The DOI matches its Crossref record; 127 of the 128 references it cites were found in a registry or an index.
Big Data Analytics Capabilities and Innovation: The Mediating Role of Dynamic Capabilities and Moderating Effect of the Environment
Open accessAbstract
Abstract With big data analytics growing rapidly in popularity, academics and practitioners have been considering the means through which they can incorporate the shifts these technologies bring into their competitive strategies. Drawing on the resource‐based view, the dynamic capabilities view, and on recent literature on big data analytics, this study examines the indirect relationship between a big data analytics capability (BDAC) and two types of innovation capabilities: incremental and radical. The study extends existing research by proposing that BDACs enable firms to generate insight that can help strengthen their dynamic capabilities, which in turn positively impact incremental and radical innovation capabilities. To test their proposed research model, the authors used survey data from 175 chief information officers and IT managers working in Greek firms. By means of partial least squares structural equation modelling, the results confirm the authors’ assumptions regarding the indirect effect that BDACs have on innovation capabilities. Specifically, they find that dynamic capabilities fully mediate the effect on both incremental and radical innovation capabilities. In addition, under conditions of high environmental heterogeneity, the impact of BDACs on dynamic capabilities and, in sequence, incremental innovation capability is enhanced, while under conditions of high environmental dynamism the effect of dynamic capabilities on incremental innovation capabilities is amplified.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“much recent literature suggesting that digital strategy can drive digital transformation by improving decision-making processes (Mikalef et al., 2019).”
From Mastering digital transformation: The nexus between leadership, agility, and digital strategy (2022) · cites this paper as Mikalef et al., 2019
In the citing paper
“While operations-line managers might be highly interested and motivated to invest and build BDA capability ( Akter et al., 2016 ;Mikalef et al., 2019 )”
From Applications of big data in emerging management disciplines: A literature review using text mining (2021) · cites this paper as Mikalef et al., 2019
Citations
Cites
Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003) · Journal of Applied Psychology · doi:10.1037/0021-9010.88.5.879 · Cited by 82,194
Firm Resources and Sustained Competitive Advantage
Barney, J. (1991) · Journal of Management · doi:10.1177/014920639101700108 · Cited by 48,334
A new criterion for assessing discriminant validity in variance-based structural equation modeling
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-014-0403-8 · Cited by 38,459
Preacher, K. J., & Hayes, A. F. (2008) · Behavior Research Methods · doi:10.3758/brm.40.3.879 · Cited by 34,117
Pls-Sem: indeed a silver bullet
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011) · Journal of Marketing Theory and Practice · doi:10.2753/mtp1069-6679190202 · Cited by 21,631
A primer on partial least squares structural equation modeling (PLS-SEM)
Leguina, A. (2015) · International Journal of Research & Method in Education · doi:10.1080/1743727x.2015.1005806 · Cited by 18,921
Teece, D. J. (2007) · Strategic Management Journal · doi:10.1002/smj.640 · Cited by 16,825
(1998) · Cited by 12,725
Research in Organizational Behavior.
Grimes, A. J., Cummings, L. L., & Staw, B. M. (1986) · Administrative Science Quarterly · doi:10.2307/2392975 · Cited by 11,303
The resource-based theory of competitive advantage: Implications for strategy formulation
Grant, R. M. (1991) · California Management Review · doi:10.2307/41166664 · Cited by 9,699
Strategic assets and organizational rent
Amit, R., & Schoemaker, P. J. H. (1993) · Strategic Management Journal · doi:10.1002/smj.4250140105 · Cited by 8,425 · cited 1×
“In incomplete markets, heterogeneity among firm capabilities can serve as the basis for developing competitive advantages and rent differentials (Amit & Schoemaker, 1993).”
