Growing awareness about environmental responsibility among businesses and policymakers has increased interest in Green Supply Chain Management (GSCM). For the first time, using the SDG mapping algorithms, this article focused on 7009 publications from 2013 to 2022 mapped explicitly to 17 SDGs. This study uses bibliometric and science mapping techniques to create a detailed mapping between GSCM research and SDGs. This study created an SDG citation network to show how specific SDGs are related to GSCM practices. The most mapped SDGs in this study are SDG 9 (Industry, Innovation, and Infrastructure), SDG 12 (Responsible Consumption and Production), and SDG 17 (Partnership for the Goals). Our results showed that GSCM research mainly focuses on three thematic areas: industry 4.0 and sustainable supply chains, GSCM practice coordination, and sustainable environmental policy management. This also includes integrating the circular economy into GSCM, sustainable sourcing, supply chain resilience, digital transformation in GSCM for better environmental performance, and the social impact of GSCM. A shift towards integrating sustainability into supply chain processes has been found. Environmental management, performance monitoring, and new technologies like Industry 4.0 and AI have been used to support the SDGs. International interest and collaboration in GSCM research can be seen from the bibliographic coupling study covering countries like Europe, Western Countries, the Middle East, Southeast Asia, and Eastern Europe. This study shows how GSCM can directly address global challenges identified by the United Nations by mapping GSCM research to specific SDGs.

The drive to achieve the Sustainable Development Goals (SDGs) becomes more urgent as the 2030 deadline draws near, increasing research in various sectors. Nevertheless, studies that systematically map Analytical Hierarchy Process (AHP) publications with the SDGs need to be more conspicuously lacking. Our study adds a new perspective to the field by creatively bridging this knowledge gap using the Elsevier SDG Mapping Initiative. To find research clusters, trends, and themes linked to SDGs and their connection to environmental sustainability, we thoroughly analyzed 29,897 publications from 2012 to 2022. The analysis showed that SDG 15, SDG 7, SDG 12, SDG 13, and SDG 11 were the top five SDGs, with an environmental focus among the 17 SDGs. These top SDGs had many clusters connected to them, illustrating various sustainability-related problems. The study also looked at connections between SDGs, the nations with the highest rates of productivity, the top contributors, and the journals with the highest citation counts. We discovered three separate SDG clusters using co-occurrence network analysis, each representing a different SDG. We discovered relevant SDGs using Matrice d'impacts croisés multiplication appliquée á un classment (MICMAC) analysis and centrality indicators like eigenvector and betweenness. This novel method for publishing analysis combines an AHP focus that aligns with the SDGs with social network analysis and centrality metrics. Our research advances knowledge of how the AHP technique can assess initiatives supporting the SDGs. We offer essential insights into prioritizing sustainable development measures by identifying research clusters, trends, and issues related to environmental sustainability. This study highlights the subject's most important SDGs, productive nations, helpful organizations, and significant journals.

Purpose: Resilience, the ability of start-ups to deal with anticipated instabilities and probable disruptions, is becoming an important success element during coronavirus disease 2019 (Covid-19). To survive in this pandemic situation, resilience is an important concept for start-ups. The present paper aims to “identify”, “analyse” and “categorize” the resilience factors for start-ups during the Covid-19 pandemic using total interpretive structural modelling (TISM). Design/methodology/approach: The resilience elements of start-ups during Covid-19 were identified and shortlisted during the first phase, which included literature analysis and extensive interaction with experts. TISM was used in the second phase to investigate or to determine how the factors interplayed between the resilience factors of start-ups during Covid-19. The Matrice d'impacts Croises Multiplication Appliquee a un Classment (MICMAC) method is used to rank and categorize the factors. Closed-ended questionnaire with the scheduled interview was conducted to collect the data. Findings: The first part of the study found ten resilience elements in total. The TISM digraph was constructed in the second step to show why one resilience component led to another. The MICMAC analysis divided these factors into four groups: autonomous, linkage, dependent and independent. These groups represented resilience variables based on their driving and dependent power, which assist executives and managers in proactively addressing them while using the TISM digraph as a guide. Research limitations/implications: During the Covid-19 epidemic, this study focused primarily on resilience characteristics for Indian start-ups. Practical implications: This study will help key stakeholders and scholars to better understand the elements that contribute to start-up's resilience. Originality/value: The TISM method for start-up's resilience is suggested in this paper, which is a novel attempt in the field of resilience in this industry.

Interpretive structural modeling (ISM) is widely used to understand the complex connections between different components. This study presents a bibliometric overview of ISM research, with a focus on its linkages to the Sustainable Development Goals (SDGs) and the impact of COVID-19. The study analyzed 1988 publications on ISM published between 2012 and 2021, of which 1202 were directly mapped to the SDGs and 59 were related to COVID-19. The study identified key authors, institutions, countries, and journals involved in the research and their linkages to the SDGs. The results showed that ISM research is strongly linked to SDG 12 (on responsible consumption and production) and SDG 9 (on industry, innovation, and infrastructure). We also identified influential SDGs on the basis of centrality measures such as betweenness and eigenvector. The top four countries contributing to ISM publications were India, China, the United Kingdom, and the United States. The most frequently cited journals were Benchmarking: An International Journal, Sustainability, the Journal of Modelling in Management, and the Journal of Cleaner Production. Four main clusters were identified in the ISM research, including (1) integration with AHP and fuzzy logic for promoting sustainability alignment, (2) ISM-based strategy development for various stakeholders, (3) ISM-based decision-making in various fields, and (4) ISM-based risk evaluation. For the first time, studies that used the ISM approach to understand the epidemiological characteristics of COVID-19 were identified, and their key findings were discussed. The study also identified several emerging topics for future ISM research, such as blockchain and IoT, environmental management systems, climate change adaptation, smart cities, and humanitarian logistics and their potential linkages to the SDGs.

The study highlights the impact of cloud-native technology in entrepreneurship for innovative business models, scalability, and cost efficiency by combining the trends including microservices, serverless computing, and technology disruptions. The study attempts to examine the role of cloud-native technology affects the entrepreneurial landscape in creating and advancing innovative business models and approaches, and the difficulties while applying cloud-native technology. The systematic literature review based on PRISMA is used to explore cloud-native technology and its applications by analyzing selected 111 studies from Scopus, Web of Science, Dimensions, and ProQuest. The study identified that one of the main forces behind disruption is the quick development of new technologies including blockchain, 5G, IoT, quantum computing, and AI. Cloud-native technology supports innovative business models in entrepreneurship such as SaaS, serverless computing, managed Kubernetes, data analytics platforms, BaaS, and Edge Computing. The urgency to incorporate and develop new security features and tools for measurement is necessary. The study shows that startups can use cloud-native technologies for innovative business models that rely on serverless computing, subscription services, and on-demand cloud services which are providing opportunities. The findings of the study highlight the need for entrepreneurs to utilize emerging technologies to meet competition, and there is a requirement for continuous investment in data analytics, automation, cloud solutions, and emerging technologies. Collaboration is essential for the application of the technologies for early stage startups and enterprises. Incubators, accelerators, and venture capital firms support essential to the adoption of disruptive technologies. The policymaker's and enterprises' focus and actionable intervention are necessary for developing mechanisms to solve the barriers of regulatory compliance, lack of skilled manpower, data security, privacy issues, and upfront investment for entrepreneurial success.