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Agility is the ability of an organization to adjust its supply chain tactics and operations to respond quickly against altering business environments such as fluctuating demand pattern, supply chain disruption and global competition. An agile organization must possess a promising capability of swiftly responding to dynamic conditions while being cost-effective without compromising the efficiency. Such high-performance adaptability necessitates the role of supply chain managers to maximize the agility of the supply chain through the efficient use of input resources. Therefore, the purpose of this study to reveal a new decision support tool that would allow the key decision-makers to maximize the agility of the supply chain while deploying the input resources more effectively.

In present study, an integrated approach of popular analytic hierarchy process (AHP) and goal programming (GP) has been adopted as a potential solution methodology. AHP has been implemented to allocate the local and global weights to decision variables, whereas GP incorporates the AHP weights into the desired model.

It was found that the proposed decision support tool restricts the value of the decision variables for maximizing the agility and optimizing the usage of input resources. The results obtained from the model validate the objective of achieving targeted agility level within the available resource limitations.

The decision support tool developed in the proposed study offers a systematic and effectively simple approach to supply chain managers with a goal of identifying the degree of focus under each decision variable in the respective manufacturing organizations.

A novel decision support tool has been developed known as an agility control system), which helps the decision-maker to achieve the required agility in the supply chain by controlling the decision variables.

This purpose of the study is to investigate enablers of building agility capabilities in healthcare organisations in developing countries. The key research questions are: (1) What are the key enablers for building healthcare agility? (2) Is there an interdependence among the enablers of healthcare agility? (3) What is the driving and dependence power of the enabling factors of healthcare agility?

The enablers for building capabilities of organisational agility were identified from the extant literature. Perceptual responses for pair-wise comparison of identified enablers were collected from 17 clinical and non-clinical professionals working in Indian hospitals through online interviews. Participants were selected from India which supposedly represents the socioeconomic contexts and healthcare systems in developing economies. Next, the data was analysed using multicriteria decision-making (MCDM) techniques to develop a structural framework depicting the enablers and their interdependence.

The TISM framework showed that the two most influential enablers of healthcare agility in developing countries are policy and regulatory support and strategic commitment and resource availability. The results were based on the analysis of four enablers identified from the literature. The results of MICMAC analysis revealed the driving and dependence power of each enabler and classified the enablers into driving, autonomous, dependence and linkage groups.

The study will help stakeholders and academics in the healthcare domain in devising effective strategies for building agility within healthcare systems and processes.

The study contributes to the service operations literature on building agile systems for dynamic and complex service environments.

The purpose of this paper is to report a case study carried out to assess the agility and identify obstacles to agility in a supply chain. A human perception-based framework is used for the calculation of agility. The case study was carried out in a North India-based manufacturing organization.

In this study, the concept of a multi-grade fuzzy logic approach is used. Using this concept, the overall agility index has been determined. The fuzzy logic approach has been used to overcome the disadvantages such as impreciseness and vagueness using a scoring method.

From the analysis, it is observed that the organization on which the study was performed is “very agile.” After evaluating the agility level, the fuzzy performance importance index is calculated, which helps to identify the barriers of agility in the supply chain. These barriers help decision makers to implement appropriate improvement measures for improving agility level. Overall, 11 barriers were identified in the study.

Managers of the contemporary manufacturing organization have to measure the agility level of the organization and identify barriers to agility in order to survive in a competitive environment. The obstacles identified in this study are used to improve the performance of the organization. The enterprise should improve on the weak areas in order to achieve the highest agility level.

The agile supply chain (ASC) enablers proposed by previous researchers are not sufficient for the evaluation of agility of a supply chain. There are a few more ASC enablers such as customer satisfaction, flexibility and adaptability that also play a vital role in making a supply chain agile. Adding these three ASC enablers, a total of seven ASC enablers along with their attributes are being considered for the development of a conceptual model.

The purpose of this paper is to explore and encapsulate the enablers that can facilitate agility in faculty members of engineering institutions. The paper also aims to conduct a prelim qualitative validation of the enablers and analyze the interplay between them using the total interpretive structural modeling (TISM) approach.

The study adopted the TISM approach to comprehend the interactions and transitivity between the enablers. Cross-impact multiplication matrix (MICMAC) analysis was applied to rank the enablers and classify them on the basis of the driving and dependence power into dependent, autonomous, independent and linkage enablers.

