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Online question-and-answer (Q&A) communities serve as important channels for knowledge diffusion. The purpose of this study is to investigate the dynamic development process of online knowledge systems and explore the final or progressive state of system development. By measuring the nonlinear characteristics of knowledge systems from the perspective of complexity science, the authors aim to enrich the perspective and method of the research on the dynamics of knowledge systems, and to deeply understand the behavior rules of knowledge systems.

The authors collected data from the programming-related Q&A site Stack Overflow for a ten-year period (2008–2017) and included 48,373 tags in the analyses. The number of tags is taken as the time series, the correlation dimension and the maximum Lyapunov index are used to examine the chaos of the system and the Volterra series multistep forecast method is used to predict the system state.

There are strange attractors in the system, the whole system is complex but bounded and its evolution is bound to approach a relatively stable range. Empirical analyses indicate that chaos exists in the process of knowledge sharing in this social labeling system, and the period of change over time is about one week.

This study contributes to revealing the evolutionary cycle of knowledge stock in online knowledge systems and further indicates how this dynamic evolution can help in the setting of platform mechanics and resource inputs.

The purpose of this paper is twofold: (1) to map and analyze existing complexity typologies and (2) to develop a framework for characterizing complexity-based approaches.

This study was conducted in three stages: (1) initial identification of typologies related to complexity following a structured procedure based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol; (2) backward and forward review to identify additional relevant typologies and (3) content analysis of the selected typologies, categorization and framework development.

Based on 17 selected typologies, a comprehensive overview of complexity studies is provided. Each typology is described considering key concepts, contributions and convergences and differences between them. The epistemological, theoretical and methodological diversity of complexity studies was explored, allowing the identification of the main schools of thought and authors. A framework for characterizing complexity-based approaches was proposed including the following perspectives: ontology of complexity, epistemology of complexity, purpose and object of interest, methodology and methods and theoretical pillars.

This study examines the main typologies of complexity from an integrated and multidisciplinary perspective and, based on that, proposes a novel framework to understanding and characterizing complexity-based approaches.

The purpose of this study is to conduct a systematic review of the literature of the studies that have examined several theoretical perspectives on corporate social performance (CSP) and identify possible future research questions based on various theoretical viewpoints.

The study used systematic literature review analysis on a sample of 667 studies published in top A* and A category journals listed in the Australian Business Dean Council list. The present study derived articles between 1975 and 2023 from the SCOPUS database by using relevant keywords to identify research activities in CSP.

The findings suggest that many studies on CSP have been undertaken globally. But there is a lack of studies on various theoretical perspectives, including peer uncertainty evaluation, buyer–supplier sustainability links, the role of primary stakeholders (especially consumers, employees, suppliers and secondary stakeholders), the use of technology, firm-related heterogeneities, and the role of demographic and socio-economic factors. Future research areas are recommended.

The study investigates existing research gaps to identify possible future research questions and frameworks that can be explored to advance the research on CSP.

The research also provides implications for firms in terms of understanding diverse theoretical perspectives to develop strategies to improve a firm’s social performance.

The findings are derived from a systematic review of the literature in top-category studies that examined existing theories and frameworks in the CSP domain. This highlights the importance of other understudied complementary theories, such as complexity theory, spillover theory, critical mass theory, slack theory and so on, and related variables that can improve a firm’s social performance. Evaluation of existing theoretical perspectives is not included in other review studies.

Purpose: The present study aims to test the Quadratic Programming model for Optimal Portfolio selection empirically.

Need for the Study: All the investors who buy financial products are motivated to obtain higher profits or, in other words, to maximise their returns. However, the high returns are often accompanied by higher risks, and avoiding such risks has become the primary concern for all investors. There is a great need for such a model to maximise profits and minimise risk, which can help design an investment portfolio with minimum risk and maximum return. The Quadratic Programming model is one such model which can be applied for selected shares to build an optimised portfolio.

Methodology: This study optimises the stock samples using a two-level screening of correlation coefficient and coefficient of variation. The monthly closing prices of the NSE-listed Indian pharmaceutical stocks from December 2019 to January 2022 have been used as sample data. The Lagrange Multiplier method is used to apply the model to achieve the optimal portfolio solution. Based on the market reality, the transaction costs have also been considered. The Quadratic programming model is further optimised to achieve the optimal portfolio for the select stocks.

Findings: The traditional portfolio theory and the modified quadratic model gives similar and consistent results. In other words, the modified quadratic model asserts the accuracy of the conventional portfolio model. The portfolio constructed in the present study gives a return much higher than the return of the benchmark portfolio of Nifty Fifty, indicating the usefulness of applying the Quadratic Programming model.

Practical Implications: The construction of an optimal portfolio using the traditional or modified Quadratic model can help investors make rational investment decisions for better returns with lower risks.

This paper aims to map the research on management accounting (MA), clarifying its current role and identifying gaps and opportunities for future research.

In this paper, 784 papers were reviewed for the 1958–2019 period, published in 220 scientific journals indexed on Clarivate Analytics’ Web of Science (Science Citation Index Expanded [SCI-EXPANDED] and Social Sciences Citation Index [SSCI]). In the process, content analysis, regression analysis and bibliometric analysis were used.

The most relevant journals, authors and topics in MA, along with trends and patterns in the literature, were identified. Seven clusters that represent the overall thematic research structure of the MA field were also identified. This study shows that MA is becoming a multidimensional management decision-support instrument covering all organizational dimensions. As such, the research on MA is following the recent concerns with the sustainable development and digitalization of business processes.

Based on the findings of this research study, theoretical and practical implications for MA researchers were provided. These findings could also be useful to industry practitioners to improve their knowledge of emerging trends in MA practices, strategies and concepts.

Based on bibliometric and content analysis, a framework that shows an organizational, market and social context for the evolution of MA over the past 60 years was provided. It highlights the dynamics of MA alignment with organizational and external environment changes. Future research opportunities and implications for researchers and practitioners were also identified.

The purpose of this research was to investigate how VR-mediated sports, as opposed to 2-D screens, affect the emotional and cognitive experiences of fans with the game and its sponsors.

The current study employed a single-factorial experimental design, in which participants were randomly assigned to either watch a soccer game through a VR headset or a 2-D screen. Physiological and self-reported measures were used to measure levels of presence, arousal, attention and memory.

Participants who watched sports through VR experienced a higher level of presence, greater psychophysiological arousal, and exhibited higher levels of attention toward the game. However, they showed lower recognition for in-stadium signage compared to those who watched the game on a 2-D screen.

The results suggest that sports teams can use VR to create a more immersive and engaging experience for fans. Additionally, in-stadium signage advertising may not be as effective in VR sport broadcasting contexts, and sports practitioners may want to explore alternative forms of advertising that are better suited for VR environments.

Methodologically, this study used a combination of self-reported and real-time physiological measures to capture dynamic and spontaneous changes in fans while watching games. Theoretically, this study utilized the Dynamic Human-Centered Communication System Theory to adopt a human-centered approach to understand how VR impacts the experience of sport game viewers.

The purpose of this research is to examine how a change in team dynamics impacts an individual's motivation to engage in helping behavior and operational performance.

An online vignette experiment and a hybrid discrete event and agent-based simulation model are used.

Study findings demonstrate how a non-core worker's perception of team dynamics influence engagement in helping behavior and system performance.

This study provides a further understanding on how team members react to changes in team processes. This study theorizes on how an individual team member responds to fairness concerns. This study also advances our understanding of the critical importance of helping behavior in a retail logistics setting. This research illustrates how the theory of strategic core and procedural justice literature can be adopted to explain team dynamics in supply chain management.