ترتیب بر اساس: جدیدترینپربازدیدترین
فیلترهای جستجو: فیلتری انتخاب نشده است.
نمایش ۶۱ تا ۸۰ مورد از کل ۵۹٬۰۳۳ مورد.
۶۱.

Critical Analysis and Evaluation of the Textbook "Management of Digital Libraries: A Practical Guide" Based on the Standards and Criteria of University Textbooks(مقاله علمی وزارت علوم)

نویسنده:
حوزه‌های تخصصی:
تعداد بازدید : ۵۷ تعداد دانلود : ۶۵
Purpose : The purpose of this paper was to critically analyze the textbook "Management of Digital Libraries: A Practical Guide" written by Mitra Samiei (2023) from Chapar Publications and evaluate it based on the standards and criteria of university textbooks. Method : This was an applied research study in terms of purpose and mixed-method in terms of approach, which used critical qualitative analysis and descriptive survey. A checklist was employed for qualitative evaluation of the content and formal structures of the textbook on a 5-point Likert scale. Findings : According to the analysis results, the textbook scored 54/70 (72%) for formal criteria, which was acceptable. In contrast, it scored 40/70 (53.33%) and 47/70 (67.14%) for structural and writing criteria, respectively, which were unacceptable. It scored 66/95 (69.47%, almost 70%) for content criteria. In general, the textbook under criticism can be suitable and practical for students as a work that collects all the materials available in digital libraries by solving the stated problems. Conclusion : Among the factors that can help improve the present work are modifying photo captions, the publisher's innovative cover design, footnotes for jargon, required persons and concepts, citations, glossary and index, and a list of tables and figures. Therefore, the author is recommended to provide practical examples and new instances, employ up-to-date sources, reduce textbook volume, and avoid duplicate content to improve the current work in the next editions. Also, among the strengths of this textbook is a separate chapter dedicated to digital librarianship, organizational structure, human resources in digital libraries, and the author's credibility and expertise.
۶۲.

Providing a Product-oriented Culinary Tourist Behavior Model Based on Saffron (case study: Qaenat region)(مقاله علمی وزارت علوم)

حوزه‌های تخصصی:
تعداد بازدید : ۶۲
Postmodern tourism is gradually shifting away from mass tourism toward more personalized, experience-based, and interest-driven forms of travel. In response to this trend, many destinations are increasingly emphasizing local cuisine and developing culinary tourism as one of the most dynamic and creative sectors of the tourism industry. However, the successful development of culinary tourism is not possible without a clear understanding of culinary tourists’ behavior. Accordingly, the aim of this study is to explain the behavior of product-oriented culinary tourists, the most specialized segment of culinary tourism, by developing a behavioral model using a mixed-method approach. In the qualitative phase, a meta-synthesis method was applied, while the quantitative phase employed structural equation modeling (SEM) using SmartPLS 4 to identify key dimensions, components, and indicators, as well as to examine the relationships among them. The sample size was determined using the Cochran formula and consisted of 285 participants, who were randomly selected from saffron culinary tourists visiting the Qaenat region. The findings indicate that tourists’ motivation, destination image, and perceived service quality have direct effects on satisfaction and indirect effects on behavioral intentions. Notably, perceived service quality also shows a direct and significant influence on behavioral intentions. Furthermore, the results highlight several key destination characteristics that strongly influence the quality of culinary tourism tours. These include cultural and culinary involvement, accommodation quality, farm-based experiences, food and beverage quality, reliable service delivery, a sense of safety and tranquillity, effective tour organization, and the quality of tour guide services .
۶۳.

Finding all Redacts in Financial Information Systems Based on Neighbourhood Rough Set Theory for Finance Data with Decision Makers Point of View(مقاله علمی وزارت علوم)

حوزه‌های تخصصی:
تعداد بازدید : ۸۹ تعداد دانلود : ۸۶
The Neighborhood Rough Set (NRST) method is a valuable approach for selecting a subset of features from a complete dataset, enabling us to preserve the essential information that the entire feature set provides. In financial datasets, which often contain high-dimensional input features, effective feature selection techniques are crucial to identify the features that yield the most predictable results. In this work, we use neighborhood concepts to discover data dependencies and reduce the number of features in a financial dataset based solely on the data itself, without relying on additional information. This process also includes removing extra features. To facilitate a simple algorithm, we use the properties of neighbourhood rough sets to formulate a Binary Integer Linear Programming (BILP) model. Optimal solutions to these problems are obtained using genetic algorithms. Our approach allows for feature reduction from minimum to maximum cardinality. We demonstrate the efficiency of our proposed method compared to other techniques through various tables showing the results on several benchmark datasets characterized by unbalanced class distributions. The financial dataset used in the present study is taken from the UCI Machine Learning Repository.
۶۴.

