کارابرن عزیز، مقالات isi بالاترین کیفیت ترجمه را دارند، ترجمه آنها کامل و دقیق می باشد (محتوای جداول و شکل های نیز ترجمه شده اند) و از بهترین مجلات isi انتخاب گردیده اند. همچنین تمامی ترجمه ها دارای ضمانت کیفیت بوده و در صورت عدم رضایت کاربر مبلغ عینا عودت داده خواهد شد.
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Firm technological responses to regulatory changes: A longitudinal study in the Le Mans Prototype racing
پاسخ های فناورانه شرکت به تغییرات مقرراتی: یک مطالعه طولی در مسابقه آزمایش لی مانز-2018
Despite the critical role of regulations on competition and innovation, little is known about firm responses and related effects on performance under regulatory contingencies that are permissive or restrictive. By longitudinally investigating hybrid cars competing in the Le Mans Prototype racing (LMP1), we counter-intuitively suggest that permissive regulations increase technological uncertainty and thus decrease the firms’ likelihood of shifting their technological trajectory, while restrictive regulations lead to the opposite outcome. Further, we suggest that permissive regulations favour firms that innovate their products by sequentially upgrading core and peripheral subsystems, while restrictive regulations (in the long term) favour firms upgrading them simultaneously. Implications for theory and practice are discussed.
keywords: Regulations | Environmental change | Technological innovation | System complexity | Technological trajectory | Knowledge| Performance | Hybrid vehicles | Le Mans Prototype racing | LMP1
Effect of disruptive customer behaviors on others overall service experience: An appraisal theory perspective
تاثیر سفارشات رفتارهای درهم گسیخته مشتری روی تجربه کلی خدماتی سایرین: یک دیدگاه نظریه ارزیابی-2018
Drawing upon the appraisal theory, this study proposes and tests a conceptual model to delineate customers’ evaluative process of disruptive customer behaviors in a shared service environment (e.g., theme parks, airplanes, restaurants). Using a scenario-based online experiment, two sets of data were collected from U.S. customers and analyzed by a series of regression analyses. Findings suggest that customers go through a systematic evaluative process of primary appraisal (e.g., congruence and relevance) and secondary appraisal (e.g., cognitions and emotions), which results in the development of coping behaviors (e.g., active and passive coping). Cognitions are found to have direct influences on passive and active coping. Perceived powerlessness, perceived betrayal, and perceived identity threat are identified as critical cognitions. Negative emotions are found to result in active coping. Primary appraisal (e.g., congruence and relevance) either directly affects coping behaviors, or indirectly through cognitions and negative emotions. Theoretical and managerial implications are further elaborated.
keywords: Customer misbehavior| Disruptive customers| Appraisal theory| Perceived powerlessness| Perceived betrayal| Negative emotions
When are stakeholder pressures effective? An extension of slack resources theory
چه موقع فشارهای سهامدار موثر می باشد؟ یک بسطی از نظریه منابع سست-2018
There has been an intense debate on when stakeholder pressures are effective in driving firms to contribute to sustainable development. Drawing upon institutional theory and slack resources theory, we theorize that country-level sustainability performance interacts with slack resources in shaping corporate responsiveness to stakeholder pressures. Empirical results based on the data from 6th International Manufacturing Strategy Survey and secondary data of the Human Development Index and the Environmental Performance Index support our hypotheses. As hypothesized, in countries with low level sustainability performance, firms with considerable slack resources are more responsive to stakeholder pressures than their peers with limited slack resources. In contrast, in countries with high levels of sustainability performance, there are no significant differences between firms with and without considerable slack resources in their responsiveness to stakeholder pressures. This study contributes to a better understanding of organizational responses to stakeholder pressures. Moreover, it suggests that stakeholders, depending on country-level sustainability performance, should adopt different strategies to stimulate firms to participate in sustainable development.
keywords: Environmental issues |Social responsibility |Stakeholder pressures |Survey methods |Hierarchical linear modelling
Hotel location when competitors may react: A game-theoretic gravitational model
مکان هتل وقتی که رقبا ممکن است واکنش نشان دهند: یک مدل نظری گرانشی بازی-2018
This paper presents a hotel location model that incorporates concepts from both game theory and gravitational site location models. We consider a hotel chain intending to build new hotels in a given region. Customers travel to the region to visit some specific points, termed “attractions”, and they choose a hotel according to room price, location and hotel attractiveness. Competitor hotels react to the new hotels by changing prices, in order to maximize their own profits, so the final set of prices will be a Nash equilibrium. We propose an iterative procedure for finding the equilibrium prices and a genetic algorithm-based procedure for finding the optimal strategy, in terms of new hotels to be built and respective typologies. Using a mini case, we illustrate and analyse the influence of several parameters. Then, we present computational experiments, concluding that the proposed procedures are effective in finding good solutions for the model.
keywords: Tourism site location| Game theory| Genetic algorithms| Spatial interaction models
Competitive store closing during an economic downturn
بستن انبار رقابتی درطی یک رکود اقتصادی-2018
The economic downturn of the late 2000s resulted in the closing of a number of retail stores. When doing so a firm has to consider which stores to close, and when to close them, so that profits are maximized. Since retail stores operate in a competitive environment, these decisions are not simply a function of a retailers existing store locations but are also contingent on the location, and closing decisions, of stores operated by rival firms. This paper examines a game between two retail chains looking to downsize operations in a given region and presents a solution procedure that captures the equilibrium store closing decisions. The solution procedure includes a single period mixed integer program model and a multi-period heuristic with a backward and forward pass to find near optimal solutions. Our results provide guidelines for developing effective strategies to systematically reduce the number of stores so that profit is maximized while competitive pressure is exerted on rival stores.
