Actualizing big data analytics for smart cities: A cascading affordance study

Zeng, Delin; Tim, Yenni; Yu, Jiaxin; Liu, Wenyuan

doi:10.1016/j.ijinfomgt.2020.102156

Cited by 41 publications

(31 citation statements)

References 47 publications

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“…More recently, the research stream revolving around smart tourism destinations and smart cities has underscored the importance of Big Data and analytics to effectively manage and market tourism destinations and to inform operations, services and innovation processes, at the destination level (e.g., Bakıcı et al, 2013;Batty, 2013;Becken et al, 2019;Gajdošík, 2019;Shao et al, 2017;Wise & Heidari, 2019;Xiang et al, 2015;Zeng et al, 2020). "Smart tourism" has been described as "a distinct step in the evolution of ICT in tourism in that the physical and governance dimensions of tourism are entering the digital playing field, new levels of intelligence are achieved in tourism systems" (Gretzel et al, 2015: 180) as the ways in which tourism experiences are created, consumed and shared are different.…”

Section: Big Data and Big Data Analytics For Destination Management And Innovation And Smart Tourism Destinationsmentioning

confidence: 99%

The competitive productivity (CP) of tourism destinations: an integrative conceptual framework and a reflection on big data and analytics

Mariani

Bresciani

Dagnino

2021

IJCHM

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Purpose The purpose of this study is twofold. First, this study elaborates an integrative conceptual framework of tourism destination competitive productivity (TDCP) by blending established destination competitiveness frameworks, the competitive productivity (CP) framework and studies pertaining to big data and big data analytics (BDA) within destination management information systems and smart tourism destinations. Second, this study examines the drivers of TDCP in the context of the ongoing 4th industrial revolution by conceptualizing the destination business intelligence unit (DBIU) as a platform able to create sustained destination business intelligence under the guise of BDA, useful to support destination managers to achieve the tourism destination’s economic objectives. Design/methodology/approach In this work, the authors leverage both extant literature (under the guise of research on CP, tourism destination competitiveness [TDC] and destination management information systems) and empirical work (in the form of interviews and field work involving destination managers and chief executive officers of destination management organizations and convention bureaus, as well as secondary data) to elaborate, develop and present an integrative conceptual framework of TDCP. Findings The integrative conceptual framework of TDCP elaborated has been found helpful by a number of destination managers trying to understand how to effectively and efficiently manage and market a tourism destination in today’s fast-paced, digital and hypercompetitive environment. While DBIUs are at different stages of implementation, often as part of broader smart destination initiatives, it appears that they are increasingly fulfilling the purpose of creating sustained destination business intelligence by means of BDA to help tourism destinations achieve their economic goals. Research limitations/implications This work bears several practical implications for tourism policymakers, destination managers and marketers, technology developers, as well as tourism and hospitality firms and practitioners. Tourism policymakers could embed TDCP into tourism and economic policies, and destination managers and marketers might build and make use of platforms such as the proposed DBIU. Technology developers need to understand that designing destination management information systems in general and more specifically DBIUs requires an in-depth analysis of the stakeholders that are going to contribute, share, control and use BDA. Originality/value To the best of the authors’ knowledge, this study constitutes the first attempt to integrate the CP, TDC and destination management information systems research streams to elaborate an integrative conceptual framework of TDCP. Second, the authors contribute to the Industry 4.0 research stream by examining the drivers of tourism destination CP in the context of the ongoing 4th industrial revolution. Third, the authors contribute to the destination management information systems research stream by introducing and conceptualizing the DBIU and the related sustained destination business intelligence.

