انتشارات "فن پایا"مطالعات علوم محیط زیست2588-685111220260622Investigating the Impact of E-Commerce Adoption on Waste Reduction and Recycling in Businesses: Evidence from Selected EU Countriesبررسی تأثیر پذیرش تجارت الکترونیک بر کاهش زباله و بازیافت در کسبوکارها: شواهدی از کشورهای منتخب اتحادیه اروپا111881120125172010.22034/jess.2026.591282.2469FAمحدثهعظیمی پناه راینبخش اقتصاد، دانشکده مدیریت و اقتصاد، دانشگاه شهید باهنر کرمان، کرمان، ایران0009-0002-7255-4267علیرضاحسن زاده جزدانیبخش اقتصاد، دانشکده مدیریت و اقتصاد، دانشگاه شهید باهنر کرمان، کرمان، ایران0000-0003-0276-3055مهدینجاتیبخش اقتصاد، دانشکده مدیریت و اقتصاد، دانشگاه شهید باهنر کرمان، کرمان، ایران0000-0003-4103-869XJournal Article20260713EXTENDED ABSTRACT<br>Introduction<br>The rapid expansion of the digital economy and e-commerce has fundamentally transformed global production, distribution, and consumption paradigms, offering unprecedented opportunities for economic growth and operational efficiency. As physical processes are increasingly replaced by digital alternatives—a phenomenon known as dematerialization—there is a theoretical expectation of reduced environmental pressure. However, the concurrent rise in e-commerce has introduced a complex environmental paradox. While digitalization optimizes supply chain management and reduces inventory waste, it simultaneously exacerbates new environmental challenges, most notably the exponential increase in individual packaging, fragmentation of the last-mile delivery, and elevated rates of product returns. Despite these conflicting outcomes, empirical research quantifying the net effect of business-level e-commerce adoption on internal waste management indicators remains scarce. Most existing literature focuses heavily on macroscopic carbon footprints or qualitative consumer-side packaging issues rather than firm-level operational outcomes. To address this critical gap, the present study aims to quantitatively investigate the impact of e-commerce adoption on waste generation and recycling rates among businesses in 12 selected European Union (EU) member states over the period from 2015 to 2020. Furthermore, the study explores the moderating role of environmental policy stringency (EPS) in shaping these relationships, providing nuanced insights into the interplay between technological adoption and institutional frameworks.<br>Materials and methods <br>This research adopts an applied, descriptive-analytical approach utilizing balanced panel data from 12 EU member countries (Austria, Belgium, Czech Republic, Germany, Hungary, Italy, Netherlands, Poland, Portugal, Slovakia, Slovenia, and Spain) spanning from 2015 to 2020. Data were meticulously compiled from highly authoritative international databases, including Eurostat, the World Bank, and the Organization for Economic Cooperation and Development (OECD). The dependent variables are per capita waste generation (WG) and the recycling rate (RR). The primary independent variable is the rate of e-commerce adoption among businesses (ECOM), measured as the percentage of enterprises engaged in electronic sales. The moderating variable is the OECD’s Environmental Policy Stringency (EPS) index. Control variables encompass energy consumption (NRG), gross domestic product per capita (GDP), and population density (POPDENS). Given that official waste management statistics are systematically reported on a biennial basis (even years), a scientifically rigorous linear interpolation method was employed to estimate values for the intervening odd years (2015, 2017, 2019), ensuring a continuous time series while preserving local macroeconomic trends. For the econometric analysis, preliminary diagnostic tests (Chow, Breusch-Pagan, and Hausman) were conducted, which collectively indicated that the Random Effects model was the most appropriate structural specification. However, subsequent tests confirmed the presence of cross-sectional heteroscedasticity and serial autocorrelation within the panel data. To robustly correct for these classical assumption violations, the models were estimated using the Estimated Generalized Least Squares (EGLS) method, fortified with cluster-robust standard errors to ensure the validity of statistical inferences.