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Student interest and learning success is an important component of teaching learning research. However, while the impact of emotions and psychological needs on students' achievements has been a focus of research, the impact of their physiological needs has been under studied. In this explorative study, I examine what impact the physiological and psychological needs of student teachers have on their feelings, motivation, and interest in different learning settings.

The research method used was the daily reconstruction method and included the Felix-App, a new digital research and feedback tool that allows the measurement of feelings, needs, motivation, and interest in real time.

The results suggest the importance of physiological needs for perceived emotions, motivation, and interest in the learning subject. The psychological needs, on the other hand, are of less importance.

The Felix-App is an innovative tool to learn more about learners' emotions and needs in real learning settings. The importance of physiological needs has been known since Maslow, but should be considered much more in the context of teaching and learning research in the future. There is a need for further research on the importance of physical aspects in learning.

Hazel Kyrk, one of the first women economists at the Economic Department of the University of Chicago and author of A Theory of Consumption (1923), conducted groundbreaking research for the Bureau of Home Economics of the US Department of Agriculture and the Bureau of Labor Statistics. Kyrk made a considerable contribution to the development of standards for a “decent living,” the Consumer Price Index, and the conceptualization of what would later turn into the definition of the poverty line. This chapter evaluates Kyrk’s use of eugenic notions of gender and race that were widely used in Kyrk’s day. This chapter shows that eugenic reasoning impacts Kyrk’s theoretical work only superficially but does structure her research on consumption standards through her focus on the white middle-class family as the unit of analysis for consumer behavior. This chapter also makes clear that the American Institutionalist approach to consumer behavior, rather than marginalized and side-tracked due to a lack of theoretical progress, was relegated to the margins of economics science together with the research of women economists into Home Economics departments and policy research at government institutions.

Drawing on social capital theory, this study investigated the effects of structural, cognitive and relational family social capital on employees' career advancement through the mechanism of family-to-work enrichment (FWE), taking perceived organizational politics (POP) as a moderator.

Survey data were collected from 252 full-time employees working in public institutions and government departments in China, a collectivist cultural context. Hierarchical regression and path analysis were conducted to test the hypotheses.

FWE significantly mediated the positive relationships between the three subtypes of family social capital and career advancement. The effects of structural and cognitive family social capital, but not relational family social capital (RFSC), on FWE were stronger when POP was low (vs high).

FWE is arguably a promising mechanism for explaining the links between family social capital and career outcomes. However, due to the cross-sectional nature of the data, conclusions regarding causality remain limited.

Family social capital may enrich the careers of employees in collectivist cultures. Managers should mitigate their organization's political climate to promote employees' career advancement.

This study contributes to career research by linking family social capital to career outcomes through the lens of FWE for the first time and by identifying organizational politics as an important moderator that can influence the dynamics of resource enrichment in a collectivist culture.

This article presents a novel case study that analyzes the applicability of DoE in the curling sport in order to improve their own performance and the performance of its athletes. Specifically, this study analyzes the most important factors to increase accuracy and precision in the draw game with curlers' opinions. It was decided to use the “Last Stone Draw (LSD)’ as an appropriate play situation.

Specifically, this study analyzes most important factors to increase accuracy and precision in the draw game with curlers opinions from the German Curling association. Three research techniques were used in this study: case study, interviews and a well-designed experiment. The analysis through the use of DoE includes a measurement system analysis, an initial variance test between two players, a screening and a characterization experiment.

The results obtained from DoE suggest that the factors routine, stress, release, balance, and the previous play situation have a substantial impact on the score of the player's draw game. However, no factor has a statistically significant impact on the average distance to the center of the target. Moreover, the DoE analysis also concludes that the accuracy and precision of the player's performance is not affected equally by all analyzed factors, but they turn into highly significant when examining their relationship to the other factors.

The findings of this study can be beneficial to other sports events in improving the performance. Moreover, DoE has proved to be an invaluable tool for many people in the German Curling Association in understanding the factors which influence the curlers performance and also factors which do not affect the curlers performance.

This research attempts to contribute to the existing sports management literature by identifying a way in which DoE can be an effective tool in non-manufacturing settings for identification of most important factors which influence the curling performance.

