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.

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.

Software as a Service, Semantic Web, and Big Data

2021 ◽  
pp. 1179-1201
Author(s):  
Kijpokin Kasemsap
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Semantic Web ◽  
Organizational Performance ◽  
Big Data Analytics ◽  
Digital Age ◽  
Software As A Service ◽  
Semantic Web Technologies ◽  
Business Applications ◽  
Computing Platforms

This chapter explains the overview of software as a service (SaaS); SaaS and application service provision (ASP); the security concern of SaaS; the perspectives on SaaS adoption; the challenges of SaaS in the digital age; the overview of the Semantic Web; the current trends in the Semantic Web services; the overview of Big Data; the concept of Big Data analytics; and the prospects of Big Data in the digital age. SaaS offers a wide range of business applications through the cloud computing service providers toward enhancing organizational performance. The Semantic Web extends beyond the capabilities of the current Web 2.0, thus enabling more effective collaborations and smarter decision making in modern operations. Big Data from the cloud computing platforms provides the significant advantage, if the essential data sources are hosted by the same SaaS and enhanced by the Semantic Web technologies.

Software as a Service, Semantic Web, and Big Data

2017 ◽  
pp. 264-285 ◽  
Author(s):  
Kijpokin Kasemsap
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Semantic Web ◽  
Organizational Performance ◽  
Big Data Analytics ◽  
Digital Age ◽  
Software As A Service ◽  
Semantic Web Technologies ◽  
Business Applications ◽  
Computing Platforms

This chapter explains the overview of software as a service (SaaS); SaaS and application service provision (ASP); the security concern of SaaS; the perspectives on SaaS adoption; the challenges of SaaS in the digital age; the overview of the Semantic Web; the current trends in the Semantic Web services; the overview of Big Data; the concept of Big Data analytics; and the prospects of Big Data in the digital age. SaaS offers a wide range of business applications through the cloud computing service providers toward enhancing organizational performance. The Semantic Web extends beyond the capabilities of the current Web 2.0, thus enabling more effective collaborations and smarter decision making in modern operations. Big Data from the cloud computing platforms provides the significant advantage, if the essential data sources are hosted by the same SaaS and enhanced by the Semantic Web technologies.

scholarly journals Vision: A Missing Key Dimension in the 5V Big Data Framework

2015 ◽  
Vol 1 (3) ◽  
pp. 40-47
Author(s):  
Uma G. Gupta ◽  
Ashok Gupta
Keyword(s):  
Big Data ◽  
Competitive Advantage ◽  
Organizational Performance ◽  
Positive Impact ◽  
Critical Role ◽  
Sustainable Competitive Advantage ◽  
Data Framework ◽  
Big Data Applications ◽  
Key Stakeholders ◽  
Data Volume

If Big Data is to deliver on its big promises, a well-articulated vision must be developed in a collaborative way and effectively communicated to all key stakeholders. Without a guiding technology vision, the promise and benefits of Big Data will become elusive and lost to many organizations. The literature on Big Data frequently refers to the 5Vs of Big Data (Volume, Variety, Velocity, Veracity and Value). Based on a strategic framework, this paper adds another dimension to this important and widely used framework, namely Vision, and elaborates on the critical role of vision and its relationship and impact on the remaining Vs. Research shows that vision has a positive impact on organizational performance. Organizations that link vision with strategic information systems, such as Big Data applications, ga5in a sustainable competitive advantage in the marketplace. The importance of carefully defining, establishing and communicating the vision of Big Data to the entire organization and to key stakeholders in order to leverage Big Data for growth, profits, and sustainable competitive advantage is discussed.

scholarly journals Impacto de las prácticas de recursos humanos en el capital humano y los resultados organizativos de las empresas hoteleras

2020 ◽  
pp. 311-332
Author(s):  
Jorge Plaza Bolaños ◽  
Julia Nieves
Keyword(s):  
Organizational Performance ◽  
Hospitality Industry ◽  
Recursos Humanos ◽  
Tourism And Hospitality Industry ◽  
Organizational Results ◽  
Tourism And Hospitality ◽  
Capital Development ◽  
Capital Humano ◽  
Retention Practices

Existe un amplio consenso respecto a la conveniencia de mejorar la cualificación de los empleados en el ámbito de la hostelería y turismo. Asimismo, la literatura sugiere la importancia de las prácticas de RRHH en la mejora de los resultados organizativos. Este trabajo pretende aportar evidencia empírica del papel que las prácticas de reclutamiento-selección y de retención desempeñan como determinantes del capital humano y el desempeño organizativo en las empresas hoteleras. Los resultados muestran el importante papel que ejercen, fundamentalmente, las prácticas de reclutamiento-selección. There is an extended consensus related to the need to improve the qualification of workforce in tourism and hospitality industry. Likewise, the literature suggests the importance of HR practices to improve organizational results. This paper aims to show empiric evidence about the role of recruitment-selection and retention practices on the human capital development and organizational performance in hotel firms. The results show the important role of recruitment-selection practices, particularly.

