درخت حوزه‌های تخصصی

Many organizations in the power and energy sector rely on research and development (R&D) projects to achieve their strategic goals. Given the simultaneous execution of multiple projects, managing R&D portfolios effectively has become an essential capability for adapting to environmental changes and maintaining competitive advantage. This study aims to present a model that identifies and prioritizes the factors influencing R&D portfolio management in the energy sector. Employing a mixed-method approach, the research integrates qualitative data collected through interviews with fifteen experts in the energy sector—analyzed using grounded theory via MAXQDA 2020—with quantitative data from 134 managers and experts, analyzed using Smart PLS V.3. In the qualitative phase, 105 codes were categorized into six dimensions, with 17 codes excluded during factor analysis, resulting in a validated model comprising 88 codes across six dimensions. The proposed model emphasizes critical factors such as project selection, project evaluation, project definition, budget allocation, portfolio analysis, and addressing challenges in portfolio integration. By balancing these dimensions, the model aims to reduce risks, optimize resource allocation, and enhance the probability of commercial success for R&D projects. This study offers new insights into R&D portfolio management in the Iranian energy industry, addressing the unique challenges of this sector. It provides a systematic framework for selecting, evaluating, and balancing R&D projects while aligning with organizational strategies to ensure the effective commercialization of research outcomes. The findings also stress the importance of integrating local investment in R&D to drive technological innovation and sustainable economic development in the energy sector.

Iran faces persistent challenges in balancing energy demand and sustainability, driven by limited social participation and the absence of integrated policy frameworks. This study introduces an innovative hybrid decision-making approach that combines PESTEL, SWOT, and Analytic Hierarchy Process (AHP) models to identify, evaluate, and prioritize strategies for enhancing public participation in sustainable energy management. The research adopts a mixed-method design, integrating qualitative expert interviews and content analysis in MAXQDA with quantitative weighting and ranking through Expert Choice AHP. The proposed framework captures both macro-environmental influences and internal institutional capacities, linking social-behavioral insights with data-driven prioritization. Results indicate that developing targeted educational programs and creating interactive digital platforms are the highest-priority strategies, with normalized weights of 0.35 and 0.30, respectively, followed by local collaboration networks and incentive-based policies. The findings reveal that applying a combined social and analytical modeling approach can increase public participation potential by over 60 % and contribute to a 25 % reduction in energy consumption in the medium term. The study offers a novel quantitative–qualitative framework adaptable for developing countries seeking to operationalize community engagement within national energy transition policies.

This study investigates the impact of global crude oil price fluctuations on the volatility of the Iranian Rial–U.S. Dollar exchange rate over the period November 2011 to August 2025. Using daily data and employing GARCH-family models—including GARCH(1,1), EGARCH(1,1), and GJR-GARCH(1,1,1) under heavy-tailed distributions—we examine whether oil price shocks influence the mean and conditional variance of exchange rate returns. The results indicate that higher oil prices significantly appreciate the Rial, reflecting Iran’s dependence on oil revenues and foreign exchange inflows. Volatility dynamics reveal strong persistence, with shocks exhibiting long memory. Asymmetric effects are also evident: negative oil price shocks increase exchange rate volatility more than positive shocks, highlighting the destabilizing role of downturns in global oil markets. Diagnostic tests confirm the adequacy of the estimated models, with EGARCH and GJR specifications providing the best fit. The findings underscore three key policy implications. First, Iran’s exchange rate remains highly sensitive to oil revenues, reinforcing the need for structural diversification. Second, the persistence of volatility complicates short-term stabilization, demanding long-term reserve and fiscal policies. Third, the asymmetric impact of oil downturns calls for proactive risk management to mitigate volatility in times of declining oil prices. Overall, the study provides new evidence on the oil–exchange rate nexus in an oil-exporting economy, offering lessons for macroeconomic management under external shocks. Robustness checks — including Bai–Perron breakpoint tests and alternative model specifications with event dummies — confirm the main findings.