This study aims to propose a combined effect framework to explore the relationship between research and development (R&D) team networks, knowledge diversity and breakthrough technological innovation. In contrast to conventional linear net effects, the article explores three possible types of team configuration within enterprises and their breakthrough innovation-driving mechanisms based on machine learning methods.

Based on the patent application data of 2,337 Chinese companies in the biopharmaceutical manufacturing industry to construct the R&D team network, the study uses the K-Means method to explore the configuration types of R&D teams with the principle of greatest intergroup differences. Further, a decision tree model (DT) is utilized to excavate the conditional combined relationships between diverse team network configuration factors, knowledge diversity and breakthrough innovation. The network driving mechanism of corporate breakthrough innovation is analyzed from the perspective of team configurations.

It has been discerned that in the biopharmaceutical manufacturing industry, there exist three main types of enterprise R&D team configurations: tight collaboration, knowledge expansion and scale orientation, which reflect the three resource investment preferences of enterprises in technological innovation, network relationships, knowledge resources and human capital. The results highlight both the crowding-out effects and complementary effects between knowledge diversity and team network characteristics in tight collaborative teams. Low knowledge diversity and high team structure holes (SHs) are found to be the optimal team configuration conditions for breakthrough innovation in knowledge-expanding and scale-oriented teams.

Previous studies have mainly focused on the relationship between the external collaboration network and corporate innovation. Moreover, traditional regression methods mainly describe the linear net effects between variables, neglecting that technological breakthroughs are a comprehensive concept that requires the combined action of multiple factors. To address the gap, this article proposes a combination effect framework between R&D teams and enterprise breakthrough innovation, further improving social network theory and expanding the applicability of data mining methods in the field of innovation management.

Social psychology has focused on an individual’s reaction to emergencies and witnessing a crime, which has developed theories of bystander intervention and bystander apathy. The purpose of this study is to explore why people choose to intervene when they are a bystander to intimate partner violence (IPV) and the psychological processes that underpin this. Decision-making was explored drawing on literature from the whistleblowing field.

Through a mixed methods epistemology, this study explored factors that explained intervening behaviour concerning IPV. In total, 212 participants who had known someone who was a victim of IPV were recruited from the general population.

A logistic regression model indicated that conscientiousness and fairness were found to predict intervening behaviour. Being a child witness was found to predict non-intervening behaviour. Qualitative analysis revealed three types of bystander apathy: those who lacked capability as they were children; those who were indifferent and did not see it as their place to intervene; and those who wanted to intervene but did not as they were frightened of exacerbating the situation.

IPV has significant physical and psychological effects on victims. However, the choice to intervene is complex, and bystander intervention in this study was also associated in some cases with not only a continuation of the IPV behaviour towards the victim but also aggression and physical violence towards the bystander (whistleblower retaliation). Based on the findings of this study, recommendations are made for how to support bystanders and victims of IPV.

This study involved participants with real-life experience of being a bystander to IPV. The mixed methodology provided an insight into the psychological processes, which underpin bystander experiences of IPV and maps onto the literature in relation to whistleblowing.

Building on the social cognitive theory, a mediation model was examined to understand the role of teacher self-efficacy as the underlying mechanism for the relationship between instructional leadership and teacher job satisfaction.

The study tests a mediation model between instructional leadership, teacher self-efficacy and job satisfaction. The data were collected via online survey from primary school teachers (N = 320) working for the Municipal Corporation of Delhi (MDC) in India. The mediation model was tested using the AMOS 22.0 after establishing the reliability and validity of measures.

Regression analyses using the bootstrapping method indicated that teacher self-efficacy mediates the relationship between instructional leadership and teacher job satisfaction.

This is a cross-sectional study. The scope for causal inferences is, thus, limited.

In the Indian setting, the study examines the association between instructional leadership and job satisfaction. The results show that the instructional leadership of the school principal is strongly related to teachers' self-efficacy, which, in turn is positively associated with teacher’s job satisfaction. Further, the findings confirm that instructional leadership, emphasizing instructional improvement, improves teachers' self-efficacy and job satisfaction.

The study explains the underlying process through which a school principal’s instructional leadership is related to teacher job satisfaction. This study is perhaps the first to focus on an Indian or a non-Western context.