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Role congruity theory and gender stereotypes research suggests men are expected to engage in agentic behavior and women in communal behavior as leaders, and that role violation results in backlash. However, extant gender and leadership research does not directly measure expectations–behavior incongruence. Further, researchers have only considered one condition of role incongruence – display of counter-role behavior – and have not considered the outcomes of failing to exhibit role-congruent behavior. Additionally, few studies have examined outcomes for male leaders who violate gender role prescriptions. The present study aims to address these shortcomings by conducting a novel empirical test of role congruity theory.

This experimental study used polynomial regression to assess how followers evaluated leaders under conditions of incongruence between follower expectations for men and women leaders’ behavior and leaders’ actual behavior (i.e. exceeded and unmet expectations). Respondents read a fictional scenario describing a new male or female supervisor, rated their expectations for the leader’s agentic and communal behavior, read manipulated vignettes describing the leader’s subsequent behavior, rated their perceptions of these behaviors, and evaluated the leader.

Followers expected higher levels of communal behavior from the female than the male supervisor, but no differences were found in expectations for agentic behavior. Regardless of whether expectations were exceeded or unmet, supervisor gender did not moderate the effects of agentic or communal behavior expectations–perceptions incongruence on leader evaluations in polynomial regression analyses (i.e. male and female supervisors were not evaluated differently when displaying counter-role behavior or failing to display role-congruent behavior).

In addition to providing a novel, direct test of role congruity theory, the study highlighted a double standard in gender role-congruent behavior expectations of men and women leaders. Results failed to support role congruity theory, which has implications for the future of theory in this domain.

This study aims to analyze the effectiveness and efficiency of research-based community service programs in Indonesia that used government funds in 2017–2021.

The design of this research is a quantitative research method using a data envelopment analysis to evaluate 370 leading universities in Indonesia. Furthermore, six analytical models were considered to compare effectiveness and efficiency between universities. It involved two resource (budget and staff academic involved), three output (intellectual property, prototype and publication) and three outcome variables (economic impact, social impact and capacity building).

The findings showed that several universities are considered necessary, with great potential to increase output and outcome efficiency in community involvement. The study mapped and divided the position of 370 universities for additional information. The effectiveness aspect provides another perspective in assessing the performance of tertiary institutions in Indonesia and can be an option for evaluating research performance to improve the quality of output.

The authors use data from research and community service management information systems used, both the resources used and the results. Efficiency and effectiveness of 370 universities were compared in this study, including comparing their position on the previous assessment with the assessment of the results of this study. Approach to the concept of Mandl et al. (2008) regarding the relationship between input, output and outcome as the main component of the indicators, the authors apply to analyze efficiency and effectiveness.

Coastal zone ecological restoration project is of great significance to alleviate marine ecological degradation. Evaluating the effect of coastal ecological restoration projects and identifying the obstacle factors affecting their restoration level can provide an empirical basis for future Marine ecological restoration projects.

However, due to the initial stage of coastal zone ecological restoration projects, the actual monitoring data of coastal zone ecological restoration is relatively lacking. Based on the CRITIC-TOPSIS (combination of CRITIC method and TOPSIS method) method, combined with the subjective perception of the public and the actual data of the restoration project, this paper proposes an evaluation method of the coastal zone ecological restoration effect to obtain the specific implementation effect of the coastal zone ecological restoration project. The main obstacle factors affecting the evaluation of coastal ecological restoration effect are identified by using the obstacle degree model.

This paper conducted an empirical study on the restoration of sandy shoreline and coastal wetland in Qinhuangdao city. Based on the data of restoration projects and the subjective perception of ecological restoration by the public in Qinhuangdao city, the research results showed that the coastal zone ecological restoration effect of Qinhuangdao city was general. The quality of the restoration project and the public perception have an important influence on the evaluation of the restoration effect. Improving the quality of the restoration project, strengthening the public's participation in ecological restoration and allowing the public to better participate in the ecological restoration of the coastal zone can improve the effect of ecological restoration of the coastal zone in an all-round way.

The research results of this paper have a guiding role in the ecological restoration of coastal cities in the future, and also have a demonstration and reference role for the assessment of the effect of ecological restoration of coastal zones.

In today’s digital economy, it is very important to cultivate digital professionals with advanced interdisciplinary skills. The purpose of this paper is that universities play a vital role in this effort, and research teams need to use the synergistic effect of various educational methods to improve the quality and efficiency of personnel training. For these teams, a powerful evaluation mechanism is very important to improve their innovation ability and the overall level of talents they cultivate. The policy of “selecting the best through public bidding” not only meets the multi-dimensional evaluation needs of contemporary research, but also conforms to the current atmosphere of evaluating scientific and technological talents.

Nonetheless, since its adoption, several challenges have emerged, including flawed project management systems, a mismatch between listed needs and actual core technological needs and a low rate of conversion of scientific achievements into practical outcomes. These issues are often traced back to overly simplistic evaluation methods for research teams. This paper reviews the literature on the “Open Bidding for Selecting the Best Candidates” policy and related evaluation mechanisms for research teams, identifying methodological shortcomings, a gap in exploring team collaboration and an oversight in team selection criteria.

