درخت حوزه‌های تخصصی

مدیریت دانش و IT

حوزه‌های تخصصی
ادبیات اقتصاد تاریخ تربیت بدنی جغرافیا حقوق روانشناسی زبان شناسی علم اطلاعات و دانش‌شناسی علوم اجتماعی علوم اسلامی علوم انسانی علوم تربیتی علوم سیاسی فلسفه و منطق مدیریت مطالعات زنان هنر و معماری
اخبار مدیریت تئوری های مدیریت گروههای ویژه مدیریت آموزشی مدیریت استراتژیک مدیریت بازرگانی مدیریت دانش و IT مدیریت دولتی مدیریت سازمانی و منابع انسانی مدیریت صنعتی مدیریت مالی – حسابداری نقد و بررسی کتاب
پیش بینی، اجرا و ارزیابی تکنولوژی تکنولوژی و توسعه حقوق مالکیت سرمایه گذاریهای خارجی و انتقال تکنولوژی سیستم های پشتیبانی تصمیم گیری سیستمهای خبره کلیات مدلهای انتقال تکنولوژی مدیریت دانش مدیریت فناوری اطلاعات منطق فازی و هوش مصنوعی
ترتیب بر اساس: جدیدترینپربازدیدترین
فیلترهای جستجو: فیلتری انتخاب نشده است.
نمایش ۴۱ تا ۶۰ مورد از کل ۲٬۹۱۷ مورد.
۴۱.

Corporate Digital Transformation: A Comprehensive Definition and Conceptual Framework for Enhancing Business Performance(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۷, Special Issue on Strategic, Organizational, and Social Issues of Digital Transformation in Organizations, ۲۰۲۵ 81 - 102

کلیدواژه‌ها: Corporate Digital Transformation Digital Transformation Key Drivers Digital Transformation Defini-Tion Business performance Content Analysis

حوزه‌های تخصصی:
تعداد بازدید : ۱۱۸ تعداد دانلود : ۸۰
This study aims to analyze 45 definitions of digital transformation (DT) to identify key drivers and propose a conceptual framework to outline their impact on business performance. Through content analysis, 24 key drivers were identified, focusing on the frequency of occurrence across the definitions. The analysis highlights drivers such as IT technologies & innovation, business model, business performance, customer experience, and operational processes. The results show a significant emphasis placed on various drivers of DT, reflecting its multidimensional nature. Key drivers include technological innovation, organizational adaptation, customer-centric strategies, and change management practices. By conceptualizing the relationships between key drivers and performance outcomes, the proposed conceptual framework provides theoretical insights into the mechanisms underlying digital transformation and its impact on business performance. The proposed framework integrates technological, strategic, organizational, and cultural dimensions. The analysis underscores the complexity and multidimensional nature of DT as a strategic phenomenon and offers drivers on which the organizations should focus to face the challenges of digital disruption. This paper's original theoretical contribution lies in synthesizing various definitions of digital transformation from the past two decades to propose a comprehensive definition of Corporate Digital Transformation.
۴۲.

Readiness for Artificial Intelligence Adoption in Malaysian Manufacturing Companies(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۷, Issue ۱, ۲۰۲۵ 1 - 13

کلیدواژه‌ها: Technology Readiness TOE Artificial Readiness Artificial Intelligence

حوزه‌های تخصصی:
تعداد بازدید : ۲۷۲ تعداد دانلود : ۱۳۹
The advancement of artificial intelligence (AI) and its growing societal importance are reshaping decision-making processes and policy analysis roles. This study examines the readiness of manufacturing companies in Malaysia to embrace AI technology, considering its potential to enhance decision-making, productivity, quality control, job automation, and data analysis. Focusing on the Technology, Organization, and Environment (T-O-E) readiness framework, the research investigates the relationship between these dimensions and AI adoption readiness among manufacturing companies in Shah Alam, Selangor, Malaysia. AI adoption readiness serves as the dependent variable, while technological, organizational, and environmental readiness dimensions act as independent variables. The study applies the T-O-E framework to AI readiness and proposes a framework for assessing AI readiness at the manufacturing level. It identifies factors influencing readiness within the technological, organizational, and environmental dimensions, including relative advantage, compatibility, resources, competitive pressure, top management support, and government regulations. Through rigorous analysis, patterns, trends, and correlations are revealed, highlighting a significant link between the T-O-E readiness dimensions and AI adoption readiness. Notably, organizational readiness emerges as a key driver of AI adoption in Malaysian manufacturing companies. The results of this investigation have broad implications, offering suggestions to improve organizational preparedness and unlock AI’s potential benefits for businesses in the industrial sector. Additionally, the research lays the groundwork for further studies on AI readiness across various industries and international contexts. As AI becomes increasingly integrated into manufacturing processes, adaptive businesses gain competitive advantages on a global scale. These advantages include increased productivity, informed decision-making, streamlined quality control, improved customer satisfaction, and potential contributions to economic growth. The study concludes by recommending strategies to reinforce organizational readiness and emphasizes the need for future research to deepen understanding of AI adoption readiness in the manufacturing industry. The integration of AI technology offers benefits such as enhanced productivity, decision-making, quality control, and customer satisfaction, granting businesses a competitive edge in the digital landscape and increasing stakeholder interest.
۴۳.

