Management Strategies and Engineering Sciences

The purpose of this study is to evaluate the indicators of Financial Technologies (FinTech) using a mixed-methods approach in the banking industry. This research is applied in nature and descriptive-analytical in terms of methodology, conducted through a cross-sectional survey. The research employs an exploratory mixed-method approach, combining qualitative (Delphi method) and quantitative (Importance-Performance Analysis) techniques. The statistical population of the study consists of two groups: the qualitative group includes banking experts with doctoral degrees in financial management and information and communication technology, while the quantitative group comprises an unlimited number of customers from the banking industry. A purposive sampling method was used, with a sample size of ... determined for the qualitative group, and 384 participants for the quantitative group based on Cochran’s formula. Based on semi-structured interviews, the desired components were identified using thematic analysis. In the quantitative section, partial least squares (PLS) regression was used to determine the relationships between variables and their associated importance coefficients, with Importance-Performance Matrix Analysis used for component ranking. Based on Delphi results, a researcher-made questionnaire was applied in the quantitative phase. Excel software was used in the qualitative section, while SMARTPLS was utilized in the quantitative phase. Banks' goals and planning based on FinTech, considering the rapid changes in the market and customer needs, should be designed to adapt to these changes and innovations. Strategic planning based on FinTech helps banks to remain flexible in the face of new market challenges and opportunities, paving the way for their success.

The aim of this study is to design a model for the impact of viral marketing in social networks using the Adaptive Neuro-Fuzzy Inference System (ANFIS). This research utilizes the Adaptive Neuro-Fuzzy Inference System due to its ability to implement human knowledge through concepts like timestamps and fuzzy rules, its nonlinear nature, adaptability, and superior accuracy compared to other methods in conditions with limited data. These features are among the most significant advantages of ANFIS systems. The MATLAB software was employed in the ANFIS framework to modify inputs and outputs. This research followed the steps of input fuzzification, fuzzy rule base development, fuzzy inference engine construction, aggregation phase, and defuzzification when employing the Adaptive Neuro-Fuzzy Inference System. Value-based marketing relies on the principle that individuals who have used a product or service and had a positive experience share this experience with others, encouraging them to use the product or service as well. Viral marketing is, in a way, a form of partnership where an individual shares their experience with another person who needs the product or service. Due to its broad reach, low cost, high speed, and simplicity, companies can implement controlled viral marketing campaigns through principled and regulatory-compliant marketing efforts, thereby contributing to the growth of the company. This is because, within a short period, many people become familiar with the company and its brand name.

This research examines the factors influencing the implementation of strategic management accounting methods. Based on library research and statistical analyses, this study investigates the role of three variables—networking, organizational culture, and information system quality—in the implementation of these methods. The study is applied in terms of its outcome and is classified as descriptive-survey research in terms of its goal. The statistical population consists of manufacturing and industrial companies listed on the Tehran Stock Exchange in 2022, totaling 287 companies, with 166 questionnaires used for the analysis. Hypothesis testing was performed using Partial Least Squares Structural Equation Modeling (PLS-SEM), along with t-statistics, significance levels, and path coefficients. The research utilized Excel 2016, SmartPLS 3, and SPSS 26 software. The results indicate that networking, innovation-based culture, results-based culture, and information system quality significantly influence the implementation of strategic management accounting methods. Furthermore, information system quality significantly affects the role of networking and the implementation of these methods. While innovation-based culture has a significant indirect effect on the implementation of strategic management accounting methods through the mediating role of networking, this indirect effect was not confirmed for results-based culture. Based on the findings, it can be stated that the implementation of strategic management accounting methods is more likely in organizations with effective and extensive communication networks, high-quality information systems, and an innovation- and results-driven culture. Additionally, the use of effective communication networks, coupled with a quality information system, and supported by an innovation-based culture, facilitates the implementation of these methods. In results-based cultures, managers will continue to study and gather the necessary information to achieve strategic organizational goals, even in the absence of effective communication networks.

The study aimed to investigate the factors influencing employee learning based on the heutagogy approach at Day Insurance Company. By focusing on individual, organizational, and environmental factors, the research sought to identify their contributions to self-determined learning in a workplace context. The study further aimed to validate a structural equation model of these factors and their relationships with employee learning outcomes, providing insights for fostering heutagogical practices in organizations. A quantitative survey-based research design was employed to collect data from employees of Day Insurance Company. A researcher-designed questionnaire was developed to assess factors influencing heutagogical learning, which included individual (e.g., motivation, job satisfaction), organizational (e.g., managerial support, feedback mechanisms), and environmental (e.g., socio-cultural factors) dimensions. The sample consisted of 230 employees, selected using the Cochran formula. Data were analyzed using SPSS for descriptive statistics and SmartPLS for structural equation modeling to evaluate the relationships among variables and the overall model fit. The results revealed that individual factors had the strongest influence on employee learning outcomes, with motivation and job satisfaction emerging as critical contributors. Organizational factors, such as managerial support, job expectations, and technological infrastructure, also significantly impacted learning outcomes, while environmental factors played a comparatively weaker role. The model demonstrated a strong fit (R² = 0.834), indicating that the identified factors accounted for 83.4% of the variance in employee learning outcomes. These findings highlight the importance of both individual agency and organizational support in implementing heutagogical learning practices. The study underscores the effectiveness of the heutagogy approach in fostering employee learning, with individual and organizational factors playing pivotal roles. Organizations should prioritize strategies that enhance motivation, provide supportive feedback, and invest in technological infrastructure to support self-determined learning. These findings contribute to the growing body of research on heutagogy and its practical applications in workplace learning.

