Search results

This study examines the research landscape on women empowerment and self-help groups (SHGs) using bibliometric analysis and network cluster analysis. It also intends to create a model that prioritizes the sustainability of women-led SHGs in order to promote women’s empowerment.

A list of keywords relating to women empowerment and SHGs was employed as a search strategy to highlight current research characteristics and trajectories. The analysis included 397 Web of Science (WoS) and Scopus papers over a period of 20 years from 2003 to 2022.

The analysis indicated an upward trend in the number of publications over the last decade, with India emerging as the most prolific contributor. Furthermore, the network clustering technique facilitated the identification of five central clusters that guide future research.

This study informs policymakers and microfinance institutions about the sustainability of women-led SHGs by empowering women in multiple capacities, including implementing inclusive microfinance for poverty alleviation; promoting nutritional empowerment for women in SHGs; capacity building and entrepreneurial training; evaluating the socioeconomic impact of SHGs in developing contexts; and fostering social capital and inclusive networking for community development.

This research employed Scopus and WoS databases to encompass a wider range of indexed journals. The contribution lies in proposing new research directions and providing practical solutions for sustainability of women-led SHGs to achieve women empowerment.

Business competitiveness is critical for a thriving economy that requires companies to be more efficient and innovative to outperform their rivals. This paper investigates the main determinants of business competitiveness from the resource-based view (RBV) perspective.

Data were collected from 140 discrete and large manufacturing firms in Malaysia through a cross-sectional quantitative-based survey with a convenience sampling procedure. The findings from the PLS-SEM analysis showed that implementing LAG manufacturing significantly amplifies business competitiveness.

It was found that cost leadership strategy drives lean and agile manufacturing implementation, while differentiation positively amplifies the implementation of lean, agile and green manufacturing. This study contributes to the body of knowledge and provides insight to practitioners in tailoring strategies to steer manufacturing firms toward being more competitive.

This study identifies the effect of LAGP implementation on business competitiveness. This paper will benefit practitioners and managers by providing insights into tailoring strategies to steer manufacturing firms towards being more competitive. This paper follows a structure that includes: an introduction to the study, a review of relevant literature on business competitiveness, lean, agile and green manufacturing implementation, the development of hypotheses, the presentation of research methodology and findings, and finally, a conclusion with a discussion, implications, limitations and suggestions for future research.

The study examines the impact of macroeconomic risk and volatility associated with key macroeconomic indicators on financial market uncertainty; and the extent to which governance and institutional structures moderate such relationships.

The study employs data from 33 countries in Sub-Saharan Africa (SSA) for the period between 1996 and 2019. Variable derivation techniques such as the generalized autoregressive conditional heteroskedasticity (GARCH) for deriving volatility data, and the principal component analysis (PCA) for index construction were employed. The data is examined using the two-step system generalized method of moments (TS-SGMM) technique.

Empirical results suggest that macroeconomic risk and exchange rate volatility heighten financial market uncertainty among economies in the sub-region. Further empirical estimates show that institutional quality and government effectiveness have a negative moderating effect on the nexus between macroeconomic risk, inflation uncertainty, GDP growth, exchange rate, and financial market uncertainty.

The key macroeconomic conditions with the propensity to foment financial market uncertainty are worth monitoring with adequate buffers to mitigate their impacts on the financial market.

Compared to related studies, this study focuses on uncertainty associated with financial markets among emerging economies in sub-Saharan Africa (SSA) instead of the performance of the financial markets or specific financial market indicators such as the stock market; and the extent to which a host of macroeconomic conditions influence such uncertainty. For instance, Abaidoo and Agyapong (2023) focused on the impact of macroeconomic indicators or conditions on the performance of the financial market and the efficiency of financial institutions respectively instead of the uncertainty or risk associated with the financial market as pursued in the current study. This differing approach is pursued with the goal of proffering appropriate strategies for policy makers towards assuaging the financial market risk (uncertainty) due to macroeconomic dynamics. We further examine how the various fundamental relationships may be moderated by effective governance and institutional quality.

This study analyzes whether industry relatedness between a corporate borrower and its group peers significantly affects that firm's borrowing cost.

