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 ۸۱ تا ۱۰۰ مورد از کل ۲٬۹۱۰ مورد.
۸۱.

Designing an Adoption Model for Electronic Human Resource Management in Service-Oriented Organizations: A Case Study of Tehran Municipality(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۶, Issue ۲, ۲۰۲۴ 91 - 111

کلیدواژه‌ها: adoption technology adoption model EHRM

حوزه‌های تخصصی:
تعداد بازدید : ۱۸۰ تعداد دانلود : ۱۵۸
This study aims to develop an adoption model tailored for service-oriented organizations and then evaluate its effectiveness within the specific context of Tehran Municipality, Iran's foremost service-oriented institution. Utilizing a mixed-method research approach integrating qualitative and quantitative methodologies, this study delineated the dimensions, categories, and indicators pertinent to the adoption of Electronic Human Resource Management (EHRM) systems in service-oriented organizations. Qualitative methodologies were employed to identify and develop the adoption model, which was subsequently evaluated within Tehran Municipality using a quantitative approach. In the qualitative segment of this study, in-depth interviews were conducted using a snowball sampling technique until theoretical saturation was achieved. For the quantitative phase, a sample of 310 experts affiliated with Tehran Municipality's EHRM system was surveyed. Structural equation modeling and Smart PLS 4.0 software were employed for data analysis. Ultimately, this research extracted five dimensions, 14 categories, and 94 indicators for the proposed adoption model. Notably, experts accorded the highest priority to the technological dimension in the adoption model, with specific emphasis on “adaptive architecture, security and privacy of employees, trialability and reliability, organizational citizenship behavior, organizational dynamic capabilities, digital Leadership Policy and Actions, cloud computing, etc…”, as pivotal factors in EHRM adoption. The organizational dimension assumed the second-highest priority, while the individual dimension was assigned a third-place ranking. Micro and macro-environmental factors followed in subsequent priority order.
۸۲.

Analyzing the Relationship Between Dimensions of Mental Image, Brand Awareness, and Brand Recognition in Customer Attraction Considering Electronic Service Marketing(مقاله علمی وزارت علوم)

نویسنده:
منبع: International Journal of Digital Content Management, Vol. ۵, No. ۸, Winter & Spring ۲۰۲۴ 22 - 46

کلیدواژه‌ها: brand awareness brand recognition Customer Attraction Electronic Service Marketing mental image

حوزه‌های تخصصی:
تعداد بازدید : ۱۴۴ تعداد دانلود : ۱۳۴
Purpose: In the present research   the relationship between the dimensions of mental image, brand awareness and brand recognition in attracting customers, has been investigated and analyzed with   marketing of electronic services (the case study of Iran Postbank) especially taken into account. E-marketing has greatly facilitated the banking operation.Method: This research is applied in terms of purpose and descriptive-survey and correlational as regards the nature of data collection. The statistical population of the research includes managers and senior supervisors of Iran Postbank. The sample size of the research is 168 people, and simple sampling method was used, and 117 people were selected for the research. A questionnaire was used to collect data. The validity of the questionnaire was confirmed through content validity and its reliability using Cronbach's alpha coefficient. To analyze the data, structural equation modeling was used with the help of PLS ​​software.Findings: The results of this research showed that the variables of mental image, brand awareness and brand recognition have a significant and positive impact on the marketing of electronic services, also the marketing of services has a positive and significant impact on customer attraction and the marketing of electronic banking services will increase customer attraction.Conclusion: Given the increasing competition among Iranian banks and the challenge of attracting new customers and keeping current customers, as discussed in this research, brand awareness is one of the most important factors affecting customer attraction in the bank.
۸۳.

The Influence of Social Media Marketing Activities on Purchase Intention: A Study of the E-Commerce Industry(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۶, Issue ۱, ۲۰۲۴ 201 - 216

کلیدواژه‌ها: Social media marketing purchase intention brand awareness

حوزه‌های تخصصی:
تعداد بازدید : ۳۱۶ تعداد دانلود : ۲۲۲
This paper sought to examine the impact of perceived Social Media Marketing Activities (SMMAs) on customer purchase intention via brand awareness in an online context. An online questionnaire was used to collect data from 188 samples. The data were analyzed using the structural equation modeling approach, and the research hypotheses were examined using SEM. The study measured SMMAs through personalization, customer community, and live video. The results revealed that SMMAs were insignificant towards brand awareness and purchase intention. The result also stated that brand awareness does not mediate the relationship between SMMA and purchase intention. However, brand awareness was found to affect purchase intention positively. The current study introduces the stimulus–organism–response model as a theoretical support to examine SMMAs of e-commerce to customers' purchase intention via brand awareness.
۸۴.

