This review paper aims at providing a systematic analysis of articles published in various journals and related to the uses and business applications of big data. The goal is to provide a holistic picture of the place of big data in the tourism industry. The reviewed articles have been selected for the period 2013-2020 and have been classified into 8 broad categories namely business strategy and firm performance; banking and finance; healthcare; hospitality; networks and telecommunications; urbanism and infrastructures; law and legal regulations; and government. While the categories are reflective of components of tourism industries and infrastructures, the meta-analysis is organized around 3 broad themes: preferred research contexts, conceptual developments, and methods used to research big data business applications. Main findings revealed that firm performance and healthcare remain popular contexts of research in the big data realm, but also demonstrated a prominence of qualitative methods over mixed and quantitative methods for the period 2013-2020. Scholars have also investigated topics involving the notions of competitive advantage, supply chain management, smart cities, but also ethics and privacy issues as related to the use of big data.
AcharjyaD. P., & AhmedK. (2016). A survey on big data analytics: Challenges, open research issues and tools. International Journal of Advanced Computer Science and Applications, 7(2), 511–518.
2.
AkterS., & WambaS. F. (2016). Big data analytics in e-commerce: A systematic review and agenda for future research. Electronic Markets, 26(2), 173–194.
3.
AkterS.WambaS. F.GunasekaranA.DubeyR., & ChildeS. J. (2016). How to improve firm performance using big data analytics capability and business strategy alignment? International Journal of Production Economics, 182, 113–131.
4.
Al NuaimiE., Al NeyadiH., MohamedN., & Al-JaroodiJ. (2015) Applications of big data to smart cities. Journal of Internet Services and Applications, 6(1), 25.
5.
AllenA. L. (2016). Protecting one's own privacy in a big data economy. Harvard Law Review Forum, 130, 1–8.
6.
Álvarez-GarcíaJ.Durán-SánchezA. del Río-Rama, MdlC., & Simonetti, B. (2020). Big data and tourism research: Measuring research impact. Quality and Quantity. Advance online publication. https://doi.org/10.1007/s11135-020-01044-z
7.
AngraveD.CharlwoodA.KirkpatrickI.LawrenceM., & StuartM. (2016). HR and analytics: Why HR is set to fail the big data challenge. Human Resource Management Journal, 26(1), 1–11.
8.
ArdagnaC. A.CeravoloP., & DamianiE. (2016, December 5–8). Big data analytics as-a-service: Issues and challenges. Paper presented at the IEEE International Conference on Big Data, Washington, DC, USA.
9.
BabuM. S. P., & SastryS. H. (2014, June 27–29). Big data and predictive analytics in ERP systems for automating decision making process. Paper presented at the 2014 IEEE 5th International Conference on Software Engineering and Service Science, Beijing, China.
10.
BanicL.MihanovicA., & BrakusM. (2013, May 20–24). Using big data and sentiment analysis in product evaluation. Paper presented at the 2013 36th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), Opatija Croatia.
11.
BarhamH. (2017, July 9–13). Achieving competitive advantage through big data: A literature review. Paper presented at the 2017 Portland International Conference on Management of Engineering and Technology (PICMET), Portland, OR, USA.
12.
BatesD. W.SariaS.Ohno-MachadoL.ShahA., & EscobarG. (2014). Big data in health care: Using analytics to identify and manage high-risk and high-cost patients. Health Affairs, 33(7), 1123–1131.
13.
BenjellounF. Z.LahcenA. A., & BelfkihS. (2015, March 25–26). An overview of big data opportunities, applications and tools. Paper presented at the 2015 Intelligent Systems and Computer Vision (ISCV), Fez, Morocco.
14.
BerenteN.SeidelS., & SafadiH. (2019). Research Commentary—Data-driven computationally intensive theory development. Information Systems Research, 30(1), 50–64.
15.
BergerM. L., & DobanV. (2014). Big data, advanced analytics and the future of comparative effectiveness research. Journal of Comparative Effectiveness Research, 3(2), 167–176.
16.
BhimaniA. (2015). Exploring big data's strategic consequences. Journal of Information Technology, 30(1), 66–69.
17.
BihlT. J.YoungW. A., & WeckmanG. R. (2016). Defining, understanding, and addressing big data. International Journal of Business Analytics, 3(2), 1–32.
18.
