Management Strategies and Engineering Sciences

The present study aims to design and explain a political marketing model with a focus on individual behavior components. The data collection method in this study was conducted using both library research and field research. The data collection tool in the quantitative section was a researcher-made questionnaire, developed based on the results of the qualitative section and distributed among 310 individuals using non-probability random sampling. For qualitative data analysis, inductive qualitative content analysis was employed. For quantitative data analysis, descriptive statistics were used, and for examining the research questions, inferential statistics and the partial least squares (PLS) method were applied using SPSS and SMARTPLS software. The study's findings indicate that individual factors, including variables such as political awareness, vote market needs assessment, and value creation for voters, play a key role in stimulating and directing voter behavior. Marketing and media factors include variables such as media framing, effective marketing and advertising, branding, and the development of a new paradigm in political marketing. Additionally, environmental and technological factors encompass variables such as technological changes, international pressures, and continuous environmental monitoring. These factors, as external variables, shape the political and social environment and influence marketing strategies. However, leveraging voters’ political awareness to develop targeted electoral messages and designing political marketing strategies with an emphasis on technology and media can create greater impact.

This study aims to explore the influence of natural light in interior architecture on mental health, highlighting architectural strategies that optimize daylight exposure to enhance psychological well-being. A scientific narrative review method was employed, analyzing scholarly articles published between 2015 and 2025 from databases such as Scopus, Web of Science, and ScienceDirect. The selection criteria focused on studies related to natural light in architectural design and its psychological effects, using thematic analysis to synthesize key findings on the relationship between daylight exposure and mental health. The review reveals that natural light significantly enhances mood, reduces stress, and improves cognitive performance by regulating circadian rhythms and promoting visual comfort. Architectural strategies such as large windows, skylights, atriums, and reflective surfaces are effective in maximizing daylight exposure. The findings highlight that natural light contributes to mental well-being in various settings, including workplaces, educational institutions, healthcare facilities, and residential spaces, underscoring its importance in human-centric architectural design. Integrating natural light into architectural design is essential for creating environments that support mental health. Thoughtful spatial design that prioritizes daylight exposure enhances well-being, cognitive function, and emotional resilience, making it a critical consideration in contemporary architecture.

The aim of the present study is to design and validate a behavioral model of banking system customers. The research method is a sequential exploratory mixed-methods approach. In the qualitative section, research participants included university professors in fields related to marketing management and business, as well as heads, deputies, and customer relations managers in Bank Day branches in Tehran, totaling 12 individuals selected through purposive (snowball) sampling based on the principle of theoretical saturation. The data collection tool consisted of semi-structured interviews, and the validity and reliability of the tool were evaluated based on the method proposed by Lincoln and Guba. Data analysis was conducted using thematic analysis (Attride-Stirling method) with MAXQDA 2020 software. In the quantitative section, the research method was descriptive-survey, and the statistical population consisted of Bank Day customers in Tehran. Due to the unlimited population, 410 individuals were selected as the statistical sample using Cochran's formula and stratified random sampling. The data collection tool in this section was a researcher-made questionnaire derived from expert opinions in the qualitative section. To assess the validity of the research tool, construct validity was measured using the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy and Bartlett's test of sphericity, while reliability was assessed using Cronbach’s alpha coefficient and composite reliability. Quantitative data were analyzed using descriptive statistics (mean and standard deviation) and inferential statistics with SPSS 22 and SMART PLS 3 software. The results of the qualitative data analysis led to the identification of four overarching themes (banking services, financial affairs, branch characteristics, and human and communication factors) in the form of ten organizing themes (electronic banking, quality and diversity of banking services, foreign exchange and international operations, banking loans and interest payments, investment, internal and external branch design, branch accessibility and welfare facilities, customers, human resources, marketing and advertising) and 66 basic themes. Ultimately, the findings from the quantitative data analysis indicated that the designed model possesses desirable fit and validity.

IoT is a network of smart things. This indicates the ability of these physical things to transfer information with other physical things. The characteristics of these networks, such as topology dynamicity and energy constraint, challenges the routing problem in these networks. Previous routing methods could not achieve the required performance in this type of network. One of the routing methods is utilization of multipath protocols which send data to its destination using routes with separate links. One of such protocols is RPL routing protocol. In this paper, this method is improved using composite metrics which chooses the best paths used for separate routes to send packets. the protocol of Energy and Load aware RPL (ELaM-IoT), has been suggested that it has a rise of RPL protocol. It applies a composite metric, estimated based upon the extant energy, hop count, load & battery depletion index, and Link Expiration Time, for the selection of route. In order to evaluate and report the results, the proposed ELaM-IoT method is compared to the ERGID and ADRM-IoT approaches with regard to average remaining energy, and network lifetime. The results demonstrate the superior performance of the proposed ELaM-IoT compared to the ERGID and ADRM-IoT approaches.

