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Today’s marketplace has witnessed intense competitive pressures and high levels of uncertainty and disruption. Therefore, supply chains require agility to obtain a sustainable competitive advantage and cope with uncertainties as well as disruptions. Although a wide range of studies exists on supply chain agility (SCA) from the perspective of antecedents or consequences, there is little research on the investigation of enablers of SCA and their relations among them. Furthermore, the literature has investigated proactive and reactive enablers for enhancing SCA, but most studies have not sufficiently framed their analysis of both aspects synchronically. This paper aims to find out the interrelationships among the proactive and reactive enablers for enhancing SCA.

An extensive literature review has been conducted to identify SCA enablers and a Delphi study has been performed to elucidate SCA enablers in the manufacturing industry in Turkey. Interpretive structural modeling (ISM) has been used to identify the contextual relationship among the SCA enablers, and the model has been validated based on Matriced Impact Croises Multiplication Appliquee a un Classement (MICMAC) analysis.

On theoretical and practical levels, the proposed ISM model in this study can help organizations analyze and interpret interrelationships among enablers of SCA. For managers, it can provide better insights and understanding of the facilitators of SCA to enhance the effectiveness of the supply chain and cope with uncertainties and turbulence. According to results, enhancing “supply and demand side competency”, “delivery speed” and “strategic sourcing” are the most significant enablers of SCA.

The study extends the existing literature related to the enablers of SCA by modeling the proactive and reactive enablers of SCA based on the Al Humdan et al. (2020) classification. Arranging the enablers of SCA in a hierarchy and classifying the enablers into different levels with the help of the ISM-MICMAC approach is an exclusive effort to achieve successful management of the supply chain.

Business environments and global transportation system have become more complex than ever due to complexity drivers of industries which create uncertainty and unpredictability to organizations. Like other industries, the maritime business faces different and difficult problems which threaten organizational survival. The ability to cope with those uncertainties, threats and problems shows the resilience ability of organizations that help to survive and prosper. The organizational resilience concept arises as a requirement to deal with problems and uncertainties of business environments which are swiftly changing. This study aims to suggest an organizational framework to show how maritime business organizations as the sea leg of global transportation system can develop resilient organizations via complex adaptive systems (CAS) approach if adequate design features of CAS could be defined and included in organizational properties.

A total of 15 CAS features were identified as the enablers of organizational resilience throughout the literature. An interpretive structural modeling (ISM) approach has been conducted to determine the mutual relation between the CAS features which constitute an organizational framework. These CAS features have been categorized by conducting MICMAC analysis.

This study proposes a framework that identifies CAS features as the enabler of resilient maritime business organizations. The CAS approach offers new managerial toolkit to realize current organizational situations and allows managers to understand that it is difficult to control their system in this dynamic environment where special management practices are required especially in volatile times rather than ordinary times. Also, organizations could not compete as a sole organization but as a web/system of organizations. CAS is more resilient than other systems because resilience is the emergent occurrence of the system formed from nonlinear, dynamic interactions with self-organized agents.

The research has some limitations, like organizational resilience studies are in the infant stage and further research into this area should be extended. This study uses the CAS approach to develop organizational resilience. Further studies could use different lenses and contemporary subjects in management field which should also be useful while developing resilience in organizations. This study uses ISM and MICMAC analysis where further studies could use quantitative design and methods like formal concept analysis or the decision making trial and evaluation laboratory to determine the relational weighs of CAS features while developing resilient organizations. Future studies may also focus on different maritime stakeholders like IMO or ILO, maritime agencies, freight forwarders or insurance underwriters regarding developing and enhancing resilience of the maritime system.

World trade and transportation systems are getting more uncertain and lean on complex relations where maritime transportation is a “vital backbone” of such operations. But becoming more complex structures leads to vulnerable systems and organizations. Most risk management applications are based on predicting the known risks where many of them are not enough to fight with unknowns. Coping with today's problems are difficult for organizations in any industry. But for maritime business stakeholders who work in such a global web of relations, it is much more challenging. So, stakeholders of the system like forwarders, ports or ship chandlers may easily apply those features to develop resilient organizations too. Legal authorities of the system and rule-makers like local Chambers of Shipping, IMO or Classification societies can benefit from this framework and provide supportive settings to develop system-wide resilient organizations.