BiswasS., & SenJ. (2017). A proposed architecture for big data driven supply chain analytics. arXiv preprint. arXiv:1705.04958.
19.
BodislavD. A. (2015). Transferring business intelligence and big data analysis from corporations to governments as a hybrid leading indicator. Theoretical and Applied Economics, 22(1), 257–264.
20.
Bøe-LillegravenT. (2014). Untangling the ambidexterity dilemma through big data analytics. Journal of Organization Design, 3(3), 27–37.
21.
BughinJ. (2016). Big data, big bang? Journal of Big Data, 3(1), 1–14.
22.
CasadoR., & YounasM. (2015). Emerging trends and technologies in big data processing. Concurrency and Computation: Practice and Experience, 27(8), 2078–2091.
23.
ChangY. C.KuC. H., & ChenC. H. (2020). Using deep learning and visual analytics to explore hotel reviews and responses. Tourism Management, 80, 104129.
24.
ChatfieldA.ReddickC., & Al-ZubaidiW. (2015). Capability challenges in transforming government through open and big data: Tales of two cities. 36th International Conference on Information Systems, Fort Worth, Texas, 1–21
25.
ChauhanS.AgarwalN., & KarA. K. (2016). Addressing big data challenges in smart cities: A systematic literature review. Info, 18(4), 73–90.
26.
ChenH. M.SchützR.KazmanR., & MatthesF. (2017). How Lufthansa capitalized on big data for business model renovation. MIS Quarterly Executive, 16(1), 4.
27.
ChenP. C. L., & ZhangC. Y. (2014). Data-intensive applications, challenges, techniques and technologies: A survey on Big Data. Information Sciences, 275, 314–347.
28.
ChenP. T.LinC. L., & WuW. N. (2020). Big data management in healthcare: Adoption challenges and implications. International Journal of Information Management, 53, 102078.
29.
ChluskiA., & ZioraL. (2015). The application of big data in the management of healthcare organizations: A review of selected practical solutions. Informatyka Ekonomiczna, 1(35), 9–18.
30.
ChunJ.KimC. K.KimG. S.JeongJ., & LeeW. K. (2020). Social big data informs spatially explicit management options for national parks with high tourism pressures. Tourism Management, 81104136.
31.
CohenP.HahnR.HallJ.LevittS., & MetcalfeR. (2016). Using big data to estimate consumer surplus: The case of uber (No. w22627). National Bureau of Economic Research, Cambridge, Massachusetts.
32.
Côrte-RealN.OliveiraT., & RuivoP. (2017). Assessing business value of big data analytics in European firms. Journal of Business Research, 70, 379–390.
33.
CouldryN., & TurowJ. (2014). Advertising, big data, and the clearance of the public realm. International Journal of Communications, 8(1), 1710–1726.
34.
CrawfordK., & SchultzJ. (2014). Big data and due process: Toward a framework to redress predictive privacy harms. Boston College Law Review, 55, 93.
35.
CustersB., & UršičH. (2016). Big data and data reuse: A taxonomy of data reuse for balancing big data benefits and personal data protection. International Data Privacy Law, 6(1), 4–15.
De MauroA., GrecoM., & GrimaldiM. (2015). What is big data? A consensual definition and a review of key research topics. AIP Conference Proceedings, 1644 (1), 97–104.
38.
De MauroA., GrecoM., & GrimaldiM. (2016). A formal definition of big data based on its essential features. Library Review, 65(3), 122–135.
39.
DekimpeM. G. (2020). Retailing and retailing research in the age of big data analytics. International Journal of Research in Marketing, 37(1), 3–14.
40.
Del VecchioP. D., MeleG., NdouV., & SecundoG. (2018). Creating value from social big data: Implications for smart tourism destinations. Information Processing and Management, 54(5), 847–860.
41.
DubeyR.GunasekaranA., & ChildeS. J. (2019). Big data analytics capability in supply chain agility: The moderating effect of organizational flexibility. Management Decision, 57(8), 2092–2112.
42.
ElgendyN., & ElragalA. (2014). Big data analytics: A literature review paper. In PernerP. (Ed.), Advances in data mining. Applications and theoretical aspects. ICDM2014. Lecture notes in computer science (Vol. 8557, pp. 214–227). Cham, Germany: Springer.
43.
ElgendyN., & ElragalA. (2016). Big data analytics in support of the decision making process. Procedia Computer Science, 100, 1071–1084.
