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This study estimates returns to higher education across different fields in Thailand for 2019 and 2021, accounting for field selection endogeneity. The comparison offers insights into the impact of the pandemic and other economic shocks on the returns.

The study applies an econometric causal framework, integrating economic theory with empirical analysis using data from Thailand’s socioeconomic surveys in 2019 and 2021. A multinomial treatment effects model with sample selection correction is used to estimate the impact of different fields of study on income, accounting for selection both into higher education in different fields and into employment, addressing potential biases from ability sorting and sample selection.

The study finds variations in returns to education across fields. In 2019, teaching offered the highest returns on average, followed by healthcare. Social sciences, business and computer-related fields showed moderate returns, while the combined group of science, agriculture, engineering and architecture had non-significant returns, indicating a low weighted average across these diverse fields. In 2021, healthcare exhibited the highest return due to pandemic-driven demand. Across both years, controlling for occupation reduced the estimated returns by approximately 50%, highlighting the role of occupational status in mediating educational returns.

This study uniquely applies an econometric causal framework to analyze returns to higher education by field of study in Thailand. It offers insights for policymakers to align educational programs with labor market demand and emphasizes the importance of data-driven decisions in responding to disruptions.

Research on technology acceptance of online entertainment with age, gender and cultural factors as moderator, is rarely conducted. Previous research predominantly focused on age or gender as moderator, neglecting the influence of cultural factors. Therefore, this study aims to investigate acceptance of online entertainment technology, incorporating age, gender and cultural factors as moderator.

Data were collected through a survey comprising 1,121 individuals aged 14–24 years from three cities in Indonesia. The proposed theoretical model examined the causal effect of acceptance and moderating effects due to individual gender, age, power distance, individualism, feminism and uncertainty avoidance (AU). Subsequently, structural equation modeling was used to evaluate the theoretical model, and the results confirmed several findings from previous research.

The findings confirmed the positive direct impact of habit and price value (PV) on behavioral intention and hedonic motivation, as well as social influence on habit. The recent findings derived from the moderating effect analysis showed that age, individualism and feminism played a moderating role in the effects on individual intention due to habit. Additionally, gender and AU moderated the effects on individual habits due to hedonic motivation.

This research contributes to the limited knowledge of technology acceptance of online entertainment, and also integrates the causal effects of individual intention due to habit, PV, hedonic motivation and social influence, considering the moderating role of culture, age and gender. Consequently, the investigation provides valuable insights into the literature by presenting evidence of age, gender and cultural differences in acceptance. Furthermore, it offers practical guidance to online entertainment application developers on designing applications to satisfy consumers of different ages, genders and cultures.

Being clear and specific on what moderating and/or mediating variables are included and what effects are observed in academic research helps the reader to better understand the academic research context and results. But in terms of managerial relevance, it is also important to do this in a way that it provides descriptive, goal and operational relevance to decision makers in practice, depending on the type of intended research. This article wants to provide “a question-based step-by-step guide” on how to make the analysis of moderating/mediating variables and their observed effects more managerially relevant.

Based on a critical review of the literature, important criteria of managerial relevance are confronted with important aspects of theory building with respect to mediating and moderating effects, leading to best-practice insights and recommendations. Moreover, exemplary articles are used to illustrate these findings.

The insights and step-by-step recommendations assist the academic researcher in making choices when analyzing moderators and mediators, by not only taking a theoretical perspective, but also a managerial (relevance) perspective. Adding moderators/mediators may for instance challenge the “core logic of managerial practice” (in terms of thinking and decision making), even if it does not change the “core logic of a theory” as such. In the other direction, academics (and their theory) may be challenged by practitioners, in the way they define moderators/mediators and their levels. The steps in this article relate to aspects such as measurability, controllability and role of moderators and mediators in managerial problem and decision contexts. In case of multiple moderating and/or mediating variables, the decision architecture for managers becomes more complex, especially when the effects are countervailing/opposite. Multiple studies in this article illustrate that in that case, making optimal decisions becomes a “balancing” act for managers/decision makers and may even challenge their common beliefs (e.g. linear thinking).

The guidelines on managerial relevance of moderating and/or mediating variables and their effects can be used by academic researchers and editors of academic journals, pursuing not only academic rigor, but also managerial relevance. Besides being a guide for managerially relevant output, it also helps in determining for which questions in the research process, input from practitioners or at least insights from practice (e.g. through sources such as business magazines and portals) may be needed. The guidelines may also be used for teaching purposes, complementing more theoretical articles that mainly focus on methodological/statistical issues of moderating/mediating variables and their effects.