A Two-Stage DEA–PROMETHEE II Framework for Fully Ranking Global Retail Firms in a Competitive Environment(مقاله علمی وزارت علوم)

حوزه‌های تخصصی:
تعداد بازدید : ۵۳ تعداد دانلود : ۵۸
Objective : In the competitive global retail industry, achieving sustainable competitive advantage is a key factor for long-term success. This advantage arises when companies effectively utilize their unique resources and capabilities to outperform competitors. Operational efficiency and financial performance are critical for evaluating competitiveness and investment attractiveness. Data Envelopment Analysis (DEA) is a standard method for measuring efficiency, but classical DEA cannot fully rank efficient units. Integrating DEA with multi-criteria decision-making (MCDM) methods addresses this limitation, considering investor-relevant financial ratios. This study proposes a two-stage approach to evaluate and rank retail companies comprehensively.  Methodology: In the first stage, an input-oriented CCR model of DEA is applied, with assets, operating expenses, and the number of employees as inputs, and total revenue and net profit as outputs, to assess relative efficiency. In the second stage, financial indicators—asset turnover, dividend yield, return on equity (ROE), return on assets (ROA), and return on investment (ROI)—alongside DEA efficiency scores are evaluated using the PROMETHEE II method to generate a complete preference-based ranking of retailers. Results : DEA in the first stage provides relative efficiency insights but cannot rank efficient units. Employing PROMETHEE II in the second stage, and considering financial ratios, overcomes this limitation and produces a comprehensive ranking. Validation against DEA, hybrid DEA–PROMETHEE II, and hybrid DEA–AHP rankings demonstrates a strong alignment of the results with the actual market positions of retailers. Conclusion : The proposed method enables investors to identify high-performing companies and provides retailers with a strategic tool to monitor competitiveness, identify strengths and weaknesses, optimize resource allocation, and achieve a sustainable competitive advantage.
۶۵.

Relief Logistics Network Design for Facility Location and Flow Allocation under Environmental Considerations(مقاله علمی وزارت علوم)

حوزه‌های تخصصی:
تعداد بازدید : ۶۷ تعداد دانلود : ۷۳
Objective : This paper develops a single-objective and a bi-objective mixed-integer linear programming model to optimize the post-earthquake relief logistics network involving transfer points, hospitals, and relief centers in Tehran, Iran. The primary aim is to minimize the total time required to transfer injured individuals through the system, while the bi-objective model additionally minimizes penalties for failing to transfer casualties due to capacity shortages.  Methodology: The methodology involves formulating location-allocation models in which demand points, transfer points, hospitals, and relief centers are represented by specific capacity and travel-time parameters. The models are applied to two earthquake scenarios in south-central Tehran: a magnitude-6 event with lower casualties and selective facility activation, and a magnitude-7 event requiring full capacity utilization and a 30% assumed increase in hospital capacity. Results : The model’s effectiveness in optimizing the relief network is demonstrated. For the magnitude-6 scenario, the model selects 10 transfer points, 15 hospitals, and 25 relief centers to minimize total transfer time. For the magnitude-7 scenario, utilizing all available facilities, the model optimally allocates casualties despite severe capacity constraints. Conclusion : The proposed models offer a practical decision-support tool for designing efficient humanitarian supply chains in earthquake-prone urban areas. They underscore the necessity of pre-disaster planning, including establishing transfer points with triage and outpatient capabilities, increasing hospital surge capacity, and ensuring public awareness to direct casualties to designated transfer points.
۶۶.

Industry 4.0-enabled Customer-Centric Supply Chain Processes in Creative Industries: A Meta-Synthesis Framework(مقاله علمی وزارت علوم)

