فیلترهای جستجو:
فیلتری انتخاب نشده است.
نمایش ۴۱ تا ۶۰ مورد از کل ۲٬۸۶۶ مورد.
منبع:
International Journal of Digital Content Management, Vol. ۵, No. ۸, Winter & Spring ۲۰۲۴
272 - 303
حوزههای تخصصی:
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.
Analyzing the Relationship Between Dimensions of Mental Image, Brand Awareness, and Brand Recognition in Customer Attraction Considering Electronic Service Marketing(مقاله علمی وزارت علوم)
منبع:
International Journal of Digital Content Management, Vol. ۵, No. ۸, Winter & Spring ۲۰۲۴
22 - 46
حوزههای تخصصی:
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.
Identification of Stakeholders in Personal Health Records Using Blockchain Technology: A Comprehensive Review(مقاله علمی وزارت علوم)
حوزههای تخصصی:
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.
Breast Cancer Classification through Meta-Learning Ensemble Model based on Deep Neural Networks(مقاله علمی وزارت علوم)
حوزههای تخصصی:
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.
The Influence of Social Media Marketing Activities on Purchase Intention: A Study of the E-Commerce Industry(مقاله علمی وزارت علوم)
حوزههای تخصصی:
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.
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)
حوزههای تخصصی:
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.
Exploring the Nexus of Big Data Capabilities, Business Model Innovation, and Firm Performance in Uncertain Environments: A Systematic Review(مقاله علمی وزارت علوم)
حوزههای تخصصی:
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.
Validation of the Pattern of Digital Marketing Capabilities Affecting Product Development(مقاله علمی وزارت علوم)
منبع:
International Journal of Digital Content Management, Vol. ۵, No. ۸, Winter & Spring ۲۰۲۴
183 - 205
حوزههای تخصصی:
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.
Efficient NetB3 for Enhanced Lung Cancer Detection: Histopathological Image Study with Augmentation(مقاله علمی وزارت علوم)
حوزههای تخصصی:
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.
Evaluation of the effectiveness of implementing artificial intelligence in the Google Advertising service(مقاله علمی وزارت علوم)
حوزههای تخصصی:
This paper examines the effectiveness of implementing artificial intelligence (AI) in the Google Ads advertising service. The study analyzes the advantages and disadvantages of AI integration, focusing on attribution models and end-to-end analytics. The findings show that traditional metrics, such as CTR, CPC, and ROI, used to evaluate advertising campaign performance, exhibit significant statistical errors when AI tools are applied, with errors reaching up to 35%, exceeding typical business margins. A comparative analysis in the construction industry highlights discrepancies of 10% to 35% between traditional and AI-driven models. The study concludes that universal AI algorithms often fail to account for industry-specific dynamics, leading to inaccurate evaluations. The practical significance of this research lies in proposing an alternative approach that combines traditional evaluation methods with AI-based tools, offering a more reliable framework for assessing campaign effectiveness
Enterprise Resilience Behavioral Management in a Decision Support System(مقاله علمی وزارت علوم)
حوزههای تخصصی:
This article identifies the factors for managing the behavioral resilience of a firm in the face of exogenous shocks in the economy. Its main hypothesis is that each enterprise has certain resilience competencies that need to be strengthened and developed in the future. The paper identifies 17 key competencies that determine the behavioral resilience of an enterprise. Using the method of factor analysis, a model of behavioral resilience is built, which is used to support management decision-making. The factor model of behavioral resilience SELF&IRR includes 7 competencies: S – Speed of response to processes and events; E – Endurance; L – Leadership; F – Flexibility; I – Innovation, ideas, ingenuity; R – Responsibility; R – Resource capabilities. This model can be used to determine the level of behavioral resilience, based on which a decision is made on the choice of the enterprise's strategy. Depending on the level of behavioral resilience, the management staff decides on the choice of a certain strategy (systemic transformation; structural transformation; local changes in the firm's competencies; adaptation of competencies to changes), which is aimed at strengthening the firm's viability and development. The successful execution of a chosen strategy enhances the firm's capacity to withstand current and future threats while actively seeking or purposefully creating new opportunities for development.