An Accurate Prediction Framework for Cardiovascular Disease Using Convolutional Neural Networks(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۶, Issue ۱, ۲۰۲۴ 27 - 43

کلیدواژه‌ها: Deep-Learning CNN Heart-Disease Prediction Cardiovascular disease Accuracy

حوزه‌های تخصصی:
تعداد بازدید : ۳۳۶ تعداد دانلود : ۱۷۶
Cardiovascular-Diseases (CVD) are a principal cause of death worldwide. According to the World-Health-Organization (WHO), cardiovascular illnesses kill 20 million people annually. Predictions of heart-disease can save lives or take them, depending on how precise they are. The virus has rendered conventional methods of disease anticipation ineffective. Therefore, a unified system for accurate illness prediction is required. The study of disease diagnosis and identification has reached new heights thanks to artificial intelligence. With the right kind of training and testing, deep learning has quickly become one of the most cutting-edge, reliable, and sustaining technologies in the field of medicine. Using the University of California Irvine (UCI) machine-learning (ML) heart disease dataset, we propose a Convolutional-Neural-Network (CNN) for early disease prediction. There are 14 primary characteristics of the dataset that are being analyzed here. Accuracy and confusion matrix are utilized to verify several encouraging outcomes. Irrelevant features in the dataset are eliminated utilizing Isolation Forest, and the data is also standardized to enhance accuracy. Accuracy of 98% was achieved by employing a deep learning technique.
۸۵.

Breast Cancer Classification through Meta-Learning Ensemble Model based on Deep Neural Networks(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۶, Issue ۱, ۲۰۲۴ 61 - 87

کلیدواژه‌ها: Deep-Learning Meta-Learning EL CNN Breast-Cancer Classification

حوزه‌های تخصصی:
تعداد بازدید : ۳۰۱ تعداد دانلود : ۱۹۱
Predicting the development of cancer has always been a serious challenge for scientists and medical professionals. The prompt identification and prognosis of a disease is greatly aided by early-stage detection. Researchers have proposed a number of different strategies for early cancer detection. The purpose of this research is to use meta-learning techniques and several different kinds of convolutional-neural-networks(CNN) to create a model that can accurately and quickly categorize breast cancer(BC). There are many different kinds of breast lesions represented in the Breast Ultrasound Images (BUSI) dataset. It is essential for the early diagnosis and treatment of BC to determine if these tumors are benign or malignant. Several cutting-edge methods were included in this study to create the proposed model. These methods included meta-learning ensemble methodology, transfer-learning, and data-augmentation. With the help of meta-learning, the model will be able to swiftly learn from novel data sets. The feature extraction capability of the model can be improved with the help of pre-trained models through a process called transfer learning. In order to have a larger and more varied dataset, we will use data augmentation techniques to produce new training images. The classification accuracy of the model can be enhanced by using meta-ensemble learning techniques to aggregate the results of several CNNs. Ensemble-learning(EL) will be utilized to aggregate the results of various CNN, and a meta-learning strategy will be applied to optimize the learning process. The evaluation results further demonstrate the model's efficacy and precision. Finally, the suggested model's accuracy, precision, recall, and F1-score will be contrasted to those of conventional methods and other current systems.
۸۶.