<br>Results and discussion <br>The econometric estimations yielded highly significant and nuanced findings. In the first model (Waste Generation), the direct coefficient of e-commerce adoption was -4.96 (p < 0.01), indicating a strong waste-reducing potential inherent to digital commerce operations. However, the interaction term between e-commerce and environmental policy stringency (ECOM × EPS) exhibited a significant positive coefficient of +4.70 (p < 0.01). Marginal effect analysis reveals a conditional relationship: e-commerce significantly reduces per capita waste generation only in regulatory environments where the EPS index is relatively weak (below a threshold of approximately 2.87). In countries with stricter environmental regulations—which encompasses the sample mean (EPS ≈ 2.99)—the net effect of e-commerce neutralizes and even shifts to a slightly positive value. This dynamic can be explained through institutional isomorphism; under weak regulations, the intrinsic efficiencies of e-commerce (e.g., dematerialization, inventory optimization) create a substantial comparative advantage over traditional retail. Conversely, stringent regulations enforce high resource-efficiency standards across all market participants, eroding the relative advantage of digital platforms while exposing the rebound effects of increased packaging waste associated with granular e-commerce logistics. <br>A parallel conditional dynamic emerged in the second model (Recycling Rate). The direct effect of e-commerce on recycling was positive (+2.95, p < 0.01), highlighting the capacity of e-commerce reverse logistics to facilitate the collection of recyclable materials. Yet, the interaction coefficient (ECOM × EPS) was highly negative (-2.88, p < 0.01). Consequently, the positive marginal impact of e-commerce on recycling rates is sustained only at lower EPS levels (below 2.79). At higher regulatory stringency levels, this effect diminishes and turns marginally negative. <br>Furthermore, the analysis highlighted the profound independent impact of institutional frameworks. The EPS index exhibited the largest direct effects across both models, drastically reducing waste generation (coefficient: -12.38) and substantially boosting recycling rates (coefficient: +7.38). This provides robust empirical validation for the Porter Hypothesis, demonstrating that rigorous environmental policies actively stimulate systemic efficiency and circularity rather than merely acting as economic constraints. Additional findings indicated that higher energy consumption correlates with increased waste and decreased recycling, while GDP per capita growth reflects absolute decoupling from waste generation, aligning with the Environmental Kuznets Curve. Interestingly, higher income levels negatively impacted recycling rates, a phenomenon theorized by Becker’s allocation of time model, where the rising opportunity cost of time in affluent societies deters household participation in time-consuming waste sorting.<br>Conclusion <br>The findings unequivocally demonstrate that the environmental impact of e-commerce is not absolute, but deeply conditional upon the prevailing institutional and regulatory landscape. While digital commerce acts as a potent catalyst for waste reduction and recycling in environments with nascent environmental policies, its comparative ecological benefits are largely neutralized under highly stringent regulatory regimes, where the rebound effects of packaging and fragmented delivery overshadow operational efficiencies. Therefore, policymakers must not view the transition to a digital economy as an automatic substitute for robust environmental governance. <br>To harness the synergies between the twin transitions of digitalization and sustainability, several strategic interventions are recommended. For advanced economies like the EU, transitioning from prescriptive regulations to smart, incentive-based frameworks is crucial. Policymakers should provide tax incentives for platforms adopting fully circular packaging and enforce Extended Producer Responsibility (EPR) mandates rigorously. The implementation of the Digital Product Passport (ESPR) is essential to eliminate the "free-rider" problem currently exploited by cross-border e-commerce sellers, ensuring full accountability across the global value chain. Moreover, urban planning should leverage population density by integrating municipal waste management systems with e-commerce delivery networks, transforming reverse logistics into a cost-effective, high-yield channel for recovering secondary raw materials. In developing regulatory environments, such as Iran, authorities should preemptively capitalize on the structural efficiencies of growing digital platforms to bypass traditional linear models, while concurrently institutionalizing EPR frameworks for dominant tech companies before a "throwaway society" culture becomes deeply entrenched.