An assessment of the use of partial least squares structural equation modeling in marketing research
Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-011-0261-6 · Cited by 8,088
Using pls path modeling in new technology research: updated guidelines
Henseler, J., Hubona, G., & Ray, P. A. (2016) · Industrial Management & Data Systems · doi:10.1108/imds-09-2015-0382 · Cited by 7,173
Tenenhaus, M., Vinzi, V. E., Chatelin, Y.-M., & Lauro, C. (2005) · Computational Statistics & Data Analysis · doi:10.1016/j.csda.2004.03.005 · Cited by 6,312
Business intelligence and analytics: from big data to big impact
Chen, H., Chiang, R. H. L., & Storey, V. C. (2012) · MIS Quarterly · doi:10.2307/41703503 · Cited by 6,250
Knowledge management: An organizational capabilities perspective
Gold, A. H., Malhotra, A., & Segars, A. H. (2001) · Journal of Management Information Systems · doi:10.1080/07421222.2001.11045669 · Cited by 6,233
Jarvis, C. B., MACKENZIE, S. B., & Podsakoff, P. M. (2003) · Journal of Consumer Research · doi:10.1086/376806 · Cited by 5,910
Understanding dynamic capabilities
Winter, S. G. (2003) · Strategic Management Journal · doi:10.1002/smj.318 · Cited by 5,315
(2011) · Cited by 5,203
Bharadwaj, A. S. (2000) · MIS Quarterly · doi:10.2307/3250983 · Cited by 5,042
Wetzels, M., Odekerken-Schröder, G., & van Oppen, C. (2009) · MIS Quarterly · doi:10.2307/20650284 · Cited by 4,944
Index Construction with Formative Indicators: An Alternative to Scale Development
Diamantopoulos, A., & Winklhofer, H. M. (2001) · Journal of Marketing Research · doi:10.1509/jmkr.38.2.269.18845 · Cited by 4,852
Artificial intelligence in radiology
Hosny, A., Parmar, C., Quackenbush, J., Schwartz, L. H., & Aerts, H. J. W. L. (2018) · Nature Reviews Cancer · doi:10.1038/s41568-018-0016-5 · Cited by 3,803
The Influence of Intellectual Capital on the Types of Innovative Capabilities
Subramaniam, M., & Youndt, M. A. (2005) · Academy of Management Journal · doi:10.5465/amj.2005.17407911 · Cited by 3,639
Big Data : The Management Revolution
マカフィー, ア., ブリニョルフソン, エ., & 有賀, 裕. (2013) · Harvard business review · Cited by 3,545
Common methods variance detection in business research
Fuller, C. M., Simmering, M. J., Atinc, G., Atinc, Y., & Babin, B. J. (2016) · Journal of Business Research · doi:10.1016/j.jbusres.2015.12.008 · Cited by 3,519
From the Editors: Common method variance in international business research
Chang, S., van Witteloostuijn, A. C., & Eden, L. (2010) · Journal of International Business Studies · doi:10.1057/jibs.2009.88 · Cited by 3,365
MacKenzie, S. B., Podsakoff, P. M., & Podsakoff, N. P. (2011) · MIS Quarterly · doi:10.2307/23044045 · Cited by 3,165
Entrepreneurship and dynamic capabilities: a review, model and research agenda
Zahra, S. A., Sapienza, H. J., & Davidsson, P. (2006) · Journal of Management Studies · doi:10.1111/j.1467-6486.2006.00616.x · Cited by 3,152
Data-intensive applications, challenges, techniques and technologies: A survey on Big Data
Philip Chen, C. L., & Zhang, C.-Y. (2014) · Information Sciences · doi:10.1016/j.ins.2014.01.015 · Cited by 3,047
Wade, M., & Hulland, J. (2004) · MIS Quarterly · doi:10.2307/25148626 · Cited by 2,822
Validation Guidelines for IS Positivist Research
Straub, D., & Gefen, D. (2004) · Communications of the Association for Information Systems · doi:10.17705/1cais.01324 · Cited by 2,797
Sharma, S., & Vredenburg, H. (1998) · Strategic Management Journal · doi:10.1002/(sici)1097-0266(199808)19:8 · Cited by 2,540
Big data analytics and firm performance: Effects of dynamic capabilities
Wamba, S. F., Gunasekaran, A., Akter, S., Ren, S. J.-F., Dubey, R., & Childe, S. J. (2017) · Journal of Business Research · doi:10.1016/j.jbusres.2016.08.009 · Cited by 2,474
CONDUCTING INTERORGANIZATIONAL RESEARCH USING KEY INFORMANTS.
