Big data in the business environment: an analysis of its contributions to Competitiveness. A Literature Review
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In the era of Industry 4.0, characterized by transformative technological advancements reshaping manufacturing processes, big data has become a common practice in business intelligence. It encompasses the use of data with advanced analytics techniques and plays an important role in business aspects and customer choice. In this context, the primary goal of this research is to comprehend the relationship between big data and the competitiveness of businesses. The research is based on a review of 83 articles published on the Web of Science in the period 2016 and 2023. Through cluster analysis, four groups of research categories are identified in this area (big data and AI in Industry 4.0, analysis of data for decision-making, big data and business innovation, and Internet of Things as a data source). The practical implications of this research are pertinent to organizational management activities involving innovation processes and decision-making, with direct implications for small and midsize enterprises competitiveness. On a theoretical level, the identified categories provide a framework for future research in understanding the connection between big data and competitiveness in the context of industry 4.0.
Jin X, Wah BW, Cheng X, Wang Y. Significance and challenges of big data research. Big data research. 2015;2(2):59-64. DOI: https://doi.org/10.1016/j.bdr.2015.01.006
Bariff ML. Advanced analytics group and intraorganisational power. International Journal of Technology Management. 2019;79(2):108-25. DOI: https://doi.org/10.1504/IJTM.2019.097521
Yang CW, Huang QY, Li ZL, Liu K, Hu F. Big Data and cloud computing: innovation opportunities and challenges. International Journal of Digital Earth. 2017;10(1):13-53. DOI: https://doi.org/10.1080/17538947.2016.1239771
Stone M, Aravopoulou E, Gerardi G, Todeva E, Weinzierl L, Laughlin P, et al. How platforms are transforming customer information management. The Bottom Line. 2017;30(3). DOI: https://doi.org/10.1108/BL-08-2017-0024
Sheng J, Amankwah-Amoah J, Wang XJ. A multidisciplinary perspective of big data in management research. International Journal of Production Economics. 2017;191:97-112.
George G, Haas MR, Pentland A. Big data and management. Academy of Management Briarcliff Manor, NY; 2014. p. 321-6. DOI: https://doi.org/10.5465/amj.2014.4002
Gupta M, George JF. Toward the development of a big data analytics capability. Information & Management. 2016;53(8):1049-64. DOI: https://doi.org/10.1016/j.im.2016.07.004
Hashem IAT, Yaqoob I, Anuar NB, Mokhtar S, Gani A, Khan SU. The rise of “big data” on cloud computing: Review and open research issues. Information Systems. 2015;47:98-115. DOI: https://doi.org/10.1016/j.is.2014.07.006
Jin DH, Kim HJ. Integrated Understanding of Big Data, Big Data Analysis, and Business Intelligence: A Case Study of Logistics. Sustainability. 2018;10(10). DOI: https://doi.org/10.3390/su10103778
Li F, Li T, Liu LJ. Research on the Influence of Economic Globalization on International Relations in the Background of Big Data and Internet of Things. Wireless Communications & Mobile Computing. 2022;2022. DOI: https://doi.org/10.1155/2022/8773395
Ying SS, Liu H. The Application of Big Data in Enterprise Information Intelligent Decision-Making. IEEE Access. 2021;9:120274-84. DOI: https://doi.org/10.1109/ACCESS.2021.3104147
Nagy J, Olah J, Erdei E, Mate D, Popp J. The Role and Impact of Industry 4.0 and the Internet of Things on the Business Strategy of the Value Chain-The Case of Hungary. Sustainability. 2018;10(10). DOI: https://doi.org/10.3390/su10103491
Sheng J, Amankwah-Amoah J, Wang X. A multidisciplinary perspective of big data in management research. International Journal of Production Economics. 2017;191:97-112. DOI: https://doi.org/10.1016/j.ijpe.2017.06.006
Gandomi A, Haider M. Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management. 2015;35(2):137-44. DOI: https://doi.org/10.1016/j.ijinfomgt.2014.10.007
Sivarajah U, Kamal MM, Irani Z, Weerakkody V. Critical analysis of Big Data challenges and analytical methods. Journal of Business Research. 2017;70:263-86. DOI: https://doi.org/10.1016/j.jbusres.2016.08.001
Russom P. Big data analytics. 2011 Contract No.: 4.