Scroll, Click, Buy: The Impact of Social Media Attributes on Purchase Intentions among Young Adults(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۷, Issue ۱, ۲۰۲۵ 99 - 118

کلیدواژه‌ها: habit Informativeness purchase intention social media Young Adult

حوزه‌های تخصصی:
تعداد بازدید : ۱۷۰ تعداد دانلود : ۱۵۳
Online review sites and social media platforms have become crucial sources of information for consumers, greatly influencing their purchasing behavior and decision-making, especially in the food and beverage industry. However, not many studies have been carried out to understand how social media influences customers’ purchase intentions at fast-food restaurants. This paper examines the growing influence of social media attributes on purchase intentions, with a focus on the Malaysian context. Previous studies highlight the increasing importance of social media platforms as marketing tools and their impact on customers’ purchase intentions. The research explores the relationship between habit and informativeness and their influence on purchase intentions among young adults in fast-food restaurants. A purposive sampling method was utilized to gather data from 142 fast-food customers through a cross-sectional online survey. The research hypotheses were analyzed using the partial least square structural equation modeling. Key findings found that habit and informativeness have a significant positive impact on customers’ intentions to purchase at fast-food restaurants. The study contributes to the existing literature by highlighting the growing influence of social media on consumer behavior in the context of fast-food restaurants. It adds to our understanding of how social media platforms serve as effective marketing tools, particularly among young adults, and how they can influence purchase intentions. By understanding the interplay of habit, informativeness, and purchase intentions, businesses can develop more effective marketing strategies and foster stronger relationships with their customers.
۴۴.

A Hybrid Approach to Feature Extraction and Information Gain-Based Reduction for Image Classification(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۷, Special Issue on SI: Intelligent Security and Management, ۲۰۲۵ 1 - 15

کلیدواژه‌ها: Image classification Feature extraction feature reduction information gain UCI ge-netic algorithm

حوزه‌های تخصصی:
تعداد بازدید : ۶۱ تعداد دانلود : ۴۸
Image classification is a significant process in the field of computer science. It has applications in every field, such as spam detection in emails, medical diagnosis, image recognition, sentiment analysis, object detection, weather forecasting, pattern recognition, and security. Image classification deals with the grouping of images based on labels or characteristics. Feature extraction, feature selection, feature reduction, and classification are the main steps used to classify images. A medicinal and non-medicinal flowers data set is prepared by clicking images for the study. Methodology is used to achieve satisfactory classification results on the seeds, Wisconsin Diagnostic Breast Cancer, Heart Failure Clinical Records, and Wisconsin Prognostic Breast Cancer data sets, which are taken from the University of California, Irvine (UCI) repository. The proposed methodology suggests an efficient feature extraction and selection approach for data sets under consideration. An information gain-based genetic algorithm is used for feature reduction. It is performed on the extracted features to retrieve an optimized feature set. Fitness of the features is evaluated to choose the most relevant features. A neural network is used to classify the obtained feature subset. Better classification results are attained with the help of feature extraction and feature reduction.
۴۵.

The Intersection of Quantum Computing, Artificial Intelligence and Financial Risks: A Bibliometric Analysis of the Modern Financial Sector(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۷, Special Issue on Strategic, Organizational, and Social Issues of Digital Transformation in Organizations, ۲۰۲۵ 3 - 23

کلیدواژه‌ها: Quantum Computing Financial risk Artificial Intelligence bibliometric analysis

حوزه‌های تخصصی:
تعداد بازدید : ۱۳۲ تعداد دانلود : ۷۵
The finance sector is experiencing substantial technological disruption as Quantum Computing and Artificial Intelligence (AI) continue to advance at a rapid pace. This study employs bibliometric analysis, specifically VOS Viewer, to investigate the academic environment at the intersection of financial risk, AI, and quantum computation. From 2014 to 2023, a comprehensive bibliometric analysis was performed on a total of 145 journal articles that were published in Scopus and Web of Sciences (WoS). Articles are categorized based on their homogeneity in the disciplines of Quantum Computing, Financial Risk, and AI, as well as their interdisciplinary compositions. The results, which include authorship trends, keyword dynamics, and linked works, are analyzed and presented. This extensive bibliometric analysis offers critical insights into contemporary research and pinpointing areas necessitating further exploration. As quantum computers and AI algorithms become more sophisticated, this paper investigates the potential weaknesses and issues that financial institutions may encounter. By analyzing the intersection of two transformative technologies, the report offers critical insights into the discourse surrounding the safeguarding of financial systems in the quantum era. The analysis not only enhances the quality of the review but also directs researchers to significant papers and identifies regions of publications, thereby facilitating a more comprehensive understanding of the research environment.
۴۶.