keywords: Location analysis |Store closing |Integer linear programming |Game theory
Fault-diagnosis for reciprocating compressors using big data and machine learning
تشخیص گسل برای کمپرسورهای مجاور با استفاده از داده های بزرگ و یادگیری ماشین-2018
Reciprocating compressors are widely used in petroleum industry. A small fault in recipro cating compressor may cause serious issues in operation. Traditional regular maintenance and fault diagnosis solutions cannot efficiently detect potential faults in reciprocating com pressors. This paper proposes a fault-diagnosis system for reciprocating compressors. It applies machine-learning techniques to data analysis and fault diagnosis. The raw data is denoised first. Then the denoised data is sparse coded to train a dictionary. Based on the learned dictionary, potential faults are finally recognized and classified by support vector machine (SVM). The system is evaluated by using 5-year operation data collected from an offshore oil corporation in a cloud environment. The collected data is evenly divided into two halves. One half is used for training, and the other half is used for testing. The results demonstrate that the proposed system can efficiently diagnose potential faults in com pressors with more than 80% accuracy, which represents a better result than the current practice.
Keywords: Reciprocating compressor، Big data ، Cloud computing ، Deep learning ، RPCA ، SVM
Leverage constraints and asset prices: Insights from mutual fund risk taking
محدودیت های اهرم بندی و قیمت های دارایی: بینش هایی از به خطر افتادن سرمایه دوطرفه-2018
Prior theory suggests that time variation in the degree to which leverage constraints bind affects the pricing kernel. We propose a measure for this leverage constraint tightness by inverting the argument that constrained investors tilt their portfolios to riskier assets. We show that the average market beta of actively managed mutual funds—intermediaries facing leverage restrictions—captures their desire for leverage and thus the tightness of constraints. Consistent with theory, it strongly predicts returns of the betting-against-beta portfolio, and is a priced risk factor in the cross-section of mutual funds and stocks. Funds with low exposure to the factor outperform high-exposure funds by 5% annually, and for stocks this difference reaches 7%. Our results show that the tightness of leverage constraints has important implications for asset prices.
keywords: Leverage constraints |Asset prices |Betting-against-beta |Mutual fund performance |Cross-section of stock returns
Simulation methodology and performance analysis of network coding based transport protocol in wireless big data networks
روش شبیه سازی و تجزیه و تحلیل کارایی پروتکل انتقال مبتنی بر کدگذاری شبکه در شبکه های داده های بزرگ بی سیم-2018
The Multi-Path, Multi-Hop (MPMH) communications have been extensively used in wire less network. It is especially suitable to big data transmissions due to its high throughput. To provide congestion and end-to-end reliability control, two types of transport layer pro tocols have been proposed in the literature: the TCP-based protocols and the rateless cod ing based protocols. However, the former is too conservative to explore the capacity of the MPMH networks, and the latter is too aggressive in filling up the communication capac ity and performs poorly when dealing with congestions. To overcome their drawbacks, a novel network coding scheme, namely, Adjustable Batching Coding (ABC), was proposed by us, which uses redundancy coding to overcome random loss and uses retransmissions and window size shrink to relieve congestion. The stratified congestion control strategy makes the ABC scheme especially suitable for big data transmissions. However, there is no simu lation platform built so far that can accurately test the performance of the network coding based transport protocols. We have built a modular, easy-to-customize simulation system based on an event-based programming method, which can simulate the ABC-based MPMH transport layer behaviors. Using the proposed simulator, the optimal parameters of the protocol can be fine-tuned, and the performance is superior to other transport layer pro tocols under the same settings. Furthermore, the proposed simulation methodology can be easily extended to other variants of MPMH communication systems by adjusting the ABC parameters.
Keywords: Network simulator ، Wireless big data networks ، Multi-path multi-hop communications ، Transport layer ، Network coding
If you, tourist, behave irrationally, I’ll find you!
اگر توی گردشگر رفتاری غیر منطقی کنی من تورا پیدا خواهم کرد!-2018
When departures from rational behavior can potentially be expected, modeling should allow for their identification and their quantification. In this regard, prices in tourism might have effects that may not be as apparent as economic theory predicts. This article incorporates the sticker shock formulation into the mixed logit model without imposing consistency with consumer theory to accommodate any possible positive or negative price effects. By allowing the parameters of “price” and “sticker shock term” to take any value – negative or positive – we detect abnormal behaviors in the tourist demand: not only is the negative relationship between price and demand inverted for some people but also some tourists might be willing to accept higher-than-expected prices. The “non-well-behaved” groups shares are estimated.
keywords: Utility theory| Irrational behavior| Reference prices| Sticker shock model| Choice model
IOT and big data based cooperative logistical delivery scheduling method and cloud robot system
اینترنت اشیا و داده های بزرگ مبتنی بر همکاری لایسنسسی برنامه ریزی تحویل و سیستم ربات ابر-2018
Many studies have been done for logistics delivery scheduling technologies, but the cooperating and relaying of resources in the process of logistics delivery remains elusive. We proposed IOT and big data based cooperative logistical delivery scheduling method and cloud robot system, After obtaining the big data of logistics delivery resources and requirements from logistics delivery companies through the IOT and/or Internet, establishing the map of logistics delivery routes based on the big data of logistics delivery resources, the logistics delivery route corresponding to the logistics delivery requirements is selected from the map of logistics delivery routes by using the shortest route algorithm of the graph theory, and then the logistics delivery resources corresponding to the logistics delivery route are scheduled to the corresponding logistics delivery requirements, which can greatly improve the cooperative scheduling of logistics delivery resources among different logistics delivery companies to enhance the level of logistics delivery resources utilization, reduce the logistics delivery logistics delivery costs, and improve customer experience.
Keywords: logistical delivery, cooperative scheduling, IOT, big data, cloud robot