Extensive literature review and expert opinion helped identify 16 enablers that can promote workforce agility. The results indicate “management support” as the most crucial enabler. Rewards and recognition and employee empowerment were among the other enablers that have a high driving force. New capabilities, learning and innovation and the expanding role of faculty members were found to have high dependence power, which makes the enablers dependent on other enablers for activation.

The results of this study would assist the management of engineering colleges and universities to design, adopt and implement policies and practices that would facilitate agility in faculty members. Faculty members shoulder the responsibility of molding the future generation, and hence, it is important that they are competent enough to impart quality education. The policymakers should focus on policies and practices that leverage human resource potential and support an innovative climate that nurtures entrepreneurial activities in engineering institutions.

So far research on workforce agility has predominantly focused on the manufacturing sector. Despite the workforce (refers to faculty members here) being crucial in contributing to the progress of universities and colleges, very little work is done on how faculty members can be made agile. Application of the TISM method in identifying the variables that can facilitate faculty members' agility in engineering institutions in India is a new and original contribution to the literature on workforce agility.

This paper aims to analyze the agile manufacturing practices in small and medium enterprises (SMEs) within the auto-ancillary sector spread across eastern India. Using statistical method, a number of crucial insights have been captured and discussed in detail.

A structural equation model (SEM) encapsulating pertinent agile manufacturing attributes and enablers as the focal construct is conceptualized and validated in this research. The SEM model is evolved in a manner that agile attributes and agile enablers are modeled as latent dependent and manifest variable, respectively.

A number of key hypothesis entailing interactions of key agility enablers, i.e. manufacturing responsiveness agility, manufacturing strategy agility, workforce agility, technology agility, manufacturing management agility, etc. are conceptualized and validated.

The authors specifically focus on evolving agile manufacturing framework (characterized by agility enablers and attributes) that lies at the intersection of SMEs, automotive sector and an emerging economy.

The purpose of this study is to critically examine the scholarly articles associated with the diverse aspects of supply chain agility (SCA). The review highlights research insights, existing gaps and future research directions that can help academicians and practitioners gain a comprehensive understanding of SCA.

The present study has adopted author co-citation analysis as the research methodology, with a view to thoroughly investigating the good-quality articles related to SCA that have been published over a period of 22 years (1999-2020). In this study, 126 research papers on SCA – featuring diverse aspects of agility – from various reputed journals have been examined, analysed and assimilated.

The salient findings of this research are, namely, agility is different from other similar concepts, such as flexibility, leanness, adaptability and resilience; of the 13 dimensions of agility discussed in the literature, the prominent ones are quickness, responsiveness, competency and flexibility; literature related to SCA can be categorised as related to modelling the enablers, agility assessment, agility implementation, leagility and agility maximisation. This research proposes a more practical definition and framework for SCA. The probable areas for future research are, namely, impediments to agility, effective approaches to agility assessment, cost-benefit trade-offs to be considered whilst implementing agility, empirical research to validate the framework and SCA in the domain of healthcare and disaster relief supply chains.

This paper provides substantial insights to practitioners who primarily focus on measuring and implementing agility in the supply chain. The findings of this study will help the supply chain manager gain a better idea about how to become competitive in today’s dynamic and turbulent business environment.

The originality of this study is in: comprehensively identifying the various issues related to SCA, such as related concepts, definitions, dimensions and different categories of studies covered in literature, proposing a new definition and framework for SCA and identifying potential areas for future research, to provide deeper insights into the subject and highlight areas for future research.

This study aims to identify the factors influencing agile readiness in start-ups. Start-ups are being confronted with increased competition, customer demands, technological innovations and changes in the market environment. Adopting agile readiness for sustainable operations is a profitable and dependable way to improve the competition and reduce the number of failures of start-ups. The start-ups may investigate “how” after understanding the “whys.” The answers to these questions will be crucial to develop a strategy and a plan for luring clients, users, investors and partners. Therefore, this study will help in answering these crucial questions by using Total Interpretive Structural Modeling (TISM), whose main aim is to answer the key question of “what,” “how” and “why.” Using the “Total Interpretive Structural Modeling (TISM)” technique, this research tries to “describe,” “analyze” and “categorize” the agile readiness for sustainable operations enablers in start-ups.