حوزه‌های تخصصی:
تعداد بازدید : ۶۳ تعداد دانلود : ۶۴
Objective : This study addresses the critical gap in understanding how Industry 4.0 technologies—Artificial Intelligence (AI), Internet of Things (IoT), blockchain, and Extended Reality (XR)—synergistically transform customer-centric supply chains in creative industries (e.g., music, fashion, film). It moves beyond fragmented analysis to develop a unified framework for customer-integrated value delivery. Methodology: A systematic meta-synthesis was conducted following established seven-stage protocols. A targeted search across Scopus and Web of Science (2016–2025) identified relevant literature. After stringent screening and quality appraisal (the Critical Appraisal Skills Programme (CASP) checklist), 59 high-quality publications were analyzed through iterative coding and thematic analysis. Results : The analysis produced a novel framework of five interdependent components: (1) Customer-Integrated Value Creation (e.g., AI co-design), (2) Omnichannel & Immersive Fulfillment (e.g., XR commerce), (3) Dynamic Value Capture Models (e.g., fan-driven financing), (4) Algorithmic & Gamified Community Engagement , and (5) Networked Co-Creation Ecosystems . The framework demonstrates how AI, IoT, blockchain, and XR interconnect to transform linear supply chains into agile, experiential, community-integrated value networks. Conclusion : This study presents the first synthesized framework for Industry 4.0-enabled, customer-centric supply chains in creative industries. It bridges technology, culture, and operations management, offering researchers a structured model for future inquiry and providing practitioners with a strategic roadmap for building responsive, community-driven operations. The research fills a significant literature gap and offers a blueprint for competitive advantage in the digital creative economy.
۶۷.

Gamification Really Works Out! An Experiment among Adolescents Reading Gamified Electronic Books(مقاله علمی وزارت علوم)

حوزه‌های تخصصی:
تعداد بازدید : ۶۶ تعداد دانلود : ۱۰۱
Purpose : The current study examined the effectiveness of gamified reading of electronic books among adolescents in school libraries. Method : A randomized sample of students aged 11 to 12 years including two control and experimental groups from four schools participated in this study. According to the Mechanics, Dynamics, and Emotions (MDE) framework, six gamification elements were implemented as group challenges. The experiences were then evaluated based on a quasi-experimental design with a post-test via the GAMEX scale. Findings : Multiple independent t-tests using SPSS 26.0 showed that the gamified experience and its relevant subscales including enjoyment, absorption, creative thinking, activation, absence of negative affect, and dominance differed significantly between the two groups. Therefore, the results revealed that implementing gamification in the reading experience within a gamified environment is highly effective and will influence adolescents' interest, motivation and ability to read in library contexts, which can be of interest to experts and policymakers in education and computer science. Conclusion : Various game mechanisms can be integrated into the educational context or platforms like electronic books to make learning interesting and motivating to the students.
۶۸.

An Advertising Policy Model in Digital Marketing Using Eye Tracking(مقاله علمی وزارت علوم)

حوزه‌های تخصصی:
تعداد بازدید : ۷۶ تعداد دانلود : ۶۹
Purpose : This research aims to develop an advertising policy model in digital marketing based on eye tracking. Method : The research method is qualitative and based on grounded theory. Semi-structured interviews were used to collect information, and data analysis was performed using the Strauss and Corbin method and the paradigm model. Sampling was theoretical sampling using targeted (judgmental) techniques, based on which 15 interviews were conducted with managers and marketing and advertising experts. Findings : The findings of the research show that during the process of open, central and selective coding, the advertising policy model based on the use of eye tracking consists of Causal categories that include Advertising content, Quality of environmental advertising and Promotional features; contextual categories consist of advertising slogans,  billboard elements, analysis of customer eye movements;  intervening categories consist of online advertising,  advertising costs, advertising through media and mass communication; Central categories that consist of environmental advertising status, development of advertising influence, effective advertising on customers' intentions; category of strategies includes advertising message attractions, evaluation of target environmental advertising selection process, advertising based on customers' taste; consequence category includes competitive advantage, currency innovation, Promotion of strategic marketing decisions. Conclusion : The study concludes that the eye tracking-based advertising policy model provides a comprehensive framework for enhancing advertising strategies. The model emphasizes the importance of considering various factors such as advertising content, consumer behavior, and contextual elements in developing effective advertising campaigns. The research highlights the potential of eye tracking in optimizing advertisements and gaining a competitive edge in the market. From a managerial perspective, the model offers actionable insights for marketers to improve customer engagement and increase advertising effectiveness by leveraging eye tracking data. It also suggests that advertisements should be tailored to consumer preferences and the context in which they are viewed. The study advocates for further research in this area to broaden the application of eye tracking technology in other marketing domains and service sectors. From an academic standpoint, this research contributes to the limited body of knowledge regarding environmental advertising and the use of eye tracking in marketing. It provides a foundation for future studies to explore the relationship between visual marketing and consumer behavior, offering insights that could foster innovative advertising strategies in the digital marketing field.
۶۹.

