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|
Leading successful government-academia collaborations using FLOSS and agile values
پیشرو همکاریهای موفق دولت و آکادمی با استفاده از FLOSS و مقادیر چابک-2020
Government and academia share concerns for efficiently and effectively servicing societal demands, which includes the development of e-government software. Government-academia partnerships can be a valu- able approach for improving productivity in achieving these goals. However, governmental and academic institutions tend to have very different agendas and organizational and managerial structures, which can hinder the success of such collaborative projects. In order to identify effective approaches to overcome collaboration barriers, we systematically studied the case of the Brazilian Public Software portal project, a 30-month government-academia collaboration that, using Free/Libre/Open Source Software practices and agile methods for project management, developed an unprecedented platform in the context of the Brazil- ian government. We gathered information from experience reports and data collection from repositories and interviews to derive a collection of practices that contributed to the success of the collaboration. In this paper, we describe how the data analysis led to the identification of a set of three high-level decisions supported by the adoption of nine best practices that improved the project performance and enabled professional training of the whole team.
Keywords: Project management | Government-Academia collaboration | Free software | Open source software | Agile methodologies | e-Government
Designing with differences, cross-disciplinary collaboration in transport infrastructure planning and design
طراحی با تفاوت ها ، همکاری های متقابل انضباطی در برنامه ریزی و طراحی زیرساخت های حمل و نقل-2020
The study explores enablers and barriers of collaborative planning and design work in transport infrastructure planning projects, drawing upon five cases of projects in Sweden. The study apply a set of theoretical lenses complied of previous research focusing professional knowledge and co-production in planning and design practices, and research revolving around the concept of boundary objects in studies of collaborative work. The study provides insights into the mechanisms of practitioners learning across professional boundaries: what they learn fromeach other, howthey learn, and how the learning facilitates collaborative work. The results show that disciplinary barriers can be bridged through both individual efforts and project management strategies. This study shed light a set of enablers on individual level including; 1) a capacity to change focus between solving tasks within the remit of ones own discipline and jointly solving tasks together with professionals representing other disciplines; 2) curiosity and interest other professional perspectives; 3) willingness to learn from other professionals; and 4) motivation to engage in cross-disciplinary design processes. Project management is proposed to enable collaboration by; 1) opening up discussions about reasons and motives for collaborative work; 2) opening up discussions about strategies for collaborative processes; 3) promoting and facilitating learning processes among project participants, 4) coordinating meetings and activities for collaboration, and 5) facilitating deliberative dialogues at project meetings in which different types of knowledge can be put forth and interrelated.
Keywords: Transport infrastructure planning | Cross-disciplinary collaboration | Landscape architects | Engineers | Boundary objects | Professional knowledge
DOES TRIPLE HELIX COLLABORATION MATTER FOR THE EARLY INTERNATIONALISATION OF TECHNOLOGY-BASED FIRMS IN EMERGING ECONOMIES?
