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The purpose of this paper is to study price discovery and price convergence in securities trading within a fragmented market environment where stocks are traded on multiple venues. The results provide novel empirical insights questioning the generalizability of the current literature and aim to expand the understanding of price determination in a fragmented market microstructure.

This paper provides an empirical data analysis based on an event study methodology. The authors applied Thomson Reuters Tick History data covering German blue chip stocks listed on multiple venues in 2009 and 2013. Different time aggregations up to one second are applied to provide an in-depth analysis.

The paper empirically discovers a persistent price leader-follower relationship not only during intraday auctions but also in subsequent continuous trading. The authors found that trading on alternative venues instantly dries out in case the dominant market switches to a call auction. In these situations, alternative markets await and adopt the official price signal of the dominant market although prices on alternative venues still indicate a certain extent of price discovery. This phenomenon remains persistent at different levels of market fragmentation, indicating that alternative trading venues fully accept the price leadership role of the dominant market, no matter their own market share.

This paper provides an innovative empirical setup to analyze price co-movement and convergence based on high-frequent data. Further, the results provide novel and robust insights into the price determination process in fragmented markets that clarify the role of price follower and price leader.

Kidney transplantation (KT) is the treatment of choice for end-stage chronic kidney disease (CKD) and is well known to improve the clinical outcome of patients. However, the impact of KT on comorbid psychological symptoms, particularly depression and anxiety, is less clear, and recipients of living-donor (LD) organs may have a different psychological outcome from recipients of dead-donor (DD) organs.

In total, 152 patients were included and analyzed using a cross-sectional design. Of these patients, 25 were pre-KT, 13 were post-KT with a LD transplant and 114 were post-KT with a DD transplant. The patients were tested for a variety of psychometric outcomes using the Hospital Anxiety and Depression Scale, the 12-Item Short Form Health Survey (assessing physical and mental health-related quality of life), the Resilience Scale, the Coping Self-Questionnaire and the Social Support Questionnaire.

The mean age of the patients was 51.25 years and 40 per cent of the patients were female. As expected, the post-KT patients had significantly better scores on the physical component of the Short Form Health Survey than the pre-KT patients, and there were no significant differences between the two post-KT groups. There were no significant differences among the groups in any of the other psychometric outcome parameters tested, including anxiety, depression and the mental component of health-related quality of life.

KT and the origin of the donor organ do not appear to have a significant impact on the psychological well-being of transplant patients with CKD. Although the diagnosis and early treatment of psychological symptoms, such as depression and anxiety, remain important for these patients, decisions regarding KT, including the mode of transplantation, should not be fundamentally influenced by concerns about psychological impairments at the population level.

CKD is a serious condition involving profound impairment of the physical and psychological well-being of patients. KT is considered the treatment of choice for most of these patients. KT has notable advantages over dialysis with regard to the long-term physical functioning of the renal and cardiovascular system and increases the life expectancy of patients. However, the data on the improvement of psychological impairments after KT are less conclusive.

Online education enables location-independent learning, potentially providing university students with more flexible study programs and reducing traffic-related CO₂ emissions. This paper aims to examine whether online education can contribute to university-related sustainable everyday mobility, with particular consideration given to aspects of social sustainability and potential rebound effects. Specifically, it explores sustainability dilemmas that arise from conflicting social and ecological effects.

Drawing on qualitative data from mobility diaries and extensive semistructured interviews (n = 26) collected at Osnabrück University of Applied Sciences in Germany, this study deploys thematic analysis and a typification approach to analyze and classify students’ daily practices related to studying, mobility and dwelling, which may be impacted by online education.

The study identifies six distinct student types with diverse practices in studying, mobility and dwelling. Comparisons between student types reveal stark differences regarding professional and social goals that students associate with their studies, influencing university-related mobility and residential choices. This leads to varying assessments of online education, with some students expecting benefits and others anticipating severe drawbacks.

The typology developed in this paper can assist Higher Education Institutions (HEIs) in comparable contexts in understanding the distinct needs and motivations of students, thereby proactively identifying sustainability dilemmas associated with online education. By leveraging these findings, HEIs can effectively balance diverse interests and contribute meaningfully to sustainability.

To the best of the authors’ knowledge, this study is among the first to systematically investigate conflicts and rebound effects of online education in the context of sustainable mobility within HEIs.

This paper aims to make a systematic review of the manpower prediction model of the construction industry. It aims to determine the forecasting model's development trend, analyse the use limitations and applicable conditions of each forecasting model and then identify the impact indicators of the human resource forecasting model from an economic point of view. It is hoped that this study will provide insights into the selection of forecasting models for governments and groups that are dealing with human resource forecasts.

The common search engine, Scopus, was used to retrieve construction manpower forecast-related articles for this review. Keywords such as “construction”, “building”, “labour”, “manpower” were searched. Papers that not related to the manpower prediction model of the construction industry were excluded. A total of 27 articles were obtained and rated according to the publication time, author and organisation of the article. The prediction model used in the selected paper was analysed.

The number of papers focussing on the prediction of manpower in the construction industry is on the rise. Hong Kong is the region with the largest number of published papers. Different methods have different requirements for the quality of historical data. Most forecasting methods are not suitable for sudden changes in the labour market. This paper also finds that the construction output is the economic indicator with the most significant influence on the forecasting model.

The research results discuss the problem that the prediction results are not accurate due to the sudden change of data in the current prediction model. Besides, the study results take stock of the published literature and can provide an overall understanding of the forecasting methods of human resources in the construction industry.

Through this study, decision-makers can choose a reasonable prediction model according to their situation. Decision-makers can make clear plans for future construction projects specifically when there are changes in the labour market caused by emergencies. Also, this study can help decision-makers understand the current research trend of human resources forecasting models.

