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This paper investigates the interactional relationships between sustainable human resource management (SHRM) and organizational performance (OP). Sustainable HRM is an approach that links HRM and sustainability. These studies focused on integrating HR with sustainable developments, such as economic and social aspects, in favour of focusing on the environmental aspect. Organizational change is an ongoing process that has to be managed effectively to keep the change in place for a long time.

A framework was offered to estimate the cause-and-effect relation of the SHRM and OP factors. Data is gathered from professionals from various pharmaceutical industries. This study applied two methods, Fuzzy AHP and DEMATEL Type II. These techniques are used to understand the cause-and-effect factors and their interactions.

It was observed from the findings that the factor of SHRM, such as Social Justice (F2), Green Job Design (F5), Green Training (F6) and Implementation of Green Policy (F8), was the most critical for the pharmaceutical sector that effects Financial performance (F13), Customer Satisfaction (F15) and Market performance (F14). Pharmaceutical firms ought to coordinate public health advocacy efforts, engage in healthcare initiatives and provide financial support for environmentally friendly efforts that improve social and economic conditions.

For this sustainability, managers concentrate on creating an environment that is healthy and acceptable, and they work hard to mitigate the impact of natural factors and repair damage done to the environment; it is essential to move towards sustainable development to resolve environmental problems. Improving HR efficiency is among essential HRM responsibilities, as they expand the knowledge base of the workforce, enhance human capital, and eventually create valuable intangible assets and promote and encourage sustainable pharmaceutical products for some years.

This research paper has presented exclusive worth to the SHRM and organizational performance literature as it employs fuzzy FAHP and DEMATEL type 2. There is less research on SHRM in the pharmaceutical sector with these factors. In addition, FAHP and TYPE 2 DEMATEL are used in very few researches on SHRM approaches.

Organizations have increasingly been compelled to engage in ecological businesses in recent decades, necessitating identifying environmental practices contributing to enhanced sustainability. One of the main reasons for doing this research is to see how far down the path to green transformational leadership (GTFL) in Green Human Resource Management (GHRM) practices in the healthcare industry in Pakistan. Additionally, this research aims to analyze how this change affects the long-term success of businesses in sustainable performance (SP).

To identify factors related to the study variables, the research utilized master journals, as well as the Web of Science and Scopus databases. The ISM-DEMATEL (Interpretive Structural Modeling - Decision Making Trial and Evaluation Laboratory) technique was employed to establish a hierarchical model. This model facilitated the identification of cause-and-effect relationships among factors, which were further elucidated using the DEMATEL interrelationship diagram.

The analysis of the results indicates that Green Training (F4), Green Job Analysis (F1), Intellectual Stimulation (F10), and Green Product Innovation (F9) are the primary factors that have a significant impact on achieving Environmental Policies and Regulations (F13), and Subjective Environment Norms (F14) of SP factors.

The study is implemented in the healthcare industry of Pakistan, with a focus on practical and managerial aspects. It encourages managers to develop and adapt their human resources policies and environmental strategies. Implementing safety health standards is crucial to mitigate the detrimental effects on the environment. The research was carried out during the period of the pandemic. The scope of this study was restricted to the healthcare industry in Pakistan.

In order to improve SP, this study presents a unique strategy combining sustainability into decision-making procedures with the function of GTFL in GHRM. Implementing safety health standards is crucial to mitigate the detrimental effects on the environment.

The advancements in internet technologies and the use of sophisticated digital devices in supply chain operations incessantly generate enormous amounts of data, which is termed as big data (BD). The BD technologies have brought about a paradigm shift in the supply chain decision-making towards profitability and sustainability. The aim of this work is to address the issue of implementation of the big data analytics (BDA) in sustainable supply chain management (SSCM) by identifying the relevant factors and developing a structural model for this purpose.

Through a comprehensive literature review and experts’ opinion, the crucial factors are found using the PESTEL framework, which covers political, economic, social, technological, environmental and legal factors. The structural model is developed based on the results of the total interpretive structural modelling (TISM) procedure and MICMAC analysis.

The policy support regarding IT, culture of data-based decision-making, inappropriate selection of BDA technologies and the laws related to data security and privacy are found to affect most of the other factors. Also, the company’s vision towards environmental performance and willingness for material and energy optimization are found to be crucial for the environmental and social sustainability of the supply chain.

The study is focused on the manufacturing supply chain in emerging economies. It may be extended to other industry sectors and geographical areas. Also, additional factors may be included to make the model more robust.

The proposed model imparts an understanding of the relative importance and interrelationship of factors. This may be useful to managers to assess their strengths and weaknesses and ascertain their priorities in the context of their organization for developing a suitable investment plan.

The study establishes the importance of BDA for conservation and management of energy and material. This is crucial to develop strategies for enhancing eco-efficiency of the supply chain, which in turn enhances the economic returns for the society.

