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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.

The purpose of this paper is to explore the role of qualitative research in causality, with particular emphasis on process causality. In one paper, it is not possible to discuss all the issues of causality, but the aim is to provide useful ways of thinking about causality and qualitative research. Specifically, a brief overview of the regularity theory of causation is provided, qualitative research characteristics and ontological and epistemological views that serve as a potential conceptual frame to resolve some tensions between quantitative and qualitative work are discussed and causal processes are explored. This paper offers a definition and a model of process causality and then presents findings from an exploratory study that advanced the discussion beyond the conceptual frame.

This paper first conceptually frames process causality within qualitative research and then discusses results from an exploratory study that involved reviewing literature and interviewing expert researchers. The exploratory study conducted involved analyzing multiple years of literature in two top human resource development (HRD) journals and also exploratory expert interviews. The study was guided by the research question: How might qualitative research inform causal inferences in HRD? This study used a basic qualitative approach that sought insight through inductive analysis within the focus of this study.

The exploratory study found that triangulation, context, thick description and process research questions are important elements of qualitative studies that can improve research that involves causal relationships. Specifically, qualitative studies provide both depth of data collection and descriptive write-up that provide clues to cause-and-effect relationships that support or refute theory.

A major conclusion of this study is that qualitative research plays a critical role in causal inference, albeit an understated one, when one takes an enlarged philosophical view of causality. Equating causality solely with variance theory associated with quantitative research leaves causal processes locked in a metaphoric black box between cause and effect, whereas qualitative research opens up the processes and mechanisms contained within the box.

This paper reframed the discussion about causality to include both the logic of quantitative studies and qualitative studies to demonstrate a more holistic view of causality and to demonstrate the value of qualitative research for causal inference. Process causality in qualitative research is added to the mix of techniques and theories found in the larger discussion of causality in HRD.

The purpose of this study is to investigate the causal interrelations among the four pillars of corporate sustainability, which indicate a firm’s contribution to environmental, social, governance and economic activities. Moreover, this study identifies the critical drivers of corporate sustainability by focusing on the levels of market developments and geographical regions.

Based on corporate sustainability data of 2,725 global companies in 2016, this study uses a combination of analytical techniques including cluster analysis, data mining, partial least square path modeling and importance performance map analysis.

This study finds that companies in European developed markets exhibit the highest-ranking of corporate sustainability. In line with the social impact hypothesis, environmental, social and governance performance positively affects economic performance. Moreover, there is strong evidence of causal relationships and synergistic effects among the four pillars of corporate sustainability. In accordance with the institutional theory, the patterns of causal directions and the critical pillars depend on levels of market developments and geographical regions. Overall, social and environmental pillars are among the most critical drivers of corporate sustainability.

The methodology does not aim to provide a new weighting scheme for calculating the corporate sustainability index.

Corporate managers should consider sustainability practices in all dimensions to benefit from synergistic effects among environmental, social, governance and economic activities. Furthermore, corporate sustainability strategies should not be generalized across countries with different levels of market developments and geographical regions.

This study prioritizes environmental, social, governance and economic pillars of corporate sustainability in emerging and developed markets across geographical regions.

This study has two objectives. The first aim is to ascertain whether innovation and market orientation have direct, indirect, and causal effects on customer service. The second objective is to ascertain whether market orientation has a moderating effect on the relationship between innovation and customer service. This research follows three distinct methodologies. The first approach uses Cronbach’s alpha coefficient in order to check reliability while an exploratory factor analysis and a confirmatory factory analysis ascertain validity. The second method uses the analysis of structural equation models to test a causal link between variables. The third methodology uses a moderated regression analysis to verify the moderating effects. As our analysis results show, intelligence generation and intelligence dissemination have a moderating effect on the relationship between innovation and flexibility. These results can be interpreted as follows: firstly, customs clearance firms can provide superior service to customers if they strive to understand customer needs and provide them with flexible service at the same time. Secondly, these firms can enhance their flexibility of service in all departments though innovation and information sharing acquired from the market.

The purpose of this paper is to examine the causal relationship between Chinese housing and stock markets. The authors discuss the three transmission mechanisms between the two markets: wealth effect, modern portfolio theory and credit-price effect. Moreover, the authors focus on the effects of inflation on the relationship between the two markets.

This paper uses wavelet analysis to test the housing and stock markets relationship both in the frequency domain and time domain.

The empirical results indicate that housing prices have a positive effect on stock prices, and these have the same effect on housing prices. Moreover, this positive effect means that stock prices have a wealth effect on housing prices and these have a credit-price effect on stock prices.

