How ‘Big Data’ Can Make Big Impact: Findings from a Systematic Review and a Longitudinal Case Study

Big data has the potential to revolutionize the art of management. Despite the high operational and strategic impacts, there is a paucity of empirical research to assess the business value of big data. Drawing on a systematic review and case study findings, this paper presents an interpretive framework that analyzes the definitional perspectives and the applications of big data. The paper also provides a general taxonomy that helps broaden the understanding of big data and its role in capturing business value. The synthesis of the diverse concepts within the literature on big data provides deeper insights into achieving value through big data strategy and implementation.

[1]  Yong Hu,et al.  The application of data mining techniques in financial fraud detection: A classification framework and an academic review of literature , 2011, Decis. Support Syst..

[2]  M. Lim,et al.  RFID in the warehouse: A literature analysis (1995–2010) of its applications, benefits, challenges and future trends , 2013 .

[3]  J. Mervis U.S. science policy. Agencies rally to tackle big data. , 2012, Science.

[4]  William H. Dutton,et al.  Clouds, big data, and smart assets: Ten tech-enabled business trends to watch , 2010 .

[5]  Helmut Krcmar,et al.  Big Data , 2014, Wirtschaftsinf..

[6]  Si’en Chen,et al.  Analytics: The real-world use of big data in financial services studying with judge system events , 2016, Journal of Shanghai Jiaotong University (Science).

[7]  K. Cukier,et al.  The Rise of Big Data , 2013 .

[8]  Werner Callebaut,et al.  Scientific perspectivism: A philosopher of science's response to the challenge of big data biology. , 2012, Studies in history and philosophy of biological and biomedical sciences.

[9]  Sheila Anderson,et al.  Taking the Long View: From e-Science Humanities to Humanities Digital Ecosystems , 2012 .

[10]  Soumendra Mohanty,et al.  “Big Data” in the Enterprise , 2013 .

[11]  Tim Highfield Talking of Many Things: Using Topical Networks to Study Discussions in Social Media , 2012 .

[12]  Krzysztof Janowicz,et al.  Observation‐Driven Geo‐Ontology Engineering , 2012, Trans. GIS.

[13]  Ian T. Foster,et al.  Software as a service for data scientists , 2012, Commun. ACM.

[14]  Swati Agarwal The Secret Life of DATA STEP , 2013 .

[15]  D. Coddington,et al.  The big deal about big data. , 2013, Healthcare financial management : journal of the Healthcare Financial Management Association.

[16]  S. Thompson The perils of partnering in developing markets. , 2012, Harvard business review.

[17]  Steven Ruggles,et al.  Big Data: Large-Scale Historical Infrastructure from the Minnesota Population Center , 2011, Historical methods.

[18]  I. Misztal Breeding and Genetics Symposium : Really Big Data : Processing and Analysis of Very Large Datasets , 2011 .

[19]  Colin Tankard,et al.  Big data security , 2012, Netw. Secur..

[20]  Eric W.T. Ngai,et al.  Implementing an RFID-based manufacturing process management system: Lessons learned and success factors , 2012 .

[21]  Danny Bradbury Data mining with LinkedIn , 2011 .

[22]  Erik Brynjolfsson,et al.  Big data: the management revolution. , 2012, Harvard business review.

[23]  Ohbyung Kwon,et al.  Effects of data set features on the performances of classification algorithms , 2013, Expert Syst. Appl..

[24]  Benjamin H. Brinkmann,et al.  Large-scale electrophysiology: Acquisition, compression, encryption, and storage of big data , 2009, Journal of Neuroscience Methods.

[25]  Alberto Soncini,et al.  The big kahuna , 2000 .

[26]  Izak Benbasat,et al.  The Case Research Strategy in Studies of Information Systems , 1987, MIS Q..

[27]  Lemuria Carter,et al.  RFID Applications, Issues, Methods and Theory: A Review of the AIS Basket of TOP Journals , 2013 .

[28]  Brian Fitzgerald,et al.  Software Crisis 2.0 , 2012, Computer.