This study addresses the implementation of BDA in SSCM in the context of emerging economies. It uses the PESTEL framework for identifying the factors, which is a comprehensive framework for strategic planning and decision-making. This study makes use of the TISM methodology for model development and deliberates on the social and environmental implications too, apart from theoretical and managerial implications.

Implementing blockchain in sustainable development goals (SDGs) and environmental, social and governance (ESG)-aligned infrastructure development involves intricate strategic factors. Despite technological advancements, a significant research gap persists, particularly in emerging economies. This study aims to address the challenges related to SDGs and ESG objectives during infrastructure delivery remain problematic, identifying and evaluating critical strategic factors for successful blockchain implementation.

This study employs a three-stage methodology. Initially, 13 strategic factors are identified through a literature review and validated by conducting semi-structured interviews with six experts. In the second stage, the data were collected from nine additional experts. In the final stage, the collected data undergoes analysis using interpretive structural modeling (ISM)–cross-impact matrix multiplication applied to classification (MICMAC), aiming to identify and evaluate the independent and dependent powers of strategic factors driving blockchain implementation in infrastructure development for SDGs and ESG objectives.

The study’s findings highlight three significant independent factors crucial for successfully integrating blockchain technology (BT) into infrastructure development for SDGs and ESG goals: data security (F4), identity management (F8) and supply chain management (F7). The study unravels these factors, hierarchical relationships and dependencies by applying the MICMAC and ISM techniques, emphasizing their interconnectedness.

This study highlights critical strategic factors for successful blockchain integration in SDG and ESG-aligned infrastructure development, offering insights for policymakers and practitioners while emphasizing the importance of training and infrastructure support in advancing sustainable practices.

The fresh food supply chain industry faces significant challenges in risk management because of the complexity, immature development and unpredictable external environment of imported fresh food supply chains (IFFSCs). This study aims to identify specific risk factors in IFFSCs, demonstrate how these risks are transmitted within the system and provide an analytical framework for managing these risks.

A total of 15 risk factors for IFFSCs through extensive literature review and expert consultation are identified and classified into seven levels using interpretive structural modeling (ISM) to demonstrate the risk transmission path. Fuzzy Matrice d’Impacts Croises-Multiplication Appliance Classement (MICMAC) analysis is then used to analyze the role of each factor.

The interactions of the 15 identified risk factors of IFFSCs, classified into seven levels, are visualized using ISM. The fuzzy MICMAC analysis classifies the factors into four groups, namely, dependent, independent, linkage and autonomous factors, and identifies the relatively critical risk factors in the system.

The findings of this research provide a clear framework for enterprises operating in IFFSCs to understand the specific risks they may face and how these risks interact within the system. The fuzzy MICMAC analysis also classifies and highlights critical risk factors in the system to facilitate the formulation of appropriate mitigation measures.

This study provides enterprises in IFFSCs with a comprehensive understanding of how the risks can be effectively managed and a basis for further exploration. The theoretical model constructed is also a new effort to address the issues of risk in IFFSCs. The ISM and the fuzzy MICMAC analysis offer clear insights for researchers and enterprises to grasp complex concepts.

With gaining popularity, online communities are increasing. It is leading to the data and information overflow. So, there are some challenges like cyber frauds, cyberbullying, etc. while engaging with online communities. Not only this, anonymity of the participants, stress and racism are also big challenges in online communities' interaction. Online harassers' attack tactics have changed over time. In addition, there are challenges like quality of discussion, inequality in participation of the users, etc. may scale online communities towards incitement and activism. Therefore, this study will try to analyse these challenges for overall benefit of the society.

The underlying fuzzy set theory is employed to handle the fuzziness of users' perceptions since the attributes are expressed in linguistic preferences. Through exhaustive literature review, the authors have identified 15 challenges. These challenges are further categorised as cause and effect by using DEMATEL (Decision-Making Trial and Evaluation Laboratory) approach.

Lack of strategic planning and uninspired discussions between users has emerged as a major challenge in cause category. This study further demonstrates how individual challenge can be managed and developed to navigate the online communities to maintain a healthy environment in society.

Results are based on limited dataset. Therefore, findings cannot be generalised for all online communities.

The research findings offer a suitable direction to policymakers to formulate and design policies, laws and regulations to increase user engagement in the online community. The study is beneficial to firms and researchers in understanding the factors influencing effective management of online communities.

The purpose of this study is to find out what is the relationship between sustainability toward consumer behavior. Consumer behavior is the method of choosing, buying and using goods and services with an attachment to needs and wants. Now consumers are aware about sustainability, they make purchase decisions according to environmental safety, benefit to the society and increase economic growth.