44.
ErevellesS.FukawaN., & SwayneL. (2016). Big data consumer analytics and the transformation of marketing. Journal of Business Research, 69(2), 897–904.
45.
FanS.LauR. Y. K., & ZhaoJ. L. (2015). Demystifying big data analytics for business intelligence through the lens of marketing mix. Big Data Research, 2(1), 28–32.
46.
FanningK., & GrantR. (2013). Big data: Implications for financial managers. Journal of Corporate Accounting and Finance, 24(5), 23–30.
47.
FeltM. (2016). Social media and the social sciences: How researchers employ Big Data analytics. Big Data and Society. Advance online publication. https://doi.org/10.1177/2053951716645828
48.
FloodM. D.JagadishH. V., & RaschidL. (2016). Big data challenges and opportunities in financial stability monitoring. Financial Stability Review, 20, 129–142.
49.
Frizzo-BarkerJ.Chow-WhiteP. A.MozafariM., & HaD. (2016). An empirical study of the rise of big data in business scholarship. International Journal of Information Management, 36(3), 403–413.
50.
FuH. L.ManogaranG.WuK.CaoM.JiangS., & YangA. M. (2020). Intelligent decision-making of online shopping behavior based on internet of things. International Journal of Information Management, 50, 515–525.
GaoJ.KoroniosA., & SelleS. (2015). Towards a process view on critical success factors in big data analytics projects.
53.
GeczyP. (2014). Big data characteristics. Macrotheme Review, 3(6), 94–104.
54.
GhasemaghaeiM. (2020). The role of positive and negative valence factors on the impact of bigness of data on big data analytics usage. International Journal of Information Management, 50, 395–404.
55.
GhasemaghaeiM., & CalicG. (2020). Assessing the impact of big data on firm innovation performance: Big data is not always better data. Journal of Business Research, 108, 147–162.
56.
GillespieT. (2020). Content moderation, AI, and the question of scale. Big Data and Society. Advance online publication. https://doi.org/10.1177/2053951720943234
57.
GroverV.ChiangR. H. L.LiangT.-P., & ZhangD. (2018). Creating strategic business value from big data analytics: A research framework. Journal of Management Information Systems, 35(2), 388–423.
58.
GroverV.LindbergA.BenbasatI., & LyytinenK. (2020). The perils and promises of big data research in information systems. Journal of the Association for Information Systems, 21 (2), 268–293.
59.
GrovesP.KayyaliB.KnottD., & KuikenS. V. (2016). The ‘big data’ revolution in healthcare: Accelerating value and innovation. McKinsey & Company.
60.
GunasekaranA.PapadopoulosT.DubeyR.WambaS. F.ChildeS. J.HazenB., & AkterS. (2016). Big data and predictive analytics for supply chain and organizational performance. Journal of Business Research, 70, 308–317.
61.
GunasekaranA.YusufY. Y.AdeleyeE. O., & PapadopoulosT. (2018). Agile manufacturing practices: The role of big data and business analytics with multiple case studies. International Journal of Production Research, 56(1–2), 385–397.
62.
GuptaM., & GeorgeJ. F. (2016). Toward the development of a big data analytics capability. Information and Management, 53(8), 1049–1064.
63.
GuptaR. (2014). Journey from data mining to Web Mining to Big Data. International Journal of Computer Trends and Technology, 10(1), 18–20.
64.
HartmannP. M.ZakiM.FeldmannN., & NeelyA. (2016). Capturing value from big data—A taxonomy of data-driven business models used by start-up firms. International Journal of Operations and Production Management, 36(10), 1382–1406.
65.
HashemI. A. T.ChangV.AnuarN. B.AdewoleK.YaqoobI.GaniA.AhmedE., & ChiromaH. (2016). The role of big data in smart city. International Journal of Information Management, 36(5), 748–758.
66.
HeL.XueM., & GuB. (2020). Internet-of-things enabled supply chain planning and coordination with big data services: Certain theoretic implications. Journal of Management Science and Engineering, 5(1), 1–22.
67.
KacheF., & SeuringS. (2017). Challenges and opportunities of digital information at the intersection of Big Data Analytics and supply chain management. International Journal of Operations and Production Management, 37(1), 10–36.
68.