Although the human resource prediction model's effectiveness in the construction industry is affected by the dynamic change of data, the research results show that it is expected to solve the problem using artificial intelligence. No one has researched this area, and it is expected to become the focus of research in the future.

Cosmopolitanism represents a complex, multilevel, multilayer phenomenon manifested in a variety of social spheres, including moral, political, social, and cultural. Yet, despite its prominence in other disciplines, cosmopolitanism has received relatively scant attention in international management research. Furthermore, the understanding of cosmopolitanism as an ever-present social condition in which individuals are embedded lags significantly behind.

In this chapter, we develop a conceptual framework for cosmopolitanism as an individual-level phenomenon situated at the intersection of the moral, political, and sociocultural perspectives. The framework explicates the interrelations between macrolevel dynamics and individual experiences in a globalized world. We conceptualize cosmopolitanism as an individual disposition manifested and enacted through identities, attitudes, and practices. We also highlight the diversity of individuals who can be considered cosmopolitans, including those who may not possess the classic cosmopolitan CV. Finally, the chapter explores the implications of cosmopolitanism for global organizations and global leadership.

This study investigates whether and when during the life cycle women fall behind in terms of career progression because of children. We use 1987–1997 Norwegian panel data that contain information on individuals’ position in their career hierarchy as well as a direct measure of their promotions. We measure overall promotions as increases in rank within the same establishment as well as in combination with an establishment change. Women with children are 1.6 percentage points less likely promoted than women without children; this is what we refer to as the family gap in climbing the career. We find that mothers tend to enter on lower ranks than non-mothers. Thirty-seven percent of the gap can be explained by rank fixed effects and human capital characteristics. A large part remains unexplained. Graphical analyses show that part of the difference already evolves during the early career. Part of this seems related to the relatively low starting ranks.

The purpose of this paper is to develop a framework and a reference process for achieving channel alignment in companies that use traditional and electronic marketing channels. Instruments for gathering and structuring of information on channel deployment are proposed and integrated in the process of strategy formulation.

The research grounds on a conceptual model of strategic channel alignment (MSCA) that is a recently proposed modification of the well‐established strategic alignment model (SAM). Framework, instruments, and reference process were developed by drawing on results from literature analysis and experiences gathered in a research and consulting project at a large multinational corporation. The case context is explicated.

The developed management tools were successfully applied in strategic business units of the case company. They were found to be useful for facilitating strategic channel alignment by fostering processes of communication and collaboration between managers across organizational units. The framework helps to implement a common “strategy language” on multi channel management. The instruments support the creation of a shared information base on a company's multi channel strategy and operations.

The paper contributes to research on strategic alignment processes and discusses model‐driven alignment as social process that aims at the construction of a common understanding of multi channel issues. The beneficial role of management tools in such processes is spelled out.

The generic nature of the proposed management tools makes further practical applications possible. Companies that strategically address the alignment of their marketing channels can utilize the methodology and adapt it to their specific needs.

The paper translates a conceptual management model into a practical methodology. Models like the SAM and the MSCA are frequently discussed but research and reports on their practical value has been scarce. This paper contributes to filling this gap and develops tools of practical value in a particular domain of strategic management.

Tens of thousands of news articles are posted online each day, covering topics from politics to science to current events. To better cope with this overwhelming volume of information, RSS (news) feeds are used to categorize newly posted articles. Nonetheless, most RSS users must filter through many articles within the same or different RSS feeds to locate articles pertaining to their particular interests. Due to the large number of news articles in individual RSS feeds, there is a need for further organizing articles to aid users in locating non‐redundant, informative, and related articles of interest quickly. This paper aims to address these issues.

The paper presents a novel approach which uses the word‐correlation factors in a fuzzy set information retrieval model to: filter out redundant news articles from RSS feeds; shed less‐informative articles from the non‐redundant ones; and cluster the remaining informative articles according to the fuzzy equivalence classes on the news articles.

The clustering approach requires little overhead or computational costs, and experimental results have shown that it outperforms other existing, well‐known clustering approaches.

The clustering approach as proposed in this paper applies only to RSS news articles; however, it can be extended to other application domains.

The developed clustering tool is highly efficient and effective in filtering and classifying RSS news articles and does not employ any labor‐intensive user‐feedback strategy. Therefore, it can be implemented in real‐world RSS feeds to aid users in locating RSS news articles of interest.

Virtual teams are becoming a norm in current knowledge-based society and offer a wide range of organizational benefits. This paper aims to investigate the effects of leaders’ motivating language (ML) and feedback approach on virtual team members’ creativity performance.

A 2×2 with pre-test and post-test experimental design was employed to explore how to stimulate virtual team members’ creativity performance using a group decision support system.

The results show that leaders’ ML and feedback approach via e-mail instructions have different interaction effects on members’ creativity and idea generation performance. Team members receiving direction-giving instructions generate more ideas under the demanding feedback approach and team member receiving instructions with more empathetic language exhibit higher creativity performance under the encouraging feedback approach.

Shortcomings of virtual environment and leadership remain the major factors influencing such findings. Since the results are also restrained by the functionality of the utilized software tool, tools for virtual teams are recommended to include features that can support the effective use of team leaders’ motivational language.

Virtual team leaders should provide proper guidance to members using understanding and empathetic wording approach. For task-oriented work, leaders should consider giving more specific instructions and provide constant feedback for completed work. For creative work, leaders should give positive encouragement as feedback or even challenge team members to stimulate their creativity. Additionally, facilitation rules can be set up in advance so that the intelligent agent can timely send out follow-up instructions/feedback.

The gained insights beneficially help tool developers for virtual teams build/enhance their tools based on the need of team leaders. This paper also usefully offers important implications regarding how to motivate virtual team members’ creative thinking.