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Performance measurement (PM) of any supply chain is prerequisite for improving its competitiveness and sustainability. This paper develops a framework for supply chain performance measurement (SCPM) for agriculture supply chain (ASC) based on internet of things (IoT). Moreover, this article explains the role of IoT in data collection and communication (SC visibility) based on the supply chain operation reference (SCOR) model.

This research identifies various key performance indicators (KPIs) and also their role in SCPM for improving its sustainability by using SCOR. Further, Shannon entropy is utilized for weighing the basic processes of SCPM and by using weights, fuzzy TOPSIS is applied for ranking of identified KPIs at metrics level 2 (deeper level).

“Flexibility” and “Responsiveness” have been reported as two most important KPIs in IoT based SCPM framework for ASC towards achieving sustainability.

In this research, metrics are explained only at SCOR level 2. But, this research will guide the managers and practitioners of various organizations to set their benchmark for comparing their performance at different levels of business processes. Further, this paper has managerial implications to develop an effective system for PM of IoT based data-driven ASC.

By using IoT based data driven system, this article fills the gap between SCPM by measuring different SC strategies in their performance measurable form of reliable, responsive and asset management etc.

Circular supply chain management (CSCM) is proving to be a strong contributor towards sustainable development. The purpose of this study is to analyse the circular practices in CSCM implementation towards sustainability in the Indian auto sector; these practices are at the initial stage in a developing economy.

In this research work, a framework has been developed to enrich understanding of various CSCM practices for sustainability. To develop a causal framework, a Fuzzy Decision-Making Trial and Evaluation Laboratory (F-DEMATEL) methodology has been adopted.

The results produce 32 practices with cause and effect groups and their importance/priorities. Based on F-DEMATEL, these 32 practices are grouped into cause and effect groups based on R + C and R − C values.

The findings will help managers and decision-makers to gain a deeper understanding of the practices and their nature; the governmental and financial practices are identified as the most critical factors that need more attention. The results will help strategy makers to plan accordingly.

This research has identified and analysed 32 basic practices and their interrelationships to achieve sustainability in CSCM.

Digital financial services (DFS) have substantial prospect to offer a number of reasonable, appropriate and secure banking services to the underprivileged in developing countries through pioneering technologies such as mobile phone based solutions, digital platforms and electronic money models. DFS allow unbanked people to obtain access to financial services through digital technologies. However, DFS face tough challenges of adoption. Realising this, the purpose of this paper is to identify such challenges and develop a framework.

The authors developed a framework of challenges by utilising interpretive structural modelling (ISM) and fuzzy MICMAC approach. The authors explored 18 such unique set of challenges culled from the literature and further gathered data from two sets of expert professionals. In the first phase, the authors gathered data from 29 professionals followed by 18 professionals in the second phase. All were pursuing Executive MBA programme from a metropolitan city in South India. The implementation of ISM and fuzzy MICMAC provided a precise set of driving, linkage and dependent variables that were used to derive a framework.

ISM model is split in eight different levels. The bottom level consists of a key driving challenge V11 (i.e. high cost and low return related problem), whereas the topmost level consists of two highly dependent challenges namely V1 (i.e. risk of using digital services) and V14 (i.e. lack of trust). The prescribed ISM model shows the involvement of “high cost and low return related problem (V11)”, which triggers further challenges of DFS.

None of the existing research has explored key challenges to DFS in detail nor formulated a framework for such challenges. To the best of the authors’ knowledge, this is the first paper on DFS that attempts to collate its challenges and incorporate them in a hierarchical model using ISM and further divide them into four categories of factors using fuzzy MICMAC analysis.

The purpose of this research is to establish a conceptual model to understand the impact of Total Productive Maintenance (TPM) and Industry 4.0 (I4.0) on the transition of a Circular Economy (CE). Also, the paper explores the combined impact of TPM, I4.0 and CE on the sustainability performance (SP) of manufacturing firms.

The conceptual model is proposed using the dynamic capability view (DCV) and empirically validated by partial least squares-structural equation modelling (PLS-SEM) using 304 responses from Indian manufacturing firms.

The results suggest that I4.0 positively impacts TPM, CE and SP, also showing TPM's positive impact on CE and SP. In addition, CE has a positive influence on the SP of manufacturing firms. Furthermore, CE partially mediates the relationship between I4.0 and SP with TPM and SP. The study also identifies TPM, I4.0 and CE as a new bundle of dynamic capabilities to deliver SP in manufacturing firms.