گسترش اقتصاد دیجیتال و تجارت الکترونیک با ایجاد تحول در شیوههای تولید، توزیع و مصرف، فرصتهای جدیدی برای رشد اقتصادی فراهم کرده است. با این حال، تجارت الکترونیک میتواند چالشهای زیستمحیطی جدیدی را تشدید نماید. پژوهش حاضر با هدف بررسی تأثیر پذیرش تجارت الکترونیک بر تولید زباله و نرخ بازیافت در ۱۲ کشور عضو اتحادیه اروپا طی دوره ۲۰۱۵ تا ۲۰۲۰ انجام شده است. برای برآورد مدلهای پژوهش، روش حداقل مربعات تعمیمیافته (EGLS) همراه با خطاهای استاندارد مقاوم خوشهای به کار گرفته شده است. یافتهها نشان میدهد رابطه میان پذیرش تجارت الکترونیک و سرانه تولید زباله، رابطهای شرطی و وابسته به شدت سیاستهای زیستمحیطی (EPS) است: ضریب مستقیم تجارت الکترونیک برابر 4.96- ضریب جمله تعاملی آن با EPS برابر 4.70 برآورد شده است (هر دو در سطح اطمینان ۹۹ درصد معنادار). تنها در کشور-سالهایی با سیاستهای زیستمحیطی ضعیفتر (EPS کمتر از حدود 2.87)، افزایش پذیرش تجارت الکترونیک سرانه تولید زباله را بهطور معناداری کاهش میدهد؛ در حالیکه در سطوح بالاتر سختگیری قانونی (شامل میانگین نمونه (2.99≈EPS)) اثر خالص تجارت الکترونیک مثبت میشود. بهطور مشابه، پذیرش تجارت الکترونیک با نرخ بازیافت دارای رابطهای متقابل و وابسته به EPS است: ضریب مستقیم برابر 2.95 و ضریب جمله تعاملی برابر 2.88-؛ این اثر افزایشی تنها در سطوح پایین سختگیری قانونی برقرار است و در سطوح بالاتر (شامل میانگین نمونه) به اثری اندک و منفی تبدیل میشود. سیاستهای زیستمحیطی نقش تعدیلکننده معناداری در این روابط ایفا میکند. بر این اساس، تجارت الکترونیک را نباید جایگزینی برای سیاستگذاری زیستمحیطی قلمداد کرد؛ بلکه تلفیق آن با ابزارهای تنظیمگری هوشمند (نظیر مشوقهای مالیاتی برای بستهبندیهای چرخشی، الزام پلتفرمهای واسط به رعایت مسئولیت گسترده تولیدکننده در تجارت فرامرزی از طریق پاسپورت دیجیتال محصول (ESPR)، و توسعه زیرساختهای لجستیک معکوس در مناطق پرتراکم شهری) مسیر مطمئنتری برای دستیابی به اهداف اقتصاد چرخشی فراهم میسازد.https://www.jess.ir/article_251720_04c2bd24a8d9c8acbd2fda0aef40760a.pdfانتشارات "فن پایا"مطالعات علوم محیط زیست2588-685111220260622Evaluation of Heavy Metals (Fe,Pb,Cd,Cr,Ni,V,Zn and Cu) Pollution Status in the Sediments of the Hoor Al-Azim Wetland Using Pollution Indicesارزیابی وضعیت آلودگی رسوبات تالاب هورالعظیم به فلزات سنگین (آهن،سرب، کادمیوم، کروم، نیکل، وانادیوم، روی و مس) با استفاده از شاخص های آلودگی112021121425173110.22034/jess.2026.589137.2467FAروزبهمیرزادانشکده علوم دریایی و اقیانوسی، دانشگاه علوم و فنون دریایی خرمشهر، خرمشهر، ایران0009-0004-9845-9094مظاهرمعین الدینیگروه محیط زیست، دانشکده منابع طبیعی، دانشگاه تهران، کرج، ایران0000-0002-3931-5339محسنمحفوظیکارشناس دفتر زیستگاهها و امورمناطق، معاونت محیط طبیعی و تنوع زیستی، سازمان حفاظت محیط زیست،تهران، ایران0000-0002-3931-5339Journal Article20260701Introduction<br>Wetlands are among the most productive and ecologically valuable ecosystems on Earth, providing a wide range of ecosystem services that are essential for environmental sustainability and human well-being. They support exceptionally high levels of biodiversity, serve as habitats for numerous aquatic and terrestrial species, regulate hydrological processes by mitigating floods and storing water, recharge groundwater resources, improve water quality through the retention and transformation of pollutants, sequester carbon, and contribute significantly to climate regulation. In addition, wetlands provide important socioeconomic benefits by supporting fisheries, agriculture, tourism, and the livelihoods of local communities. Despite their ecological and economic importance, wetlands throughout the world have experienced extensive degradation during recent decades owing to rapid urbanization, industrialization, agricultural expansion, population growth, and climate change. These pressures have substantially increased the discharge of industrial effluents, municipal wastewater, agricultural runoff, petroleum products, and other contaminants into aquatic ecosystems.The Hoor Al-Azim Wetland, located in southwestern Iran along the Iran–Iraq border, is the largest permanent freshwater wetland in the country and is recognized as one of the most valuable wetlands in the Middle East. The wetland plays a fundamental role in maintaining regional biodiversity, supporting migratory birds, sustaining fisheries, regulating the local climate, and preserving ecological balance. However, the ecosystem has undergone severe environmental degradation during the past several decades. Intensive oil exploration and extraction, expansion of the Yadavaran and Azadegan oil fields, construction of roads, pipelines and drilling platforms, repeated drought events, upstream dam construction, and reduced freshwater inflow have significantly altered the wetland's hydrological regime and ecological condition. These anthropogenic activities have increased the risk of contaminant