Coping Competencies of Iranian Students in E-Learning: A Mixed-Methods Evaluation(مقاله علمی وزارت علوم)
حوزههای تخصصی:
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
طراحی و آزمون مدل موفقّیت آموزش الکترونیکی در صنعت آموزش(مقاله پژوهشی دانشگاه آزاد)
منبع:
مطالعات مدیریت و توسعه پایدار سال ۴ تابستان ۱۴۰۳ شماره ۲
147 - 177
حوزههای تخصصی:
هدف اصلی این پژوهش طراحی و آزمون مدل موفقیت آموزش الکترونیکی در صنعت آموزش است. این مطالعه با استفاده از رویکرد کیفی نظریه داده بنیاد و رویکرد کمّی مدل سازی معادلات ساختاری انجام گرفت. صاحب نظران، اساتید دانشگاه رشته مدیریت، مدیران مؤسسات آموزش الکترونیکی و افراد خبره جامعه آماری را تشکیل دادند و تعداد 8 نفر از این افراد به عنوان نمونه آماری در بخش کیفی و تعداد 70 نفر از این افراد در بخش کمّی انتخاب شدند. به منظور گردآوری داده ها در بخش کیفی از مصاحبه و در بخش کمّی از پرسشنامه استفاده شده است. برای انجام تحلیل های مذکور از نرم افزار MAXQDA نسخه 2020 در بخش کیفی و نرم افزار مدل سازی معادلات ساختاری با استفاده از نرم افزار Smart PLS نسخه 4 در بخش کمّی استفاده شد. یافته های کیفی نشان داد شرایط علّی الگوی موفقیت آموزش الکترونیکی از 33 کد اولیه و 6 مقوله فرعی؛ شرایط زمینه ای شامل 24 کد اولیه و 5 مقوله فرعی؛ شرایط مداخله گر از 36 کد اولیه و 8 مقوله فرعی تشکیل شده است. راهبردهای الگوی موفقیت آموزش الکترونیکی از مقوله های فرعی توسعه جغرافیایی کسب و کار، نقش برنامه ریزی در آموزش الکترونیکی، لزوم بهره گیری از دستاورد های روز، بکارگیری آموزش الکترونیکی در کاهش هزینه ها، عوامل فرهنگی و آموزش الکترونیکی، الزامات آموزش الکترونیکی، استراتژی کسب و کار، طراحی بستر اصولی آموزش الکترونیکی، الزامات موفقیت آموزش الکترونیکی، توانایی کسب وکارهای الکترونیکی می شود. همچنین، یافته ها نشان داد پیامدهای الگوی موفقیت آموزش الکترونیکی شامل مزایای آموزش الکترونیکی، تعامل در محیط های یادگیری الکترونیکی، نقش آموزش الکترونیکی در کسب و کارهای آموزشی، جامعه و آموزش الکترونیکی، پتانسیل آموزش الکترونیکی، آموزش الکترونیکی و کسب و کار و توصیه برای آموزش الکترونیکی می شود. یافته های کمّی نیز نشان داد مدل پژوهش به خوبی برازش شده است.
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)
منبع:
International Journal of Digital Content Management, Vol. ۵, No. ۸, Winter & Spring ۲۰۲۴
229 - 246
حوزههای تخصصی:
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.
Presentation and Validation of Brand-Customer Communication Model in Social Media Platform: A Case Study: Cosmetics Industry(مقاله علمی وزارت علوم)
منبع:
International Journal of Digital Content Management, Vol. ۵, No. ۹, Summer & Fall ۲۰۲۴
110 - 138
حوزههای تخصصی:
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.
Prediction of Time Series of Financial Information Based on Lyapunov View of Information Using Chaos Theory(مقاله علمی وزارت علوم)
حوزههای تخصصی:
Purpose: The purpose of this research was to provide a model for predicting time series of financial information based on the Lyapunov representation of information using chaos theory.Method: This research is applied in its purpose, which is conducted using a quantitative approach. The research ranks as descriptive-causal accounting research based on actual information in companies' financial statements. The research method is the "post-event" type and was carried out using chaos theory and Saida's method based on the Lyapunov view.Findings: The findings showed that during the ADF test, the null hypothesis was rejected at a level of less than 5% type 1 error and 95% confidence, and it shows that the data is not static. During the substitution analysis test and its significance level, the behavior of the time series of the main financial information is significantly different compared to their substitutes. The obtained value was calculated to describe the production process of all data sets for μ = 2, ApEnMax equal to 0.65 and rMax equal to 0.32, and for μ = 3, ApEnMax equal to 0.6 and rMax equal to 0.44. The value of the Lyapunov profile in stability at a certain point is less than zero and in the limited cycle of stability is equal to zero and in chaos, it is greater than zero and smaller than ∞, and in noise it is equal to ∞.Conclusion: The results show that higher returns, encourage investors to invest and increase the flow of capital. It is believed that companies' stock returns are a function of systematic risk, and systematic risk represents the changes in the return rate of a share compared to the changes in the return rate of the entire stock market.
A Blockchain Network for Public Health Interoperability and Real-Time Data Sharing(مقاله علمی وزارت علوم)
حوزههای تخصصی:
In terms of storage and consumption, blockchain technology is poised to transform the way we manage healthcare data. The primary goal is to empower individuals to take charge of their health records, allowing them to become independent of the institutions or organizations they use. Elec-tronic Health Records (EHRs) can be tracked in a novel and unique way through blockchain tech-nology and smart contracts. This technology can give patients more control over their data. Health practitioners and institutions, such as hospitals, may be granted access to patient data controlled by other organizations. This research highlights how blockchain technology can be used to manage EHRs while improving operational efficiency through process simplification and transparency. Additionally, the study proposes an architecture for managing and sharing healthcare data across enterprises. The suggested approach could significantly reduce the time required to transfer patient data among various health organizations while lowering overall costs.
