scholarly journals Big data and analytics in tourism and hospitality: opportunities and risks

2020 ◽  
Vol 6 (3) ◽  
pp. 257-262 ◽  
Author(s):  
Anca Yallop ◽  
Hugues Seraphin
Keyword(s):  
Big Data ◽  
Data Management ◽  
Data Governance ◽  
Privacy And Security ◽  
Content Type ◽  
Data Ethics ◽  
Technological Advances ◽  
International Tourist ◽  
Tourism And Hospitality Industry ◽  
Tourism And Hospitality

Purpose The purpose of this paper is to examine and provide insights into one of the most influential technologies impacting the tourism and hospitality industry over the next five years, i.e. big data and analytics. It reflects on both opportunities and risks that such technological advances create for both consumers and tourism organisations, highlighting the importance of data governance and processes for effective and ethical data management in both tourism and hospitality. Design/methodology/approach This paper is based on a review of academic and industry literature and access to trends data and information from a series of academic and industry databases and reports to examine how big data and analytics shape the future of the industry and the associated risks and opportunities. Findings This paper identifies and examines key opportunities and risks posed by the rising technological trend of big data and analytics in tourism and hospitality. While big data is generally regarded as beneficial to tourism and hospitality organisations, there are extensively held ethical, privacy and security concerns about it. Therefore, the paper is making the case for more research on data governance and data ethics in tourism and hospitality and posits that to successfully use data for competitive advantage, tourism and hospitality organisations need to solely expand compliance-based data governance frameworks to frameworks that include more effective privacy and ethics data solutions. Originality/value This paper provides useful insights into the use of big data and analytics for both researchers and practitioners and offers new perspectives on the debate on data governance and ethical data management in both tourism and hospitality. Because forecasts from the UNWTO indicate a significant increase in international tourist arrivals (1.8 billion tourist arrivals by 2030), the ways tourism and hospitality organisations manage customers’ data become important.

The digital traveller: implications for data ethics and data governance in tourism and hospitality

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Anca C. Yallop ◽  
Oana A. Gică ◽  
Ovidiu I. Moisescu ◽  
Monica M. Coroș ◽  
Hugues Séraphin
Keyword(s):  
Big Data ◽  
The Body ◽  
Data Governance ◽  
Privacy And Security ◽  
Content Type ◽  
Data Ethics ◽  
Data Framework ◽  
Social License ◽  
Governance Practices ◽  
Tourism And Hospitality

Purpose Big data and analytics are being increasingly used by tourism and hospitality organisations (THOs) to provide insights and to inform critical business decisions. Particularly in times of crisis and uncertainty data analytics supports THOs to acquire the knowledge needed to ensure business continuity and the rebuild of tourism and hospitality sectors. Despite being recognised as an important source of value creation, big data and digital technologies raise ethical, privacy and security concerns. This paper aims to suggest a framework for ethical data management in tourism and hospitality designed to facilitate and promote effective data governance practices. Design/methodology/approach The paper adopts an organisational and stakeholder perspective through a scoping review of the literature to provide an overview of an under-researched topic and to guide further research in data ethics and data governance. Findings The proposed framework integrates an ethical-based approach which expands beyond mere compliance with privacy and protection laws, to include other critical facets regarding privacy and ethics, an equitable exchange of travellers’ data and THOs ability to demonstrate a social license to operate by building trusting relationships with stakeholders. Originality/value This study represents one of the first studies to consider the development of an ethical data framework for THOs, as a platform for further refinements in future conceptual and empirical research of such data governance frameworks. It contributes to the advancement of the body of knowledge in data ethics and data governance in tourism and hospitality and other industries and it is also beneficial to practitioners, as organisations may use it as a guide in data governance practices.