accumulation, particularly heavy metals, within wetland sediments.Heavy metals are among the most persistent environmental pollutants because they are non-biodegradable, resistant to natural degradation processes, toxic even at relatively low concentrations, and capable of bioaccumulation and biomagnification through aquatic food webs. Sediments function both as long-term sinks and potential secondary sources of heavy metals, releasing contaminants back into the water column under changing environmental conditions. Consequently, sediment quality assessment provides valuable information regarding the long-term pollution status of aquatic ecosystems and the potential ecological risks posed to benthic organisms and higher trophic levels. Therefore, the present study aimed to determine the spatial distribution of selected heavy metals in surface sediments of the Hoor Al-Azim Wetland and to evaluate sediment contamination using internationally recognized sediment pollution indices and sediment quality guidelines.<br>Materials and Methods<br>Twenty-seven sampling stations were selected throughout the Hoor Al-Azim Wetland to provide representative spatial coverage of different ecological zones while considering potential anthropogenic pollution sources, including oil drilling sites, production facilities, transportation pipelines, industrial infrastructures, inflowing waterways, and relatively undisturbed reference areas. Surface sediment samples (0–5 cm depth) were collected using standard sediment sampling procedures during the study period. The collected samples were placed in clean polyethylene containers, transported to the laboratory under appropriate conditions, air-dried, homogenized, sieved, and prepared for chemical analysis. Concentrations of iron (Fe), copper (Cu), zinc (Zn), nickel (Ni), vanadium (V), lead (Pb), cadmium (Cd), and chromium (Cr) were determined using Inductively Coupled Plasma Mass Spectrometry (ICP-MS), which provides high analytical sensitivity and precision for trace metal determination. Quality assurance and quality control procedures included the analysis of reagent blanks, duplicate samples, certified reference materials, and recovery tests. To evaluate sediment contamination, measured concentrations were compared with international Sediment Quality Guidelines (SQGs), including Threshold Effect Level (TEL), Probable Effect Level (PEL), Effect Range Low (ERL), and Effect Range Median (ERM) values where applicable. In addition, the Geoaccumulation Index (Igeo) was calculated to evaluate contamination intensity relative to background concentrations, whereas the Combination Pollution Index (CPI) was employed to determine the overall pollution status at each sampling station. Statistical analyses were performed using one-way analysis of variance (ANOVA) to identify significant spatial differences among sampling stations at a significance level of P < 0.05.<br>Results and Discussion<br>Heavy metal concentrations exhibited considerable spatial variability throughout the wetland, indicating heterogeneous contamination patterns associated with both natural processes and anthropogenic activities. Mean concentrations ranged from 0.26 to 106.49 mg kg⁻¹ dry weight depending on the element analyzed. Statistical analysis demonstrated significant differences among sampling stations for all investigated metals (P < 0.05), confirming substantial spatial heterogeneity in sediment contamination. The highest concentrations of most heavy metals were consistently observed at Stations 2 and 19, which are located adjacent to intensive oil drilling operations, production facilities, oil transportation pipelines, and associated industrial infrastructure. These observations strongly suggest that petroleum-related activities constitute the dominant source of localized heavy metal contamination in the study area. Additional contributions from industrial wastewater discharge, surface runoff, and atmospheric deposition associated with petroleum production cannot be excluded. Comparison of measured concentrations with international Sediment Quality Guidelines demonstrated that nickel and chromium represent the most environmentally significant contaminants in the wetland sediments. Their concentrations exceeded guideline values at several locations, indicating the potential for adverse biological effects on benthic organisms and other sediment-associated aquatic fauna. Because benthic organisms constitute an important component of aquatic food webs, prolonged exposure to elevated concentrations of these metals may influence ecosystem structure and ecological functioning.The Geoaccumulation Index classified sediment quality from unpolluted to moderately polluted, with Igeo values ranging between −2.81 and 2.11. Similarly, the Combination Pollution Index identified polluted conditions only at Stations 2, 3, 10, and 19 (CPI > 1), whereas the remaining sampling stations exhibited CPI values below one, indicating generally low contamination throughout most areas of the wetland. Collectively, these findings demonstrate that although widespread severe contamination has not yet occurred, localized pollution hotspots are closely associated with oil production activities and require continuous environmental surveillance.