Digital Value Creation by Online Taxi Driving with of Relationship Bonding and Relationship Quality(مقاله علمی وزارت علوم)
منبع:
International Journal of Digital Content Management, Vol. ۵, No. ۸, Winter & Spring ۲۰۲۴
79 - 102
حوزههای تخصصی:
Purpose: This study extends the current understanding of customer engagement by examining the impact of relationship bonding and relationship quality on customer engagement in value creation for online taxis.Method: A quantitative research design was used to validate the hypotheses proposed in this research. Customer engagement has become an important metric for measuring the quality of relationships between brands and their customers. Despite this, there has been limited research into how relationship bonds affect the effectiveness of building such a relationship in online taxi services. A survey was conducted using the convenience method among 600 users of online transportation services in the city of Urmia, Iran to test the theoretical model. Structural equation modelling in software Amos 23 were used in this study to test the research hypotheses. Findings: Findings showed that relationship bonding (financial, social, and structural) positively affects the quality of online relationships. Moreover, it was found that the quality of online relationships had a positive impact on all four aspects of customer engagement value (lifetime value, influence value, customer knowledge value, and customer referral value).Conclusion: In order to demonstrate the promotion of customer engagement through relationship bonds and online relationship quality, the study adds new data to the literature on online taxis services. Online taxi services are able to offer open innovation structures to help them increase customer engagement, gather innovative ideas and integrate them into their operations. In this regard, in order to enrich ideas, customers who have successfully come up with new ideas should be rewarded.
شناسایی و اعتبارسنجی پیشایندها و پیامدهای احتکار دانش توسط کارکنان دانشی(مقاله علمی وزارت علوم)
منبع:
مدیریت راهبردی دانش سازمانی سال ۷ تابستان ۱۴۰۳ شماره ۲۵
107 - 132
حوزههای تخصصی:
احتکار دانش توسط کارکنان دانشی، سازمان را از منابع بسیار ارزشمندی محروم می سازد و می تواند پیامدهای مستقیم و غیرمستقیم فراوانی در پی داشته باشد. پژوهش حاضر با هدف شناسایی و اعتبارسنجی پیشایندها و پیامدهای احتکار دانش توسط کارکنان دانشی انجام شده است. این پژوهش کاربردی با رویکرد آمیخته متوالی اکتشافی انجام گردیده است. شناسایی عوامل با رویکرد کیفی و با استفاده از روش تحلیل مضمون صورت پذیرفته است. مشارکت کنندگان این مرحله شامل اعضای هیئت علمی و خبرگان فنی منتخب نهاجا بوده اند که برای پیمایش دیدگاه آنان، از مصاحبه نیمه ساختاریافته و برای اعتبارسنجی عوامل شناسایی شده در مرحله کمی از روش مدل سازی معادلات ساختاری (تحلیل عاملی تاییدی) استفاده شده است. به این منظور پرسشنامه ای براساس عوامل احصاء شده طراحی و در میان خبرگان فنی منتخب به صورت هدفمند توزیع شد تا روابط بین شاخص ها و مقوله ها ارزیابی شود. داده های مرحله کمی با استفاده از نرم افزار Smart Pls نسخه 3 مورد تحلیل قرار گرفتند. یافته ها نشان داد پیشایندهای احتکار دانش شامل عوامل فردی (تمایلات و علایق، دغدغه ها و نگرانی ها، انگیزه ها، صفات و ویژگی های فردی)، عوامل میان فردی (عوامل ارتباطی)، عوامل سازمانی (عوامل شغلی، فرهنگ سازمانی، عوامل مدیریتی، عوامل ساختاری)، عوامل فراسازمانی (عوامل اجتماعی، فرهنگی و عوامل اقتصادی) بوده است. همچنین پیامدهای احتکار دانش نیز به دو دسته پیامدهای فردی و سازمانی طبقه بندی شدند. تحلیل های کمی نیز معنی داری ارتباط بین شاخص ها و مولفه های مورد نظر را تایید کردند. نتایج این پژوهش می تواند برای مدیریت نمودن پدیده احتکار دانش، شناخت مفیدی در این زمینه فراهم سازد. شناسایی همزمان عوامل موثر بر بروز احتکار دانش در سطوح چهارگانه پیش گفته و همچنین پیامدهایی که این عارضه می تواند برای کارکنان دانشی و سازمان در پی داشته باشد می تواند شناخت موثری برای مدیریت این رفتار مخرب سازمانی فراهم سازد. توجه همزمان به ریشه ها و پیامدهای فردی و سازمانی این عارضه وجه تمایز برجسته این پژوهش به شمار می رود.
Clinical Healthcare Applications: Efficient Techniques for Heart Failure Prediction Using Novel Ensemble Model(مقاله علمی وزارت علوم)
حوزههای تخصصی:
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.