By understanding environmental uncertainty and complexity better than others, organizations become resilient and cope with significant difficulties which make them more competitive as a substantial strategic advantage. Resilient management offers to break down points at the system and shows them ways to restore quickly while transporting goods while traditional risk assessments are not enough.

The originality of the study lies in two folds; first of all the key and most used features of CAS is linked to developing resilient maritime organizations and by maritime expert opinions, this study tries to determine which of these CAS features are the most effective to trigger other features to develop organizational resilience in the maritime business. And secondly, the concept of organizational resilience and the CAS approach are not analyzed in depth in the context of maritime business.

This study aims to propose an integrated framework for analyzing the effect of lean and agile innovation on the lean and agile supply chains.

The literature was reviewed and the dimensions of lean and agile supply chain/innovation were extracted. The statistical population included the managers and experts of pharmaceutical companies in Isfahan province. Eight pharmaceutical companies were selected. A researcher-made questionnaire was used to investigate the research variables. The face and content validity of the questionnaire and the data reliability were confirmed. After data collection, the studied companies were positioned in a two-by-two matrix and the associated data of two cells of the matrix, i.e. high lean supply chain/innovation and high agile supply chain/innovation were used for further statistical effect analysis using Smart-PLS.

The research results indicated that with the improvement of lean innovation in pharmaceutical companies, the lean supply chain improved by 97.9%; and with the improvement of agile innovation, the agile supply chain improved by 97.1%.

Considering lean innovation, pharmaceutical companies should deal with the process of conceptualizing innovation, and regarding agility strategy, their focus should be more on generating ideas to improve their agile supply chain. This study was performed during the COVID-19 pandemic and offers appropriate innovation strategies to improve the supply chain of pharmaceutical companies.

The literature review implies that no research has been conducted on the selected and classified variables of this study. Also, using the positioning matrix before statistical analysis distinguishes this paper from similar studies.

The use of technology in 4th industrial revolution is at its peak. Industries are trying to reduce the consumption of resources by effectively utilizing information and technology to connect different functioning agents of the manufacturing industry. Without digitization “Industry 4.0” will be a virtual reality. The present survey-based study explores the factual status of digital manufacturing in the Northern India.

After an extensive literature review, a questionnaire was designed to gather different viewpoints of Indian industrial practitioners. The first half contains questions related to north Indian demographic factors which may affect digitalization of India. The latter half includes the queries concerned with various operational factors (or drivers) driving the digital revolution without ignoring Indian constraints.

The focus of this survey was to understand the current level of digital revolution under the ongoing push by the Indian government focused upon digital movement. The analysis included non-parametric testing of the various demographic and functional factors impacting the digital echoes, specifically in Northern India. Findings such as technological upgradations were independent of type of industry, the turnover or the location. About 10 key operational factors were thoughtfully grouped into three major categories—internal Research and Development (R&D), the capability of the supply chain and the capacity to adapt to the market. These factors were then examined to understand how they contribute to digital manufacturing, utilizing an appropriate ordinal logistic regression. The resulting predictive analysis provides seldom-seen insights and valuable suggestions for the most effective deployment of digitalization in Indian industries.

The country-specific Industry 4.0 literature is quite limited. The survey mainly focuses on the National Capital Region. The number of demographic and functional factors can further be incorporated. Moreover, an addition of factors related to ecology, environment and society can make the study more insightful.

The present work provides valuable insights about the current status of digitization and expects to facilitate public or private policymakers to implement digital technologies in India with less efforts and the least resistance. It empowers India towards Industry 4.0 based tools and techniques and creates new socio-economic dimensions for the sustainable development.

The quantitative nature of the study and its statistical predictions (data-based) are novel. The clubbing of similar success factors to avoid inter-collinearity and complexity is seldom seen. The predictive analytics provided in this study is quite elusive as it provides directions with logic. It will help the Indian Government and industrial strategists to plan and perform their interventions accordingly.

Businesses are increasingly vulnerable and exposed to physical climate change risks, which can cascade through local, national and international supply chains. Currently, few methodologies can capture how physical risks impact businesses via the supply chains, yet outside the business literature, methodologies such as sustainability assessments can assess cascading impacts.

