دانلود و نمایش مقالات مرتبط با تجارت الکترونیکی::صفحه 1
دانلود بهترین مقالات isi همراه با ترجمه فارسی 2

با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد). 

نتیجه جستجو - تجارت الکترونیکی

تعداد مقالات یافته شده: 30
ردیف عنوان نوع
1 Research on the financing income of supply chains based on an E-commerce platform
تحقیق در مورد درآمد تأمین مالی زنجیره های تأمین براساس یک بستر تجارت الکترونیکی-2021
Rapid economic development has brought about the expansion of the supply chain. In the context of the demand for finance and emerging financial technology tools, supply chain finance on e-commerce platforms is developing rapidly. It not only strengthens the ability to serve the real economy, but also brings market risks caused by excessive supply chains. In the Internet era, IoT technology promotes the exchange of information, while it also has certain risk characteristics. This research implements the peaks over threshold (POT) model to investigate the value at risk (VaR) and expected loss (ES) in the supply chain of e-commerce platforms under the risk of un- expected changes in the market. The study finds that the supply chain of e-commerce platforms based on Internet of Things (IoT) technology suffers less risk in losses. The application and expansion of this technology will effectively lower the market risk of supply chain finance and better serve economic development.
Keywords: E-commerce platform | Supply chain | Market risk | POT model
مقاله انگلیسی
2 بازاریابی جاذبه ای دیجیتال: اندازه گیری عملکرد اقتصادی تجارت الکترونیکی خواروبار در اروپا و آمریکا
سال انتشار: 2021 - تعداد صفحات فایل pdf انگلیسی: 13 - تعداد صفحات فایل doc فارسی: 30
این تحقیق به بررسی رابطه هزینه-نتیجه اقدامات بازاریابی جاذبه ای مورد استفاده تجارت الکترونیکی خواروبار می پردازد. این تحلیل بر اساس به کارگیری مدل درفمن و استینر (1954) برای بودجه تبلیغات بهینه است که مولفین آن را با بازاریابی دیجیتال تطبیق می دهند و با تحلیل آماری تجاری تایید میکنند. با توجه به 29 شرکت عمده در شش کشور در افق زمانی شش سال، تحلیل ترکیبی تکنیک های بهینه سازی موتور جستجو و بازاریابی موتور جستجو هدف جذب کارکنان به صفحات وب شرکت ها را دنبال می کند. نتایج تایید می کند که تجارت الکترونیکی بازاریابی جاذبه ای دیجیتال را بهینه سازی می کند. تفاوت ها بسته به نوع فرمت و سطح کشور فرق دارند.
واژگان کلیدی: بازاریابی جاذبه ای | بازاریابی دیجیتال | تجارت الکترونیک | خرده فروشی | عملکرد اقتصادی | بهینه سازی سرمایه گذاری بازاریابی.
مقاله ترجمه شده
3 Platform-based customer agility: An integrated framework of information management structure, capability, and culture
چابکی مشتری مبتنی بر پلتفرم: چارچوب یکپارچه ساختار مدیریت اطلاعات، قابلیت و فرهنگ-2021
Platform-based customer agility is the ability to leverage the voice of the customer on a platform to achieve market intelligence and to explore competitive action opportunities. Prior studies have indicated the critical role of customer agility in enabling the survival and prosperity of contemporary organizations in a turbulent business environment, although how to develop this capability is not answered. The current research attempts to fill this theoretical gap. Drawing on the information management literature, we propose an integrative information management framework to investigate the process of developing customer agility. By conducting a case study of a leading e-commerce platform in China, we identify three types of platform-based customer agility (i.e. reactive customer agility, proactive customer agility, and coactive customer agility) in different phases of the growth of the platform. Furthermore, a process model is developed from the case study. It shows that platform-based customer agility is achieved by establishing information management structure, developing information man- agement capability, and instilling information management culture. This study contributes to the knowledge on customer agility and information management. Detailed recommendations are also provided for potential practitioners.