Green entrepreneurship (GE) is a novel concept in business and enhances environmentally friendly production and operation activities for “sustainable development” (SD). The aim of this study is to determine the drivers that contribute to the growth and success of “micro, small, and medium enterprises” (MSMEs) in the manufacturing sector in India. The study also examines the mutual and cause-and-effect relationships among these identified drivers.

The study used integrated research methodology and identified nine key drivers of GE (GEDs) through extensive literature reviews, theoretical perspectives (i.e. “resource-based view” (RBV), “natural resource-based view” (NRBV) and “critical success factor theory” (CSFT)), and expert opinions. Further, “total interpretive structural modeling” (TISM) and “matrice d'impacts croisés multiplication appliquée á un classment” (MICMAC) analysis are used here to develop a hierarchical model and cluster the drivers, and fuzzy “decision-making trial and evaluation laboratory” (fuzzy-DEMATEL) is used to develop causal relationships among the drivers. Further, a sensitivity analysis is conducted to ensure the robustness of the results.

Results indicated that green manufacturing and operation capability development, green business process management and attitudes toward developing sustainable business models significantly impacted GE and SD. The findings of this study help managers, policymakers, and practitioners gain an in-depth understanding of the drivers of GE.

The study considers a limited number of drivers and is specific to Indian manufacturing MSMEs only. Further, a limited number of experts from different enterprises are considered for data analysis. This study is also based on interrelationships and their relative importance based on multicriteria decision-making techniques. This study aids government decision-making, policy formulation and strategic decision-making for manufacturing businesses in achieving SD goals. In addition, this research also encourages green entrepreneurs to start eco-driven companies and facilitate the use of environmentally friendly goods to offset environmental challenges and accomplish sustainable development goals.

This study proposes an integrated methodology that will benefit managers, practitioners and others in developing strategies and innovations to improve and develop green practices. This study further helps with responsive, sustainable business development in various manufacturing MSMEs.

The paper examines the impact of market power on wages within the context of a developing country, focusing on Brazil.

With access to matched employer–employee data from Brazil, we first characterized the evolution of the local labor market concentration (Municipality Herfindahl–Hirschman Index [HHI]). Then, we built a fixed-effect model with instrumental variables to verify the association between the local labor market concentration and wages. Finally, a difference-in-difference (DiD) was implemented to verify whether a merger transaction impacted the workers’ earnings in the Brazilian banking sector.

The paper’s findings suggest that there may be a negative relationship between market power and workers’ earnings.

This research conducted an in-depth investigation of the labor market power in a developing country. As far as we know, our work is the first to evaluate the extension of local concentration in Brazilian formal labor markets and to illustrate its evolution over the last decades. Additionally, when going through the effects of market concentration on wages, we use a new identification strategy that explores changes in the HHI that are caused by national trends in an industry as a source of exogenous variation. Finally, the last part of the paper assesses the effects of antitrust policy on the labor market, a kind of investigation that is still scarce.

Rapid innovation and developments in personal electronic technology have encouraged users to change users' devices more frequently than ever, which has resulted in creating a massive increase in the amount of electronic waste. The study focuses on identifying the barriers to closed-loop supply chain (CLSC) in the electronic industry.

A framework for analyzing the relationships among CLSC adoption barriers is designed. The authors adopted the decision-making trial and evaluation laboratory (DEMATEL) technique to determine the critical barriers of electronic CLSC from the opinion of experts in the field.

The outcome from the analysis suggests that cost barriers, financial barrier, process barriers and supplier-side barriers are the main causal factors that prevent the adoption and implementation of e-waste CLSC. The causal relationship indicates that financial barrier is the most influential factor, while phycological barrier is the most flexible barrier to the adoption of e-waste CLSC.

This study is restricted to CLSC adoption barriers in the electronic industry by evaluating 36 sub-barriers grouped into 8 main dimensions related to different members of the supply chain.

Closed-loop adoption barriers have been proposed to understand the crucial barriers to implementation of CLSC in the electronic industry. The cause-and-effect relationship indicates the critical factors to be improved to increase adoption of e-waste CLSC, helping managers and regulatory bodies to mitigate the problem areas.

This study contributes to the literature on CLSC by adopting a multi-criteria decision-making (MCDM) technique which captures the critical barriers of e-waste CLSC adoption in Indian scenario.

Iron deficiency anemia (IDA) is the most common form of anemia in the world, affecting children, women and the elderly, while also being a common comorbidity in several medical conditions. Several studies have suggested a possible association between IDA and neurological dysfunction. Epilepsy, one of the common neurological disorders, has an unknown association with IDA. This pa per aims to investigate whether there is a causal relationship between IDA and epilepsy using a two-sample Mendelian randomization (MR) design.