Adopting a scoping review framework by Arksey and O'Malley (2005) and the PRISMA extension for scoping reviews (PRISMA-ScR), this paper reviews 27 articles that assess climate risk in supply chains.

The literature on supply chain risks of climate change using quantitative techniques is limited. Our review confirms that no research adopts sustainability assessment methods to assess climate risk at a business-level.

Alongside the need to quantify physical risks to businesses is the growing awareness that climate change impacts traverse global supply chains. We review the state of the literature on methodological approaches and identify the opportunities for researchers to use sustainability assessment methods to assess climate risk in the supply chains of an individual business.

Identifying and prioritizing supply chain risk is significant from any product’s quality and reliability perspective. Under an input-process-output workflow, conventional risk prioritization uses a risk priority number (RPN) aligned to the risk analysis. Imprecise information coupled with a lack of dealing with hesitancy margins enlarges the scope, leading to improper assessment of risks. This significantly affects monitoring quality and performance. Against the backdrop, a methodology that identifies and prioritizes the operational supply chain risk factors signifies better risk assessment.

The study proposes a multi-criteria model for risk prioritization involving multiple decision-makers (DMs). The methodology offers a robust, hybrid system based on the Intuitionistic Fuzzy (IF) Set merged with the “Technique for Order Performance by Similarity to Ideal Solution.” The nature of the model is robust. The same is shown by applying fuzzy concepts under multi-criteria decision-making (MCDM) to prioritize the identified business risks for better assessment.

The proposed IF Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) for risk prioritization model can improve the decisions within organizations that make up the chains, thus guaranteeing a “better quality in risk management.” Establishing an efficient representation of uncertain information related to traditional failure mode and effects analysis (FMEA) treatment involving multiple DMs means identifying potential risks in advance and providing better supply chain control.

In a company’s supply chain, blockchain allows data storage and transparent transmission of flows with traceability, privacy, security and transparency (Roy et al., 2022). They asserted that blockchain technology has great potential for traceability. Since risk assessment in supply chain operations can be treated as a traceability problem, further research is needed to use blockchain technologies. Lastly, issues like risk will be better assessed if predicted well; further research demands the suitability of applying predictive analysis on risk.

The study proposes a hybrid framework based on the generic risk assessment and MCDM methodologies under a fuzzy environment system. By this, the authors try to address the supply chain risk assessment and mitigation framework better than the conventional one. To the best of their knowledge, no study is found in existing literature attempting to explore the efficacy of the proposed hybrid approach over the traditional RPN system in prime sectors like steel (with production planning data). The validation experiment indicates the effectiveness of the results obtained from the proposed IF TOPSIS Approach to Risk Prioritization methodology is more practical and resembles the actual scenario compared to those obtained using the traditional RPN system (Kim et al., 2018; Kumar et al., 2018).

This study provides mathematical models to simulate the supply chain risk assessment, thus helping the manufacturer rank the risk level. In the end, the authors apply this model in a big-sized organization to validate its accuracy. The authors validate the proposed approach to an integrated steel plant impacting the production planning process. The model’s outcome substantially adds value to the current risk assessment and prioritization, significantly affecting better risk management quality.

Environmental impact and changes are becoming essential in textile and yarn industries, where reliable measurement of parameters related to processing harmful substances needs to be examined. Such findings can be cumulated using smart assessment like life cycle analysis. The ecological impact category, supply chain, and climate-changing factors were considered for the necessary assessment.

This paper applies the Life Cycle Assessment technique in the textile and yarn industry to estimate critical environmental potentials. The critical input for the fabric and yarn industry was put in the GaBi software model to estimate various environmental potentials.

Global warming potential, electricity, and raw cotton consumption in the fabric and yarn industry were critical concerns where attention should be focused on minimizing environmental potentials from cradle to gate assessment.

This qualitative study is made via the industry case-wise inputs and outputs, which can vary with demographic conditions. Some machine and human constraints have not been implemented in modelling life cycle model for smart simulation. Smart simulation helps in linking different parameters and simulates their combined effects on the product life cycle.

This modelling approach will help access pollution constituents in different supply chain production processes and optimize them simultaneously.

