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Every company or manufacturing system is vulnerable to breakdowns. This research aims to analyze the role of Multi-Agent Technology (MAT) in minimizing breakdown probabilities in Manufacturing Industries.

This study formulated a framework of six factors and twenty-eight variables (explored in the literature). A hybrid approach of Multi-Criteria Decision-Making Technique (MCDM) was employed in the framework to prioritize, rank and establish interrelationships between factors and variables grouped under them.

The research findings reveal that the “Manufacturing Process” is the most essential factor, while “Integration Manufacturing with Maintenance” is highly impactful on the other factors to eliminate the flaws that may cause system breakdown. The findings of this study also provide a ranking order for variables to increase the performance of factors that will assist manufacturers in reducing maintenance efforts and enhancing process efficiency.

The ranking order developed in this study may assist manufacturers in reducing maintenance efforts and enhancing process efficiency. From the manufacturer’s perspective, this research presented MAT as a key aspect in dealing with the complexity of manufacturing operations in manufacturing organizations. This research may assist industrial management with insights into how they can lower the probability of breakdown, which will decrease expenditures, boost productivity and enhance overall efficiency.

This study is an original contribution to advancing MAT’s theory and empirical applications in manufacturing organizations to decrease breakdown probability.

This paper aims to evaluate the progress made in achieving sustainable development goal-2 (SDG 2) in India, with a focus on ending hunger, ensuring food security, improving nutrition and promoting sustainable agriculture. The assessment uses data from SDG Index reports, which offer a comprehensive overview of the advancements made by 28 states and 8 union territories (UTs) in India.

The evaluation is based on information derived from three editions of the SDG Index reports, initially published in 2018 and subsequently in 2019 and 2020. These reports provide a detailed analysis of the status and achievements of different states and UTs in relation to SDG 2. The categorization of states and UTs into aspirant, performer, front runner and achiever categories serves as a crucial framework for assessing the progress.

Despite concerted efforts by India, the majority of states and UTs are positioned in the aspirant and performer categories, suggesting that significant challenges persist in achieving SDG 2 targets. The results emphasize the necessity for stronger measures to elevate states and UTs to the categories of front-runners and achievers. The persistent challenges of malnutrition, hunger and their economic ramifications require immediate and strategic interventions to address these pressing concerns.

This paper contributes to the existing literature by providing a comprehensive analysis of the progress towards SDG 2 in India, using the insights from the SDG Index reports. The categorization framework used in this assessment offers a nuanced understanding of the challenges faced by different regions, highlighting the original contribution of this study. The findings underscore the urgency of targeted efforts to address malnutrition, hunger and related issues, emphasizing the importance of sustained commitment to achieving SDG 2 for the overall well-being of vulnerable populations.

The adoption of residential rooftop solar panel systems (SPS) in India is at a nascent stage. Therefore, this study aimed to examine the factors affecting consumers’ intention to purchase SPS by expanding the theory of planned behavior (TPB) with three environmental psychology factors. The study was targeted at potential users’ intention to purchase SPS, thus it further explored the moderating role of perceived government subsidy policy (PGSP) in determining consumers’ purchase intention of SPS.

Using G*power software, the minimum sample size of 189 was calculated; accordingly, 292 valid responses were gathered from potential users of SPS from three Indian states, namely Rajasthan, Punjab and Haryana, via an online questionnaire survey with the help of purposive sampling method. Structural equation modeling technique of partial least squares was employed to analyze the data.

Results demonstrated that attitude, subjective norms, perceived behavioral control, perceived consumer effectiveness (PCE) and PGSP significantly influence purchase intention of SPS. Green trust and green self-identity did not influence the purchase intention of SPS. Further, PGSP strengthens the effect of attitude, green trust, PCE on purchase intention of SPS while it weakens the effect of subjective norms on purchase intention of SPS.

This study contributes to the existing literature by integrating green trust, green self-identity, PCE and PGSP into the TPB model to better understand factors affecting consumers’ purchase intention towards SPS in India.

This study aims to evaluate the relationship of corporate social responsibility (CSR) reporting with the financial performance of firms using various market and accounting-based parameters in a developing economy, India.

The study uses content analysis to develop a CSR reporting index for the Indian firms listed on the Bombay Stock Exchange. The two-step system generalized methods of moments has been used for the estimation of the panel data.

The results from the study suggest that the CSR reporting-based activities of the firms may impact the financial performance of the firms, but at the same time, the need of the hour is to create awareness among the investors and market players so that they realize the relevance of CSR reporting, which can further improve other dimensions of financial performance as well.

The study relies on Tobin’s Q and return on assets while measuring financial performance, though there are various other parameters that can be used to gauge the performance. The outcomes of this study have practical implications for the practitioners as well as policymakers, incentivizing them to integrate CSR aspects into their decision-making frameworks.

To the best of the authors’ knowledge, this is the first Indian study to develop a unique index for CSR reporting and linking it with financial performance. This study shall assist the researchers in broadening the scope of CSR studies in India and can be used to draw a systematic comparison with developed nations.

Supply chain management (SCM)-embedded valuable resources, such as capital, raw-materials, products, partners, customers and finished inventories, where the evaluation of environmental texture and flexibilities are needed to perceive sustainability. The present study aims to identify and evaluate the directory of green and agile (G-A) attributes based on decision support framework (DSF) for identifying dominating measures in SCM.

DSF is developed by exploiting generalized interval valued trapezoidal fuzzy numbers (GIVTFNs). Two technical approaches, i.e. degree of similarity approach (DSA) and distance approach (DA) under the extent boundaries of GIVTFNs, are implicated for data analytics and for recognizing constructive G-A measures based on comparative study for robust decision. A fuzzy-based performance indicator, i.e. fuzzy performance important index (FPII), is presented to enumerate the weak and strong G-A characteristics to manage knowledge risks in allied business environment.

The modeling is illustrated from the insights of decision-makers for augmenting business value based on cognitive identification of measures, where the best performance score is identified by the “sustainable packaging” under the traits of green supply chain management (GSCM). “The use of Web-based applications” under the traits of agile supply chain management (ASCM) and “Outsourcing flexibility” under traits of ASCM is found as the second and third most significant performance characteristics for business sustainability. Additionally, the “Reutilization (recycling) and reprocessing” under GSCM in manufacturing and “Responsiveness and speed toward customers needs” under ASCM are found difficult in attainment.

The G-A evaluation will assist in attaining performance excellence in day-to-day operations and overall functioning. The outcomes will help executives to plan strategic objectives and attaining success.

To reinforce the capabilities of SCM, wide extent of G-A dimensions are presented, concept of FPII is reported to manage knowledge risks based on identification of strong attributes and two technical approaches, i.e. DSA and DA under GIVTFNs are presented for attaining robust decision and directing managerial decision-making process.

The set of 2,509 documents related to the human-centric aspect of manufacturing were retrieved from Scopus database and systmatically analyzed. Using an unsupervised machine learning approach based on Latent Dirichlet Allocation we were able to identify latent topics related to human-centric aspect of Industry 5.0.

This study aims to create a scientific map of the human-centric aspect of manufacturing and thus provide a systematic framework for further research development of Industry 5.0.

In this study a 140 unique research topics were identified, 19 of which had sufficient research impact and research interest so that we could mark them as the most significant. In addition to the most significant topics, this study contains a detailed analysis of their development and points out their connections.

Industry 5.0 has three pillars – human-centric, sustainable, and resilient. The sustainable and resilient aspect of manufacturing has been the subject of many studies in the past. The human-centric aspect of such a systematic description and deep analysis of latent topics is currently just passing through.