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The purpose of the study is to investigate, synthesize and critically evaluate empirical research findings on the behavioral traits of fund managers from 1994 to 2024. The ultimate goal is to provide a unified body of literature on three broad topics: first, fund managers' demographic and professional characteristics, such as age, gender, level of education and years of industry experience; second, fund managers' social and political connections; and third, fund managers' behavioral biases that lead to irrational investment decisions.

The relevant papers from selected journals were discovered and manually validated using the Scopus database. From 317 retrieved documents, 57 relevant articles were chosen and analyzed after the forward and backward search of the existing articles.

This paper presents a categorized summary of behavioral factors that have gained a foothold in influencing the behavior of fund managers in fund management research, with several studies demonstrating their significance leading to improved prediction and model precision, as this review indicates. In addition, the study summarized the contributions of prior empirical studies within the aforementioned three major categories and illustrated their consequences.

The present study contributes to the understanding of the effects of behavioral finance theories on fund managers by providing meaningful explanations of their behavioral traits based on empirical evidence and existing trends and knowledge gaps, both of which can influence the future direction of research.

This study explores the contagion of greenwashing strategies among ESG mutual funds. It investigates how the greenwashing behaviors of peer funds within the same family influence a fund’s decision to engage in greenwashing. The research also examines the impact of greenwashing on genuine ESG funds and explores the mechanisms through which greenwashing strategies spread across ESG mutual funds.

This paper employs a two-stage least squares regression model with cross-fund returns standard deviation as an instrumental variable to disentangle the peer effects of greenwashing from family-level characteristics. The analysis incorporates various fund characteristics and introduces four contagion channels through which greenwashing may influence genuine ESG funds.

The study finds greenwashing behavior in ESG funds is positively influenced by similar practices within their fund family. Larger assets under management and older funds with higher management fees show resilience against greenwashing influences, while team-managed funds are more susceptible. Additionally, socially responsible investors struggle to distinguish between genuine and greenwashing ESG funds, which may contribute to the persistence of greenwashing practices.

This paper contributes to the literature by delineating the mechanisms of greenwashing contagion within ESG mutual funds. It also examines the demand-side incentives for adopting greenwashing strategies, offering insights into the implications for fund flows and investor behavior. This study is among the first to analyze the contagion effects of greenwashing strategies across an extensive network of ESG funds, enriching our understanding of the broader impacts of greenwashing in the context of socially responsible investing.

Financial satisfaction is a potential ambition of individuals' lives that requires well-strategized economic behaviors. The authors examine the impact of various factors on the financial behavior (FB) and financial satisfaction (FIS) of individuals in India's National Capital Region (NCR).

Through a literature review, a survey questionnaire was formulated using existing scales on FIS. For more in-depth insights, data are obtained from 427 respondents in the NCR region using self-administered questionnaires. This article used “partial least square structural equation modeling (PLS-SEM)” to inspect the hypothesized model of individuals' FIS.

According to the study results, financial attitude (FA), financial self-efficacy (FSE), financial knowledge (FK) and demographic characteristics (DC) significantly influence FB. Conversely, financial stress (FS) negatively impacts FB. It also highlights that FA, FSE, FK and FB all significantly impact FIS. Nevertheless, FS and DC insignificantly influence FIS.

To the best knowledge of the authors, this article is an initial attempt to offer a novel perspective of individuals' FB and FIS in India. It would help the government and stakeholders by providing various pioneering economic schemes and making policies that help increase individuals' FIS.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-03-2023-0239

The paper examines the recent trends in information technology for combating corruption and its impact on the Indian economy. It further explores how technology is being used to tackle corruption in India and the resulting economic benefits.

The methodology encompasses qualitative analysis to investigate corruption comprehensively. It involves content analysis of corruption-related documents, case studies, and expert interviews. Recent information technological advancements are explored, including blockchain and AI, for their anti-corruption potential.

This study reveals that the negative impacts of corruption on society include reduced economic growth, weakened institutions, and decreased public trust in government. Various technological advancements such as e-governance, blockchain, AI, and big data analytics have been implemented to enhance transparency and accountability in government processes. Special cases and examples of application of such technology tools and techniques adopted by the organizations to control corruption are discussed.

