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The complex network structure causes several disruptions in the supply chain that make risk management essential for supply chain management including halal supply chain (HSM). During risk management, several challenges are associated with the risk assessment phase, such as incomplete and uncertain information about the system. To cater this, the authors propose a risk assessment framework that addresses the issues of uncertainty using neutrosophic theory and demonstrated the applicability of the proposed framework through the case of halal supply chain management (HSCM).

The proposed framework is using the capabilities of the neutrosophic number which can handle uncertain, vague and incomplete information. Initially, the risk related to the HSC is identified through a literature review and expert’s input. Further, the probability and impact of each HSM-related risk are assessed using experts’ input through linguistic terms. These linguistic values are transformed into single-value trapezoidal neutrosophic numbers (SVTNNs). Finally, the severity of each HSM-related risk is determined through the multiplication of the probability and impact of each risk and prioritised the risks based on their severity.

A comprehensive risk assessment framework is developed that could be used under uncertainty. Initially, 16 risks are identified related to the HSM. Further, the identified risks are prioritised using the severity of the risks. The high-priority risk is “raw material status”, “raw material wholesomeness” and “origin of raw material” while “information integrity” and “people integrity” are low-priority risks.

HSM risk can be effectively assessed through the proposed framework. The proposed framework applied neutrosophic numbers to represent real-life situations, and it could be used for other supply chains as well.

The proposed method is effectively addressing the issue of linguistic subjectivity, inconsistent information and uncertainty in the expert’s opinion. A case study of the HSC is adopted to illustrate the efficiency and applicability of the proposed risk framework.

The objectives of the study were to identify the effects of blockchain technology (BT) on the university librarians, the impact of BT on the university library services and to reveal the challenges to adopt BT in the university libraries.

A systematic literature review was applied to address the objectives of the study. Around 25 studies published in peer-reviewed journals were selected to conduct the study.

The findings of the study revealed that blockchain technology (BT) has positive effects on the university librarians as it assists them in digital resources management, provision of integrated library services, effective records management and continued professional development. The study also displayed that BT has a positive impact on the university libraries through effective information management, user privacy, collaboration, technological innovation and access control. Results also revealed that technical issues, financial constraints, security problems, skill issues and sociocultural issues created challenges to adopt BT in the university libraries.

The study has offered theoretical implications for future investigators through the provision of innovative literature on the prospectus and challenges associated with blockchain in the context of librarianship. The study has also provided practical implications for management bodies by offering recommendations for the successful adoption of blockchain in the university libraries. Additionally, a framework has been developed to adopt BT successfully in the university libraries for the delivery of smart library services to library patrons.

The study was initiated to test the relationship of social media site addiction on librarians' performance. Furthermore, the study also tested the mediating role of task distraction and moderating role of effective self-control in aforesaid relationship.

This was an empirical study, and data for the research were collected through a standardized questionnaire from 503 librarians who were having Facebook accounts and are questionnaire developed through “Google Forms” and the link of the questionnaire was distributed using Facebook groups. Data was analyzed using descriptive analysis, correlation, Baron and Kenny's approach, and Normal Test Theory.

Results indicate that social media addiction is an important factor for that is reducing librarians' performance. At the same time task distraction also adds to negative impact of social media addiction on librarians' performance. However, effective self-control can reduce the negative impact of social media addiction on their performance.

This research has some important theoretical as well as practical implications for librarians, library management, and well as for policy makers and government.

Social media is commonly used for communication but when it becomes addiction, it can reduce the employees' performance. Most of existing researched focused on positive aspects of social media; only few researches explored the negative impacts of social media. The proposed relationship was never tested on librarians. This study filled this literature gap and proposed as well as empirically tested a model for evaluating negative impact of social media on librarians' performance.

The aim of this study is to investigate how green supply chain management (GSCM) practices mediate the effect of Industry 4.0 technologies on operational and green innovation performances.

To explore the study, data were collected from 225 different manufacturing industries in Pakistan. Gathered data were used to test the hypotheses using SmartPLS 3 software by using structural equation modeling.

The findings reveal that operational and green innovation performances are directly affected by the adoption of Industry 4.0 technologies and GSCM practices. Furthermore, the GSCM practices positively affect operational and green innovation performances. The study also investigated that the GSCM practices partially mediate the effect of Industry 4.0 on operational and green innovation performances.

