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نتیجه جستجو - رقابت

تعداد مقالات یافته شده: 419
ردیف عنوان نوع
31 Quality manipulation and limit corruption in competitive procurement
دستکاری کیفیت و محدود کردن فساد در خرید رقابتی-2020
We study competitive procurement administered by an agent who is supposed to evaluate bids on both price and quality by a scoring rule designed by the principal. Since the agent is in charge of verifying delivered quality, he has an opportunity to manipulate his evaluation of quality proposals in exchange for a bribe. In the presence of corruption, the optimal mechanism can be implemented by both first- score and second-score auctions in such a way that the scoring rule should deemphasize quality relative to price. We further identify factors that influence equilibrium corruption: (1) more efficient suppliers are willing to pay higher bribe; (2) the probability of corruption is decreasing in competition and increasing in the agent’s manipulation power; (3) compared to the first-score auction, the second-score auction leads to higher equilibrium bribe and thus is more vulnerable to corruption.
Keywords: Project management | Multidimensional procurement | Corruption
مقاله انگلیسی
32 Reduced Demand Uncertainty and the Sustainability of Collusion: How AI Could Affect Competition
کاهش عدم اطمینان تقاضا و پایداری تبانی: چگونه هوش مصنوعی می تواند بر رقابت تأثیر بگذارد-2020
We model how a technology that perfectly predicts one of two stochastic demand shocks alters the character and sustainability of collusion. Our results show that mechanisms that reduce firms’ uncertainty about the true level of demand have ambiguous welfare implications for consumers and firms alike. An exogenous improvement in firms’ ability to predict demand may make collusion possible where it was previously unsustainable or more profitable where it previously existed. However, an increase in transparency also may make collusion impracticable where it had been possible. The intuition for this ambiguity is that greater clarity about the true state of demand raises the payoffs both to colluding and to cheating. Our findings on the ambiguous welfare implications of reduced uncertainty contribute to the emerging literature on how algorithms, artificial intelligence (AI), and “big data” in market intelligence applications may affect competition.
Keywords: Artificial Intelligence | Uncertainty | Collusion | Price Discrimination | Antitrust
مقاله انگلیسی
33 Deep reinforcement learning for condition-based maintenance planning of multi-component systems under dependent competing risks
یادگیری تقویتی عمیق برای برنامه ریزی نگهداری مبتنی بر شرایط سیستم های چند جزئی تحت خطرات رقابت وابسته-2020
Condition-Based Maintenance (CBM) planning for multi-component systems has been receiving increasing attention in recent years. Most existing research on CBM assumes that preventive maintenances should be conducted when the degradations of system components reach specific threshold levels upon inspection. However, the search of optimal maintenance threshold levels is often efficient for low-dimensional CBM but becomes challenging if the number of components gets large, especially when those components are subject to complex dependencies. To overcome the challenge, in this paper we propose a novel and flexible CBM model based on a customized deep reinforcement learning for multi-component systems with dependent competing risks. Both stochastic and economic dependencies among the components are considered. Specifically, different from the threshold-based decision making paradigm used in traditional CBM, the proposed model directly maps the multicomponent degradation measurements at each inspection epoch to the maintenance decision space with a cost minimization objective, and the leverage of deep reinforcement learning enables high computational efficiencies and thus makes the proposed model suitable for both low and high dimensional CBM. Various numerical studies are conducted for model validations.
