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This research explores the key factors that contribute to the success of Black students in a predominantly White institution (PWI). Two measures of success are examined: cumulative grade point average (GPA) and graduation status.

Using student-level data from a southeastern university, this research estimates education production functions using ordinary least squares regression.

While the negative effect of being Black is significant for both cumulative GPA and graduation status, the effect becomes overshadowed when peer effects are added. The authors also found the critical effect of institutional support on student success.

The student-level data are restricted to a single institution over a relatively short period of time, which limits the authors' ability to analyze institution-level factors.

This research provides a broad view of many significant factors for student success with particular highlights on the importance of encouraging Black students to utilize institutional support.

This study is an extension of the education production function model in the field of student success. The study identified peer effects and institutional support as more powerful determinants of student success than race.

Recent high-profile ethical scandals in start-up organizations have made people wonder whether entrepreneurship may cultivate a work environment with less emphasis on ethics. This study examined a psychological process about how an organization’s entrepreneurial orientation (EO) can affect its treatment of probationary employees, a vulnerable yet understudied group of workers.

The authors recruited 241 participants through Amazon Mechanical Turk. They answered an online survey about their experiences as probationary employees.

This study found that job feedback and meaning moderated the relationship between EO and ethical climate, such that this relationship was statistically significant and positive only among participants who reported high levels of feedback and job meaning. Ethical climate, in turn, was found to be related to a reduction in workplace incivility experienced by probationary employees. The indirect effect of EO on incivility via ethical climate was contingent on job feedback and meaning.

This study extends the discussion on the entrepreneurial context, adds to EO literature with findings on its indirect effect on nonfinancial performance and reinforces institutional theory through job characteristics’ moderating roles. However, a methodological limitation is conducting a cross-sectional single-source survey due to limited access to firms and probationary employees, considering the hidden population involved.

This study found no evidence of probationary employee exploitation in high EO organizations. Job seekers should embrace probationary work at start-ups. Entrepreneurial leaders should balance being proactive, innovative and caring toward employees.

It is debatable whether entrepreneurship leads to unethical organizational conduct. By studying a vulnerable group of employees, the authors discovered that EO, when paired with favorable job design factors, can create a more ethical workplace where temporary talents are treated with dignity and respect.

One of the most cited literature in SHRM is Schuler and Jackson’s (1987) behavioural model. This model proposes that organisational performance is dependent on the extent to which HRM practices can be effectively connected to competitive strategy and desired employee behaviours. Importantly, this model recognises the salient role of employee behaviour in performance outcomes and, moreover that different competitive strategies imply both promulgation and reinforcement of different sets of employee skills and behaviours. Surprisingly, despite its significant influence on SHRM, studies rarely examine this model in its entirety. Motivated by the need to better understand this model’s arguments in contemporary settings, our study uses a multi-actor design to explore the connections between competitive strategies (cost reduction and differentiation), employee behaviours, and HRM practices in service environments.

Adopting a multi-level, multi-actor survey design, our exploratory deductive study assesses the utility of strategic HRM’s (SHRM) behavioural model. Drawing on data from a sample of service organisations and using univariate analyses, we compare operationalised HRM practices and employee behaviours across different strategy types.

Results lend provisional support for the behavioural model, particularly in the case of a differentiation strategy where notable differences in HRM practices and employee behaviours were observed. Findings suggest growing levels of memetic and competitive isomorphism may be occurring, with this likely attributable to the increased incidence of idea generation and information sharing about best practices occurring amongst practitioners, as well as a growing nuance in operating markets, managerial preferences, employee expectations, stakeholder objectives, and the like.

Our study suggests refinements to the behavioural model are needed. Some support for the model’s key tenets is found, but these appear context specific. Thus, the merit in developing a priori typologies linking strategy type to HRM practices and employee behaviours where organisations operate in environments which are particularised and tumultuous appears debatable.

This study highlights the behavioural model’s nuance to modern service organisations and, by doing so, practitioners are provided with a behavioural pathway for achieving competitive advantage through their HRM practices. Findings also suggest that increasingly competitive environments might be encouraging practitioners to engage in isomorphic behaviours.

The use of a comparative research design allowed our study to contribute much needed empiricism to the largely conceptually informed stylised typologies depicting the linkages between different competitive strategies, implied employee role behaviours and HRM practices, thereby supporting the need for model refinement.

Learning from past construction accident reports is critical to reducing their occurrence. Digital technology provides feasibility for extracting risk factors from unstructured reports, but there are few related studies, and there is a limitation that textual contextual information cannot be considered during extraction, which tends to miss some important factors. Meanwhile, further analysis, assessment and control for the extracted factors are lacking. This paper aims to explore an integrated model that combines the advantages of multiple digital technologies to effectively solve the above problems.

A total of 1000 construction accident reports from Chinese government websites were used as the dataset of this paper. After text pre-processing, the risk factors related to accident causes were extracted using KeyBERT, and the accident texts were encoded into structured data. Tree-augmented naive (TAN) Bayes was used to learn the data and construct a visualized risk analysis network for construction accidents.

The use of KeyBERT successfully considered the textual contextual information, prompting the extracted risk factors to be more complete. The integrated TAN successfully further explored construction risk factors from multiple perspectives, including the identification of key risk factors, the coupling analysis of risk factors and the troubleshooting method of accident risk source. The area under curve (AUC) value of the model reaches up to 0.938 after 10-fold cross-validation, indicating good performance.

This paper presents a new machine-assisted integrated model for accident report mining and risk factor analysis, and the research findings can provide theoretical and practical support for accident safety management.

We attempt to construct a grey three-way conflict analysis model with constraints to deal with correlated conflict problems with uncertain information.

