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This study aims to examine the association between mandatory corporate social responsibility (CSR) regulations (CSR mandate) and social disclosures (SOCDS) in India. It also investigates whether CSR committees mediate the relationship between CSR mandate and SOCDS. Furthermore, this paper explores how business group (BG) affiliation moderates CSR committee quality and SOCDS.

This study uses a data set of 5,345 observations from the Bombay stock exchange (BSE)-listed firms over 10 years (2011–2020) to examine the research questions. Baron and Kenny’s (1986) three-step model is estimated to examine the mediating role of CSR committees on the relationship between CSR mandate and SOCDS.

The study reveals that the CSR mandate positively impacts SOCDS in India due to coercive pressures. CSR committees mediate this relationship, with higher CSR committee quality leading to increased SOCDS. Furthermore, the authors report that SOCDS in India is positively related to CSR committee quality, and this relationship is stronger for BG firms. Finally, the supplementary analysis reveals that promoting CSR committee quality enhances firms’ likelihood of meeting CSR mandatory spending and actual CSR spending in India.

This research contributes to the academic literature by shedding light on the intricate dynamics of CSR mandates, CSR committees and SOCDS in emerging economies. Notably, the authors identify the previously unexplored mediation role of CSR committees in the link between CSR mandates and SOCDS. The creation of a composite index that measures complementary CSR committee attributes allows us to undertake a novel assessment of CSR committee quality. An examination of the moderating influence of BG affiliation documents the importance of CSR committee quality, particularly in governance, for enhancing SOCDS transparency within BG firms.

Identifying and prioritizing supply chain risk is significant from any product’s quality and reliability perspective. Under an input-process-output workflow, conventional risk prioritization uses a risk priority number (RPN) aligned to the risk analysis. Imprecise information coupled with a lack of dealing with hesitancy margins enlarges the scope, leading to improper assessment of risks. This significantly affects monitoring quality and performance. Against the backdrop, a methodology that identifies and prioritizes the operational supply chain risk factors signifies better risk assessment.

The study proposes a multi-criteria model for risk prioritization involving multiple decision-makers (DMs). The methodology offers a robust, hybrid system based on the Intuitionistic Fuzzy (IF) Set merged with the “Technique for Order Performance by Similarity to Ideal Solution.” The nature of the model is robust. The same is shown by applying fuzzy concepts under multi-criteria decision-making (MCDM) to prioritize the identified business risks for better assessment.

The proposed IF Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) for risk prioritization model can improve the decisions within organizations that make up the chains, thus guaranteeing a “better quality in risk management.” Establishing an efficient representation of uncertain information related to traditional failure mode and effects analysis (FMEA) treatment involving multiple DMs means identifying potential risks in advance and providing better supply chain control.

In a company’s supply chain, blockchain allows data storage and transparent transmission of flows with traceability, privacy, security and transparency (Roy et al., 2022). They asserted that blockchain technology has great potential for traceability. Since risk assessment in supply chain operations can be treated as a traceability problem, further research is needed to use blockchain technologies. Lastly, issues like risk will be better assessed if predicted well; further research demands the suitability of applying predictive analysis on risk.

The study proposes a hybrid framework based on the generic risk assessment and MCDM methodologies under a fuzzy environment system. By this, the authors try to address the supply chain risk assessment and mitigation framework better than the conventional one. To the best of their knowledge, no study is found in existing literature attempting to explore the efficacy of the proposed hybrid approach over the traditional RPN system in prime sectors like steel (with production planning data). The validation experiment indicates the effectiveness of the results obtained from the proposed IF TOPSIS Approach to Risk Prioritization methodology is more practical and resembles the actual scenario compared to those obtained using the traditional RPN system (Kim et al., 2018; Kumar et al., 2018).

This study provides mathematical models to simulate the supply chain risk assessment, thus helping the manufacturer rank the risk level. In the end, the authors apply this model in a big-sized organization to validate its accuracy. The authors validate the proposed approach to an integrated steel plant impacting the production planning process. The model’s outcome substantially adds value to the current risk assessment and prioritization, significantly affecting better risk management quality.