keywords: تجارت الکترونیکی | چابکی مشتری مبتنی بر پلتفرم | مدیریت اطلاعات | مطالعه موردی | چین | Electronic commerce | Platform-based customer agility | Information management | Case study | China
مقاله انگلیسی
4 عکس العمل های شناختی، عاطفی و رفتاری مصرف کننده به واقعیت افزوده در تجارت الکترونیک: مطالعه تطبیقی
سال انتشار: 2021 - تعداد صفحات فایل pdf انگلیسی: 17 - تعداد صفحات فایل doc فارسی: 36
این مقاله به بررسی مزیت نسبی واقعیت افزوده نسبت به ارائه محصول در وب می پردازد. مدل واکنش مصرف کننده را طراحی کرده و واکنش مصرف کنندگان به نرم افزار مکانی آی کی ایی ای و وب سایت موبایلی آی کی ایی ای در گوشی های هوشمند مقایسه می کنیم. نتایج نشان می دهد که واقعیت افزوده عملکرد بهتری نسبت به ارائه محصول در وب سایت دارد در حالی که عکس قضیه به ازای کارایی رسانه درست است. نتایج نشان می دهد ارائه محصول در وب با ایجاد لذت واکنش عاطفی (پسند محصول، لذت جویی) و شناختی (اثربخشی محصول، اعتماد انتخابی) به ویژگی واقعیت افزوده همراه است. برای دستیابی به قصد خرید بالا، آنها باید تعامل را با مشتری افزایش دهند و از محصول انتخاب شده اطمینان یابند.
کلید واژه ها: واقعیت افزوده | بازاریابی واقعیت افزوده | همخوانی واقعیت شناخته شده | سیستم واکنش مصرف کننده | تجارت الکترونیکی | نمایش محصول
مقاله ترجمه شده
5 Website and e-shop Development as an e business Teaching Programme Innovation in Management Education
توسعه وب سایت و فروشگاه الکترونیکی به عنوان یک برنامه آموزش کسب و کار الکترونیکی نوآوری در آموزش مدیریت-2020
The article points out the need to introduce practical e-business learning in management education in Poland in order to adapt it to the labour market demand for new professionals such as digital manager, e commerce manager or e-commerce front-end developer. It also presents both the results of a research on the curricula of business studies and the conclusions of a survey conducted among students of the Faculty of Management, UTP University of Science and Technology in Bydgoszcz, Poland, who attended the e-business/e-commerce classes. It follows that the practical implementation of this subject is not popular in major economics and management courses, while among the public universities studied only UTP conduct classes using WordPress. According to the respondents, this area of knowledge is necessary, and the course itself is attractive and will be useful in the future. Therefore, research results indicate an innovative character of the presented teaching approach.© 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0)Peer-review under responsibility of the scientific committee of the KES International.
