Management Strategies and Engineering Sciences

The geotourism industry, as a subset of the tourism sector, is significantly influenced by economic changes and digital marketing patterns. This study aims to examine the impact of economic changes on digital marketing patterns in the geotourism industry of Mazandaran Province. This study adopts a descriptive-analytical approach and employs quantitative methods. Data were collected through the distribution of structured questionnaires among 50 experts and practitioners in the tourism industry of Mazandaran. The statistical population included all experts and managers related to the geotourism industry as well as tourists in the region. To analyze the data, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) multi-criteria decision-making model was utilized to assess the extent to which the counties of Mazandaran Province have benefited from economic changes and digital marketing patterns. The results indicated that Neka County, with the highest final score (18113.89) and ranking first, is the most successful county in leveraging economic changes and implementing effective digital marketing strategies. In contrast, Ramsar and Babol counties, ranked 16th and 15th, respectively, face more challenges in this regard. Additionally, Sari, Miandorud, Babolsar, and Fereydunkenar counties were identified as regions with strong potential for attracting tourists. These findings enable decision-makers and geotourism industry practitioners to identify the strengths and weaknesses of each county and formulate more optimal strategies for improving economic conditions and enhancing digital marketing activities. Ultimately, this research can contribute to the sustainable development of the geotourism industry in Mazandaran.

This study aims to develop an indigenous social media marketing model tailored to the banking services industry in Iran through a mixed methods approach. In the qualitative phase, grounded theory methodology was employed to analyze data collected from 16 semi-structured interviews with marketing experts, digital banking professionals, and academic specialists. The data were coded using Strauss and Corbin’s three-stage process—open, axial, and selective coding—using MAXQDA software. The findings revealed six main categories, fourteen subcategories, and seventy-four indicators influencing social media marketing strategies. Based on these, a theoretical model was proposed, identifying causal conditions (social media-related factors, managerial factors, structural factors), strategic categories (marketing and human resource actions), contextual conditions (relationship marketing and ICT), intervening conditions (customer trust, perceived risk, environmental threats), and outcomes (awareness, perceived quality, customer satisfaction and trust, environmental opportunities and threats). In the quantitative phase, a researcher-developed questionnaire was distributed to 384 customers of Bank Mellat who use social media. The instrument's validity was confirmed through content validity index (CVI) and content validity ratio (CVR), and reliability was assessed via Cronbach’s alpha, composite reliability, and Fornell-Larcker criteria. Structural equation modeling using partial least squares (PLS) indicated significant relationships among the proposed variables. The findings underscore the importance of strategic, contextual, and organizational factors in enhancing the effectiveness of social media marketing in the banking sector. The study offers a comprehensive framework for banking institutions to optimize their digital marketing strategies and improve customer engagement, satisfaction, and trust.

This study aims to experimentally assess the simultaneous effectiveness of lead-core rubber base isolators and linear viscous dampers in enhancing the seismic stability of mid-rise steel frame structures. An eight-story steel flexural frame model, scaled 1:4 and designed per the 4th edition of the 2800 Code for Soil Type III, was subjected to dynamic testing using a two-dimensional shake table. The experiment was conducted under fifteen real earthquake accelerograms. First, the model was tested without control devices. Then, four lead-core rubber isolators were installed at the base and two linear viscous dampers on the second and fourth floors. MEMS accelerometers and laser displacement sensors recorded the seismic responses. A paired t-test was used to statistically compare the stability index before and after the control intervention, with significance set at p<0.05. The results demonstrated a statistically significant improvement in structural stability. The average stability index increased by 12.7%, with all 15 records showing consistent positive differences (Δ ranging from 0.0070 to 0.0126). The paired t-test yielded t(14) = 21.769, p < 0.0001, and a Cohen’s d ≈ 5.5, indicating a very large effect size. Time-history analysis revealed a reduction in interstory drift of up to 30% and a substantial decline in floor accelerations, bringing the structure into the code-defined serviceability range. The system displayed consistent performance across a spectrum of seismic inputs, with a coefficient of variation at 18%, indicating high reliability. Economically, the system reduced the demand for secondary reinforcement, offsetting part of its installation cost. The combined use of base isolators and viscous dampers significantly improves seismic performance by reducing drift and accelerations, while ensuring structural stability and economic feasibility. This integrated approach presents a reliable and sustainable solution for enhancing the seismic resilience of mid-rise buildings.