[29]  Marimuthu Palaniswami,et al.  Fuzzy c-Means Algorithms for Very Large Data , 2012, IEEE Transactions on Fuzzy Systems.

[30]  Steve Kelling,et al.  Data-Intensive Science: A New Paradigm for Biodiversity Studies , 2009 .

[31]  Barbara Kitchenham,et al.  Procedures for Performing Systematic Reviews , 2004 .

[32]  M. White,et al.  Digital workplaces , 2012 .

[33]  Robert J. Kauffman,et al.  Business and data analytics: New innovations for the management of e-commerce , 2012, Electron. Commer. Res. Appl..

[34]  J. Manyika,et al.  Are you ready for the era of ‘big data’? , 2010 .

[35]  Steven M. Drucker,et al.  Exploratory Visualization Involving Incremental, Approximate Database Queries and Uncertainty , 2012, IEEE Computer Graphics and Applications.

[36]  Karen Ka-Leung Moon,et al.  RFID research: An academic literature review (1995–2005) and future research directions , 2008 .

[37]  Eric W. T. Ngai,et al.  Design of an RFID-based Healthcare Management System using an Information System Design Theory , 2009, Inf. Syst. Frontiers.

[38]  S. Koonin,et al.  Big data and city living – what can it do for us? , 2012 .

[39]  Jacques Bughin,et al.  Seizing the potential of ‘ big data , 2011 .

[40]  Erik Meijer Your Mouse is a Database , 2012, ACM Queue.

[41]  George O. Strawn Scientific Research: How Many Paradigms?. , 2012 .

[42]  T. Davenport Competing on analytics. , 2006, Harvard business review.

[43]  E. W. T. Ngai,et al.  A literature review and classification of electronic commerce research , 2002, Inf. Manag..

[44]  Veda C. Storey,et al.  Business Intelligence and Analytics: From Big Data to Big Impact , 2012, MIS Q..

[45]  HuYong,et al.  The application of data mining techniques in financial fraud detection , 2011 .

[46]  Dominic Barton,et al.  Making advanced analytics work for you. , 2012, Harvard business review.

[47]  Phil Tattersall The great race: Investment managers apply new technologies to get ahead , 2012 .

[48]  Geoffrey Little Managing the Data Deluge , 2012 .

[49]  Akemi Takeoka Chatfield,et al.  A contingency model for creating value from RFID supply chain network projects in logistics and manufacturing environments , 2009, Eur. J. Inf. Syst..

[50]  I Aguilar,et al.  Breeding and Genetics Symposium: really big data: processing and analysis of very large data sets. , 2012, Journal of animal science.

[51]  Lemuria Carter,et al.  literature review of RFID-enabled healthcare applications and issues amuel , 2013 .

[52]  J. Manyika Big data: The next frontier for innovation, competition, and productivity , 2011 .

[53]  Eugene Kolker,et al.  Opportunities and challenges for the life sciences community. , 2012, Omics : a journal of integrative biology.

[54]  MaryAnne M. Gobble,et al.  Big Data: The Next Big Thing in Innovation , 2013 .

[55]  Rodrigo Fernandes de Mello,et al.  An Online Data Access Prediction and Optimization Approach for Distributed Systems , 2012, IEEE Transactions on Parallel and Distributed Systems.

[56]  Catalin Boja,et al.  Distributed Parallel Architecture for "Big Data" , 2012 .

[57]  T. Davenport,et al.  How ‘ Big Data ’ is Different FALL 2012 , 2012 .

[58]  Erik Meijer The World According to LINQ , 2011, ACM Queue.

[59]  Ranjit Bose,et al.  Advanced analytics: opportunities and challenges , 2009, Ind. Manag. Data Syst..

[60]  Shvetank P. Shah,et al.  Good Data Won't Guarantee Good Decisions , 2012 .

[61]  Adam Jacobs,et al.  The pathologies of big data , 2009, Commun. ACM.