<br>Conclusions<br>This study provides a comprehensive assessment of heavy metal contamination in the surface sediments of the Hoor Al-Azim Wetland and offers valuable baseline information for future environmental monitoring programs. The results demonstrate that oil exploration, drilling operations, industrial wastewater discharge, and associated petroleum infrastructure are the principal sources of localized heavy metal contamination. Although most sampling stations exhibited relatively low contamination levels, Stations 2 and 19 showed markedly elevated concentrations of nickel, vanadium, chromium, and lead, reflecting the influence of nearby petroleum-related activities. The sediment quality assessment further indicated that contamination generally ranges from unpolluted to moderately polluted according to the Geoaccumulation Index and Combination Pollution Index. However, nickel and chromium were identified as the metals posing the greatest ecological risk because of their elevated concentrations relative to international sediment quality guidelines and their potential adverse effects on benthic organisms. These findings emphasize the necessity for continuous environmental monitoring, stricter environmental management of petroleum exploration and industrial activities, implementation of effective pollution mitigation measures, and development of sustainable conservation strategies to preserve the ecological integrity, biodiversity, and ecological functions of the Hoor Al-Azim Wetland. The results of this study can also provide a scientific basis for environmental decision-making and long-term management of protected wetland ecosystems affected by industrial development.اکوسیستمهای آبی و منابع آبهای سطحی، شامل رودخانهها، دریاچهها و تالابها، از ارزشمندترین زیستگاههای اکولوژیکی هستند که بهطور مداوم در معرض آلایندههای ناشی از فعالیتهای انسانزاد قرار دارند. تالاب هورالعظیم، بهعنوان یکی از مهمترین تالابهای بینالمللی ایران، در سالهای اخیر بهدلیل گسترش فعالیتهای استخراج نفت، توسعه زیرساختهای صنعتی و کاهش جریانهای ورودی آب، با تنشهای محیطزیستی فزایندهای مواجه شده است. در میان آلایندههای محیطزیستی، فلزات سنگین بهدلیل پایداری، سمیت و قابلیت بالای تجمع زیستی، از مهمترین تهدیدها برای این اکوسیستم محسوب میشوند. هدف از این پژوهش، ارزیابی وضعیت آلودگی رسوبات سطحی تالاب هورالعظیم به فلزات سنگین و بررسی کیفیت رسوبات با استفاده از شاخصهای آلودگی و دستورالعملهای کیفیت رسوب (SQGs) بود. بدین منظور، ۲۷ نمونه رسوب سطحی (عمق ۰ تا ۵ سانتیمتر) جمعآوری شد. پس از آمادهسازی نمونهها و هضم اسیدی، غلظت عناصر آهن،مس، روی، نیکل، وانادیوم، سرب، کادمیوم و کرومبا استفاده از دستگاه طیفسنجی جرمی پلاسمای جفتشده القایی (ICP-MS) اندازهگیری شد. نتایج نشان داد که غلظت فلزات مورد بررسی در محدوده 26/0 تا 49/106 میلیگرم بر کیلوگرم وزن خشک قرار دارد. براساس شاخص تجمع زمینی مولر (Igeo) و شاخص ترکیبی آلودگی (CPI) وضعیت آلودگی رسوبات بهطور کلی در کلاس کم تا متوسط قرار گرفت. همچنین، مقایسه غلظت فلزات با دستورالعملهای کیفیت رسوب (SQGs) نشان داد که نیکل و کروم، در مقایسه با سایر فلزات، دارای بیشترین پتانسیل خطر اکولوژیکی بوده و ممکن است اثرات نامطلوبی بر موجودات کفزی (بنتیک) تالاب داشته باشند. در مجموع، یافتههای این پژوهش بر ضرورت پایش مستمر محیطزیستی، کنترل مؤثر منابع آلاینده و اجرای راهبردهای مدیریتی مناسب بهمنظور حفاظت از این اکوسیستم ارزشمند تأکید میکند.https://www.jess.ir/article_251731_b284ac2cd2c06b776ef83ee3b18e2e5b.pdfانتشارات "فن پایا"مطالعات علوم محیط زیست2588-685111220260622Carbon emission reduction with optimization of integrated smart parking management for electric vehicles considering behavioral uncertainties and power distribution network constraintsکاهش انتشار کربن با بهینهسازی مدیریت یکپارچه پارکینگ هوشمند خودروهای الکتریکی با در نظرگیری عدم قطعیتهای رفتاری و محدودیتهای شبکه توزیع برق112151123125282810.22034/jess.2026.572383.2441FAمحمدمهدیشهبازیاستادیار، گروه مهندسی برق، دانشکده مهندسی، دانشگاه بوعلی سینا، همدان، ایران0000-0002-7685-936Xحسینصالحیاستادیار، گروه مهندسی برق، دانشکده مهندسی، دانشگاه بوعلی