https://barresybazargani.itsr.ir/ Commercial Surveys en daily 1 Wed, 21 Jan 2026 00:00:00 +0330 Wed, 21 Jan 2026 00:00:00 +0330 https://barresybazargani.itsr.ir/article_737581.html The research and development (R&D) tax credit policy allows firms to deduct part of their R&D expenditures from income tax or carry unused credits forward to subsequent years. Introduced under the Knowledge-Based Production Leap Law, this policy aims to stimulate business investment in R&D. However, its actual implementation has fallen far short of expectations. This study therefore provides a diagnostic analysis of the implementation of the R&D tax credit policy in Iran to identify the factors underlying its limited effectiveness. Using an exploratory qualitative approach and a case study design, data were collected through 23 semi-structured interviews with policymakers and implementers, R&D assessment experts, and managers of eligible firms. The data were analyzed using content analysis with MAXQDA software. The findings identify five major clusters of implementation challenges: shortcomings in policy design and coverage; weak institutional coordination and a lack of mutual trust among key implementing actors; complexity, ambiguity, and instability in implementation procedures and the supporting electronic system; limited policy, analytical, and administrative capacity of responsible institutions; and the heterogeneity of firms and R&D activities, which has resulted in unequal access for small and start-up firms. The findings illustrate a design–implementation gap, suggesting that without institutional trust, effective inter-sectoral coordination, and targeted investment in implementation capacity, even well-designed policy instruments are unlikely to generate substantial increases in business R&D investment. https://barresybazargani.itsr.ir/article_737577.html Investment is widely recognized as a key driver of economic growth, making the identification of its determinants essential for effective policymaking. Given the strategic importance of the industry, mining, and trade sectors in Iran’s economy, this study investigates the main determinants of investment in these sectors using an econometric approach. The analysis focuses on the effects of sectoral value added, lagged oil revenues, lending interest rates, outstanding credit facilities, real money supply, and economic sanctions. The estimation results indicate that investment in the industrial sector is significantly influenced by industrial value added, lagged oil revenues, lending interest rates, outstanding credit facilities, real money supply, and sanctions. Similar results are obtained for the mining sector, where mining value added, lagged oil revenues, lending interest rates, outstanding credit facilities, real money supply, and sanctions significantly affect investment. Likewise, investment in the trade sector is determined by trade value added, lagged oil revenues, lending interest rates, outstanding credit facilities, real money supply, and sanctions. The findings also reveal that economic sanctions have adversely affected investment primarily through financial and banking restrictions, particularly by limiting the participation of foreign banks in opening letters of credit. In addition, reduced investment in the oil and gas sector has generated negative spillover effects on industry through extensive backward and forward linkages, resulting in higher financing costs, increased production costs, underutilized industrial capacity, and delays or suspension of investment projects. The findings suggest that improving access to finance, stabilizing exchange rates, strengthening investment incentives, and reducing financial constraints are essential for promoting investment in Iran’s industry, mining, and trade sectors. https://barresybazargani.itsr.ir/article_737582.html The development of high-tech industries in Iran, particularly the electric vehicle (EV) industry, is constrained by institutional, policy, and techno-economic barriers rooted in weak integrated governance. This study adopts a quantitative descriptive-survey approach to identify, prioritize, and analyze the structural barriers to EV development in Iran and to identify the requirements for integrated governance. The study population consisted of managers, experts, and specialists in the automotive, energy, supply chain, and policymaking sectors. A total of 67 participants were selected through purposive and snowball sampling. Data were collected using a researcher-developed questionnaire comprising nine independent variables and 36 items. Its validity was confirmed using the Delphi method and the CVR and CVI indices. Data were analyzed through multivariate regression modeling. The findings classified the structural barriers into two broad categories: institutional challenges (institutional fragmentation, contradictory policies, infrastructure gaps, and lack of value chain integration) and techno-economic challenges (energy supply-demand imbalance, weak key technologies, financing constraints, and the assembly trap). The results indicate that energy supply-demand imbalance and technological weaknesses exert the strongest direct effects. However, the underlying causes lie in institutional