Validation of the Pattern of Digital Marketing Capabilities Affecting Product Development(مقاله علمی وزارت علوم)

نویسنده:
منبع: International Journal of Digital Content Management, Vol. ۵, No. ۸, Winter & Spring ۲۰۲۴ 183 - 205

کلیدواژه‌ها: Abadan Petrochemical Company Accreditation Digital Marketing product development

حوزه‌های تخصصی:
تعداد بازدید : ۲۰۶ تعداد دانلود : ۱۲۷
Purpose: Due to the importance of creating competitive advantages, the present study was conducted with a view to validating the pattern of digital marketing capabilities affecting the development of new Abadan petrochemical products. The present research is applied in terms of purpose and has been done with a survey method.Method: The type of research is quantitative. The data collection tool was a questionnaire with 50 questions. Confirmatory factor analysis was used for the validation of the questionnaire as well as Cronbach's alpha coefficient.Findings: Findings showed that the value of confirmatory factor analysis (t-value) for all 5 paths of the model is greater than 1.96 and the significance of the test is less than 0.05, so with a 95% confidence level causal factors affect the main category (marketing capabilities for new product development) by 0.705; The main category (marketing capabilities for new product development) has an impact on strategies of 0.379; Intervening factors affect strategies by 0.129; Underlying factors affect strategies by 0.457; Finally, strategies have an impact on outcomes of 0.849Conclusion: The results show that the innovation, customer orientation, marketing technologies improvement, research and development capabilities and communication capabilities are confirmed. Also they emphasized as causal dimensions and the basis of digital marketing. Finally, the board diversity is confirmed as the underlying dimensions and platform of digital marketing.
۸۷.

Comparative Study on Different Machine Learning Algorithms for Neonatal Diabetes Detection(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۶, Issue ۱, ۲۰۲۴ 5 - 26

کلیدواژه‌ها: Voting Classifiers Meta-Classification Technique Diabetes Risk Prediction Biomedical Clinical Risk Factors Random Forest Logistic regression Gradient Boosting Support Vector Machines

حوزه‌های تخصصی:
تعداد بازدید : ۲۳۵ تعداد دانلود : ۱۶۶
This paper gives a performance analysis of multiple vote classifiers based on meta-classification methods for estimating the risk of diabetes. The study's dataset includes a number of biological and clinical risk variables that can result in the development of diabetes. In the analysis, classifiers like Random Forest, Logistic Regression, Gradient Boosting, Support Vector Machines, and Artificial Neural Networks were used. In the study, each classifier was trained and evaluated separately, and the outcomes were compared to those attained using meta-classification methods. Some of the meta-classifiers used in the analysis included Majority Voting, Weighted Majority Voting, and Stacking. The effectiveness of each classifier was evaluated using a number of measures, including accuracy, precision, recall, F1-score, and Area under the Curve (AUC). The results show that meta-classification techniques often outperform solo classifiers in terms of prediction precision. Random Forest and Gradient Boosting, two different classifiers, had the highest accuracy, while Logistic Regression performed the worst. The best performing meta-classifier was stacking, which achieved an accuracy of 84.25%. Weighted Majority Voting came in second (83.86%) and Majority Voting came in third (82.95%).
۸۸.

Coping Competencies of Iranian Students in E-Learning: A Mixed-Methods Evaluation(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۶, Issue ۴, ۲۰۲۴ 122 - 141

کلیدواژه‌ها: Academic Staff Coping Competencies E-Learning university students

حوزه‌های تخصصی:
تعداد بازدید : ۱۲۳ تعداد دانلود : ۷۴
The study evaluated the opportunities and challenges of e-learning for university students and investigated their experiences. A sequential exploratory mixed-methods approach (quantitative and qualitative) was used. In the quantitative phase, a survey was conducted to explore students' competencies in coping with e-learning attributes, involving 237 university students (46.9% male, 53.1% female). Descriptive and analytical tests were used to analyze the data. The results indicated the mean scores of students' perspectives on the opportunities and challenges of e-learning in university were 4.05 ± 0.49 out of 5. In the qualitative phase, data were collected through semi-structured interviews. To provide a richer context and better understanding and interpretation of the quantitative findings, the current research employed qualitative research methodologies, including focus group discussions with ten interviewees—five academic staff members and five students. Combining both student and academic staff perspectives provides a more comprehensive understanding of the research topic. Students and staff may have different viewpoints, experiences, and needs related to the subject matter. The qualitative analysis identified five significant themes: communication defects, technical challenges, personal-level challenges, curricular-level issues, and social challenges. The study's findings may be utilized to design better policies and strategies to enhance e-learning and address its issues among both instructors and students. Finally, the study provides implications for relevant stakeholders
۸۹.

