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This study examines opinion leadership's personal and social characteristics to see which one is more effective in opinion leadership in four different industries: fashion, travel and tourism, wellness and book and literature. The specific subject of this investigation is how largely openness, exhibitionism and competence in interpersonal relationships and status and attitude homophily affect the opinion leadership and the decision-making of opinion leaders' followers.

The proposed model was tested with the questionnaire shared via stories featured on Instagram among followers of four micro-influencers in different industries. For the purpose of testing the offered hypotheses of this study, the partial least squares method was used.

The findings show that openness, exhibitionism and competence in interpersonal relationships have a substantial effect on opinion leadership. It was also evident that status and attitude homophily impact opinion leadership. The model supports the effect of both personal and social characteristics on opinion leadership; however, based on the results, the effect of personal characteristics on opinion leadership is more remarkable, both in a direct relationship and through the mediating role of para-social interaction.

This study is novel in categorizing opinion leaders' attributes in two different extents of personal and social characteristics. The authors defined a model of the effectiveness of each personal and social characteristic on opinion leaders. The model investigates whether the personal or social characteristics have the most effect on opinion leadership, particularly with the mediating role of para-social interaction.

Because of importance of technological learning for less developed countries, the notion has received increasing attention of scholars. The purpose of this paper is to investigate technological learning systematically by assessing the effect of technology transfer actors on technological learning in less developed countries context.

The paper presents assessment model by adopting technological learning concept based on technology absorption and incremental innovation at firm level and identifying key roles of technology transfer actors (State – Scientific and technological infrastructure – Industry) that affect technological learning. The paper follows survey as research methodology. Thus, a questionnaire was addressed to 33 Syrian textile factories to examine the assessment model. Simple linear, multiple linear and ordinal regression analyses are preformed to examine relationships of model components.

The regression models show notable ability of technology transfer actors to explain technological behavior of firms to accumulate operative capability and consequently to generate passive incremental innovation. The findings indicate passive technical change system of Syrian textile industry. Therefore, goal-oriented evaluation of actual technology policy is preliminary step for achieving improvements, as well as activating scientific and technological infrastructure role by enabling strong relationships with industry and supporting interactions of domestic firms of textile industry and with foreign players.

The paper enriches technological learning literature by proposing systematic approach that sets the nature of technical change process of less developed countries in core of analysis. Moreover, it provides a guide for technological learning practices at firm level and for policymakers based on assessing actual status of Syrian textile industry.

Anxiety disorders have a high prevalence in children. Those children with anxious symptoms are more likely to experience significant disruption in their lives. This disruption can interrupt or even stop a child from participating in a variety of typical childhood experiences. It is understood that genetic and environmental factors may cause this disorder. The purpose of this paper is to focus on environmental factors, namely, the mediating role of maladaptive schemas in mothers’ child-rearing and childhood anxiety disorders.

This study used correlation-modeling to assess the analysis. The sample included 326 students (aged 9-12 years old) and their mothers. The parenting style (Baumrind, 1973), Early Maladaptive Schema (Rijkeboer and de Boo, 2010), and anxiety disorders (Muris et al., 2006) questionnaires were used in this study.

The results showed a relationship between parenting styles of mothers and childhood anxiety disorders, a significant correlation between childhood maladaptive schemas and childhood anxiety disorders, a relation between child-rearing styles and childhood maladaptive schemas, and finally a mediating role on childhood anxiety disorders and mothers’ child-rearing styles for some childhood maladaptive schemas.

This research contributes to the knowledge base of the importance of children’s mental health. The paper analyzes the relationship of mothers’ parenting styles and children’s anxiety. It also focuses on maladaptive schemas as a mediator and its relationship with childhood anxiety disorders.

This study aims to investigate the effect of the dynamics and potential of the board of directors on investment efficiency and the comparability of financial information in companies listed on the Tehran Stock Exchange.

The number of observations for this study includes 1,218 observations from companies listed on the Tehran Stock Exchange during 2014–2020. The authors used econometric statistical methods such as multiple linear regression, the Chow and Hausman test and the Kendall correlation coefficient using Eviews software to conduct the research. To measure the board’s effectiveness, two variables are used, including board dynamics and potential.

The results showed a positive and significant relationship between dynamics, board potential and investment efficiency. Also, no significant relationship was observed between the board dynamics and the comparability of financial information. Finally, a positive and significant relationship exists between the board’s potential and the comparability of financial information.

The importance of this research is the use of board proxies, including the dynamics and potential of the board. In addition, other variables of board characteristics, such as size, independence, ownership and gender, and the relationship between these variables with investment efficiency and comparability of financial information, have been examined in this study.

New business practices and the globalization of markets force firms to take innovation as the fundamental pillar of their competitive strategy. Research and Development (R&D) plays a vital role in innovation. As technology advances and product life cycles become shorter, firms rely on R&D as a strategy to invigorate innovation. R&D project portfolio selection is a complex and challenging task. Despite the management's efforts to implement the best project portfolio selection practices, many projects continue to fail or miss their target. The problem is that selecting R&D projects requires a deep understanding of strategic vision and technical capabilities. However, many decision-makers lack technological insight or strategic vision. This article aims to provide a method to capitalize on the expertise of R&D professionals to assist managers in making informed and effective decisions. It also provides a framework for aligning the portfolio of R&D projects with the organizational vision and mission.

This article proposes a new strategic approach for R&D project portfolio selection using efficiency-uncertainty maps.

The proposed strategy plane helps decision-makers align R&D project portfolios with their strategies to combine a strategic view and numerical analysis in this research. The proposed strategy plane consists of four areas: Exploitation Zone, Challenge Zone, Desperation Zone and Discretion Zone. Mapping the project into this strategic plane would help decision-makers align their project portfolio according to the corporate perspectives.

