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The United Nations member countries adopted a set of 17 sustainable development goals (SDGs) to achieve a better and more sustainable future for all. It encourages the use of sustainable practices during new product development (NPD). Competitiveness has put pressure on organizations to maintain their market share and look for new approaches related to NPD. The current study aims to focus on creating a framework that can help to achieve the SDGs by adopting agile new product development (ANPD) practices and Industry 4.0 technologies.

From the literature, various ANPD practices, Industry 4.0 technologies, performance metrics, their interconnection and their contribution toward achieving SDGs are extracted. The weights of selected Industry 4.0–ANPD practices are computed by robust best worst method (RBWM), and the Fuzzy-VIKOR method is used to rank the selected performance metrics. To test the robustness of the developed framework, sensitivity analysis is also performed.

The results show that among the various Industry 4.0–ANPD practices “Multi-skilled employees” have the highest weight followed by “Customer requirement analysis and prioritization.” Whereas for performance metrics, “The number of innovative products launched per year” is ranked first, with the “Average time between two launches” at second place.

This research contributes to the adoption of ANPD practices and Industry 4.0 technologies for the achievement of the business SDGs. The shortlisted Industry 4.0–ANPD practices will help in resolving the social and environmental issues. The set of performance metrics will help practitioners and managers to evaluate the performance of ANPD in the context of business SDGs.

This study adds to the understanding related to Industry 4.0–ANPD practices adoption. And to the best of the authors’ knowledge, it is believed that no similar work has been done previously and by using industry insights into technology components, this work contributes to valuable insights into the subject.

To endure against the global rivalry, various organizations are espousing several quality melioration techniques, but most of them flunk to implement them in palmiest way; hence, to surmount the failure of implementation, it is very essential to identify and prioritize the impediments of the technique to be implemented. Lean Six Sigma (LSS) has evolved as one of the most efficacious technique implemented by organizations. The purpose of this paper is to identify and prioritize the barriers of LSS for its productive implementation.

The study initiates from conducting a literature review of peer-reviewed articles concentrating on LSS barriers. The barriers are identified from literature as well as opinion from industry experts. These barriers are categorized underneath the canopy of five major criteria. The final elite barriers are prioritized and stratified by employing the fuzzy analytical hierarchy process approach.

The present study identifies 27 critical barriers that obturate the palmy LSS implementation. Further prioritization of these barriers will help the practitioners to develop the strategies to tackle the barriers.

The LSS barriers are identified through the literature search and opinions from industry experts, while a survey can be conducted in order to incorporate more barriers related to manufacturing concerns.

The main contribution of this paper includes identification of LSS barriers and later prioritizing them to project their intensity in order to make the practitioners comfortable to handle the LSS implementation issues.

The purpose of this paper is to identify Lean Six Sigma enablers (LSSEs) and analyse the interaction among the enablers via a hierarchical model developed by employing interpretive structural modelling (ISM) and determine the driving and dependence power of enablers through fuzzy MICMAC (Matriced’ Impacts Croise´s Multiplication Applique´ea´un Classement) analysis.

An expert group of industry professionals and academicians is consulted at the initial stage as an input for ISM methodology to explore the paired relationship among LSSEs for each parameter of Lean Six Sigma (LSS) implementation. The outcome of ISM is further utilized by fuzzy MICMAC analysis to discover the enablers that are strong drivers and highly dependent. Fuzzy set is included in MICMAC analysis in order to obtain more precise output and effective model.

In total, 20 key enablers are identified through a literature review and expert opinion that emerged as the most significant factors towards LSS implementation. The identified enablers are portrayed into a structural form representing as input and output variables. Later, the driving and the dependence power of each enabler is presented in cluster form.

The paired relationships among LSSEs are obtained through the interpretation made by the experts. The judgments of experts are subjective and may be biased; as difference in expert opinion may influence the final outcome. Conducting a large-scale survey may provide a better catch for interactions of LSSEs.

This study provides strong practical implications for researchers as well as industry practitioners. The industry professionals must deliberately focus on the identified LSSEs more conservatively during LSS implementation and the top management should plan strategically to avoid any implementation failure.

The present study identifies 20 crucial enablers of integrated LSS and presents them in a hierarchical form which will be beneficial for researchers and practitioners. The interactions among the enablers shown in cluster form will help in better execution of LSS.

This paper aims to guide about prioritisation and ranking of the solutions and overcoming barriers to facilitate the adoption of Lean Six Sigma (LSS) by using a hybrid framework.