[62]  Alexander S. Szalay,et al.  Big Data [Guest editorial] , 2011, Comput. Sci. Eng..

[63]  Johannes Gehrke,et al.  Quo vadis, data privacy? , 2012, Annals of the New York Academy of Sciences.

[64]  Kushagra Vaid,et al.  Mobile processors for energy-efficient web search , 2011, TOCS.

[65]  Hirokazu Tatano,et al.  E-Government Challenge in Disaster Evacuation Response: The Role of RFID Technology in Building Safe and Secure Local Communities , 2010, 2010 43rd Hawaii International Conference on System Sciences.

[66]  G. Nolan,et al.  Computational solutions to large-scale data management and analysis , 2010, Nature Reviews Genetics.

[67]  Angappa Gunasekaran,et al.  A review for mobile commerce research and applications , 2007, Decis. Support Syst..

[68]  Viswanath Venkatesh,et al.  Bridging the Qualitative-Quantitative Divide: Guidelines for Conducting Mixed Methods Research in Information Systems , 2013, MIS Q..

[69]  R. Yin Yin, Robert K., Case Study Research: Design and Methods, 2nd ed. Newbury Park, CA: Sage, 1994. , 1994 .

[70]  Dursun Delen,et al.  Leveraging the capabilities of service-oriented decision support systems: Putting analytics and big data in cloud , 2013, Decis. Support Syst..

[71]  Keith Gordon,et al.  What is Big Data , 2013 .

[72]  Julia Lane O Privacy, Where Art Thou?: Protecting Privacy and Confidentiality in an Era of Big Data Access , 2012 .

[73]  Xiao Cheng,et al.  The rise of the Big Data , 2013 .

[74]  So Young Sohn,et al.  Behavior scoring model for coalition loyalty programs by using summary variables of transaction data , 2013, Expert Syst. Appl..

[75]  Brian David Johnson,et al.  Entertainment in the Age of Big Data , 2012, Proceedings of the IEEE.

[76]  Matthew Smith,et al.  Big data privacy issues in public social media , 2012, 2012 6th IEEE International Conference on Digital Ecosystems and Technologies (DEST).

[77]  K. Eisenhardt Building theories from case study research , 1989, STUDI ORGANIZZATIVI.

[78]  Li Xiu,et al.  Application of data mining techniques in customer relationship management: A literature review and classification , 2009, Expert Syst. Appl..

[79]  Debarati Guha-Sapir,et al.  Annual Disaster Statistical Review 2009 , 2010 .

[80]  Eugene Kolker,et al.  DELSA Global for “Big Data” and the Bioeconomy: Catalyzing Collective Innovation , 2012 .

[81]  D. Boyd,et al.  CRITICAL QUESTIONS FOR BIG DATA , 2012 .

[82]  Alexander S. Szalay,et al.  Data-Intensive Computing in the 21st Century , 2008, Computer.

[83]  R. Yin Case Study Research: Design and Methods , 1984 .

[84]  John Gantz,et al.  The Digital Universe in 2020: Big Data, Bigger Digital Shadows, and Biggest Growth in the Far East , 2012 .

[85]  Mary Czerwinski,et al.  Interactions with big data analytics , 2012, INTR.

[86]  George Siemens,et al.  Penetrating the fog: analytics in learning and education , 2014 .

[87]  Samuel Fosso Wamba,et al.  Achieving supply chain integration using RFID technology: The case of emerging intelligent B-to-B e-commerce processes in a living laboratory , 2012, Bus. Process. Manag. J..

[88]  Carsten Bange,et al.  In-memory analytics – strategies forreal-time CRM , 2011 .

[89]  John Wilbanks,et al.  'Omics Data Sharing , 2009, Science.

[90]  Michael D. Myers,et al.  What Does the Best is Research Look like? An Analysis of the AIS Basket of Top journals , 2011, PACIS.

[91]  Samuel Fosso Wamba,et al.  ‘Big Data’ as a Strategic Enabler of Superior Emergency Service Management: Lessons from the New South Wales State Emergency Service , 2012 .