Effective risk management and strategic planning are critical determinants of success in construction projects. To explore the academic landscape surrounding construction risk management, a total of 284 scholarly sources were systematically reviewed. These included 222 journal articles, 36 conference proceedings, 21 books, one doctoral dissertation, two master's theses, and two patents, all published between 2000 and 2024. The literature was identified through rigorous searches of academic databases, digital libraries, and scientific search engines. The analysis reveals that while conventional approaches—such as Work Breakdown Structure (WBS), regional strategies, and equilibrium-based frameworks—remain in use, increasing scholarly attention has been directed toward mathematical modeling techniques grounded in optimization theory. These models are favored for their enhanced efficiency and efficacy in selecting risk response strategies within construction environments. The advanced model identified in the literature integrates multi-objective optimization, accounting not only for traditional parameters such as time, cost, and quality, but also for project resilience and resource fluctuation control. Notably, the incorporation of plan resilience and resource fluctuation control into an optimization-based risk management framework marks a significant innovation in the field. Furthermore, this model supports the concurrent identification and evaluation of both influential and affected risks, enabling the development of synchronized response strategies that foster synergistic risk mitigation. Application of this model in large-scale and high-rise construction projects demonstrates its potential to improve overall project outcomes by systematically balancing key performance objectives.

This study was conducted with the aim of designing a model for the selection of branch managers at Bank Melli Iran. The strategy of this research is qualitative and based on the meta-synthesis approach. The statistical population of the study consists of two parts: documents, articles, theses, books, and scientific records related to the research topic from the years 2011–2024 (Gregorian calendar), and interviews with three groups—academic experts, senior professionals, and executive managers of Bank Melli Iran. Sampling of scientific sources was performed using a purposive method aligned with the meta-synthesis approach. Additionally, purposive and snowball sampling methods were used to identify research participants, continuing until theoretical data saturation was reached. Ultimately, 16 individuals were selected as the final sample. Data were analyzed using the seven-step approach by Sandelowski et al. (2007). Based on the data analysis, the model for selecting branch managers at Bank Melli Iran was designed in the form of 6 main categories, 17 subcategories, and 81 concepts. According to the findings of this study, it can be concluded that the selection and appointment of branch managers at Bank Melli Iran requires comprehensive and systematic attention to a combination of professional competencies, behavioral capabilities, ethical characteristics, managerial skills, and strategic insight.

The specific oil shocks also exhibited the lowest Akaike criterion values under a normal distribution. Analyzing the results of the copula model under the Student’s t-distribution revealed that significant risk spillovers exist between the two markets during all three types of shocks. However, regarding oil supply shocks, the results confirm the presence of spillover effects from oil supply shocks to the stock market, and the 95% Value at Risk (VaR) is higher than the corresponding conditional CoVaR at the same probability level. This indicates that risk spillover from the oil market supply is associated with lower levels of value at risk in the stock market. Regarding demand-side shocks and specific oil shocks, it was also observed that significant and asymmetric risk spillover effects from the oil market to stock returns are statistically significant and confirmable. The Expected Shortfall (ES) results, except for supply shocks, were consistent with the conditional Value at Risk calculations. In fact, for all three types of oil supply shocks, the ES value is higher at the 95% level, but at the 5% level, the conditional expected shortfall is greater. This, despite confirming the existence of risk spillover effects, suggests that the spillover of oil supply shocks to the stock market is not symmetric. The spillover effects have varied across different levels of market risk exposure, indicating a long-term interpretation of shock spillover effects. Additionally, increasing and decreasing values of supply shocks have not had the same impact on stock returns.

In today's world, a dynamic economy and intense competition in the business arena have increasingly challenged brands. Among them, legacy brands that once dominated the market gradually lose their position and may even be forgotten by consumers. To prevent this and maintain their market share, many of these brands turn to brand revival strategies. The objective of these strategies is to restore the lost credibility and popularity of the brand and to re-establish a connection with customers. This is achieved through the renewal and reconstruction of brand identity, the introduction of new and appealing products and services, and the adoption of innovative marketing and advertising methods. In essence, brand revival is an effort to return to the peak of success and re-enter market competition. The present study aimed to examine brand revival strategies using a meta-synthesis method. In this regard, employing the seven-stage method of Sandelowski and Barroso, the required data were extracted from scientific and research articles published over a 24-year period (1990-2014). Following an initial review, 24 articles were selected for in-depth analysis. The extracted data were analyzed using MAXQDA 2020 software based on the conceptual model of the study. The results of this analysis led to the identification of 94 sub-strategies, which were categorized into seven main strategies. The primary brand revival strategies encompass various aspects, which can be broadly classified as follows: brand identity and image management to clarify and enhance audience perception of the brand, product renewal and development to meet contemporary market demands and attract new customers, integrated marketing to ensure consistency and alignment across all marketing and advertising activities, customer relationship management to establish a sustainable and effective connection with customers and increase their satisfaction, market repositioning to define an appropriate competitive position for the brand and attract target customers, brand heritage and authenticity management to preserve and enhance the historical and cultural values of the brand, and finally, organizational change management to implement necessary modifications in the organizational structure and processes to support brand revival strategies.

