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This paper aims to synthesize the diverse literature on nomination and remuneration committees and provide avenues for future research.

This study provides a comprehensive literature review of theoretical and empirical studies published in reputable international journals indexed by Scopus.

The literature review reveals several aspects of the nomination and remuneration committee. These aspects have been classified into the definition of the nomination and remuneration committee, dimensions of the nomination and remuneration committee, measurement and research review results, reasons for conflict empirical findings, company dynamics and research on moderators, as well as recommending future research.

Our literature review shows that nomination and remuneration committees play a role in improving board performance and company performance, reducing agency conflicts and improving corporate governance to provide implications for companies, regulators and investors and pave the way for future research.

This paper identifies issues related to nomination and remuneration committees, their theoretical and practical implications and avenues for future research.

The purpose of this study is to investigate the barriers that prevent workers in the software industry from experiencing flow in their work.

This study was conducted by using a qualitative critical incident technique-inspired questionnaire.

The findings suggest that workers in the software industry perceive that the most obvious obstacles to experiencing flow are related to work not presenting enough cognitive challenges and situational barriers related to the characteristics of the job (e.g. workdays having too many interruptions and distractions, timetables often being considered too tight for creative exploration and problem solving and having negative user experiences with development tools).

The findings provide insights into flow barriers, specifically barriers that prevent workers in the software industry from experiencing flow.

The purpose of this paper is to identify the areas and logic of integration of different stakeholders using different methods and to analyse their applicability and challenges in practical projects. The main aim is to describe how these different methods impact value creation.

Action design research was carried out in a large hospital construction project where the first author acted as an “involved researcher” and the second author acted as an “outside researcher”. Two workshops were organised to evaluate the direct and indirect challenges and benefits of the applied four methods and to explain how different methods enable value creation.

All the studied methods provide good results in terms of usability and commitment to the aims of the project, thus delivering the direct benefits expected. Process, people and tools logic works well in this case project when applying the methods properly. Significant evidence was provided on secondary deliverables of the methods, and all analysed methods had a significant impact in the area of leading people, clarifying what “focus on people” means and how it is enabled.

Focus on people can be achieved through different operative methods if applied in the right way. It is necessary to select the most suitable methods based on all the direct and indirect deliverables.

This case project offered a platform to analyse integration methods in a real-life project using the collaborative contract method. The authors were able to participate in the analysis by taking action from the very beginning of the project in terms of training, learning, continuous development and coaching of these methods and evaluating the applicability.

Given declining tuition funds and government grants, Kenyan universities need to develop strategies, including increased research grants and collaborations, to diversify their income sources. Well-managed doctoral students can boost a university’s teaching and research outputs. However, numbers of students enrolled in doctoral programmes at Kenyan universities are low, and graduation rates and time-to-graduate statistics are disturbing. Research undertaken elsewhere underline the important role played by supervisors and peers in facilitating students’ sense of belonging and their success. Therefore, this study aims to investigate the influence of supervisory and peer support on PhD students’ sense of belonging and their success at Kenyan universities.

In this cross-sectional study, data were gathered through an online questionnaire from 614 students admitted to doctoral programmes at Kenyan universities between 2010 and 2018. We used multi-item scales to collect data on PhD students’ self-efficacy, supervisory and peer support and a sense of belonging.

Structural equation modelling results revealed that PhD students’ modes of study and self-efficacy were significantly associated with the quality of supervision, peer support and a sense of belonging. However, only age, a sense of belonging and the quality of supervision were directly linked to their success.

This study contributes to the literature on doctoral-level education, responding to the need for research on the influence of relationships with supervisors and peers on PhD students’ sense of belonging and their success, especially in developing countries.

The objective of this paper is to investigate the direction of the causal relationship between dividend policy (DP) and earnings management (EM).

This research utilizes the panel data analysis to investigate the causal relationship between EM and DP. It provides empirical insights based on a sample of 280 French nonfinancial companies listed on the CAC All-Tradable index during the period of 2008–2015. The study initiates with a Granger causality examination on the unbalanced panel data and employs a dynamic panel approach with the generalized method of moments (GMM). It further estimates the empirical models simultaneously using the three-stage least squares (3SLS) method and the iterative triple least squares (iterative 3SLS) method.

The estimation of our various empirical models confirms the presence of a bidirectional causal relationship between DP and EM.

Our study highlights the prevalence of EM in the French context, particularly within DP. It underscores the need for regulatory bodies, the Ministry of Finance, external auditors and stock exchange organizers to prioritize governance mechanisms for improving the quality of financial information disclosed by companies.

This research is, to the best of our knowledge, the first is to extensively investigate the reciprocal causal relationship between DP and EM in France. Previous studies have not placed a significant emphasis on exploring this bidirectional link between these two variables.

Considering the important development that research on debt financing decisions of family firms (FFs) has undergone in recent years, we aim to assess the current state of the literature with the latest advances in this field.

We undertake a systematic review of 42 journal articles published on this topic in recent years.

As a result of our work, new directions for the advancement of this research field are established, such as the consideration of different methodologies and sources of heterogeneity of FFs, the need for an integration of the supply and demand side of funds or the importance of evaluating a diversity of firm-specific and contextual factors affecting the debt financial behaviour of FFs.