Service Quality Performance of E-Hailing Services in Sarawak, Malaysia(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۷, Issue ۱, ۲۰۲۵ 14 - 32

کلیدواژه‌ها: public transportation E-hailing industry PLS-SEM Sarawak

حوزه‌های تخصصی:
تعداد بازدید : ۲۳۲ تعداد دانلود : ۱۴۵
With the advancement of communication technology, e-hailing services are becoming more widespread in Malaysia. Even though e-hailing services offer relative advantages compared to other types of public transport, research on the service quality aspects and customer satisfaction is essential to ensure customers receive worthwhile service with the money they spend on the services. Therefore, the growth of the e-hailing sector in Malaysia has drawn attention from the government, service providers, passengers, and even academics to the issues of service quality and customer satisfaction. Much research on service quality has been conducted in Malaysia; however, limited research has yet to be done on e-hailing services specifically for the state of Sarawak (East Malaysia) compared to peninsular areas. Thus, this research aims to measure the service quality performance of e-hailing in Sarawak and investigate the factors influencing passenger satisfaction. Three hundred ninety-two e-hailing users voluntarily participated in the survey, which was conducted in 2023. The partial least squares structural equation modeling (PLS-SEM) was performed to assess the measurement and structural model. The analysis revealed that vehicle condition, customer service, and reliability have a significant one-percent relationship with passenger satisfaction. To ensure e-hailing vehicles are always in good condition, e-hailing companies and government agencies must make it mandatory for e-hailing cars to be maintained periodically. Next, the driver should improve communication skills and show a good attitude to provide excellent customer service. Besides, prompt response to customer orders is a must to ensure e-hailing services are reliable public transportation.
۴۷.

Utilizing Deep Learning for Aspect-Based Sentiment Analysis in Restaurant Reviews(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۷, Issue ۲, ۲۰۲۵ 50 - 68

کلیدواژه‌ها: deep learning text mining Sentiment Analysis Neural Network

حوزه‌های تخصصی:
تعداد بازدید : ۱۰۲ تعداد دانلود : ۹۰
Consumers rely on social media opinions to make product choices and purchases. With the popularity of web-based platforms like Tripadvisor, consumers express their opinions and feelings about food quality, service, and other aspects affecting restaurants through comments. Hence, analyzing these comments can be valuable for others to choose a restaurant or to improve and develop their products and brands. Sentiment analysis utilizes text mining methods to extract, identify, and study emotions and subjective perceptions. Since consumers can use comments to choose a restaurant, this study seeks to provide sentiment analysis of their reviews on the Tripadvisor website about Iranian restaurants. This study is applied in nature, aiming to analyze and manually label 4000 comments from the Tripadvisor website regarding restaurants in ten tourist cities across Iran. It uses a standard extended long short-term memory algorithm for sentiment analysis, a deep learning neural network, and Python text mining packages for modeling. The results indicate that the F-Measure for all aspects exceeds 80%, indicating sufficient efficiency and accuracy of the aspect-based sentiment analysis model for restaurant reviews. The most significant features for customers of Iranian restaurants are the food and the atmosphere. This study represents one of the initial efforts to analyze comments posted on the Tripadvisor website concerning Iranian restaurants. Business owners in the tourism industry, especially restaurant owners, can use the proposed model to automatically and quickly analyze customer feedback, improve performance, and gain a competitive edge. The proposed model can also assist users of online platforms in analyzing the opinions of others, enabling them to make informed decisions more efficiently.
۴۸.

Consumers’ Impulse Buying Behavior on E-Commerce Shopping Platforms: 7C Framework and Emotions(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۷, Issue ۱, ۲۰۲۵ 119 - 130

کلیدواژه‌ها: Impulse Buying Behavior 7C Framework emotions SOR

حوزه‌های تخصصی:
تعداد بازدید : ۳۱۲ تعداد دانلود : ۱۲۸
The world of digital marketing has been fast advancing in recent times. Marketers have developed various practices to attract consumers to their products and services. Online shopping applications have introduced different methods to encourage consumer impulse buying. However, past literature has overlooked the 7C framework, despite its introduction during the early stages of e-commerce development. Thus, this study aims to examine the dimensions of digital marketing and the mediating role of emotions on impulse buying behavior in e-commerce shopping platforms. This study used the Stimulus-Organism-Response (SOR) framework as the underpinning theory for developing the proposed framework. The 7Cs framework, serving as the stimulus (S), includes content, context, commerce, customization, connection, communication, and community. Emotions represent the organism (O), while impulse buying behavior is the response (R). A survey was conducted to collect data from 331 shoppers from two major online platforms in Malaysia. Exploratory Factor Analysis was performed and revealed six dimensions of digital marketing. Furthermore, it was found that emotions partially mediate the relationship of (a) context, (b) connection, and (c) commerce on impulse buying behavior. Emotions fully mediate the relationship between (a) communication and (b) customization on impulse buying behavior. This study enhances the understanding of the 7C framework, which is underexplored in the context of e-commerce. The 7C framework can be used to assess not only website design but also the design of e-commerce shopping platforms.
۴۹.

