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تغییر یا نابودی : بررسی نقش سرمایه انسانی و توانمندی های بازاریابی فعال در بخش هتلداری
سال انتشار: 2021 - تعداد صفحات فایل pdf انگلیسی: 13 - تعداد صفحات فایل doc فارسی: 33 بسیاری از محققان تلاش کرده اند شرح دهند کدام عوامل بر مزیت رقابت آمیز پایدار تاثیر می گذارند. بدین منظور، این مقاله به ادبیات بازاریابی و مدیریت هتلداری افزوده و شواهد تجربی مبنی بر نحوه تاثیر سرمایه انسانی، توانایی بازاریابی پویا و پویایی بازار بر مزیت رقابت آمیز در بخش هتداری فراهم می سازد. داده های نظرسنجی مقطعی را از مدیران فروش و بازاریابی 165 هتل با مصاحبه مفصل در سه هتل واقع در کشورهای شورای همکاری خلیج مشتمل بر عربستان سعودی، قطر، امارات و بحرین جمع آوری کردیم. یافته ها نشان داد که سرمایه انسانی به طور مستقیم و غیرمستقیم از طریق توانمندی بازاریابی پویا نقش اساسی در گسترش مزیت رقابت آمیز ایفا می کند. برای مفهوم سازی این نقش، تحقیق ما نشان می دهد که پویایی بازار در رابطه بین سرمایه انسانی و مزیت رقابتی از طریق توانمندی بازار مداخله می کند. مفاهیم نظری و مدیریتی را برای گسترش مزیت رقابتی در بخش هتل مطرح می کنیم.
کلمات کلیدی: سرمایه انسانی | قابلیت های بازاریابی فعال | پویایی بازار | مزیت رقابت آمیز | بخش هتلداری |
مقاله ترجمه شده |
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Improving sustainability and social responsibility of a two-tier supply chain investing in emission reduction technology
بهبود پایداری و مسئولیت اجتماعی یک زنجیره تأمین دو لایه سرمایه گذاری در فناوری کاهش انتشار-2021 This paper studies a retailer-dominated supply chain including a single upstream manufacturer that produces two substitutable products and a single downstream retailer that
undertakes corporate social responsibility activities. The manufacturer is also regulated by
a cap-and-trade policy. We first compare two optimization models for a decentralized system, one that does and one that does not incorporate emission reduction technology, to
show that the profit of each system member in the former is higher than that in the latter, while the opposite is true for carbon emissions when the technology level invested by
the manufacturer is higher than a threshold. To test the performance of the decentralized
model that incorporates emission reduction technology, we model a centralized system
and reveal that the system profit in the decentralized model is increased and the corresponding carbon emissions generated during production can be reduced. These findings
motivate us to propose a revenue and cost-sharing contract to coordinate the decentralized system. The result shows that the economic and environmental sustainability of the
decentralized system can be improved. Finally, several managerial implications are derived
by conducting a numerical study. Keywords: Retailer-dominated supply chain | CSR | Emission reduction technology | Sustainability | Coordination |
مقاله انگلیسی |
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Message personalization and real-time adaptation as next innovations in sport sponsorship management? How run-of-play and team affiliation affect viewer response
شخصی سازی پیام و سازگاری در زمان واقعی به عنوان نوآوری های بعدی در مدیریت حمایت ورزشی؟ نحوه اجرای بازی و وابستگی به تیم چگونه بر پاسخ بینندگان تأثیر می گذارد-2021 The digitization of sports content and technological innovations in sports media offer disruptive new ways to adapt sponsor messages to real-time events during live broadcasts. To date, sponsorship management mostly ignores the run-of-play and viewers’ team affiliation. This paper seeks to demonstrate how a dynamic management approach can contribute to greater sponsor message efficiency. For this purpose, real-time data were collected during live broadcasts of the 2018 soccer World Cup. Arousal was captured using changes in heart rate, attention to sponsor brands was measured via eye tracking, and in-play betting odds were continuously obtained from a sports betting website. Mixed models predict viewer arousal and sponsor brand attention from biometric and betting data. Evidence is provided for how run-of-play and viewer characteristics affect sponsor message communication outcomes. The applicability of the models for distinctive sponsor exposure tactics is demonstrated, and the theoretical and managerial implications are outlined. |
مقاله انگلیسی |
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Buyer selection and service pricing in an electric fleet supply chain
انتخاب خریدار و قیمت گذاری خدمات در زنجیره تأمین ناوگان الکتریکی-2021 Much attention has been focused on supplier selection in operations. There has been less research on the
supplier selecting buyers in a two-echelon supplier-buyer chain, which we study for downstream taxicab