fragmentation and fragmented governance, where contradictory policies and institutional fragmentation create the conditions for techno-economic crises and lock the automotive industry into an assembly trap. The study identifies three fundamental prerequisites for integrated governance: a single cross-sectoral coordinating authority, an integrated long-term national strategy, and a transition from an assembly-based model to an integrated value chain. Redefining the governance structure is a necessary prerequisite for any technology development strategy or industrial investment in this sector. https://barresybazargani.itsr.ir/article_737586.html The emergence of digital technologies and Industry 4.0 has introduced a new approach to digital transformation for organizations and societies. Alongside the emergence of new business models, these developments have also created disruptions across industries and global markets. In an era characterized by increasing volatility, uncertainty, complexity, and ambiguity, where unexpected crises occur frequently, organizations' ability to develop resilient systems has become essential for ensuring continuity and long-term sustainability. Therefore, this study aims to identify the growing potential of digital technologies to enhance industrial resilience and transform continuous changes into opportunities for business improvement. This study adopts a bibliometric approach based on a systematic literature review. By searching relevant keywords in major scientific databases and screening the retrieved publications, 44 articles in the field of industrial resilience and 7 articles on industrial digitalization were selected for analysis. Subsequently, a meta-synthesis was conducted to analyze the extracted qualitative data and identify the key digital enablers and industrial resilience essentials. The proposed framework identifies industrial resilience essentials across four temporal phases: before a crisis (anticipation), during a crisis (coping), after a crisis (adaptation), and the long term (business continuity). It also categorizes digital enablers into seven groups: information technology, artificial intelligence, cloud computing, simulation technologies, cyber-physical systems, internet-enabled systems, and additive manufacturing. https://barresybazargani.itsr.ir/article_737584.html Given the important role of exports in economic growth and regional development, this study aims to identify and prioritize the barriers to food industry exports in Sistan and Baluchestan Province. Export barriers were identified in six major categories: infrastructural, political, economic, market, legal, and human resource and managerial factors, and were evaluated based on expert opinions. The barriers were prioritized using Grey Relational Analysis (GRA) according to five criteria: severity of impact, probability of occurrence, cost implications, time delay, and controllability. Data processing was performed using the Python programming language. The results indicate that infrastructural barriers are the most significant constraints on food industry exports in the province, followed by political and economic barriers. Among the individual barriers identified, weaknesses in the cold chain and export logistics, shortages of skilled labor in food processing and packaging, inadequate packaging, weak advertising and branding, and instability in exchange rate and trade policies were found to be the most critical obstacles. The findings suggest that the major challenge facing food industry exports in the province extends beyond production and is largely associated with weaknesses in post-production activities, including storage, packaging, transportation, marketing, and policymaking. Accordingly, policymakers and provincial authorities should shift from a production-oriented approach to a value chain-oriented approach by prioritizing the development of cold chain infrastructure, upgrading export terminals, improving refrigerated transportation, enhancing packaging technologies, developing a skilled workforce, strengthening advertising and branding, and reducing policy uncertainty in provincial export planning. https://barresybazargani.itsr.ir/article_737585.html The purpose of this study is to develop a paradigmatic model for revitalizing failed brands through entrepreneurs’ personal brands. The study is applied-developmental in terms of purpose and adopts a qualitative approach based on Strauss and Corbin’s grounded theory. The participants consisted of 12 experts with practical experience, including branding experts, marketing and brand managers, branding consultants, and entrepreneurs with established personal brands, selected through purposive and theoretical sampling. Data were collected through in-depth semi-structured interviews until theoretical saturation was achieved and analyzed using MAXQDA through open, axial, and selective coding.The findings revealed that causal conditions, including brand revitalization planning, digital branding, mobilization of revitalization resources, and customer participation, influence the central phenomenon of failed brand revitalization. Contextual conditions, including entrepreneurs’ reputation and symbolic capital, as well as the intervening condition