Brown B. Connectivity in the Multi-Layered City: Towards the Sustainable City. Open House International. 2011;36(2):24-35. DOI: https://doi.org/10.1108/OHI-02-2011-B0004
Ozdemir V, Hekim N. Birth of Industry 5.0: Making Sense of Big Data with Artificial Intelligence, “The Internet of Things” and Next-Generation Technology Policy. Omics-a Journal of Integrative Biology. 2018;22(1):65-76. DOI: https://doi.org/10.1089/omi.2017.0194
Wright LT, Robin R, Stone M, Aravopoulou E. Adoption of Big Data Technology for Innovation in B2B Marketing. Journal of Business-to-Business Marketing. 2019;26(3-4):281-93. DOI: https://doi.org/10.1080/1051712X.2019.1611082
Mishra D, Gunasekaran A, Papadopoulos T, Childe SJ. Big Data and supply chain management: a review and bibliometric analysis. Annals of Operations Research. 2018;270(1):313-36. DOI: https://doi.org/10.1007/s10479-016-2236-y
Lin KY. Big Data Technology in the Macrodecision-Making Model of Regional Industrial Economic Information Applied Research. Computational Intelligence and Neuroscience. 2022;2022. DOI: https://doi.org/10.1155/2022/7400797
Tranfield D, Denyer D, Smart P. Towards a methodology for developing evidence‐informed management knowledge by means of systematic review. British Journal of Management. 2003;14(3):207-22. DOI: https://doi.org/10.1111/1467-8551.00375
Manyika J, Chui M, Brown B, Bughin J, Dobbs R, Roxburgh C, et al. Big data: The next frontier for innovation, competition, and productivity: McKinsey Global Institute; 2011.
Feng Z, Guo X, Zeng D, Chen Y, Chen G. On the research frontiers of business management in the context of Big Data. Journal of Management sciences in china. 2013;16(1):1-9.
Llopis AC, Rubio F, Valero F. Impact of digital transformation on the automotive industry. Technological Forecasting and Social Change. 2021;162. DOI: https://doi.org/10.1016/j.techfore.2020.120343
Saniuk S, Saniuk A, Caganova D. Cyber Industry Networks as an environment of the Industry 4.0 implementation. Wireless Networks. 2021;27(3):1649-55. DOI: https://doi.org/10.1007/s11276-019-02079-3
Jiang WX. An Intelligent Supply Chain Information Collaboration Model Based on Internet of Things and Big Data. IEEE Access. 2019;7:58324-35. DOI: https://doi.org/10.1109/ACCESS.2019.2913192
Li D, Wang XJ. Dynamic supply chain decisions based on networked sensor data: an application in the chilled food retail chain. International Journal of Production Research. 2017;55(17):5127-41. DOI: https://doi.org/10.1080/00207543.2015.1047976
Valamede LS, Akkari ACS. Lean 4.0: A New Holistic Approach for the Integration of Lean Manufacturing Tools and Digital Technologies. International Journal of Mathematical Engineering and Management Sciences. 2020;5(5):851-68. DOI: https://doi.org/10.33889/IJMEMS.2020.5.5.066
Feng YX, Zhao YL, Zheng H, Li ZW, Tan JR. Data-driven product design toward intelligent manufacturing: A review. International Journal of Advanced Robotic Systems. 2020;17(2). DOI: https://doi.org/10.1177/1729881420911257
Popkova EG, Sergi BS, Rezaei M, Ferraris A. Digitalisation in transport and logistics: a roadmap for entrepreneurship in Russia. International Journal of Technology Management. 2021;87(1):7-28. DOI: https://doi.org/10.1504/IJTM.2021.118887