Efficient NetB3 for Enhanced Lung Cancer Detection: Histopathological Image Study with Augmentation(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۶, Issue ۱, ۲۰۲۴ 98 - 117

کلیدواژه‌ها: Lung cancer Convolutional Neural Network (CNN) Histopathological Images Transfer Learning Lung Cancer Detection

حوزه‌های تخصصی:
تعداد بازدید : ۲۵۴ تعداد دانلود : ۱۹۲
Cancer is an abnormal cell growth that occurs uncontrollably within the human body and has the potential to spread to other organs. One of the primary causes of mortality and morbidity for people is cancer, particularly lung cancer. Lung cancer is one of the non-communicable diseases (NCDs), causing 71% of all deaths globally, and is the second most common cancer diagnosed worldwide. The effectiveness of treatment and the survival rate of cancer patients can be significantly increased by early and exact cancer detection. An important factor in specifying the type of cancer is the histopathological diagnosis. In this study, we present a Simple Convolutional Neural Network (CNN) and EfficientNetB3 architecture that is both straightforward and efficient for accurately classifying lung cancer from medical images. EfficientnetB3 emerged as the best-performing classifier, acquiring a trustworthy level of precision, recall, and F1 score, with a remarkable accuracy of 100%, and superior performance demonstrates EfficientnetB3’s better capacity for an accurate lung cancer detection system. Nonetheless, the accuracy ratings of 85% obtained by Simple CNN also demonstrated useful categorization. CNN models had significantly lower accuracy scores than the EfficientnetB3 model, but these determinations indicate how acceptable the classifiers are for lung cancer detection. The novelty of our research is that less work is done on histopathological images. However, the accuracy of the previous work is not very high. In this research, our model outperformed the previous result. The results are advantageous for developing systems that effectively detect lung cancer and provide crucial information about the classifier’s efficiency.
۹۰.

Exploring the Nexus of Big Data Capabilities, Business Model Innovation, and Firm Performance in Uncertain Environments: A Systematic Review(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۶, Issue ۳, ۲۰۲۴ 132 - 149

کلیدواژه‌ها: Big Data Capabilities Business Model Innovation Firm Performance Environmental uncertainty Micro small and Medium Enterprises (MSMEs)

حوزه‌های تخصصی:
تعداد بازدید : ۲۲۱ تعداد دانلود : ۱۷۰
This paper provides a systematic review of the literature on big data capabilities, business model innovation, firm performance, and environmental uncertainty. It aims to establish a foundation for theoretical modeling, research proposition refinement, and the overall research framework by meticulously examining the theoretical backgrounds of existing studies and identifying research gaps. An initial search yielded 1,360 articles, which were filtered to remove duplicates and irrelevant studies, resulting in 475 articles for final analysis. These articles were classified into three main categories: the relationship between big data capabilities and business model innovation, the impact of business model innovation on firm performance, and the integrated relationship involving environmental uncertainty. Additionally, it examines the mediating role of business model innovation on firm performance as well as the moderating effect of environmental uncertainty on these relationships. Finally, the paper formulates research hypotheses and discusses identified research gaps, establishing a solid groundwork for methodological discussions in future research and contributing to the advancement of knowledge in the field.
۹۱.

Unveiling Critical Drivers for Effective Digital Transformation Leadership and its Influence on Corporate Economic Performance: A Conceptual Model and Empirical Analysis in the Landscape of Emerging Economies(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۶, Issue ۲, ۲۰۲۴ 132 - 160

کلیدواژه‌ها: Digital Transformation Success factors Economic performance conceptual framework Structural Equation Modeling Sequential explanatory design