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Section: Big Data and Big Data Analytics For Destination Management And Innovation And Smart Tourism Destinationsmentioning

confidence: 99%

The competitive productivity (CP) of tourism destinations: an integrative conceptual framework and a reflection on big data and analytics

Mariani

Bresciani

Dagnino

2021

IJCHM

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“…In (3), k z denotes a concept of medical knowledge per z-level relationships. Relationships among concepts can be expressed as G (K), G represents a knowledge graph, and K = {k} represents a set of knowledge bases.…”

Section: Relationships Within Datasets In Healthcarementioning

confidence: 99%

“…A growing number of studies show that big data has demonstrated its tremendous value and has served every aspect of human life. [1][2][3] Big data-driven algorithms and applications are capable of processing medical and health data in structured, semi-structured, and non-structured format. However, the traditional characteristics of big data, such as volume, velocity, variety, and even variability (4Vs), hinder the further use of big data.…”

Section: Introductionmentioning

confidence: 99%

A novel framework for bringing smart big data to proactive decision making in healthcare

Zhou¹,

Zhang

Chen

et al. 2021

Health Informatics J

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Big data have shown their great potential value to serve many aspects of human life. Due to complexity of the medical and healthcare big data in real life, traditional big data analysis methods are difficult to be dealt with. Therefore, a single method is unable to analyze and manage heterogeneous big data sources. To utilize data fully from the perspective of decision-making, we propose a novel framework which guides the healthcare big data to be smartly and proactively processed for decision-making without user interventions. The framework contains five stages, which are intelligent data cleaning, customized data fusion, analysis mapping, exploratory visualization analysis, and generation of decision-making reports. It also enables learning from the data and correlating them with the existing human knowledge. Subsequently, a smart big data-driven application exhibits innovative management in intelligent healthcare. The proposed framework provides the guidelines of the best practices of big data-driven analysis for intelligent healthcare according to our practical applications. The platform provides the appropriate reference for the big data-driven innovation of management in intelligent healthcare.

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“…On the other hand, more mass use of online technology can be included among the other positives. In some cases, there has also been an acceleration in the use of Big Data Analytics (BDA) to support the transformation of cities into smart destinations leading to facilitate the achievement of smart tourism goals and the contribution to sustainable tourism [15]. In the case of the Czech Republic, apart from Prague, Brno and others, Ostrava is already one of the intelligent cities, which applies smart solutions in the field of transport, water management and air protection [16].…”

Section: The Positive Impacts Of Coronavirusmentioning

confidence: 99%

The Impact of the Global Pandemic on Selected Aspects of Sustainable Tourism in the Czech Republic

Stuchlíková

Botlíková

2021

SHS Web of Conf.

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Research background: The overall impact of coronavirus has some positives and negatives on the tourism sector and thus on other downstream sectors. The stagnation of tourism will make it easier for overcrowded tourist centers, which corresponds to the goals of sustainable tourism. On the other hand, negatives can be attributed to it. The Covid -19 epidemic caused the decline in business activities in tourism to almost zero, not only in the Czech Republic, but in the entire global area. If we consider with the intention that a large part of tourism enterprises is dependent on foreign clients, then the steps necessary to prevent the further spread of the epidemic were fatal for many enterprises and contribute to rising unemployment, reducing public budget revenues, etc. It is clear that the functioning of tourism will not return to pre-coronavirus and will be gradual. Businesses will need to adapt their services and find new ways to distribute them. Purpose of the article: The aim of the paper is to map the effect of coronavirus on selected aspects of sustainable tourism in the Czech Republic. Methods: We used primary data obtained from controlled interviews with the operators of the monitored facilities and secondary data (EUROSTAT, CSO). Findings & Value added: The paper includes models of the impact of coronavirus in the field of tourism, focusing mainly on accommodation and catering establishments.

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Actualizing big data analytics for smart cities: A cascading affordance study

Cited by 41 publications

References 47 publications

The competitive productivity (CP) of tourism destinations: an integrative conceptual framework and a reflection on big data and analytics

The competitive productivity (CP) of tourism destinations: an integrative conceptual framework and a reflection on big data and analytics

A novel framework for bringing smart big data to proactive decision making in healthcare

The Impact of the Global Pandemic on Selected Aspects of Sustainable Tourism in the Czech Republic

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