IDEAS home Printed from https://ideas.repec.org/a/spr/gjofsm/v18y2017i3d10.1007_s40171-017-0159-3.html
   My bibliography  Save this article

Big Data Analytics: A Review on Theoretical Contributions and Tools Used in Literature

Author

Listed:
  • Purva Grover

    (Indian Institute of Technology Delhi)

  • Arpan Kumar Kar

    (Indian Institute of Technology Delhi)

Abstract

The importance of data science and big data analytics is growing very fast as organizations are gearing up to leverage their information assets to gain competitive advantage. The flexibility offered through big data analytics empowers functional as well as firm-level performance. In the first phase of the study, we attempt to analyze the research on big data published in high-quality business management journals. The analysis was visualized using tools for big data and text mining to understand the dominant themes and how they are connected. Subsequently, an industry-specific categorization of the studies was done to understand the key use cases. It was found that most of the existing research focuses majorly on consumer discretionary, followed by public administration. Methodologically, a major focus in such exploration is in social media analytics, text mining and machine learning applications for meeting objectives in marketing and supply chain management. However, it was found that not much focus was highlighted in these studies to demonstrate the tools used for the analysis. To address this gap, this study also discusses the evolution, types and usage of big data tools. The brief overview of big data technologies grouped by the services they enable and some of their applications are presented. The study categorizes these tools into big data analysis platforms, databases and data warehouses, programming languages, search tools, and data aggregation and transfer tools. Finally, based on the review, future directions for exploration in big data has been provided for academic and practice.