These results provide information to financial institutions and individual investors in China to assist them in constructing investment portfolios within these two asset markets.

The authors first use wavelet analysis to analyze Chinese housing and stock markets and to provide information both on the frequency domain and time domain. Moreover, the authors take the inflation factor as a control variable in the causal relationship between the housing and stock markets.

The difficulties that MR poses for comparativists were anticipated 40 years ago in Sidney Verba's essay “Some Dilemmas of Comparative Research”, in which he called for a “disciplined configurative approach…based on general rules, but on complicated combinations of them” (Verba, 1967, p. 115). Charles Ragin's (1987) book The Comparative Method eloquently spelled out the mismatch between MR and causal explanation in comparative research. At the most basic level, like most other methods of multivariate statistical analysis MR works by rendering the cases invisible, treating them simply as the source of a set of empirical observations on dependent and independent variables. However, even when scholars embrace the analytical purpose of generalizing about relationships between variables, as opposed to dwelling on specific differences between entities with proper names, the cases of interest in comparative political economy are limited in number and occupy a bounded universe.² They are thus both knowable and manageable. Consequently, retaining named cases in the analysis is an efficient way of conveying information and letting readers evaluate it.³ Moreover, in practice most producers and consumers of comparative political economy are intrinsically interested in specific cases. Why not cater to this interest by keeping our cases visible?

This study aims to investigate an under-researched area, the impact of causal attributions (i.e. causal stability and company-related/-unrelated attributions) on salespeople’s job satisfaction following their performance appraisal.

A pre-test and a between-subjects experimental study test the effect of accurate or biased perceptions of causal attributions on salespeople’s job satisfaction. Data collected from 209 salespeople provide evidence that they make perceptual attribution errors in their appraisals of the performance outcome they achieve or do not achieve.

When salespeople correctly attribute their performance, causal stability affects their job satisfaction. However, company-related attributions affect their satisfaction only in the case of a poor performance outcome. As expected, salespeople who make biased attributions experience misattributed or “unwarranted” satisfaction or dissatisfaction, a higher or lower satisfaction level than they would have experienced had they made proper causal attributions.

Using Weiner’s theory of emotion and motivation as a theoretical framework, this study confirms that cognitive appraisals of event outcomes (in this case performance reviews) impacts salespeople’s emotional experience. Furthermore, causal ascriptions following the salesperson’s performance appraisal affect job satisfaction.

This study discusses how managers can ensure the continued satisfaction of their salespeople, which constitutes a stable source of motivation, by understanding their performance attributions.

This study introduces a new concept of misattributed job satisfaction or dissatisfaction. While anecdotally some scholars have investigated when salespeople play “the blame game”, this study shows how salespeople correctly or incorrectly ascribe blame for the outcomes and the impact on job satisfaction.

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.

The purpose of this paper is to investigate dynamics of causal interactions and financial risk contagion among BRICS stock markets under rare events.

Two methods are adopted: The new causal inference technique, namely, the Liang causality analysis based on information flow theory and the dynamic causal index (DCI) are used to measure the financial risk contagion.

The causal relationships among the BRICS stock markets estimated by the Liang causality analysis are significantly stronger in the mid-periods of rare events than in the pre- and post-periods. Moreover, different rare events have heterogeneous effects on the causal relationships. Notably, under rare events, there is almost no significant Liang's causality between the Chinese and other four stock markets, except for a few moments, indicating that the former can provide a relatively safe haven within the BRICS. According to the DCIs, the causal linkages have significantly increased during rare events, implying that their connectivity becomes stronger under extreme conditions.

The obtained results not only provide important implications for investors to reasonably allocate regional financial assets, but also yield some suggestions for policymakers and financial regulators in effective supervision, especially in extreme environments.

This paper uses the Liang causality analysis to construct the causal networks among BRICS stock indices and characterize their causal linkages. Furthermore, the DCI derived from the causal networks is applied to measure the financial risk contagion of the BRICS countries under three rare events.

Examines the relationships between five components of students′ quality of learning experience (resources, content, learning flexibility, student‐faculty contact, and involvement) and four criteria of college outcomes (students′ satisfaction with their college experience, perceived performance in college, commitment to their college and students′ grades). The major findings of this study indicate that students′ involvement and learning flexibility are the dominant predictors of all four students′ college outcomes, whereas resources and content are the weakest predictors. In addition, quality of learning experience indicators are effective predictors of students′ satisfaction with their college experience (R⊃2 = 0.27) and grades (R⊃2 = 0.20). Discusses the implications of these findings.