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This study aims to analyze the performance of quality indices to continuously validate a predictive model focused on the control chart classification.

The research method used analytical statistical methods to propose a classification model. The project science research concepts were integrated with the statistical process monitoring (SPM) concepts using the modeling methods applied in the data science (DS) area. For the integration development, SPM Phases I and II were associated, generating models with a structured data analysis process, creating a continuous validation approach.

Validation was performed by simulation and analytical techniques applied to the Cohen’s Kappa index, supported by voluntary comparisons in the Matthews correlation coefficient (MCC) and the Youden index, generating prescriptive criteria for the classification. Kappa-based control charts performed well for m = 5 sample amounts and n = 500 sizes when Pe is less than 0.8. The simulations also showed that Kappa control requires fewer samples than the other indices studied.

The main contributions of this study to both theory and practitioners is summarized as follows: (1) it proposes DS and SPM integration; (2) it develops a tool for continuous predictive classification models validation; (3) it compares different indices for model quality, indicating their advantages and disadvantages; (4) it defines sampling criteria and procedure for SPM application considering the technique’s Phases I and II and (5) the validated approach serves as a basis for various analyses, enabling an objective comparison among all alternative designs.

The complex world in which we reside is calling for more critical approaches to address the precarity experienced by the most marginalized in social systems. However, human resource development (HRD) lacks empirical data to describe, define and project the objectives and future directions of Critical HRD in today’s turbulent and volatile times. Therefore, the purpose of this study is to examine the historical and contemporary progression of Critical HRD, as described by nine of its most well-known scholars.

Data were collected through semistructured interviews, and a constructivist grounded theory coding approach was applied during analysis to identify themes and patterns.

The findings of this study highlight the persistent scholarship versus practice divide among Critical HRD scholars, suggesting that Critical HRD may merely be an academic undertaking and something not practiced within the public domain. The authors call for an evolution of Critical HRD toward more practice- and action-oriented approaches to scholarship and teaching so that meaningful changes can take place in actual organizations and workplaces.

To the best of the authors’ knowledge, this study was the first to empirically show that there is a real research–practice gap, particularly among Critical HRD scholars. Critical HRD scholars need to take these findings seriously as an opportunity to reflect on how they can take Critical HRD to the next level beyond academic discourse.

The integration of social media and e-commerce has resulted in a rising phenomenon among individual content providers (ICPs), who used to offer free content, to provide consumers with paid content, such as online courses, Q&As or consultations. Despite the prevalence of ICPs’ content monetization, empirical research has rarely studied its underlying mechanism. This paper examines how the characteristics of free content contributed by ICPs on social media platforms influence their paid content sales, focusing on the perspective of human brand.

The empirical setting is an online knowledge exchange platform, where users are allowed to provide free content (e.g. answers) on the social media platform and launch paid content (e.g. lectures) on the e-commerce platform. A machine learning technique is employed to construct measures for the characteristics of free content, and fixed-effects estimation is presented to confirm which factors have a significant influence on the sales of paid content.

The empirical results show that the quality, diversity and expertness of free content have a significant positive impact on the sales of the ICP-paid content, with the brand popularity of ICP playing a mediating role.

This study is the first attempt to demystify the relationship between content contribution and ICPs’ content monetization from the perspective of human brand. The findings validate the effectiveness of the “Selling by Contribution” strategy and provide valuable insights for ICPs and social media platforms.

Transformative generative artificial intelligence (AI) tools, such as ChatGPT, have revolutionized various sectors, including higher education. Since its release in November 2022, it has gathered attention from academia, scholars, students, regulators and education policymakers. Opinions diverge on whether ChatGPT’s use in academia should be circumscribed or regulated. To offer insights into some of these, this study synthesizes 139 contributions (articles and blogs) authored by instructors, publishers, professors, editors and education journalists in the education domain.

The study uses sentiment analysis and topic modelling to examine the 139 articles and blogs. Drawing on their insights, it firstly explores emotional dimensions of the content. Subsequently, using critical discourse analysis, it integrates them with emerging concerns (what and why), and explicates key processes (how) to inform academia, research, practice and policy.