KUMAR, N., STERN, L. W., & ANDERSON, J. C. (1993) · Academy of Management Journal · doi:10.2307/256824 · Cited by 2,467
(2012) · PubMed · Cited by 2,326
Woodside, A. G. (2013) · Journal of Business Research · doi:10.1016/j.jbusres.2012.12.021 · Cited by 1,945
How ‘big data’ can make big impact: findings from a systematic review and a longitudinal case study
Fosso Wamba, S., Akter, S., Edwards, A., Chopin, G., & Gnanzou, D. (2015) · International Journal of Production Economics · doi:10.1016/j.ijpe.2014.12.031 · Cited by 1,905
Wang, Y., Kung, L., & Byrd, T. A. (2018) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2015.12.019 · Cited by 1,571
Data science and its relationship to big data and data-driven decision making
Provost, F., & Fawcett, T. (2013) · Big Data · doi:10.1089/big.2013.1508 · Cited by 1,568
Wang, G., Gunasekaran, A., Ngai, E. W. T., & Papadopoulos, T. (2016) · International Journal of Production Economics · doi:10.1016/j.ijpe.2016.03.014 · Cited by 1,545
Knowledge management, innovation and firm performance
Darroch, J. (2005) · Journal of Knowledge Management · doi:10.1108/13673270510602809 · Cited by 1,542
Waller, M. A., & Fawcett, S. E. (2013) · Journal of Business Logistics · doi:10.1111/jbl.12010 · Cited by 1,522
Toward the development of a big data analytics capability
Gupta, M., & George, J. F. (2016) · Information & Management · doi:10.1016/j.im.2016.07.004 · Cited by 1,445
Untangling dynamic and operational capabilities: Strategy for the (N) ever - changing world
Helfat, C. E., & Winter, S. G. (2011) · Strategic Management Journal · doi:10.1002/smj.955 · Cited by 1,439
Sağıroğlu, Ş., & Terzi, D. S. (2013) · International Conference on Collaboration Technologies and Systems (CTS) · doi:10.1109/cts.2013.6567202 · Cited by 1,425
Big data consumer analytics and the transformation of marketing
Erevelles, S., Fukawa, N., & Swayne, L. (2016) · Journal of Business Research · doi:10.1016/j.jbusres.2015.07.001 · Cited by 1,377
van Doorn, J., Mende, M., Noble, S. M., Hulland, J., Ostrom, A. L., Grewal, D., & Petersen, J. A. (2017) · Journal of Service Research · doi:10.1177/1094670516679272 · Cited by 1,344
Understanding the elusive black Box of dynamic capabilities
Pavlou, P. A., & El Sawy, O. A. (2011) · Decision Sciences · doi:10.1111/j.1540-5915.2010.00287.x · Cited by 1,329
Pavlou, P. A., & El Sawy, O. A. (2006) · Information Systems Research · doi:10.1287/isre.1060.0094 · Cited by 1,311
Lu, Y., & Ramamurthy, K. (. (2011) · MIS Quarterly · doi:10.2307/41409967 · Cited by 1,309
Survey research methodology in management information systems: an assessment
Pinsonneault, A., & Kraemer, K. (1993) · Journal of Management Information Systems · doi:10.1080/07421222.1993.11518001 · Cited by 1,288
Schilke, O., Hu, S., & Helfat, C. E. (2018) · Academy of Management Annals · doi:10.5465/annals.2016.0014 · Cited by 1,226
Multidimensional constructs in organizational behavior research: an integrative analytical framework
Edwards, J. R. (2001) · Organizational Research Methods · doi:10.1177/109442810142004 · Cited by 1,128
Understanding dynamic capabilities: progress along a developmental path
Helfat, C. E., & Peteraf, M. A. (2009) · Strategic Organization · doi:10.1177/1476127008100133 · Cited by 1,121
Bhatt, G. D., & Grover, V. (2005) · Journal of Management Information Systems · doi:10.1080/07421222.2005.11045844 · Cited by 1,117
Determinants of innovation capability in small electronics and software firms in southeast England
Romijn, H., & Albaladejo, M. (2002) · Research Policy · doi:10.1016/s0048-7333(01)00176-7 · Cited by 1,061
Mikalef, P., & Pateli, A. (2017) · Journal of Business Research · doi:10.1016/j.jbusres.2016.09.004 · Cited by 1,038
Self-citationCreating Strategic Business Value from Big Data Analytics: A Research Framework