KamakshiP. (2014). Survey on big data and related privacy issues. International Journal of Research in Engineering and Technology, 3(12), 68–70.
69.
KempR. (2014). Legal aspects of managing Big Data. Computer Law and Security Review, 30(5), 482–491.
70.
KimG.-H.TrimiS., & ChungJ.-H. (2014). Big-data applications in the government sector. Communications of the ACM, 57(3), 78–85.
71.
KimM.-K., & ParkJ.-H. (2017). Identifying and prioritizing critical factors for promoting the implementation and usage of big data in healthcare. Information Development, 33(3), 257–269.
72.
KodapanakkalR. I.BrandtM. J.KoglerC., & van Beest, I. (2020). Self-interest and data protection drive the adoption and moral acceptability of big data technologies: A conjoint analysis approach. Computers in Human Behavior, 108106303.
73.
KorhonenJ. J. (2014). Big data—Big deal for organization design? Journal of Organization Design, 3(1), 31.
74.
KoroniosA.GaoJ., & SelleS. (2014). Big Data project success-A metaanalysis. PACIS 2014 Proceedings, Paper 376.
75.
KshetriN. (2014). Big data's impact on privacy, security and consumer welfare. Telecommunications Policy, 38(11), 1134–1145.
76.
KubinaM.VarmusM., & KubinovaI. (2015). Use of big data for competitive advantage of company. Procedia Economics and Finance, 26, 561–565.
77.
KumarA., & PrakashA. (2014). Role of big data and analytics in smart cities. International Journal of Scientific Research (IJSR), 6(14), 12–23.
78.
Kupwade PatilH., & SeshadriR. (2014, June 27–July 2). Big data security and privacy issues in healthcare. Paper presented at the 2014 IEEE International Congress on Big Data, Anchorage, AK, USA.
LeeM.CaiY. (, DeFranco, A., & Lee, J. (2020). Exploring influential factors affecting guest satisfaction: Big data and business analytics in consumer-generated reviews. Journal of Hospitality and Tourism Technology, 11(1), 137–153.
81.
LiJ.TaoF.ChengY., & ZhaoL. (2015). Big Data in product lifecycle management. International Journal of Advanced Manufacturing Technology, 81(1–4), 667–684.
82.
LiJ.XuL.TangL.WangS., & LiL. (2018). Big data in tourism research: A literature review. Tourism Management, 68, 301–323.
83.
LindbergA. (2020). Developing theory through integrating human and machine pattern recognition. Journal of the Association for Information Systems, 21(1), 90–116.
84.
LineN. D.DogruT.El-ManstrlyD.BuoyeA.MalthouseE., & KandampullyJ. (2020). Control, use and ownership of big data: A reciprocal view of customer big data value in the hospitality and tourism industry. Tourism Management, 80, 104106.
85.
LiuO.ManK. L.ChongW., & ChanC. O. (2016). Social network analysis using big data. In Proceedings of the International Multiconference of Engineers and Computer Scientists, 2, 6–7.
86.
LiuY.HeJ.GuoM.YangQ., & ZhangX. (2014). An overview of big data industry in China. China Communications, 11(12), 1–10.
87.
LvD., & ZhuS. (2020). Achieving secure big data collection based on trust evaluation and true data discovery. Computers and Security, 96, 101937.
88.
MaglioP. P., & LimC.-H. (2016). Innovation and big data in smart service systems. Journal of Innovation Management, 4(1), 11–21.
89.
MahrtM., & ScharkowM. (2013). The value of big data in digital media research. Journal of Broadcasting and Electronic Media, 57(1), 20–33.
90.
MarkusM. L., & TopiH. (2015). Big data, big decisions for science, society, and business: Report on a research agenda setting workshop. Bentley University, Waltham, Massachusetts.
91.
MathewP. S., & PillaiA. S. (2015, March 19–20). Big Data solutions in healthcare: Problems and perspectives. Paper presented at the 2015 International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS), Coimbatore, India.
92.
MatthiasO.FouweatherI.GregoryI., & VernonA. (2017). Making sense of Big Data—Can it transform operations management? International Journal of Operations and Production Management, 37(1), 37–55.
93.
MehraliyevF.KirilenkoA. P., & ChoiY. (2020). From measurement scale to sentiment scale: Examining the effect of sensory experiences on online review rating behavior. Tourism Management, 79, 104096.
94.