الگوی تحلیلی رابطه فرهنگ متقابل با اثربخشی سازمانی، فرهنگ سازمانی و رهبری سازمانی در شرکت نفت حفاری شمال(مقاله علمی وزارت علوم)

حوزه‌های تخصصی:
تعداد بازدید : ۲۹ تعداد دانلود : ۴۷
هدف پژوهش حاضر ارائه الگوی تحلیلی رابطه فرهنگ متقابل با اثربخشی سازمانی، فرهنگ سازمانی و رهبری سازمانی در شرکت نفت حفاری شمال بود. از نظر هدف این پژوهش کاربردی، به لحاظ شیوه جمع آوری داده ها توصیفی از نوع پیمایشی در نمونه 384 نفری از کارکنان شرکت نفت حفاری شمال بود. داده ها با استفاده از پرسشنامه استاندارد گردآوری و برای تحلیل آن از تحلیل عاملی تأییدی و برای محاسبه ضرایب مسیر از تحلیل مسیر معادلات ساختاری به کمک برآوردهای نرم افزار PLS بهره گرفتیم. نتایج این پژوهش نشان داد که فرهنگ متقابل بر اثربخشی سازمانی (682/0)، فرهنگ سازمانی (611/0) و رهبری سازمانی (567/0) تأثیر معنی دار دارد. بر اساس یافته ها، فرهنگ سازمانی و رهبری سازمانی نقش میانجی در ارتباط بین فرهنگ متقابل و اثربخشی سازمانی ایفا می نمایند.
۷۰.

Community Perceptions of Tourism Development and Its Poverty-Alleviation Potential in Wukari LGA, Taraba State, Nigeria(مقاله علمی وزارت علوم)

حوزه‌های تخصصی:
تعداد بازدید : ۴۸ تعداد دانلود : ۵۷
Tourism is widely acknowledged as a potential engine of economic growth and poverty reduction, particularly in developing countries. This research investigates the impact of tourist growth on poverty reduction in Wukari Local Government Area, Taraba State, Nigeria. The study concentrated on its contributions, problems, and ideas for increasing its pro-poor effect. The questionnaire was applied to obtain data from 400 respondents. The data were examined descriptively. The findings show a clear consensus that tourism may greatly help to poverty reduction, with job creation and income generation highlighted as main advantages. However, fundamental constraints such as inadequate infrastructure, poor security, and little government backing impede tourist expansion. Respondents significantly approve policies such as government infrastructure investment, enhanced security measures, entrepreneurial training, awareness campaigns, and community participation in tourist planning. The study indicates that tourism has significant potential for poverty reduction in Wukari LGA, and that focused interventions are required to solve its obstacles for long-term and inclusive growth.
۷۱.

Analyzing the Elderly Healthcare Ecosystem: A Hybrid Stakeholder Salience and Fuzzy Cognitive Mapping Approach(مقاله علمی وزارت علوم)

حوزه‌های تخصصی:
تعداد بازدید : ۶۱ تعداد دانلود : ۶۳
Objective : The global increase in the elderly population has heightened the need for coordinated, tailored healthcare services that address the complex needs of older adults. This study aims to conceptualize the elderly healthcare ecosystem by identifying its key actors, classifying their roles, and examining the nature of their interactions. Methodology: A multi-stage methodological approach was employed. First, an extensive literature review—focusing on healthcare ecosystems and ageing studies—was conducted to develop an initial analytical framework. Based on this, ecosystem actors were identified and categorized using Mitchell et al.’s Stakeholder Salience Model. An expert panel was then consulted to validate actor attributes and refine classifications. To analyze interdependencies and determine influential actors, a Fuzzy Cognitive Map was constructed, enabling the assessment of causal relationships and the dynamic positioning of stakeholders within the ecosystem. Results : The analysis identified seven groups of actors within the healthcare ecosystem. FCM findings reveal that the elderly, families, and medical centers are the most influential actors. At the same time, the Ministry of Health and Medical Education, insurance and pension funds, and the Ministry of Cooperatives, Labor, and Social Welfare emerge as the most influential and central stakeholders in advancing ecosystem objectives. Conclusion : The study demonstrates that the elderly healthcare ecosystem is inherently dynamic, and stakeholder classifications should not be viewed as static. Attributes such as power, legitimacy, and urgency are fluid and context-dependent. The FCM results further highlight this dynamism by illustrating how shifts in causal relationships can reposition actors across stakeholder categories, underscoring the need for adaptive policymaking.
۷۲.