The present research adds to the knowledge and literature on DCV by identifying the importance of CE in the settings of I4.0 and TPM, especially in the context of sustainability. Also, the current study offers a new set of dynamic capabilities and provides some significant future recommendations for researchers and practitioners.

Circularity has acted as an essential phenomenon for small and medium enterprises (SMEs) in emerging economies, pressuring entrepreneurs to its adoption in their businesses. During the adoption and implementation of circularity, entrepreneurs or circular entrepreneurs (to be precise) are facing various challenges to its effective functioning. However, the scholarly literature has offered limited research into this phenomenon. Thus, the purpose of this research is to identify the various barriers and sub-barriers for circular entrepreneurs to adopt circularity in SMEs of emerging economies.

A combined qualitative and quantitative approach was employed to achieve the objectives of the study. In the first stage, through an extensive literature review, a list of barriers was identified and in the second stage, a deductive approach was employed to finalize the barriers. Finally, Best-Worst Method (BWM), a multi-criteria decision-making (MCDM) method, was used to analyse the significant importance of the barriers.

The findings of the study suggested the “financial barrier” as the first-ranked barrier in the adoption of Circular Business Models (CBMs), followed by the “regulatory and operational barrier” as the top second and third barriers. In terms of sub-barriers, “lack of access to funding and capital” has been identified as the top sub-barrier in the adoption of CBM, followed by “excessive regulations and red tape” and “challenges due to ambiguity of the concept”.

To transition from a circular to a linear business approach considerably quicker and smoother, entrepreneurs may utilize the findings of this study as a blueprint for the steps to overcome the barriers in a linear to a circular transition.

This research differentiates from other studies due to solicited input directly from the people who are most familiar with the challenges of making the transition from linear to CBM, i.e. the entrepreneurs themselves.

The objective of this article is to carry out the driving power and dependency analysis of green human resource management (GHRM) indicators of the automotive service sector to identify the most significant ones.

The GHRM indicators were identified through exhaustive literature search and validated through the semi-structured interview with 15 domain experts. The ‘Total Interpretive Structural Modelling (TISM)’ approach was applied for exploring the contextual relationship between the indicators and simultaneously developing their structural hierarchy. The MICMAC analysis was used for categorising the indicators based on their ability to influence the other ones.

In the present study, indicators namely ‘Green organisational culture and adoption of green strategy (C5)’ and ‘Green training and development (C1)’ were found to be the significant ones, whereas ‘Green employee relations and union-management (C10)’ was found to be highly dependent on the rest of the indicators.

The proposed model has been developed in the Indian context and is limited to the automotive sector. However, the same model may apply to other domains of different economies by carrying out slight modifications to the same. Also, the inputs taken from the experts of the case sector could be biased. For the HR professionals, the present study helps to identify the key indicators which need to be considered for enlightening the environmental performance of the service organisation.

This research adds a significant assessment to the current knowledge base by assessing the contextual relationship between the indicators of GHRM as none of the past studies focused on the same by using the TISM method in the Indian service sectors context.

In this paper, the authors emphasize that COVID-19 pandemic is a serious pandemic as it continues to cause deaths and long-term health effects, followed by the most prolonged crisis in the 21st century and has disrupted supply chains globally. This study questions “can technological inputs such as big data analytics help to restore strength and resilience to supply chains post COVID-19 pandemic?”; toward which authors identified risks associated with purchasing and supply chain management by using a hypothetical model to achieve supply chain resilience through big data analytics.

The hypothetical model is tested by using the partial least squares structural equation modeling (PLS-SEM) technique on the primary data collected from the manufacturing industries.

It is found that big data analytics tools can be used to help to restore and to increase resilience to supply chains. Internal risk management capabilities were developed during the COVID-19 pandemic that increased the company's external risk management capabilities.

The findings provide valuable insights in ways to achieve improved competitive advantage and to build internal and external capabilities and competencies for developing more resilient and viable supply chains.

To the best of authors' knowledge, the model is unique and this work advances literature on supply chain resilience.

