positively impact flow state and perceived usefulness of Twitter, while information quality, surprisingly, does not show any effect. The findings also indicate that flow state plays a significant role in shaping physicians’ satisfaction with Twitter. The study also enhances our understanding concerning the effects of perceived usefulness on flow state and satisfaction.

Understanding factors that influence Twitter satisfaction can help healthcare managers construct appropriate intervention strategies for maximising professional benefits of social media and minimising user resistance. This is important because top managers usually ratify traditional practices that are only of limited effect. Also, the findings help vendors to accentuate user’s concerns in addition to system functionalities in social media applications.

The paper is an early attempt to propose a model for social media success in a professional context in general and healthcare in particular. It also one of first studies that examine social media satisfaction through integrating contemporary information system success and acceptance models with flow theory.

The rapid global changes we are witnessing pose a pressing challenge that necessitates reevaluating conventional supply chain practices. Consequently, the integration of digital technologies into supply chain operations, often referred to as digital supply chain (DSC), has emerged as a strategic shift that aims to empower organizations to proactively seize new opportunities rather than being caught off guard by unforeseen disruptions arising from economic volatility, global pandemics and regional conflicts. Thus, this study embraces a knowledge-centric approach to explore the direct and indirect impact of knowledge management, innovation and learning capabilities on DSC adoption in an emerging economy context. Furthermore, it aims to shed light on the moderating role of environmental dynamism in this intricate interplay.

Employing a cross-sectional survey, the research data were collected from 354 managers representing Egyptian manufacturing and service firms utilizing a structured questionnaire. Data analysis was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM).

The results unveiled that knowledge management capability (KMC) has the highest path coefficient value among all endogenous variables. It accounts for a significant portion of the variance in innovation and learning capabilities, which play pivotal roles in adopting DSC. Notably, learning capability appears to exert a more powerful influence on DSC adoption than innovation capability through direct and mediating effects. Furthermore, the findings underscore the moderating effect of environmental dynamism on the relationship between learning capability and DSC adoption. However, this moderating role is not observed in the link between innovation capability and DSC adoption.

There is a growing trend among firms to adopt DSC in response to significant environmental shifts. This study offers valuable insights for managers and policymakers, providing them with a deeper understanding of the DSC adoption process. The study’s findings assist in identifying crucial factors that boost DSC adoption and offer guidance on successfully leveraging digital technologies for managing supply chain practices. Moreover, the study offers stimulating directions for future DSC research directions.

The study contributes to the existing literature by expanding our understanding of the adoption of DSC by utilizing knowledge, innovation and learning capabilities within the context of emerging economies.

This paper has predicted digital supply chain (DSC) adoption through the role of firms' proactiveness, knowledge management capability (KMC), innovation ambidexterity and the moderating effect of environmental dynamism.

Survey data from 354 managers in manufacturing and service firms were analysed using the PLS-SEM model.

The present study's findings ascertained the significant role of innovation ambidexterity in influencing DSC adoption, given that innovation exploration's direct and mediating impacts were greater than innovation exploitation's. Firms' proactiveness had the highest path coefficient value among the endogenous variables as an indispensable source for firms to successfully embrace KMC and innovation ambidexterity. The role of firm size on DSC adoption was also significant, revealing that SMEs were more likely than larger firms to adopt DSC practices. Despite its significant effect on innovation ambidexterity, KMC surprisingly exhibited no direct influence on DSC adoption. Furthermore, the findings demonstrated the significant moderating role of environmental dynamism on the effect of KMC on innovation exploration.

This research endeavour has presented valuable insights for scholars and managers, furnishing them with a framework to facilitate decision-making processes regarding adopting DSC practices. A key insight gleaned from this study has been the remarkable value of firms' proactive behaviour and innovation ambidexterity in facilitating DSC adoption decisions. Such adoption has empowered organisations to deploy appropriate interventions and allocate resources efficiently, considering the pivotal role of innovation exploration in contrast to the relatively limited impact of innovation exploitation within this context. Managers may also underscore the significance of firm size in shaping DSC adoption decisions. Small- and medium-sized enterprises (SMEs) have been more likely to embrace DSC initiatives than their larger counterparts. The agile scale and streamlined organisational structures of SMEs often translate into faster decision-making processes, allowing for DSC adoption with relative ease. SMEs might also exhibit a greater openness to reap the benefits associated with DSC systems, such as improved operational efficiency and cost reduction.

The present study has advanced DSC adoption research by examining innovation ambidexterity, knowledge management capability and firms' proactiveness. It has also provided valuable insights for scholars and managers, presenting a framework for decision-making processes regarding DSC adoption in an emerging economy context.

Research on the Internet of Things (IoT) has gained momentum in various industry contexts. However, the literature lacks broad empirical evidence on the factors that influence users' intention to adopt this cutting-edge technology, especially in the food and beverage industry (F&BI) – a significant yet unexplored setting. Therefore, the authors aim to extend the “Unified Theory of Acceptance and Use of Technology (UTAUT)” model by coupling it with perceived collaborative advantage, organizational inertia and perceived cost and explore the key determinants of IoT adoption for the digital transformation of the F&BI.