Today, marketing has become a fundamental and essential element for the success of both profit and non-profit organizations. Given the continuously changing environment and the increasing number of uncontrollable external factors and threats in the market, mere gradual improvement is no longer sufficient. All organizations and companies need to move toward creativity and innovation to ensure their survival and active presence in the market. On the other hand, the aim of organizational intelligence is to accelerate the decoding and transfer of organizational knowledge, identify opportunities, and solve business problems more quickly than in the past. This study aims to propose a qualitative model of the indicators and components of internal marketing, organizational intelligence, and organizational innovation in the Tax Administration of Iran. The research is applied in purpose and uses a thematic analysis method. The sampling method was snowball sampling, and the main data collection method was conducting in-depth interviews with 15 experts, managers, and specialists in the fields of marketing and tax administration until theoretical saturation was reached. The thematic analysis process, following the approach provided by Braun and Clarke (2006), was conducted in six stages. Initially, 213 primary codes were obtained, and after removing duplicate codes, 35 selective codes were extracted. By aggregating the selective codes into broader semantic domains, six main and sub-themes were identified and named. The data were analyzed using MAXQDA software, both separately and in general. In the findings, two sub-themes and 13 basic themes were identified for internal marketing, two sub-themes and 10 basic themes for organizational innovation, and two sub-themes and 11 basic themes for organizational intelligence.

This study examines the impact of Environmental, Social, and Governance (ESG) indicators on the selection and ranking performance of corporate banking clients. Given the increasing importance of sustainability in financial systems, this research seeks to investigate the effects of ESG indicators on reducing credit risk and improving financial performance. The data utilized includes information from clients of selected banks in emerging markets and has been analyzed using advanced econometric methods. The results indicate that ESG indicators play a significant role in reducing financing costs and enhancing investor confidence. Furthermore, banks that are leaders in implementing ESG criteria have achieved more sustainable performance through better risk management. Finally, it is suggested that standardized policy and reporting frameworks be designed in developing countries to facilitate the implementation of ESG criteria.

The metropolises of developing countries have consistently struggled with traffic and its associated problems, leading to significant losses. Considering the importance of this issue, the present study aims to explain strategies for developing clean transportation in District Eight of Shiraz. This study employed mixed methods (descriptive-analytical and survey). In other words, data collection utilized both field methods (questionnaire completion and expert interviews) and library research. Furthermore, to achieve the research objectives, the SWOT model and the QSPM matrix were applied. The study's findings indicate that the superior strategy for developing clean transportation in District Eight of Shiraz is the ST strategy. In other words, for the development of clean transportation, the studied area should adopt a defensive (ST) strategy as its operational foundation. Regarding the development of clean transportation in the studied area, the top operational strategy priority should be providing diverse transportation plans for public use.

This study aims to identify and validate key policy indicators to facilitate the transition from conventional transportation modes to sustainable alternatives, with the goal of reducing environmental pollution in Iran. A qualitative approach was employed using the fuzzy Delphi method to achieve expert consensus on the critical dimensions and indicators of sustainable transportation policies. The study engaged 20 experts, including university professors and senior professionals from the transportation and environmental sectors, selected through purposive and snowball sampling methods. Data collection involved semi-structured interviews, and the analysis focused on coding and triangulation to identify relevant policy dimensions. Triangular fuzzy sets (l, m, u) were used to quantify expert opinions and address uncertainties, ensuring the reliability of the findings. The study identified six key dimensions for effective policymaking: the role of policymakers, policy approaches, mechanisms for creating dynamism, policymakers' capabilities, mastery of environmental conditions, and the provision and utilization of necessary data. Specific indicators under these dimensions include evidence-based policymaking, participatory approaches, collaboration with academic and professional experts, integration of reliable data, and alignment with contemporary scientific paradigms. The findings emphasize the importance of institutional frameworks, systematic approaches, and stakeholder engagement in fostering sustainable transportation systems. The proposed indicators achieved consensus among experts, with fuzzy scores exceeding the threshold for validation. The results provide a comprehensive framework for developing sustainable transportation policies that address environmental challenges. The identified dimensions and indicators align with global best practices and offer actionable insights for policymakers. By emphasizing participatory and evidence-based approaches, the findings can guide national efforts to reduce environmental pollution through the promotion of sustainable transportation modes.