It proposes a theoretical framework for the evaluation and selection mechanisms of research teams under the “Open Bidding for Selecting the Best Candidates” model, offering a solid foundation for further in-depth studies in this area.

Research progress on the Evaluation Mechanism of Scientific Research Teams in the Digital Economy Era from the Perspective of “Open Bidding for Selecting the Best Candidates.”

Evaluating emergency preparedness exercises is crucial for assessing enhanced knowledge, facilitating learning and implementing knowledge in organizations. The cognitive process of motivation for action is a precursor for action, coping behavior and individual learning. This study aims to focus on how guided evaluation of emergency preparedness exercises can enhance cognitive motivation and influence the mental readiness of exercise participants.

This is a conceptual paper with a model approach design. The main conceptual contribution is suggesting a model for guided evaluation in emergency preparedness exercises. We present a theoretical background for understanding the increase in motivation based on social cognitive learning theory. In particular, this study discusses how different evaluation steps contribute to enhanced motivation and learning for exercise participants.

Increased motivation and enhanced personal performance standards could be achieved through using processes that lead to self-efficacy in guided exercise evaluation. Specifically, sources of enhanced motivation, such as repeated coping experiences, self-regulation processes, mastery motivation and performance motivation, would proliferate the readiness of individual crisis managers and teams.

This article suggests an evaluation model for use in emergency preparedness exercises. This approach combines bottom-up and top-down processes for debriefing, reflection and feedback, both individually and in teams. This approach aims to enhance exercise participants’ motivation and utilize exercise evaluation for organizational learning.

The conceptual discussion leads to developing implications for evaluation practice, suggesting how to structure evaluation and why. This study is novel for its explanation of how to use evaluation in the learning process.

Objectively evaluating the fairness of the algorithm, exploring in specific scenarios combined with scenario characteristics and constructing the algorithm fairness evaluation index system in specific scenarios.

This paper selects marketing scenarios, and in accordance with the idea of “theory construction-scene feature extraction-enterprise practice,” summarizes the definition and standard of fairness, combs the application link process of marketing algorithms and establishes the fairness evaluation index system of marketing equity allocation algorithms. Taking simulated marketing data as an example, the fairness performance of marketing algorithms in some feature areas is measured, and the effectiveness of the evaluation system proposed in this paper is verified.

The study reached the following conclusions: (1) Different fairness evaluation criteria have different emphases, and may produce different results. Therefore, different fairness definitions and standards should be selected in different fields according to the characteristics of the scene. (2) The fairness of the marketing equity distribution algorithm can be measured from three aspects: marketing coverage, marketing intensity and marketing frequency. Specifically, for the fairness of coverage, two standards of equal opportunity and different misjudgment rates are selected, and the standard of group fairness is selected for intensity and frequency. (3) For different characteristic fields, different degrees of fairness restrictions should be imposed, and the interpretation of their calculation results and the means of subsequent intervention should also be different according to the marketing objectives and industry characteristics.

First of all, the fairness sensitivity of different feature fields is different, but this paper does not classify the importance of feature fields. In the future, we can build a classification table of sensitive attributes according to the importance of sensitive attributes to give different evaluation and protection priorities. Second, in this paper, only one set of marketing data simulation data is selected to measure the overall algorithm fairness, after which multiple sets of marketing campaigns can be measured and compared to reflect the long-term performance of marketing algorithm fairness. Third, this paper does not continue to explore interventions and measures to improve algorithmic fairness. Different feature fields should be subject to different degrees of fairness constraints, and therefore their subsequent interventions should be different, which needs to be continued to be explored in future research.

This paper combines the specific features of marketing scenarios and selects appropriate fairness evaluation criteria to build an index system for fairness evaluation of marketing algorithms, which provides a reference for assessing and managing the fairness of marketing algorithms.

Algorithm governance and algorithmic fairness are very important issues in the era of artificial intelligence, and the construction of the algorithmic fairness evaluation index system in marketing scenarios in this paper lays a safe foundation for the application of AI algorithms and technologies in marketing scenarios, provides tools and means of algorithm governance and empowers the promotion of safe, efficient and orderly development of algorithms.

In this paper, firstly, the standards of fairness are comprehensively sorted out, and the difference between different standards and evaluation focuses is clarified, and secondly, focusing on the marketing scenario, combined with its characteristics, key fairness evaluation links are put forward, and different standards are innovatively selected to evaluate the fairness in the process of applying marketing algorithms and to build the corresponding index system, which forms the systematic fairness evaluation tool of marketing algorithms.

This study aims to examine the impact of consumer risk appetite, biases (specifically negative recency bias), and the importance of reviews in enhancing information quality. By analyzing these variables, the authors gain insights into their role in enriching the overall information spectrum available to consumers. The findings contribute to a better understanding of how risk appetite, biases and consumer reviews shape the quality of information.

The questionnaire assessed the relationship between dependent and independent variables by asking participants to rate their experiences in relevant scenarios. Variance-based structural equation modeling with the ADANCO program was used to examine the data. ADANCO software is used explicitly for variance-based structural equation modeling. To evaluate research models and test hypotheses, partial least square path modeling is used.