The raw data used in this analysis are collected from an Indian small scale textile industry. In the textile fabrication industry, earlier assessments were carried out in cotton generation, impact of PET, cradle to grave assessment of textile products and garment processing only. In this research the smart model is drawn to consider each input parameter of yarn and textile fabric to determine the criticality of each input in this assessment. This article mainly talks about life cycle and circular supply assessment applied to first time for both cotton to yarn processing and yarn to fabric industry for necessary estimation of environment potentials.

This research is about embedding service-based supply chain management (SCM) concepts in the education sector. Due to Canada's competitive education sector, the authors focus on Canadian universities.

The authors develop a framework for evaluating and forecasting university performance using data envelopment analysis (DEA) and artificial neural networks (ANNs) to assist education policymakers. The application of the proposed framework is illustrated based on information from 16 Canadian universities and by investigating their teaching and research performance.

The major findings are (1) applying the service SCM concept to develop a performance evaluation and prediction framework, (2) demonstrating the application of DEA-ANN for computing and predicting the efficiency of service SCM in Canadian universities, and (3) generating insights to enable universities to improve their research and teaching performances considering critical inputs and outputs.

This paper presents a new framework for universities' performance assessment and performance prediction. DEA and ANN are integrated to aid decision-makers in evaluating the performances of universities.

The findings suggest that higher education policymakers should monitor attrition rates at graduate and undergraduate levels and provide financial support to facilitate research and concentrate on Ph.D. programs. Additionally, the sensitivity analysis indicates that selecting inputs and outputs is critical in determining university rankings.

This research proposes a new integrated DEA and ANN framework to assess and forecast future teaching and research efficiencies applying the service supply chain concept. The findings offer policymakers insights such as paying close attention to the attrition rates of undergraduate and postgraduate programs. In addition, prioritizing internal research support and concentrating on Ph.D. programs is recommended.

Visibility management is essential to sustainable supply chains (SSCs), allowing the ability to see the chain end-to-end, with opportunities to derive benefits, including competitive advantage. Central to visibility management is visibility assessment and identification of areas for improvement. This paper aims to propose a method of assessing visibility in SSCs and the generation of proposals for improvement.

A hierarchically structured assessment template is developed that comprises of dimensions, factors and attributes of visibility in SSCs. The template permits the use of linguistic variables. A fuzzy logic approach is adopted to calculate visibility levels and generate improvement areas based on linguistic data captured through the template. An industry-based case study is used to illustrate the process.

This study reveals that visibility can be measured straightforwardly using the method developed in this paper. It is found that automation and contextual factors can significantly impact visibility levels, so also is sustainability awareness and practices adopted.

This paper describes a visibility assessment model that incorporates linguistic variables, fuzzy logic and the use of an adaptable visibility assessment template. The assessment model can identify potential inhibitors of visibility for SSC under study.

Halal integrity assurance is the primary objective of Halal supply chain management. Several halal-related risks are present that have the potential to breach halal integrity. Therefore, this study aims to develop the framework for the assessment of halal-related risk from a supply chain perspective.

Risk related to halal is identified through the combined approach of the systematic literature review and experts’ input. Further, these risks are assessed using the integrated approach of intuitionistic fuzzy number (IFN) and D-number based on their severity score. This integrated approach can handle fuzziness, inconsistency and incomplete information that are present in the expert’s input.

Eighteen significant risks related to halal are identified and grouped into four categories. These risks are further prioritised based on their severity score and classified as “high priority risk” or “low priority risks”. The findings of the study suggests that raw material status, processing methods, the wholesomeness of raw materials and common facilities for halal and non-halal products are more severe risks.

This study only focusses on halal-related risks and does not capture the other types of risks occurring in the supply chain. Risks related to halal supply chain management are not considered in this study. Prioritisation of the risks is based on the expert’s input which can be biased to the experts' background.

The proposed risk assessment framework is beneficial for risk managers to assess the halal related risks and develop their mitigation strategies accordingly. Furthermore, the prioritisation of the risks also assists managers in the optimal utilisation of resources to mitigate high-priority risks.

This study provides significant risks related to halal integrity, therefore helping in a better understanding of the halal supply chain. To the best of the authors' knowledge, this is the first comprehensive study for developing a risk assessment model for the halal supply chain.