Huang SH. Product Innovation Design Method Based on BP Neural Network. Advances in Multimedia. 2022;2022. DOI: https://doi.org/10.1155/2022/6830892
Rana NP, Chatterjee S, Dwivedi YK, Akter S. Understanding dark side of artificial intelligence (AI) integrated business analytics: assessing firm’s operational inefficiency and competitiveness. European Journal of Information Systems. 2022;31(3):364-87. DOI: https://doi.org/10.1080/0960085X.2021.1955628
Davenport TH. From analytics to artificial intelligence. Journal of Business Analytics. 2018;1(2):73-80. DOI: https://doi.org/10.1080/2573234X.2018.1543535
Kersting K, Meyer U. From Big Data to Big Artificial Intelligence? KI - Künstliche Intelligenz. 2018;32(1):3-8. DOI: https://doi.org/10.1007/s13218-017-0523-7
Jagatheesaperumal SK, Rahouti M, Ahmad K, Al-Fuqaha A, Guizani M. The duo of artificial intelligence and big data for industry 4.0: Applications, techniques, challenges, and future research directions. Ieee Internet of Things Journal. 2021;9(15):12861-85. DOI: https://doi.org/10.1109/JIOT.2021.3139827
Yoo SK, Kim BY. A Decision-Making Model for Adopting a Cloud Computing System. Sustainability. 2018;10(8). DOI: https://doi.org/10.3390/su10082952
Saritas O, Bakhtin P, Kuzminov I, Khabirova E. Big data augmentated business trend identification: the case of mobile commerce. Scientometrics. 2021;126(2):1553-79. DOI: https://doi.org/10.1007/s11192-020-03807-9
Ramos CMQ, Martins DJ, Serra F, Lam R, Cardoso PJS, Correia MB, et al. Framework for a Hospitality Big Data Warehouse: The Implementation of an Efficient Hospitality Business Intelligence System. International Journal of Information Systems in the Service Sector. 2017;9(2):27-45. DOI: https://doi.org/10.4018/IJISSS.2017040102
Gyulai D, Bergmann J, Gallina V, Gaal A, editors. Towards a connected factory: Shop-floor data analytics in cyber-physical environments. 7th CIRP Global Web Conference on Towards Shifted Production Value Stream Patterns through Inference of Data, Models, and Technology (CIRPe); 2019 Oct 16-18; Electr Network; 2019. DOI: https://doi.org/10.1016/j.procir.2020.01.016
Bustamante A, Sebastia L, Onaindia E. BITOUR: A Business Intelligence Platform for Tourism Analysis. Isprs International Journal of Geo-Information. 2020;9(11). DOI: https://doi.org/10.3390/ijgi9110671
Miller GJ, editor. Comparative Analysis of Big Data Analytics and BI Projects. Federated Conference on Computer Science and Information Systems (FedCSIS); 2018 Sep 09-12; Poznan, POLAND; 2018. DOI: https://doi.org/10.15439/2018F125
Bian WY, Bian WM. Construction of Application Model of Accounting Framework Platform for Industry-Finance Integration Management under the Background of Multimedia Technology. Mobile Information Systems. 2022;2022. DOI: https://doi.org/10.1155/2022/1151226
Ji GJ, Yu MH, Tan KH. Cooperative Innovation Behavior Based on Big Data. Mathematical Problems in Engineering. 2020;2020. DOI: https://doi.org/10.1155/2020/4385810
Yuan ZH, Qin WZ, Zhao JS. Smart Manufacturing for the Oil Refining and Petrochemical Industry. Engineering. 2017;3(2):179-82. DOI: https://doi.org/10.1016/J.ENG.2017.02.012
Del Vecchio P, Mele G, Ndou V, Secundo G. Open Innovation and Social Big Data for Sustainability: Evidence from the Tourism Industry. Sustainability. 2018;10(9). DOI: https://doi.org/10.3390/su10093215