Hybrid Modeling Approaches for Forecasting the Yield of Iranian Islamic Treasury Bonds(مقاله علمی وزارت علوم)

حوزه‌های تخصصی:
تعداد بازدید : ۸۲ تعداد دانلود : ۱۴۲
Forecasting financial variables, especially the returns of debt instruments, plays a vital role in economic decision-making and risk management. Although the forecasting literature in financial markets is extensive, few studies have focused on predicting the returns of Islamic Treasury Bonds with unconventional structures. Moreover, despite the importance of these bonds, very limited work has been done using machine learning in the debt market. This study aims to predict the returns of Islamic Treasury Bonds using three models: Multiple Linear Regression (MLR), Multilayer Perceptron Neural Network (MLP), and Radial Basis Function Neural Network (RBF). Monthly data from 2018 to 2023 were collected using Excel and Python. The training and evaluation of the models were carried out in MATLAB. Eleven influential variables were selected based on previous studies and expert opinions. The models' performance was evaluated using Root Mean Square Error (RMSE) and the coefficient of determination (R²). The findings indicate that the Multilayer Perceptron Neural Network model has higher accuracy in predicting the returns of Islamic Treasury Bonds compared to Multiple Linear Regression and Radial Basis Function models. These results suggest that neural network models can serve as more effective tools in financial and economic analyses, significantly enhancing forecasting accuracy.
۷۳.

Corporate Risk-Taking and Cash Holdings Adjustment Speed: The Moderating Role of CEO Tenure(مقاله علمی وزارت علوم)

حوزه‌های تخصصی:
تعداد بازدید : ۹۳ تعداد دانلود : ۸۹
The motivations driving cash holdings have a profound influence on corporate decision-making and performance. Exploring the dynamics between risk-taking behaviour, cash reserves, and their adjustment pace provides valuable insights into effective financial resource management. This study examines the impact of corporate risk-taking on the adjustment speed of cash holdings, with a focus on the moderating effect of CEO tenure. A sample of 151 firms listed on the Tehran Stock Exchange from 2011 to 2023 (1,963 firm-year observations) was analysed using multiple regression and the Generalized Method of Moments (GMM) estimator. Results indicate that the adjustment speed of cash holdings is 49.5%. A significant negative relationship exists between corporate risk-taking and the speed of cash holdings adjustment, suggesting that elevated risk-taking decelerates the alignment of cash reserves with optimal levels. Moreover, the findings highlight the moderating role of CEO tenure in the relationship between corporate risk-taking and the speed of cash holdings adjustment; in other words, in firms with longer-tenured CEOs, the negative association between corporate risk-taking and cash holdings adjustment speed is weaker than in firms with shorter-tenured CEOs. These findings suggest that risk-taking hinders swift cash adjustment, necessitating a precise determination of optimal cash levels to prevent liquidity shortages in high-risk scenarios. Additionally, the experience of long-tenured CEOs appears to facilitate better liquidity management, aligning corporate interests with strategic financial goals.
۷۴.

تدوین برنامه راهبردی روابط عمومی صنعت نفت در افق(مقاله علمی وزارت علوم)

حوزه‌های تخصصی:
تعداد بازدید : ۴۳ تعداد دانلود : ۴۴
هدف پژوهش حاضر تدوین برنامه راهبردی روابط عمومی صنعت نفت در افق 1407 است که با رویکرد AFI انجام شده است. در این برنامه با الهام از مدل برنامه ریزی راهبردی هانگر ویلن (AFI)، ابتدا کنکاش محیط داخلی (قوت ها و ضعف ها) و محیط خارجی (فرصت ها و تهدیدها)، ثانیاً تدوین ارکان جهت ساز (چشم انداز، مأموریت و ارزش)، هدف های بلندمدت روابط عمومی صنعت نفت انجام شده است؛ سپس با استفاده از ابزارهای ماتریس ارزیابی عوامل داخلی و خارجی (IE) ، ماتریس عوامل داخلی و خارجی (SWOT)و همچنین هم ترازی ماتریس های (IE) و (SWOT)، موقعیت راهبردی روابط عمومی صنعت نفت مشخص گردید. با توجه به موقعیت راهبردی به دست آمده، استراتژی های روابط عمومی صنعت استخراج و راهبرد قابل اجرا به روش ماتریس تصمیم استراتژیک SDM اولویت بندی گردید. در پایان رهنمودهایی برای اجرا و تدوین برنامه عملیاتی ارائه شد. قلمرو این تحقیق، روابط عمومی صنعت نفت است.
۷۵.

