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Despite the fact that hygiene and sanitation are becoming more critical for improving the present situation in developing nations, the factors that affect them are not well covered in the present research. This paper investigates the quality of the hygiene and sanitization factors and identifies the interrelations between the identified factors.

A graph theory-based approach is proposed to assess the factors influencing the practice, and a critical service index (CSI) is used to quantify the same.

Two Indian villages are used to illustrate the implementation of the suggested approach. This represents the validation of the suggested method, as well as assisting in the development of essential suggestions for increasing the quality of hygiene and sanitization in the Indian context. In spite of the increasing importance of hygiene and sanitation for improving the current situation in developing countries, the factors that influence them are not well-researched.

This study contributes in two ways. First, it provides an organized methodology for quantifying hygiene and sanitation factors and a critical service index that incorporates the findings. The suggested approach may also be used to evaluate and classify other sectors. Second, it shows how the methodology was used to create key recommendations for two Indian villages, which may be considered the first effort in India’s hygiene and sanitation initiatives.

This research discussed improvements in sanitation and hygiene habits among Indian households, which have not been achieved as expected under the Swachh Bharat Mission.

This paper aims to investigate the firm performance of micro, small and medium enterprises (MSMEs) by using artificial intelligence-based supply chain resilience strategies. A theoretical framework shows the relationship between artificial intelligence, supply chain resilience strategy and firm performance.

A questionnaire is developed to survey the MSMEs of India. A sample size of 307 is considered for the survey. The employees working in MSMEs are targeted responses. The conceptual model developed is tested empirically.

The study found that eight hypotheses were accepted and two were rejected. There are five mediating variables in the current study. Artificial intelligence, the independent variable, positively affects all five mediators. Then, according to the survey and analysis of the final 307 responses from MSMEs, the mediating variables significantly impact the dependent variable, firm performance.

This study is limited to emerging markets only. Also this study used only cross sectional data collection methods.

This study is essential for supply chain managers and top management willing to adopt the latest technology in their organisation or firmfor a better efficient supply chain process.

This study investigated artificial intelligence-based supply chain resilience for improving firm performance in emerging countries like India. This study tried to fill the research gap in artificial intelligence and supply chain resilience.

The waste-to-energy (WtE) project plays a significant role in the sustainable development of urban environments. However, the inherent “Not in my backyard” (NIMBY) effect presents substantial challenges to site selection decisions. While effective public participation is recognized as a potential solution, research on incorporating it into site selection decision-making frameworks remains limited. This paper aims to establish a multi-attribute group decision-making framework for WtE project site selection that considers public participation to enhance public satisfaction and ensure project success.

Firstly, based on consideration of public demand, a WtE project site selection decision indicator system was constructed from five dimensions: natural, economic, social, environmental and other supporting conditions. Next, the Combination Ordered Weighted Averaging (C-OWA) operator and game theory were applied to integrate the indicator weight preferences of experts and the public. Additionally, an interactive, dynamic decision-making mechanism was established to address the heterogeneity among decision-making groups and determine decision-maker weights. Finally, in an intuitive fuzzy environment, an “acronym in Portuguese of interactive and multi-criteria decision-making” (TODIM) method was used to aggregate decision information and evaluate the pros and cons of different options.

This study develops a four-stage multi-attribute group decision-making framework that incorporates public participation and has been successfully applied in a case study. The results demonstrate that the framework effectively handles complex decision-making scenarios involving public participation and ranks potential WtE project sites. It can promote the integration of expert and public decision-making preferences in the site selection of WtE projects to improve the effectiveness of decision-making. In addition, sensitivity and comparative analyses confirm the framework’s feasibility and scientificity.

This paper provides a new research perspective for the WtE project site selection decision-making, which is beneficial for public participation to play a positive role in decision-making. It also offers a valuable reference for managers seeking to effectively implement public participation mechanisms.

The purpose of this study is to delve into the intricate terrain of assimilating sustainability practices into digital accounting and finance, centring on the transformative dynamics introduced by artificial intelligence (AI)-enabled FinTech. The primary objective is to scrutinize critical lacunae in existing literature, exploring how organizations can meticulously construct comprehensive sustainability frameworks. Simultaneously, the study investigates the protracted repercussions of AI-enabled FinTech on the enduring sustainability paradigms.

Executing a systematic literature review, the research engaged in the meticulous identification and assessment of a voluminous pool of 1,158 articles. Using a judicious two-phase strategy, the scrutiny distilled a mere 64 pertinent articles, subjecting them to rigorous evaluation encompassing methodologies, contributions and overall quality. The Fuzzy Delphi method was used to elicit expert opinions and facilitate consensus-building, leveraging fuzzy logic to accommodate uncertainties in the data.