Keywords: e-business education | e-commerce education | managers education | higher education | WordPress;
مقاله انگلیسی
6 Can the development of a patient’s condition be predicted through intelligent inquiry under the e-health business mode? Sequential feature map-based disease risk prediction upon features selected from cognitive diagnosis big dat
آیا می توان از طریق استعلام هوشمند تحت شرایط تجارت الکترونیکی ، وضعیت یک بیمار را پیش بینی کرد؟ پیش بینی خطر ابتلا به بیماری مبتنی بر ویژگی های توالی بر ویژگی های انتخاب شده از تشخیص شناختی داده های بزرگ-2020
The data-driven mode has promoted the researches of preventive medicine. In prediction of disease risks, physicians’ clinical cognitive diagnosis data can be used for early prevention of diseases and, therefore, to reduce medical cost, to improve accessibility of medical services and to lower medical risk. However, researches involved no physicians’ cognition of patients’ conditions in intelligent inquiry under e-health business mode, offered no diagnosis big data, neglected the values of the fused text information generated by joint activities of online and offline medical data, and failed to thoroughly analyze the phenomenon of redundancy-complementarity dispersion caused by high-order information shortage from the online inquiry data-driven perspective. Besides, the risk prediction simply based on offline clinical cognitive diagnosis data undoubtedly reduces prediction precision. Importantly, relevant researches rarely considered temporal relationships of different medical events, did not conduct detailed analysis on practical problems of pattern explosion, did not offer a thought of intelligent portrayal map, and did not conduct relevant risk prediction based on the sub-maps obtained from the map. In consequence, the paper presents a disease risk prediction method with the model for redundancy-complementarity dispersion-based feature selection from physicians’ online cognitive diagnosis big data to realize features selection from the cognitive diagnosis big data of online intelligent inquiry; the obtained features were ranked intelligently for subsequent high-dimensional information shortage compensation; the compensated key feature information of the cognitive diagnosis big data was fused with offline electronic medical record (EMR) to form the virtual electronic medical record (VEMR). The formed VEMR was combined with the method of the sequential feature map for modelling, and a sequential feature map-based model for disease risk prediction was presented to obtain online users’ medical conditions. A neighborhood-based collaborative prediction model was presented for prediction of an online intelligent medical inquiry user’s possible diseases in the future and to intelligently rank the risk probabilities of the diseases. In the experiments, the online intelligent medical inquiry users’ VEMRs were used as the foundation of the simulation experiments to predict disease risks in chronic obstructive pulmonary disease (OCPD) population and rheumatic heart disease (RHD) population. The experiments demonstrated that the presented method showed relatively good metric performances in the VEMR and improved disease risk prediction.
Keywords: Cognitive diagnosis big data | Online intelligent inquiry | Sequential feature map | Disease risk prediction | Redundancy and complementarity dispersion
مقاله انگلیسی
7 Contextual factors and performance impact of e-business use in Indonesian small and medium enterprises (SMEs)
عوامل زمینه ای و تأثیر عملکرد استفاده از تجارت الکترونیکی در شرکت های کوچک و متوسط اندونزی (SME)-2020
This study proposes an integrated framework that investigates interrelationships between contextual factors that influence e-business use and consequently its impact on enterprise performance among small and medium en- terprises (SMEs). This study starts with an extensive systematic review of e-business use factors that are contextualized in the technology, organization and environment (TOE) framework and conceptualized using resource-based view (RBV). Data are obtained through a survey of 325 Indonesian SMEs. The partial least square structural equation modeling technique is used to analyze the data and test the hypotheses. The organizational context emerges as the most significant predictor of e-business use, followed by technological and environmental contexts respectively. In addition, e-business use has stronger positive influence on enterprise performance at operational level, rather than managerial and strategic levels. However, e-business uses influence on performance impact at strategic level is indirect, mediating through operational and managerial levels. While the study has attempted to explain the contextual factors that influence the use of e-business as a whole, it is deficient in explaining contextual factors that influence each of e-business applications being used. This study could help SMEs identify contextual areas that may guide them to successfully use e-business and realize its potential benefits.
Keywords: Enterprise resource planning | ERP | Success model | Performance | Management learning | Information systems | Computer science | Human-centered computing | Education | Information science | Business
مقاله انگلیسی
8 Blockchain-enabled logistics finance execution platform for capitalconstrained E-commerce retail
پلت فرم اجرای تأمین مالی تدارکات با استفاده از بلاکچین برای خرده فروشی تجارت الکترونیکی محدود-2019
As one of the most prevailing retail channels, E-commerce has nowadays facilitated retailers to sell goods to customers worldwide and tremendously increased the supply chain efficiency by removing most intermediate links. The broaden business scope and accelerated goods circulation, nevertheless, have generally led to capital shortages for retailers, especially small and medium enterprises (SMEs). Given the SMEs’ difficulty in acquiring capital from financial institutions such as banks, logistics finance (LF) has emerged as an alternative, which is the combination of logistics and financial service. However, the frequent order fulfillment and diversity of pledges in E-commerce hinder SMEs in meeting LFs financing requirements. Furthermore, the current LF relies more on large and reputable third-party logistics (3PLs) to alleviate financing risks, which in turn raises the entry threshold for other 3PLs. Hence, this paper has proposed a blockchain-enabled logistics finance execution platform (BcLFEP) as an integrated solution to facilitate LF for E-commerce retail. A cross-layered architecture is proposed to organize and manage involved resources, workflows and decisions based on the object-oriented methodology (OOM). A hybrid finite state machine-based smart contract (HFSM-SC) is designed to associate and coordinate with all kinds of agents for LF operations throughout its lifecycle. Moreover, blockchain is integrated with agent technology to construct a blockchain-enabled multi-agent system (BcMAS), providing a trusted runtime environment to more autonomously and efficiently execute smart contract. Finally, a case study is conducted to implement BcLFEP-enabled dynamic pledge management for verification and evaluation.
