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The already-strained vaccine supply chain (VSC) of the expanded program for immunization (EPI) require a more robust and structured distribution network for pandemic/outbreak vaccination due to huge volume demand and time constraint. In this paper, a lean-agile-green (LAG) practices approach is proposed to improve the operational, economic and environmental efficiency of the VSC.

A fuzzy decision framework of importance performance analysis (IPA)–analytical hierarchy process (AHP)–technique for order for preference by similarity in ideal solution (TOPSIS) has been presented in this paper to prioritize the LAG practices on the basis of the influence on performance indicators. Sensitivity analysis is carried out to check the robustness of the presented model.

The derived result indicates that sustainable packaging, coordination among supply chain stakeholders and cold chain technology improvement are among the top practices affecting most of the performance parameters of VSC. The sensitivity analysis reveals that the priority of practices is highly dependent on the weightage of performance indicators.

This study's finding will help policymakers reframe strategies for sustainable VSC (SVSC) by including new management practices that can handle regular immunization programs as well as emergency mass vaccination.

To the best of the authors' knowledge, this is the first study that proposes the LAG framework for SVSC. The IPA–Fuzzy AHP (FAHP)–Fuzyy TOPSIS (FTOPSIS) is also a novel combination in decision-making.

Each individual needs to be vaccinated to control the spread of the COVID-19 pandemic in the shortest possible time. However, the vaccine distribution with an already strained supply chain in low- and middle-income countries (LMICs) will not be effective enough to vaccinate all the population in stipulated time. The purpose of this paper is to show that there is a need to revolutionize the vaccine supply chain (VSC) by overcoming the challenges of sustainable vaccine distribution.

An integrated lean, agile and green (LAG) framework is proposed to overcome the challenges of the sustainable vaccine supply chain (SVSC). A hybrid best worst method (BWM)–Measurement of Alternatives and Ranking According to COmpromise Solution (MARCOS) methodology is designed to analyze the challenges and solutions.

The analysis shows that vaccine wastage is the most critical challenge for SVSC, and the coordination among stakeholders is the most significant solution followed by effective management support.

The result of the analysis can help the health care organizations (HCOs) to manage the VSC. The effective vaccination in stipulated time will help control the further spread of the virus, which will result in the normalcy of business and availability of livelihood for millions of people.

To the best of the author's knowledge, this is the first study to explore sustainability in VSC by considering the environmental and social impact of vaccination. The LAG-based framework is also a new approach in VSC to find the solution for existing challenges.

Recently, in turbulent and highly competitive marketplace, organizational sustainability in the long run necessitates the adaptation of appropriate supply chain (SC) strategies. Hence, traditional SC philosophies are being restructured nowadays to fulfill different business goals. Articulation of lean, agile, green and resilient SC strategies could amply be found in the literature; however, integration of those in various modes may definitely improve overall SC’s performance. Past researchers have focused on the integration of lean, agile and green paradigms together to ensure an efficient SC construct. But the integration of green and resilient paradigm has been rarely reported in the literature. To deal with the unexpected situations/disturbances in the SC management along with embedded environmental consciousness, the purpose of this paper is to integrate the resilient SC and green SC philosophies; thereof to evaluate of an overall SC “g-resilient”/“ecosilient” index for a case automotive company.

A consolidated list consisting of supply chain practices (combining green and resilient performance indices) have been articulated in this study. A decision-making group has been assumed; where, the role of the decision makers is to provide individuals’ judgment (subjective opinion) toward determining the weight and the rating (performance extent) of various performance indices. The overall g-resilient SC performance has been determined by computing a unique ecosilient (g-resilient) index. The concepts of fuzzy performance importance index along with Degree of Similarity (DOS) adapted from fuzzy set theory (FST) have been applied to rank various performance indicators. In addition to that, the interrelationships amongst various g-resilient indices (performance indicators) have also been established through interpretive structural modeling.

By exploring the concept of fuzzy DOS, outlined in the trapezoidal fuzzy numbers set theory, various SC performance indicators have been classified into three distinct performance categories/levels (namely regretful, tolerable, and satisfactory). Such categorization has been found helpful in order to determine ill (poor) performing SC areas, which need future improvement toward boosting up the overall g-resilient index of the company’s SC.

The study bears significant managerial implications. The decision support framework suggested in this paper is found capable enough to determine a unique index known as “ecosilient (g-resilient) index” toward exploring “greenness” as well as “resiliency” for the case automotive company. Application potential of the proposed ecosilient (g-resilient) index evaluation system has been explored in this reporting. The recommended framework enables the managers to cope up with unexpected disruptions and found helpful in order to reduce the environmental impacts.

Today, proficient practices are required to stimulate along various boundaries of the supply chain (SC) to exploit manufacturing resources economically, effectually and gracefully for retaining operational excellence. Accordingly, varieties of paramount practices, i.e. Lean, Agile, Resilient and Green practices, are integrated in present study with the objective to develop a Decision Support Framework (DSF) to select robust supplier under the extent of Lean-Agile-Resilient-Green (LARG) practices for a manufacturing firm. The framework is developed and validated in the Indian automotive sector, where the primary data is collected based on perceptions of the respondents working in an automotive company.