Coronavirus disease 2019 (COVID-19) has disrupted global supply chains, revealing dreadful gaps and exposing vulnerabilities. Retailers are challenged to tackle risks and organise themselves to fit into the “new normal” scenario. This global outbreak has established a volatile environment for supply chains; it has raised the question of survival in the market, forcing companies to rethink resilient strategies to be adopted for the post-pandemic situation to mitigate the long-term effects of this virus. This study explores the priorities for retail supply chains (RSCs) to align their business operations and strategies for the post-pandemic world.

This study has utilised integrated full consistency model (FUCOM) – best–worst method (BWM) for assessment of RSCs to enhance their business performance irrespective of pandemic disruptions. The FUCOM has been employed to identify the priorities of determinants enhancing business performance, whereas RSC strategies are evaluated using the BWM method.

The current study identifies “Collaboration Efficiency” as the main criterion for accelerating the performance of RSCs in a dynamic social environment. Also, the study concludes that “Order Fulfilment” and “Digital RSCs” are the most appropriate resilient business strategies to mitigate the long-term effects.

Supply-demand balancing is a challenging task at the moment, but highly significant for the future. The pandemic disruptions have placed intense pressure on retailers to deliver products as per consumers' changing behaviours towards the purchase of essentials and other products. Hence, “Order Fulfilment” and “Digital RSCs” should be adopted for meeting customer requirements and to ensure sustainability in the post-pandemic business world.

This work sets out a comprehensive framework which will be helpful for accelerating RSCs performance against pandemic disruption by adopting resilient strategies to mitigate the long-term effects.

Technology forecasting (TF) and assessment (TA), all in all, apply to any intentional and deliberate endeavours to forecast and view the potential heading, rate, attributes and impacts of technological change, especially for development, advancement, selection and utilisation of resources, which ultimately helps in the benchmarking. A vast variety of methods are available for TF and TA. Till now, practically, no exertion has been made to choose proper, satisfactory innovation methods or technology. The paper aims to discuss this issue.

In this paper, there is an endeavour to summarise the vast field of TF and TA, through its evolution, functions, applications and techniques. This paper provides the in-depth review of the utilisation of TF and TA methodologies and its improvement, which helps the users in selecting the appropriate method of TF and TA for a specific situation.

This study concludes that the quest for a single strategy for doing forecast and assessment is a misconception. This neglects to perceive that forecast and assessment oblige a suitable blend of strategies and methods drawn from a variety of fields. Researchers and practitioners must be innovative, imperative and specialised in choosing TF and TA methodologies, and cannot be programmed.

The technology seems to be the most significant driver of the present day global developments. Some technologies have far-reaching implications, and the authors need to understand these issues regarding its’ forecasting and its assessment.

The decision of proper worthy procedure amid a circumstance may have an impact on the exactness and reliability of the forecast and assessment. Significant observations regarding learning, action/s, actor/s and expected outcomes are discussed.

The study aims to examine the influence of Sustainable Human Resource Management (SHRM) practices and Industry 4.0 Technologies (I4Te) adoption on the Employability Skills (ES) of the employees. The study has undertaken four major SHRM practices – Training (TR), Flexibility (FL), Employee Participation (EP) and Employee Empowerment (EE) to measure its impact on the ES along with I4Te.

A survey approach method was designed on the identified constructs from existing literature based on SHRM, I4Te and ES. The survey resulted into 198 valid responses. The study used confirmatory factor analysis (CFA) and structural equation modelling (SEM) using SPSS 25.0 and AMOS 25.0 for constructs validation and hypothesis testing.

The current study reveals that all the four SHRM practices (TR, FL, EP and EE) along with I4Te directly influence ES in the organisation. The I4Te along with the SHRM practices may bring enhancement in the skills and competencies of the employees that is the requirement of future organisations.

Considering the results, the SHRM practices aligned with I4Te may directly influence the employee's ES including core skills, IT skills and personal attributes. The SHRM practices in the organisation will enhance the opportunities for the employees and bring long-term association with the employees.

For the development of the economy and the individual, the SHRM practices need to conduct themselves in more socially responsible ways along with the I4Te to enhance the ES of the employees. The individual development will bring sustainable behavioural changes in the employees.

There has been no research conducted on exploring SHRM, I4Te and ES together. This is the pioneer in the HRM fields that explores the interrelationships and influence amongst the five constructs undertaken in the study.