This paper obtained summary data on IDA and epilepsy from the FinnGen consortium. Genetic variants significantly associated with IDA were used as instrumental variables (IVs). Epilepsy, focal epilepsy and generalized epilepsy were the outcomes. This paper used inverse variance weighted (IVW) as the primary estimate, and other MR methods were used as supplementary measures. Sensitivity analysis was also performed to assess heterogeneity and pleiotropy.

IVW estimates genetically predicted a causal relationship between IDA and the risk of epilepsy [odds ratio (OR), 1.15; 95% confidence interval (95% CI), 1.05–1.26; p = 0.002] and focal epilepsy (OR, 1.978, 95% CI, 1.58–2.48, p ≤ 0.0001), while no significant causal relationship was found with generalized epilepsy (OR, 1.1, 95% CI, 0.94–1.3, p = 0.24). There was no evidence of horizontal pleiotropy and heterogeneity in the sensitivity analysis.

This two-sample MR study found that IDA has a negative effect on the development of epilepsy. Clinical control of IDA may be helpful in the prevention of epilepsy. There is a need for further studies to explain the underlying mechanisms of this association.

This paper aimed to examine the impacts of agricultural services on welfare of rural farmers in Ghana.

Using data from 1431 rural maize farmers, we employ multinomial endogenous switching regression and multivalued inverse probability weighted regression adjustment to assess the impacts.

Results show that 19.8%, 9.7% and 3.42% of farmers adopted solely irrigation, extension and mechanization, respectively. Furthermore, utilizing a range of agricultural services significantly improves maize yields, gross income and per capita food consumption.

This study recommends strategies that target the adoption of combinations of agricultural services to enhance rural farmers’ welfare in Ghana and other developing countries.

While agricultural services are claimed to improve agricultural production and peasants’ welfare, their impacts are not studied exhaustively. This paper contributes by providing empirical evidence of the impacts of agricultural services on farmers’ welfare.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2022-0745.

This study aims to investigate whether stimulating a family business image can serve as a signal to enhance customer brand co-creation.

The authors tested the proposed moderated serial mediation model utilising a sample of 521 experienced online customers. Using a scenario-based approach with an experimental design, the authors investigated how the stimulation of a family business image influences customers’ co-creation activities on social media.

Stimulating a family business image plays a significant role in fostering interactions among customers who respond to this signal. Furthermore, when there is an alignment between customers’ self-concept and their perception of brand authenticity, a stronger brand contribution is established. Nonetheless, this alignment does not translate into heightened involvement in brand co-creation activities, as active participation in co-creation necessitates empowerment derived from the co-creation process.

By taking a co-creation viewpoint, this study empirically demonstrates how stimulating a family business image can impact different levels of brand-related involvement. It also highlights the moderating influence of self-congruence in transmitting the signal, shedding light on individual differences in brand engagement. From a practical standpoint, the distinctive nature of a family business image should be recognised as an asset that enables managers to enhance customer responses and strengthen their market position.

By exploring the impact of digital knowledge resources (DKR) on the carbon emission intensity of the pig industry (PCEI), this study aims to reveal the role of DKR in reducing PCEI.

Based on provincial panel data in China from 2011 to 2021, this study uses the entropy and Intergovernmental Panel on Climate Change coefficient methods to calculate the evaluation index system of DKR and PCEI, respectively. Empirical analysis using a panel fixed-effects model examines the influence of DKR on PCEI and its underlying mechanisms.

DKR can significantly reduce PCEI. This conclusion still holds even after undergoing endogeneity treatment and a series of robustness tests. Mechanism test results indicate that DKR can operate indirectly through the mediation mechanism of rural human capital (RHC) and pig breeding technology innovation (PTI), while environmental regulation intensity (ERI) plays a positive moderating role in the relationship between DKR and PCEI. The magnitude of the impact of DKR on PCEI depends on ERI. Further studies found that the impact of DKR on PCEI has obvious heterogeneity characteristics, and the promotion effect is more obvious in regions with good integration degrees and high development potential.

This paper divides DKR into three dimensions: digital technology knowledge (DTK), digital management knowledge (DMK) and digital application knowledge (DAK), providing a new framework for research and enriching the understanding of the relationship between DKR and PCEI. Furthermore, the research results reveal the application potential of DKR in the pig industry, particularly in terms of resource allocation efficiency. This is of great significance for promoting low-carbon development in the pig industry and provides insights for the low-carbon transformation of other industries. In addition, the study emphasizes the moderating effect of ERI on the mechanism of carbon reduction in the pig industry through DKR. This offers a new perspective for understanding the relationship between knowledge management and environmental governance, providing a reference basis for policy formulation in related fields.

This paper further enriches the role of DKR in the livestock industry. Integrating DKR with traditional industries promotes knowledge innovation, information distribution and utilization and scientific decision-making. This has significant value in promoting the development and application of carbon reduction technologies, enhancing industrial competitive advantages, and other aspects.