Gentrification and functional change in Budapest – ‘ruin bars’ and the commodification of housing in a post-socialist context

2020 ◽  
Vol 65 (1) ◽  
pp. 17-26
Author(s):  
Gergely Olt ◽  
Adrienne Csizmady
Keyword(s):  
Ownership Structure ◽  
Hospitality Industry ◽  
Housing Stock ◽  
Field Research ◽  
Functional Change ◽  
Global Changes ◽  
Heritage Buildings ◽  
The Subject ◽  
Tourism And Hospitality Industry ◽  
Tourism And Hospitality

AbstractThe growth of the tourism and hospitality industry played an important role in the gentrification of the post-socialist city of Budapest. Although disinvestment was present, reinvestment was moderate for decades after 1989. Privatisation of individual tenancies and the consequent fragmented ownership structure of heritage buildings made refurbishment and reinvestment less profitable. Because of local contextual factors and global changes in consumption habits, the function of the dilapidated 19th century housing stock transformed in the 2000s, and the residential neighbourhood which was the subject of the research turned into the so called ‘party district’. The process was followed in our ongoing field research. The functional change made possible speculative investment in inner city housing and played a major role in the commodification of the disinvested housing stock.

Beach Town

2017 ◽  
Author(s):  
Christopher Hilliard
Keyword(s):  
Hospitality Industry ◽  
First World War ◽  
Social Position ◽  
Maritime Trade ◽  
World War ◽  
Ship Building ◽  
Coastal Shipping ◽  
Tourism And Hospitality Industry ◽  
Tourism And Hospitality ◽  
First World

The chapter surveys post-First World War Littlehampton, a coastal town where tourism and hospitality had overtaken maritime trade, but where coastal shipping and ship-building remained important industries. The libel case unfolded in the Beach Town district, where Littlehampton’s hotels and apartment houses were concentrated. Many of the tradesmen, small businesswomen, labourers, and domestics who serviced the tourism and hospitality industry lived in the neighbourhood. Working from the evidence George Nicholls gathered, census records, and documents in the Littlehampton Museum, the chapter provides an anatomy of the neighbourhood and then examines the families at the centre of the dispute, their economic and social position, and relationships within the household, which were often marked by violence.

scholarly journals The Perception of Job-related Motivators When Choosing a Career in the Tourism and Hospitality Industry – A Comparative Study Between Polish and Spanish Students

2017 ◽  
Vol 53 (2) ◽  
pp. 84-106 ◽  
Author(s):  
Aleksandra Grobelna
Keyword(s):  
Competitive Advantage ◽  
Rapid Growth ◽  
Career Paths ◽  
Hospitality Industry ◽  
Staff Turnover ◽  
Motivating Factors ◽  
Tourism Experience ◽  
Tourism And Hospitality Industry ◽  
Tourism And Hospitality

AbstractThe recent rapid growth of the tourism and hospitality industries raises a question about the quantity and quality of the workforce needed in these sectors. In the tourism/hospitality industry, where most services are delivered directly by employees, competitive advantage is primarily attained through people (employees), who are perceived as an integral component of tourism experience. This creates challenges for an industry suffering from high rates of staff turnover, especially of young employees who leave their jobs after graduation, choosing other career paths.This study presents the job related motivators that students found important when considering their future careers, and investigates the extent to which those motivators can be found in the tourism and hospitality industry. Is the industry able to offer the motivators that will keep the employees willing to choose this particular path? We focus on two groups of potential employees – Polish and Spanish students. The study reveals that both groups generally do not believe that a career in the TH industry offered these motivating factors. We also contrast and compare both groups’ perceptions in this area.

Big data analytics capabilities and organizational performance: the mediating effect of dual innovations

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xiaofeng Su ◽  
Weipeng Zeng ◽  
Manhua Zheng ◽  
Xiaoli Jiang ◽  
Wenhe Lin ◽  
...  
Keyword(s):  
Big Data ◽  
Organizational Performance ◽  
Empirical Analysis ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Mediating Effect ◽  
Content Type ◽  
Mediating Role ◽  
The Relationship

PurposeFollowing the rapid expansion of data volume, velocity and variety, techniques and technologies, big data analytics have achieved substantial development and a surge of companies make investments in big data. Academics and practitioners have been considering the mechanism through which big data analytics capabilities can transform into their improved organizational performance. This paper aims to examine how big data analytics capabilities influence organizational performance through the mediating role of dual innovations.Design/methodology/approachDrawing on the resource-based view and recent literature on big data analytics, this paper aims to examine the direct effects of big data analytics capabilities (BDAC) on organizational performance, as well as the mediating role of dual innovations on the relationship between (BDAC) and organizational performance. The study extends existing research by making a distinction of BDACs' effect on their outcomes and proposing that BDACs help organizations to generate insights that can help strengthen their dual innovations, which in turn have a positive impact on organizational performance. To test our proposed research model, this study conducts empirical analysis based on questionnaire-base survey data collected from 309 respondents working in Chinese manufacturing firms.FindingsThe results support the proposed hypotheses regarding the direct and indirect effect that BDACs have on organizational performance. Specifically, this paper finds that dual innovations positively mediate BDACs' effect on organizational performance.Originality/valueThe conclusions on the relationship between big data analytics capabilities and organizational performance in previous research are controversial due to lack of theoretical foundation and empirical testing. This study resolves the issue by provides empirical analysis, which makes the research conclusions more scientific and credible. In addition, previous literature mainly focused on BDACs' direct impact on organizational performance without making a distinction of BDAC's three dimensions. This study contributes to the literature by thoroughly introducing the notions of BDAC's three core constituents and fully analyzing their relationships with organizational performance. What's more, empirical research on the mechanism of big data analytics' influence on organizational performance is still at a rudimentary stage. The authors address this critical gap by exploring the mediation of dual innovations in the relationship through survey-based research. The research conclusions of this paper provide new perspective for understanding the impact of big data analytics capabilities on organizational performance, and enrich the theoretical research connotation of big data analysis capabilities and dual innovation behavior.

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