مطالب

In the multifaceted landscape of entrepreneurship, this research delves into the intricate relationship between entrepreneurial orientation and entrepreneurial intention, focusing specifically on the final-year female undergraduates in Nigerian federal universities. Grounded in the Human Capital Theory (HCT), this study uncovers profound insights into the multifaceted relationships between various entrepreneurial traits and their influence on entrepreneurial intentions. The findings reveal a nuanced relationship between traits such as autonomy, competitive aggressiveness, risk-taking, self-esteem, and the sense of inclusion with entrepreneurial intentions. Autonomy and competitive aggressiveness emerge as significant influencers, while risk-taking displays a non-significant association. Self-esteem holds profound implications, while the sense of inclusion exerts a more subdued impact on entrepreneurial intentions. Theoretical implications challenge and expand existing frameworks, notably HCT. While HCT posits that investments in education and training foster entrepreneurial traits, this study suggests a more intricate relationship. The non-significant association of certain traits, despite their emphasis in HCT, underscores the need for a nuanced understanding, possibly integrating other theoretical frameworks. From a practical standpoint, these findings guide policymakers and educators in designing targeted interventions. Specialized training programs, workshops, and courses emphasizing autonomy, competitive aggressiveness, and self-esteem can be developed. Integrating competitive elements, like business plan competitions, can nurture students' competitive drive. Policy recommendations include tailored entrepreneurial education, fostering inclusive environments, promoting a risk-taking culture, supporting longitudinal studies, and enhancing collaboration between educational institutions and industry.

The research aimed to estimate the economic-recreational value of Yadegar Emam Stadium in Tabriz from the spectators' perspective using the contingent valuation approach. A sample size of 415 football fans attending the matches was studied through simple random sampling. A researcher-made questionnaire was used, and Logit and Probit rank-based methods with Stata software were employed for data analysis. The findings revealed that factors including income, proposed price, watching matches on television, satisfaction with stadium facilities, and enjoyment from watching games, positively influenced the willingness to pay. Conversely, variables including education level, age, and marital status had a negative correlation with willingness to pay. These results highlight the significant economic and recreational value held by Yadegar Emam Stadium. The estimation data can aid in managerial decision-making, sports development, and planning, leading to economic and social benefits, and promoting the football industry.

The study examines the effects of the Self-Determined Learning Model of Instruction (SDLMI) on intermediate English as a foreign language (EFL) learners’ L2 autonomous motivation, self-efficacy, and perceived locus of causality. Given the evolving paradigms of language teaching, SDLMI values ​​autonomy, competence and connectedness in teaching instruction and offers a distinctive approach. Drawing on contemporary motivational theories, the study examines how SDLMI impacts these key dimensions in intermediate EFL learners compared to a traditional instructional approach. Participants from four EFL classrooms completed SDLMI in the experimental group and conventional instruction in the control group. Instruments included the Preliminary English Test, motivational questionnaires, and SDLMI-based assessments. Data were analyzed using descriptive statistics and independent samples t-tests. Descriptive statistics for both groups (mean and SD) were calculated. Independent samples t-tests were conducted to compare the means between the experimental group and the control group and to examine possible significant differences in the effect of SDLMI on autonomous motivation, self-efficacy, and perceived locus of causality. The study contributes to instructional practices, advocating for autonomy-supportive strategies in fostering holistic language. 

Objective: The aim of this study was to determine the mediating role of family leisure and humor in the relationship between parenting stress and co-parenting. Methods: The present study population consisted of all parents living in Kermanshah in 2020, from which 300 people were selected to participate in the study using multi-stage cluster sampling. Research instruments included Parenting Stress Index-Short Form, Zabriski Family Leisure Activity Profile, Co-parenting Relationship Scale, and the Family Members’ Humor Scale. The research was descriptive and structural equation modeling was used to analyze the data. Results: The results of data analysis showed that there is a significant direct relationship between parenting stress variables and co-parenting (P< 0.001; β = -0.43), parenting stress and family humor (P< 0.001; β= -0.34), parenting stress variables and family leisure (P< 0.001; β= -0.28), humor in the family and co-parenting (P< 0.001; β= 0.4). Also, the humor variable in the family could play a mediating role in the relationship between parenting stress and co-parenting (P< 0.002; β= 0.17). Conclusion: Therefore, it can be said that humor and games in families can play an important role both in creating co-parenting and decreasing of the negative effect of parenting stress on co-parenting.

