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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 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.

In 1990, the federal government of the United States passed a bill to allow an increase in legal immigration by 1.2 million until 1994. Many questions concerning immigration have been detailed in the economics literature. They concern the effects of immigration on the earnings of the native born, immigration as a form of worker‐sorting, and the allocation schemes concerning the immigration of skilled and non‐skilled workers. Examines the theoretical and empirical answers to these questions. Points out that an examination of immigrant earnings over time often depends on the type of model selected, cohort or cross‐sectional analysis. Also, many immigrants seek a political and economic environment that promotes self‐employment as a form of worker‐sorting. Also of interest, theoretical debate is provided on the nature of immigration, being either political or economic. The debate over immigration has many policy implications for the 1990s, because of the first changes in immigration restrictions since Simpson‐Rodino of 1965.

This study aims to investigate the effect of organizational ambidexterity (OA) and organizational green culture (OGC) on corporate sustainability (CS) while incorporating the mediating role of green innovation (GI) to provide a detailed insight into CS. The study also presents a research framework based on the Organizational Ambidexterity theory and Natural Resource-based view to explain the factors contributing to CS.

Using stratified sampling, the study collected data through survey-based empirical research from 307 textile companies registered with the Securities and Exchange Commission of Pakistan (SECP) or the All-Pakistan Textile Mills Association (APTMA). The collected data were analysed using path analysis, mediation analysis and moderation analysis through smart PLS-SEM version 4.0 to assess the composition and causal association of factors.

The study found a significant relationship between OA and OGC with CS. Furthermore, the study revealed that green innovation partially mediates the relationship between OGC and CS. The proposed research framework can be valuable for promoting and recommending actions to enhance CS.

The study on CS in the textile sector of Pakistan has limitations such as a narrow focus, cross-sectional design and reliance on self-reported data. Future research should explore additional factors, conduct longitudinal research, investigate contextual factors, scrutinize specific green innovation practices and broaden the scope of the study to include SMEs and other textile organizations.

The research framework can help senior executives to foster CS by promoting OGC, OA and GI. Practitioners and academicians can also utilize or further investigate the proposed framework for validation and to foster CS.

This study fills gaps in the existing literature by investigating the mediating effect of GI between OGC and CS. The proposed research framework provides a comprehensive understanding of the factors contributing to CS based on the Organizational Ambidexterity theory and Natural Resource-based view.

This paper proposes a unified original general framework, designed to theoretically develop and to extremely easily implement elastoplastic constitutive laws defined in the so called two-invariants space, both in small and finite strain regime.

A general return mapping algorithm is proposed, and particularly a standard procedure is developed to compute the two algorithmic tangent operators, required to solve the Newton–Raphson scheme at the local and global level and thus cast the elastoplastic algorithm within a FEM code.

This work demonstrates that the proposed procedure is fully general and can be applied whatever is the elastic law, the yield surface, the plastic potential function and the hardening law. Several numerical examples are reported, not only to demonstrate the accuracy and robustness of the algorithm, but also explain how to use this general algorithm also in other applications.

The proposed algorithm and its numerical implementation into a FEM code is new and original. The usefulness and the value of the algorithm is twofold: (1) it can be implemented in a small and finite strain simulation FEM code, in order to handle different types of constitutive laws in the same modular way, thus fully leveraging on modern object-oriented coding approach; (2) it can be used as a framework to develop (and then to implement) new constitutive models, since the researcher can simply define the relevant functions (and its main derivatives) and automatically get the numerical algorithm.

Health care organisations implement lean six sigma (LSS) methodology to achieve improved performance in terms of cost, quality and productivity. However, the way it gets implemented differs between organisations. Hence, this paper deal with a review of case studies describing the implementation of LSS in health care organisations to understand the nuances of implementation and identify future research directions.

The journal articles indexed in the Web of Science and Scopus database were filtered out. In total, 154 articles were evaluated using specific structural dimensions to categorise the literature into various groups, and content analysis was performed to synthesise the same.

