Artificial intelligence and big data in tourism: a systematic literature review

2020 ◽  
Vol 11 (2) ◽  
pp. 343-367 ◽  
Author(s):  
Dimitra Samara ◽  
Ioannis Magnisalis ◽  
Vassilios Peristeras
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Literature Review ◽  
Systematic Literature Review ◽  
New Technologies ◽  
Recent Literature ◽  
Content Type ◽  
Analysis Methodology ◽  
Tourism Sector

Purpose This paper aims to research, identify and discuss the benefits and overall role of big data and artificial intelligence (BDAI) in the tourism sector, as this is depicted in recent literature. Design/methodology/approach A systematic literature review was conducted under the McKinsey’s Global Institute (Talwar and Koury, 2017) methodological perspective that identifies the four ways (i.e. project, produce, promote and provide) in which BDAI creates value. The authors enhanced this analysis methodology by depicting relevant challenges as well. Findings The findings imply that BDAI create value for the tourism sector through appropriately identified disseminations. The benefits of adopting BDAI strategies include increased efficiency, productivity and profitability for tourism suppliers combined with an extremely rich and personalized experience for travellers. The authors conclude that challenges can be bypassed by adopting a BDAI strategy. Such an adoption will stand critical for the competitiveness and resilience of existing established and new players in the tourism sector. Originality/value Besides identifying the benefits that BDAI brings in the tourism sector, the research proposes a guidebook to overcome challenges when introducing such new technologies. The exploration of the BDAI literature brings important implication for managers, academicians and consumers. This is the first systematic review in an area and contributes to the broader e-commerce marketing, retailing and e-tourism research.

Strategic issues of big data analytics applications for managing health-care sector: a systematic literature review and future research agenda

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rajesh Kumar Singh ◽  
Saurabh Agrawal ◽  
Abhishek Sahu ◽  
Yigit Kazancoglu
Keyword(s):  
Health Care ◽  
Big Data ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Health Care Sector ◽  
Future Research ◽  
Research Gaps ◽  
Content Type

PurposeThe proposed article is aimed at exploring the opportunities, challenges and possible outcomes of incorporating big data analytics (BDA) into health-care sector. The purpose of this study is to find the research gaps in the literature and to investigate the scope of incorporating new strategies in the health-care sector for increasing the efficiency of the system.Design/methodology/approachFora state-of-the-art literature review, a systematic literature review has been carried out to find out research gaps in the field of healthcare using big data (BD) applications. A detailed research methodology including material collection, descriptive analysis and categorization is utilized to carry out the literature review.FindingsBD analysis is rapidly being adopted in health-care sector for utilizing precious information available in terms of BD. However, it puts forth certain challenges that need to be focused upon. The article identifies and explains the challenges thoroughly.Research limitations/implicationsThe proposed study will provide useful guidance to the health-care sector professionals for managing health-care system. It will help academicians and physicians for evaluating, improving and benchmarking the health-care strategies through BDA in the health-care sector. One of the limitations of the study is that it is based on literature review and more in-depth studies may be carried out for the generalization of results.Originality/valueThere are certain effective tools available in the market today that are currently being used by both small and large businesses and corporations. One of them is BD, which may be very useful for health-care sector. A comprehensive literature review is carried out for research papers published between 1974 and 2021.

Big data-driven strategic orientation in international marketing

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shahriar Akter ◽  
Md Afnan Hossain ◽  
Qiang (Steven) Lu ◽  
S.M. Riad Shams
Keyword(s):  
Big Data ◽  
Literature Review ◽  
Systematic Literature Review ◽  
International Marketing ◽  
Strategic Orientation ◽  
Data Driven ◽  
Future Research ◽  
Content Type ◽  
Strategic Orientations ◽  
Marketing Activities