The new approach combines the efficiency and uncertainty dimensions in portfolio selection into an integrated framework that: (i) provides a complete representation of the stochastic decision-making processes, (ii) models the endogenous uncertainty inherent in the project selection process and (iii) proposes a computationally practical and visually unique solution procedure for classifying desirable and undesirable R&D projects.

The purpose of this study is to identify the situation of evaluating Iranian digital libraries using DigiQUAL protocol.

Evaluative survey research method is used in this study to assess digital libraries. In this way, digital libraries of Iranian research institutes constitute the study population. DigiQUAL protocol actually was used to evaluate eight Iranian digital libraries. Systematic observation and interview based on researcher-made checklist was used for data collection. In fact, checklist was constructed based on DigiQual protocol.

The results showed that Digital Library of Isfahan Science and Technology Town has the best performance and Noor digital library has the lowest operation in studied digital libraries. The overall score of all studied digital libraries was under 60 (out of 100) which shows the average performance of the digital libraries.

This study emphasizes on evaluating active digital libraries in Iran by DigiQUAL protocol. Because digital libraries are new in Iran and their progress need to evaluate their activity, this research was done to demonstrate their situation.

Health is one of the most basic human rights. Self-medication not only results in many risks, complications and mortalities but also remains a massive economic burden on governments’ pharmaceutical budgets, insurance companies and the general population. The importance of self-medication as one of the worldwide health problems, this paper aims to investigate the extent of this problem and related factors in Sanandaj, Iran in 2018.

This cross-sectional, descriptive study was conducted on 838 people who referred to pharmacies in Sanandaj, Iran in 2018. The subjects were selected in 10 pharmacies, 84 in each, randomly. A self-constructed questionnaire was used to collect information about demographic features, prevalence and reasons for self-medication. The data was analyzed statistically by SPSS software.

The results show a high prevalence of self-medication, 73.70 per cent among people who referred to the pharmacies in Sanandaj during 2018. There was a significant correlation between self-medication and occupation, education level, age groups, chronic disease, smoking or reasons to refer to pharmacies (p < 0.05). Analgesics, antibiotics; non-steroid anti-inflammatory, cold and gastrointestinal medicines were the most commonly used medicines by the subjects. People with headache, cold, infection, stomach pain, toothache and dysmenorrhea were more likely to act self-medication than people with other complaints. Among people who do self-medication, (85.60 per cent) had already experienced satisfactory results after using medicines. Mild symptoms of the disease (74.11 per cent), availability of medicines (72.98 per cent) and easy access to medicine supplies in pharmacies (71.35 per cent) are other reasons for self-medication.

In general, the study had some limitations. One of the limitations was related to the research period i.e. spring and summer. So, it is suggested to conduct studies in other seasons, too. Furthermore, as the time of self-medication was the past three months, there was a probability of recall bias.

The prevalence of self-medication in Sanandaj is high and alarming, implementing educational programs about this issue is extremely required. Health policymakers should take all necessary steps to tackle self-medication efficiently.

The purpose of this study is to identify and analyze the characteristics and visual patterns of successful knowledge workers using quantitative methods, particularly eye-tracking technology. By conducting a systematic review and matching identified factors with theoretical literature, the research aims to uncover key attributes that contribute to the effectiveness of knowledge workers. These insights are intended to improve employee selection processes, ensuring the right candidates are chosen based on their cognitive, behavioral and visual traits.

A mixed-methods approach is employed in this study, consisting of three phases: (1) a systematic literature review identifies key characteristics of successful knowledge workers, (2) these factors are aligned with theoretical frameworks and expert insights to assess their applicability and (3) empirical data is collected through questionnaires and eye-tracking assessments involving ten high-performing site design employees and ten students from Shahid Beheshti University. SPSS software and Tobii Pro Lab tools are used for data analysis to establish correlations between eye movement patterns and attributes of effective knowledge workers.

The findings reveal that students whose eye movement patterns resemble those of high-performing knowledge workers also share similar cognitive and behavioral characteristics. Identified key attributes include enhanced problem-solving skills, adaptability and effective communication. The study further highlights the potential of eye-tracking technology as a valuable tool in employee selection, offering insights into visual behaviors that correlate with high performance in knowledge work. These findings provide a deeper understanding of the critical traits that optimize organizational performance.

This study presents a novel approach by integrating eye-tracking technology into the knowledge worker selection process. It provides empirical evidence of the visual and cognitive patterns associated with high performance, thereby enhancing the theoretical understanding of knowledge worker selection. The study contributes valuable insights for organizations aiming to refine their hiring practices, emphasizing the importance of both cognitive skills and visual behaviors in candidate assessment. This research lays the groundwork for future studies exploring the intersection of technology and human resource management to optimize workforce effectiveness.

This study aims to analyze the mediating role of data analytics management capability (DAMC) in the relationship between supply chain integration (SCI) and supply chain agility, adaptability and alignment (Triple-A). It also studies the role of Triple-A supply chains in performance improvement. We develop and present a model based on our proposition and informed by the dynamic capabilities perspective.

The authors employ meta-analytic structural equation modeling to test the proposed model by analyzing reported statistics of 117 published studies.

This study’s results describe why some prior research findings are contradictory. For example, researchers have posited mixed findings on the impact of SCI on agility. The results show that SCI and agility do not have a significant direct association, and DAMC mediates their indirect relationship.

The impact of SCI on performance is debatable. SCI permits access to shared resources for competitive advantage; conversely, SCI-induced rigidity may reduce supply chain agility and adaptability. Informed by dynamic capabilities theory, the authors demonstrate that DAMC positively mediates the impact of SCI on performance.