Considering the notable development of the field of debt financing decisions of FFs in recent years, we find it opportune and valuable to revise the advances and trends published in the most recent papers. Thus, by connecting previous and current knowledge, we provide an updated integrative model of the state of the art and posit key research questions to solve in the future.

Financial stability has become a focal point for central banks since the global financial crisis. However, the optimal mix between monetary and financial stability policies remains unclear. In this study, the “soft” approach to such policy mix was tested – how often monetary policy (in inflation reports) analyses financial stability issues. This paper aims to discuss the aforementioned objective.

A total of 648 inflation reports published by 11 central banks from post-communist countries in 1998-2019 were reviewed using a text-mining method.

Results show that financial stability topics (mainly cyclical aspects of systemic risk) on average account for only 2%of inflation reports’ content. Although this share has grown somewhat since the global financial crisis (in CZ, HU and PL), it still remains at a low level. Thus, not enough evidence was found on the use of a “soft” policy mix in post-communist countries.

Given the strong interactions between price and financial stability, this paper emphasizes the need to increase the attention of monetary policymakers to financial stability issues.

The study combines two research areas, i.e. monetary policy and modern text mining techniques on a sample of post-communist countries, something which to the best of the authors’ knowledge has not been sufficiently explored in the literature before.

This study aims to explore the management learning during a long-term crisis like a pandemic. The paper addresses both what health-care managers have learnt during the COVID-19 pandemic and how the management learning is characterized.

The paper is based on a qualitative case study carried out during the COVID-19 pandemic at two different public hospitals in Sweden. The study, conducted with semi-structured interviews, applies a combination of within-case analysis and cross-case comparison. The data were analyzed using thematic deductive analysis with the themes, i.e. sensemaking, decision-making and meaning-making.

The COVID-19 pandemic was characterized by uncertainty and a need for continuous learning among the managers at the case hospitals. The learning process that arose was circular in nature, wherein trust played a crucial role in facilitating the flow of information and enabling the managers to get a good sense of the situation. This, in turn, allowed the managers to make decisions meaningful for the organization, which improved the trust for the managers. This circular process was iterated with higher frequency than usual and was a prerequisite for the managers’ learning. The practical implications are that a combined management with hierarchical and distributed management that uses the normal decision routes seems to be the most successful management method in a prolonged crisis as a pandemic.

The gained knowledge can benefit hospital organizations, be used in crisis education and to develop regional contingency plans for pandemics.

This study has explored learning during the COVID-19 pandemic and found a circular process, “the management learning wheel,” which supports management learning in prolonged crises.

This case study sought to investigate the relationship between pre-service teachers’ participation in designing and delivering one-on-one literacy intervention lessons to beginning readers and their own evolving self-efficacy in literacy instruction.

The study was embedded within a 4000-level course in the elementary education major where pre-service teachers learn to administer, analyze and interpret a variety of literacy assessments. Based on the results of these assessments, pre-service teachers designed and implemented literacy lessons (twice a week, 30-min sessions) that addressed the beginning readers' specific instructional needs. Through collecting pre/post data with their first-grade intervention students, and participating in reflective “check-ins” (surveys, a focus group and end-of-course written reflection), a portrait of increased pre-service teacher self-efficacy in literacy instruction comes into focus.

The data showed, primarily through the thematic analysis of qualitative data, that the experience of conducting a one-on-one intervention with a striving reader impacted pre-service teachers’ self-efficacy positively.

The methodology of this study was limited by the small sample size and the low participant response rate on the quantitative survey measure.

This paper highlights one aspect in which clinically-rich field experiences can make a difference in the literacy instruction self-efficacy of pre-service teachers.

This study adds to the support for authentic instructional applications of course content in educator preparation programs, specifically in Professional Development School (partner school system) contexts. The aspect of observing and measuring intervention student progress was one lens through which pre-service teachers viewed their efficacy. Further investigations focusing on other assessment-instruction cycles could provide additional insights.

The purpose of this paper is to provide a guiding framework for studying the travel patterns of PT users. The combination of public transit (PT) users’ travel data and user profiling (UP) technology to draw a portrait of PT users can effectively understand users’ travel patterns, which is important to help optimize the scheduling of PT operations and planning of the network.

To achieve the purpose, the paper presents a three-level classification method to construct the labeling framework. A station area attribute mining method based on the term frequency-inverse document frequency weighting algorithm is proposed to determine the point of interest attributes of user travel stations, and the spatial correlation patterns of user travel stations are calculated by Moran’s Index. User travel feature labels are extracted from travel data containing Beijing PT data for one consecutive week.

In this paper, a universal PT user labeling system is obtained and some related methods are conducted including four categories of user-preferred travel area patterns mining and a station area attribute mining method. In the application of the Beijing case, a precise exploration of the spatiotemporal characteristics of PT users is conducted, resulting in the final Beijing PTUP system.

This paper combines UP technology with big data analysis techniques to study the travel patterns of PT users. A user profile label framework is constructed, and data visualization, statistical analysis and K-means clustering are applied to extract specific labels instructed by this system framework. Through these analytical processes, the user labeling system is improved, and its applicability is validated through the analysis of a Beijing PT case.