MehtaN., & PanditA. (2018). Concurrence of big data analytics and healthcare: A systematic review. International Journal of Medical Informatics, 114, 57–65.
95.
MenonS., & SarkarS. (2016). Privacy and big data: Scalable approaches to sanitize large transactional databases for sharing. MIS Quarterly, 40(4), 963–981.
96.
MikalefP.KrogstieJ.PappasI. O., & PavlouP. (2020). Exploring the relationship between big data analytics capability and competitive performance: The mediating roles of dynamic and operational capabilities. Information and Management, 57(2), 103169.
97.
MikalefP.PappasI. O.GiannakosM. N.KrogstieJ., & LekakosG. (2016). Big data and strategy: A research framework. MCIS 2016 Proceedings, 2016, 50.
98.
MilanS. (2020). Techno-solutionism and the standard human in the making of the COVID-19 pandemic. Big Data and Society. Advance online publication. https://doi.org/10.1177/2053951720966781
99.
MishraD.GunasekaranA.PapadopoulosT., & ChildeS. J. (2018). Big Data and supply chain management: A review and bibliometric analysis. Annals of Operations Research, 270(1–2), 313–336.
100.
MoriokaM.KuramochiK.MishinaY.AkiyamaT., & TaniguchiN. (2015). City management platform using big data from people and traffic flows. Hitachi Review, 64(1), 53.
NguyenT.ZhouL.SpieglerV.IeromonachouP., & LinY. (2018). Big data analytics in supply chain management: A state-of-the-art literature review. Computers and Operations Research, 98, 254–264.
103.
NunanD., & Di Domenico, M. (2013). Market research and the ethics of big data. International Journal of Market Research, 55(4), 505–520.
104.
OguntimilehinA., & AdemolaE. O. (2014). A review of big data management, benefits and challenges. Journal of Emerging Trends in Computing and Information Sciences, 5(6), 433–438.
105.
OneteC.-B.VargasV. M., & ChitaS. D. (2020). Study on the implications of personal data exposure on the social media platforms. Transformations in Business and Economics, 19(2), 243–258.
106.
Orenga-RogláS., & ChalmetaR. (2016). Social customer relationship management: Taking advantage of Web 2.0 and Big Data technologies. SpringerPlus, 5(1), 1462.
PereraC.RanjanR.WangL.KhanS., & ZomayaA. (2015). Privacy of big data in the internet of things era. IEEE It Professional Magazine, 17, 32–39.
109.
PetticrewM., & RobertsH. (2008). Systematic reviews in the social sciences: A practical guide. Chichester: UK, John Wiley & Sons.
110.
PoletoT. de Carvalho, V. D. H., & Costa, A. P. C. S. (2015). The roles of big data in the decision-support process: An empirical investigation. In B. Delibašić, J. E. Hernández, J. Papathanasiou, F. Dargam, P. Zaraté, R. Ribeiro, S. Liu, & I. Linden (Eds.), Decision support systems V – Big data analytics for decision making. ICDSST2015. Lecture notes in business information processing (pp. 10–21). Cham, Germany: Springer.
111.
PopovicA.HackneyR.TassabehjiR., & CastelliM. (2018). The impact of big data analytics on firms’ high value business performance. Information Systems Frontiers, 20(2), 209–222.
112.
ProvostF., & FawcettT. (2013). Data science and its relationship to big data and data-driven decision making. Big Data, 1(1), 51–59.
113.
RaghupathiW., & RaghupathiV. (2014). Big data analytics in healthcare: Promise and potential. Health Information Science and Systems, 2(1), 3.
114.
RahmanN., & AldhabanF. (2015, August 2–6). Assessing the effectiveness of big data initiatives. Paper presented at the 2015 Portland International Conference on Management of Engineering and Technology (PICMET), Portland, OR, USA.
115.
RahmanN., & IversonS. (2015). Big data business intelligence in bank risk analysis. International Journal of Business Intelligence Research, 6(2), 55–77.
116.
RajpurohitA. (2013, October 6–9). Big data for business managers—Bridging the gap between potential and value. Paper presented at the 2013 IEEE International Conference on Big Data, Silicon Valley, CA, USA.
RoskiJ.Bo-LinnG. W., & AndrewsT. A. (2014). Creating value in health care through big data: Opportunities and policy implications. Health Affairs, 33(7), 1115–1122.