Mastering Big Data in the Digital Age

2016 ◽  
pp. 104-129 ◽  
Author(s):  
Kijpokin Kasemsap
Keyword(s):  
Big Data ◽  
Organizational Performance ◽  
Hospitality Industry ◽  
Big Data Analytics ◽  
Digital Age ◽  
Sustainable Competitive Advantage ◽  
Privacy And Security ◽  
Big Data Applications ◽  
Tourism And Hospitality Industry ◽  
Tourism And Hospitality

This chapter explains the overview of big data; the volume, velocity, variety, veracity, and variability of big data; the privacy and security of big data applications; big data and multimedia utilization; the concept of MapReduce; the concept of Hadoop; big data and data mining; big data and cloud computing; the applications of big data in health care industry; the applications of big data analytics in tourism and hospitality industry; and the challenges and implications of big data in the digital age. Big data is the large volumes of data of high velocity and their variety requiring information processing to add value to the information in the future. The chapter argues that applying big data has the potential to increase organizational performance and gain sustainable competitive advantage in the digital age.

A structural equation model for big data adoption in the healthcare supply chain

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Dindayal Agrawal ◽  
Jitender Madaan
Keyword(s):  
Factor Analysis ◽  
Big Data ◽  
Supply Chain ◽  
Latent Variables ◽  
Structural Equation ◽  
Equation Model ◽  
Equation Modeling ◽  
Data Governance ◽  
Social Perspective ◽  
Content Type

PurposeThe purpose of this study is to examine the barriers to the implementation of big data (BD) in the healthcare supply chain (HSC).Design/methodology/approachFirst, the barriers concerning BD adoption in the HSC were found by conducting a detailed literature survey and with the expert's opinion. Then the exploratory factor analysis (EFA) was employed to categorize the barriers. The obtained results are verified using the confirmatory factor analysis (CFA). Structural equation modeling (SEM) analysis gives the path diagram representing the interrelationship between latent variables and observed variables.FindingsThe segregation of 13 barriers into three categories, namely “data governance perspective,” “technological and expertise perspective,” and “organizational and social perspective,” is performed using EFA. Three hypotheses are tested, and all are accepted. It can be concluded that the “data governance perspective” is positively related to “technological and expertise perspective” and “organizational and social perspective” factors. Also, the “technological and expertise perspective” is positively related to “organizational and social perspective.”Research limitations/implicationsIn literature, very few studies have been performed on finding the barriers to BD adoption in the HSC. The systematic methodology and statistical verification applied in this study empowers the healthcare organizations and policymakers in further decision-making.Originality/valueThis paper is first of its kind to adopt an approach to classify barriers to BD implementation in the HSC into three distinct perspectives.

No business as usual: a case for data ethics and data governance in the age of coronavirus

2020 ◽  
Vol 44 (6) ◽  
pp. 1217-1221
Author(s):  
Anca C Yallop ◽  
Omid Aliasghar
Keyword(s):  
Information And Communication Technologies ◽  
Data Privacy ◽  
Dynamic Capabilities ◽  
New Technologies ◽  
Business Practices ◽  
Data Governance ◽  
Content Type ◽  
Ethical Implications ◽  
Data Ethics ◽  
Business As Usual

PurposeThe purpose of this commentary is to reflect on the transformative changes organisations experience, in the form of increased use of emergent information and communication technologies (ICTs), as a significant factor in enabling the continuation of normal business practices during the COVID-19 pandemic, and subsequent key ethical considerations in the use of new technology by organisations.Design/methodology/approachThis commentary adopts a reflective approach and is based on a review of theories on diffusion of innovation, dynamic capabilities and data ethics and governance, as well as up-to-date business reports to reflect on the ethical implications of new technologies for organisations.FindingsOrganisations from different industries and sectors around the world have experienced major disruptive changes because of the COVID-19 pandemic. Adoption and integration of new ICTs occurred at an accelerated pace in a collective effort to maintain “business as usual”. The use of emergent technologies is not without risks. The commentary argues that, in times of crisis, it is vital that organisations address the growing concerns around privacy and security of personal data by designing effective data governance frameworks that go beyond a mere compliance with existing policies and prevailing data privacy and protection laws to ensure data security and protection for all stakeholders.Originality/valueThis commentary is making the case for more considered approaches to data governance and data ethics in business following the unprecedented challenges posed by the recent COVID-19 pandemic and suggests possible ways of moving forward from an ethical perspective.