A regression analysis is run on bank-loan data of a sample of Indonesian companies for 2010–2020. The main variables of interest are the natural logarithms of the borrowing firm's number of affiliates classified within either similar 2- or 4-digit GICS industries, and the Caves weighted index of these firms' related diversification. This index measures how firms in a group are diversified in relation to the borrower. The dependent variable is the all-in credit spread, stated in basis points, over the LIBOR or similar benchmark, as of the loan issuance date.

Findings support the industry-relatedness hypothesis and contradict the risk-reduction hypothesis and show that banks charge lower loan spreads on a borrowing firm that either operates within a similar industry as its affiliate or diversifies into related sectors or industries. Consistent with the co-insurance-effect hypothesis, the results also underline the importance of the parent and first-layer firms as supporting instead of the tunneling vehicles within business groups. These conclusions hold even after segregating the sample and using the loan maturity as the dependent variable.

This study uses a unique diversification measurement based on the borrowing firm's sector or industry, relative to other group members, and offers new insights on business group diversification and bank loan costs.

This paper examines the relationship between a pyramidal firm’s control-ownership wedge and the amount of its debt relative to the group’s total debt and its likelihood of having guaranteed debt in its capital structure.

The study sample consists of the 200 largest Indonesian companies listed on the Indonesia Stock Exchange for the period 2015–2022. I run baseline regressions and a number of robustness tests, which include two-stage least squares, censored regressions, difference-in-differences and subsample regressions as well as regressions with interaction terms.

The results show that, within pyramidal business groups, member firms with large control-ownership wedges are associated with less group debt allocation and a higher probability of having guaranteed debt.

To the best of my knowledge, this paper is the first to examine the direct link between a pyramidal firm’s control wedge and its’ proportion of group debt allocation and probability of having guaranteed debt. Therefore, it enriches the theory of tradeoffs within business groups and sheds more insights on the intragroup guarantees literature.

This study aims to examine how mental health symptoms and social support predict changes in online and in-person social networks among gamers over time. Although research has explored how social networks influence mental health, less is known about how mental health shapes the evolution of social connections in gaming contexts where relationships can form and dissolve fluidly.

Adult gamers (n = 236) completed surveys at two time points approximately six months apart measuring mental health symptoms (depressive symptoms, anxiety), perceived social support and characteristics of both their in-person and gaming-based social networks. Partial least squares regression models examined how Time 1 mental health and support measures predicted changes in network characteristics while controlling for baseline network measures.

Results revealed distinct patterns of network evolution across contexts. Higher initial depressive symptoms predicted strengthening of in-person relationships but decreases in online relationship quality over time. Anxiety emerged as a particularly influential predictor of online network development, with higher baseline anxiety associated with decreased closeness, confiding behavior and positive interactions in gaming relationships. Strong initial gaming community integration predicted decreased quality of in-person relationships, suggesting potential competition between virtual and physical social spheres.

This study provides longitudinal examination of how mental health symptoms distinctly influence the evolution of social networks across online and offline contexts among gamers. The findings demonstrate that different symptoms show unique patterns of association with network development over time, challenging assumptions about gaming spaces serving as universally accessible social environments.

The aim of this paper was to delve into the underlying mechanism of the relationship between environmental knowledge and green purchase intentions, using an extended model based on the knowledge-attitude-behaviour (KAB) theory.

The parallel and serial mediation effects of environmental concern, green perceived value and green attitude were examined using PROCESS macro (Models 4 and 6). Data were collected from 395 youth in three different cities in India using a purposive sampling method.

The study’s findings revealed that environmental concern, green perceived value and green attitude act as parallel and sequential mediators between environmental knowledge and green purchase intentions. However, the direct impact of environmental knowledge on green purchase intentions was deemed insignificant. In essence, environmental knowledge, along with environmental concern and green perceived value, significantly contributes to the formation of attitudes conducive to green purchase intentions.

The present study theoretically contributes to green behaviour research by proposing and testing an extended model of KAB theory with parallel and serial mediations in the Indian context. The model explores the underlying mechanism of the relationship between environmental knowledge and green purchase intentions in detail.

When a company practices greenwashing, it breaks consumers’ trust by purposefully misleading them about its environmental practices or the benefits of its products/services. This study aims to contribute to the literature by testing the effect of perceived greenwash on green purchase intention through green trust, green perceived value and green skepticism. Furthermore, the study introduces environmental knowledge as a moderator in the relationship between perceived greenwash and three attitudinal factors by integrating the theory of cognitive dissonance and information asymmetry as a foundational framework.