Expert feedback and literature reviews from various start-ups led to the discovery of 10 enablers. In this study, the TISM technique was used to examine the inter-relationships between the enablers. The agile readiness for sustainable operations enablers was ranked and classified using the “Multiplication Applied to Classification (MICMAC)” technique. They were divided into four different categories: “autonomous,” “independent,” “linkage” and “dependent enablers.”

The results show that executive-level aid is the key agile readiness factor for sustainable operations. The next priority has been capability, experienced and skilled employees, market knowledge and environment agility. Leadership and clear vision have been given further priority. The next important is flexibility. The last and the least priority is given to receptive and strategic agility. This directional flow assists management in attaining adaptable sustainability, leading to continued growth in this dynamic environment.

The study focuses primarily on the agile readiness for sustainable operations of start-ups. This study offers a recommended list of crucial elements for start-ups, which may aid in creating guidelines for implementing agility for sustainable operations. This study provides academics with a TISM model that illustrates how start-ups can be ready to implement agility for sustainable operations. Future researchers could add more agility readiness variables to this study and validate this model across different start-ups.

Before implementing agile readiness for sustainable operations in start-ups, this study will aid managers and practitioners in the start-up business in understanding the relationships of enablers and identifying important readiness enablers.

The current study analyzes the agile readiness for sustainable operations in Start-ups. To the best of the authors’ knowledge, it is the first endeavor to use the “TISM approach” to examine the interrelationships across agile readiness for sustainable operations characteristics in start-ups.

The purpose of this study is two-fold. First, to identify and encapsulate the enablers that can facilitate technology integration in higher education and second, to understand and analyze the interplay between technology agility enablers.

The study used the Total Interpretive Structural Modeling (TISM) approach to construct a theoretical model of the technology agility enablers in higher education and MICMAC analysis for ranking and segregating the enablers based on their dependence power into four categories: Autonomous, Dependent, Linkage and Independent.

The study helped identify eight technology agility enablers, with the Covid-19 pandemic as the most significant enabler. The Covid-19 pandemic has catalyzed the diffusion of technology across the education sector in India, including tertiary higher education. The study revealed government initiatives and institutional commitment as other enablers that can promote technology agility in higher education.

The results of this study would assist the policymakers and management of universities and colleges in understanding the important enablers that can facilitate technology integration in higher education.

Research in the past on technology adoption in higher education has looked into each enabler in isolation. This research provides a comprehensive view of the enablers and has attempted to establish a multidirectional interplay between the enablers.

The purpose of this paper is to identify the key supply chain variables, on which the practitioner should focus, to make supply chains of manufacturing enterprises more agile. Further, these variables are structured to determine their interactive behavior.

An interpretive structural modeling (ISM)‐based approach has been employed to model the agility variables of supply chains. These variables have been categorized into five levels based on their driving power and dependence.

The paper identifies various enablers used by researchers and practitioners for flexibility, integration and responsiveness to customers needs. ISM is used to establish mutual relationships among these enablers and to prepare a hierarchy‐based model.

The index of enablers, based on driving power and dependency provides useful insights to supply chain managers in identifying strategic variables having high driving power and effective use of these can help in achieving the corporate goals.

By presenting enablers in the form of hierarchy using ISM and ranking them into various driving power and dependent categories, this paper is an attempt to develop insights related to agile supply chains in the Indian context.

The purpose of this paper is to determine if companies in the modular and offsite construction (MOC) industry are agile or not and its level of application for agility principles, which allows for quick responses to the increasingly dynamic nature of industry environments.

This paper proposes an agility assessment framework for MOC that uses 48 assessment attributes organized into four categories: metrics, drivers, enablers and capabilities. A questionnaire approach was used to disseminate the framework globally in 19 countries and synthesize its relevance to the MOC industry. The questionnaire had 55 complete responses, majority of respondents work in managerial positions for MOC manufacturing facilities and onsite general contractors.

It was found that the lowest metric score for adapting to change was for cost since controlling cost would be difficult for any changes required after the design freeze stage. The top agility driver was found to be the need to respond to the wide variety of customer expectations, while the lowest driver was the existence of competing priorities. The top agility enabler was vendor partnership, which can be related to current postpandemic supply chain disruptions. Regarding technological capabilities, Europe and the USA acquired better scores compared to Asia, Latin America and Africa.

This study contributes to the MOC body of knowledge by creating an agility assessment tool for MOC firms to analyze their agile approach and environment, identifying the preliminary importance of agility assessment attributes and determining significant agile differences between the main MOC industry groups.