vehicle fleets. We consider the problem of pricing infrastructure services by an electric vehicles (EVs) service provider (SP), which determines the group of taxicab companies (TCs) that will adopt EVs. We study
SP’s pricing decisions in a decentralized supply chain under a general infrastructure cost function, multiple TCs, and symmetric information. We extend the modeling to the case with (i) endogenous demand
and EV-taxicab end-consumer pricing and (ii) asymmetric information between SP and TC. We analyze
the factors that influence SP’s profits and the set of participating TCs who adopt EVs. We find that when
the fleet size of TCs increases, SP prefers to serve more low-mile TCs than the high-mile TCs and even
removes some high-mile TCs in exchange for low-mile TCs, where low and high-miles correspond to average miles driven in a time period (shift). When the coefficient of variation of miles driven increases,
SP prefers to serve more high-mile TCs than the low-mile TCs. In general, the set of TCs that adopt EVs
cannot be simply characterized using inputs such as average miles driven by different TCs. This study
provides a modeling framework and managerial implications for TC selection and pricing contracts by an
EV infrastructure service provider. Keywords: Supply chain management | Buyer selection | Electric Vehicles | Service pricing | Submodular infrastructure cost |
مقاله انگلیسی |
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Investigating the effect of horizontal coopetition on supply chain resilience in complex and turbulent environments
بررسی تأثیر همکاری افقی بر انعطاف پذیری زنجیره تأمین در محیطهای پیچیده و آشفته-2021 Today supply chain operations are continuously threatened by frequent and unpredictable disruptions. To survive in such complex and fast-changing environments, firms need to develop resilient strategies for their supply chains. To this regard, previous studies in literature have shown that cooperative relationships play a relevant role. However, there are evidence that firms more often prefer a coopetition strategy, where both cooperative and competitive relationships are simultaneously adopted to manage supply chain relationships. Despite the relevance of this topic, how coopetitive relationships influence resilience has been less investigated so far. In this paper, we use a complex adaptive system approach to conceptualize horizontal coopetition in supply chains and develop a novel agent-based model to simulate its effect on supply chain resilient performance in different environmental conditions, characterized by increasing level of complexity and frequency of disruptions. Results show that coopetition can be beneficial for supply chain resilience and that environmental complexity (turbulence) positively (negatively) moderates this relation. Theoretical contributions and managerial implications are finally discussed. Keywords: Coopetition | Horizontal coopetition | Supply chains | Resilience | Agent-based model |
مقاله انگلیسی |
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Characterizing customer experience management in business markets
توصیف مدیریت تجربه مشتری در بازارهای تجاری-2020 Managing the customer experience has become a top priority for marketing managers and researchers. Research on customer experience management (CEM) has traditionally adopted a customer’s viewpoint. Few studies have explicitly embraced an organizational perspective, and existing research focuses mainly on business-to-consumer settings. The present study espouses the utility of CEM in business-to-business (B2B) settings on the grounds that interactions in B2B contexts are also “experienced”. It explains how B2B firms can design and manage the customer experience to influence the customer at different touchpoints. The paper develops a comprehensive framework that characterizes CEM in B2B. The paper articulates key challenges for B2B CEM; relationship expectations (mismatches in customer relationships, siloed customer experiences); actor interaction issues (mis- matches across the customer’s journey, lack of touchpoint control); and temporal challenges (dynamics of the customer experience). The paper draws out the theoretical implications and develops managerial implications for B2B firms. Keywords: Customer experience management | Customer journey | Market strategy | B2B | Touchpoint |
مقاله انگلیسی |
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Artificial intelligence and business models in the sustainable development goals perspective: A systematic literature review