آیا همکاری سه گانه هلیکس برای بین المللی سازی اولیه شرکتهای مبتنی بر فن آوری در اقتصادهای در حال رشد اهمیت دارد؟-2020
Firms’ early internationalisation (EI) is a complex process derived from uncertain market conditions, entrepre- neurial vision, and strategic entry decisions. Academic debates still require deepening and broadening the dis- cussion on early internationalisation of new technology-based firms (NTBFs). This study proposes a framework to analyse how NTBFs are adopting collaborative networks with the triple helix actors (government, university, and industry) to implement an EI strategy in emerging economies. Our findings show that the lack of specialised knowledge and resources stimulates collaboration with multiple triple helix agents to ensure the early entry strategy into international markets. We state the relevant implications and propositions concerning the inter- nationalisation of NTBFs and the relationship with triple helix stakeholders.SPECIAL DEDICATIONIn memory of Juan Arriaga, Department of Innovation and Entrepre- neurship, EGADE Business School
Keywords: NTBFs | International entrepreneurship | Triple helix | Early internationalisation | Emerging economies
Facilitating collaboration in forest management: Assessing the benefits of collaborative policy innovations
تسهیل همکاری در مدیریت جنگل: ارزیابی مزایای نوآوری های سیاست مشارکتی-2020
Collaborative governance and landscape approaches have become a more prevalent in public land management in the United States in the face of increasing ecological and societal complexity and decreasing government resources and capacity. In this era of devolution and social-ecological change, there is a growing need for policy approaches that facilitate partnerships and participatory approaches to land management. One unique policy that emphasizes collaboration and large-landscape restoration on US federal forestlands is the Collaborative Forest Landscape Restoration Program (CFLRP), established in 2009 to accelerate the pace and scale of forest restoration. The policy included novel characteristics such as a decade-long commitment to landscapes and formal requirements for collaboration. This program presented an opportunity to assess how this policy affected collaboration and the factors that led to differential policy implementation. We conducted 89 interviews across all 23 CFLRP projects with internal agency staff and external collaborators on each project. We found that the CFLRP generated a variety of benefits related to collaboration, including increased trust and stronger relationships, increased collaborative partner influence, decreased litigation and conflict, and increased capacity to accomplish work; however, there were also challenges associated with the program, including thetime-intensive nature of collaboration and the lack of industry or contractors. Various local factors affected collaborative outcomes under the policy, including staff turnover and capacity, local leadership, and collaborative history. Successful collaborative outcomes were widespread under the CFLRP, and from this, we draw implications for the broader environmental governance literature about the policy characteristics that facilitate collaboration and the other institutional variables that may require attention in this context.
Keywords: Collaborative governance | Community-based forestry | Adaptive governance | Ecological | Restoration | Policy design
Coordinated behavior of cooperative agents using deep reinforcement learning
رفتار هماهنگ عوامل تعاونی با استفاده از یادگیری تقویتی عمیق-2020
In this work, we focus on an environment where multiple agents with complementary capabilities co- operate to generate non-conflicting joint actions that achieve a specific target. The central problem ad- dressed is how several agents can collectively learn to coordinate their actions such that they complete a given task together without conflicts. However, sequential decision-making under uncertainty is one of the most challenging issues for intelligent cooperative systems. To address this, we propose a multi-agent concurrent framework where agents learn coordinated behaviors in order to divide their areas of respon- sibility. The proposed framework is an extension of some recent deep reinforcement learning algorithms such as DQN, double DQN, and dueling network architectures. Then, we investigate how the learned be- haviors change according to the dynamics of the environment, reward scheme, and network structures. Next, we show how agents behave and choose their actions such that the resulting joint actions are op- timal. We finally show that our method can lead to stable solutions in our specific environment.
Keywords: Deep reinforcement learning | Multi-agent systems | Cooperation | Coordination
Digital Twin-enabled Collaborative Data Management for Metal Additive Manufacturing Systems
مدیریت داده های همکاری مشترک زوج دیجیتال برای سیستم های تولید مواد افزودنی فلز-2020
Metal Additive Manufacturing (AM) has been attracting a continuously increasing attention due to its great advantages compared to traditional subtractive manufacturing in terms of higher design flexibility, shorter development time, lower tooling cost, and fewer production wastes. However, the lack of process robustness, stability and repeatability caused by the unsolved complex relationships between material properties, product design, process parameters, process signatures, post AM processes and product quality has significantly impeded its broad acceptance in the industry. To facilitate efficient implementation of advanced data analytics in metal AM, which would support the development of intelligent process monitoring, control and optimisation, this paper proposes a novel Digital Twin (DT)-enabled collaborative data management framework for metal AM systems, where a Cloud DT communicates with distributed Edge DTs in different product lifecycle stages. A metal AM product data model that contains a comprehensive list of specific product lifecycle data is developed to support the collaborative data management. The feasibility and advantages of the proposed framework are validated through the practical implementation in a distributed metal AM system developed in the project MANUELA. A representative application scenario of cloud-based and deep learning-enabled metal AM layer defect analysis is also presented. The proposed DT-enabled collaborative data management has shown great potential in enhancing fundamental understanding of metal AM processes, developing simulation and prediction models, reducing development times and costs, and improving product quality and production efficiency.