In order to address these correlated conflict problems with uncertain information, considering the interactive influence and mutual restraints among agents and portraying their attitudes toward the conflict issues, we utilize grey numbers and three-way decisions to propose a grey three-way conflict analysis model with constraints. Firstly, based on the collected information, we introduced grey theory, calculated the degree of conflict between agents and then analyzed the conflict alliance based on the three-way decision theory. Finally, we designed a feedback mechanism to identify key agents and key conflict issues. A case verifies the effectiveness and practicability of the proposed model.

The results show that the proposed model can portray their attitudes toward conflict issues and effectively extract conflict-related information.

By employing this approach, we can provide the answers to Deja’s fundamental questions regarding Pawlak’s conflict analysis: “what are the underlying causes of conflict?” and “how can a viable consensus strategy be identified?”

Although wearable health-monitoring technology (WHMT) has become a stimulus for public health, women’s acceptance rate of this technology appears to be low. Thus, this study intends to investigate the factors affecting women’s adoption of WHMT.

The unified theory of acceptance and use of technology–2 model has been used in this study as a research framework that has been extended to include lifestyle and attitude. The proposed extended framework is validated using primary data (n = 314) collected from female respondents using a structured questionnaire; the partial least square-based structural equation modeling technique is subsequently used to test the proposed hypothesis.

The results show that effort expectancy, social influence, price value, habit, attitude and lifestyle have significant positive effects on women’s behavioral intention to use WHMT and accelerate actual usage behavior. Notably, effort expectancy and habit exhibit the largest impact on behavioral intention. However, performance expectancy, facilitating conditions and hedonic motivation are not significantly associated with behavioral intentions.

The findings of this study are important for healthcare practitioners and service providers to comprehensively understand the factors that affect women’s behavioral intentions in line with their actual usage behavior. This insight will help policymakers design viable strategies regarding WHMT to promote its sustainable usage in least developed countries.

This study contributes novelty by using an extended model that links women’s attitudes and lifestyles to their adoption of WHMT. This study also fills the gaps in the existing literature on women’s behavioral intentions in the context of WHMT by showing novel associations in the domain of WHMT uptake.

Disasters and other emergencies are increasing, with millions of people affected by events like earthquakes, fires and flooding. The use of mobile emergency alert systems (MEAS) can improve people’s responses by providing targeted alerts based on location and other personal details. This study aims to understand the factors that influence people’s willingness to share the personal information that is needed to provide context-specific messaging about a threat and protective actions.

Drawing on protection motivation theory (PMT), this study proposes and tests a model of willingness to use personalised MEAS that incorporates key factors related to an individual’s appraisal of a potential threat (i.e. perceived vulnerability and severity) and coping capacity (i.e. response efficacy and self-efficacy), with deterrents like response cost and privacy concern. This study uses survey data from 226 respondents in New Zealand and SmartPLS to assess the model.

The results show how willingness to use MEAS is influenced by people’s appraisal of an emergency threat and their perception of how using MEAS would help them to cope effectively. Fear and perceived severity are significant motivators of MEAS use, along with coping appraisal. However, when the negative influences of privacy concern and response cost are strong enough, they can dissuade use, despite knowing the risks.

The study addresses a gap in research on the use of alert systems like MEAS, which require sharing of personal information and continuous engagement such as the real-time disclosure of one’s location. It confirms the significance of factors not studied in prior research, such as privacy concerns, that can dissuade use. This study also extends the application of the PMT in the context of emergency management.

Showrooming presents a complex and evolving challenge to retail managers, as it signifies the emergence of new forms of exchange rules. The purpose of this research is to investigate how factors responsible for information search and evaluation affect showrooming and also consider the consumer mindset as a moderator.

This research undertakes three experimental designs to investigate how the push (i.e. assortment size), pull (i.e. price discount), and mooring (i.e. sunk cost) factors influence consumers' showrooming intention. Specifically, consumers' maximizing tendency plays the role of moderator.

The results reveal that push, pull, and mooring factors are significantly related to consumers' showrooming intention. Furthermore, the findings show that maximizers have higher showrooming intention than satisficers in the context of the push, pull, and mooring factors.

By integrating the push-pull-mooring framework and the maximizing mindset theory, this research proposes a novel research model and the empirical testing results support six hypotheses. The findings add to the body of knowledge in showrooming behavior by taking consumer mindset into account. The results also provide implications for practitioners to develop their retail strategies.

To enrich the research on the economic consequences of enterprise digital development from the perspective of capacity utilization.

Using a sample of listed firms from 2010 to 2020, this paper exploits text analysis of annual reports to construct a proxy for enterprise digital development.

Results show that enterprise digital development not only improves their own capacity utilization but also generates a positive spillover effect on the capacity utilization of peer firms and firms in the supply chain. Next, based on the incomplete information about market demand and potential competitors when making capacity-building decisions, the mechanism tests show that improving the accuracy of market forecasts and reducing investment surges are potential channels behind the baseline results. Cross-sectional tests show the baseline result is more pronounced when industries are highly homogeneous and when firms have access to less information.

This paper contributes to the research related to the economic consequences of digital development. With the development of the digital economy, the real effects of enterprise digital development have also triggered extensive interest and exploration. Existing studies mainly examine the impact on physical operations, such as specialization division of labor, innovation activities, business performance or total factor productivity (Huang, Yu, & Zhang, 2019; Yuan, Xiao, Geng, & Sheng, 2021; Wang, Kuang, & Shao, 2017; Li, Liu, & Shao, 2021; Zhao, Wang, & Li, 2021). These studies measure the economic benefits from the perspective of the supply (output) side but neglect the importance of the supply system to adapt to the actual market demand. In contrast, this paper focuses on capacity utilization, aimed at estimating the net economic effect of digital development by considering the supply-demand fit scenario. Thus, our findings enrich the relevant studies on the potential consequences of digital development.