scholarly journals Anomaly data management and big data analytics: an application on disability datasets

2018 ◽  
Vol 2 (2) ◽  
pp. 164-176
Author(s):  
Zhiwen Pan ◽  
Wen Ji ◽  
Yiqiang Chen ◽  
Lianjun Dai ◽  
Jun Zhang
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Data Management ◽  
Big Data Analytics ◽  
Quality Data ◽  
Content Type ◽  
Data Mining Algorithms ◽  
Management Scheme ◽  
The Disabled ◽  
Mining Scheme

Purpose The disability datasets are the datasets that contain the information of disabled populations. By analyzing these datasets, professionals who work with disabled populations can have a better understanding of the inherent characteristics of the disabled populations, so that working plans and policies, which can effectively help the disabled populations, can be made accordingly. Design/methodology/approach In this paper, the authors proposed a big data management and analytic approach for disability datasets. Findings By using a set of data mining algorithms, the proposed approach can provide the following services. The data management scheme in the approach can improve the quality of disability data by estimating miss attribute values and detecting anomaly and low-quality data instances. The data mining scheme in the approach can explore useful patterns which reflect the correlation, association and interactional between the disability data attributes. Experiments based on real-world dataset are conducted at the end to prove the effectiveness of the approach. Originality/value The proposed approach can enable data-driven decision-making for professionals who work with disabled populations.

Unraveling the fuzzy predictors of stress at work

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sanaz Vatankhah ◽  
Mona Bouzari ◽  
Homayoun Pasha Safavi
Keyword(s):  
Hospitality Industry ◽  
Current Knowledge ◽  
Fuzzy Theory ◽  
Research Attention ◽  
Content Type ◽  
Workplace Stressors ◽  
Mental Demand ◽  
Tourism And Hospitality Industry ◽  
Stress At Work ◽  
Tourism And Hospitality

Purpose This study aims to identify and rank the significant determinants of stress among tourism and hospitality employees. Design/methodology/approach A mixed-method approach is used to identify and rank workplace stressors. Particularly, the synthesis of relative literature and interview with the panel of experts resulted in the preliminary identification of workplace stressors. Underpinned by fuzzy theory, in addition, the fuzzy analytical hierarchy process is used to rank identified criteria and relative sub-criteria. Findings Results of three-wave investigation lead to an index comprising key components and weighted ranking of workplace stressors in the tourism and hospitality industry with job characteristics as the most important criteria and mental demand as the most salient sub-criteria influencing stress at work. Research limitations/implications The pattern of findings enhances the current knowledge regarding significant workplace stressors in the tourism and hospitality industry. Practical implications Compositional framework and the weight-based ranking of identified components may act as a source of strategic solution for managers to reduce and manage stress among employees. Originality/value Workplace stressors have attracted considerable research attention, however, no general consensus yet exists among scholars and practitioners conferring to the key composition and relative importance of workplace stressors.

scholarly journals Employees’ evaluative repertoires of tourism and hospitality jobs

2019 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Anna Schneider ◽  
Corinna Treisch
Keyword(s):  
Cultural Context ◽  
Working Hours ◽  
Tourism Industry ◽  
Content Type ◽  
Job Attributes ◽  
Hierarchical Bayesian Analysis ◽  
Job Preferences ◽  
Flexible Working Hours ◽  
Tourism And Hospitality Industry ◽  
Tourism And Hospitality