This study examined the impact of the Glasgow Climate Pact on the abnormal returns of global clean energy stocks. Further, this study examines which country-specific and firm-specific variables drive the cumulative abnormal returns (CARs) of clean energy stocks.

The authors used the event study method and cross-sectional multivariate regression model. The clean energy stocks in this study are limited to 81 constituent firms of the S&P Global Clean Energy Index across 17 nations. The final sample includes 80 firms and the sample period ranges from January 26, 2021, to December 07, 2021.

The study finds that the Glasgow Climate Pact negatively affects the stock returns of clean energy firms. Moreover, the climate change performance index (CCPI) positively impacts cumulative abnormal returns (CARs), signifying that clean energy investors react positively to firms in nations with good CCPI scores. The environmental, social and governance (ESG) measure for the shorter window (−1, +1) exhibited a negative relationship with CARs. The firm-specific variables (BTM, stock liquidity, size and past returns) exhibit a negative relationship with CARs in different event windows.

The authors use the CCPI as a proxy for the stringency of environmental policies in any nation. The authors extend the existing literature by employing firm-specific variables and supporting previous findings. Their findings have policy implications for clean energy investors, policymakers and other market participants.

Climate risks impact the global financial market, so the findings have implications for global regulatory bodies. Currently, there are bankruptcy cases due to climate risks. Because financial markets must play a critical role in shifting the economy toward a green one, regulators can use the cross-sectional drivers of this study to shape policy. It is also critical for regulators to reduce stock price volatility in the event of the implementation of environmental regulations and improve environmental disclosures by publicly traded companies. Furthermore, governments are interested in researching the effects of environmental regulations to protect stakeholders' interests. These regulations significantly impact emerging markets because they lack the same solid institutional frameworks as developed markets.

The authors provide evidence that firms with better ESG scores and larger firm sizes have experienced fewer abnormal returns, as these firms have stable financial and non-financial fundamentals. This timely study on the ongoing regulatory shift in environmental policy will help investors, policymakers, firms and other stakeholders make relevant decisions.

Industry 4.0 has received significant attention in today's competitive business market, necessitating a restructuring of functional domains in nearly every manufacturing organization. A comprehensive strategy to improve performance in preparation for Industry 4.0 implementation necessitates several steps, one of which is the establishment of performance outcomes (POs). The aim of this paper is to identify and rank the POs realized due to the adoption of Industry 4.0 enablers.

Based on an extensive literature review and inputs received from experts, a comprehensive list of enablers and the POs was prepared and finalized. This paper proposes a framework based on hybrid solution methodology, namely Neutrosophic Analytical Hierarchy Process (N-AHP) and Neutrosophic Combined Compromise Solution (N-CoCoSo), to rank the POs realized due to the adoption of Industry 4.0 enablers. The N-AHP methodology has been adopted to calculate the relative weights of the Industry 4.0 enablers. In comparison, the N-CoCoSo method has been adopted to rank the POs of Industry 4.0.

The proposed framework is applied to an Indian manufacturing organization to test the organization's practical applicability. Additionally, sensitivity analysis is also carried out to check the steadiness of the proposed framework. The findings of this study revealed that “Improved responsiveness to market conditions in today's competitive business environment” is the top-ranked PO of Industry 4.0, followed by “Enhanced competitiveness and better market share”, “Better product quality, through smart management of production process” and “Reduction in manufacturing waste and environmental sustainability” which could be realized due to adoption of its enablers.

This research would aid practitioners by enhancing the practitioners' capacity to understand and prioritize the various POs resulting from implementing Industry 4.0 enablers. Embracing a clear strategic plan will further assist practitioners in improving the efficiency of Industry 4.0 implementation.

Previous literature has only addressed the relationship between Industry 4.0 enablers and POs in a limited way. This paper attempts to compile a comprehensive list of Industry 4.0 enablers relevant to manufacturing organizations in order to fill this knowledge and research gap.