تجزیه و تحلیل بازگشت دانش بازنشستگان در زنجیره تأمین پالایشگاه اصفهان با رویکرد تلفیقی مدل سازی ساختاری تفسیری و مدل سازی معادلات ساختاری(مقاله علمی وزارت علوم)

نویسنده:
منبع: مدیریت راهبردی دانش سازمانی سال ۸ بهار ۱۴۰۴ شماره ۲۸ 98 - 120

کلیدواژه‌ها: بازگشت دانش بازنشستگان دانش زنجیره تأمین مدیریت دانش

حوزه‌های تخصصی:
تعداد بازدید : ۸۰ تعداد دانلود : ۶۳
هدف: علی رغم اهمیت دانش بازنشستگان در رفع پیچیدگی ها و چالش های مختلف در زنجیره تأمین پالایشگاه از جمله ریسک های ناشی از نوسانات قیمت نفت و بازار، عدم همکاری و هماهنگی میان اعضای زنجیره تأمین، چالش های نفتی همچون نشت و آتش سوزی و ...، در سالیان اخیر حجم قابل توجهی از دانش با بازنشسته شدن کارکنان خارج شده است. هدف از انجام پژوهش حاضر تجزیه و تحلیل بازگشت دانش بازنشستگان در زنجیره تأمین پالایشگاه اصفهان است. روش پژوهش: پژوهش حاضر از لحاظ هدف، کاربردی و از نظر ماهیت و روش، توصیفی- علی و از نظر شیوه گردآوری داده ها، مطالعه غیرآزمایشی از نوع پیمایشی مقطعی است. در ابتدا 12 عامل مؤثر بر بازگشت دانش بازنشستگان بر اساس مرور پیشینه پژوهش شناسایی و به تأیید خبرگان دانشگاهی و صنعتی (پالایشگاه اصفهان) رسید. به منظور ارائه مدل مفهومی پژوهش از رویکرد مدل سازی ساختاری تفسیری استفاده شده است. در این بخش ابتدا پرسشنامه مقایسات زوجی میان عوامل اثرگذار بر بازگشت دانش بازنشستگان در زنجیره تأمین پالایشگاه اصفهان طراحی شد. سپس با استفاده از روش نمونه گیری قضاوتی و نظرخواهی از 15 نفر از خبرگان دانشگاهی و صنعتی، نحوه ارتباط میان عوامل مؤثر بر بازگشت دانش بازنشستگان شناسایی و مدل مفهومی ارائه شد. به منظور تأیید یا رد مدل مفهومی از رویکرد مدل سازی معادلات ساختاری و نرم افزار Smart PLS3 استفاده شده است. با استفاده از روش نمونه گیری در دسترس تعداد 300 پرسشنامه میان کارکنان و مدیران پالایشگاه اصفهان توزیع که از این میان تعداد 243 پرسشنامه بازگشت داده شد. روایی پرسشنامه پژوهش با استفاده از روایی همگرا (ضرایب بار عاملی و معیار AVE) و روایی واگرا (جدول فورنل- لارکر) تأیید شده است. همچنین پایایی پرسشنامه پژوهش با استفاده از معیارهای آلفای کرونباخ و پایایی ترکیبی مورد تأیید قرار گرفته است. یافته ها: نتایج این پژوهش نشان داد که حمایت دولت با ضریب مسیر 495/0 و دانش و تجربه بازنشستگان با ضریب مسیر 416/0 بر حمایت مدیریت ارشد و حمایت مدیریت ارشد با ضریب مسیر 789/0 بر مشوق های مالی و با ضریب مسیر 854/0 بر مشوق های غیرمالی تأثیرگذار است. علاوه بر این نتایج پژوهش نشان داد که مشوق های مالی با ضریب مسیر 383/0 و مشوق های غیرمالی با ضریب مسیر 522/0 بر فرهنگ حفظ و ارتقاء دانش سازمانی، فرهنگ حفظ و ارتقاء دانش سازمانی با ضریب مسیر 817/0 بر استفاده از فناوری های پیشرفته، استفاده از فناوری های پیشرفته بر مطلوبیت محیط کار با ضریب مسیر 787/0، مطلوبیت محیط کار با ضریب مسیر 805/0 بر مشارکت و همکاری کارکنان و مشارکت و همکاری کارکنان با ضریب مسیر 774/0 بر انسجام و ثبات سازمانی تأثیرگذار است. از دیگر نتایج این پژوهش می توان به تأثیر انسجام و ثبات سازمانی با ضریب مسیر 797/0 بر تسهیل ارتباطات و تأثیر تسهیل ارتباطات بر کیفیت محصولات و خدمات با ضریب مسیر 804/0 اشاره کرد. نتیجه گیری: نتایج پژوهش نشان داد که بازگشت دانش بازنشستگان نقش تعیین کننده ای در رفع چالش ها در زنجیره تأمین پالایشگاه اصفهان دارد. همچنین بر اساس مدل مفهومی ارائه شده از رویکرد مدل سازی ساختاری تفسیری، حمایت دولت و دانش و تجربه بازنشستگان به عنوان عوامل کلیدی در بازگشت دانش بازنشستگان در زنجیره تأمین پالایشگاه اصفهان شناسایی شده اند.
۵۰.