Application of Clustering and Classification Algorithms in Analyzing Customer Behavior in Data-Driven Marketing: A Case Study of Amazon Customers(مقاله علمی وزارت علوم)

حوزه‌های تخصصی:
تعداد بازدید : ۷۸ تعداد دانلود : ۷۴
In data-driven marketing, customer behavior analysis plays a crucial role in developing targeted marketing strategies aimed at increasing return on investment, enhancing profitability, and gaining a larger market share. In this study, four clustering methods- including K-means, density-based clustering, principal component analysis, and hierarchical clustering- as well as four classification methods- including Support Vector Machine, XGBoost, Random Forest, and Gradient Boosting- are examined for customer behavior analysis. The data for this study was extracted from the "Amazon Customer Behavior Survey" dataset, which includes 23 features from 602 customers. Initially, the data was preprocessed, and then, using clustering methods, customers were divided into different groups. The performance of these methods was evaluated based on criteria such as the silhouette index, and ultimately, appropriate marketing strategies for each cluster were proposed. Additionally, to examine the possibility of predicting customer membership in the extracted clusters, the aforementioned classification models were implemented and compared. The results indicate that the K-means method performed the best in clustering, while the XGBoost model performed the best in classification. The innovation of this research lies in combining clustering and classification methods to provide targeted marketing strategies and comprehensively comparing these methods on real customer data. This study demonstrates that combining clustering and classification methods can help businesses better understand customer behavior and make more optimal marketing decisions.
۷۶.

توسعه بانکداری بدون تصمیم گیر انسانی با اتکاء به عامل های خودمختار مالی

حوزه‌های تخصصی:
تعداد بازدید : ۴ تعداد دانلود : ۷
با گسترش سریع فناوری های هوش مصنوعی، یادگیری ماشین و سیستم های چندعاملی، نظام های بانکی در حال ورود به مرحله ای نوین از تحول دیجیتال هستند که در آن نقش تصمیم گیر انسانی به تدریج کاهش یافته و به سمت خودکارسازی کامل حرکت می کند. این مقاله به بررسی توسعه مفهوم بانکداری بدون تصمیم گیر انسانی با اتکاء به عامل های خودمختار مالی می پردازد. در این پژوهش، از رویکرد توصیفی تحلیلی و مطالعه کتابخانه ای استفاده شده و داده ها از منابع علمی معتبر، مقالات بین المللی و گزارش های حوزه فین تک گردآوری و تحلیل شده اند. همچنین، برای تبیین ساختار پیشنهادی، از رویکرد مدل سازی مفهومی سیستم های چندعاملی بهره گرفته شده است. در این چارچوب، عامل های هوشمند قادرند وظایف کلیدی بانکی شامل اعتبارسنجی مشتریان، تخصیص اعتبارات، مدیریت نقدینگی، تحلیل ریسک های مالی و کشف تقلب را به صورت بلادرنگ و بدون مداخله انسانی انجام دهند. معماری پیشنهادی مبتنی بر ترکیب یادگیری عمیق، پردازش کلان داده ها و تعامل میان عامل های خودمختار طراحی شده است که موجب افزایش سرعت، دقت و مقیاس پذیری تصمیم گیری می شود. با وجود مزایای قابل توجه مانند کاهش خطاهای انسانی و افزایش بهره وری، این رویکرد با چالش هایی همچون شفافیت الگوریتمی، مسئولیت حقوقی، ریسک های سیستمی و ملاحظات اخلاقی مواجه است. نتایج پژوهش نشان می دهد که تحقق کامل بانکداری بدون انسان در کوتاه مدت دشوار است، اما حرکت تدریجی به سمت بانکداری خودمختار می تواند ساختار صنعت مالی را به طور بنیادین متحول سازد.
۷۷.

