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راهحلهای هوش مصنوعی برای بازاریابی دیجیتال
سال انتشار: 2019 - تعداد صفحات فایل pdf انگلیسی: 7 - تعداد صفحات فایل doc فارسی: 12 چکیده
تکامل تدریجی تکنولوژی در سالهای اخیر باعث حرکت رو به جلوی صنایع شده است. بازاریابی در سیر تکاملی خود به مرحلهای رسیده است که سازگاری با روندهای دیجیتالی ناگزیر است. اگرچه این به صورت فرآیندی تحمیلی بر بازاریابها به نظر میرسد اما در واقع، تمام برنامهها و سیستمهای خودکار که مبتنی بر هوش مصنوعی هستند تنها از پیچیدگیهای متداول هدف گذاری و فرآیندهای بومیسازی میکاهند. در بسیاری از موقعیتها بسترهای مورد استفاده برای تبلیغات آنلاین حاوی الگوریتمهایی برای شناسایی بهترین برهمکنشها هستند، در سایر موقعیتها شرکتها ابتکار عمل را برای توسعه و پیاده سازی ساختارهای ویژه درونی بر عهده میگیرد. هدف محققان، توصیف وضعیت فعلی هوش مصنوعی در فرآیندهای بازاریابی و ارائهی یک مدل متوالی چهار مرحلهای است که از راهحل هوشمند بازاریابی استفاده میکند که میتواند شفافیت وب سایت را از طریق کلمات کلیدی بهبود بخشد.
کلمات کلیدی: هوش مصنوعی | بازاریابی هوشمند | شخصیسازی بازاریابی | ماشینیسازی فرآیند | یادگیری عمیق. |
مقاله ترجمه شده |
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The influence of goal attainment and switching costs on customers’ staying intentions
تاثیر حصول به هدف و سوئیچینگ هزینه بر قصد ماندن مشتریان-2019 It examines the effectiveness of goal attainment (i.e. a value enhancement strategy) and switching costs (i.e. a
defensive retention strategy) in enhancing customers’ staying intentions, where the service type is a key
boundary condition. The data was collected using a survey design and analyzed using a multi-group SEM approach.
Goal attainment played a stronger role in influencing staying intentions in services with passive customer
participation and a low degree of customization (i.e. retail banking) than in services with active customer
participation and a high degree of customization (i.e. stock brokerage). Different switching costs varied in importance
across the two service industries Keywords: Switching costs | Goal attainment | Customers’ staying intentions | Retail banking | Stockbrokerage services |
مقاله انگلیسی |
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Proactive vs: reactive personalization: Can customization of privacy enhance user experience?
شخصی سازی فعالانه در مقابل واکنشی: آیا شخصی سازی حریم شخصی می تواند تجربه کاربر را افزایش دهد؟-2019 Online recommender systems have triggered widespread privacy concerns due to their reliance on personal user
data for providing personalized services. To address these concerns, some systems have started allowing users to
express their preferences before receiving personalized content (i.e., reactive personalization) rather than automatically
pushing it to them (i.e., proactive personalization). However, this would mean constant calls for user
action, which can adversely affect user experience. One potential solution is to offer users the ability to customize
their privacy settings at the outset, thus obviating the need for constant consultation. We conducted a 2
(Personalization: Reactive vs. Proactive) X 3 (Customization of Settings: Absence vs. Action vs. Cue) factorial
experiment (N=299) with a movie recommendation system. Findings show that interface cues suggesting
customization enhance user experience, even in the presence of proactive personalization. They also highlight
the important role played by negative privacy experiences in the past.. Keywords: Customization | Personalization | Recommender systems | Privacy | User experience | Experiment |
مقاله انگلیسی |
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استفاده از بلاکچین برای بازگشت در دنیای جدید پس از حقیقت و بررسی گسترش اخبار جعلی
سال انتشار: 2019 - تعداد صفحات فایل pdf انگلیسی: 6 - تعداد صفحات فایل doc فارسی: 15 این مشکل به دلیل ظهور پدیدههای مختلف همراه مانند (۱) دیجیتال سازی زندگی انسان و سهولت انتشار اخبار از طریق برنامههای شبکههای اجتماعی (مانند فیس بوک و واتس آپپ) (۲) در دسترس بودن دادههای بزرگ که امکان سفارشیسازی تغذیه اخبار و ایجاد به اصطلاح " فیلتر - حبابها و (۳) پیشرفت سریع ایجاد شده توسط یادگیری ماشین مولد (ML) و یادگیری عمیق (DL) را فراهم میکند، به وجود آمده است. نیاز حیاتی برای مبارزه با ظهور شایع اخبار تقلبی و اطلاعات دروغ وجود دارد. در این مقاله، ما یک مرور سطح بالا از یک چارچوب مبتنی بر بلاکچین برای جلوگیری از اخبار ساختگی پیشنهاد میکنیم و موضوعات مختلف طراحی و توجه به چنین چارچوب مبتنی بر بلاکچین برای مقابله با اخبار جعلی را برجسته میکنیم. |