حوزه‌های تخصصی:
تعداد بازدید : ۱۷۵ تعداد دانلود : ۱۴۶
This paper aims to conceptualize the success factors of a digital transformation (DT) strategy and analyze its impact on a company's economic performance. We explore the concepts that affect the field of DT definition and the key drivers that lead to successful DT. Through these key drivers considered as success factors, we propose a research framework linking these drivers to the DT strategy and then corporate economic performance in emerging markets. To test the research model empirically and provide a contextualized interpretation of the results, we adopted a sequential explanatory design. Initially, we performed a quantitative study through a survey among companies listed on the Casablanca Stock Exchange in Morocco. We then analyzed the collected data using the structural equation method. Next, to explain the results, we conducted a qualitative analysis through interviews with semi-structured questions. The findings show that in an emerging economy context such as Morocco, placing the customer at the core of the DT strategy, aligning the organization with the DT strategy, adopting a value system imbued with DT values, and establishing an operational roadmap to drive the change can enhance the company’s digital transformation. These drivers contribute to 59.5% of the implementation of the DT strategy. Driving a DT strategy has a significant impact on companies' economic performance, contributing to 21.5% of their commercial and financial outcomes. This study highlights that the maintenance of a "phygital" business model, which mixes digital and physical business models, and the lack of human resources involvement in the DT process are specific to the emerging market context studied.
۹۲.

Identification of Stakeholders in Personal Health Records Using Blockchain Technology: A Comprehensive Review(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۶, Issue ۲, ۲۰۲۴ 181 - 205

کلیدواژه‌ها: Personal Health Record stakeholder theory Blockchain technology

حوزه‌های تخصصی:
تعداد بازدید : ۲۷۰ تعداد دانلود : ۱۵۵
Leveraging supplementary technology such as Blockchain has the potential to alter the stakeholders involved in a system. Paying attention to stakeholders is one of the main pillars of developing a system. Evidence has shown that Blockchain can solve existing challenges and add new capabilities. These actions will change the stakeholders of PHR. If a value is different for everyone, at the first stage, stakeholders should be identified, and that is our goal in this study. The research adhered to the guidelines outlined in the PRISMA statement. To this end, the study utilized databases including MEDLINE, ScienceDirect, and Google Scholar for English language articles, while the "iranjournals.nlai.ir" database was accessed for Persian language articles. Finally, 35 articles were chosen from searching databases, and six extra articles were selected from reviewing the final articles' references. Stakeholders were categorized into 15 groups. The patient (individual) was identified as the most frequent stakeholder (41 times), and infrastructure providers and the token exchange market were mentioned once each. The usage type is categorized into four groups: direct user interaction, data user, impact user, and financial beneficiaries, comprising six, eight, four, and four stakeholders, respectively. Patients (individuals) use the four groups, and health care providers, policymakers, hospitals, and the government each use two groups. Intelligent contracts are neglected in PHR, which can significantly impact the motivation and creation of incentives for using different stakeholders. The grouping presented here can be used in the preparation of the business model of PHR based on Blockchain. Data has the most usage for stakeholders and strengthens and supports investments in technologies such as Blockchain as an infrastructure for creating data markets, new business models, and creating value.
۹۳.

The Role of Socio-economic Status in Information Seeking Behavior Based on the Knowledge Gap Theory: A Case Study of Qom University, Iran(مقاله علمی وزارت علوم)

نویسنده:
منبع: International Journal of Digital Content Management, Vol. ۵, No. ۸, Winter & Spring ۲۰۲۴ 272 - 303

کلیدواژه‌ها: Information seeking behavior Knowledge Gap Theory Qom University Socio-economic status

حوزه‌های تخصصی:
تعداد بازدید : ۲۱۳ تعداد دانلود : ۱۳۴
Purpose: Economic and social status play a prominent role in many human activities and their  function is accentuated in the theory of the knowledge gap. According to the idea, the knowledge of the people with higher socio-economic status increases compared to those with lower socio-economic status. The purpose of this study was to determine the role of socio-economic status (based on knowledge gap theory) in the information-seeking behavior of fellow members of staff at  Qom University.Method: The study was an applied research in terms of purpose and in terms of strategy and data collection was correlational. The population consisted of 761 university employees. Based on Cochran’s formula the sample of the study included 255 employees. A researcher-made questionnaire was used to collect data. Spearman and X2 statistical tests were applied to analyze data.Findings: People who have a higher socio-economic status (with higher employment, income and education levels) are more motivated to search and obtain information, and there is a significant relationship between the components of individuals' socio-economic status and the type of the used information resources. Socio-economic status affects the criteria for evaluating information resources, and people with higher rate use various evaluation criteria while assessing the information. People with socio-economic status use various and different channels to obtain information, thus, there is a positive and significant relationship between the use of search engines and meta-search engines, internal and external databases, conference papers, library RSS, specialized social networks, consultation with librarians and technical blogs, and their socio-economic status.Conclusion: The social and economic status explains and predicts the information-seeking behavior of the staff and the results confirmed the theory of knowledge gap. Prediction of the facilities required for searching and seeking information in organizations and making them accessible to all human resources can help provide fair access to information for the better part of society and reduce the knowledge gap.
۹۴.

