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The imperative to conserve resources and minimize operational expenses has spurred a notable increase in the adoption of lean manufacturing within the context of the circular economy across diverse industries in recent years. However, a notable gap exists in the research landscape, particularly concerning the implementation of lean practices within the pharmaceutical industry to enhance circular economy performance. Addressing this void, this study endeavors to identify and prioritize the pivotal drivers influencing lean manufacturing within the pharmaceutical sector.

The outcome of this rigorous examination highlights that “Continuous Monitoring Process for Sustainable Lean Implementation,” “Management Involvement for Sustainable Implementation” and “Training and Education” emerge as the most consequential drivers. These factors are deemed crucial for augmenting circular economy performance, underscoring the significance of management engagement, training initiatives and a continuous monitoring process in fostering a closed-loop practice within the pharmaceutical industry.

The findings contribute valuable insights for decision-makers aiming to adopt lean practices within a circular economy framework. Specifically, by streamlining the process of developing a robust action plan tailored to the unique needs of the pharmaceutical sector, our study provides actionable guidance for enhancing overall sustainability in the manufacturing processes.

This study represents one of the initial efforts to systematically identify and assess the drivers to LM implementation within the pharmaceutical industry, contributing to the emerging body of knowledge in this area.

The main objective of this study is to evaluate the driving forces behind the adoption of indoor environmental quality (IEQ) principles in building designs from the perspectives of Nigerian quantity surveying firms.

A quantitative approach was used which involved administering a well-structured questionnaire to a sample of 114 quantity surveyors. The collected data were analyzed using various statistical methods, including frequencies, percentages, mean item scores, Kruskal–Wallis test and exploratory factor analysis.

The top five ranked drivers were climate change mitigation, conservation of natural resources, reduction of waste and pollution, use of sustainable building materials and development of new materials and building systems. Based on the factor analysis, the study identified five clusters of drivers: (1) health and well-being drivers (2) economic drivers (3) environmental drivers (4) innovation and technology drivers and (5) regulatory drivers.

The findings from this study suggest that to effectively integrate IEQ principles, quantity surveying firms should consider developing comprehensive guidelines and checklists that align with the identified drivers and clustered categories. These resources can serve as practical tools for project teams, facilitating a structured and holistic approach to the incorporation of IEQ factors throughout the project lifecycle.

The study’s identification of the top drivers and the subsequent clustering of these drivers into five distinct categories contributes to the existing body of knowledge on IEQ. This approach provides a structured framework for comprehensively understanding the factors influencing IEQ adoption, offering a valuable tool for researchers, policymakers and industry practitioners.

This study investigates the drivers of CSR practices among construction companies in Lagos, Nigeria.

This research adopted a questionnaire survey to achieve the aim. A purposefully chosen group of managing directors, directors, other senior construction experts or management personnel working for small, medium and large-sized construction enterprises in Nigeria were given questionnaires to complete. 196 questionnaires were issued, out of which 103 were properly completed and returned, with a return percentage of 61% which served as the basis for this study. Utilizing both descriptive and inferential statistics, the collected data were examined.

The results from the study revealed that “vision of the founder”, “creating public attention”, “competitive advantage” and “business strategy” were the top most four drivers of CSR initiatives among construction companies in Lagos, Nigeria. The results also showed that, there is a statistically significant degree of agreement between various categories of construction companies in Lagos, Nigeria regarding the drivers of CSR initiatives.

The study contributes more effectively to CSR studies by highlighting the drivers of CSR initiatives in construction companies. The finding would facilitate the adoption and implementation of CSR initiatives in construction organizations. The adoption of best CSR practices fosters strong relationship among construction companies, project stakeholders and communities.

This study responds to the calls from the literature on identifying interactions among the sustainable supply chain management (SSCM) drivers, which influence focal firms’ SSCM decisions. It also determines how the effect of SSCM drivers differs across the upstream and downstream supply chains (SCs) entities of fast-moving consumer goods (FMCGs) companies.

We employ a multi-method design encompassing three studies: study 1 (multiple-case study), study 2 (quantitative survey), and study 3 (multiple-criteria decision-making or MCDM modeling).

The results show that the external drivers such as customer pressure, competition, and supplier pressure and internal drivers such as top management commitment interact to influence the adoption of SSCM practices, and this interaction is diverse across upstream and downstream SC entities of the FMCG sector. The study provides empirical evidence of relationships among the SSCM drivers, which influence SSCM decisions.

Understanding these interactions will help managers derive strategies to manage the overall SSCM ecosystem and recognize the multiplier effects of upstream to downstream and vice versa.

Drawing on the social identity theory, this paper explores the impact of rider–driver ethnicity match on the driver’s expected ride satisfaction and willingness to perform, and rider’s trust on the driver.

The study relies on scenario-based online experiments with 291 ride-hailing drivers and 282 riders in the USA.

The findings indicate that ethnicity match between ride-hailing drivers and riders positively impact driver’s ride satisfaction and willingness to perform, and rider’s trust in the driver. The study also revealed a significant positive moderation effect of ethnic identity on the relationship of ethnicity match and those constructs.