مقاله ترجمه شده |
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Learning about risk: Machine learning for risk assessment
یادگیری در مورد ریسک: یادگیری ماشینی برای ارزیابی ریسک-2019 Risk assessment has a primary role in safety-critical industries. However, it faces a series of overall challenges,
partially related to technology advancements and increasing needs. There is currently a call for continuous risk
assessment, improvement in learning past lessons and definition of techniques to process relevant data, which
are to be coupled with adequate capability to deal with unexpected events and provide the right support to
enable risk management. Through this work, we suggest a risk assessment approach based on machine learning.
In particular, a deep neural network (DNN) model is developed and tested for a drive-off scenario involving an
Oil & Gas drilling rig. Results show reasonable accuracy for DNN predictions and general suitability to (partially)
overcome risk assessment challenges. Nevertheless, intrinsic model limitations should be taken into account and
appropriate model selection and customization should be carefully carried out to deliver appropriate support for
safety-related decision-making. Keywords: Risk assessment | Dynamic risk analysis | Machine learning | Deep learning |
مقاله انگلیسی |
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Customer Relationship Management and Big Data Enabled: Personalization & Customization of Services
مدیریت ارتباط با مشتری و داده های بزرگ فعال: شخصی سازی و سفارشی سازی خدمات-2018 The emergence of big data brings a new wave of Customer Relationship Management (CRM)’s
strategies in supporting personalization and customization of sales, services and customer services.
CRM needs big data for better customers experiences especially personalization and customization
of services. Big data is a popular term used to describe data that is volume, velocity, variety,
veracity, and value of data both structured and unstructured. Big data requires new tools and
techniques to capture, store and analyse it and is used to improve decision making for enhancing
customer management. The aim of the research is to examine big data for CRM’s scenario. The
method of collection of data for this study was literature review and thematic analysis from recent
studies. The study reveals that CRM with big data has enabled business to become more aggressive
in term of marketing strategy like push notification through smartphone to their potential target
audiences.
Key words: Big Data, Data Analytics, CRM, Web 2.0, Social Networks |
مقاله انگلیسی |
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Experience-involvement, memorability and authenticity: The service providers effect on tourist experience
درگیری با تجربه، خاطره انگیز بودن و اصلیت: تاثیر ارائه دهنده خدمات روی تجربه گردشگر-2018 The purpose of the research was to investigate how service providers can enhance memorable and authentic tourist experiences in on-site conditions, in the context of sightseeing tours. Based on scale development, the experience-involvement construct is introduced to measure on-site tourist experience. The role of on-site experience as a predictor of memorable and authentic experiences was emphasized and empirically tested, and four dimensions of on-site tourist experience were identified: emotional, mental, flow-like and social experience-involvement. PLS-SEM revealed that interactive service elements and customization have a significant effect on on-site, memorable and authentic tourist experience formation, however, organizational service elements (e.g. physical environment, comfort) do not. The findings not only contribute to the body of knowledge on tourist experience formation with potential managerial implications, but fuel the emerging academic and industry discussion about the differences between services generating satisfaction (only) and those leading to memorability.