Corporate entrepreneurship is an entrepreneurial process that organizations undergo to enable all employees to function as entrepreneurs, allowing them to continuously, swiftly, and efficiently carry out individual or group activities within the central organization. In this context, knowledge management, innovation, and research and development (R&D) processes can be influential. This study aims to examine the role of knowledge management in corporate entrepreneurship through innovation and R&D. To achieve this, a review of the theoretical literature was first conducted to establish the research framework. Based on this framework, a conceptual model was formulated, and research hypotheses were developed. To test the research hypotheses, the statistical population consisted of managers and experts from a knowledge-based company operating in the oil and gas sector, with a total of 56 individuals. Since no sampling was conducted, the questionnaire was distributed among all personnel. The questions in the questionnaire were adapted from reliable sources, and their validity and reliability were confirmed. Given the non-normal distribution of the data, the partial least squares (PLS) method and Smart PLS 2 software were employed for statistical analysis. Based on the significance values related to the hypotheses, all five hypotheses were confirmed. The effect of knowledge management on R&D was found to be 0.816, the effect of knowledge management on corporate entrepreneurship was 0.842, the effect of knowledge management on innovation was 0.881, the effect of R&D on corporate entrepreneurship was 0.874, and the effect of innovation on corporate entrepreneurship was 0.825. The findings of this study indicate that knowledge management can influence not only corporate entrepreneurship but also innovation and R&D. Furthermore, innovation and R&D can contribute to enhancing corporate entrepreneurship. Considering the components and indicators of each of these variables can help improve three dimensions: innovation, the development of new products and services, or risky processes, ultimately impacting performance.

The purpose of this study is to design an influencer marketing model for attracting tourists in Iran's tourism industry. Given the research objectives, this study is an applied-developmental research. Adopting a qualitative approach and utilizing thematic analysis, an effort was made to propose the intended model. The qualitative study participants include theoretical experts (faculty members specializing in management and marketing at universities). The criterion for selecting the qualitative sample population was faculty members holding a PhD degree with expertise and teaching experience in marketing. Additionally, practical experts, including managers and experts from the Ministry of Cultural Heritage, Tourism, and Handicrafts, were also considered. A combination of purposive and snowball sampling methods was employed. The sample size in the qualitative phase was determined by theoretical saturation, meaning that interviews with theoretical and practical experts continued until theoretical saturation was reached. The saturation point was achieved after conducting semi-structured interviews with 16 experts. Data collection in the qualitative phase was conducted through semi-structured interviews. To ensure the reliability of the qualitative research phase and theoretical saturation, the agreement matrix test and a dual-coder reliability chart were used. The model design and identification of main and sub-themes were carried out using Maxqda 2020 software. Based on the findings, the main themes of the influencer marketing model for attracting tourists in Iran’s tourism industry consist of seven key components: identifying and selecting appropriate influencers, producing and disseminating engaging content, creating targeted campaigns, enhancing audience engagement, utilizing innovative marketing technologies, emphasizing Iran's competitive advantages, and measuring and evaluating marketing effectiveness.

Nowadays, organizations are able to gain sustainable and long-term competitive advantages for themselves by relying their information and knowledge which leads to improve their performance. For this mean, supply chain management has been the focus of management researchers as an effective approach in creating long-term relationships between raw material suppliers and final consumers. The purpose of writing the current research is to represent model for measuring the impact of supply chain management on business performance in dairy industries. The statistical population in the qualitative section included 14 senior managers of the subsidiaries of Damdaran Company and in the quantitative section included 610 experts and managers in different levels of Damdaran company from which 236 ones were selected as a sample. At first, the research model was obtained through semi-structured interviews with experts and during the coding process. The final supply chain management model includes dimensions of financial factors (price and production cost components), integration (supplier and customer integration components) and environmental factors (including eco-friendly design, green productivity, and intra-organizational factors components) and includes 28 indicators. Meanwhile, final model of business performance was included the dimensions of strategic performance (market position components and competitive power development components) and market performance (including financial performance components and sales performance) and includes 14 indicators. Finally, the results of structural equation modeling illustrated that supply chain management has a significant impact on the business performance of dairy industries.

The present study aimed to design and validate a competency development model for digital transformation leadership in the country's banking system. This research follows an exploratory mixed-methods approach. The qualitative phase employed thematic analysis, while the quantitative phase utilized a survey research method. The statistical population in the qualitative section consisted of 15 banking system experts, selected through purposive sampling based on the principle of theoretical saturation. In the quantitative section, the statistical population included bank managers and supervisors across the country, from whom a sample of 335 individuals was selected using stratified random sampling. In the qualitative phase, data collection was conducted through field research using semi-structured in-depth interviews. Similarly, in the quantitative phase, data collection was also based on field research, utilizing a researcher-developed questionnaire. Data analysis in the qualitative phase was performed using coding techniques, while in the quantitative phase, descriptive and inferential statistical methods were employed. The results indicated that digital leadership competencies include individual characteristics, digital intelligence, and digital capability/capacity. Additionally, competency development methods comprise self-learning, virtual training, experience transfer, coaching and consulting, role-playing, behavior analysis, job rotation, on-the-job training, workshops, mentoring, and career path planning. The findings also revealed that bank managers possess the necessary competencies and are in a favorable state.