The review navigates the convoluted impact of AI across diverse sectors, accentuating its transformative imprint on realms such as health care, finance and transportation. Specifically, in the financial domain, the discerning eye of AI-enabled FinTech optimizes investment portfolios, augments risk assessment, propels financial inclusion and streamlines the intricate landscape of sustainability reporting. The study meticulously pinpoints research gaps encompassing investment optimization, risk management, financial inclusion, sustainability reporting and ethical considerations within the intricate milieu of AI-enabled FinTech. This research contributes to the existing body of knowledge by synthesizing intricate thematic strands, discerning overarching trends and spotlighting critical voids in the synthesis of sustainability practices and AI-enabled FinTech. The findings resonate with far-reaching implications, emphasizing the exigency of comprehensive investigations into the longitudinal sustainability ramifications instigated by AI-enabled FinTech.

The study underscores the imperative of crafting robust ethical frameworks for the equitable and transparent deployment of AI solutions within the intricate landscape of FinTech. Moreover, this research stands poised to shape organizational strategies, inform regulatory frameworks and guide investment decisions, thereby catalyzing the cultivation of conscientious and sustainable financial practices.

This paper aims to provide empirical evidence on adopting artificial intelligence (AI), including generative AI, in knowledge management (KM) processes and its impact on organisational decision-making. Specifically, the study addresses three key research questions: RQ1: How is (generative) AI adopted within KM processes in organisations? RQ2: What factors influence the adoption of AI in these processes, either facilitating or inhibiting it? RQ3: How does AI adoption in KM processes affect organisational decision-making?

An explorative investigation has been conducted through semi-structured interviews with KM and AI experts from a worldwide sample of 52 mostly private, large and for-profit organisations. Interviews have been analysed through a mixed thematic analysis.

The study provides an original framework in which the three investigated concepts are interconnected according to a dual relationship: linear and retroactive and 20 factors affecting AI adoption within KM processes.

The provided model guides managers in improving their organisational decision-making through AI adoption in KM processes. Moreover, according to the rational decision-making model, the authors propose a six-step systematic procedure for managers.

To the best of the authors’ knowledge, this is the first study that simultaneously addresses AI, KM and decision-making and provides an integrated framework showing the relationships between them, allowing organisations to better and practically understand how to ameliorate their decision-making through AI adoption in KM processes.

This study aims to investigate the evolution of terminology in supply chain management (SCM) and its implications for the field’s strategic orientation. It also aims to understand how SCM terms adapt to interdisciplinary contexts, reflecting shifts in theoretical and practical approaches within the discipline.

This study uses a systematic literature review and analyzes over 3,500 unique SCM-related terms extracted from approximately 33,000 abstracts. By using Descending Hierarchical Classification and factor analysis, the research methodologically identifies key shifts in terminology and discerns underlying patterns.

This study categorizes terminological variations in SCM into three main clusters: product–agent, performance objective orientation and structure. These variations signal not only linguistic changes but also strategic shifts in SCM understanding and practice. Notably, terms such as “green,” “sustainable” and “circular” supply chains have emerged in response to evolving internal and external pressures and trends. In addition, this paper offers a nuanced understanding of these terminological adaptations, proposing a reference framework for navigating SCM’s evolving lexicon and highlighting global usage and geographical and cultural nuances in SCM discourse.

This paper presents a reference framework that complements existing SCM definitions, fostering a shared understanding of SCM variations on a global scale. This framework enhances cultural sensitivity within the field and underscores SCM’s adaptability and flexibility. These insights offer a nuanced view of SCM dynamics, benefiting researchers and practitioners alike. Beyond terminology, this study sheds light on the interplay between language and SCM strategy, providing a valuable perspective for navigating the evolving SCM landscape. The study’s scope is constrained by the analyzed abstracts. Future research could broaden this analysis to encompass more SCM literature or delve deeper into the implications of terminological changes.

This study offers practitioners a reference framework for navigating the evolving lexicon of SCM. This framework aids in understanding the strategic implications of terminological changes, enhancing clarity and context in both academic and practical applications.

By acknowledging global usage and variations, the research underscores the impact of geographical and cultural nuances on SCM discourse. This global perspective enriches the understanding of SCM as a dynamic and culturally sensitive field.

This research is novel in its extensive and systematic exploration of SCM terminology. This study offers a comprehensive analysis of how language evolves in tandem with strategic shifts in the field, providing a unique perspective on the interplay between terminology and strategy in SCM.

Despite the importance of green supply chain integration (GSCI) in advancing green innovation (GI) is recognized, it remains unclear how firms can translate their GSCI efforts into GI. Therefore, this study aims to understand how GSCI affects GI, with its dimensions (exploitative GI and exploratory GI), as well as to investigate the mediating role of green knowledge integration capability (GKIC) and the moderating role of blockchain technology (BCT) adoption.

On the basis of data collected from 247 managers working in Indian firms in the automotive industry, the authors tested the proposed model using the PROCESS macro tool via SPSS software.