Evidence-based policymaking stands at the forefront of contemporary governance, where data and evidence have emerged as indispensable allies in shaping effective and informed decisions. This article embarks on a comprehensive exploration of the challenges and critical issues encountered when data assumes the role of evidence in policy formulation. The foundation of this investigation is rooted in the extensive body of literature on evidence-based policy-making. We delve into the scholarly discourse, tracing the evolution of policy formulation from relying on intuition to being guided by empirical insights. As we navigate through this intellectual landscape, the crucial role of data as a catalyst for this transformation becomes apparent. Delving deeper, we will explore the intricacies of data and the rise of big data. Once regarded as mere numbers, data now represents the currency of the information age. Its volume, velocity, and variety characterize it, making it a powerful tool for generating evidence and formulating policies. As we explore its features, we uncover the potential of data to unlock unprecedented insights and inform governance with empirical precision. To conduct a comprehensive examination of the difficulties encountered when utilizing data as evidence in policy-making, we employ a rigorous scoping review methodology. Through meticulous screening, we have identified and analyzed 36 exemplary articles that offer invaluable insights into the multifaceted landscape of data-driven governance. These articles provide a comprehensive overview of the challenges, which can be grouped into three distinct clusters: technical challenges arising from data complexities, legal and privacy dilemmas intertwined with governance, and the formidable issues faced by policymakers. Our discussion unravels the intricate web of challenges, ranging from data quality and integration to confidentiality, ethics, and governance issues. We delve into the intricacies of data access, the fight against bias, and the challenges posed by data volume and complexity. Simultaneously, we explore the complex legal landscape of data ownership, security, sharing, and compliance. The challenges policymakers face in fostering data-driven cultures, navigating resource constraints, and communicating data-driven insights are brought to the forefront. In conclusion, our exploration sheds light on the complex challenges and crucial issues that underlie the use of data as evidence in evidence-based policy-making. This research underscores the transformative power of data in governance and emphasizes the challenges and pressing issues associated with using data as evidence in policymaking.

The present study investigates Peer Review Ethics (PRE) in scientific journals in Iran, with a specific focus on compiling the PRE statement for the Journal of Information Processing and Management (JIPM). Moreover, qualitative analysis was conducted on the PRE statements of the journals published by the Ministry of Science, Research, and Technology (MSRT). The review process and documents of the JIPM were then analyzed. This evidence-based case study was conducted using a mixed-method approach, which included three research methods: researcher-based, data-based, and research-based. A focus group discussion (FGD) was also conducted to validate the research findings. The findings showed that PRE elements were classified such as "timeliness," "confidentiality," "bias," "conflict of interest," "research misconduct," "respectful and fair expressions," "constructive and objective feedback," and "accountability and responsibility." The analysis of ethical statements in MSRT journals found that only half of the journals published PRE statements. In addition, 102 instances of violations of PRE, accounting for 15% of each review, were identified in documents submitted for review in JIPM.  

The role of the capital market is fundamental and decisive in the economy of all countries [6]. Studies show that in the capital market, prices are determined based on macroeco-nomic variables[2]. Accordingly, In this study is to provide a model for measuring the impact of economic policy uncertainty (EPU) on information asymmetryn.The research method is applied and has been made to present a model for measuring the effect of EPU on information asymmetry in the EVIEWS12 and MATLAB2021 software environment. The research time period is determined from 2011 to 2020 and 101 companies are selected based on the applied restrictions to estimate the model. In this study, 40 variables affecting EPU are entered into the According to the results of BMA, the most important variables affecting the EPU is provided[2]. Based on the principal components approach, the EPU index is calculated using the most important variables affecting this variable. Then, with the GARCH model, the uncertainty part of the EPU index is extracted, and finally, using the powerful nonlinear TVPFAVAR model, the shock caused by the EPU variable on the information asymmetry indices in the research period is analyzed. The results show that the shock caused by the fluctuation of the variable of EPU has increased the index of information asymmetry in recent years. Based on the results, EPU shock on the index of information asymmetry has had a stronger effect on in the short and long term information asymmetry than the medium term.