Presentation and Validation of Brand-Customer Communication Model in Social Media Platform: A Case Study: Cosmetics Industry(مقاله علمی وزارت علوم)

نویسنده:
منبع: International Journal of Digital Content Management, Vol. ۵, No. ۹, Summer & Fall ۲۰۲۴ 110 - 138

کلیدواژه‌ها: Brand-Customer Interaction Cosmetics Industry Social media marketing

حوزه‌های تخصصی:
تعداد بازدید : ۱۵۸ تعداد دانلود : ۱۰۸
Purpose: The purpose of this research was to provide a model for Validating and Presenting Brand-Customer Interaction Model in Digital Platform in the Cosmetics Industry.Method: This research was applied in its purpose and utilized a mixed approach (qualitative and quantitative). In this regard, this study was conducted with the aim of presenting and validating the brand-customer interaction model in Instagram Platform. The present study is a descriptive survey in terms of its practical-developmental purpose and data collection method. The statistical population in the qualitative section includes marketing professors and cosmetics industry managers, 20 of whom were selected by purposive sampling. The statistical population in the quantitative section also includes customers of cosmetics and health products, 384 participants were selected using the convenience sampling. The data collection tools were a semi-structured interview and a researcher-made questionnaire. First, thematic analysis method was used to analyze the expert interviews. Next, the identified pattern was validated using partial least squares method. Thematic analysis and partial least squares were done with MaxQDA software and Smart PLS software, respectively.Findings: The criterion to achieve data saturation has been to achieve repetition in extracting codes. 235 codes were identified in the open coding stage. Finally, three overarching themes, eight organizing themes, and 49 basic themes were obtained through axial coding. Based on the structural equation model, the proposed model was fitted and confirmed.Conclusion: Based on the results, effective marketing and digital content marketing are the basic elements of the model, which increase brand recognition and brand identity among customers by increasing interaction with customers. Brand recognition and identity contribute to positive word-of-mouth marketing, which in turn affects brand positioning on Instagram. Finally, in this way, it is possible to create a constructive and interactive brand-customer relationship.
۹۵.

Mobile Learning Adoption: Using Composite Model Measurement Invariance to Assess Gender Differences(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۶, Issue ۲, ۲۰۲۴ 35 - 61

کلیدواژه‌ها: mobile learning perceived ease of use perceived usefulness subjective norm Behavioral Intention

حوزه‌های تخصصی:
تعداد بازدید : ۳۰۱ تعداد دانلود : ۱۶۲
This study investigates Ghanaian students' adoption of Mobile Learning (ML) by extending the technology acceptance model with a subjective norm variable. Specifically, this study focuses on the moderating effect of gender using the Measurement Invariance of Composite Models for the analysis. The study used a purposive sampling technique to collect the data for the study from sec-ond-year diploma students at the University of Professional Studies in Accra. SmartPLS 3.3.3 was used to analyze the data from 330 respondents. The findings of the study suggest that perceived ease of use, perceived usefulness, and subjective norm have a significant influence on the behavior-al intention to adopt mobile learning for the complete data set. In addition, the results suggest that the impact of the subjective norm was not significant for female students but for male students. Also, the impact of perceived ease of use and perceived usefulness on behavioral intention were insignificant. Furthermore, the findings suggest that behavioral intention influences students' actual use of mobile devices to access learning materials. Finally, gender moderates the relationship be-tween subjective norms and behavioral intention. The findings demonstrate group heterogeneity, therefore, investigations on technology adoption must always incorporate group dynamics to un-derstand how different groups respond to its adoption. The findings of the study hold significance for both policy and research implications.
۹۶.