The study aims to examine the impact of six events related to the escalating Indo-China border conflicts in 2020 on the Indian stock market, including the role of firm-specific variables.

This study employs an event-study method on a sample of 481 firms from August 23, 2019 to March 3, 2022. A cross-sectional regression is employed to examine the association between event-led abnormal returns and firm characteristics.

The results show that, although the individual events reflect heterogeneous effects on stock market returns, the average impact of the event categories is negative. The study also found that net working capital, current ratio, financial leverage and operating cash flows are significant financial performance indicators and drive cumulative abnormal returns. Further, size anomaly is absent, indicating that more prominent firms are resilient to new information.

The ongoing conflict between Russia and Ukraine is an example of how these disagreements can devolve into a disaster for the parties to the war. Although wars have an impact on markets at the global level, the impacts of border disputes are local. Border disputes are ongoing, and the study's findings can be used to empower investors to make risk-averting decisions that make their portfolios resilient to such events.

This study provides firm-level insight into the impacts of border conflicts on stock markets. The authors compare the magnitude of such impacts on two types of events, namely injuries and casualties due to country-specific border tensions and a government ban on Chinese apps. Key implications for policymakers, stakeholders and academics are presented.

This paper aims to investigate the influence of “BroncoCut-X” (copper core-ZnCu50 coating) electrode on the machining of Ti-3Al-2.5V in view of its extensive use in aerospace and medical applications. The machining parameters are selected as Spark-off Time (ST_off), Spark-on Time (ST_on), Wire-speed (S_w), Wire-Tension (WT) and Servo-Voltage (S_v) to explore the machining outcomes. The response characteristics are measured in terms of material removal rate (MRR), average kerf width (KW) and average-surface roughness (SA).

Taguchi’s approach is used to design the experiment. The “AC Progress V2 high precision CNC-WEDM” is used to conduct the experiments with ϕ 0.25 mm diameter wire electrode. The machining performance characteristics are examined using main effect plots and analysis of variance. The grey-relation analysis and fuzzy interference system techniques have been developed to combine (called grey-fuzzy reasoning grade) the experimental response while Rao-Algorithm is used to calculate the optimal performance.

The hybrid optimization result is obtained as ST_off = 50µs, ST_on = 105µs, S_w = 7 m/min, WT = 12N and S_v=20V. Additionally, the result is compared with the firefly algorithm and improved gray-wolf optimizer to check the efficacy of the intended approach. The confirmatory test has been further conducted to verify optimization results and recorded 8.14% overall machinability enhancement. Moreover, the scanning electron microscopy analysis further demonstrated effectiveness in the WEDMed surface with a maximum 4.32 µm recast layer.

The adopted methodology helped to attain the highest machinability level. To the best of the authors’ knowledge, this work is the first investigation within the considered parametric range and adopted optimization technique for Ti-3Al-2.5V using the wire-electro discharge machining.

This paper aims to examine the uniform diffracted fields from a perfectly magnetic conductive (PMC) surface with the extended theory of boundary diffraction wave (BDW) approach.

Miyamoto and Wolf’s symbolic expression of the vector potential was used in the extended theory of BDW integral. This vector potential is applied to the problem, and the nonuniform field expression found was made uniform. Here, the expression is made uniform, using the detour parameter with the help of the asymptotic correlation of the Fresnel function. The BDW theory for the PMC surface extended the diffracted fields, and the uniform diffracted fields were calculated.

The field expressions obtained were interpreted with the graphs numerically for different aperture radii and observation distances. It has been shown that the BDW is continuous behind the diffracting aperture. There does not exist any discontinuity at the geometrically light-to-shadow transition boundary, as is required by the theory.

The results were graphically compared with diffracted fields for other surfaces. As far as we know, the uniform diffracted fields from the circular aperture on a PMC surface were calculated for the first time with the extended theory of the BDW approach.