This paper highlights the need for legal reforms, institutional strengthening, and awareness-raising campaigns to complement technological advancements in the fight against corruption.

This study investigates the multifaceted barriers and facilitators affecting research data sharing across the research data lifecycle. It aims to broaden the understanding of data sharing beyond the publication phase, emphasizing the continuous nature of data sharing from generation to reuse.

Employing a mixed-methods approach, the study integrates the Theory of Planned Behavior, the Technology Acceptance Model, and the Institutional Theory to hypothesize the influence of various factors on data sharing behaviors across the lifecycle. A questionnaire survey and structural equation modeling are utilized to empirically test these hypotheses.

This study identifies critical factors influencing data sharing at different lifecycle stages, including perceived behavioral control, perceived effort, journal and funding agency pressures, subjective norms, perceived risks, resource availability, and perceived benefits. The findings highlight the complex interplay of these factors and their varying impacts at different stages of data sharing.

This study illuminates the dynamics of research data sharing, offering insights while recognizing its scope might not capture all disciplinary and cultural nuances. It highlights pathways for stakeholders to bolster data sharing, suggesting a collaborative push towards open science, reflecting on how strategic interventions can bridge existing gaps in practice.

This study offers actionable recommendations for policymakers, journals, and institutions to foster a more conducive environment for data sharing, emphasizing the need for support mechanisms at various lifecycle stages.

This study contributes to the literature by offering a comprehensive model of the research data lifecycle, providing empirical evidence on the factors influencing data sharing across this continuum.

This study aims to ascertain the personal characteristics of a group of successful academic entrepreneurs in a South African university enterprise and the prevalent barriers and enablers to their entrepreneurial endeavour.

The authors used a Delphi process to identify and rank the characteristics, enablers, barriers and behaviours of entrepreneurial academics, with a Nominal Group Technique applied to establish challenges they encounter managing their enterprise and to propose solutions.

Perseverance, resilience and innovation are critical personal characteristics, while collaborative networks, efficient research infrastructure and established research competence are essential for success. The university’s support for entrepreneurship is a significant enabler, with unnecessary bureaucracy and poor access to project and general enterprise funding an impediment. Successful academic entrepreneurs have strong leadership, and effective management and communication skills.

The main limitation is the small study participant group drawn from a single university enterprise, which complicates generalisability. The study supported the use of Krueger’s (2009) entrepreneurial intentions model for low- and middle-income country (LMIC) academic entrepreneur investigation but proposed the inclusion of mitigators to entrepreneurial activation to recognise contextual deficiencies and challenges.

Skills-deficient LMIC universities should extensively and directly support their entrepreneurial academics to overcome their contextual deficiencies and challenging environment.

This study contributes to addressing the paucity of academic entrepreneur research in LMIC contexts by identifying LMIC-specific factors that inhibit the entrepreneur’s movement from entrepreneurial intention to entrepreneurial action.

This study aims to highlight the growth and development of Indo-German collaborative research over the past three decades. Moreover, this study encompasses an in-depth examination of funding acknowledgements to gain valuable insights into the financial support that underpins these collaborative endeavours. Together with this paper, the authors provide an openly accessible data set of Indo-German research papers for further and reproducible research activities (the “Indo-German Literature Dataset”).

The data were retrieved from the Web of Science (WoS) database from the year 1990 till the 30th of November 2022. A total of 36,999 records were retrieved against the used query. Acknowledged entities were extracted using a named entity recognition (NER) model specifically trained for this task. Interrelations between the extracted entities and scientific domains, lengths of acknowledgement texts, number of authors and affiliations, number of citations and gender of the first author, as well as collaboration patterns between Indian and German funders were examined.

The study reveals a consistent and increasing growth in the publication trend over the years. The study brings to light that Physics, Chemistry, Materials Science, Astronomy and Astrophysics and Engineering prominently dominate the Indo-German collaborative research. The USA, followed by England and France, are the most active collaborators in Indian and German research. Largely, research was funded by major German and Indian funding agencies, international corporations and German and American universities. Associations between the first author’s gender and acknowledged entity were observed. Additionally, relations between entity, entity type and scientific domain were discovered.