It identifies LSS barriers and solutions to facilitate LSS adoption through literature review and by involving subject experts. The study makes use of fuzzy set theory and proposes a fuzzy analytical hierarchy process (AHP)-modified TOPSIS (technique for order preference by similarity to ideal solution) framework. It uses sensitivity analysis to establish framework robustness.

The key findings of this techno-managerial study are identification and prioritisation of 27 LSS barriers and 22 solutions to overcome adoption challenges, proposition and usage of fuzzy AHP-modified TOPSIS framework, guidance regarding where to focus for facilitating LSS adoption and ensuring robustness using sensitivity analysis, which establishes insignificant deviation in rankings when criteria weights are altered.

Some biasness and subjectivity may exist during pairwise comparisons as human judgements are involved.

Handling a hybrid solution like LSS is never easy. It is expected that the study will help industry professionals to plan their LSS adoption attempts effectively. Guidance regarding LSS barriers will assist in observing necessary precautions to avoid failures. It will open up new research fronts for researchers also.

Literature is full of studies regarding LSS barriers and its rankings. It is very rare to witness a study like ours, which discusses the barriers and links with solutions and its prioritisation. Proposed hybrid framework for a hybrid techno-managerial approach such as LSS is unique and acts as the roadmap for smooth implementation.

The main purpose of this study is to explore different aspects of the Green Lean Six Sigma (GLSS) approach, application status and potential benefits from a comprehensive review of the literature and provide an avenue for future research work. This study also provides a conceptual framework for GLSS.

To do a systematic analysis of the literature, a systematic literature review methodology has been used in this research work. From the reputed databases, 140 articles were identified to explore hidden aspects of GLSS. Exploration of articles in different continents, year-wise, approach-wise and journal-wise was also done to find the execution status of GLSS.

This study depicts that GLSS implementation is increasing year by year, and it leads to considerable improvement in all dimensions of sustainability. Enablers, barriers, tools and potential benefits that foster the execution of GLSS in industrial organizations are also identified based on a systematic review of the literature.

The study’s uniqueness lies in that, to the best of the authors’ knowledge, this study is the first of its kind that depicts the execution status of GLSS, and its different facets, explores different available frameworks and provides avenues for potential research in this area for potential researchers and practitioners.

The literature of lean six sigma (LSS) is flooded with frameworks. But to date, there has been no attempt to expose the inconsistencies in the existing frameworks and associated research trends. The purpose of this paper is to critically review 26 LSS frameworks and highlight inconsistencies. The study also helps in analysing research trends and constructs of LSS frameworks, and facilitates new applications.

It uses Scopus database and finalises 26 frameworks in the LSS domain considering a timeframe from 2000 to 2017, using a structured literature review approach and involving domain experts. It uses a battery of systematic requirements-based questions to understand trends and covers building blocks/constructs also.

It reveals inconsistencies at three different stages, namely, the framework stage, usage stage capturing existing research trends and construct stage. It also offers details at building block/construct level. Thus, it offers guidance in reducing inconsistencies and possible modifications in the existing frameworks. It not only exposes existing constructs and sub-constructs but also guides about the new upcoming changes in the business influencing the LSS domain. It also educates about the strengths and weaknesses of each framework.

This study tries to reduce inconsistencies, but does not offer new generalised or sector-specific framework.

This study will assist for modification/corrections in the existing frameworks by reducing inconsistencies and will encourage new frameworks to facilitate applications.

This is a unique study which offers frameworks-based review, portrays research trends and guides about constructs of a framework by exposing inconsistencies at each stage. It helps in reducing inconsistencies and offers guidance regarding modifications in the LSS framework considering upcoming challenges.

Sustainable supply chain management (SSCM) is a new subfield of supply chain management. The purpose of this research is to develop a framework for assessing the impact of agile new product development (ANPD) practices on the environmental SSCM performance.

The ANPD practices and SSCM environmental performance metrics (SEPMs) are identified through the literature review. The shortlisted ANPD practices are categorized into five major criteria each with an own set of sub-criteria. A four-level conceptual framework is developed. The weights of these ANPD practices are computed using the Pythagorean fuzzy Analytical Hierarchy Process (PFAHP), and the SEPMs are ranked using the Pythagorean fuzzy Combined Compromise Solution (PFCoCoSo).

The results show that the major criterion “Innovation Aspects” is the most important with a weightage of 0.2368, followed by “Policy Aspects” having 0.2228, “Technology Aspects” with 0.1959, “Organisation Aspects” having 0.1786 and “Executive Aspects” with 0.1658 weightage. The SEPMs “Frequency of NPD” is ranked first with an assessment value (Ki) of 2.5569, followed by “Lead time reduction” and “Number of design iterations” with Ki of 2.4482 and 2.3897, respectively. The research findings show that the ANPD practices like customer need assessment, availability of multidisciplinary team and Industry 4.0 technology usage contribute more to achieving environmental SSCM.