Drawing on the results obtained from sentiment analysis, the study identifies that the overall sentiments surrounding generative AI tools such as ChatGPT in higher education are more positive (33%) than negative (11%). Using topic modelling, the study further highlights four thematic areas to explore benefits and challenges: perceptions and biases, pedagogical impact, ethical considerations and implementation and adoption.

Limitations include the absence of student perspectives, which may offer deeper insights into perception, pedagogical impacts, and integrity-related issues. Additionally, while findings are applicable across various domains, specialized areas may present differing insights that could refine the conclusions.

Overall, contributors acknowledge the capabilities of generative AI tools like ChatGPT in enhancing students’ productivity. The findings suggest that it is likely to offer significant gains in the education domain, providing several benefits to both teachers and students. Nevertheless, they also consider its limitations, discrimination and bias, copyright infringement, plagiarism, fabricated unauthentic textual content and assessment bias.

This paper investigates the intersectionality of entrepreneurial masculinity within the context of venture accelerators. As such, it aims to shed light on how intersecting factors influence the construction and expression of masculinity among male entrepreneurs in venture accelerators.

This research is based on an in-depth analysis of four distinct accelerator cohort groups, employing a semi-structured interview approach. Interviewees were conducted with four accelerator managers and 52 male accelerator participants across four distinct accelerator cohort groups. Such a methodological choice is deemed instrumental in unravelling the nuanced dynamics within accelerator environments and their implications on hegemonic masculinity.

This study elucidates the nuanced ways in which men navigate the venture accelerator landscape. The findings revealed that the accelerator environment facilitated the reinforcement of traditional masculine behaviours. Whilst diversity was ostensibly valued, its acceptance decreased if it posed a challenge to male dominance or stereotypical masculine traits. Indeed, there was marginalisation of nontraditional expressions of masculinity, leading to a sense of “othering”.

By integrating intersectionality theory into the examination of masculine dynamics within venture accelerator contexts, this study expands current understanding of venture accelerator environments and their effects on both traditional and nontraditional forms of hegemonic masculinity. In particular, we highlight the impact of non-intersectional institutional norms on male entrepreneurs who deviate from traditional stereotypes. As such, we advance the understanding of venture accelerators by examining how they perpetuate and reinforce traditional masculine norms, even in environments that strive for diversity.

This study reviews and discusses the accounting literature that analyzes the role of auditors and enforcers in the context of fraud.

This literature review includes both qualitative and quantitative studies, based on the idea that the findings from different research paradigms can shed light on the complex interactions between different financial reporting controls. The authors use a mixed-methods research synthesis and select 64 accounting journal articles to analyze the main proxies for fraud, the stages of the fraud process under investigation and the roles played by auditors and enforcers.

The study highlights heterogeneity with respect to the terms and concepts used to capture the fraud phenomenon, a fragmentation in terms of the measures used in quantitative studies and a low level of detail in the fraud analysis. The review also shows a limited number of case studies and a lack of focus on the interaction and interplay between enforcers and auditors.

This study outlines directions for future accounting research on fraud.

The analysis underscores the need for the academic community, policymakers and practitioners to work together to prevent the destructive economic and social consequences of fraud in an increasingly complex and interconnected environment.

This study differs from previous literature reviews that focus on a single monitoring mechanism or deal with fraud in a broadly manner by discussing how the accounting literature addresses the roles and the complex interplay between enforcers and auditors in the context of accounting fraud.

This study examines the motivational processes of charged behavior and collective efficacy driving interdependence and agency in new product development (NPD) teams and the moderating impact of team risk-taking propensity as affective, cognitive and behavioral social processes support team innovation.

Data were collected from 92 NPD teams engaged in B2C and B2B product and service development. Mediating and moderating effects are examined using partial least squares structural equation modeling, referencing social cognitive and collective agency theories as the research framework.

The analysis validates collective self-efficacy and charged behavior as interdependent motivational–affective processes that align cognitive resources and govern team effort toward innovativeness. Teams' risk-taking propensity regulates behavior, and collective efficacy facilitates self-regulated motivational engagement. Charged behavior cultivates the emotional contagion, team identification, cohesion and adaptation required for team functioning. Team potency fosters cohesiveness, while team learning improves adaptability along the innovation journey. The resulting theory asserts that motivational drivers enhance the interplay between cognitive and behavioral processes.