Keywords: Metal Additive Manufacturing | Digital Twin | data management | data model | machine learning | product lifecycle management
Coopetition and COVID-19: Collaborative business-to-business marketing strategies in a pandemic crisis
Coopetition و COVID-19: استراتژی های مشارکتی بازاریابی از کسب و کار در یک بحران همه گیر-2020
Although coopetition (simultaneous cooperation and competition) should positively affect company perfor- mance, it is unclear how implementation of these business-to-business marketing strategies can take place during large-scale emergencies. Therefore, guided by resource-based theory and the relational view, this investigation examines how organisations have used coopetition to cope with the novel Coronavirus (COVID-19) pandemic. Key examples include retailers sharing information about stock levels, pharmaceutical organisations working together to develop a vaccine, technological giants collaborating for the greater good, and charities forming alliances for a joint cause. This paper strengthens the extant literature by highlighting the heterogeneity of coopetition strategies that firms can use within a global crisis. Practitioners must balance the risks and rewards of coopetition activities. In turn, they should decide whether to continue to cooperate with their competitors once the pandemic has ended, or resume operating under individualistic business models. This article ends with some future research directions.
Keywords: Coopetition | Coronavirus | COVID-19 | Business-to-business marketing
The application of artificial intelligence in police interrogations: An analysis addressing the proposed effect AI has on racial and gender bias, cooperation, and false confessions
کاربرد هوش مصنوعی در بازجویی های پلیس: تحلیلی در مورد تأثیر پیشنهادی هوش مصنوعی بر تعصب نژادی و جنسیتی ، همکاری و اعترافات دروغین-2020
Research presented in this study examines the potentiality of artificial intelligence as an interrogator within a police interrogation to promote a non-biased environment in an effort to mitigate the ongoing racial and gender divide in statistics regarding false confessions. Ideally, artificial intelligence supplementation may help promote the elicitation of non-coerced, voluntary confessions. This study suggests that the racial and gender bias influencing false confessions may be due to the two fold bias occurring within the interrogator-to-suspect dynamic, referenced in this study as “the Bias-Uncooperative Loop.” It argues that applying artificial intelligence within the interrogation room may minimize the two fold bias occurring in the dynamic. It suggests the potential for cooperation between the two parties can be conditioned by programmable similarity; whereby artificial intelligence can mimic the racial, ethnic and/or cultural similarities of the suspect in question. This is reflected in research in different arenas (not inclusive to interrogations) to have an effect on enhanced comfortability and cooperation with AI. This paper assumes similar results within interrogations.
Keywords: Artificial intelligence | Bias | Policing | Interrogations | Discrimination | Crime
An intelligent semantic system for real-time demand response management of a thermal grid
یک سیستم معنایی هوشمند برای مدیریت پاسخ به تقاضای زمان واقعی یک شبکه حرارتی-2020
“Demand Response” energy management of thermal grids requires consideration of a wide range of factors at building and district level, supported by continuously calibrated simulation models that reflect real operation conditions. Moreover, cross-domain data interoperability between concepts used by the numerous hardware and software is essential, in terms of Terminology, Metadata, Meaning and Logic. This paper leverages domain ontology to map and align the semantic resources that underpin building and district energy management, with a focus on the optimization of a thermal grid informed by real-time energy demand. The intelligence of the system is derived from simulation-based optimization, informed by calibrated thermal models that predict the network’s energy demand to inform (near) real-time generation. The paper demonstrates that the use of semantics helps alleviate the endemic energy performance gap, as validated in a real district heating network where 36% reduction on operation cost and 43% reduction on CO2 emission were observed compared to baseline operational data.
Keywords: Thermal grid | Demand response | Energy optimization | Operation cost | Data interoperability | Semantic ontology