of brand equity erosion, shape the strategies and actions. The main strategy identified was leveraging entrepreneurs’ personal brands, which leads to outcomes such as improved brand identity, brand repositioning, and reconstruction of market legitimacy. The results demonstrate that failed brand revitalization is a dynamic and multidimensional process. Entrepreneurs’ symbolic capital and reputation provide the foundation for trust-building, while brand equity erosion increases the need for more intensive revitalization strategies. Strategic use of entrepreneurs’ personal brands reduces the trust gap and creates a renewed brand narrative. This study presents an integrated model to help brand managers and entrepreneurs facilitate failed brand revitalization through personal branding. https://barresybazargani.itsr.ir/article_737507.html Refractory cement, due to its resistance to high temperatures, corrosion, and abrasion, is widely used across various industries. Considering the availability of limestone required for its production in Hamedan Province, this study evaluates the feasibility of establishing a refractory cement plant in the region using a mixed-methods (quantitative–qualitative) approach. Data were collected through library research and semi-structured interviews with 16 industry experts. The research was conducted in three stages, including marketing studies, technical–technological assessments, and financial–economic analysis. Domestic and international market trends were forecast based on trade data using structured interviews and regression analysis. For estimating fixed and operating costs, statistical data and inquiries from reliable sources were used. Ultimately, the financial evaluation was carried out using COMFAR software. The results indicate that despite challenges related to the supply of high-purity alumina, refractory cement production in Iran has strong growth and export potential. The supply–demand gap shows a positive trend, increasing from 10,993 tons in 2023 to 32,054 tons in 2026. In addition, neighboring countries present a significant export capacity of approximately 458,000 tons. The total required investment is estimated at 27,590,511 million rials, and the project reaches its break-even point in the first year of operation at 11.55% of production capacity. The payback period is 4.67 years, the net present value (NPV) is 9,098,279 million rials, and the internal rate of return (IRR) is 42.51%, indicating that the project is financially and economically viable. https://barresybazargani.itsr.ir/article_737576.html This study aimed to design and validate a sustainable marketing model centered on digital transformation in Iran's automotive industry, using an exploratory mixed-methods approach. In the qualitative phase, semi-structured interviews were conducted with 15 academic experts and senior automotive managers, and data were analyzed using grounded theory and MAXQDA software. In the quantitative phase, a researcher-developed questionnaire based on qualitative findings, with a five-point Likert scale, was distributed among 200 managers and experts, and data were analyzed using partial least squares (PLS) via SMART PLS. Qualitative findings revealed causal conditions including institutional and regulatory pressures, changes in consumer behavior, technological competition, and sustainable development requirements. Technological and informational infrastructures, along with structural-industrial characteristics, were identified as contextual conditions, while structural and processual challenges in the sustainable digital transition path were recognized as intervening conditions. The core strategy involves implementing digital transformation through data-driven approaches, intelligent customer relationship management, marketing channel integration, improved decision-making, and sustainable value chain reinforcement, leading to economic, environmental, social, technological, and industrial outcomes. Quantitative validation confirmed statistically significant relationships and path coefficients, affirming the predictive role of model variables. R² values demonstrated adequate explanatory power, and fit indices confirmed measurement and structural model adequacy. The innovation lies in presenting an integrated paradigmatic framework that synthesizes sustainable marketing, digital capabilities, institutional requirements, emerging consumer behavior, and automotive structural contingencies, enabling empirical assessment of relationships among these dimensions. https://barresybazargani.itsr.ir/article_737579.html Based on the concept of the technological trajectory in developing countries, the innovation process in these economies begins as latecomer firms interact with mature foreign companies and acquire knowledge and technology from the developed world. The dynamism of this process can, through open innovation approaches, turn latecomers themselves into sources of technology and innovation. However, the processes and mechanisms that focal firms employ in open innovation to raise their technological capability have not yet been fully identified and documented. This study aims to identify and historically analyze the open innovation patterns of Iran's steel industry from