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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.

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.

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.

The purpose of this study is to improve supplier performance and strategic sourcing decisions by integrating jobshop scheduling, inventory management and agile new product development. During the COVID-19 pandemic, the organizations have struggled a lot to maintain the supplier performance and strategic sourcing decisions in the organizational benefit. However, in this context, the organization’s agile new product development (ANPD) process must be aligned with this requirement by maintaining the inventory and jobshop scheduling. As a result, identifying ANPD indicators, performance metrics and developing a structural framework to guide practitioners at various stages for smooth adoption is essential to improve the overall performance.

A comprehensive literature review is conducted to identify jobshop scheduling, inventory management and ANPD indicators along with the performance metrics, and the hierarchical structure is developed with the help of expert opinion. The modified stepwise weight assessment ratio analysis (SWARA) and weighted aggregated sum product assurance (WASPAS) techniques, along with expert judgement, are used in this study to calculate the weights of the indicators and the ranking of the performance metrics.

As per the weight computation by SWARA method, the strategy indicators have the highest relative weight, followed by the product design indicators, management indicators, technical indicators, supply chain indicators and organization culture indicators. According to the ranking of performance metrics obtained through WASPAS, the “frequency of new product development is at the top”, followed by “advances in product design and development” and “estimated versus actual time to market”.

It is believed that the framework developed will help industrial practitioners to plan effectively to improve supplier performance. The indicators identified may guide the ANPD penetration, and performance metrics may be useful for evaluation and comparison.

The outcomes of the present study will be extremely beneficial for the industry practitioners to improve the supplier performance. The indicators identified may guide the ANPD penetration, and performance metrics may be useful for evaluation and comparison.

A unique combination of modified SWARA–WASPAS technique has been used in this study which would be beneficial for organizations willing to adopt the jobshop scheduling and inventory management and ANPD for improving supply chain performance.

The Sustainable Lean Six Sigma (SLSS) adoption approach, advancements in Internet technologies and the use of Industry4.0 technologies has resulted in faster customer need fulfilment. The Industry4.0 technologies have resulted in a new paradigm where strategic and operational decisions are in favour of profitability and long-term viability. The purpose of this study is to identify Industry4.0-SLSS practices and sustainable supply chain performance metrics, as well as to develop a framework for decision-makers and managers to make supply chains more sustainable.

The 33 Industry4.0-SLSS practices and 24 performance metrics associated with the sustainable supply chain are shortlisted based on extensive literature review and expert opinion. The Pythagorean Fuzzy Analytical Hierarchy Process (PF-AHP) approach is used to evaluate the weights of Industry4.0-SLSS practices after collecting expert panel opinions. The Weighted Aggregated Sum Product Assessment (WASPAS) methodology used these weights to rank performance metrics.

According to the results of PF-AHP, “Product development competencies (PDC)” are first in the class of major criteria, followed by “Advanced technological competencies (ATC)” second, “Organisational management competencies (OMC)” third, “Personnel and sustainable competencies (PSC)” fourth and “Soft Computing competencies (SCC)” fifth. The performance metric “Frequency of NPD” was ranked first by the WASPAS method.

The proposed paradigm helps practitioners to comprehend Industry4.0 technology and SLSS practices well. The identified practices have the potential to boost the sustainability and supply chain's performance. Organizational effectiveness will benefit from practices that promote a sustainable supply chain and the use of developing technology. Managers can evaluate performance using performance metrics that have been prioritized.

The present study is one of the unique attempts to establish a framework for enhancing the performance of the sustainable supply chain. The idea of establishing Industry4.0-SLSS practices and performance measures is the authors' original contribution.

The COVID-19 pandemic era has severely hampered the economy over the globe. However, the manufacturing organizations across all the countries have struggled heavily, as they were among the least who worked on online mode. The organizations are adopting various innovative quality methodologies to improve their performance. In this regard, they are adopting the Sustainable Lean Six Sigma (SLSS) concept and Industry 4.0 technologies to develop products at a faster rate. The use of Industry 4.0 technologies may reduce material movement and supply chain disruptions with the help of smart intelligent systems. There is a strong synergy between SLSS and Industry 4.0 technologies, resulting in an integrated approach for adoption. This study aims to develop a framework that practitioners can use to adopt Industry 4.0-SLSS practices effectively.

This study portrays 31 Industry 4.0-SLSS practices and 22 performance metrics identified through a literature review to improve the manufacturing supply chain performance. To compute the weights of these practices, the Robust Best–Worst Method (RBWM) is used. The Pythagorean fuzzy combined compromise solution (PF-CoCoSo) method is used to rank performance metrics.

According to the RBWM results, “Process Development Practices (PDP)” are first among the major criteria, followed by “Organizational Management Practices (OMP)” at second, “Technology Adoption Practices (TAP)” at third, “Strategy Management Practices (SMP)” at fourth and “Executive Management Practices (EMP)” at fifth, whereas the PF-CoCoSo method resulted in the performance metric “On time product delivery” ranking first.

The identified practices have the potential to significantly improve the performance of the manufacturing supply chain. Practices that encourage a sustainable manufacturing supply chain and the usage of emerging technology will benefit organizational effectiveness. Managers can assess performance using prioritized performance metrics.

During the COVID-19 pandemic era, this is one of the unique attempts to provide a framework to improve the manufacturing supply chain performance. This study integrates and identifies Industry 4.0-SLSS practices and performance metrics for enhancing overall performance.