The empirical results indicate that GSCI is positively associated with both exploitative and exploratory GI, with a higher effect on exploitative GI. In addition, GKIC mediates the link between GSCI and exploitative GI in contrast to exploratory GI. Notably, the relationship between GSCI and GKIC is stronger when BCT adoption is high.

This study opens the black box of how GSCI affects exploitative and exploratory GI by revealing the mediating role of GKIC and the moderating role of BCT adoption. It provides valuable insights for practitioners to translate GSCI efforts into GI through developing GKIC and adopting BCT.

This study aims to examine and discuss the importance and benefits of Open Innovation (OI), Transformational Leadership (TL), Innovation Strategy (IS), Creative Climate (CC), Radical Innovation (RI) and Sustainable Competitive Advantage (SCA) for small and medium-sized enterprises (SMEs) in Dubai. This work also examines the mediating impact of future foresight drivers (FFD) on SMEs' SCA. The study provides a theoretical framework for enhancing SMEs' organizational performance and highlights the need for future empirical research.

The study uses a systematic literature review (SLR) approach and a bibliometric analysis approach to collect, examine and analyze data from previous research on OI, TL, IS, CC, RI and SCA. This work evaluated 110 publications from separate scholarly databases, Scopus and Web of Science (WoS).

The study finds a positive relationship between OI, TL, IS, CC, RI and SCA and that future empirical research is needed. While there is limited information on the impact of these concepts on SMEs in the Middle East and especially in Dubai, the study presents new concepts to be debated. The study provides a vital tool for businesses to improve their performance by adopting OI, TL and IS and analyzing their present competitive status to develop new strategies and build competitiveness.

The originality of this study lies in its contribution to understanding the relationships among OI, TL, IS, CC and RI and their impact on SMEs' SCA in Dubai. By emphasizing the importance of OI, TL and IS in improving SMEs' performance and competitiveness, this study provides valuable insights for SME managers seeking to enhance their organizations' sustainability and long-term success. The review also identifies a gap in the literature regarding the impact of these concepts on SMEs in the Middle East, emphasizing the need for further research in this area.

Nowadays, the electricity supply chain is significant for most societies, so it is necessary to use new technologies such as blockchain in the electricity industry. This study aims to identify and prioritize the factors influencing the adoption of blockchain technology in the electricity supply chain of the US.

In this study, after reviewing the research literature, the influential factors of blockchain adoption in the electricity industry are identified and the consensus of the experts is reached. Experts have a thorough understanding of blockchain technology and the US electricity industry. Data is collected using a Step-Wise Weight Assessment Ratio Analysis (SWARA) questionnaire from November 2022 to July 2023. Using the SWARA questionnaire, experts compared 16 influential subcriteria of blockchain adoption. Then, using the Fuzzy SWARA method, the following influential subcriteria of blockchain adaptation in the US electricity industry are evaluated and prioritized.

The results show that the most significant subcriterion among the 16 influential subcriteria for the adoption of blockchain technology in the electricity supply chain is reducing cost, whereas the collaborating with supply chain partners subcriterion is recognized as the least important subcriterion.

The present study helps managers improve their knowledge to apply blockchain technology and also have the best performance for applying blockchain technology in the electricity supply chain.

Dietary diversity (DD) is a proxy indicator of nutrient adequacy and has been propagated as a health beneficial component of dietary behavior. This study aims to understand DD and its association with lipid indices among Indian Kho-Kho players.

In all, 50 Indian Kho-Kho players aged between 16 years and 31 years belonging to different regions of India were recruited. Dietary diversity score (DDS; food groups/day) and food variety score (FVS; number of food items/day) were considered to assess the DD. The United Nations Food and Agricultural Organization food frequency questionnaire was used as a tool. Serum total cholesterol (TC), triglycerides (TG), LDL, VLDL and HDL were measured.

The DDS and FVS showed that athletes were consuming approximately 7 of 9 food groups (Mean ± SD: 6.5 ± 1.3) and 27 varieties of foods (Mean ± SD:27.0 ± 8.6) from 9 food groups per day. This study could not find significant differences for DDS and FVS among athletes belonging to different regions. FVSs of organ meat, eggs and spices and condiments were significantly positively associated with TG (p < 0.036, p < 0.020 and p < 0.001) and VLDL (p < 0.054, p < 0.021 and p < 0.001). LDL was inversely significantly associated with FVS of cereals, white root and tubers (p < 0.032).

DDS and FVS were not associated with lipid indices among Kho-Kho players. However, individual FVS of organ meat, eggs and spices and condiments may increase TG and VLDL. Optimum consumption of cereals and root tubers may help to maintain LDL levels among Kho-Kho players.

It was found that daily consumption of organ meat and eggs may increase TG and VLDL, and optimum consumption of cereals and white roots and tubers may help to maintain LDL. High energy and fat foods may act as mediators along with spices and condiments in increasing TG and VLDL.