the perspective of technological learning. To this end, a case study method and a qualitative content analysis approach were adopted, and data were gathered through semi-structured interviews with 19 experts from four stakeholder groups (policymakers, steel producers, engineering firms, and academic research institutes) until theoretical saturation was reached. The findings reveal three main patterns: "the instructive organization as an integration of inbound and outbound knowledge flows," "the creation of engineering companies as spin-off firms," and "the creation and development of an innovation ecosystem for knowledge-frontier technologies." The historical analysis shows that each pattern has a definite starting point but no end point, persisting as overlapping layers that remain active to the present; moreover, over time the key actors and dominant learning mechanisms in each period shift, moving the industry from incremental toward radical innovation. T https://barresybazargani.itsr.ir/article_737580.html In the entrepreneurship literature, digitalization has often been measured as a uniform construct, and previous research has largely neglected how its distinct dimensions interact with the institutional context. Adopting a disaggregated approach, this study breaks digitalization down into three core components: connectivity, internet use, and digital technology integration. It empirically investigates whether these components have heterogeneous effects on entrepreneurial activity (TEA) and whether institutional quality asymmetrically moderates each of them. To this end, panel data from 41 countries (both developed and developing) over the period 2007–2023 are used, along with the System GMM estimator to discourse endogeneity and represent entrepreneurial dynamics. The results reveal that: first, all three digital components have a positive and significant impact on entrepreneurship, but the magnitudes differ, with connectivity being the strongest direct driver. Second, institutional quality asymmetrically moderates the effect of each component; notably, the moderating effect of institutions on digital technology integration (the most advanced layer of digitalization) is very large and significant, while this effect is much weaker for connectivity (the infrastructural layer). Third, a final-effect analysis shows that in weak institutional environments, connectivity yields the dominant return, but as institutions improve, digital technology integration achieves the highest payoff. These findings carry important policy implications: in countries with weak institutions, priority should be given to investing in communication infrastructure, whereas in economies with strong institutions, https://barresybazargani.itsr.ir/article_737583.html Purpose: Iran's home appliance industry is shifting from an assembly-based model toward original design manufacturing (ODM) and export development. This study aims to develop alternative market scenarios for the 1414 horizon (2035–2036), identify key drivers, and provide a strategic roadmap.Methodology: This applied-developmental, descriptive-analytical research adopts a futures studies approach. Using a sequential exploratory mixed method, PESTEL scanning and expert panels identified 34 variables. Structural analysis via MicMac software extracted 12 key drivers. The Global Business Network (GBN) model was then used to identify critical uncertainties and formulate alternative scenarios.Findings: Four critical uncertainties shape the industry's future: international interactions/sanctions, smart ecosystem penetration, environmental sustainability, and governance regulatory structure. Four scenarios were developed: Technological Leap, Fragile Growth, Divergent Development, and Chain Collapse. Export market development is only achievable through dynamic capabilities and business model renewal.Conclusion: This research offers a native model linking foresight to operational marketing capabilities. Strategies such as modular architecture development and service-oriented models are robust strategies that, regardless of which scenario unfolds, will ensure the survival and growth of Iran's home appliance industry in its turbulent environment. https://barresybazargani.itsr.ir/article_738612.html This study aims to identify and explain the strategies, platforms, and barriers affecting the application of marketing mix components for electric vehicles on social media. Given the exploratory nature of the subject and the need to achieve a deep, context-specific understanding of the phenomenon, a qualitative approach and the Grounded Theory strategy were employed. The research participants consisted of 19 experts, including academic experts (university professors in business management) and practical experts (managers and executives in the electric vehicle industry and digital marketing specialists), selected through purposive sampling based on the theoretical saturation principle. Data were collected through in-depth, semi-structured interviews and analyzed using thematic analysis in three stages of open, axial, and selective coding with the assistance of MAXQDA software. https://barresybazargani.itsr.ir/article_738919.html The retail industry, amidst rapidly expanding data, is