The study paves the way for enhanced collaboration, optimized resource utilization and societal advantages by offering a profound comprehension of the intricacies inherent in research partnerships between India and Germany. Implementation of the insights gleaned from this study holds the promise of cultivating a more resilient and influential collaborative research ecosystem between the two nations.

The study highlights a deeper understanding of the composition of the Indo-German collaborative research landscape of the past 30 years and its significance in advancing scientific knowledge and fostering international partnerships. Furthermore, the authors provide an open version of the original WoS data set. The Indo-German Literature Data set consists of 22,844 papers from OpenAlex and is available for related studies like literature studies and scientometrics.

This study analyses how different forms of online accountability – hierarchical/individualising, hierarchical/calculative and socialising accountability – influence online financing success of non-profit organisations (NPOs).

The study is based on 797 NPOs’ projects listed on three international crowdfunding platforms providing space for NPOs to present, account for and fund social projects.

Results show that accountability forms developed online play significantly different roles in NPOs’ financing. While online hierarchical/individualising and socialising accountability enhance NPO funding, hierarchical/calculative accountability reduces financing success.

The empirical analysis is limited to the specific research context. However, the research provides theoretical and practical insights for the accounting literature.

The paper recommends that NPOs invest more in explaining their past and future activities rather than reporting on pure financial performances, as this may lead to stakeholders’ perception of mission drift and reduce financing success.

This research enhances the understanding of online accountability and its significance in securing financial resources for NPOs by highlighting the necessity of examining various accountability forms individually, as they may serve distinct functions in the financial sustenance of NPOs.

The purpose of this paper is to understand US federal government policy during the early stages of the COVID-19 pandemic and the connections to graduate education. Using the multiple streams framework, the paper outlines these actions through various streams (problems, policy and political) and perspectives (defining problems, articulating options and mobilizing responses).

The primary sources of data collected for this study were US federal government policies from March 2020 through May 2021. Policies were examined through introduction, implementation and alteration (when possible) within the specific time period of the study. The policies outlined in this paper were connected to the US Department of Education, and to a lesser extent, the National Institutes of Health, the National Science Foundation and other federal agencies. Data analysis was a two-fold process. First, the individual policy was considered as a single case and second, a cross-case comparison occurred across the multiple cases.

Analysing the study’s data in the problem stream provides a strong indicator of how the pandemic was perceived as a challenge for US graduate education. The pandemic served as a focusing event and illuminated the connections of graduate education to key institutional functions, including research and teaching. Broadly, US federal policy actions in this area focused on giving institutions resources and flexibility to support graduate students and allow them to continue their academic work while also seeding funding and incentives to continue the movement of knowledge, activities and people in the research pipeline. Actions in the policy stream aligned with the decentralized nature of the US higher education system and allowed for choice by academic institutions within the parameters of options.

This paper extends extant literature related to policy-making and graduate education to consider policy-making during a time of crisis. The paper offers methodological and conceptual ideas for consideration in future research.

The present study reviews the literature on the history and evolution of investment strategies in the stock market for the period from 1900 to 2022. Conflicts and relationships arising from such diverse seminal studies have been identified to address the research gaps.

The studies for this review were identified and screened from electronic databases to compile a comprehensive list of 200 relevant studies for inclusion in this review and summarized for the cognizance of researchers.

The study finds a coherence to complex theoretical documentation of more than a century of evolution on investment strategy in stock markets, capturing the characteristics of time with a chronological study of events.

There were complications in locating unpublished studies leading to biases like publication bias, the reluctance of editors to publish studies, which do not reveal statistically significant differences, and English language bias.

Practitioners can refine investment strategies by incorporating behavioral finance insights and recognizing the influence of psychological biases. Strategies span value, growth, contrarian, or momentum indicators. Mitigating overconfidence bias supports effective risk management. Social media sentiment analysis facilitates real-time decision-making. Adapting to evolving market liquidity curbs volatility risks. Identifying biases guides investor education initiatives.

This paper is an original attempt to pictorially depict the seminal works in stock market investment strategies of more than a hundred years.