Suggested Citation

  • Purva Grover & Arpan Kumar Kar, 2017. "Big Data Analytics: A Review on Theoretical Contributions and Tools Used in Literature," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 18(3), pages 203-229, September.
  • Handle: RePEc:spr:gjofsm:v:18:y:2017:i:3:d:10.1007_s40171-017-0159-3
    DOI: 10.1007/s40171-017-0159-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40171-017-0159-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s40171-017-0159-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Graham, Gary & Mehmood, Rashid, 2014. "The strategic prototype “crime-sourcing” and the science/science fiction behind it," Technological Forecasting and Social Change, Elsevier, vol. 84(C), pages 86-92.
    2. Jimmy Q. Li & Paat Rusmevichientong & Duncan Simester & John N. Tsitsiklis & Spyros I. Zoumpoulis, 2015. "The Value of Field Experiments," Management Science, INFORMS, vol. 61(7), pages 1722-1740, July.
    3. Schneider, Matthew J. & Gupta, Sachin, 2016. "Forecasting sales of new and existing products using consumer reviews: A random projections approach," International Journal of Forecasting, Elsevier, vol. 32(2), pages 243-256.
    4. Mohammed Hussain & Mohamed Al-Mourad & Sujith Mathew & Abdullah Hussein, 2017. "Mining Educational Data for Academic Accreditation: Aligning Assessment with Outcomes," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 18(1), pages 51-60, March.
    5. Xu, Zhenning & Frankwick, Gary L. & Ramirez, Edward, 2016. "Effects of big data analytics and traditional marketing analytics on new product success: A knowledge fusion perspective," Journal of Business Research, Elsevier, vol. 69(5), pages 1562-1566.
    6. Julia Lane, 2016. "Big Data For Public Policy: The Quadruple Helix," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 35(3), pages 708-715, June.
    7. Stephen L. France & Sanjoy Ghose, 2016. "An Analysis and Visualization Methodology for Identifying and Testing Market Structure," Marketing Science, INFORMS, vol. 35(1), pages 182-197, January.
    8. Brown, Christopher L. & Cavusgil, S. Tamer & Lord, A. Wayne, 2015. "Country-risk measurement and analysis: A new conceptualization and managerial tool," International Business Review, Elsevier, vol. 24(2), pages 246-265.
    9. Kelly D. Martin & Patrick E. Murphy, 2017. "The role of data privacy in marketing," Journal of the Academy of Marketing Science, Springer, vol. 45(2), pages 135-155, March.
    10. Daniel M. Ringel & Bernd Skiera, 2016. "Visualizing Asymmetric Competition Among More Than 1,000 Products Using Big Search Data," Marketing Science, INFORMS, vol. 35(3), pages 511-534, May.
    11. Jonathan J.J.M. Seddon & Wendy L. Currie, 2017. "A model for unpacking big data analytics in high-frequency trading," Post-Print hal-01404316, HAL.
    12. Ron S. Jarmin & Amy B. O'Hara, 2016. "Big Data And The Transformation Of Public Policy Analysis," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 35(3), pages 715-721, June.
    13. Zhong, Ray Y. & Huang, George Q. & Lan, Shulin & Dai, Q.Y. & Chen, Xu & Zhang, T., 2015. "A big data approach for logistics trajectory discovery from RFID-enabled production data," International Journal of Production Economics, Elsevier, vol. 165(C), pages 260-272.
    14. Kallinikos, Jannis & Constantiou, Ioanna D., 2015. "Big data revisited: a rejoinder," LSE Research Online Documents on Economics 63020, London School of Economics and Political Science, LSE Library.
    15. Aron Culotta & Jennifer Cutler, 2016. "Mining Brand Perceptions from Twitter Social Networks," Marketing Science, INFORMS, vol. 35(3), pages 343-362, May.
    16. Bradlow, Eric T. & Gangwar, Manish & Kopalle, Praveen & Voleti, Sudhir, 2017. "The Role of Big Data and Predictive Analytics in Retailing," Journal of Retailing, Elsevier, vol. 93(1), pages 79-95.
    17. Liu, Yong & Teichert, Thorsten & Rossi, Matti & Li, Hongxiu & Hu, Feng, 2017. "Big data for big insights: Investigating language-specific drivers of hotel satisfaction with 412,784 user-generated reviews," Tourism Management, Elsevier, vol. 59(C), pages 554-563.
    18. Jun, Seung-Pyo & Park, Do-Hyung & Yeom, Jaeho, 2014. "The possibility of using search traffic information to explore consumer product attitudes and forecast consumer preference," Technological Forecasting and Social Change, Elsevier, vol. 86(C), pages 237-253.
    19. Erevelles, Sunil & Fukawa, Nobuyuki & Swayne, Linda, 2016. "Big Data consumer analytics and the transformation of marketing," Journal of Business Research, Elsevier, vol. 69(2), pages 897-904.
    20. S. Vijayakumar Bharathi, 2017. "Prioritizing and Ranking the Big Data Information Security Risk Spectrum," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 18(3), pages 183-201, September.