Keywords: Multi-agent system | Blockchain agent | Logistics finance | E-commerce retail
مقاله انگلیسی
9 Multiobjective e-commerce recommendations based on hypergraph ranking
توصیه های تجارت الکترونیکی چندوجهی مبتنی بر رتبه بندی هایپرگراف-2019
Recommender systems are emerging in e-commerce as important promotion tools to assist customers to discover potentially interesting items. Currently, most of these are single- objective and search for items that fit the overall preference of a particular user. In real applications, such as restaurant recommendations, however, users often have multiple ob- jectives such as group preferences and restaurant ambiance. This paper highlights the need for multi-objective recommendations and provides a solution using hypergraph ranking. A general User–Item–Attribute–Context data model is proposed to summarize different in- formation resources and high-order relationships for the construction of a multipartite hy- pergraph. This study develops an improved balanced hypergraph ranking method to rank different types of objects in hypergraph data. An overall framework is then proposed as a guideline for the implementation of multi-objective recommender systems. Empirical ex- periments are conducted with the dataset from a review site Yelp.com, and the outcomes demonstrate that the proposed model performs very well for multi-objective recommenda- tions. The experiments also demonstrate that this framework is still compatible for tradi- tional single-objective recommendations and can improve accuracy significantly. In conclu- sion, the proposed multi-objective recommendation framework is able to handle complex and changing demands for e-commerce customers.
Keywords: Recommender systems | E-commerce | User personalization | Hypergraph
مقاله انگلیسی
10 An integrated recommender system for improved accuracy and aggregate diversity
یک سیستم توصیه گر یکپارچه برای بهبود دقت و تنوع کل-2019
Information explosion creates dilemma in finding preferred products from the digital marketplaces. Thus, it is challenging for online companies to develop an efficient recommender system for large portfolio of products. The aim of this research is to develop an integrated recommender system model for online companies, with the ability of providing personalized services to their customers. The K-nearest neighbors (KNN) algorithm uses similarity matrices for performing the recommendation system; however, multiple drawbacks associated with the conventional KNN algorithm have been identified. Thus, an algorithm considering weight metric is used to select only significant nearest neighbors (SNN). Using secondary dataset on MovieLens and combining four types of prediction models, the study develops an integrated recommender system model to identify SNN and predict accurate personalized recommendations at lower computation cost. A timestamp used in the integrated model improves the performance of the personalized recommender system. The research contributes to behavioral analytics and recommender system literature by providing an integrated decision-making model for improved accuracy and aggregate diversity. The proposed prediction model helps to improve the profitability of online companies by selling diverse and preferred portfolio of products to their customers.
Keywords: Recommender system | Behavioral analytics | Extreme learning | Aggregate diversity | E-business | Decision support system
مقاله انگلیسی
rss مقالات ترجمه شده rss مقالات انگلیسی rss کتاب های انگلیسی rss مقالات آموزشی
logo-samandehi
بازدید امروز: 2881 :::::::: بازدید دیروز: 3084 :::::::: بازدید کل: 5965 :::::::: افراد آنلاین: 59