Managers should consider NPD teams as social systems with a capacity for collective agency nurtured through interdependence, which requires collective efficacy and shared competencies to generate motivational purpose and innovativeness. Managers must remain mindful of teams' risk tolerance as regulating the impact of motivational factors on innovativeness.

This study contributes to research on the motivational–affective drivers of NPD charged behavior and collective efficacy as complementary to cognitive and behavioral processes sustaining team innovativeness.

The purpose of this paper is to contribute to science communication literature by further highlighting the underexplored role of organizational and corporate perspectives in science communication.

The paper takes the form of a conceptual article that uses two illustrative vignettes to highlight the power of corporate science communication.

The key argument is that corporate science communication is a compound ideology that results from merging the hegemonic corporate voice with the ultimate/god-term science (see the work of Kenneth Burke) to form a mega-ideological construct and discourse. Such communication can be so powerful that vulnerable publics and powerful advocates speaking on their behalf have little to no recourse to effectively challenge such discourse. While critiques of corporate science communication in practice are not new, what the authors offer is a possible explanation as to why such discourse is so powerful and hard to combat.

The value of this paper is in the degree to which it both sets an important applied research agenda for the field and fills a critical void in the science communication literature. This conceptual article, in the form of a critical analysis, fills the void by advocating for the inclusion of organizational perspectives in science communication research because of the great potential that organizations have, via science communication, to shape societal behavior and outcomes both positively and negatively. It also coins the terms “compound ideology” and “mega-ideology” to denote that while all ideologies are powerful, ideologies can operate in concert (compound) to change their meaning and effectiveness. By exposing the hegemonic power of corporate science communication, future researchers and practitioners can use these findings as a foundation to combat misinformation and disinformation campaigns wielded by big corporate science entities and the public relations firms often hired to carry out these campaigns.

Alongside its remarkable growth, problematic Bitcoin investment (BI) behavior and its associated negative consequences have become prevalent, and only a few studies have examined it. Therefore, this study aims to examine problematic BI behavior by investigating its specific antecedents and consequences and identifying which antecedents were more influential in it. In addition, we also examine the role of financial literacy on the relationship between the antecedents and problematic BI behavior.

We collected survey data from 413 investors with Bitcoin investment experience in 2018, when a Bitcoin frenzy occurred. The partial least squares method was used to test the proposed research model.

The results show that prudent, negative urgency, overexpectation and sensation seeking are positively associated with problematic BI behavior, while restraint is negatively associated. Problematic BI behavior is negatively related to investor well-being. Our findings also indicate that both objective and subjective financial literacy moderate the relationship between the antecedents and problematic BI behavior. Four types of investors in terms of their objective and subjective Bitcoin knowledge show different patterns in the relationship between the antecedents and problematic BI behavior.

This study offers insights for researchers by providing a deeper understanding of the contextual antecedents of problematic BI behavior and the role of financial literacy in it. This study provides detailed implications for financial institutions, policymakers, and regulators to guide rational Bitcoin investment behaviors.

This study examines the impact of climate legislation on green agricultural production and tests the heterogeneous impact of different types of climate legislation on agricultural green production.

In this study, the super-slacks-based measure (super-SBM) model is used to calculate agricultural green total factor productivity (AGTFP). The impact of climate legislation (including legislative acts and executive orders) on AGTFP is examined through regression analysis. The transmission mechanism of climate legislation affecting agricultural green production is further investigated.

This study shows that climate legislation has a positive long-term effect on AGTFP. It stimulates innovation in agricultural green technology but has a negative impact on resource allocation efficiency. Executive orders have a more significant effect on AGTFP than climate legislative acts. The effectiveness of climate legislation is more significant in countries with stronger legislation. Moreover, climate legislation reduces AGTFP in low-income countries while enhancing AGTFP in high-income countries. This effect is most prominent in upper-middle-income countries.

This study examines the different effects of various types of climate legislation, considering the level of economic development and the strength of the legal system on AGTFP. The findings can offer a global perspective and insights for China’s policymaking.