PurposeBig data is one of the most demanding topics in contemporary marketing research. Despite its importance, the big data-based strategic orientation in international marketing is yet to be formed conceptually. Thus, the purpose of this study is to systematically review and propose a holistic framework on big data-based strategic orientation for firms in international markets to attain a sustained firm performance.Design/methodology/approachThe study employed a systematic literature review to synthesize research rigorously. Initially, 2,242 articles were identified from the selective databases, and 45 papers were finally reported as most relevant to propose an integrative conceptual framework.FindingsThe findings of the systematic literature review revealed data-evolving, and data-driven strategic orientations are essential for performing international marketing activities that contain three primary orientations such as (1) international digital platform orientation, (2) international market orientation and (3) international innovation and entrepreneurial orientation. Eleven distinct sub-dimensions reflect these three primary orientations. These strategic orientations of international firms may lead to advanced analytics orientation to attain sustained firm performance by generating and capturing value from the marketplace.Research limitations/implicationsThe study minimizes the literature gap by forming knowledge on big data-based strategic orientation and framing a multidimensional framework for guiding managers in the context of strategic orientation for international business and international marketing activities. The current study was conducted by following only a systematic literature review exclusively in firms' overall big data-based strategic orientation concept in international marketing. Future research may extend the domain by introducing firms' category wise systematic literature review.Originality/valueThe study has proposed a holistic conceptual framework for big data-driven strategic orientation in international marketing literature through a systematic review for the first time. It has also illuminated a future research agenda that raises questions for the scholars to develop or extend theory in this area or other related disciplines.

Exploring BIM-triggered organisational and professional culture change: a systematic literature review

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sonali Alankarage ◽  
Nicholas Chileshe ◽  
Raufdeen Rameezdeen ◽  
David J. Edwards ◽  
Aparna Samaraweera
Keyword(s):  
Literature Review ◽  
Systematic Literature Review ◽  
Essential Element ◽  
Future Research ◽  
Content Type ◽  
New Employees ◽  
Body Of Knowledge ◽  
Building Information ◽  
Considerable Impact

Purpose Building information modelling (BIM) has had a considerable impact on the socio-technical aspects of construction organisations. Culture has been considered an essential element in BIM practice. Hence, this paper aims to explore existing research relates to culture in the BIM context. Design/methodology/approach A systematic literature review (SLR) was conducted based on the PRISMA guidelines using 104 articles published between 2011 and 2020 and directed with a descriptive and content analysis. Findings The SLR results give evidence that culture in the BIM context is still an under-researched topic. Culture has been considered as both a dependent and independent factor in the BIM domain. Organisational BIM culture is a collection of fundamental beliefs established in a BIM using organisation and passed to new employees with the use of BIM. BIM using organisations are have either weak or strong BIM cultures. Proper analysis and understanding of the BIM culture of different organisations are necessary to realise the strategies of transformation from a weak BIM culture to a strong BIM culture. Originality/value To the best of the author's knowledge, this is the first SLR in BIM research that investigates the role of culture in the BIM setting. This study contributed to the existing body of knowledge by proposing a conceptual framework to understand and change a weak BIM culture of an organisation to a strong, matured BIM culture. This SLR serves as a future research basis in BIM-triggered culture.

Stakeholders' involvement in sustainability planning and implementation: the case of Cyprus

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Iordanis Katemliadis ◽  
Georgios Markatos
Keyword(s):  
Literature Review ◽  
Systematic Literature Review ◽  
Design Methodology ◽  
Stakeholder Involvement ◽  
Tourism Planning ◽  
Content Type ◽  
Sustainable Tourism Development ◽  
Sustainability Planning ◽  
Active Involvement

PurposeTourism planning and development has revolved around sustainability concepts and issues, and this paper aims to provide an analysis of stakeholder involvement in sustainability planning and implementation in Cyprus.Design/methodology/approachThe article provides a comprehensive perspective on stakeholder involvement in sustainability planning and implementation based on a systematic literature review.FindingsStudy findings indicate that the active involvement of stakeholders is a prerequisite in order to address the complex issues of sustainable tourism development.Originality/valueThe authors examined the role of stakeholders at individual, local and international levels, and how they can make a difference in transitioning to a more sustainable future for tourism in Cyprus.