LARG metrics can ponder ecological balance, customer satisfaction, associations, effectiveness and sustainability and thus, the study consolidated LARG practices in one umbrella to develop a DSF. The analytical approach under DSF is developed by the integration AHP, DEMATEL, ANP, Extended MOORA and SAW techniques in present study to evaluate a robust supplier under the aegis of LARG practices in SC. DSF is developed by scrutinizing and categorizing LARG characteristics, where the selected LARG characteristics are handled by fuzzy sets theory to deal with the impreciseness and uncertainty in decision making.

The study has identified 63 measures (15 for Lean, 15 for Agile, 14 for resilient and 19 for Green) to support the robust supplier selection process for manufacturing firms. The findings of study explicate “Internal communication agility”, “Interchangeability to personnel resources”, “Manufacturing flexibility”, “degree of online solution”, “Quickness to resource up-gradation”, “Manageability to demand and supply change”, “Overstocking inventory practices” as significant metrics in ranking order. Additionally, “Transparency to share information”, “Internal communication agility”, “Manufacturing Flexibility”, “Green product (outgoing)” are found as influential metrics under LARG practices respectively.

A technical DSF to utilize by the managers is developed, which is connected with knowledge-based theory and a case of an automobile manufacturing firm is presented to illustrate its implementation. The companies can utilize presented DSF to impose service excellence, societal performance, agility and green surroundings in SC for achieving sustainable outcomes to be welcomed by the legislations, society and rivals. The framework represents an important decision support tool to enable managers to overcome imprecise SC information sources.

The study presented a proficient platform to review the most significant LARG alternative in the SC. The study suggested a cluster of LARG metrics to support operational improvement in manufacturing firms for shifting gear toward sustainable SC practices. The present study embraces its existence in enrolling a high extent of collaboration amongst clients, project teams and LARG practices to virtually eradicate the likelihood of absolute project failure.

The purpose of this paper is to contribute to the existing knowledge system of lean supply chain management (LSCM), i.e. by using main path analysis, and the authors extract the main development track of LSCM. It is advantageous for relevant scholars to deepen their understanding of this academic field from a bibliometrics view to grasp the future directions better.

Structuring a citation network with the processed data set containing 866 papers and relevant information collected from Web of Science (WoS). Conducting review analyses aiming at the main paths that are extracted from the above citation network.

There are two different evolution paths in LSCM field, i.e. improving corporate sustainability performance through combining lean and green practices, and seeking the balance between lean and agility to structure leagile supply chain for specific industries. LSCM research studies mainly focus on five aspects: (1) establishment and development of LSCM theory; (2) structuration of lean supply chain; (3) research studies of the relationship between LSCM and corporate performance; (4) supply chain evaluation system; and (5) review and vista of LSCM field. The intersection of two knowledge evolute routes would be Industry 4.0, which is an integrated theory system combining lean, agility, green and other supply chain thinking.

The data set collected from WoS cannot contain all the research studies about LSCM is the main research limitation. Sustainability, as represented by environmental performance, will continue to be a major pursuit of this field. Integrating LSCM in Industry 4.0 will be the next hotspot in LSCM field.

Providing the main research contents and common methods of LSCM field. It is conducive to deepening the understanding of relevant practitioners and scholars to LSCM field from a dynamic perspective.

To the best of the authors’ knowledge, it is the first time to reveal the knowledge diffuse trajectories of LSCM under different view with main path analysis. This study is unique that it provides a new view to understand the field of LSCM.

In the modern manufacturing environment, it is imperative to apply the manufacturing concepts of lean, agile, resilient and green, collectively known as LARG manufacturing, to achieve excellence in which lean manufacturing eliminates wastes; agile manufacturing makes processes fast, efficient and flexible; resilient paradigm deals with countering the uncertainty while green manufacturing improves environmental performance. The objective of this study is to develop an integration framework that synergizes LARG manufacturing with Industry 4.0.

Through a literature review, the authors have explored the possibility of collaboration between constituents of lean, agile, resilient and green manufacturing with the facets of Industry 4.0.

The authors have developed a comprehensive integration framework that has been divided into 11 phases and 31 steps in which the various Industry 4.0 facets have supplemented the lean, agile, resilient and green paradigms.

This investigation and adoption of technologically intensive automation shall provide clarity to practitioners regarding the synergy of LARG manufacturing & Industry 4.0, so that fast and efficient manufacturing processes can be achieved.

The framework provides detailed insight towards implementation of LARG practices in a manufacturing organization in coalescence with Industry 4.0 practices.

The purpose of this paper is to present green supply chain, resilient supply chain, agile supply chain, cold supply chain and lean supply chain (GRACL SC) procedures based on a detailed perspective, analyzing subjects in the past 19 years with a systematic literature review (SLR) of the papers reported from 2000 to 2019, and offering information and guidelines for further studies.