transitioning toward a phygital ecosystem where machine learning (ML) plays a vital role in transforming raw data into actionable insights. The ultimate effectiveness of these applications depends on precisely analyzing purchasing behavior, predicting future trends, and proactively influencing consumer decisions. However, existing literature lacks a comprehensive, structured guiding framework specifically a technology roadmap that outlines the precise sequence of technical investments and operational processes required to achieve these macro-objectives. Although current studies consistently highlight ML’s high potential to make marketing decisions smart and optimized, research has largely remained fragmented, offering isolated insights rather than an integrated architectural blueprint. To address this literature gap, this study employs a qualitative meta-synthesis approach. By systematically extracting, analyzing, and integrating key components from selected prior research, this study develops a comprehensive foundational framework and roadmap designed to streamline ML integration within modern retail ecosystems. https://barresybazargani.itsr.ir/article_738920.html This study investigates the effect of university-educated labor on industrial profitability across the provinces of Iran. Using panel data of industries across Iranian provinces from 2013 to 2021 (1392–1400) and a fixed-effects regression model, the analysis examines the relationship between university-educated labor and industrial profitability. The dependent variable is profitability, while the independent variables include industry size, value-added growth, university-educated labor, industry concentration, and the square of concentration. The findings indicate that industry size and value-added growth have a positive and statistically significant impact on profitability, consistent with theoretical expectations. In contrast, university-educated labor exhibits a negative effect on profitability. This adverse effect may be attributed to increased wage costs, a mismatch between acquired skills and operational industry needs, or because the returns to human capital materialize over a longer term than the short-term profitability horizon. Furthermore, the negative coefficient on the squared concentration term implies an inverted-U-shaped relationship between concentration and profitability. Specifically, as concentration increases, profitability initially rises but declines after an optimal threshold. This phenomenon may result from reduced competition, inefficiencies at very large scales, or heightened regulatory interventions in highly concentrated markets. The results underscore the necessity of revisiting policies for hiring specialized labor, improving the alignment between the educational system and industry requirements, and simultaneously considering labor quality, skill matching, and competitive market structure in industrial policymaking. Increasing the share of university-educated labor without proper skill alignment, as well as excessive market concentration, can have adverse effects on firm financial performance. https://barresybazargani.itsr.ir/article_738921.html Investment is one of the key factors in the sustainable development of religious tourism, and the continued attraction of investors in this field depends on the economic and financial attractiveness of investment opportunities. However, identifying the factors that shape this attractiveness and determining its role in the realization and sustainability of investor attraction remain among the major challenges in religious tourism. Accordingly, the present study aims to design and test a structural model of the economic and financial attractiveness of investment and to explain its effect on the realization and sustainability of investor attraction in religious tourism. In this model, the institutional environment and governance of religious investment, along with the infrastructure and capabilities of religious destinations, are considered antecedent constructs; the economic and financial attractiveness of investment is considered a mediating construct; and the realization and sustainability of investor attraction is considered the outcome construct.In terms of purpose, this study is applied, and in terms of data collection method, it is descriptive-survey research. The statistical population consisted of active investors in tourism and religious tourism, managers and experts of related organizations, and tourism economics specialists in 1404. Purposeful judgmental sampling was used, and 100 individuals were selected as the sample. Data were collected using a researcher-made questionnaire and analyzed through structural equation modeling . The results showed that the infrastructure and capabilities of religious destinations, as well as the institutional environment and governance of religious investment, have a positive and significant effect on the economic. https://barresybazargani.itsr.ir/article_738922.html The present study was conducted with the aim of structural modeling of factors affecting organizational learning in industrial organizations (case study: Iran Khodro Company). To achieve the research objective, an consisted of senior experienced managers of