طراحی چارچوب مفهومی انتقال فناوری های پیشرفته در انقلاب صنعتی پنجم: رویکرد تحلیل مضمون(مقاله علمی وزارت علوم)

نویسنده:
منبع: مدیریت راهبردی دانش سازمانی سال ۸ بهار ۱۴۰۴ شماره ۲۸ 121 - 145

کلیدواژه‌ها: انتقال فناوری صنعت 5.0 فناوری های پیشرفته تحول دیجیتال

حوزه‌های تخصصی:
تعداد بازدید : ۸۴ تعداد دانلود : ۹۰
هدف: ظهور پارادایم صنعت 5.0 با تمرکز بر تعامل هوشمندانه انسان و ماشین، چالش های جدیدی را در فرآیند انتقال فناوری های پیشرفته ایجاد کرده است. هدف این پژوهش تبیین چارچوب مفهومی جامع برای انتقال فناوری های پیشرفته در پارادایم صنعت 5.0 است. روش پژوهش: این پژوهش با رویکرد پراگماتیسم و استراتژی استقرایی-قیاسی انجام شده است. از میان مقالات علمی منتشر شده بین سال های 2017 تا 2024 در پنج پایگاه داده معتبر، 84 مقاله با نمونه گیری هدفمند انتخاب شدند. داده ها با استفاده از رویکرد ترکیبی متن کاوی و تحلیل مضمون تحلیل شدند. در فاز کمی از الگوریتم های LDAو K-means برای خوشه بندی مفاهیم، و در فاز کیفی از روش تحلیل مضمون براون و کلارک استفاده شد. روایی یافته ها با استفاده از روش مثلث سازی و پایایی با محاسبه ضریب توافق کاپا (83/0) تأیید گردید. یافته ها: تحلیل متن کاوی به شناسایی پنج خوشه اصلی منجر شد که شامل فناوری های پیشرفته (54.4%)، انتقال فناوری (8.5%)، صنعت 5.0 (19.2%)، چالش ها و فرصت ها (11.4%) و سیاست گذاری و قوانین (6.6%) بودند. تحلیل مضمون منجر به شناسایی 40 مضمون اصلی و 163 مضمون فرعی شد که در قالب هشت مرحله اصلی انتقال فناوری دسته بندی شدند. این مراحل شامل شناسایی و گزینش، اکتساب، انطباق، جذب و تحلیل، کاربرد و بهره برداری، توسعه و بهبود، اشاعه، و یادگیری و نوآوری است. نتیجه گیری: موفقیت در انتقال فناوری های پیشرفته در صنعت 5.0 مستلزم ایجاد یک اکوسیستم پویا و تعاملی است که در آن عوامل فنی، سازمانی، انسانی و محیطی به طور همزمان مدیریت می شوند. اصالت/ارزش: این پژوهش برای نخستین بار با ترکیب رویکردهای متن کاوی و تحلیل مضمون، چارچوبی جامع برای انتقال فناوری در پارادایم صنعت 5.0 ارائه می دهد که فراتر از مدل های خطی موجود رفته و رویکردی اکوسیستمی ارائه می کند. این چارچوب می تواند مبنایی برای پژوهش های آتی در حوزه انتقال فناوری های پیشرفته و راهنمای عمل مدیران و سیاست گذاران باشد.
۵۱.

Employability and Digitalization: A Bibliometric Analysis with Future Research Directions(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۷, Special Issue on Strategic, Organizational, and Social Issues of Digital Transformation in Organizations, ۲۰۲۵ 125 - 151

کلیدواژه‌ها: employability digitalization Industry 4.0 SPAR-4-SLR

حوزه‌های تخصصی:
تعداد بازدید : ۱۲۱ تعداد دانلود : ۷۵
Digitalization is rapidly changing employment dynamics, demanding an understanding of how digital technologies impact employability. This study provides a comprehensive analysis of the relationship between digitalization and employability through a hybrid approach combining bibliometric analysis with a systematic theoretical review, based on the 4Ws framework (What, When, Where, and Why). Through the examination of thematic trends spanning the years 2010 to 2023, this study reveals significant domains in which digital transformation is influencing employability. The results underscore three primary thematic categories: the evolution of employment models catalyzed by digital technologies, the shift from Industry 4.0 to Industry 5.0, and theoretical advancements that concentrate on the informal economy alongside comparative analyses. This research contributes to addressing theoretical gaps regarding the lasting impact of digitalization on labor markets, with a particular focus on skill acquisition and job security. It presents targeted approaches for scholars, educators, and industry stakeholders to improve employability amid technological change. These include creating adaptive skill development programs, using AI in workforce management, and encouraging policies that enhance workers’ adaptability to new digital innovations. By presenting clear insights on how digitalization may affect employability, this research aims to enable more informed decisions for designing educational strategies and labor policies.
۵۲.