Innovative drivers for family business models in tourism

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Gabriella Arcese ◽  
Marco Valeri ◽  
Stefano Poponi ◽  
Grazia Chiara Elmo
Keyword(s):  
Literature Review ◽  
Business Model ◽  
Family Business ◽  
Systematic Literature Review ◽  
Business Models ◽  
Extensive Literature ◽  
Family Needs ◽  
Content Type ◽  
Tourism Sector ◽  
Innovation Dynamics

PurposeThe aim of this paper is to verify whether, in the tourism sector, the “family business model” is an important development opportunity and, in particular, if it is an innovation driver for this industry development. In the literature, there is no conclusive evidence of this for the tourism sector. In this context, the authors investigate personal and family needs and preferences alongside the relationship between family business model, growth and profit maximization and the development of tourism businesses through innovation drivers.Design/methodology/approachTo develop this topic, the authors conducted an extensive literature review considering the scientific papers published and contained mainly in database in the last 10 years (2010–2020) and focused the attention on the last five years. The authors ran content and structural analysis on the collected sources by main scientific databases (EBSCO, Scopus, Thomson Reuter, etc.). Based on a systematic literature review, the analysis was conducted using statistical criteria and bibliometric indicators. In detail, the authors used systematic literature review, bibliometric analysis and automatic text analysis (ATA) tools for identified lexicon analysis and strategic keywords and used statistical correlation to classify the different approaches in the literature and to outline the orientations of the various research groups.FindingsFrom this analysis, the correlation between tourism, hospitality, entrepreneurship, life cycle and innovation dynamics was analysed. Important research gaps are identified, and future research priorities are suggested. Implications for both family business and tourism theory are discussed.Originality/valueWhile the intersection between tourism management and family business model has been established in the literature, the number of related publications is still limited. Against this background, a literature review as a total analysis was an adequate and practicable research methodology. This paper proposes a comprehensive literature review and a reflection on the potential developments and applications for family business in the tourism sector. Authors also suggest several research directions that have not been adequately investigated yet. In particular, scholars do not seem to have caught all the implications of innovation adoption, especially for SMEs and family ownerships in tourism.

scholarly journals Big data and dynamic capabilities: a bibliometric analysis and systematic literature review

2019 ◽  
Vol 57 (8) ◽  
pp. 2052-2068 ◽  
Author(s):  
Riccardo Rialti ◽  
Giacomo Marzi ◽  
Cristiano Ciappei ◽  
Donatella Busso
Keyword(s):  
Big Data ◽  
Literature Review ◽  
Bibliometric Analysis ◽  
Systematic Literature Review ◽  
Dynamic Capabilities ◽  
Process Management ◽  
Big Data Analytics ◽  
Management Decision ◽  
Content Type ◽  
Management Decision Making

Purpose Recently, several manuscripts about the effects of big data on organizations used dynamic capabilities as their main theoretical approach. However, these manuscripts still lack systematization. Consequently, the purpose of this paper is to systematize the literature on big data and dynamic capabilities. Design/methodology/approach A bibliometric analysis was performed on 170 manuscripts extracted from the Clarivate Analytics Web of Science Core Collection database. The bibliometric analysis was integrated with a literature review. Findings The bibliometric analysis revealed four clusters of papers on big data and dynamic capabilities: big data and supply chain management, knowledge management, decision making, business process management and big data analytics. The systematic literature review helped to clarify each clusters’ content. Originality/value To the authors’ best knowledge, minimal attention has been paid to systematizing the literature on big data and dynamic capabilities.

A systematic literature review of data science, data analytics and machine learning applied to healthcare engineering systems

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Roberto Salazar-Reyna ◽  
Fernando Gonzalez-Aleu ◽  
Edgar M.A. Granda-Gutierrez ◽  
Jenny Diaz-Ramirez ◽  
Jose Arturo Garza-Reyes ◽  
...  
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Big Data ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Data Analytics ◽  
Research Area ◽  
Engineering Systems ◽  
Content Type ◽  
Healthcare Engineering