Purpose This paper aims to examine employees’ evaluative repertoires of tourism and hospitality jobs and segments them based on a set of job attribute preferences. Understanding the social–cultural underpinnings of employees’ job preferences is vital if employers are to overcome the challenging task of finding and retaining talented employees in the tourism and hospitality industry. Design/methodology/approach A discrete-choice experiment with waiters, barkeepers, cooks and front-desk employees working in the Tyrolean tourism industry was conducted. Employees were categorized into distinct segments using a hierarchical Bayesian analysis and a cluster analysis. Findings Results show that flexible working hours and the ability to balance professional and private aspirations are the most important job attributes for employees. Overall, the evaluative repertoires of the “green” and “domestic (family)” conventions are most prevalent. Research limitations/implications This study contributes to literature on talent management by providing insights into employees’ evaluations of jobs and their evaluative repertoires embedded in the broader social–cultural context. Practical implications Industry representatives and employers can adapt their recruiting and retention strategies based on employees’ job preferences. Social implications Adapting job attributes according to employees’ evaluative repertoires helps to ensure the long-term sustainability of the industry workforce. Originality/value Applying the Economics of Convention (EC) perspective, combining organizational job attributes and socially embedded evaluative repertoires provides a new approach to analysing and understanding employees’ job preferences.

Big data adoption in academic libraries: a literature review

2020 ◽  
Vol 37 (4) ◽  
pp. 1-5
Author(s):  
Nove E. Variant Anna ◽  
Endang Fitriyah Mannan
Keyword(s):  
Big Data ◽  
Data Management ◽  
Academic Libraries ◽  
Data Analytics ◽  
Academic Library ◽  
Big Data Analytics ◽  
Research Data ◽  
Management Policy ◽  
Content Type ◽  
Scopus Database

Purpose The purpose of this paper is to analyse the publication of big data in the library from Scopus database by looking at the writing time period of the papers, author's country, the most frequently occurring keywords, the article theme, the journal publisher and the group of keywords in the big data article. The methodology used in this study is a quantitative approach by extracting data from Scopus database publications with the keywords “big data” and “library” in May 2019. The collected data was analysed using Voxviewer software to show the keywords or terms. The results of the study stated that articles on big data have appeared since 2012 and are increasing in number every year. The big data authors are mostly from China and America. Keywords that often appear are based on the results of terminology visualization are including, “big data”, “libraries”, “library”, “data handling”, “data mining”, “university libraries”, “digital libraries”, “academic libraries”, “big data applications” and “data management”. It can be concluded that the number of publications related to big data in the library is still small; there are still many gaps that need to be researched on the topic. The results of the research can be used by libraries in using big data for the development of library innovation. Design/methodology/approach The Scopus database was accessed on 24 May 2019 by using the keyword “big data” and “library” in the search box. The authors only include papers, which title contain of big data in library. There were 74 papers, however, 1 article was dropped because of it not meeting the criteria (affiliation and abstract were not available). The papers consist of journal articles, conference papers, book chapters, editorial and review. Then the data were extracted into excel and analysed as follows (by the year, by the author/s’s country, by the theme and by the publisher). Following that the collected data were analysed using VOX viewer software to see the relationship between big data terminology and library, terminology clustering, keywords that often appear, countries that publish big data, number of big data authors, year of publication and name of journals that publish big data and library articles (Alagu and Thanuskodi, 2019). Findings It can be concluded that the implementation of big data in libraries is still in an early stage, it is shown from the limited number of practical implementation of big data analytics in library. Not many libraries that use big data to support innovation and services since there were lack of librarian skills of big data analytics. The library manager’s view of big data is still not necessary to do. It is suggested for academic libraries to start their adoption of big data analytics to support library services especially research data. To do so, librarians can enhance their skills and knowledge by following some training in big data analytics or research data management. The information technology infrastructure also needs to be upgraded since big data need big IT capacity. Finally, the big data management policy should be made to ensure the implementation goes well. Originality/value This paper discovers the adoption and implementation of big data in library, many papers talk big data in business and technology context. This is offering new idea for many libraries especially academic library about the adoption of big data to support their services. They can adopt the big data analytics technology and technique that suitable for their library.

scholarly journals COVID-19: potential effects on Chinese citizens’ lifestyle and travel