Identification and Evaluation Factors for Improving Online Shopping Based on Customer Experience in E-Start-ups in the Field of Health and Medical Care(مقاله علمی وزارت علوم)

نویسنده:
منبع: International Journal of Digital Content Management, Vol. ۵, No. ۸, Winter & Spring ۲۰۲۴ 229 - 246

کلیدواژه‌ها: customer experience Health Online shopping Startup

حوزه‌های تخصصی:
تعداد بازدید : ۱۷۷ تعداد دانلود : ۱۴۴
Purpose: Start-up businesses have attracted considerable attention regarding the new approach in the modern economy The present study was conducted to investigate the factors affecting the improvement of customers’ online shopping experience in e-commerce start-ups in the healthcare sector.Method: This is an applied research conducted as a descriptive-survey. The target population includes all customers who used the electronic start-up services in the healthcare sector; out of which a sample of 384 individuals was selected using the Morgan table. A self-administered questionnaire was developed to collect the data which were analyzed using partial least squares and Smart-PLS software.Findings: All research hypotheses were confirmed, and it was proved that factors such as customer respect, customer enjoyment, importance of time, information security, convenience, perceived experience, valuable experience, and perceived image experience have a positive effect on improving customers’ online shopping experience in e-commerce start-ups.Conclusion: Applying the proposed model helps e-start-ups increase their performance   by eliminating their shortcomings and boosting their strengths.
۹۷.

The Moroccan Health Data Bank: A Proposal for a National Electronic Health System Based on Big Data(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۶, Issue ۱, ۲۰۲۴ 79 - 97

کلیدواژه‌ها: National Electronic Health System Big Data Health Information System survey Moroccan Health Data Bank MHDB

حوزه‌های تخصصی:
تعداد بازدید : ۳۰۱ تعداد دانلود : ۱۸۷
This work serves to propose a national electronic health system based on the Big Data approach. First of all, we assessed the practice of health information systems (HIS) in Morocco and their obstacles. We performed a survey that was founded on 24 questions to specify the necessary details on this topic. This study shows that there is a primary need for the establishment of an HIS that facilitates the control, analysis, and management of health data in Morocco. For this reason, we have proposed the implementation of the Moroccan Health Data Bank (MHDB). This system will be based on powerful big data technologies that save, manage, and process health data with greater efficiency. The information present in this proposed system can provide the necessary resources for several actors to exploit this wealth, which is embodied in this massive data. We have developed a general description of the MHDB, its components, its conceptual architecture, and an example of a use case.
۹۸.

Risk Assessment and Determining the Content Production Risk Index of Governmental Digital Libraries in Tehran(مقاله علمی وزارت علوم)

نویسنده:
منبع: International Journal of Digital Content Management, Vol. ۵, No. ۸, Winter & Spring ۲۰۲۴ 149 - 182

کلیدواژه‌ها: content production Governmental Digital Libraries in Tehran Risk Assessment Risk Identification Risk Management

حوزه‌های تخصصی:
تعداد بازدید : ۲۷۵ تعداد دانلود : ۱۷۵
Purpose: This research aimed to identify and evaluate the risks of content production in the governmental digital libraries of Tehran.Method: In terms of essence, this research is synthetic (library studies, qualitative and quantitative), and regarding purpose, it is an applied one.  In the first part, using the studies of the research literature, a set of indicators related to the risks of content production in the governmental libraries of Tehran was obtained. The second part of this research involved a fuzzy Delphi approach that was conducted at two stages among 20 experts. In this stage, a researcher-made questionnaire based on the indicators obtained from the first stage was used. The third part of the research was a survey-analysis conducted with a quantitative method using a questionnaire made out based on the results of qualitative stage with three criteria: the probability of occurrence, effect intensity, and the inability of organization to respond and was distributed among 100 managers and experts of governmental digital libraries in Tehran.Findings: In this research, the risks of content production were identified and fell into nine major categories (human force, environmental factors, infrastructure, protection and maintenance,  creators`  technical rights, integration, content evaluation of sources and authors and information security).Conclusion: The results of this evaluation show that digital libraries are not exactly at their best level when it comes to their responses to the risk of human resources, authors' rights, and integration risks.
۹۹.