This study has some limitations, the data of this study were majorly collected from large enterprises of Pakistani firms and related to the manufacturing sector only. So, there is a huge need for attention toward small and medium-sized enterprises (SMEs). Very few researchers are focusing on SMEs, so future research can be on SMEs. It can be suggested that the relationship between digital technologies and green innovation performance can be tested through a quantitative procedure. Moreover, the effect of GSCM's aspects can be estimated on manageable execution.

Through the mediating relationship of GSCM practices, this research has made a unique contribution by investigating the influence of Industry 4.0 on operational and green innovation performances. To the author's knowledge, no research has been undertaken in this area.

This study aims to assess the impact of participation in self-help group (SHG) on the psychological empowerment of rural tribal women.

Primary data was collected using multistage random sampling from the rural women of Jharkhand, India. The propensity score matching method was adopted using the psmatch2 command in STATA.

The results show a significant positive change in women’s self-esteem, self-confidence, self-efficacy, autonomy, knowledge and skills, reduction in agony and quality of life after participation in SHG. This reveals that participation in SHG has a significant positive impact on the psychological empowerment of rural tribal women.

Despite the numerous studies on rural women’s empowerment, there is little evidence of literature focusing on the impact of participation in SHG on psychological empowerment, specifically in the tribal context. This study primarily focuses on women belonging to the scheduled tribe category of Jharkhand, one of the poorest states of India.

This study aims to offer a hybrid stand-alone system for electric vehicle (EV) charging stations (CS), an emerging power scheme due to the availability of renewable and environment-friendly energy sources. This paper presents the analysis of a photovoltaic (PV) with an adaptive neuro-fuzzy inference system (ANFIS) algorithm, solid oxide fuel cell (SOFC) and a battery storage scheme incorporated for EV CS in a stand-alone mode. In previous studies, either the hydrogen fuel of SOFC or the irradiance is controlled using artificial neural network. These parameters are not controlled simultaneously using an ANFIS-based approach. The ANFIS-based stand-alone hybrid system controlling both the fuel flow of SOFC and the irradiance of PV is discussed in this paper.

The ANFIS algorithm provides an efficient estimation of maximum power (MP) to the nonlinear voltage–current characteristics of a PV, integrated with a direct current–direct current (DC–DC) converter to boost output voltage up to 400 V. The issue of fuel starvation in SOFC due to load transients is also mitigated using an ANFIS-based fuel flow regulator, which robustly provides fuel, i.e. hydrogen per necessity. Furthermore, to ensure uninterrupted power to the CS, PV is integrated with a SOFC array, and a battery storage bank is used as a backup in the current scenario. A power management system efficiently shares power among the aforesaid sources.

A comprehensive simulation test bed for a stand-alone power system (PV cells and SOFC) is developed in MATLAB/Simulink. The adaptability and robustness of the proposed control paradigm are investigated through simulation results in a stand-alone hybrid power system test bed.

The simulation results confirm the effectiveness of the ANFIS algorithm in a stand-alone hybrid power system scheme.

The purpose of this study is to investigate the relationship between sustainable leadership and sustainable project performance. Specifically, the study aims to examine the mediating role of knowledge integration, examining how knowledge integration within an organization influences project outcomes. In addition, the study seeks to explore the moderating role of top management knowledge values, examining how the values and beliefs of top management influence the relationship between sustainable leadership and project performance.

A three-wave survey of 392 employees working in construction sector projects in Pakistan used both hierarchical regression analysis and Hayes’ PROCESS macro method to evaluate the hypotheses.

The study results show that sustainable leadership positively relates to sustainable project performance and knowledge integration mediating this relationship. In addition, the top management knowledge value moderates the indirect effect of sustainable leadership on sustainable project performance via knowledge integration.

Although the model was tested using three-wave data, it is important to note that the data were obtained from a single source. Therefore, it is possible that common method bias may have influenced the results, and this cannot be disregarded.

Organizations seek to prioritize sustainability and integrate sustainability considerations into their project management processes. Organizations can achieve improved sustainable project performance by investing in sustainable leadership development, fostering a culture of knowledge sharing and learning, prioritizing top management support for sustainable performance and integrating sustainable considerations into project management processes.