Keywords: Maintenance | Markov decision process | Deep Q network | Failure dependency | Cost minimization
مقاله انگلیسی
34 AI-based competition of autonomous vehicle fleets with application to fleet modularity
رقابت ناوگان خودروهای مستقل مبتنی بر هوش مصنوعی با کاربرد در مدولار بودن ناوگان-2020
Because operational environments change over time and technology upgrades are common in fleets of ground vehicles, a large number of vehicles quickly become obsolete. A possible solution is to develop fleets of modular vehicles, which are built with interchangeable components, i.e. modules. This paper evaluates the performance of a future reconfigurable and autonomous vehicle fleet in a high fidelity mili- tary operation scenario. The military fleet operates in a hostile environment under a high risk of damage and needs to react to adversarial actions in real-time. The operation decisions are numerous including vehicle reconfiguration, relocation, damage recovery, and dispatch decisions. Given the limited resources and time delays in the operation, decision effectiveness and foresightedness are necessities, which re- quire a good understanding of the adversary, close collaboration among commanders, and breaking of the equilibrium between adversaries. To capture these characteristics, we formulate an intelligent agent- based model for the decision-making process during fleet operations by combining real-time optimiza- tion with artificial intelligence. With continuous updating of learning models, the intelligent agents refine their decisions during interactions with the environment and other agents, and evolve their competition strategies according to adversarial historical behaviors. With the same level of resources, the conventional fleet wins when the dispatch decisions are stochastic. However, once each fleets start to learn from each other’s behavior, the modular fleet outperforms the conventional fleet. The strategic and operational ben- efits of fleet modularity are revealed and discussed in terms of win rate, adaptability, unpredictability and damage recovery.
Keywords: Multi-agent systems | Decision processes | Artificial intelligence | Strategic planning
مقاله انگلیسی
35 Valuable strategy and firm performance in the O2O competition
استراتژی ارزشمند و عملکرد شرکت در رقابت O2O-2020
When the manufacturer opens an online channel to compete with its traditional retailer, what valuable strategy can be utilized to alleviate the O2O (online to offline) competition and conflict and improve the performances of all channel members? Our research addresses this important question by initiating an innovative strategy considering the retailers sales effort and the manufacturers support in local advertising simultaneously in a manufacturer – retailer O2O supply chain. Our results show that although the retailers sales effort helps improve the channel coordination and leads to a win-win solution for both the manufacturer and the retailer, investing in both the retailers sales effort and manufacturers support in local advertising is a more effective strategy to be employed to coordinate the O2O distribution and achieve higher profits for all parties in the manufacturer - retailer supply chain. In addition, our results also show that compared to the simultaneous mode, the Stackelberg leader-follower mode provides no competitive advantage to the manufacturer or the retailer when the retailers sales effort and manufacturers support in local advertising strategy is implemented to coordinate the O2O distributions.
Keywords: Marketing strategies | O2O competition | Channel coordination | Supply chain management
مقاله انگلیسی
36 Constrained inefficiency of competitive entrepreneurship
ناکارآمدی محدود کارآفرینی رقابتی-2020
We study the constrained efficiency of a competitive entrepreneurship model that features the occupation choice between entrepreneurs and workers. It is shown that, even when (1) the only friction is uninsurable entrepreneurial risks and (2) agents are risk-averse, the competitive market can generate too many entrepreneurs. We present a sufficient statistic that determines the constrained inefficiency and its direction (whether market generates too many entrepreneurs or too few) by exploiting the unique feature of the model where the equilibrium is characterized by an indifference condition instead of a marginal condition. The framework is also pedagogically useful to understand constrained efficiency analysis at intuitive level.© 2020 Elsevier B.V. All rights reserved.
Keywords: Constrained efficiency | Competitive entrepreneurship | Occupation choice | Incomplete markets
مقاله انگلیسی
37 Customer information resources advantage, marketing strategy and business performance: A market resources based view
مزیت منابع اطلاعاتی مشتری ، استراتژی بازاریابی و عملکرد تجاری: نمای مبتنی بر منابع بازار-2020
Chief among a firms market-based resources are its relational resources such as brand equity, customer equity and channel equity that result from its interactions with customers and marketing intermediaries, and intellectual resources – accumulated knowledge about entities in the market environment such as consumers, end use and intermediate customers and competitors. In the evolving digital data rich market environment, customer- based resources, a subset of a firms market-based resources, are becoming increasingly important as potential sources of competitive advantage. Customer information assets refer to information of economic value about customers owned by a firm. Information analysis capabilities are complex bundles of skills and knowledge embedded in a firms organizational processes employed to generate customer knowledge from customer information assets. Customer insights or knowledge is a firms extent of understanding of customers that informs its business decisions. Building on the resource-based, capabilities-based and knowledge-based views of the firm, resource advantage theory of competition, and the outside-in and inside-out approaches to strategy, this article presents a market resources-based view of strategy, competitive advantage and performance. The article presents a framework delineating the relationship between a firms customer information based resources, marketing strategy and performance, and discusses implications for theory, research and practice.