هوش مصنوعی و مدل های تجاری در چشم انداز اهداف توسعه پایدار: یک مرور ادبیات سیستماتیک-2020 This paper investigates the literary corpus on the role of Artificial Intelligence (AI) in the construction of sustainable business models (SBMs). It provides a quantitative overview of the academic literature that constitutes the field. The paper discusses the relationships between AI and rapid developments in machine learning and sustainable development (SD). Specifically, the aim is to understand whether this branch of computer science can influence production and consumption patterns to achieve sustainable resource management according to Sustainable Development Goals (SDGs) outlined in the UN 2030 Agenda. Moreover, the paper aims to highlight the role of Knowledge Management Systems (KMS) in the cultural drift toward the spread of AI for SBMs. Despite the importance of the topic, there is no comprehensive review of the AI and SBM literature in light of SDGs. Based on a database containing 73 publications in English with publication dates from 1990 to 2019, a bibliometric analysis is conducted. The findings show that the innovation challenge involves ethical, social, economic, and legal aspects. Thus, considering that the development potential of AI is linked to the UN 2030 Agenda for SD, especially to SDG#12, our results also outline the framework of the existing literature on AI and SDGs, especially SDG#12, including AI’s association with the cultural drift (CD) in the SBMs. The paper highlights the key contributions, which are: i) a comprehensive review of the key underlying relationship between AI and SBMs, offering a holistic view as needed, ii) identifying a research gap regarding KMS through AI, and iii) the implications of AI concerning SDG#12. Academic and managerial implications are also discussed regarding KMS in the SBMs, where the AI can represent the vehicle to meet the SDGs allowing for the identification of the cultural change required by enterprises to achieve sustainable goals. Thus, business companies, academic re- search practitioners, and state policy should focus on the further development of the use of AI in SBMs. Keywords: Artificial Intelligence (AI) | Machine learning sustainability | Cultural drift | Sustainable business models | Knowledge Management System (KMS) |
مقاله انگلیسی |
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Shopping intention at AI-powered automated retail stores (AIPARS)
قصد خرید در فروشگاه های خودکار خرده فروشی مجهز به هوش مصنوعی (AIPARS)-2020 Artificial Intelligence (AI) is transforming the way retail stores operate. AI-Powered Automated Retail Stores are
the next revolution in physical retail. Consumers are facing fully automated technology in these retail stores.
Therefore, it is necessary to scrutinize the antecedents of consumers’ intention to shop at AI-Powered Automated
Retail Stores. This study delves into this area to find the predictors of consumers’ intention to shop at AI-Powered
Automated Retail Stores. It extends the technology readiness and acceptance model by the addition of AI contextspecific
constructs such as Perceived Enjoyment, Customization and Interactivity from the present literature. The
proposed model is tested by surveying 1250 consumers & the data is analyzed using the PLS-SEM technique and
empirically validated. The outcome of the study reveals that Innovativeness and Optimism of consumers affect
the perceived ease and perceived usefulness. Insecurity negatively affects the perceived usefulness of AI-powered
automated retail stores. Perceived ease of use, perceived usefulness, perceived enjoyment, customization and
interactivity are significant predictors of shopping intention of consumers in AI-powered automated stores. This
research presents insightful academic and managerial implications in the domain of retailing and technology in
retail. Keywords: TRAM | PLS-SEM | Perceived enjoyment | Customization | Interactivity | Artificial intelligence-powered automated | retail stores |
مقاله انگلیسی |
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The integrated effect of Big Data Analytics, Lean Six Sigma and Green Manufacturing on the environmental performance of manufacturing companies: The case of North Africa
اثر یکپارچه تحلیل داده های بزرگ، تولید شش سیگما و سبز بر عملکرد زیست محیطی شرکت های تولیدی: مورد شمال آفریقا-2020 With the advent of Big Data Analytics (BDA) alongside the maturity of specific improvement approaches
such as Lean Six Sigma (LSS) and Green Manufacturing (GM), the integration of these initiatives to
achieve higher environmental performance (EP) is gathering the interest of both researchers and practitioners.