This research is based on 17 keywords in the title and topic of the articles and collects data from Web of Science (WOS) databases and objectively chooses 1,190 articles and performs meta-data analyses. Tables and statistical reports are based on the following three filters: publication year, authors and document type. At least, 39 publications from the ISI WOS has been examined for presenting information of categorization of the conducted research with regard to the content analysis, comprising the conceptual development and obstacles, cooperation with the supply chain elements, as well as mathematical and other optimization models.

Finally, this study answered three main questions in the research and demonstrates that the majority studies in the green supply chain (GSC) and a minimum number of studies on the cold supply chain have been conducted and 27 factors are chosen to achieve the 2000 to 2019 GRACL SCM model which robust and fit for Iranian food industries. The model shows that the agile, resilient and lean supply chain have direct effect on GSC and it can be said that all 27 groups which are selected for the final model of this research can be the main groups in the supply chain.

This paper was actually conducted by authors who reported it. To prevent plagiarized, redoubled efforts have been made and actually this paper is based on SLR methodology and the results are real and the researcher discusses the results appropriately. This investigation can have a positive impact within the field of expanding supply chain flexibility and lessening squander within the Iranian generation framework.

The research article's primary purpose is to understand the advancements in urban logistics and allied fields over time along with a consideration of its enabling technologies.

An initial review is used to build a keyword vocabulary, combinations of which were then applied to the Scopus, ScienceDirect, Emerald Insights, the Web of Science (WOS), Elsevier, Taylor and Francis, Wiley, Inderscience, Springer, Google Scholar and IEEE Xplore for extracting academic publication collection. The first part includes bibliometric analysis; network analysis is done based on the finally selected 645 papers (only those articles include either of the keywords mentioned above in title, abstract, and keywords). The second part conducts a review of the existing literature review studies (only 21 literature review studies out of 645 articles). The last one discusses the advancement in the topics based on the selected research articles.

This research discussed the advancement of the urban logistics and allied field, key academic forums and key researchers. It is evident from the analysis that the research related to key emerging themes like implementing innovative concepts and sustainability; application of green technologies; data collection, visualization, monitoring and sharing; and automatic logistic systems are still in the nascent stage. However, these research areas gained momentum in the recent past.

Urban logistics are essential and play a crucial role for such rapidly growing cities to function. Despite playing a vital role, urban ecosystem logistics is often neglected in formal urban planning. Hence, as a response to customer and business demand, private entities regularly invest in new technologies and solutions. Since such investments are toward profits, various environmental, social and economic challenges arise.

This research investigates the advancements in urban logistics toward smart, sustainable reforms in developing enabling technologies and markets. The obtained research articles are subjected to bibliometric, descriptive, network and content analysis to present a rundown of advancements, relationships and trends in emerging research gaps.

The purpose of this paper is to provide a framework for assessing the overall innovativeness of manufacturing firms using a multi-attribute group decision-making methodology.

This study identifies the indicators of firms’ innovativeness from the literature. The concept of neutrosophic numbers has been used to assign different importance weights to individual decision makers to account for the differences in their educational backgrounds and practical experience. An intuitionistic fuzzy based TOPSIS procedure is adapted for ranking the candidate firms based on their performance on identified criteria. The implementation of the proposed methodology is demonstrated through an explanatory example. Sensitivity analysis is carried out to judge the robustness of the proposed framework.

The proposed framework provides an efficient and reliable tool to subjectively evaluate and compare the innovativeness of manufacturing firms. The sensitivity analysis shows that the methodology is robust enough to absorb the noise factors/errors/variations, etc.

Motivated by this work, future studies can consider developing an integrated innovativeness index for evaluation of innovativeness of manufacturing firms. The concept of interval valued intuitionistic fuzzy and neutrosophic sets can be utilized to reduce the margin of perceptual errors even further.

The study will provide the firms with a framework for benchmarking their innovative performance. The firms can analyze their current performance and reconfigure their resources and capabilities suitably to improve their competitive position.

This study is one of the few attempts that have been made to articulate a firm level innovativeness assessment tool for manufacturing firms operating in an industry sector. Advanced concepts of fuzzy and neutrosophic sets have been utilized to eliminate the chances of bias/perceptual errors that most often affect the quality of decisions in today’s dynamic and uncertain decision-making environment.

This chapter focused on presenting the result of the Delphi study from the questionnaire distributed to the experts. The Delphi technique was used for modelling the construction supply chain management (CSCM) practice in the fourth industrial revolution (4IR) era. The technique was also used to predict the supply chain management's (SCM) possible trends in the construction industry. A total of 15 experts were selected for this study based on their working experience. The Delphi study also validated the gaps (organisational culture and 4IR component) identified from the existing CSCM model. The findings from the Delphi study revealed that organisational culture has a significant impact on the practice of CSCM in the 4IR era. Regarding adopting the 4IR component for the CSCM in Nigeria, the Delphi study revealed that smart management and virtualisation are the most adopted. Unfortunately, the cyber-physical system, the heartbeat of the 4IR, is yet to be fully implemented for CSCM practice in the Nigerian construction industry.