This study employs a cross-sectional quantitative approach, where a sample of 307 usable responses was drawn from the senior managers of the Australian F&BI.

The authors have found that performance expectancy, perceived collaborative advantage, effort expectancy, social influence and facilitating conditions have a strong positive influence on the behavioural intention to adopt IoT for the digital transformation of the F&BI. Furthermore, while high perceived costs and organizational inertia are often considered negative factors in adopting new technology, our results reveal the insignificant influence of these factors on the adoption of IoT, which is interesting. The findings also suggest that age and voluntariness significantly moderate most of the relationships, while gender is an insignificant moderator.

The study provides several novel insights into the existing body of knowledge by extending the UTAUT model with three variables and applying it in a unique context.

Despite considerable growth in literature on Industry 4.0 technologies, the research on the factors influencing the investment on these technologies in pursuit of supply chain 4.0 is yet incipient. The study aims to fill this knowledge void by exploring the perceived drivers and barriers intertwined in the implementation of supply chain 4.0 in the context of food and beverage industry.

Qualitative exploratory research was employed involving 20 semi-structured interviews with senior managers from the Australian food and beverage supply chain. The interviews' data were analysed with VOSViewer software version 1.6.14.

The results unravel that reduction in supply-demand misalignment, fast-changing consumer's needs, threat of legal penalties and cost optimisation are the key drivers; whereas lack of collaboration, organisational inertia and lack of awareness are the critical barriers to implement supply chain 4.0.

The study derives seven propositions and a theoretical framework that need to be empirically corroborated.

Understanding of drivers and barriers will help practitioners to make more informed decision in implementation of supply chain 4.0.

Implementation of supply chain 4.0 can enhance the performance of the food and beverage industry, thus offering more job opportunities and sustained food supply.

This is the first study in exploring drivers and barriers to the implementation of supply chain 4.0; thus, adds new knowledge to the growing body of the literature. The paper introduces a novel method for qualitative data analysis contributing to the methodological development of the supply chain management field.

Ostracism is a common challenge in the workplace, but little is known about the behaviours of those who trigger it. The authors examined how leader favouritism can drive coworkers to ostracise one another, given that leadership is a key factor in shaping employee attitudes and behaviour. Invoking social comparison theory, the authors assessed a model of how perceived favouritism affects ostracism through jealousy, moderated by organisation-based self-esteem (OBSE).

The authors surveyed 294 non-managerial employees from several service organisations in the United Arab Emirates (UAE) and analysed the data with partial least squares structural equation modelling (PLS-SEM) using SmartPLS 3 software.

Unexpectedly, leader favouritism did not directly affect ostracism but only indirectly through the mediation of jealousy. OBSE was found to moderate this relationship, suggesting that higher levels of OBSE can weaken the impact of leader favouritism on employee jealousy.

These findings explain the intricate dynamics and underlying reasons as to how leader favouritism can instigate employee-to-employee ostracism.

Rapid changes in the global environment and the effects of existing economic issues triggered by COVID-19 and the war in Ukraine have posed several challenges for manufacturing firms. A hybrid strategy integrating lean and agile (leagile) systems is viable for firms to enhance their capabilities in such dynamic contexts. This paper examines the critical drivers of leagile manufacturing system adoption in an emerging economy from the technological, organizational and environmental (TOE) perspective.

A cross-sectional survey is carried out to obtain data from 438 managers working in 219 manufacturing firms. Multiple regression analysis is applied to test the effect of technological, organizational and environmental drivers on the adoption of leagile systems.

The results show that organization capacity, environmental uncertainty and relative advantage demonstrate the most significant positive relationships with the leagile systems adoption wherein complexity and resistance to change appear to exhibit significant negative associations. Unexpectedly, firm size unveils no significant effect on the adoption of leagile systems.

To deal effectively with critical challenges triggered by ever-changing environment, firms have sought to adopt innovative systems for achieving products' availability in the markets at the right quality and price. A hybrid strategy integrating lean and agile (leagile) systems is viable to enhance a firm's capabilities in such dynamic contexts. The findings of our study help top management and policymakers identify and assess the critical drivers that may facilitate or hinder the successful adoption of leagile systems.

A major trend of studies in the field of manufacturing systems has focused on the critical success factors of adopting either lean or agile systems. Furthermore, research work concerning leagile as a hybrid system focuses primarily on the conceptual development rather than empirical grounds of leagile systems. Given the lack of empirical research in this field, this study offers an early attempt to predict leagile system adoption in an emerging economy. It also contributes to the manufacturing systems research by extending the extant knowledge about the role of firm-level drivers in leagile system adoption from the TOE perspective.

This paper aims to examine the technology-organization-environment (TOE) predictors of green information technology adoption in an emerging economy, namely, the United Arab Emirates (UAE) and their impact on work performance among UAE organizations.

A paper-based survey was carried out by engaging employees in different organizations in the UAE. The “partial least squares” (PLS) method was used to test and analyze the measurement and the structural research models.

The analysis shows support to all the hypotheses, with the exception of the influence of competitive force.

The results can be valuable for practitioners and decision-makers in the emerging economy context as the results will help them validate their adoption decisions and effectively contribute to sustainability strategies.