Agricultural products, are mostly perishable, and ensuring their quality through methods like cold storage or optimal conditions can present significant economic challenges for retailers and small-scale producers. In some cases, these products lose their quality and marketability within a span of less than 24 hours. The main challenge in adopting this strategy is determining the timing and amount of the price discount. To optimize price discounting, four functions need to be estimated: a) a time-dependent quality function, b) a price change function, c) a demand function that is a function of price and quality, and d) an objective function, which is considered here as the retailer's profit function. We employ dynamic pricing models that integrate factors such as quality degradation, inventory levels, and consumer behavior. The research data was collected from three fruit and vegetable stores in Gorgan city. The time period was three months, comprising all working days. Each seller was asked to report the price and quantity of sales on an hourly basis from the beginning to the end of the working day. In this way, about 1000 data were recorded from each store. Tomato was selected as case study due to their widespread consumption, continuous supply, and rapid perishability. The results show that price discounts can significantly enhance profitability while reducing the risk of unsold and wasted products. Specifically, the findings indicate that implementing price discounts every 3 to 4 hours yielded the highest profitability. The average discount is 35%, leading to an 82% increase in gross profit. In contrast, shorter discount intervals (every 1 to 2 hours) with an average discount of 18% improved gross profit by 73%. On the other hand, longer discount intervals (every five to seven hours) with an average discount of 46% resulted in a 66% increase in gross profit. Furthermore, this study further emphasizes how crucial consumer perception is to the effectiveness of dynamic pricing methods. The perception of lower product quality brought on by excessive discounting may have a detrimental effect on long-term store credit and customer trust. Perishable product waste can be reduced through the implementation of price reduction strategies. However, the results indicate that sellers’ profits increase in the absence of price reductions. Future research could enhance this framework by incorporating additional factors that influence product quality, such as temperature, humidity, and product variety; examining the effects of consumer price expectations on demand; extending the model to other perishable products, including meat and dairy; and leveraging advanced technologies, such as blockchain and artificial intelligence, to improve dynamic pricing and inventory management.

Climate change, with its gradual and complex impacts, has increasingly inflicted damages on the agricultural sector of arid and semi-arid regions in Iran, including the Zayandeh-Rud Basin. This study aims to develop strategic adaptation policies to enhance agricultural resilience in response to climate change in this basin. The research is based on the Sendai Framework for Disaster Risk Reduction (SFDRR) and the resilience criteria established by the World Economic Forum (2013). A descriptive-analytical methodology was employed, combining documentary studies, field surveys, and the Delphi policy method to achieve expert consensus. Purposive sampling targeted faculties, agricultural experts of the Ministry of Agriculture, as well as producers and exporters of agricultural products with substantial expertise in Climate change issues, adaptation policies, and resilience. Data collection instruments consisted of four structured questionnaires designed to identify strengths and weaknesses, weight resilience criteria, prioritize policies, and select strategies, complemented by semi-structured interviews. Initially, to determine the strategic position of agriculture in the Zayandeh-Rud Basin, Internal Factor Evaluation (IFE), External Factor Evaluation (EFE), and Internal-External (IE) matrices were utilized. Subsequently, the Analytic Hierarchy Process (AHP) and the multi-criteria decision-making PROMETHEE method were employed to prioritize adaptation policies aimed at enhancing resilience to Climate Change. Suitable strategies were developed and extracted through SWOT analysis, and finally, the Quantitative Strategic Planning Matrix (QSPM) was used to evaluate the relative attractiveness and feasibility of each strategy, thereby selecting the implementable final policies. Findings indicated that agriculture in the Zayandeh-Rud Basin, with a final internal factor score of 2.04 and external factor score of 2.12, is in defensive position (survival mode) and exhibits low resilience due to water transfer and scarcity, land fragmentation and subsidence, and weaknesses in modern infrastructure. The most attractive adaptation policies identified under the defensive strategy include equitable water distribution (Total Attractiveness Score (TAS=1.46), development-oriented water resource planning (TAS=1.38), optimization of water. consumption and reduction of losses (TAS=1.35), control of groundwater levels (TAS=1.23), reform of regulations related to land fragmentation (TAS=1.18), and farmer participation in water resource management (TAS=1.16(. The proposed solutions emphasize strengthening integrated and basin-based water governance, implementing participatory strategic management models, investing in modern and soft technologies, gradually revising water-related laws and regulations, and expanding research and national strategy formulation. The results of this study provide actionable, stakeholder-inclusive recommendations for policymakers to enhance sustainability and resilience in vulnerable agricultural regions.