Grover, V., Chiang, R. H. L., Liang, T.-P., & Zhang, D. (2018) · Journal of Management Information Systems · doi:10.1080/07421222.2018.1451951 · Cited by 961
Social media competitive analysis and text mining: A case study in the pizza industry
He, W., Zha, S., & Li, L. (2013) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2013.01.001 · Cited by 920
Insufficient discriminant validity: a comment on Bove, Pervan, Beatty, and Shiu (2009)
Farrell, A. M. (2010) · Journal of Business Research · doi:10.1016/j.jbusres.2009.05.003 · Cited by 914
Dynamic Capabilities: An Exploration of How Firms Renew their Resource Base
Ambrosini, V., Bowman, C., & Collier, N. (2009) · British Journal of Management · doi:10.1111/j.1467-8551.2008.00610.x · Cited by 893
Big data analytics capabilities: A systematic literature review and research agenda
Mikalef, P., Pappas, I. O., Krogstie, J., & Giannakos, M. (2018) · Information Systems and e-Business Management · doi:10.1007/s10257-017-0362-y · Cited by 888
Self-citationDebating big data: a literature review on realizing value from big data
Günther, W. A., Rezazade Mehrizi, M. H., Huysman, M., & Feldberg, F. (2017) · The Journal of Strategic Information Systems · doi:10.1016/j.jsis.2017.07.003 · Cited by 880
Dynamic capabilities, environmental dynamism, and competitive advantage: Evidence from China
Li, D., & Liu, J. (2012) · Journal of Business Research · doi:10.1016/j.jbusres.2012.08.007 · Cited by 862
Factors influencing big data decision-making quality
Janssen, M., van der Voort, H., & Wahyudi, A. (2017) · Journal of Business Research · doi:10.1016/j.jbusres.2016.08.007 · Cited by 799
Data quality management, data usage experience and acquisition intention of big data analytics
Kwon, O., Lee, N., & Shin, B. (2014) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2014.02.002 · Cited by 794
A comparative study of cb-sem and pls-sem for theory development in family firm research
Astrachan, C. B., Patel, V. K., & Wanzenried, G. (2014) · Journal of Family Business Strategy · doi:10.1016/j.jfbs.2013.12.002 · Cited by 766
Big Data Research in Information Systems: Toward an Inclusive Research Agenda
University of Virginia, Abbasi, A., Sarker, S., University of Virginia, Aalto University, Chiang, R., & University of Cincinnati (2016) · Journal of the Association for Information Systems · doi:10.17705/1jais.00423 · Cited by 688
Big data analytics in E-commerce: a systematic review and agenda for future research
Akter, S., & Wamba, S. F. (2016) · Electronic Markets · doi:10.1007/s12525-016-0219-0 · Cited by 684
Drnevich, P. L., & Kriauciunas, A. P. (2011) · Strategic Management Journal · doi:10.1002/smj.882 · Cited by 681
Ritala, P., & Hurmelinna‐Laukkanen, P. (2012) · Journal of Product Innovation Management · doi:10.1111/j.1540-5885.2012.00956.x · Cited by 665
Wilden, R., & Gudergan, S. P. (2015) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-014-0380-y · Cited by 631
The Industry 4.0 revolution and the future of Manufacturing Execution Systems (MES)
Almada-Lobo, F. (2016) · Journal of Innovation Management · doi:10.24840/2183-0606_003.004_0003 · Cited by 622
Forés, B., & Zornoza, C. C. (2015) · Journal of Business Research · doi:10.1016/j.jbusres.2015.07.006 · Cited by 591
From big data analysis to personalized medicine for all: challenges and opportunities
Alyass, A., Turcotte, M., & Meyre, D. (2015) · BMC Medical Genomics · doi:10.1186/s12920-015-0108-y · Cited by 575
Schoenherr, T., & Speier, C. (2015) · Journal of Business Logistics · doi:10.1111/jbl.12082 · Cited by 566
Big data: Dimensions, evolution, impacts, and challenges
Lee, I. (2017) · Business Horizons · doi:10.1016/j.bushor.2017.01.004 · Cited by 548
New games, new rules: big data and the changing context of strategy
Constantiou, I. D., & Kallinikos, J. (2015) · Journal of Information Technology · doi:10.1057/jit.2014.17 · Cited by 526
Motivating salespeople: what really works.