Ciampi F, Demi S, Magrini A, Marzi G, Papa A. Exploring the impact of big data analytics capabilities on business model innovation: The mediating role of entrepreneurial orientation. Journal of Business Research. 2021;123:1-13. DOI: https://doi.org/10.1016/j.jbusres.2020.09.023
Gianniti E, Ciavotta M, Ardagna D. Optimizing Quality-Aware Big Data Applications in the Cloud. Ieee Transactions on Cloud Computing. 2021;9(2):737-52. DOI: https://doi.org/10.1109/TCC.2018.2874944
Al Zahrani A, Al Hebbi M. Big Data Major Security Issues: Challenges and Defense Strategies. Tehnicki Glasnik-Technical Journal. 2022;16(2):197-204. DOI: https://doi.org/10.31803/tg-20220124135330
Wang QH. Research on Basic Information of Enterprise Electronization under the Background of Big Data. Mathematical Problems in Engineering. 2022;2022. DOI: https://doi.org/10.1155/2022/3751828
Gebremichael T, Ledwaba LPI, Eldefrawy MH, Hancke GP, Pereira N, Gidlund M, et al. Security and Privacy in the Industrial Internet of Things: Current Standards and Future Challenges. IEEE Access. 2020;8:152351-66. DOI: https://doi.org/10.1109/ACCESS.2020.3016937
Xue LQ. Financial Big Data Based on Internet of Things and Wireless Network Communication. Wireless Communications & Mobile Computing. 2021;2021. DOI: https://doi.org/10.1155/2021/8944618
Barton M, Budjac R, Tanuska P, Gaspar G, Schreiber P. Identification Overview of Industry 4.0 Essential Attributes and Resource-Limited Embedded Artificial-Intelligence-of-Things Devices for Small and Medium-Sized Enterprises. Applied Sciences-Basel. 2022;12(11). DOI: https://doi.org/10.3390/app12115672
Zhao X, Yan ZF. Analysis of Energy Conservation Big Data of Embedded Large Public Buildings and Construction of the Information Model by 5G. Wireless Communications & Mobile Computing. 2022;2022. DOI: https://doi.org/10.1155/2022/3023323
Marjani M, Nasaruddin F, Gani A, Karim A, Hashem IAT, Siddiqa A, et al. Big IoT Data Analytics: Architecture, Opportunities, and Open Research Challenges. IEEE Access. 2017;5:5247-61. DOI: https://doi.org/10.1109/ACCESS.2017.2689040
Kusi-Sarpong S, Orji IJ, Gupta H, Kunc M. Risks associated with the implementation of big data analytics in sustainable supply chains. Omega-International Journal of Management Science. 2021;105. DOI: https://doi.org/10.1016/j.omega.2021.102502
Morales PG, España JAA, Zárate JEG, González CCO, Frías TER. La nube al servicio de las pymes en dirección a la industria 4.0. Pistas Educativas. 2017;39(126).
Lobova SV, Bykovskaya NV, Vlasova IM, Sidorenko OV. Successful experience of formation of industry 4.0 in various countries. Industry 40: Industrial Revolution of the 21st Century: Springer; 2019. p. 121-9. DOI: https://doi.org/10.1007/978-3-319-94310-7_12
Wang S, Wan J, Zhang D, Li D, Zhang C. Towards smart factory for industry 4.0: a self-organized multi-agent system with big data based feedback and coordination. Computer Networks. 2016;101:158-68. DOI: https://doi.org/10.1016/j.comnet.2015.12.017
Rüßmann M, Lorenz M, Gerbert P, Waldner M, Justus J, Engel P, et al. Industry 4.0: The future of productivity and growth in manufacturing industries. Boston Consulting Group. 2015;9(1):54-89.