Enhancing Fake News Detection by Attention-Based BiLSTM and Hybrid Whale-Multi-Verse Optimization(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۷, Special Issue on SI: Intelligent Security and Management, ۲۰۲۵ 168 - 197

کلیدواژه‌ها: Bidirectional LSTM deep learning Fake news detection Hierarchical Hybrid Op-timization Information Extraction

حوزه‌های تخصصی:
تعداد بازدید : ۵۱ تعداد دانلود : ۴۴
The proliferation of fake news, characterized by the dissemination of inaccurate information to deceive audiences, has become a pressing concern in recent times. Traditional approaches to phony news detection, often focused on analyzing Twitter content, are susceptible to noise and variations in input sequences, leading to suboptimal performance. To address these challenges, this study proposes a novel method called Multi-Head Attention-Hierarchical Bidirectional Long Short-Term Memory (MHA-HBiLSTM) Networks. Our approach involves two phases: training and testing, wherein we employ tweet pre-processing techniques such as stemming, punctuation removal, stop-word elimination, URL handling, and Twitter control removal. Features are represented using the Glove word embedding technique for experimental evaluation and comparison. The MHA-HBiLSTM model integrates multi-head attention and hierarchical concepts, allowing meaningful information extraction from Twitter data. Notably, our model utilizes dual-level attention mechanisms and a hierarchical structure, reflecting the inherent hierarchy in documents and prioritizing key material during document representation. The effectiveness of the proposed MHA-HBiLSTM algorithm is evaluated using the Whale & Multi-Verse (W-MVO) Optimizer approach, with tests conducted on Kaggle and FakeNewsNet datasets. Comparative analysis with traditional machine learning approaches and deep learning models demonstrates the superior performance of the MHA-HBiLSTM approach in fake news detection.
۵۳.

The Impact of Smartphone Users’ Digital Literacy on Information Security Protection Intentions(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۷, Issue ۳, ۲۰۲۵ 148 - 172

کلیدواژه‌ها: digital Literacy Information security protection Second-order factor model Smartphone

حوزه‌های تخصصی:
تعداد بازدید : ۶۹ تعداد دانلود : ۵۶
In the digital economy era, the widespread use of smartphones has brought about new information security threats, increasing the risk of data leakage from personal devices. Digital literacy, defined as the skills and knowledge needed to navigate digital life effectively, offers new perspectives and motivation for safeguarding personal information security. This study investigates the relationship between digital literacy and smartphone users’ intention to protect their information security. Drawing on Protection Motivation Theory (PMT) and Technology Threat Avoidance Theory (TTAT), a theoretical model was developed to examine both the direct and indirect effects of digital literacy on users’ information security protection intentions. Questionnaire data from 372 smartphone users in China were analyzed using Structural Equation Modeling (SEM). The results reveal that digital literacy has a significant positive impact on users’ response efficacy, self-efficacy, and their intention to protect information security. Moreover, digital literacy influences protection intention indirectly through self-efficacy and response efficacy. However, perceived threat, although positively influenced by digital literacy, does not have a significant effect on users’ protection intention. This study offers valuable insights for policymakers, educators, and businesses in promoting a secure mobile environment and provides practical recommendations for enhancing personal information security in the digital age.
۵۴.

Adaptive Differential Privacy for Protecting User Confidential Information on Android Devices(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۷, Special Issue on SI: Intelligent Security and Management, ۲۰۲۵ 155 - 167

کلیدواژه‌ها: Android Security Data protection Confidential Information Data Leakage App Vul-nerabilities

حوزه‌های تخصصی:
تعداد بازدید : ۶۳ تعداد دانلود : ۵۲
The widespread adoption of Android phones has heightened concerns about user privacy. This research presents an Adaptive Privacy Management System (APMS) that integrates Machine Learning (ML) models with Differential Privacy techniques to enhance privacy protection. The APMS monitors application behavior and employs ML algorithms to detect anomalies and enable context-aware privacy enforcement. Differential Privacy ensures that sensitive data remains protected through the addition of noise and privacy-preserving computations. Experimental results demonstrate that the APMS achieves a 92.5% accuracy rate in detecting the privacy leakage. The anomaly detection model, using Random Forest, shows high accuracy (92.5%), recall (89.5%), and precision (73.9%), effectively identifying both normal and anomalous behaviors. Additionally, the impact of noise on data utility, controlled by the privacy budget (ε), is manageable. The results show that APMS is a robust system for safeguarding user confidential information, contributing to a more secure and privacy-centric Android ecosystem.
۵۵.

Incorporating Retroactive Operations in Large Temporal Databases Using Retroactive B-Tree(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۷, Special Issue on SI: Intelligent Security and Management, ۲۰۲۵ 87 - 107

کلیدواژه‌ها: Indexing Retroactive Query Answering Temporal Databases Retroactive B-Tree Persistent B-Tree Temporal Database Indexing Problem

حوزه‌های تخصصی:
تعداد بازدید : ۶۴ تعداد دانلود : ۳۸
Temporal databases, quickly rising in size, are distinguished by their capacity to maintain the older version of data objects against actions on them, allowing logical deletions. Queries for historical data are particularly costly due to the linear scanning of temporal versions. Temporal data structures like time-split B-Tree or multiversion B-Tree are working underlying the state-of-the-art temporal databases. So far, most efficient temporal data structures are partially persistent or fully persistent, but none of them support retroactive queries. On the other hand, efficient temporal indexing is required to address bulk loading in a real-life application. To the best of our knowledge, there is no efficient solution for bulk loading and updating retroactive index structures. This article seeks to offer a new data structure, the Retroactive B-Tree (RBT), to facilitate retroactive operations in temporal databases as well as bulk loading. It presents theoretical and empirical research and analysis of the suggested data structure and its relevant operations. The experiments were conducted to demonstrate the performance of the proposed retroactive B-Tree in terms of execution time, I/O complexity, space complexity, and bulk loading. The obtained results show that indexing with a buffer is the most powerful model for existing temporal databases for implementing a retroactive B-Tree. The tree of lists architecture is observed as an I/O efficient data structure for all variants of temporal indexing for large databases.
۵۶.