The present study builds on the resources based view of capabilities to propose and empirically
test a framework exploring whether LSS and GM mediate the relationship between BDA capabilities and
EP. A two-stage hybrid Factorial Analysis - Structural Equation Modeling is used to draw insights from
201 industry practitioners from North African companies. The findings confirm the direct influence of
BDA on EP and also identify LSS and GM as significant mediating variables that act as a catalyst to boost
indirect impacts of BDA on EP. This study can help researchers and practitioners to fully understand and
benefit from BDA capabilities and improvement initiatives such as LSS and GM while managing environmental
issues. The study discusses theoretical and managerial implications for enhancing the environmental
performance of the manufacturing organizations. Keywords: Environmental performance | Big data analytics | Lean Six Sigma | Green Manufacturing | Structural equation modeling |
مقاله انگلیسی |
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یادگیری عمیق در تجزیه و تحلیل کسبوکار و تحقیقات عملیاتی: مدلها، کاربردها و مفاهیم مدیریتی
سال انتشار: 2020 - تعداد صفحات فایل pdf انگلیسی: 14 - تعداد صفحات فایل doc فارسی: 55 تجزیه و تحلیل کسب و کار به روش ها و شیوه هایی اشاره دارد که از طریق داده ها برای افراد، شرکت ها و سازمان ها ارزش ایجاد می کند. این زمینه در حال حاضر به دلیل ظهور یادگیری عمیق، یک تغییر اساسی را تجربه میکند: شبکههای عصبی عمیق در مقایسه با مدلهای یادگیری ماشین سنتی، نوید بهبود عملکرد پیشبینی را میدهند. با این حال، تحقیقات ما در بدنه ادبیات موجود، کمیابی آثار تحقیقاتی با استفاده از یادگیری عمیق در رشته ما را نشان می دهد. بر این اساس، اهداف این مقاله مروری به شرح زیر است: (1) ما تحقیقات در مورد یادگیری عمیق برای تجزیه و تحلیل کسب و کار را از نقطه نظر عملیاتی مرور می کنیم. (2) ما انگیزه می دهیم که چرا محققان و متخصصان تجزیه و تحلیل کسب و کار باید از شبکه های عصبی عمیق استفاده کنند و موارد استفاده بالقوه، الزامات ضروری و مزایا را بررسی کنند. (3) ما ارزش افزوده تحقیقات عملیات را در مطالعات موردی مختلف با دادههای واقعی از شرکتهای کارآفرینی بررسی میکنیم. همه چنین مواردی بهبودهایی را در عملکرد عملیاتی نسبت به یادگیری ماشینهای سنتی نشان میدهند و در نتیجه سود مستقیم ارزش را نشان میدهند. (4) ما رهنمودها و مفاهیمی را برای محققان، مدیران و دست اندرکاران در تحقیقات عملیاتی ارائه می دهیم که می خواهند قابلیت های خود را برای تجزیه و تحلیل تجاری با توجه به یادگیری عمیق ارتقا دهند. (5) آزمایشهای محاسباتی ما نشان میدهد که معماریهای پیشفرض و خارج از چارچوب اغلب کمتر از حد مطلوب هستند و بنابراین ارزش معماریهای را با پیشنهاد یک شبکه عمیق تعبیهشده جدید برجسته میکنند.
کلید واژه ها: تجزیه و تحلیل | یادگیری عمیق | شبکه های عصبی عمیق | مفاهیم مدیریتی | دستور کار تحقیق |
مقاله ترجمه شده |