This study validates the result through experts in textile industry by using the Decision-Making Trial and Evaluation Laboratory approach. This method has many benefits which provide decision makers and experts to understand the interdependence and influential relation between the criteria by hierarchical approach.

According to the results, green culture (F8) and green brand (F3) are the most influential (causal) factors and exert a substantial amount of influence over other factors for achieving organizational performance and sustainability. On the other hand, past experience (F14) and time pressure (F12) are the most influenced (effect) factors that are highly influenced by other factors.

The study conducted in Pakistan underscores the significance of maintaining a healthy and pristine environment for future generations. Both consumers and organizations play a vital role in this endeavor. It is imperative that they actively promote and support goods and services that advocate for sustainability.

Mangers should use long-term strategies that meet the high product value to enhance the organization’s reputation, so it will have positive consumer perception. If managers make policies to implement natural resources in their raw material, so this policy avoids conflicts and maintains a balance in our society.

This research delves into the complexities and subtleties associated with the identification and examination of the interconnections between the success factors of sustainability and consumer behavior.

The purpose of this study is to understand the rational cogent correlation among the factors that are responsible for the implementation of entrepreneurship to reinstate the severely affected ecosystem during the coronavirus disease 2019 (COVID-19) pandemic.

This paper attempts to identify the various units of entrepreneurship and public policies of entrepreneurship from the coherent literature review and examine the units' objectives. Examination of these units will help understand how the economy can recover from the COVID-19 impact. Total interpretive structural modeling (TISM) and matrix impacts cross multiplication applique and classement (MICMAC) have been used to recognize the factors, which are responsible for detangling the slowdown of the economy.

On the basis of the literature review, a total of 13 factors have been identified. The TISM methodology represents the hierarchical structure of the recognized factors and examines the pros and cons.

The TISM lags to explain the strength and bond among the factors. The MICMAC addresses this problem and advises what factor plays an essential role and which factor impact is the least. An advocate administration of the factors could help to achieve a successful entrepreneurial plan.

An analytic study of the literature review demonstrates the relationship among the units to frame an entrepreneurial plan during the COVID-19 pandemic by using the TISM methodology. Hence, TISM provides reasonable facts to examine why and what factors need more attention for the generation of new business starters in the economic crisis.

The agri-food industry is experiencing a revolutionary shift due to the introduction of Industry 4.0 technologies to improve efficiency, transparency and sustainability. The importance of agri-food supply chains (AFSC) in promoting sustainability is expanding as the globe struggles with issues including resource scarcity, climate change and population growth. In order to better understand how Industry 4.0 might improve sustainability in a world that is changing quickly, this work aims to focus on identifying various sustainability assessment factors influencing AFSC to increase overall sustainability, minimize resource consumption, cut waste and streamline operations.

Important sustainability assessment factors are identified from the past academic literature and are then validated using the fuzzy-Delphi method. A method called decision-making trial and evaluation laboratory (DEMATEL) is used to examine and analyze structural models with complex causal linkages. The results are then validated using sensitivity analysis.

The factors that emerged as the highest ranked for evaluating the sustainability of Industry 4.0 in AFSC are market competitiveness, and knowledge and skill development, followed by resource efficiency. Industry 4.0 technologies are essential for increasing the marketability of agricultural products because of the major implications of market competitiveness. The significance of knowledge and skill development draws attention to Industry 4.0’s contribution to the promotion of chances for farmers and agricultural employees to increase their capability.

By outlining the nexus between Industry 4.0 technologies and sustainability, the study presents a comprehensive framework that would be relevant for researchers, policymakers and industry stakeholders who want to leverage Industry 4.0 technology to build more sustainable AFSC in the future. The study findings can help the farmers or producers make sensible choices that adhere to sustainability standards and guarantee long-term financial viability.

The originality of this work lies in the identification of sustainability assessment factors especially for AFSC in the era of digitalization which has not been discussed previously.

In academics and industry, significant efforts have been made to lead planners and control teams in evaluating project performance and control. In this context, numerous control metrics have been devised and put into practice, often with little emphasis on analyzing their underlying concepts. To cover this gap, this research aims to identify and analyze a holistic list of control metrics and their functionalities in the construction industry.

A multi-step analytical approach was conducted to achieve the study’s objectives. First, a holistic list of control metrics and their functionalities in the construction industry was identified. Second, a quantitative analysis based on social network analysis (SNA) was implemented to discover the most important functionalities.

The results revealed that the most important control metrics' functionalities (CMF) could differ depending on the type of metrics (lagging and leading) and levels of control. However, in general, the most significant functionalities include managing project progress and performance, evaluating the look-ahead level’s performance, measuring the reliability and stability of workflow, measuring the make-ready process, constraint management and measuring the quality of construction flow.

This research will assist the project team in getting a comprehensive sensemaking of planning and control systems and their functionalities to plan and control different dynamic aspects of the project.