Online reputation or electronic reputation can be considered one of the most significant intangible assets of companies. The objective of this study is to design a model for enhancing the reputation of online brands. The present research is qualitative in terms of methodology and employs a descriptive-exploratory approach with a phenomenological method for data analysis. The research instrument used in this study is in-depth (semi-structured) interviews. The statistical population consists of 10 experts and specialists in the field of marketing for online brands. In this study, members of the expert panel were selected using a purposive sampling approach. Key codes were extracted through a thematic analysis approach and analyzed using MAXQDA software. The validity of the research findings was assessed and confirmed based on the criteria proposed by Creswell (2002). The results indicated that the categories and components of online brand reputation enhancement include 11 main categories: online brand reputation, cultural factors, customer experience management, website quality, website security, store social responsibility, social media marketing, content marketing, targeted and intelligent advertising, product and service quality, and customer satisfaction, along with 63 subcategories.

The geotourism industry, as a subset of the tourism sector, is significantly influenced by economic changes and digital marketing patterns. This study aims to examine the impact of economic changes on digital marketing patterns in the geotourism industry of Mazandaran Province. This study adopts a descriptive-analytical approach and employs quantitative methods. Data were collected through the distribution of structured questionnaires among 50 experts and practitioners in the tourism industry of Mazandaran. The statistical population included all experts and managers related to the geotourism industry as well as tourists in the region. To analyze the data, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) multi-criteria decision-making model was utilized to assess the extent to which the counties of Mazandaran Province have benefited from economic changes and digital marketing patterns. The results indicated that Neka County, with the highest final score (18113.89) and ranking first, is the most successful county in leveraging economic changes and implementing effective digital marketing strategies. In contrast, Ramsar and Babol counties, ranked 16th and 15th, respectively, face more challenges in this regard. Additionally, Sari, Miandorud, Babolsar, and Fereydunkenar counties were identified as regions with strong potential for attracting tourists. These findings enable decision-makers and geotourism industry practitioners to identify the strengths and weaknesses of each county and formulate more optimal strategies for improving economic conditions and enhancing digital marketing activities. Ultimately, this research can contribute to the sustainable development of the geotourism industry in Mazandaran.

This study aims to develop an indigenous social media marketing model tailored to the banking services industry in Iran through a mixed methods approach. In the qualitative phase, grounded theory methodology was employed to analyze data collected from 16 semi-structured interviews with marketing experts, digital banking professionals, and academic specialists. The data were coded using Strauss and Corbin’s three-stage process—open, axial, and selective coding—using MAXQDA software. The findings revealed six main categories, fourteen subcategories, and seventy-four indicators influencing social media marketing strategies. Based on these, a theoretical model was proposed, identifying causal conditions (social media-related factors, managerial factors, structural factors), strategic categories (marketing and human resource actions), contextual conditions (relationship marketing and ICT), intervening conditions (customer trust, perceived risk, environmental threats), and outcomes (awareness, perceived quality, customer satisfaction and trust, environmental opportunities and threats). In the quantitative phase, a researcher-developed questionnaire was distributed to 384 customers of Bank Mellat who use social media. The instrument's validity was confirmed through content validity index (CVI) and content validity ratio (CVR), and reliability was assessed via Cronbach’s alpha, composite reliability, and Fornell-Larcker criteria. Structural equation modeling using partial least squares (PLS) indicated significant relationships among the proposed variables. The findings underscore the importance of strategic, contextual, and organizational factors in enhancing the effectiveness of social media marketing in the banking sector. The study offers a comprehensive framework for banking institutions to optimize their digital marketing strategies and improve customer engagement, satisfaction, and trust.