Keywords: Competitive advantage | Market based resources | Customer information based resources | Customer insights | Outside-in and inside-out approaches to | strategy
مقاله انگلیسی
38 Establishing competitive intelligence process elements in sport performance analysis and coaching: A comparative systematic literature review
ایجاد عناصر فرایند هوش رقابتی در تجزیه و تحلیل عملکرد و مربیگری عملکرد ورزشی: یک بررسی مقایسه ای ادبیات سیستماتیک-2020
Sport performance analysts and coaches collect and convert competitor and environmental information for strategic decision making. However, existing studies do not provide a systematic approach for this managerial process. Within the business domain, competitive intelligence (CI) is a proven systematic process, which is applied to enhance organizations’ competitiveness through the systematic collection, conversion and countering of information. Therefore, the objective of this comparative systematic literature review (SLR) was to establish similarities between the business CI elements and sport performance analysis (PA). The review was conducted from the functionalist quadrant, to provide rational explanations where mechanical analogies from the business CI domain were used for modelling and understanding the particular phenomenon of the CI process in sport. A systematic review protocol was established, and a total of 61 articles from the CI (34) and PA (27) domains were included. The SLR revealed substantial similarities of the current sport PA elements to the business CI process. The similarities were used to develop an information management process, which is illustrated as a literature CI model for sport coaches. Specific differences between the two domains indicated that empirical research is needed to fill the gaps of sport CI elements description.
Keywords: Competitive intelligence | Process | Development | Sport
مقاله انگلیسی
39 Tying and bundling by online platforms - Distinguishing between lawful expansion strategies and anti-competitive practices
پیوند و بسته‌بندی توسط پلتفرم‌های آنلاین - تمایز بین استراتژی‌های توسعه قانونی و اقدامات ضد رقابتی-2020
The assessment of tying and bundling practices under Art. 102 TFEU in the case of online platforms will require adjusting current practice to correspond to their technical complexity and multi sided nature. Although the current framework may appear suitable to deal with this kind of abuses, The recent cases against Google show that there is still much uncertainty in practice. Therefore this article seeks to address the matter of tying and bundling by online platforms and provide guidance with regard to the application of the current legal framework to such complex cases in order to prevent false finding in ongoing and future cases.
This article shows that finding an abuse of dominance in platform related cases requires great diligence as the joint provision of products or services and market power leveraging by platforms is an inherent part of their commercial evolvement. In this regard the article offers insight on how to distinguish between anticompetitive tying and bundling practices and legitimate expansion strategies. In order to do so, the article discusses how such practices can manifest and how they should be addressed under the framework of EU competition law in light of the similar competitive concerns they share with non-platform cases.
مقاله انگلیسی
40 The four dimensions of contestable AI diagnostics : A patient-centric approach to explainable AI
چهار بعد از تشخیص رقابتی هوش مصنوعی : یک رویکرد بیمار محور برای هوش مصنوعی قابل توضیح-2020
The problem of the explainability of AI decision-making has attracted considerable attention in recent years. In considering AI diagnostics we suggest that explainability should be explicated as ‘effective contestability’. Taking a patient-centric approach we argue that patients should be able to contest the diagnoses of AI diagnostic systems, and that effective contestation of patient-relevant aspect of AI diagnoses requires the availability of different types of information about 1) the AI system’s use of data, 2) the system’s potential biases, 3) the system performance, and 4) the division of labour between the system and health care professionals. We justify and define thirteen specific informational requirements that follows from ‘contestability’. We further show not only that contestability is a weaker requirement than some of the proposed criteria of explainability, but also that it does not introduce poorly grounded double standards for AI and health care professionals’ diagnostics, and does not come at the cost of AI system performance. Finally, we briefly discuss whether the contestability requirements introduced here are domain-specific.
Keywords: AI diagnostics | Contestability | Explainability | Health data | Bias | Performance | Organisation of diagnostic labour
مقاله انگلیسی
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