Steenburgh, T. J., & Ahearne, M. (2012) · PubMed · Cited by 519
Sharma, R., Mithas, S., & Kankanhalli, A. (2014) · European Journal of Information Systems · doi:10.1057/ejis.2014.17 · Cited by 516
Dynamic capabilities and their indirect impact on firm performance
Protogerou, A., Caloghirou, Y., & Lioukas, S. (2012) · Industrial and Corporate Change · doi:10.1093/icc/dtr049 · Cited by 503
Management challenges in creating value from business analytics
Vidgen, R., Shaw, S., & Grant, D. B. (2017) · European Journal of Operational Research · doi:10.1016/j.ejor.2017.02.023 · Cited by 493
Chiang, Y., & Hung, K. (2010) · R and D Management · doi:10.1111/j.1467-9310.2010.00588.x · Cited by 440
Schryen, G. (2013) · European Journal of Information Systems · doi:10.1057/ejis.2012.45 · Cited by 420
Lehrer, C., Wieneke, A., vom Brocke, J., Jung, R., & Seidel, S. (2018) · Journal of Management Information Systems · doi:10.1080/07421222.2018.1451953 · Cited by 404
Koberg, C. S., DeTienne, D. R., & Heppard, K. A. (2003) · The Journal of High Technology Management Research · doi:10.1016/s1047-8310(03)00003-8 · Cited by 398
The impact of big data analytics on firms’ high value business performance
Popovič, A., Hackney, R., Tassabehji, R., & Castelli, M. (2016) · Information Systems Frontiers · doi:10.1007/s10796-016-9720-4 · Cited by 392
Industrial Big Data Analytics and Cyber-physical Systems for Future Maintenance & Service Innovation
Lee, J., Ardakani, H. D., Yang, S., & Bagheri, B. (2015) · Procedia CIRP · doi:10.1016/j.procir.2015.08.026 · Cited by 383
Xu, Z. “., Frankwick, G. L., & Ramirez, E. (2015) · Journal of Business Research · doi:10.1016/j.jbusres.2015.10.017 · Cited by 378
Modelling quality dynamics, business value and firm performance in a big data analytics environment
Ren, S. J.-F., Wamba, S. F., Akter, S., Dubey, R., & Childe, S. J. (2016) · International Journal of Production Research · doi:10.1080/00207543.2016.1154209 · Cited by 362
Resource management in big data initiatives: processes and dynamic capabilities
Braganza, A., Brooks, L., Nepelski, D., Ali, M., & Moro, R. (2017) · Journal of Business Research · doi:10.1016/j.jbusres.2016.08.006 · Cited by 339
Uncertainty, Innovation, and Dynamic Capabilities: An Introduction
Teece, D. J., & Leih, S. (2016) · California Management Review · doi:10.1525/cmr.2016.58.4.5 · Cited by 327
The Information Artifact in IT Governance: Toward a Theory of Information Governance
Tallon, P. P., Ramirez, R. V., & Short, J. E. (2013) · Journal of Management Information Systems · doi:10.2753/mis0742-1222300306 · Cited by 325
Demystifying big data analytics for business intelligence through the Lens of marketing mix
Fan, S., Lau, R. Y. K., & Zhao, J. L. (2015) · Big Data Research · doi:10.1016/j.bdr.2015.02.006 · Cited by 321
Benitez, J., Castillo, A., Llorens, J., & Braojos, J. (2018) · Information & Management · doi:10.1016/j.im.2017.09.004 · Cited by 318
Cepeda‐Carrión, G., Henseler, J., Ringle, C. M., & Roldán, J. L. (2016) · Journal of Business Research · doi:10.1016/j.jbusres.2016.03.048 · Cited by 299
The effectiveness of strategic information systems planning under environmental uncertainty
Newkirk, H. E., & Lederer, A. L. (2006) · Information & Management · doi:10.1016/j.im.2005.12.001 · Cited by 287
Designing Organizations for Dynamic Capabilities
Felin, T., & Powell, T. C. (2016) · California Management Review · doi:10.1525/cmr.2016.58.4.78 · Cited by 266
Corporate Governance of Big Data: Perspectives on Value, Risk, and Cost
Tallon, P. P. (2013) · Computer · doi:10.1109/mc.2013.155 · Cited by 232
In the company of givers and takers.