طراحی سیستم هشدار زودهنگام ورشکستگی سازمان ها با تحلیل کلان داده

حوزه‌های تخصصی:
تعداد بازدید : ۵ تعداد دانلود : ۸
تحولات فناوری اطلاعات و ارتباطات در دهه اخیر موجب ظهور الگوهای نوین کسب وکار در صنعت در سال های اخیر، افزایش نوسانات اقتصادی، پیچیدگی ساختارهای مالی و رشد عدم قطعیت در محیط کسب وکار موجب شده است که شناسایی زودهنگام نشانه های ورشکستگی سازمان ها به یکی از موضوعات مهم در حوزه مالی و مدیریت ریسک تبدیل شود. هدف این پژوهش، طراحی یک سیستم هشدار زودهنگام ورشکستگی سازمان ها با استفاده از تحلیل کلان داده و بهره گیری هم زمان از داده های مالی و غیرمالی است. در این راستا، تلاش می شود با ترکیب اطلاعات مالی شرکت ها، داده های رفتاری، و داده های متنی گسترده، الگوهای پنهان مرتبط با احتمال ورشکستگی شناسایی شود.روش پژوهش مبتنی بر تحلیل کلان داده و استفاده از الگوریتم های یادگیری ماشین در قالب مدل های طبقه بندی است که توانایی تفکیک شرکت ها را در سه وضعیت سالم، در معرض بحران مالی و ورشکسته دارند. همچنین در این پژوهش از مراحل پیش پردازش داده، پاک سازی اطلاعات و انتخاب ویژگی های مؤثر استفاده می شود تا دقت و کارایی مدل افزایش یابد. به کارگیری این رویکرد امکان تحلیل هم زمان داده های ساختاریافته و غیرساختاریافته را فراهم می سازد.یافته های پژوهش های پیشین نشان می دهد که مدل های مبتنی بر یادگیری ماشین در مقایسه با روش های سنتی آماری از توانایی بیشتری در پیش بینی بحران های مالی برخوردارند. علاوه بر این، استفاده از کلان داده می تواند به شناسایی سریع تر نشانه های اولیه بحران کمک کند و دقت سیستم های پیش بینی را بهبود بخشد. در نهایت، این پژوهش نشان می دهد که ترکیب داده های مالی و کلان داده های رفتاری و متنی می تواند به طراحی یک سیستم هشدار زودهنگام دقیق تر، هوشمندتر و کارآمدتر در حوزه مدیریت ریسک مالی منجر شود.
۷۸.

رویکرد نوین برای کاهش تقلب در فرآیندهای بیمه ای با استفاده از پنهان نگاری مبتنی بر شبکه های مولد متخاصم (GAN) و رمزنگاری AES-GCM(مقاله علمی وزارت علوم)

نویسنده:
حوزه‌های تخصصی:
تعداد بازدید : ۴ تعداد دانلود : ۴
پیشینه و اهداف: یکی از چالش های بزرگ در صنعت بیمه، مقابله با تقلب در فرایند اعلام خسارت هاست که به ویژه در روش های دیجیتالی، از جمله ارسال عکس های خسارت از طریق اپلیکیشن ها، به چشم می خورد و به نظر می رسد صنعت بیمه بیش از هر زمان دیگری به بررسی روش های کشف تقلب نوین و نیز ایمن سازی اطلاعات نیاز دارد. همچنین امنیت و اصالت اطلاعات مکانی و زمانی تصاویر ارسالی از طریق اپلیکیشن نقش مهمی در کاهش تقلب دارد. در این پژوهش، روشی نوین ارائه شده است که با استفاده از تکنیک پنهان نگاری ، اطلاعات مکانی و زمانی عکس های ارسالی ازسوی بیمه گذاران رمزنگاری و مستقیماً در فایل تصویر جاسازی شده، سپس در مقصد رمزگشایی می شود. این رویکرد نه تنها امکان احراز اصالت اطلاعات ارائه شده را افزایش می دهد، بلکه امنیت داده ها را نیز تضمین می کند و خطر تقلب را کاهش می دهد. پیاده سازی این روش می تواند به بهبود اعتماد بین بیمه گر و بیمه گذار و کاهش هزینه های ناشی از تخلفات کمک کند. روش شناسی: در این پژوهش، از رویکرد استگانوگرافی مبتنی بر شبکه های مولد متخاصم (GAN) برای جاسازی اطلاعات مکانی و زمانی تصاویر خسارت استفاده شده است ابتدا اطلاعات مربوط به زمان و مکان عکس با استفاده از الگوریتم رمزنگاری AES-GCM رمزنگاری شده تا امنیت داده های حساس تضمین شود. برای ارزیابی سیستم، داده های پنهان شده از تصاویر استخراج و با داده های اصلی مقایسه شدند. سیستم روی یک مجموعه داده 100تایی از تصاویر خسارت بیمه ای خودرو آزمایش و سه روش مقایسه ای بررسی شد. روش پایه (LSB)، استگانوگرافی مبتنی بر شبکه های مولد متخاصم، و ترکیب شبکه های مولد متخاصم با رمزنگاری AES-GCM. معیارهای ارزیابی شامل کیفیت تصویر (PSNR)، ظرفیت پنهان سازی (SSIM)، میانگین خطای بیت تحت حملات استاندارد و نرخ تشخیص دستکاری در فراداده ها محاسبه شد. یافته ها : در این پژوهش مشخص شد تصاویر حاوی داده های پنهان میانگین PSNR برابر با 41 dB داشتند که نشان دهنده حفظ کیفیت بصری بالای تصاویر است. روش شبکه های مولد متخاصم، میانگین PSNR ≈ 40.6 ± 0.8 dB (در مقابل 36.7 ± 1.1 dB برای روش پایه) و SSIM بالاتری نشان داد؛ میانگین BER در برابر فشرده سازی و نویز برای شبکه های مولد متخاصم تقریباً نصف روش پایه بود (به ترتیب ≈19–12% در برابر ≈34–29%). افزودن AES-GCM تأثیری بر کیفیت تصویری نداشت، اما امنیت انتها –   به –  انتها را افزایش داد. آزمون t زوجی نشان داد این تفاوت از نظر آماری در سطح اطمینان ۹۵٪ معنادار است (p < 0.001). در آزمون های دستکاری فراداده در آزمایش حاضر، در مجموعه داده آزمایشی 100 تصویری، تمامی موارد دستکاری فراداده (meta data) با موفقیت شناسایی شد. زمان پردازش میانگین پیاده سازی موبایلی برای کل زنجیره رمزنگاری+جاسازی تقریباً 2 ثانیه در هر تصویر بود. نتیجه گیری: این پژوهش نشان داد که استفاده از استگانوگرافی مبتنی بر یادگیری عمیق می تواند چالش های امنیتی در فرایند اعلام خسارت آنلاین را برطرف کند. روش پیشنهادی ضمن تضمین کیفیت و امنیت تصاویر، امکان تأیید صحت اطلاعات مکانی و زمانی را فراهم می کند و می تواند به کاهش تقلب در بیمه کمک شایان توجهی کند. نتایج نشان می دهد که ترکیب استگانوگرافی مبتنی بر روش پیشنهادی با AES-GCM بهترین تعادل بین کیفیت تصویری، پایداری در برابر حملات و قابلیت تشخیص دستکاری فراداده را فراهم می آورد.
۷۹.