The efficiency of reviews and ratings is greatly influenced by consumer risk appetite. Businesses should focus on clients who are willing to take risks and balance positive and negative feedback. It is essential to comprehend how customers understand reviews. Credibility is increased by taking biases into account and encouraging unbiased criticism. Promoting thorough reviews strengthens influence. Monitoring and making use of these elements improve online reputation and commercial success.

The research has limitations due to the simplicity of the attributes taken into account and the requirement for a larger sample size. Overcoming barriers to promote consistent client feedback is essential, and tailored emails can help with assessment generation. Increased customer participation in writing evaluations can be achieved by removing obstacles and highlighting the advantages of participation.

Businesses and buyers rely on this “organically” generated content as the basis of their promotional strategy and buying decisions. Most of the research is related to consumer reviews, their behavior and the importance of social validation. However, some critical aspects related to this need further investigation.

This study aims to propose a collaborative knowledge-based ontological research model for designing a collaborative product development process (PDP) while considering different design for X techniques.

This study follows a thematic literature analysis to identify the key design concepts needed to assess environmental, service, safety, manufacture and assembly, supply chain and quality concerns in developing a collaborative PDP.

The proposed model provides a guide for methodology, engineering and ontology evaluation metrics (verification, assessment and validation). The findings benefit both practitioners and managers because they address the key knowledge taxonomy needed to assist them in storing information, promoting teamwork and making decisions in a collaborative PDP while incorporating various design for X approaches and product life cycles.

This study introduces a novel knowledge-based collaborative ontological research model, which is specifically designed to tackle the challenges of developing collaborative products in the contemporary landscape. The model presents a significant and valuable contribution to the field by introducing an ontological approach for acquiring, representing and leveraging knowledge in a computer-interpretable format to support the design of collaborative products. In addition, it provides a comprehensive guide for evaluating the effectiveness and efficacy of the ontology developed.

Built environments are highly vulnerable to climatic disasters such as extreme floods, droughts and storms. Inaccurate decisions in adopting emerging construction technologies can result in missed opportunities to improve the resilience of built environments. Therefore, understanding the effectiveness of emerging construction technologies in improving built environment resilience can help in making better strategic decisions at the national and organizational levels. This study aims to evaluate the effectiveness of Construction 4.0 technologies in improving built environment resilience.

A list of Construction 4.0 technologies was adopted from a national strategic plan. Then, the data were collected using the fuzzy technique for order preference by similarity to ideal solution technique from selected built environment experts to determine the relative effectiveness of Construction 4.0 technologies in improving built environment resilience.

Six Construction 4.0 technologies are critical in improving built environment resilience (in rank order): building information modeling, autonomous construction, advanced building materials, big data and predictive analytics, internet of Things and prefabrication and modular construction. In addition, adopting Construction 4.0 technologies collectively is crucial, as moderate to strong connections exist among the technologies in improving built environment resilience.

To the best of the authors’ knowledge, this is one of the first papers that evaluate the effectiveness of Construction 4.0 technologies in improving built environment resilience. Industry professionals, researchers and policymakers can use the study findings to make well-informed decisions on selecting Construction 4.0 technologies that improve built environment resilience to climatic disasters.

The purpose of this paper is to present the educational computer emergency response team (EduCERT) framework, an integrated response mechanism to bolster national cybersecurity through collaborative efforts in the higher education sector. The EduCERT framework addresses this gap by enhancing cyber security and mitigating cybercrime through collaborative incident management, knowledge sharing and university awareness campaigns.

The authors propose an EduCERT framework following the design science methodology. The framework is developed based on literature and input from focus group experts. Moreover, it is grounded in the principles of the technology-organization-environment framework, organizational learning and diffusion of innovations theory.

The EduCERT has eight components: infrastructure, governance, knowledge development, awareness, incident management, evaluation and continuous improvement. The framework reinforces national cybersecurity through cooperation between universities and the National Computer Emergency Response Team. The framework has been implemented in Jordan to generate a cybersecurity foundation for higher education. Evaluating the EduCERT framework’s influence on national cybersecurity highlights the importance of adopting comprehensive cyber-security policies and controls. The framework application shows its relevance, effectiveness, adaptability and alignment with best practices.

Despite the impact of applying the framework in the Jordanian context, it is essential to acknowledge that the proposed EduCERT framework’s practical implementation may encounter challenges specific to diverse international educational environment sectors. However, framework customization for global applicability could address varied educational institutions in other countries.

Furthermore, the proposed EduCERT framework is designed with universal applicability that extends beyond the specific country’s context. The principles and components presented in the framework can serve as valuable design advice for establishing collaborative and resilient cybersecurity frameworks in educational settings worldwide. Therefore, the research enhances the proposed framework’s practical utility and positions it as an invaluable contribution to the broader discourse on global cybersecurity in academia.

This paper enhances national cybersecurity in the higher education sector, addressing the need for a more integrated response mechanism. The EduCERT framework demonstrates its effectiveness, adaptability and alignment with best practices, offering valuable guidance for global educational institutions.