This review revealed that the number of articles publishing the application of LSS in health care has been increasing in the last five years. Academic hospitals play a pivotal role to bridge the gap between LSS theory and practice. Despite this fact, certain themes remain unexplored. Not many studies are available that document the application of LSS in non-clinical areas such as pharmacy, internal logistics, maintenance and medical records. Only 20% of articles mentioned the post-intervention data up to three years, thus questioning the sustainability aspect of the achieved improvements.

Various research gaps were identified, which can be used by the researchers to build the body of knowledge in the domain of LSS in health care.

This review provides a diversified view regarding the utility of LSS in the health care scenario. The findings will provide valuable insights for the health care practitioners regarding tools, techniques, drivers and performance measures.

To the best of the authors’ knowledge, this is the first study to review only the case studies that describe the implementation of LSS in the health care sector.

In our society, medical care and economic progress have improved the duration and quality of life, but aging is accelerated by social norms and their psychological introjection. Healthy aging involves the continuing pursuit of creative activity. Changes in self‐view and behavior will require and promote a change in social roles, and the emancipatory mobilization of senior adults of both sexes and all classes.

The study examined the influence of environmental standards set by the SME agro-based processing firms and farmers' environmental empowerment on farmers' adoption of environmentally friendly agricultural practices; and the mediating role of empowerment on the relationship between SME agro-based processing firm environmental standards and farmers' adoption of environmentally friendly agricultural practices.

Data was collected from purchasing managers of the agro-based processing firms. The SPSS software, SMART PLS and CB-SEM software were used to obtain results on the influence of environmental standards set by the SME agro-based processing firms on adoption of environmentally friendly agricultural practices; the influence of farmers' environmental empowerment on adoption of environmentally friendly agricultural practices and the mediating role of farmers' environmental empowerment on the relationship between SME agro-based processing firm environmental standards and farmers' adoption of environmentally friendly agricultural practices.

Findings indicated that SME agro-processing environmental standards have an influence on farmers' adoption of environmentally friendly agricultural practices. Empowering farmers in environmental issues influenced their adoption of environmentally friendly agricultural practices. A partial mediation effect was observed on testing the mediating role of farmers' environmental empowerment on the relationship between SME agro-based processing firm environmental standards and farmers' adoption of environmentally friendly practices.

The study mainly focused on the upstream part of agricultural supply chains. The research has implications to decision-makers in government concerned with enhancing environmentally friendly practices among farmers in general.

The influence of SME agro-based processing firm environmental standards on farmers' adoption of environmentally friendly agricultural practices; the influence of farmers' environmental empowerment on farmers' adoption of environmentally friendly practices; and the mediating role of farmers' environmental empowerment on the relationship between SME agro-based processing firm environmental standards and farmers' adoption of environmentally friendly agricultural practices are aspects that have not been given significant attention.

The paper seeks to analyse the self‐selection of international migrants on observable skills.

Based on an extended version of the Roy model, which considers random migration costs, the authors analyse the self‐selection of migrants on observable skills empirically. For this purpose, the authors employ a new panel data set on the educational attainment of migrants, which covers migration from 143 sending countries into the six main receiving countries in the OECD from 1975 to 2000.

Migrants tend to be positively self‐selected on observable skills, although the inequality in earnings is larger in the sending country relative to the destination countries. The estimation results indicate that a higher inequality in the distribution of earnings in both the receiving and the sending country affects the skill bias of the migrant population favourably. Moreover, higher migration costs and selective immigration policies increase the skill level of migrants relative to those of stayers in the sending countries.

The results may be affected by measurement error, since it was necessary to approximate the returns to education by measures for the inequality of earnings.

The paper provides, inter alia, insights as to how immigration and other policies affect the self‐selection of migrants on observable skills, which may be relevant for policy makers.

To the authors' knowledge, this is the first paper to analyse the self‐selection of migrants on the basis of a panel data set.