119.
RossiR., & HiramaK. (2015). Characterizing big data management. Issues in Informing Science and Information Technology, 12, 165–180.
SadowskiJ. (2019). When data is capital: Datafication, accumulation, and extraction. Big Data and Society. Advance online publication. https://doi.org/10.1177/2053951718820549
122.
SaggiM. K., & JainS. (2018). A survey towards an integration of big data analytics to big insights for value-creation. Information Processing and Management, 54(5), 758–790.
123.
SamuelS. J.RvpK.SashidharK., & BharathiC. R. (2015). A survey on big data and its research challenges. ARPN Journal of Engineering and Applied Sciences, 10(8), 3343–3347.
124.
SchroederR. (2016). Big data business models: Challenges and opportunities. Cogent Social Sciences, 2(1), 1166924. Sellami, M., Mezni, H., & Hacid, M. S. (2020). On the use of big data frameworks for big service composition. Journal of Network and Computer Applications, 166, 102732.
125.
SenD.OzturkM., & VayvayO. (2016). An overview of big data for growth in SMEs. Procedia - Social and Behavioral Sciences, 235, 159–167.
126.
ShahN.IraniZ., & SharifA. M. (2017). Big data in an HR context: Exploring organizational change readiness, employee attitudes and behaviors. Journal of Business Research, 70, 366–378.
127.
ShimJ. P.FrenchA. M.GuoC., & JablonskiJ. (2015). Big data and analytics: Issues, solutions, and ROI. Communications of the Association for Information Systems, 37, 797–810.
128.
SpiessJ.T'JoensY.DragneaR.SpencerP., & PhilippartL. (2014). Using big data to improve customer experience and business performance. Bell Labs Technical Journal, 18(4), 3–17.
129.
SunN.MorrisJ. G.XuJ.ZhuX., & XieM. (2014). iCARE: A framework for big data-based banking customer analytics. IBM Journal of Research and Development, 58(5/6), 4: 1–4:9.
Torabi AsrF., & TaboadaM. (2019). Big Data and quality data for fake news and misinformation detection. Big Data and Society, 6(1), 1–14.
133.
ToshniwalR.DastidarK. G., & NathA. (2015). Big data security issues and challenges. International Journal of Innovative Research in Advanced Engineering, 2(2), 6.
134.
UmanL. S. (2011). Systematic reviews and meta-analyses. Journal of the Canadian Academy of Child and Adolescent Psychiatry, 20(1), 57–59.
135.
UpadhyayP., & KumarA. (2020). The intermediating role of organizational culture and internal analytical knowledge between the capability of big data analytics and a firm's performance. International Journal of Information Management, 52, 102100.
136.
VermaJ. P.AgrawalS.PatelB., & PatelA. (2016). Big data analytics: Challenges and applications for text, audio, video, and social media data. International Journal on Soft Computing, Artificial Intelligence and Applications, 5(1), 41–51.
137.
VidgenR.ShawS., & GrantD. B. (2017). Management challenges in creating value from business analytics. European Journal of Operational Research, 261(2), 626–639.
138.
VilajosanaI.LlosaJ.MartinezB.Domingo-PrietoM.AnglesA., & VilajosanaX. (2013). Bootstrapping smart cities through a self-sustainable model based on big data flows. IEEE Communications Magazine, 51(6), 128–134.
139.
WachterS., & MittelstadtB. (2019). A right to reasonable inferences: Rethinking data protection law in the age of big data and AI. Columbia Business Law Review, 2019(2), 494–620.
140.
WambaF. S.AkterS.EdwardsA.ChopinG., & GnanzouD. (2015). How “big data” can make big impact: Findings from a systematic review and a longitudinal case study. International Journal of Production Economics, 165, 234–246.
141.
WambaS. F.GunasekaranA.AkterS.RenS. J.DubeyR., & ChildeS. J. (2017). Big data analytics and firm performance: Effects of dynamic capabilities. Journal of Business Research, 70, 356–365.
142.
WangG.GunasekaranA.NgaiE. W. T., & PapadopoulosT. (2016). Big data analytics in logistics and supply chain management: Certain investigations for research and applications. International Journal of Production Economics, 176, 98–110.
143.
WangY., & HajliN. (2017). Exploring the path to big data analytics success in healthcare. Journal of Business Research, 70, 287–299.