سینا، همدان، ایرانJournal Article20260129EXTENDED ABSTRACT<br>This study aims to develop an integrated model for optimal smart electric vehicle parking management, addressing multiple challenges including behavioral uncertainties of owners, market price fluctuations, and network operational constraints. To this end, a two-stage stochastic programming model is formulated that aims to maximize the expected profit of the parking owner by comprehensively considering revenue sources such as charging services, vehicle-to-grid V2G revenue, and flexibility services, and costs including electricity purchase, battery degradation compensation, and operational costs. Uncertainties are modeled in the form of possible scenarios for parameters such as vehicle entry and exit times, initial charge level, and electricity price. The proposed model simultaneously considers the technical limitations of batteries, the constraints of the distribution network using linearized AC load shedding, and the physical constraints of parking. The model implementation was performed using the CPLEX solver in Python and its performance was evaluated by comparing four different scenarios including base case, non-smart charging, V2G activation and full participation on a 50-space parking lot connected to the IEEE 33-bus experimental network. The simulation results show that the proposed model in the full scenario, in addition to a 47% increase in owner profit, leads to a 26% improvement in network losses and an improvement in voltage profile. As a flexible and implementable framework, this model can serve as a decision-making basis for investors and grid operators in effectively integrating electric vehicle fleets with the power system.<br>Introduction<br>As environmental concerns grow, the transition to electric vehicles has emerged as a key solution. However, the rapid spread of these vehicles has created new challenges for power grids, including uncertainty in owner behavior and unpredictable charging patterns. Smart electric vehicle parking lots, by playing the role of energy aggregator, have high potential to participate in the energy market and provide ancillary services to the grid. However, optimal management of these parking lots requires advanced mathematical models that consider technical, economic, and operational aspects in an integrated manner.<br>The main issue of this research is to address the multiple challenges of managing these parking lots. These challenges include: 1) the complexity of planning due to uncertainty in parking times and vehicle charging needs, 2) the risk of managing energy purchases and sales due to fluctuations in electricity prices, 3) the lack of a comprehensive model that simultaneously covers pricing, capacity management, and service delivery issues while considering network and parking constraints, and 4) the low implementability of existing solutions due to neglect of operational constraints.<br>This research is necessary from several perspectives. From a scientific perspective, providing a unified model helps fill a research gap. From an economic perspective, profit optimization models strengthen the incentive for private investment. From an environmental perspective, efficient parking management leads to the integration of renewable resources and reduced energy waste. From a technical perspective, the development of robust algorithms for complex problems is a step forward in power systems engineering. Finally, from a social perspective, improved service delivery can help to achieve wider adoption of this technology and accelerate the transformation of transportation.<br>Materials and Methods<br>The research methodology of this paper is based on the development of an integrated mathematical optimization model for smart parking management of electric vehicles. The model is formulated in a two-stage stochastic programming framework to handle key uncertainties such as vehicle entry and exit times, initial charge levels, and electricity price fluctuations. The modeling begins with defining a set of basic assumptions, including full access to vehicle information, rational behavior of owners, and discrete time partitioning. Then, the technical behavior of the system is modeled in detail. This section includes dynamic equations and constraints of the vehicle batteries such as the permissible range of charge level and charge/discharge power, the model of vehicle presence in the parking lot, and the calculation of battery wear cost. In the next step, the technical constraints of the power distribution network are integrated into the model using a linearized AC load distribution model to maintain voltage stability and not exceed the line capacity. To deal with uncertainties, a scenario-based approach is used. Uncertain parameters such as vehicle travel times are modeled with probability distributions such as normal and beta and then transformed into a set of discrete scenarios. The ultimate objective function is to maximize the expected profit of the parking lot owner considering all sources of revenue and cost under these scenarios. Finally, the model is transformed into a linear mixed-integer programming problem and implemented and solved using the commercial solver CPLEX in the Python environment.