Predicting Heart Disease Using Automated Machine Learning Based on Genetic Algorithms(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۷, Issue ۲, ۲۰۲۵ 91 - 122

کلیدواژه‌ها: Heart Disease Prediction Automatic Machine Learning Genetic Algorithms TPOT Framework

حوزه‌های تخصصی:
تعداد بازدید : ۱۰۴ تعداد دانلود : ۶۹
This study aims to apply automatic machine-learning approaches using genetic algorithms to enhance heart disease prediction. Heart disease has remained the major cause of mortality in the world, necessitating an effective and timely diagnosis. Most current diagnostic and assessment processes are lengthy and expensive, relying heavily on clinical expert knowledge. To help address these issues, machine learning approaches, which derive their utility from examining substantial datasets for the recognition of patterns, have emerged as a potential solution, providing solutions beyond those achievable by human recognition alone. Genetic algorithms are also suited to addressing these issues as they mimic natural evolution to perfect high-caliber machine-learning models, feature selection, and parameter selection in machine-learning applications. This study examines the utilization of genetic algorithms working alongside AutoML frameworks to improve accuracy in heart disease predictions. Reducing to the best combination of attributes and the optimum parameters for each attribute is a time-consuming task, so automating this aspect of the process allows for more accurate and prompt predictions, consequently reducing the manual work. The AutoML approach followed in this research is TPOT, which uses genetic algorithms to ascertain optimally designed machine-learning pipelines. The application of AutoML, together with genetic algorithms, is the most prominent finding that yields a significant improvement in the quality of the predictions for heart disease compared to the traditional assessment approaches, with an accuracy of 93.8%. This approach will enhance diagnostic accuracy and enable early diagnosis, thereby reducing the likelihood of misdiagnoses or ineffective treatments and ultimately lowering associated costs.
۵۷.

Sustainability Challenges of Lithium-Ion Battery Supply Chain: Evidence from the Indian Electric Vehicle Sector(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۷, Issue ۱, ۲۰۲۵ 178 - 197

کلیدواژه‌ها: Electric vehicles Environmental impact Lithium-ion batteries recycling Sustainability

حوزه‌های تخصصی:
تعداد بازدید : ۲۷۵ تعداد دانلود : ۱۵۸
This study critically examines the sustainability challenges within the lithium-ion battery (LIB) supply chain in India's electric vehicle (EV) sector, an area of growing importance due to the rapid expansion of EV adoption. While LIBs are essential for EVs due to their high energy density and reliability, their production and disposal pose significant environmental, social, and economic sustainability challenges. These include resource depletion, environmental degradation, ethical concerns in raw material sourcing, and inefficient recycling processes. This study adopts a qualitative case study approach, focusing on three leading Indian automotive companies, to explore these challenges in depth. Data were collected through semi-structured interviews with key stakeholders involved in various stages of the LIB supply chain, including production, waste management, and recycling. Key findings reveal that the primary environmental challenge is the lack of advanced green technologies for recycling and disposal, leading to high water and energy consumption, as well as hazardous waste emissions. Social challenges include unsafe labor practices, particularly in raw material extraction, and a shortage of skilled labor in battery recycling operations. On the economic front, the reliance on imported raw materials, coupled with high production and recycling costs, undermines the sector’s sustainability and profitability. The research contributes to the literature by providing a comprehensive understanding of the environmental, social, and economic dimensions of sustainability in the LIB supply chain. It also offers practical insights for stakeholders and policymakers aiming to foster a greener and more sustainable EV sector in India.  
۵۸.

Studying the Requirements of the Digital Interactive and Transformational Model in the Virtual Space at the Islamic Republic of Iran Broadcasting Organization(مقاله علمی وزارت علوم)

نویسنده:
منبع: International Journal of Digital Content Management, Vol. ۵, No. ۹, Summer & Fall ۲۰۲۴ 35 - 62

کلیدواژه‌ها: Broadcasting Organization of the Islamic Republic of Iran Digital Transformation Interactive model National media virtual space

حوزه‌های تخصصی:
تعداد بازدید : ۳۳۰ تعداد دانلود : ۲۰۳
Purpose: The current research aims to develop a model for digital transformation within the virtual space of the Broadcasting Organization in accordance with increasing the functionality of the virtual space among the audiences. Due to the lack of a model in this field in order to benefit from it, this research aims to extract the components of the model using the thematic qualitative method or theme analysis.Method: The statistical population includes 15 experts in media management and virtual space. To measure reliability, intra-subject agreement method (reliability between two coders/evaluators) was used to determine the reliability of the texts, and the reliability coefficient obtained for all three interviews and the total reliability coefficient was (0.87), surpassing the minimum acceptable threshold of 0.7, confirming the reliability of the codings and the interviews.Findings: The findings indicate that the model requirements consist of 6 main categories, 9 sub-categories, and 38 sub-categories essential for creating digital transformation and enhancing the interaction of the Islamic Republic of Iran's radio and television with the virtual space. The main categories of the model encompass content production, comprising six main components: content production (with six indicators), opportunities and threats (with 11 indicators), strengths and weaknesses (with 13 indicators), digital transformation components (with five indicators), platforms of introduction (with seven indicators), and consequences of digital transformation (with four indicators), totaling 46 indicators.Conclusion: The results show that establishing a favorable interaction in the virtual space and new media by creating a digital transformation in the national media is effective in attracting the audience and improving the performance of the national media and ensuring the satisfaction of the stakeholders.
۵۹.