    21. Julia Lane & Paul T. Decker, 2016. "Editors' Overview of Special Section on Big Data and Public Policy," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 35(4), pages 881-883, September.
    22. Nicky J. Welton & Howard H. Z. Thom, 2015. "Value of Information," Medical Decision Making, , vol. 35(5), pages 564-566, July.
    23. Wang, Pu & Liu, Bidong & Hong, Tao, 2016. "Electric load forecasting with recency effect: A big data approach," International Journal of Forecasting, Elsevier, vol. 32(3), pages 585-597.
    24. Li, Xin & Pan, Bing & Law, Rob & Huang, Xiankai, 2017. "Forecasting tourism demand with composite search index," Tourism Management, Elsevier, vol. 59(C), pages 57-66.
    25. Thomas D. Cook, 2014. "“Big Data” In Research On Social Policy," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 33(2), pages 544-547, March.
    26. Prasanna Tambe, 2014. "Big Data Investment, Skills, and Firm Value," Management Science, INFORMS, vol. 60(6), pages 1452-1469, June.
    27. Wang, Yichuan & Hajli, Nick, 2017. "Exploring the path to big data analytics success in healthcare," Journal of Business Research, Elsevier, vol. 70(C), pages 287-299.
    28. Mariani, Marcello M. & Di Felice, Marco & Mura, Matteo, 2016. "Facebook as a destination marketing tool: Evidence from Italian regional Destination Management Organizations," Tourism Management, Elsevier, vol. 54(C), pages 321-343.
    29. Roland T. Rust & Ming-Hui Huang, 2014. "The Service Revolution and the Transformation of Marketing Science," Marketing Science, INFORMS, vol. 33(2), pages 206-221, March.
    30. Seddon, Jonathan J.J.M. & Currie, Wendy L., 2017. "A model for unpacking big data analytics in high-frequency trading," Journal of Business Research, Elsevier, vol. 70(C), pages 300-307.
    31. Junliang Wang & Jie Zhang, 2016. "Big data analytics for forecasting cycle time in semiconductor wafer fabrication system," International Journal of Production Research, Taylor & Francis Journals, vol. 54(23), pages 7231-7244, December.
    32. Jagjit Singh Srai & Mukesh Kumar & Gary Graham & Wendy Phillips & James Tooze & Simon Ford & Paul Beecher & Baldev Raj & Mike Gregory & Manoj Kumar Tiwari & B. Ravi & Andy Neely & Ravi Shankar & Fiona, 2016. "Distributed manufacturing: scope, challenges and opportunities," International Journal of Production Research, Taylor & Francis Journals, vol. 54(23), pages 6917-6935, December.
    33. Njuguna, Christopher & McSharry, Patrick, 2017. "Constructing spatiotemporal poverty indices from big data," Journal of Business Research, Elsevier, vol. 70(C), pages 318-327.
    34. Jian Jin & Ying Liu & Ping Ji & Hongguang Liu, 2016. "Understanding big consumer opinion data for market-driven product design," International Journal of Production Research, Taylor & Francis Journals, vol. 54(10), pages 3019-3041, May.
    35. Mohan Priya & Paulraj Ranjith Kumar, 2015. "A novel intelligent approach for predicting atherosclerotic individuals from big data for healthcare," International Journal of Production Research, Taylor & Francis Journals, vol. 53(24), pages 7517-7532, December.
    36. Sun, Edward W. & Chen, Yi-Ting & Yu, Min-Teh, 2015. "Generalized optimal wavelet decomposing algorithm for big financial data," International Journal of Production Economics, Elsevier, vol. 165(C), pages 194-214.
    37. Milas, Goran & Mlacic, Boris, 2007. "Brand personality and human personality: Findings from ratings of familiar Croatian brands," Journal of Business Research, Elsevier, vol. 60(6), pages 620-626, June.
    38. Tan, Kim Hua & Zhan, YuanZhu & Ji, Guojun & Ye, Fei & Chang, Chingter, 2015. "Harvesting big data to enhance supply chain innovation capabilities: An analytic infrastructure based on deduction graph," International Journal of Production Economics, Elsevier, vol. 165(C), pages 223-233.
    39. Zhang, Lingyun & Lan, Chaoying & Qi, Fei & Wu, Ping, 2017. "Development pattern, classification and evaluation of the tourism academic community in China in the last ten years: From the perspective of big data of articles of tourism academic journals," Tourism Management, Elsevier, vol. 58(C), pages 235-244.
    40. Paul T. Decker, 2014. "Presidential Address: False Choices, Policy Framing, and the Promise of “Big Data”," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 33(2), pages 252-262, March.
    41. Christof Weinhardt & Arun Anandasivam & Benjamin Blau & Nikolay Borissov & Thomas Meinl & Wibke Michalk & Jochen Stößer, 2009. "Cloud Computing – A Classification, Business Models, and Research Directions," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 1(5), pages 391-399, October.
    42. Akter, Shahriar & Wamba, Samuel Fosso & Gunasekaran, Angappa & Dubey, Rameshwar & Childe, Stephen J., 2016. "How to improve firm performance using big data analytics capability and business strategy alignment?," International Journal of Production Economics, Elsevier, vol. 182(C), pages 113-131.