Grant, A. M. (2013) · PubMed · Cited by 181
Environmental Uncertainty and IT Infrastructure Governance: A Curvilinear Relationship
Xue, L., Ray, G., & Gu, B. (2010) · Information Systems Research · doi:10.1287/isre.1090.0269 · Cited by 175
Demystifying Learning Analytics in Personalised Learning
Maseleno, A., Sabani, N., Huda, M., Ahmad, R., Jasmi, K. A., & Basiron, B. B. (2018) · International Journal of Engineering & Technology · doi:10.14419/ijet.v7i3.9789 · Cited by 143
A model for unpacking big data analytics in high-frequency trading
Seddon, J. J. M., & Currie, W. L. (2016) · Journal of Business Research · doi:10.1016/j.jbusres.2016.08.003 · Cited by 139
Buettner, R. (2016) · Electronic Markets · doi:10.1007/s12525-016-0228-z · Cited by 135
Beyond the Hype: The Hard Work Behind Analytics Success
Ransbotham, S., Kiron, D. J., & Prentice, P. K. (2016) · MIT Sloan Management Review · doi:10.63383/lqte5170 · Cited by 125
Dutot, V., Bergeron, F., & Raymond, L. (2014) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2014.06.006 · Cited by 120
Akhtar, P., Khan, Z., Frynas, J. G., Tse, Y. K., & Rao‐Nicholson, R. (2017) · British Journal of Management · doi:10.1111/1467-8551.12233 · Cited by 109
Social customer relationship management: taking advantage of Web 2.0 and Big Data technologies
Orenga-Roglá, S., & Chalmeta, R. (2016) · SpringerPlus · doi:10.1186/s40064-016-3128-y · Cited by 97
Big data and competitive advantage at Nielsen
Prescott, M. E. (2014) · Management Decision · doi:10.1108/md-09-2013-0437 · Cited by 93
Big Data Analytics Capability: Antecedents and Business Value.
Mikalef, P., Framnes, V. A., Danielsen, F., Krogstie, J., & Olsen, D. H. (2017) · Journal of the Association for Information Systems · Cited by 90
Self-citation(2014) · Cited by 79
Do Parent Units Benefit from Reverse Knowledge Transfer?
Nair, S. R., Demirbag, M., Mellahi, K., & Pillai, K. G. (2018) · British Journal of Management · doi:10.1111/1467-8551.12234 · Cited by 74
Network-Based Modeling and Analysis of Systemic Risk in Banking Systems1
Hu, D., Zhao, J. L., Hua, Z., & Wong, M. C. S. (2012) · MIS Quarterly · doi:10.2307/41703507 · Cited by 69
Integration of non‐market and market activities in cross‐border mergers and acquisitions
Ahammad, M. F., Tarba, S. Y., Frynas, J. G., & Scola, A. (2017) · British Journal of Management · doi:10.1111/1467-8551.12228 · Cited by 64
Lim, L. L., Alpan, G., & Penz, B. (2014) · International Journal of Production Economics · doi:10.1016/j.ijpe.2014.01.011 · Cited by 62
Automated competitor analysis using big data analytics
Guo, L., Sharma, R., Lei, Y., Lu, R., & Rong, K. (2017) · Business Process Management Journal · doi:10.1108/bpmj-05-2015-0065 · Cited by 61
Jang, H., Sim, J., Lee, Y., & Kwon, O. (2013) · Expert Systems with Applications · doi:10.1016/j.eswa.2013.06.069 · Cited by 57
Ransbotham, S., Kiron, D. J., & Prentice, P. K. (2015) · International Linear Collider · Cited by 48
Exploring the impact of social axioms on firm reputation: a stakeholder perspective
West, B., Hillenbrand, C., Money, K., Ghobadian, A., & Ireland, R. D. (2016) · British Journal of Management · doi:10.1111/1467-8551.12153 · Cited by 40
Big data analytics in electronic markets
Ngai, E. W. T., Gunasekaran, A., Wamba, S. F., Akter, S., & Dubey, R. (2017) · Electronic Markets · doi:10.1007/s12525-017-0261-6 · Cited by 34
Intangible Assets and a Theory of Heterogeneous Firms
Teece, D. (2015) · Springer eBooks · doi:10.1007/978-3-319-07533-4_9 · Cited by 32
Specifying Formative Constructs in Information Systems Research1
Petter, S., Straub, D., & Rai, A. (2007) · MIS Quarterly · doi:10.2307/25148814 · Cited by 32
Adobe reinvents its customer experience
Kane, G. C. (2016) · Dialnet (Universidad de la Rioja) · Cited by 11
Call for Papers – Special Issue 2019 Big Data and Performance
(2017) · British Journal of Management · doi:10.1111/1467-8551.12246 · Cited by 2
Eisenhardt, K. M., & Martin, J. A. (2000) · Strategic Management Journal · doi:10.1002/1097-0266(200010/11)21:10/11
Dynamic capabilities and strategic management
Teece, D. J., Pisano, G., & Shuen, A. (1997) · Strategic Management Journal · doi:10.1002/(sici)1097-0266(199708)18:7
Research works printed but not linked: 8
- Antonakis J., 2014, Causality and endogeneity: problems and solutions, Oxford Handbook of Leadership and Organizations, 1, 93
- Aspect(2013). ‘Southwest Airlines heads to the cloud with Aspect software to provide best‐in‐class customer experience [Press release]’. Available athttp://www.aspect.com/company/news/press-releases/southwest-airlines-heads-to-the-cloud-with-aspect-software-to-provide-best-in-class-customer-experience[accessed 15 June 2018].