طراحی الگوی حکمرانی دانش بنیان در دستگاه های اجرایی(مقاله علمی وزارت علوم)

نویسنده:
منبع: مدیریت راهبردی دانش سازمانی سال ۷ تابستان ۱۴۰۳ شماره ۲۵ 11 - 42

کلیدواژه‌ها: تصمیم گیری مبتنی بر داده حکمرانی دانش حکمرانی هوشمند سازمان یادگیرنده

حوزه‌های تخصصی:
تعداد بازدید : ۲۰۱ تعداد دانلود : ۱۴۷
امروزه حکمرانی دانش بنیان می تواند، اقدامی ارزشمند و تاثیرگذار در جهت بهبود عملکرد نهادهای دولتی و خصوصی باشد. لذا، رعایت اصول حکمرانی دانش بنیان می تواند به بهبود وضعیت سازمان ها و دستگاه های اجرایی و جامعه کمک نماید و سبب استفاده حداکثری از توانایی افراد، کاهش چالش های پیش روی جامعه شده و درنتیجه رفاه عمومی جامعه را به دنبال داشته باشد. این پژوهش با روش کیفی از نوع نطریه داده بنیاد با رویکرد اشتراوس و کوربین انجام شده است جامعه آماری این پژوهش از خبرگان آشنا با موضوع تشکیل شده که با 12 نفر از آن ها با استفاده از روش نمونه گیری قضاوتی و گلوله برفی مصاحبه عمیق، صورت گرفت. تحلیل داده ها به کمک نرم افزار MAXQDA انجام شده است. تعداد 302 کد باز شناسایی شده در قالب 46 زیر مقوله و 18 مقوله اصلی قرار گرفته اند که در 6 طبقه اصلی به عناوین شرایط علی شامل تسهیم، خلق، حفظ و نگهداری دانش و شایستگی مدیران و شرایط زمینه ای شامل ایجاد زیرساخت، ساختار سازمانی و فرهنگ سازمان است. شرایط واسطه ای در برگیرنده مولفه های قوانین و رویه ها، ارزیابی عملکرد، شفافیت، تیم سازی، سیستم جذب و نگهداری، سیستم برنامه ریزی و اداره است. مولفه های قابلیت پویای نوآوری و استراتژی توسعه گرا جز شرایط راهبردی است. پیامدهای حکمرانی دانش بنیان با ارتقای عملکرد جامعه، عملکرد سازمان و عملکرد کارکنان مشخص می شود. شرایط محوری نیز حکمرانی دانش بنیان است. رویکرد داده بنیاد پژوهش و طراحی الگو در دستگاه های اجرایی جنبه منحصر به فرد بودن دارد و می تواند تسهیل گر پیاده سازی حکمرانی دانش بنیان در دستگاه های اجرایی کشور باشد
۱۰۰.

Clinical Healthcare Applications: Efficient Techniques for Heart Failure Prediction Using Novel Ensemble Model(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Information Technology Management , Volume ۱۶, Issue ۱, ۲۰۲۴ 149 - 166

کلیدواژه‌ها: Machine Learning Heart failure Cardiovascular Diseases Ensemble learning Healthcare

حوزه‌های تخصصی:
تعداد بازدید : ۳۱۰ تعداد دانلود : ۱۸۹
Heart failure is a severe medical ailment that significantly impacts patients’ well-being and the healthcare system. For improved results, early detection and immediate treatment are essential. This work aims to develop and evaluate predictive models by applying sophisticated ensemble learning techniques. In order to forecast heart failure, we used a clinical dataset from Kaggle. We used the well-known ensemble techniques of bagging and random forest (RF) to create our models. With a predicted accuracy of 82.74%, the RF technique, renowned for its versatility and capacity to handle complex data linkages, fared well. The bagging technique, which employs several models and bootstrapped samples, also demonstrated a noteworthy accuracy of 83.98%. The proposed model achieved an accuracy of 90.54%. These results emphasize the value of group learning in predicting cardiac failure. The area under the ROC curve (AUC) was another metric to assess the model’s discriminative ability, and our model achieved 94% AUC. This study dramatically improves the prognostic modeling for heart failure. The findings have extensive implications for clinical practice and healthcare systems and offer a valuable tool for early detection and intervention in cases of heart failure.

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