    43. Michael Trusov & Liye Ma & Zainab Jamal, 2016. "Crumbs of the Cookie: User Profiling in Customer-Base Analysis and Behavioral Targeting," Marketing Science, INFORMS, vol. 35(3), pages 405-426, May.
    44. Shah, Naimatullah & Irani, Zahir & Sharif, Amir M., 2017. "Big data in an HR context: Exploring organizational change readiness, employee attitudes and behaviors," Journal of Business Research, Elsevier, vol. 70(C), pages 366-378.
    45. Ingrid Gould Ellen & Keren Mertens Horn & Amy Ellen Schwartz, 2016. "Why Don't Housing Choice Voucher Recipients Live Near Better Schools? Insights from Big Data," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 35(4), pages 884-905, September.
    46. Tingliang Huang & Jan A. Van Mieghem, 2014. "Clickstream Data and Inventory Management: Model and Empirical Analysis," Production and Operations Management, Production and Operations Management Society, vol. 23(3), pages 333-347, March.
    47. Raun, Janika & Ahas, Rein & Tiru, Margus, 2016. "Measuring tourism destinations using mobile tracking data," Tourism Management, Elsevier, vol. 57(C), pages 202-212.
    48. Dimitris Bertsimas & Nathan Kallus & Amjad Hussain, 2016. "Inventory Management in the Era of Big Data," Production and Operations Management, Production and Operations Management Society, vol. 25(12), pages 2006-2009, December.
    49. Chae, Bongsug (Kevin), 2015. "Insights from hashtag #supplychain and Twitter Analytics: Considering Twitter and Twitter data for supply chain practice and research," International Journal of Production Economics, Elsevier, vol. 165(C), pages 247-259.
    50. Alnoor Bhimani & Leslie Willcocks, 2014. "Digitisation, 'Big Data' and the transformation of accounting information," Accounting and Business Research, Taylor & Francis Journals, vol. 44(4), pages 469-490, August.
    51. Miles Lubin & Iain Dunning, 2015. "Computing in Operations Research Using Julia," INFORMS Journal on Computing, INFORMS, vol. 27(2), pages 238-248, May.
    52. Stefan Bock & Filiz Isik, 2015. "A new two-dimensional performance measure in purchase order sizing," International Journal of Production Research, Taylor & Francis Journals, vol. 53(16), pages 4951-4962, August.
    53. Hazen, Benjamin T. & Boone, Christopher A. & Ezell, Jeremy D. & Jones-Farmer, L. Allison, 2014. "Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications," International Journal of Production Economics, Elsevier, vol. 154(C), pages 72-80.
    54. Gunter, Ulrich & Önder, Irem, 2016. "Forecasting city arrivals with Google Analytics," Annals of Tourism Research, Elsevier, vol. 61(C), pages 199-212.
    55. Lee, Won Sang & Han, Eun Jin & Sohn, So Young, 2015. "Predicting the pattern of technology convergence using big-data technology on large-scale triadic patents," Technological Forecasting and Social Change, Elsevier, vol. 100(C), pages 317-329.
    56. Mukesh Kumar & Gary Graham & Patrick Hennelly & Jagjit Srai, 2016. "How will smart city production systems transform supply chain design: a product-level investigation," International Journal of Production Research, Taylor & Francis Journals, vol. 54(23), pages 7181-7192, December.
    57. Edwards, David J. & Pärn, Erika & Love, Peter E.D. & El-Gohary, Hatem, 2017. "Research note: Machinery, manumission, and economic machinations," Journal of Business Research, Elsevier, vol. 70(C), pages 391-394.
    58. Zhang, Yi & Zhang, Guangquan & Chen, Hongshu & Porter, Alan L. & Zhu, Donghua & Lu, Jie, 2016. "Topic analysis and forecasting for science, technology and innovation: Methodology with a case study focusing on big data research," Technological Forecasting and Social Change, Elsevier, vol. 105(C), pages 179-191.
    59. Kim, Jiyoung & Lee, Yeon-Ok & Park, Han Woo, 2016. "Delineating the complex use of a political podcast in South Korea by hybrid web indicators: The case of the Nakkomsu Twitter network," Technological Forecasting and Social Change, Elsevier, vol. 110(C), pages 42-50.
    60. Green, Kesten C. & Armstrong, J. Scott, 2015. "Simple versus complex forecasting: The evidence," Journal of Business Research, Elsevier, vol. 68(8), pages 1678-1685.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sheng, Jie & Amankwah-Amoah, Joseph & Wang, Xiaojun, 2017. "A multidisciplinary perspective of big data in management research," International Journal of Production Economics, Elsevier, vol. 191(C), pages 97-112.
    2. Acciarini, Chiara & Cappa, Francesco & Boccardelli, Paolo & Oriani, Raffaele, 2023. "How can organizations leverage big data to innovate their business models? A systematic literature review," Technovation, Elsevier, vol. 123(C).