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jun Wen ◽  
Metin Kozak ◽  
Shaohua Yang ◽  
Fang Liu
Keyword(s):  
Public Health ◽  
Hospitality Industry ◽  
Travel Behaviour ◽  
Tourism Industry ◽  
Consumption Patterns ◽  
Content Type ◽  
The Future ◽  
Tourism And Hospitality Industry ◽  
Tourism And Hospitality ◽  
Chinese Travellers

Purpose The 2019 novel coronavirus (COVID-19) outbreak is projected to have adverse consequences on the global tourism and hospitality industry. This paper aims to examine how the outbreak may alter Chinese tourists’ lifestyle choices, travel behaviour and tourism preferences in the short and long term. Design/methodology/approach This paper is based on the synthesis of news broadcasted by several media outlets to be supported by an overview of the related literature on tourism marketing, tourism management and tourist behaviour. The authors’ experiences investigating trends in tourism and hospitality at the local and international level have also contributed to the study. Findings This paper predicts that COVID-19 will likely affect Chinese travellers’ consumption patterns, such as the growing popularity of free and independent travel, luxury trips and health and wellness tourism. New forms of tourism including slow tourism and smart tourism may also drive future tourism activities. Such changes are likely to force businesses to reconsider their service designs and distribution channels. Research limitations/implications While Chinese and other potential visitors rethink how they travel, professionals, too, should reflect upon how to bring positive or negative changes to the tourism industry following this pandemic. Subsequent research should also consider how to mitigate the effects of similar public health crises in the future. Practical implications Recommendations for industry practitioners and policymakers focus on tailoring travel arrangements to tourists’ backgrounds. The suggestions may help to alleviate outbreak-related stress, offer travellers newly enriching experiences and partially mitigate the effects of COVID-19 on the tourism and hospitality industry. These recommendations can also apply more broadly to global tourist markets. Social implications The COVID-19 outbreak has already brought significant impacts to nearly every society and industry. Tourism scholars and practitioners should carefully consider this tragedy and how it may inform industry and social practices. This and other public health crises represent sterling opportunities to view the industry holistically in terms of its effects on the environment, climate and travellers themselves. Originality/value This paper presumably represents a frontier study, critically examining the possible impacts of COVID-19 on Chinese travellers’ consumption patterns and how the tourism and hospitality industry may respond to such changes in the future.

Reflections on the theme issue outcomes

2016 ◽  
Vol 8 (3) ◽  
pp. 397-402
Author(s):  
Marina Sheresheva ◽  
John Kopiski ◽  
Richard Teare
Keyword(s):  
Hospitality Industry ◽  
Success Factors ◽  
Experience Economy ◽  
Theme Issue ◽  
Content Type ◽  
Starting Point ◽  
Detailed Assessment ◽  
Hospitality And Tourism ◽  
Tourism And Hospitality Industry ◽  
Tourism And Hospitality

Purpose This study aims to profile the Worldwide Hospitality and Tourism Themes (WHATT) issue “What are the main trends, challenges and success factors in the Russian hospitality and tourism market in the experience economy era?” with reference to the experiences of the theme editors, contributors from industry and academia and the theme issue outcomes. Design/methodology/approach This study uses structured questions to enable the theme editors to reflect on the rationale for their theme issue question, the starting point, the selection of the writing team and material and the editorial process. Findings This study provides a framework to facilitate discussion between all stakeholders in Russia’s tourism and hospitality industry; it identifies ways of improving competitiveness as a tourist destination and contributes to thinking about sustainable development. Practical implications Reports on dialogue between Russian academics and industry practitioners related to the challenges, opportunities and success factors that are important for the development of the tourism and hospitality industry in Russia. Originality/value This is the first detailed assessment of the opportunities and mechanisms for creating memorable tourist experiences in Russia. The theme issue also identifies the main problems relating to the development of tourism and hospitality, the implications for industry and the solutions needed to address them.

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