標(biāo)題: Titlebook: Big Data and Innovation in Tourism, Travel, and Hospitality; Managerial Approache Marianna Sigala,Roya Rahimi,Mike Thelwall Book 2019 Sprin [打印本頁(yè)] 作者: 習(xí)慣 時(shí)間: 2025-3-21 16:50
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作者: 不適 時(shí)間: 2025-3-21 22:27
Introduction to Diophantine Approximationsation online. Smart technology that exploits IoT data offers new opportunities for the travel and hospitality industry. The IoT enables easy access and interaction with a wide variety of information for contexts such as transportation, attractions, tours, shopping and hotels. IoT big data tourism ap作者: 蚊子 時(shí)間: 2025-3-22 03:41 作者: AMBI 時(shí)間: 2025-3-22 04:56
Introduction to ARENA Software, access more data than they know how to handle and translate into value. However, although the literature has started investigating the use of big data for generating economic value, there has been a lack of research into the use of big data for delivering social value. To address these gaps, this c作者: 我們的面粉 時(shí)間: 2025-3-22 11:21
Christos G. Cassandras,Stéphane Lafortunendustry. The tourism industry faces several challenges when using big data and volunteered geographic information (VGI) to develop new services. Managers need new capabilities to exploit this newly available information and to understand the possibilities that it has created. To give an overview of 作者: Promotion 時(shí)間: 2025-3-22 16:43 作者: conquer 時(shí)間: 2025-3-22 20:01
Introduction to Discrete-Event Simulation,s (LBSN). A major problem is the lack of knowledge in respect to the visitors’ views about a destination, as well as the fact that the visitors’ behavior needs and preferences are not visible. Many enterprises and local authorities are still using traditional methods for acquiring knowledge to make 作者: CANT 時(shí)間: 2025-3-22 21:42
Introduction to Discrete Event Systems proposals for spa services. A panel of domain experts annotated these idea descriptions with a score for their innovativeness that serves as ground truth for machine learning experiments. Thus, the contribution lies in the application of topic modeling techniques to free-text idea descriptions in o作者: Jingoism 時(shí)間: 2025-3-23 02:19 作者: inspiration 時(shí)間: 2025-3-23 08:42 作者: 外向者 時(shí)間: 2025-3-23 11:36 作者: probate 時(shí)間: 2025-3-23 17:42 作者: 開(kāi)始發(fā)作 時(shí)間: 2025-3-23 19:31 作者: Introduction 時(shí)間: 2025-3-23 22:20 作者: 賭博 時(shí)間: 2025-3-24 04:43 作者: ethereal 時(shí)間: 2025-3-24 07:36
Marianna Sigala,Roya Rahimi,Mike ThelwallUses the tourism sector as a context for demonstrating the practical implications and applications of big data exploitation.Provides a process framework consolidating all the issues that firms and res作者: Magnitude 時(shí)間: 2025-3-24 11:23 作者: 史前 時(shí)間: 2025-3-24 18:18
Introduction to Diophantine Approximationsarity of Spanish, British and German foreigners by tourism in Portugal and country specific touristic products. The obtained results contribute definitively to support and help Destination Management Organizations (DMO) enabling timely decisions.作者: Arb853 時(shí)間: 2025-3-24 20:29 作者: 債務(wù) 時(shí)間: 2025-3-25 01:56
Introduction to Discrete-Event Simulation,on of data derived from LBSNs. This provides knowledge of visitor behaviors, impressions and preferences for tourist destinations. A case study of Crete in Greece is included, based upon visitors’ posts and reviews, nationality, photos, place rankings, and engagement.作者: ATOPY 時(shí)間: 2025-3-25 07:07
Introduction to Queueing Theory,web monitoring data were available at Visit Flanders. This query was reused in 2016 and flight data was also monitored. More intensive monitoring was needed then because of the greater March 2016 tourism threat. Big data helped Visit Flanders to react separately to individual markets.作者: Axon895 時(shí)間: 2025-3-25 10:46
Composite Indicators for Measuring the Online Search Interest by a Tourist Destination,arity of Spanish, British and German foreigners by tourism in Portugal and country specific touristic products. The obtained results contribute definitively to support and help Destination Management Organizations (DMO) enabling timely decisions.作者: 誤傳 時(shí)間: 2025-3-25 13:49 作者: 斗志 時(shí)間: 2025-3-25 16:30 作者: Provenance 時(shí)間: 2025-3-25 22:51