keywords: Tourism experience |PLS-SEM |Scale development |Involvement |Flow |Memorable experience |Sightseeing tour |Tour guide |
مقاله انگلیسی |
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Integration of product development capability and supply chain capability: The driver for high performance adaptation
یکپارچگی قابلیت توسعه محصول و قابلیت زنجیره تامین: محرکی برای سازگاری با عملکرد بالا-2018 The research of the past decade indicates that the fit between product characteristics and supply chain characteristics has still not been specified. In line with this research issue, this paper proposes one key issue: whether companies can dynamically adjust the two effectively to address changing competitive circumstances along the product life cycle, rather than having just one specific life-long fit between the two sets of characteristics. Building on previous research addressing the concept of absolute supply chain orientation strategy, this study proposes that companies become high performers over time by strengthening and coordinating product development and supply chain management capabilities and adjusting their fit over time. This will be the focus of this research. To date, the mentioned approach which views the fit issue from the point of coordination between the two capabilities has not been considered in past research. This study has used diverse statistical methods on a sample of 303 plants from an international database obtained from a survey from fourteen countries, completed in 2016. Major implications of this study are to confirm that: First, the two above-mentioned capabilities counterbalance each other in order to maintain a positive relationship with each other. Second: a) companies are more competitive over time when they are high performers in both of these capabilities; b) high performers are able to leverage methods such as modularity and mass customization in their pursuit of fits; c) many average companies are advised to put relatively greater priority on strengthening supply chain capability than on product development capability as they endeavor to become high performers.
keywords: Product development strategy |Supply chain strategy |Alignment capability |
مقاله انگلیسی |
19 |
Open source ERP business model framework
چارچوب مدل تجاری سیستم ERP-2018 ERP systems became popular with large organizations in the 1990s. In the 21st Century, these products were
expanded by addition of supply chain management (SCM) and customer relationship management (CRM), as well
as access through the Web, creating the ERP II concept. Efforts to increase the market led vendors to serve not
only large organizations, but also focus more on small-to-medium sized enterprises (SMEs).
Open source software has become a player in the field of enterprise resource planning (ERP) systems. While
it is still unclear to what extent it has diffused among organizations, it is clear that opportunities exist. New
ways of delivering ERP software, such as software as a service (SaaS) have appeared. Some smaller vendors
utilized a free distribution system (Free/Open Source ERP, FOS-ERP) for their source code, relying on various
business models for corporate success. There also have been attempts to generate FOS-ERP components found on
sites such as SourceForge.com that are not only distributed freely, but also were developed through community
participation much as Linux has been developed. Some ERP vendors use community developed components for
various purposes to support their proprietorial software. Thus one dimension of ERP systems is based upon who
directs the development process. Proprietorial ERP refers to systems with closely held intellectual property rights,
such as the leading market products by SAP and Oracle as well as many smaller proprietorial competitors. FOS
ERP can be community based, or sponsored by some organization.
In this paper we present a framework that aims at analyzing FOS-ERP business models. Goals include dis
cussing the differences between FOS-ERP and their proprietary equivalents (P-ERP) in terms of business models,
selection, customization, and evolution. We will discuss challenges and opportunities that they offer to adopters
and vendors.
Keywords: Business models ، Enterprise resource planning (ERP) ، Evaluation ، Open source |
مقاله انگلیسی |
20 |
A novel methodology for optimizing display advertising campaigns using genetic algorithms
یک روش نوین برای بهینه سازی پویش های نمایش تبلیغات با استفاده از الگوریتم های ژنتیک-2018 Online advertising campaigns have attracted the attention of many advertisers willing to promote their business on the Internet. One of the main problems faced by advertisers, especially by those who have little experience in Internet advertising, is configuring their campaigns in an efficient way. To configure a campaign properly it is required to select the appropriate target, so it is guaranteed a high acceptance of users to adverts. It is also required that the number of visits that satisfy the configuration requirements is high enough to cover the advertisers’ campaigns. Thus, this paper presents a novel methodology for optimizing the micro-targeting technique in direct response display advertising campaigns by using genetic algorithms as the basis optimization model and a machine-learning based click-through rate (CTR) model. We implement our methodology to optimize display advertising campaigns on mobile devices using a real dataset. Results show that our methodology is feasible to optimize the campaigns by selecting the set of the best features required. Also, customization of the advertising campaign selecting some features by an advertiser, e.g. applying micro-targeting, can be optimized efficiently.
keywords: Display advertising campaigns |Direct response |Optimization |Genetic algorithms |Micro-targeting |Machine learning |
مقاله انگلیسی |