144.
WangY.KungL., & ByrdT. A. (2018a). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological Forecasting and Social Change, 126, 3–13.
145.
WangY.KungL.TingC., & ByrdT. A. (2015, January 5–8). Beyond a technical perspective: Understanding big data capabilities in health care. Paper presented at the 2015 48th Hawaii International Conference on System Sciences, Kauai, HI, USA.
146.
WangY.KungL.WangW. Y. C., & CegielskiC. G. (2018b). An integrated big data analytics-enabled transformation model: Application to health care. Information and Management, 55(1), 64–79.
147.
WangL., & WangG. (2016). Big data in cyber-physical systems, digital manufacturing and industry 4.0. International Journal of Engineering and Manufacturing, 6(4), 1–8.
148.
WardJ. S., & BarkerA. (2013). Undefined by data: A survey of big data definitions. ArXiv, 1309.5821. http://arxiv.org/abs/1309.5821
149.
WatsonH. J. (2014). Tutorial: Big data analytics: Concepts, technologies, and applications. Communications of the Association for Information Systems, 34, 1247–1268.
150.
WengW.-H., & LinW.-T. (2014). Development trends and strategy planning in big data industry. Contemporary Management Research, 10(3), 203–214.
151.
WielkiJ. (2013, September 8–11). Implementation of the big data concept in organizations-possibilities, impediments and challenges. Paper presented at the 2013 Federated Conference on Computer Science and Information Systems, Krakow, Poland. Wolfert, S., Ge, L., Verdouw, C., & Bogaardt, M.-J. (2017). Big data in smart farming – A review. Agricultural Systems, 153, 69–80.
152.
WuS.ChenT.WuY., & LytrasM. (2018). Smart cities in Taiwan: A perspective on big data applications. Sustainability, 10(2), 106.
153.
XiangZ.SchwartzZ.GerdesJ. H., & UysalM. (2015). What can big data and text analytics tell us about hotel guest experience and satisfaction? International Journal of Hospitality Management, 44, 120–130.
154.
XueL., & ZhangY. (2020). The effect of distance on tourist behavior: A study based on social media data. Annals of Tourism Research, 82, 102916.
155.
YasminM.TatogluE.KilicH. S.ZaimS., & DelenD. (2020). Big data analytics capabilities and firm performance: An integrated MCDM approach. Journal of Business Research, 114, 1–15.
156.
YlijokiO., & PorrasJ. (2016). Conceptualizing big data: Analysis of case studies. Intelligent Systems in Accounting, Finance and Management, 23(4), 295–310.
157.
ZhangD. (2013, July 16–18). Inconsistencies in big data. Paper presented at the 2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing, New York, NY, USA.
158.
ZhaoX.YeungK.HuangQ., & SongX. (2015). Improving the predictability of business failure of supply chain finance clients by using external big dataset. Industrial Management and Data Systems, 115(9), 1683–1703.
159.
ZhengK.YangZ.ZhangK.ChatzimisiosP.YangK., & XiangW. (2016). Big data-driven optimization for mobile networks toward 5G. IEEE Network, 30(1), 44–51.
160.
ZhengZ.ZhuJ., & LyuM. R. (2013, June 27–July 2). Service-generated big data and big data-as-a-service: An overview. Paper presented at the 2013 IEEE International Congress on Big Data, Santa Clara, CA, USA.
161.
ZhongR. Y.HuangG. Q.LanS.DaiQ. Y.ChenX., & ZhangT. (2015). A big data approach for logistics trajectory discovery from RFID-enabled production data. International Journal of Production Economics, 165, 260–272.
162.
ZhongR. Y.NewmanS. T.HuangG. Q., & LanS. (2016). Big Data for supply chain management in the service and manufacturing sectors: Challenges, opportunities, and future perspectives. Computers and Industrial Engineering, 101, 572–591.
163.
ZhouX.LiangW.WangK. I., & YangL. T. (2020). Deep correlation mining based on hierarchical hybrid networks for heterogeneous big data recommendations. IEEE Transactions on Computational Social Systems, 8(1), 171–178.
164.
ZhouZ. H.ChawlaN. V.JinY., & WilliamsG. J. (2014). Big data opportunities and challenges: Discussions from data analytics perspectives [discussion forum]. IEEE Computational Intelligence Magazine, 9(4), 62–74.