تاثیر استراتژیهای مدیریت دانش بر عملکرد زنجیره تامین پایدار با میانجی گری نوآوری سازگار با محیط زیست (مورد مطالعه: کارکنان شرکتهای کوچک و متوسط استان سمنان)(مقاله علمی وزارت علوم)

نویسنده:
منبع: مدیریت راهبردی دانش سازمانی سال ۷ زمستان ۱۴۰۳ شماره ۲۷ 91 - 115

کلیدواژه‌ها: استراتژیهای مدیریت دانش شرکتهای کوچک و متوسط عملکرد زنجیره تامین پایدار نوآوری سازگار با محیط زیست

حوزه‌های تخصصی:
تعداد بازدید : ۸۵ تعداد دانلود : ۸۲
زمینه/هدف: طی سالیان اخیر دررابطه با مدیریت دانش، زنجیره تأمین پایدار و نوآوری سازگار با محیط زیست مطالعات زیادی انجام شده است، اما در هیچ یک به بررسی روابط چندبعدی بین متغیرها و علی الخصوص موضوع نوآوری سازگار با محیط زیست، به عنوان مکانیسمی که رابطه استراتژی های مدیریت دانش و عملکرد زنجیره تأمین پایدار را میانجی می کند، پرداخته نشده است. هدف از پژوهش حاضر بررسی تأثیر استراتژی های مدیریت دانش بر عملکرد زنجیره تأمین پایدار با نقش میانجی گری نوآوری سازگار با محیط زیست است. روش پژوهش: بدین منظور از روش تحقیق توصیفی - پیمایشی استفاده شد و پرسش نامه محقق ساخته که از منابع موجود در پیشینه تحقیق تهیه شده و میزان روایی آن با استفاده از شاخص های روایی ظاهری، محتوایی، بار عاملی، روایی همگرا (AVE)، فورنل و لاکر، معیار ضریب تعیین، Q^2 و نیکویی برازش و پایایی آن از طریق آلفای کرونباخ و پایایی ترکیبی تایید گردیده بود، با روش نمونه گیری قضاوتی و هدفمند بین ۲۰۰ نفر از کارکنان شرکتهای کوچک و متوسط استان سمنان توزیع شد. یافته های پژوهش: بنا به نتایج حاصل از فرضیات فرعی پژوهش نیز مشخص شد استراتژی های مدیریت دانش بر عملکرد زنجیره تأمین پایدار (با ضریب اثر 0.178) و عملکرد نوآوری سازگار با محیط زیست (با ضریب اثر 0.301) و همچنین نوآوری سازگار با محیط زیست بر عملکرد زنجیره تأمین پایدار (با ضریب اثر 0.590) تأثیر مثبت و معناداری داشته است و بدین ترتیب تمامی فرضیات پژوهش تایید گردید. نتیجه گیری: نتایج حاصل از بررسی داده های پرسش نامه بر مبنای تحلیل های صورت گرفته با نرم افزارهای SPSS وSmart PLS ، مشخص نمود نقش نوآوری سازگار با محیط زیست به عنوان متغیر میانجی، بر روی تأثیر استراتژی های مدیریت دانش بر عملکرد زنجیره تأمین پایدار مثبت و معنادار (با ضریب اثر 0.498) بوده است.
۶۰.

Developing an Innovative Technology Model for Hotel Reception Desks in Iran(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۶, Issue ۳, ۲۰۲۴ 150 - 172

کلیدواژه‌ها: Innovation Technological innovation Hotel Service Reception Desk Hotel

حوزه‌های تخصصی:
تعداد بازدید : ۳۰۱ تعداد دانلود : ۲۱۰
In an era where customer expectations are rapidly evolving, enhancing the efficiency of hotel reception services in Iran is crucial for the growth of the hospitality sector. Recent research highlights the importance of digital transformation in improving service delivery and operational efficiency in the hospitality industry. These studies indicate that technological advancements can significantly streamline operational processes, improve customer satisfaction, and foster a competitive advantage in the hospitality industry. This research presents a technological innovation model aimed at modernizing reception desk services, addressing the pressing need for improvement in this area. Using an interpretive paradigm and an inductive approach, we conducted a qualitative study that incorporated a systematic review. Subsequently, the structures and components were extracted from the studies through qualitative coding. Our findings, derived from a review of 54 studies, revealed 295 open codes distilled into 15 constructs and four main components. This study highlights the significant impact of technological innovation on reception services, emphasizing the roles of ease of use and perceived usefulness in the technology adoption process. These insights provide essential guidelines for advancing reception desk technologies within the Iranian hotel industry, ultimately contributing to enhanced service quality.

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