- Brinkhues R., 2014, Proceedings of the 20th Americas Conference on Information Systems (AMCIS)
- Davenport T. H., 2012, Data scientist: the sexiest job of the 21st century, Harvard Business Review, 90, 70
- Kiron D., 2017, Lessons from becoming a data‐driven organization, MIT Sloan Management Review, 58, 1
- Nunnally J., 1978, Psychometric Methods
- Ransbotham S., 2017, Analytics as a source of business innovation, MIT Sloan Management Review, 58, 1
- Ross J. W., 2013, You may not need big data after all, Harvard Business Review, 91, 90
Cited by
Sorted by citations
Mikalef, P., & Gupta, M. (2021) · Information & Management · doi:10.1016/j.im.2021.103434 · Cited by 1,700
Self-citationMikalef, P., Krogstie, J., Pappas, I. O., & Pavlou, P. (2020) · Information & Management · doi:10.1016/j.im.2019.05.004 · Cited by 1,373
“While big data analytics has largely been regarded as a break-through technological development in academic and business communities [9], there is an ongoing debate about if, and under what conditions, such technologies can lead to competitive performance gains [10,11].”
BackgroundSelf-citationDubey, R., Gunasekaran, A., Childe, S. J., Bryde, D. J., Giannakis, M., Foropon, C., Roubaud, D., & Hazen, B. T. (2020) · International Journal of Production Economics · doi:10.1016/j.ijpe.2019.107599 · Cited by 889
Mastering digital transformation: The nexus between leadership, agility, and digital strategy
AlNuaimi, B. K., Kumar Singh, S., Ren, S., Budhwar, P., & Vorobyev, D. (2022) · Journal of Business Research · doi:10.1016/j.jbusres.2022.03.038 · Cited by 820
“Organizations that focus on developing solid digital strategies can use them to drive digital transformation and improve top executives ’ decision-making processes (Mikalef et al., 2019).”
BackgroundBig data analytics and firm performance: Findings from a mixed-method approach
Mikalef, P., Boura, M., Lekakos, G. D., & Krogstie, J. (2019) · Journal of Business Research · doi:10.1016/j.jbusres.2019.01.044 · Cited by 819
Self-citation
Metadata
- Authors
- Mikalef, P., Boura, M., Lekakos, G., & Krogstie, J.
- Affiliations
- Norwegian University of Science and Technology (NO)
- Athens University of Economics and Business (GR)
- Corresponding author
- Mikalef, Patrick
- Venue
- British Journal of Management
- Publisher
- Wiley
- Published
- 2019-04
- Volume
- 30
- Issue
- 2
- Pages
- 272-298
- ISSN
- 1045-3172 (ISSN-L)
- 1467-8551
- OpenAlex
- W2944471258
- Cited by
- 835
- References
- 128
- Citations by year
- 2026: 130 · 2025: 154 · 2024: 157 · 2023: 156 · 2022: 106 · 2021: 83 · 2020: 33 · 2019: 16
- FWCI
- 79.22
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- Locations
- British Journal of Management (publishedVersion)
- NORA - Norwegian Open Research Archives (submittedVersion, other-oa)
- Funders
- European Union's Horizon 2020
- Marie Sklodowska-Curie (No 704110)
- Topics
- Social Sciences › Business, Management and Accounting › Management Information Systems › Big Data and Business Intelligence
- Social Sciences › Business, Management and Accounting › Strategy and Management › Innovation and Knowledge Management
- Social Sciences › Decision Sciences › Information Systems and Management › Big Data Technologies and Applications
- Keywords
- big data analytics capability, dynamic capabilities, incremental innovation, radical innovation, innovation ability, environmental heterogeneity, environmental dynamism, mediating effect, moderating effect, resource-based view, competitive strategy, chief information officer
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review