Yu H, Lee H, Jeon H. What is 5G? Emerging 5G Mobile Services and Network Requirements. Sustainability. 2017;9(10). DOI: https://doi.org/10.3390/su9101848
Berawi MA. Utilizing big data in industry 4.0: Managing competitive advantages and business ethics. International Journal of Technology. 2018;3(1):430-3. DOI: https://doi.org/10.14716/ijtech.v9i3.1948
Shan S, Luo Y, Zhou Y, Wei Y. Big data analysis adaptation and enterprises’ competitive advantages: the perspective of dynamic capability and resource-based theories. Technology Analysis & Strategic Management. 2019;31(4):406-20. DOI: https://doi.org/10.1080/09537325.2018.1516866
Wong D. Data is the next frontier, analytics the new tool. Five Trends in Big Data and Analytics, and Their Implications for Innovation and Organizations. 2012;London: Big Innovation Centre.
Jabrane K, Bousmah M. A New Approach for Training Cobots from Small Amount of Data in Industry 5.0. International Journal of Advanced Computer Science and Applications. 2021;12(10):634-46. DOI: https://doi.org/10.14569/IJACSA.2021.0121070
Golfarelli M, Rizzi S, Cella I, editors. Beyond data warehousing: what’s next in business intelligence? Proceedings of the 7th ACM international workshop on Data warehousing and OLAP; 2004. DOI: https://doi.org/10.1145/1031763.1031765
Balachandran BM, Prasad S. Challenges and benefits of deploying big data analytics in the cloud for business intelligence. Procedia Computer Science. 2017;112:1112-22. DOI: https://doi.org/10.1016/j.procs.2017.08.138
Wang H, Xu Z, Fujita H, Liu S. Towards felicitous decision making: An overview on challenges and trends of Big Data. Information Sciences. 2016;367-368:747-65. DOI: https://doi.org/10.1016/j.ins.2016.07.007
Ndou V, Beqiri M. Introduction for the special Issue on BIG DATA. Electronic Journal of Applied Statistical Analysis: Decision Support Systems and Services Evaluation. 2014;5(1):1-3.
Chesbrough H. Open business models: How to thrive in the new innovation landscape. 1st edition ed: Harvard Business Press; 2006.
Dalenogare LS, Benitez GB, Ayala NF, Frank AG. The expected contribution of Industry 4.0 technologies for industrial performance. International Journal of Production Economics. 2018;204:383-94. DOI: https://doi.org/10.1016/j.ijpe.2018.08.019
Hanga KM, Kovalchuk Y. Machine learning and multi-agent systems in oil and gas industry applications: A survey. Computer Science Review. 2019;34:100191. DOI: https://doi.org/10.1016/j.cosrev.2019.08.002
Konanahalli A, Marinelli M, Oyedele L. Drivers and Challenges Associated With the Implementation of Big Data Within UK Facilities Management Sector: An Exploratory Factor Analysis Approach. IEEE Transactions on Engineering Management. 2022;69(4):916-29. DOI: https://doi.org/10.1109/TEM.2019.2959914
Wilson HJ, Daugherty PR. Collaborative intelligence: Humans and AI are joining forces. Harvard Business Review. 2018;96(4):114-23.
Fan J, Han F, Liu H. Challenges of big data analysis. National science review. 2014;1(2):293-314. DOI: https://doi.org/10.1093/nsr/nwt032
Kayser V, Nehrke B, Zubovic D. Data science as an innovation challenge: From big data to value proposition. Technology Innovation Management Review. 2018;8(3). DOI: https://doi.org/10.22215/timreview/1143
Younan M, Houssein EH, Elhoseny M, Ali AA. Challenges and recommended technologies for the industrial internet of things: A comprehensive review. Measurement. 2020;151:107198. DOI: https://doi.org/10.1016/j.measurement.2019.107198
Grover V, Chiang RH, Liang T-P, Zhang D. Creating strategic business value from big data analytics: A research framework. Journal of Management Information Systems. 2018;35(2):388-423. DOI: https://doi.org/10.1080/07421222.2018.1451951
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