Managers can enhance environmental SSCM performance by adopting the ANPD practices and prioritizing SEPMs. Corporate effectiveness will be increased by the practices that promote SSCM and the use of technological innovations.

This study identified a unique set of 22 performance metrics that quantitatively measure NPD performance as well as environmental SSCM performance by adopting the 31 ANPD practices that were shortlisted. The proposed framework is a novel synthesis of literature from various disciplines such as new product development (NPD), environmental management, SSCM and performance evaluation.

Because of the COVID-19 pandemic and changing market demands, competition for manufacturing industries is increasing and they face numerous challenges. In such a case, it is necessary to use multiple strategies, technologies and practices to improve organizational performance and, as a result, to integrate them for ease of adoption. The purpose of this research is to identify advanced Industry 4.0 technologies, operational excellence (OPEX) strategies and reconfigurable manufacturing system (RMS) practices. The study also computes their weights, as well as identifies and prioritizes the performance metrics for the same.

A thorough review of relevant articles was conducted to identify 28 OPEX strategies, RMS practices and advanced technologies, as well as the 17-performance metrics. The stepwise weight assessment ratio analysis approach was used to compute the weights of the selected practices, while the WASPAS approach was used to prioritize the performance metrics. While developing the framework, the industry expert’s expertise was incorporated in the form of their opinions for pairwise comparison.

According to the study findings, advanced Industry 4.0 technologies were the most prominent for improving organizational performance. As a result, integrating Industry 4.0 technologies with OPEX strategies can assist in improving the performance of manufacturing organizations. The prioritized performance metrics resulted in the production lead time ranking first and the use of advanced technologies ranking second. This emphasizes the significance of meeting dynamic customer needs on time while also improving quality with the help of advanced technologies.

The developed framework can help practitioners integrate OPEX strategies and advanced technologies into their organizations by adopting them in order of importance. Furthermore, the ranked performance metrics can assist managers and practitioners in evaluating the manufacturing system and, as a result, strategic planning for improvement.

According to the authors, this is a novel approach for integrating OPEX strategies with advanced Industry 4.0 technologies, and no comparable study has been found in the current literature.

The market's intense competition, the unpredictability of customer demands and technological advancements are compelling organizations to adopt new approaches, such as agile new product development (ANPD), which enables the introduction of new products to the market in a short span. The existing ANPD literature review articles are lacking in portraying recent developments, potential fields of adoption and the significance of ANPD in organizational development. The primary goal of this article is to investigate emerging aspects, current trends and conduct a meta-analysis using a systematic review of 177 ANPD articles published in peer-reviewed journals between 1998 and 2020.

The articles were categorized based on their year of publication, publishers, journals, authors, countries, universities, most cited articles, etc. The authors attempted to identify top journals, authors, most cited articles, enablers, barriers, performance metrics, etc. in the ANPD domain through the presented study.

The major themes of research articles, gaps and future trends are identified to assist academicians and ANPD practitioners. This study will benefit ANPD professionals by providing them with information on available literature and current ANPD trends.

Through meta-analysis, this study is one of the unique attempt to categorize ANPD articles to identify research gaps and highlight future research trends. A distinguishing feature of the presented study is the identification of active journals, publishers and authors, as well as enablers, barriers and performance metrics.

Blockchain technology (BCT) can be used for a wide variety of applications across domains and can bring many benefits. BCT-based applications can be beneficial for the government as well as businesses. Despite the many promises, BCT implementation lags behind. The purpose of this research is to identify a roadmap of critical implementation challenges that influence BCT implementation by governments.

The study develops an ISM-based model spread across seven levels to analyze the inter-relationship among the selected BCT challenges. The MICMAC analysis further helps in evaluating the variables based on their driving power and dependencies.

The findings show that all challenges have a strong impact on implementing BCT. The foundation for implementation BCT is to define standards and develop appropriate regulations. Next, the findings show the need for a shared infrastructure meeting the basic technical and societal requirements and developing viable business models to advance BCT implementation. Many challenges hinder the development of blockchain applications meeting the technical and ethical requirements.

Existing research has analyzed the relationship among challenges. To the best of the authors' knowledge this is the first paper to collate these implementation challenges and incorporate them to develop a hierarchical model using interpretive structural modeling technique. The results can be used to prioritize the tackling of the challenges.