The descriptive hypo-deductive research design was adopted to test the proposed model. This study performed survey research with a structured questionnaire. A sample of 432 responses was collected from youth living in India using a purposive sampling method. The validity and reliability of the model were tested using structural equation modeling, and moderation and mediation effects were examined using process macro.

The results support the mediation role of three attitudinal factors between perceived greenwash and green purchase intention. Furthermore, the moderation effect of environmental knowledge was significant between perceived greenwash and attitudinal factors, except between perceived greenwash and perceived green value.

This research offers valuable insights into the role of environmental knowledge and its moderating influence on shaping attitudes toward green purchase intentions. This study highlights green buying as an obscure risk, impacted by factors such as green trust, green perceived value, green skepticism and, ultimately, perceived greenwash. The proposed research framework carries significant implications for comprehending the underlying drivers of green purchase intentions, advocating for a strategic emphasis on truthful, transparent and verifiable communication by companies.

This study contributes to the existing knowledge base by delving into and examining the mediating and moderating factors influencing green purchase intentions, which was less emphasized in prior literature, especially within the context of India. The research provides empirical insights, establishes a theoretical consensus and unveils novel perspectives for reconsidering the intricate dynamics among environmental knowledge, perceived greenwash and diverse dimensions of green perceived value in the realm of sustainable products.

Financial distress (FD) is an unfavorable situation that can have severe negative consequences on a firm. Within the range of multiple micro and macro factors, firm’s dividend policy can impact FD. However, this relationship is yet to be explored. Since shareholder yield (SHY) is a major component of the dividend policy, this study aims to explore the effect of SHY on a firm’s FD. Taking insights from stakeholder theory and dividend signaling theory, we also examined if this relationship is moderated by competition and firm size.

The data from Fortune 500 companies over thirteen years (2010–2022) was subjected to panel data analysis (PDA). The analysis particularly takes the quantile panel data model to have a deeper understanding of variable’s association in different scenarios of FD.

The findings revealed that the SHY does not directly influence a firm’s FD. However, it is negatively moderated by competition at a lower quantile of financial stability and positively moderated by firm size at all quantiles of financial stability (reverse of FD). It means when competition increases, the shareholder’s yield reduces the financial stability. However, it improves financial stability when firm size increases.

The findings deliver significant implications for all the stakeholders to consider dividend policy in form of SHY as a crucial element for a firm’s financial soundness. It is very situational to improve or detriment the financial health of the firm when it combines with other factors particularly competition or firm size. Hence, it is important to understand its sensitivity for FD.

In this study, we evidenced competition and firm size as moderators to SHY and FD relationship thus presenting novel insights. The findings are integrated to stakeholder theory and dividend signaling theory, and thus offer theoretical advancements.

India’s rapid economic growth has triggered a significant transformation in its logistics sector, fueled by comprehensive reforms and digital initiatives outlined in the National Logistics Policy. Smart warehouses, equipped with cutting-edge technologies such as IoT, AI and automation, have taken center stage in this evolution. They play a pivotal role in India’s digital journey, revolutionizing supply chains, reducing costs and boosting productivity. This AI-driven transformation, in alignment with the “Digital India” campaign, positions India as a global logistics leader poised for success in the industry 4.0 era. In this context, this study highlights the significance of smart warehouses and their enablers in the broader context of supply chain and logistics.

This paper utilized the ISM technique to suggest a multi-tiered model for smart warehouse ecosystem enablers in India. Enablers are also graphically categorized by their influence and dependence via MICMAC analysis.

The study not only identifies the 17 key enablers fostering a viable ecosystem for smart warehouses in India but also categorizes them as linkage, autonomous, dependent and independent enablers.

This research provides valuable insights for practitioners aiming to enhance technological infrastructure, reduce costs, minimize wastage and enhance productivity. Moreover, it addresses critical academic and research gaps contributing to the advancement of knowledge in this domain, thus paving the way forward for more research and learning in the field of smart warehouses.

The qualitative modeling is done by collecting experts' opinions using the ISM technique solicits substantial value to this research.