The study’s grounding on organizational learning theory adds an original and valuable perspective to the relationship between sustainable leadership and sustainable project performance. This investigation is original, as it combines sustainable leadership, knowledge integration and the moderating role of top management knowledge value to understand their impact on sustainable project performance. This unique approach contributes to the literature by providing new insights into these relationships and mechanisms in the construction industry.

The evolution from emerging technologies to smart libraries is thoroughly analyzed thematically and bibliometrically in this research study, spanning 2013 through 2022. Finding and analyzing the significant changes, patterns and trends in the subject as they are represented in academic papers is the goal of this research.

Using bibliometric methodologies, this study gathered and examined a large corpus of research papers, conference papers and related material from several academic databases.

Starting with Artificial Intelligence (AI), the Internet of Things (IoT), Big Data (BD), Augmentation Reality/Virtual Reality and Blockchain Technology (BT), the study discusses the advent of new technologies and their effects on libraries. Using bibliometric analysis, this study looks at the evolution of publications over time, the geographic distribution of research and the most active institutions and writers in the area. A thematic analysis is also carried out to pinpoint the critical areas of study and trends in emerging technologies and smart libraries. Some emerging themes are information retrieval, personalized recommendations, intelligent data analytics, connected library spaces, real-time information access, augmented reality/virtual reality applications in libraries and strategies, digital literacy and inclusivity.

This study offers a thorough overview of the research environment by combining bibliometric and thematic analysis, illustrating the development of theories and concepts during the last ten years. The results of this study helps in understanding the trends and future research directions in emerging technologies and smart libraries. This study is an excellent source of information for academics, practitioners and policymakers involved in developing and applying cutting-edge technology in library environments.

The primary aim of this study is to examine the decision-making process of a reverse supply chain within a cooperative-competitive environment, with a particular emphasis on the incorporation of Internet of Things (IoT) technology in the recycling process.

The impact of IoT on recycling effectiveness, RF (refurbished) product demand and remanufacturing expenses is analyzed. The game-theoretic models are constructed to incorporate the co-competitive relationship between a IR (Internet Recycler) and a remanufacturer, with specific attention paid to the IR's application of IoT technology.

The results indicate that the use of IoT reduces the costs associated with remanufacturing, leading to an increase in the transfer price of pre-owned items procured from IRs. The efficacy of the reverse supply chain depends not only on its cost-saving capabilities but also on consumer preferences toward RF and remanufactured (RM) items.

IoT technology can benefit Internet recycling and remanufacturing by enhancing transparency, quality monitoring and automation of processes. It can also help reduce operating costs, improve customer engagement and incentivize cooperation between organizations.

This study examined the strategic decision-making processes in the context of cooperation and competition between IR and remanufacturers. In addition, this research makes a valuable contribution to the literature by elucidating the optimal conditions for the effective implementation of Internet of Things (IoT) technology in recycling operations.

Recently, interest in sustainability has grown globally in the heavy vehicle and equipment industry (HVEI). However, this industry's complexity poses a challenge to the implementation of generic sustainable supply chain management (SSCM) practices. This study aims to identify SSCM's barriers, practices and performance (BPP) indicators in the HVEI context.

The results are derived from case studies of four multinational manufacturers. Within-case and cross-case analyses were conducted to categorise the SSCM BPP indicators that are unique to HVEI supply chains.

This study's analysis revealed that supply chain cost implications and a deficient information flow between focal firms and supply chain partners are the key barriers to SSCM in the HVEI. This analysis also revealed a set of policies, programmes and procedures that manufacturers have adopted to address SSCM barriers. The most common SSCM performance indicators included eco-portfolio sales to assess economic performance, health and safety indicators for social sustainability and carbon- and energy-related measures for environmental sustainability.

The insights can help HVEI firms understand and overcome the typical SSCM barriers in their industry and develop, deploy and optimise their SSCM strategies and practices. Managers can use this knowledge to identify appropriate mechanisms with which to accelerate their transition into a sustainable business and effectively measure performance outcomes.

The extant SSCM literature has focused on the light vehicle industry, and it has lacked a concrete examination of HVEI supply chains' sustainability BPP. This study develops a framework that simultaneously analyses SSCM BPP in the HVEI.