    3. Claudio Vitari & Elisabetta Raguseo, 2019. "Big data analytics business value and firm performance: Linking with environmental context," Post-Print hal-02293765, HAL.
    4. Pournader, Mehrdokht & Ghaderi, Hadi & Hassanzadegan, Amir & Fahimnia, Behnam, 2021. "Artificial intelligence applications in supply chain management," International Journal of Production Economics, Elsevier, vol. 241(C).
    5. Roßmann, Bernhard & Canzaniello, Angelo & von der Gracht, Heiko & Hartmann, Evi, 2018. "The future and social impact of Big Data Analytics in Supply Chain Management: Results from a Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 135-149.
    6. Dawn Iacobucci & Maria Petrescu & Anjala Krishen & Michael Bendixen, 2019. "The state of marketing analytics in research and practice," Journal of Marketing Analytics, Palgrave Macmillan, vol. 7(3), pages 152-181, September.
    7. Patrick Mikalef & Ilias O. Pappas & John Krogstie & Michail Giannakos, 2018. "Big data analytics capabilities: a systematic literature review and research agenda," Information Systems and e-Business Management, Springer, vol. 16(3), pages 547-578, August.
    8. J. Piet Hausberg & Kirsten Liere-Netheler & Sven Packmohr & Stefanie Pakura & Kristin Vogelsang, 2019. "Research streams on digital transformation from a holistic business perspective: a systematic literature review and citation network analysis," Journal of Business Economics, Springer, vol. 89(8), pages 931-963, December.
    9. Ghasemaghaei, Maryam & Calic, Goran, 2020. "Assessing the impact of big data on firm innovation performance: Big data is not always better data," Journal of Business Research, Elsevier, vol. 108(C), pages 147-162.
    10. Ghasemaghaei, Maryam & Calic, Goran, 2019. "Does big data enhance firm innovation competency? The mediating role of data-driven insights," Journal of Business Research, Elsevier, vol. 104(C), pages 69-84.
    11. de Camargo Fiorini, Paula & Roman Pais Seles, Bruno Michel & Chiappetta Jabbour, Charbel Jose & Barberio Mariano, Enzo & de Sousa Jabbour, Ana Beatriz Lopes, 2018. "Management theory and big data literature: From a review to a research agenda," International Journal of Information Management, Elsevier, vol. 43(C), pages 112-129.
    12. Ray Qing Cao & Dara G. Schniederjans & Vicky Ching Gu, 2021. "Stakeholder sentiment in service supply chains: big data meets agenda-setting theory," Service Business, Springer;Pan-Pacific Business Association, vol. 15(1), pages 151-175, March.
    13. Elisabetta Raguseo & Claudio Vitari, 2017. "Investments in big data analytics and firm performance: an empirical investigation of direct and mediating effects," Grenoble Ecole de Management (Post-Print) halshs-01923259, HAL.
    14. El-Haddadeh, Ramzi & Osmani, Mohamad & Hindi, Nitham & Fadlalla, Adam, 2021. "Value creation for realising the sustainable development goals: Fostering organisational adoption of big data analytics," Journal of Business Research, Elsevier, vol. 131(C), pages 402-410.
    15. Imran Bashir Dar & Muhammad Bashir Khan & Abdul Zahid Khan & Bahaudin G. Mujtaba, 2021. "A qualitative analysis of the marketing analytics literature: where would ethical issues and legality rank?," Journal of Marketing Analytics, Palgrave Macmillan, vol. 9(3), pages 242-261, September.
    16. Raut, Rakesh D. & Mangla, Sachin Kumar & Narwane, Vaibhav S. & Dora, Manoj & Liu, Mengqi, 2021. "Big Data Analytics as a mediator in Lean, Agile, Resilient, and Green (LARG) practices effects on sustainable supply chains," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    17. Conboy, Kieran & Mikalef, Patrick & Dennehy, Denis & Krogstie, John, 2020. "Using business analytics to enhance dynamic capabilities in operations research: A case analysis and research agenda," European Journal of Operational Research, Elsevier, vol. 281(3), pages 656-672.
    18. Olabode, Oluwaseun E. & Boso, Nathaniel & Hultman, Magnus & Leonidou, Constantinos N., 2022. "Big data analytics capability and market performance: The roles of disruptive business models and competitive intensity," Journal of Business Research, Elsevier, vol. 139(C), pages 1218-1230.
    19. Elisabetta Raguseo & Claudio Vitari, 2017. "Investments in big data analytics and firm performance: an empirical investigation of direct and mediating effects," Post-Print halshs-01923259, HAL.
    20. Korayim, Diana & Chotia, Varun & Jain, Girish & Hassan, Sharfa & Paolone, Francesco, 2024. "How big data analytics can create competitive advantage in high-stake decision forecasting? The mediating role of organizational innovation," Technological Forecasting and Social Change, Elsevier, vol. 199(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:gjofsm:v:18:y:2017:i:3:d:10.1007_s40171-017-0159-3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.