Iran Khodro. Purposive sampling was conducted, and theoretical saturation was achieved with 12 individuals. The statistical population of the quantitative section also included managers and experts of Iran Khodro, estimated at 400 individuals using Cochran's formula, and simple random sampling was selected. Semi-structured interviews and questionnaires were used for data collection. Interview analysis was performed using thematic analysis method in MAXQDA 24 software. To determine the relationships and leveling of the components, interpretive structural modeling (ISM) and MICMAC software were utilized, and for model validation, the partial least squares (PLS) method and SMART PLS software were used. The findings indicated that organizational learning in the industry is a multi-level phenomenon formed through the interaction of three categories of factors: fundamental factors (infrastructures, transformational leadership, and learning culture), intermediate factors (individual competence, technological learning, technical-operational learning, cross-sectoral collaboration, and knowledge management), and strategic factors (measurement, innovation-orientation, and foresight). This chain ultimately leads to "learning-oriented organizational maturity"—a state in which learning becomes institutionalized in the organization's structure, culture, and decision-making. The innovation of the presentmanageable system in industrial organizations. This research demonstrates that organizational learning maturity is not the result of a single factor in isolation, but is formed through the cohesive linkage of infrastructural, human, technological, operational, knowledge-based, and strategic factors. https://barresybazargani.itsr.ir/article_740918.html This study addresses gaps in customer experience literature by examining how digital touchpoint experience influences customer loyalty on e-commerce platforms. Drawing on the Stimulus-Organism-Response (S-O-R) framework, we model digital touchpoint experience as the stimulus, digital engagement and customer satisfaction as organisms, and customer loyalty as the response within the context of Digikala. Methodologically, this applied, descriptive-survey research collected data from 188 active Digikala customers using convenience sampling and a standardized questionnaire by Nanta et al. (2025). Data analysis was performed using SPSS 28 and SmartPLS 3.The findings revealed that digital touchpoint experience significantly and positively affects digital engagement (β=0.437), customer satisfaction (β=0.346), and customer loyalty (β=0.298). Additionally, digital engagement significantly predicted customer satisfaction (β=0.232) and customer loyalty (β=0.203), while customer satisfaction also positively influenced customer loyalty (β=0.213). The mediating roles of both digital engagement and customer satisfaction were supported, with customer satisfaction emerging as the stronger mediator. The structural model demonstrated acceptable fit (SRMR = 0.038; NFI = 0.891). Theoretically, this study contributes to the literature by validating the S-O-R framework and comparing alternative mediating pathways within an Iranian e-retail context. Practically, the findings offer actionable insights for online retail managers to design user experiences and loyalty strategies centered on digital engagement and customer satisfaction. https://barresybazargani.itsr.ir/article_741030.html Abstract:Purpose: The rapid expansion of e commerce in recent years, despite its economic and operational benefits, has created significant environmental challenges, including higher energy consumption, intensified CO₂ emissions, and growing volumes of various types of waste. Under these conditions, leveraging advanced digital technologies—particularly Artificial Intelligence (AI) and the Internet of Things (IoT)—can play a decisive role in mitigating negative environmental impacts by improving process efficiency and enhancing decision-making quality. This study aims to analyze how the environmental sustainability of e commerce in Iran is influenced by the level of adoption of AI and IoT technologies.Method: The research employed an exploratory mixed methods design (qualitative–quantitative). In the qualitative phase, key concepts related to the research topic were identified through a systematic review of theoretical and empirical literature. Subsequently, using content analysis and open, axial, and selective coding, the main dimensions, components, and their interrelationships were extracted. In the quantitative phase, a questionnaire was developed to test and validate the relationships among the identified variables and was administered to 56 informed experts. The collected data were analyzed using structural equation modeling techniques with Smart PLS software.Findings: The results indicate that the adoption of AI and IoT technologies has a positive and statistically significant effect on enhancing the environmental sustainability of e commerce. The findings further reveal that the purposeful use of these technologies—through resource conservation, transport optimization, and reducing packaging related waste—can substantially contribute to achieving environmental sustainability goals in the e commerce sector.