The purpose of this paper is to compile a comprehensive status report on pipes/piping networks across different industrial sectors, along with specifications of materials and sizes, and showcase welding avenues. It further extends to highlight the promising friction stir welding as a single solid-state pipe welding procedure. This paper will enable all piping, welding and friction stir welding stakeholders to identify scope for their engagement in a single window.

The paper is a review paper, and it is mainly structured around sections on materials, sizes and standards for pipes in different sectors and the current welding practice for joining pipe and pipe connections; on the process and principle of friction stir welding (FSW) for pipes; identification of main welding process parameters for the FSW of pipes; effects of process parameters; and a well-carved-out concluding summary.

A well-carved-out concluding summary of extracts from thoroughly studied research is presented in a structured way in which the avenues for the engagement of FSW are identified.

The implications of the research are far-reaching. The FSW is currently expanding very fast in the welding of flat surfaces and has evolved into a vast number of variants because of its advantages and versatility. The application of FSW is coming up late but catching up fast, and as a late starter, the outcomes of such a review paper may support stake holders to expand the application of this process from pipe welding to pipe manufacturing, cladding and other high-end applications. Because the process is inherently inclined towards automation, its throughput rate is high and it does not need any consumables, the ultimate benefit can be passed on to the industry in terms of financial gains.

To the best of the authors’ knowledge, this is the only review exclusively for the friction stir welding of pipes with a well-organized piping specification detailed about industrial sectors. The current pipe welding practice in each sector has been presented, and the avenues for engaging FSW have been highlighted. The FSW pipe process parameters are characteristically distinguished from the conventional FSW, and the effects of the process parameters have been presented. The summary is concise yet comprehensive and organized in a structured manner.

This study aims to provide a causal framework for teacher burnout (BO) and work engagement (WE) by examining the factors that contribute to it and evaluating how progressive education (PE) affects teachers' performance in Higher education institutions (HEIs).

This study uses a multi-stage sampling technique with the help of computer random generation data from a selected list of teachers. The survey has two sections; the first consisted of a questionnaire of PE, BO, WE and organizational outcomes and the second contained four items to measure the demographic variables. The researcher contacted 745 teachers and asked them to fill up the questionnaire but the authors received only 498 useable responses.

The results of the study confirmed that moderating role PE reduces the BO of the teachers of HEIs and increases WE. The job demand-resource (JD-R) model was also validated in the Indian context and the model was found suitable for the Indian sample.

The study has been conducted to manage BO and teachers' engagement in HEIs and the result suggests that the Management of HEIs should value PE characteristics as a crucial component of the educational process. PE encourages academic engagement among professors and students in HEIs.

The study tests the moderating role of PE with the JD-R and the JD-R model in the higher education system in India, which is rarely tested. The study's integrated approach to BO and WE, which provide insight into both viewpoints and aids in employees' poor health.

The aim of this study is to investigate and clarify how the triple helix actors can effectively implement the concepts of Kaizen to navigate and overcome the complex obstacles brought on by the global COVID-19 pandemic.

Through broad literature reviews, nine common parameters under triple helix actor have been recognized. A regression analysis has been done to study how the triple helix actors’ common parameters impact Kaizen implementation in business operations.

The results of this study revealed insightful patterns in the relationships between the common parameters of triple helix actor and the dependent variables. Notably, the results also showed that leadership commitment (LC) emerges as a very significant component, having a big impact on employee engagement as well as organizational performance.

In addition to offering valuable insights, this study has limitations including the potential for response bias in survey data and the focus on a specific set of common parameters, which may not encompass the entirety of factors influencing Kaizen implementation within the triple helix framework during the pandemic.

The originality of this study lies in its comprehensive exploration of the interplay between triple helix actors and Kaizen principles in addressing COVID-19 challenges. By identifying and analyzing nine specific common parameters, the study provides a novel framework for understanding how triple helix actors collaboratively enhance organizational performance and employee engagement during challenging times.