While it may be challenging to influence an individual’s level of ethnic identity, managers can take steps to educate and train their employees regarding the impact of ethnic identity and discrimination, with a particular focus on those individuals who possess a strong sense of ethnic identity.

The findings of this research provide theoretical contributions to the existing literature on ride-hailing services and adds to the limited stream of logistics research that examines the impact of ethnicity on ride-hailing operations.

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 investigate the role of three customer equity drivers on customer repurchase intent in business-to-business (B2B) markets. It also explores the interconnected nature of equity drivers, specifically, the effects of brand equity and value equity on relationship equity. Further, it investigates how perceived switching costs moderates the interrelationships between customer equity drivers. The authors explore the interrelationships between the customer equity drivers in a B2B context involving commodity products in a developing market.

Data collection was done from a pool of 184 institutional customers of a lubricant brand in a developing market. The sample had representations of buyer organizations across sectors, namely, automobile, cement, metal, fertilizer, railway, defence and mining, etc. The final data were subjected to partial least squares-based structural equation modeling to test the hypothesized model.

The study found a direct effect of brand equity, and value equity on relationship equity and an indirect effect on repurchase intent, namely, relationship equity. Perceived switching cost was found to moderate the interaction between brand equity and relationship equity as well as between value equity and relationship equity. The direct effect of relationship equity on repurchase intent was also significant.

The study implies that B2B firms should ground their marketing program on these customer equity drivers, especially when dealing with commodity products. The absence of any of these drivers would be detrimental in customer retention. The study also establishes the relevance of switching cost(s) and its impact on the underlying dynamics between the different equity drivers in the context of commodity products. The customer equity drivers along with switching costs, if managed well, may become switching barriers for customers and eventually would ensure recurring revenue through repeat purchases.

To the best of the authors’ knowledge, this is one of the first studies that focuses on the disaggregated effect of customer equity on customer outcomes in the B2B context. Furthermore, this study investigates how perceived switching costs moderates the interrelationships between customer equity drivers in the industrial sales context in an emerging market.

Extant studies have discussed numerous carbon reduction drivers, but there is a dearth of holistic review and understanding of the dynamic interrelationships between the drivers from a system perspective. Thus, this study aims to bridge that gap.

The study conducted a review using Preferred Reporting Items for Systematic Reviews and Meta-Analyses and adopted interpretive structural modelling (ISM) to analyse and prioritise the drivers.

Eighteen drivers were identified and grouped into five, namely, policy instruments, bid-related, cost and risk, education and training, and reward and penalty drivers. The ISM revealed two hierarchical levels of the drivers with only higher cost of electricity/fuel on the higher level, making it the most important driver that could influence others.

The study presents an overview of decarbonisation drivers in the literature and would be of benefit to the government and stakeholders towards achieving net zero emissions in the construction industry.

The findings of the study present drivers of carbon reduction and prioritise and categorise them for tailored interventions within the construction sector. Also, it could serve as foundational knowledge for further study in the construction process decarbonisation research area.

This study aims to provide a series of drivers that prompt the blockchain technology (BT) adoption decisions in circular supply chain finance (SCF) and also assesses their degrees of influence and interrelationships, which leads to the construction of a theoretical model depicting the influence mechanism of BT adoption decisions in circular SCF.

This study mainly uses the technology-organization-environment (TOE) framework, which focuses on the aspects based on the nature of innovation, intra-organizational characteristics and extra environmental consideration, to identify the drivers of blockchain adoption in circular SCF context, while the significance and causality of the drivers are explained using interpreting structural models (ISMs) and the decision-making trial and evaluation laboratory (DEMATEL) method.

The findings of this study indicate that government policy and technological comparative advantage are the underlying reasons for BT adoption decisions, management commitment and financial expectations are the critical drivers of BT adoption decisions while other factors are the receivers of the mechanism.

This study provides theoretical references and empirical insights that influence the technology adoption decisions of both BT and circular SCF by practitioners.

The theoretical research contributes significantly to current research and knowledge in both BT and circular SCF fields, especially by extending the existing TOE model by combining relevant enablers from technological, organizational and external environmental aspects with the financial performance objectives of circular SCF services, which refer to the optimization of the financial resources flows and financing efficiency.

The objective of this research is to evaluate and rank the factors influencing omnichannel (OC) logistics, while also investigating the significant impact of big data analytics in improving these drivers of OC logistics.

Using exploratory sequential mixed method design, an in-person interview survey was conducted to identify and stratifies the enablers of OC retailing. These interviews were supplemented with a case study in an apparel firm to prioritise the enablers of OC logistics. Further, a survey was conducted to understand the role of big data analytics in improving drivers of OC logistics as well as the role of Individual capability and organisational capability in big data usage for omnichannel retailing.

Findings represent that information management is the most important driver followed by inventory management and network design for improving OC logistics. Further, significant relationship between big data analytics and drivers of omnichannel logistics has been reported.

This study identifies and classifies the drivers of OC retailing relating to their level of criticality in OC logistics which will assists practitioners to prioritise their tasks for the successful development of OC logistics. The study will also help practitioners to use BDA for developing the drivers of OC.

The study substantiates and adds to the BDA literature by emphasising the positive role of BDA in development of OC driver and highlighting the significant role of drivers of BDA in its usage.