Customer Data and Crisis Monitoring in Flanders and Brussels,web monitoring data were available at Visit Flanders. This query was reused in 2016 and flight data was also monitored. More intensive monitoring was needed then because of the greater March 2016 tourism threat. Big data helped Visit Flanders to react separately to individual markets.作者: 良心 時(shí)間: 2025-3-26 02:45
Book 2019ovation in tourism. It also provides a consolidated framework and roadmap summarising the major issues that both researchers and practitioners have to address for effective big data innovation..The book proposes a process-based model to identify and implement big data innovation strategies in touris作者: incite 時(shí)間: 2025-3-26 05:07 作者: NEX 時(shí)間: 2025-3-26 10:59
Christos G. Cassandras,Stéphane Lafortune as differences between genders or venues in the aspects of destinations that are liked. This chapter reviews the main sentiment analysis approaches with a focus on practical descriptions of how the methods work and how they can be applied. The chapter also illustrates the value of sentiment analysis for tourism research.作者: itinerary 時(shí)間: 2025-3-26 16:25 作者: 駕駛 時(shí)間: 2025-3-26 20:23 作者: Comprise 時(shí)間: 2025-3-26 23:29 作者: 花束 時(shí)間: 2025-3-27 03:44 作者: 補(bǔ)角 時(shí)間: 2025-3-27 05:59
Book 2019m. This process framework consists of four major parts: 1) inputs required for big data innovation; 2) processes required to implement big data innovation; 3) outcomes of big data innovation; and 4) contextual factors influencing big data exploitation and advances in big data exploitation for business innovation..作者: Irksome 時(shí)間: 2025-3-27 10:33 作者: Obstacle 時(shí)間: 2025-3-27 16:11
Introduction to Discrete Event Systemsopic modeling can outperform the ZeroR baseline as well as traditional survey scales for lead user identification and therefore constitute a first step towards exploring this technique for innovation research.作者: collateral 時(shí)間: 2025-3-27 18:24 作者: leniency 時(shí)間: 2025-3-28 00:11 作者: 一再煩擾 時(shí)間: 2025-3-28 05:15
ss framework consolidating all the issues that firms and resThis book brings together multi-disciplinary research and practical evidence about the role and exploitation of big data in driving and supporting innovation in tourism. It also provides a consolidated framework and roadmap summarising the 作者: AXIOM 時(shí)間: 2025-3-28 08:58 作者: MUTE 時(shí)間: 2025-3-28 10:59
Big Data and Innovation in Tourism, Travel, and Hospitality978-981-13-6339-9作者: limber 時(shí)間: 2025-3-28 14:59 作者: 津貼 時(shí)間: 2025-3-28 18:58
Simulation Software and Visual Basic,ation about what their customers do during a stay in a destination, so that these companies can offer a more customized service. Finally, OTAs should consider big data as a mindset which affects the whole company and its organizational structure, and not only as information and its associated techno作者: occurrence 時(shí)間: 2025-3-29 00:48
Christos G. Cassandras,Stéphane Lafortunethrough delineating and detailing the analytical frameworks to support an advanced B2C interface, based on various internal databases and external data sources. The role of stakeholders and necessary resources are explained, and the full potential of big data in tourism and hospitality is revealed.作者: Cardioplegia 時(shí)間: 2025-3-29 03:09 作者: sorbitol 時(shí)間: 2025-3-29 10:33 作者: Conduit 時(shí)間: 2025-3-29 13:34 作者: 輕快來(lái)事 時(shí)間: 2025-3-29 17:36 作者: Muffle 時(shí)間: 2025-3-29 22:30
Strengthening Relational Ties and Building Loyalty Through Relational Innovation and Technology: Evence to suggest a significant positive impact of relational innovation on guest perceptions of hotel technology and strength of relational ties. Moreover, information and communication technologies exert a positive impact on overall brand equity which, in turn, has a positive impact on relational ti作者: CRUMB 時(shí)間: 2025-3-30 01:24
Big Data and Its Supporting Elements: Implications for Tourism and Hospitality Marketing,ties with the help of different algorithmic solutions. Thus, this chapter aims to debate how big data, artificial intelligence and IoT are likely to reshape the traditional structure of tourism and hospitality marketing in the future and introduces new approaches as the key elements in maintaining c作者: 粗糙濫制 時(shí)間: 2025-3-30 05:52