<br>Results and Discussion<br>The simulation results indicate the success of the proposed model in achieving the economic and technical objectives. From an economic perspective, the full flexible management scenario using smart charging and V2G capability increased the average daily profit of the owner, which shows a growth of 47% compared to traditional management. The revenue structure in this scenario consisted of 55% charging revenue, 30% V2G revenue, and 15% flexibility services, emphasizing the critical role of V2G in profitability. Dynamic pricing also shifted demand to off-peak hours and attracted owner participation. From a technical perspective, the integration of grid constraints with the linear AC load shedding model led to significant improvements in grid performance. Active power losses were reduced by 26% and the voltage profile during peak hours was improved to a safe level. Also, the maximum load of the lines was reduced from 95% to 78%, which provides a capacity to accommodate 34% more electric vehicles without the need for immediate infrastructure expansion. The network reliability index also improved significantly. Comparison with previous studies shows that the present model has superior performance in terms of increasing profits and improving network stability due to simultaneous consideration of network constraints and uncertainties. Overall, the integrated approach of this research has become a win-win solution for parking lot owners and network operators.<br>Conclusion<br>The results of this study show that the integrated flexible power management model for smart parking lots simultaneously achieves both economic and technical objectives. From an economic perspective, the owner's daily profit increased with charging optimization and V2G activation. From a technical perspective, the integration of grid constraints reduced energy losses, improved voltage quality, and increased electric vehicle acceptance capacity. Comparison with previous research confirms the superiority of this comprehensive approach. As an operational framework, this model can be the basis for policy making and investment in the development of sustainable urban infrastructure.This study aims to develop an integrated model for optimal smart electric vehicle parking management, addressing multiple challenges including behavioral uncertainties of owners, market price fluctuations, and network operational constraints. To this end, a two-stage stochastic programming model is formulated that aims to maximize the expected profit of the parking owner by comprehensively considering revenue sources such as charging services, vehicle-to-grid V2G revenue, and flexibility services, and costs including electricity purchase, battery degradation compensation, and operational costs. Uncertainties are modeled in the form of possible scenarios for parameters such as vehicle entry and exit times, initial charge level, and electricity price. The proposed model simultaneously considers the technical limitations of batteries, the constraints of the distribution network using linearized AC load shedding, and the physical constraints of parking. The model implementation was performed using the CPLEX solver in Python and its performance was evaluated by comparing four different scenarios including base case, non-smart charging, V2G activation and full participation on a 50-space parking lot connected to the IEEE 33-bus experimental network. The simulation results show that the proposed model in the full scenario, in addition to a 47% increase in owner profit, leads to a 26% improvement in network losses and an improvement in voltage profile. As a flexible and implementable framework, this model can serve as a decision-making basis for investors and grid operators in effectively integrating electric vehicle fleets with the power system.https://www.jess.ir/article_252828_946357f8b9ef02a4aef67143fbc10090.pdf