PurposeThe objective of this paper is to assess and synthesize the published literature related to the application of data analytics, big data, data mining and machine learning to healthcare engineering systems.Design/methodology/approachA systematic literature review (SLR) was conducted to obtain the most relevant papers related to the research study from three different platforms: EBSCOhost, ProQuest and Scopus. The literature was assessed and synthesized, conducting analysis associated with the publications, authors and content.FindingsFrom the SLR, 576 publications were identified and analyzed. The research area seems to show the characteristics of a growing field with new research areas evolving and applications being explored. In addition, the main authors and collaboration groups publishing in this research area were identified throughout a social network analysis. This could lead new and current authors to identify researchers with common interests on the field.Research limitations/implicationsThe use of the SLR methodology does not guarantee that all relevant publications related to the research are covered and analyzed. However, the authors' previous knowledge and the nature of the publications were used to select different platforms.Originality/valueTo the best of the authors' knowledge, this paper represents the most comprehensive literature-based study on the fields of data analytics, big data, data mining and machine learning applied to healthcare engineering systems.

Debunking the myth of industry 4.0 in health care: insights from a systematic literature review

2020 ◽  
Vol 32 (4) ◽  
pp. 849-868 ◽  
Author(s):  
Mauro Cavallone ◽  
Rocco Palumbo
Keyword(s):  
Artificial Intelligence ◽  
Health Care ◽  
Health Services ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Industry 4.0 ◽  
Services Quality ◽  
State Of The Art ◽  
The State ◽  
Content Type

PurposeIndustry 4.0, artificial intelligence and digitalization have got a momentum in health care. However, scholars and practitioners do not agree on their implications on health services' quality and effectiveness. The article aims at shedding light on the applications, aftermaths and drawbacks of industry 4.0 in health care, summarizing the state of the art.Design/methodology/approachA systematic literature review was undertaken. We arranged an ad hoc research design, which was tailored to the study purposes. Three citation databases were queried. We collected 1,194 scientific papers which were carefully considered for inclusion in this systematic literature review. After three rounds of analysis, 40 papers were taken into consideration.FindingsIndustry 4.0, artificial intelligence and digitalization are revolutionizing the design and the delivery of care. They are expected to enhance health services' quality and effectiveness, paving the way for more direct patient–provider relationships. In addition, they have been argued to allow a more appropriate use of available resources. There is a dark side of health care 4.0 involving both management and ethical issues.Research limitations/implicationsIndustry 4.0 in health care should not be conceived as a self-nourishing innovation; rather, it needs to be carefully steered at both the policy and management levels. On the one hand, comprehensive governance models are required to realize the full potential of health 4.0. On the other hand, the drawbacks of industry 4.0 should be timely recognized and thoroughly addressed.Originality/valueThe article contextualizes the state of the art of industry 4.0 in the health care context, providing some insights for further conceptual and empirical developments.

Role of human behaviour attributes in mobile crowd sensing: a systematic literature review

2017 ◽  
Vol 19 (2) ◽  
pp. 168-185 ◽  
Author(s):  
Neetima Agarwal ◽  
Sumedha Chauhan ◽  
Arpan Kumar Kar ◽  
Sandeep Goyal
Keyword(s):  
Literature Review ◽  
Systematic Literature Review ◽  
Situation Awareness ◽  
Human Behaviour ◽  
New Paradigm ◽  
Mobile Crowd Sensing ◽  
Content Type ◽  
Crowd Sensing ◽  
Mobile Crowd

Purpose Mobile crowd sensing (MCS) is a new paradigm enabled by Internet of Things (IoT) in which sensor-rich ubiquitous devices collect and share the data over a large geography. Human behaviour attributes (perception, comprehension and projection) play a key role in the decision-making process for sharing and processing the data. This study aims to understand how situation awareness plays an important role in MCS in an IoT ecosystem. Design/methodology/approach A systematic literature review was conducted by following a rigorous search protocol that identified a total of 470 peer-reviewed research papers. These papers were further filtered and finally 31 relevant papers were selected. Findings The major issues and concerns arising due to human participation in the MCS system were identified. Further, probable strategies were explored to deal with the challenges resulting due to certain human behaviour attributes. Practical implications This study provides the recommendations to address the major challenges related to the MCS system, which in turn may enhance the adoption of emerging smart technology-driven services. Originality/value The study is original and is based on the existing literature and its interpretation.

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