The Effect of Social Media Sentiment on Instagram Check-in Activity in the Hospitality Industry: A Case Study of 5-star Hotels in Mashhad(مقاله علمی وزارت علوم)

حوزه‌های تخصصی:
تعداد بازدید : ۴۱ تعداد دانلود : ۵۲
Social media has become a vital communication channel in various industries, including tourism and hospitality. This study aims to investigate the impact of social media—specifically user-generated content—on the occupancy rates of 5-star hotels in Mashhad, Iran. The research follows a three-stage methodology. First, customer reviews from Instagram fan pages of selected hotels were collected using the Graph API Explorer and analyzed through sentiment analysis to classify them into positive, negative, or neutral categories. Second, hotel occupancy was estimated using the number of weekly check-ins on Instagram as a proxy due to restricted access to official occupancy data. Finally, regression analysis was applied to examine the relationship between the percentage of positive reviews and the number of check-ins. The results reveal a strong positive correlation between favorable customer comments and hotel check-ins for most of the studied hotels, suggesting that social media plays a critical role in influencing consumer decision-making and hotel occupancy. The findings emphasize the strategic importance of leveraging social media platforms for effective marketing and customer engagement in the hospitality industry.
۸۰.

A digital transformation approach to authenticate original products for foreign markets(مقاله علمی وزارت علوم)

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تعداد بازدید : ۷۴ تعداد دانلود : ۷۱
In this study, in which a new business model was constructed to examine the reflections of digitalization on the field of authentication due to the increasing importance of digitalization day by day. This paper aims to design a business model for digital transformation using Near-Field Communication (NFC) technology to develop foreign markets for original products by creating a product authentication database. Given the global use of NFC technology for authenticity checks and market development, this research is pioneering in proposing a business model for applying this approach to authenticate original products in Iran. Beyond product authentication, this approach can facilitate extensive market research, particularly in international markets, where many handicraft and clothing products are highly successful but often overlooked by industry owners. Following a description of Osterwalder’s business model, a business model canvas is developed, and service and sales revenue models are presented. The service revenue model includes two business strategies: "service provision per tap" and "annual subscription strategies (Bronze, Silver, and Gold)".

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