The emergence of “big data” and related analytic techniques are creating opportunities to advance empirical entrepreneurship theory and practice. This editorial focuses on the implications for the design and execution of empirical studies. It offers guidance on how to navigate related methodological challenges and outlines what editors, professional associations, research-method teachers, and administrators can do to enable high-quality big data research.
AllwinkleS.CruickshankP. (2011) Creating smarter cities: An overview. Journal of Urban Technology18(2): 1–16.
2.
American Psychological Association (2010) Publication manual of the American Psychological Association, 6th ed. Washington, DC: American Psychological Association.
3.
Braun, M. T., Kuljanin, G., & DeShon, R. P. (2017, February 28). Special considerations for the acquisition and wrangling of big data. Organizational Research Methods (Published Online). doi:1094428117690235.
4.
DiesnerJ.FrantzT. L.CarleyK. M. (2005) Communication networks from the Enron email corpus “it’s always about the people: Enron is no different.”. Computational and Mathematical Organization Theory11(3): 201–228.
5.
GandomiA.HaiderM. (2015) Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management35(2): 137–144.
6.
GeorgeG.HaasM. R.PentlandA. (2014) Big data and management. Academy of Management Journal57(2): 321–326.
7.
GoldbergA.SrivastavaS. B.ManianV. G.MonroeW.PottsC. (2016) Fitting in or standing out? The tradeoffs of structural and cultural embeddedness. American Sociological Review81(6): 1190–1222.
8.
GuzzoR. A.FinkA. A.KingE.TonidandelS.LandisR. S. (2015) Big data recommendations for industrial–organizational psychology. Industrial and Organizational Psychology8(4): 491–508.
9.
HeyT.TansleyS.TolleK. M. (2009) The fourth paradigm: Data-intensive scientific discovery, Redmond, WA: Microsoft Research.
10.
JinX.WahB. W.ChengX.WangY. (2015) Significance and challenges of big data research. Big Data Research2(2): 59–64.
11.
KitchinR. (2013) Big data and human geography: Opportunities, challenges and risks. Dialogues in Human Geography3(3): 262–267.
12.
KitchinR. (2014a) Big data, new epistemologies and paradigm shifts. Big Data & Society1(1): 1–12.
13.
KitchinR. (2014b) The real-time city? Big data and smart urbanism. GeoJournal79(1): 1–14.
14.
McAfeeA.BrynjolfssonE. (2012) Big data: The management revolution. Harvard Business Review90(10): 60–66.
OswaldF. L.PutkaD. J. (2015) Statistical methods for big data: A scenic tour. In: TonidandelS.KingE.CortinaJ. M. (eds) Big data at work: Data science revolution and organizational psychology, New York, NY: Routledge, pp. 43–63.
19.
PentlandA. (2012) The new science of building great teams. Harvard Business Review90(4): 60–69.
20.
PutkaD. J.OswaldF. L. (2015) Implications of the big data movement for the advancement of IO science and practice. In: TonidandelS.KingE.CortinaJ. M. (eds) Big data at work: The data science revolution and organizational psychology, New York, NY: Routledge, pp. 181–212.
ShmueliG. (2010) To explain or to predict?Statistical Science25(3): 289–310.
23.
SivarajahU.KamalM. M.IraniZ.WeerakkodyV. (2017) Critical analysis of big data challenges and analytical methods. Journal of Business Research70: 263–286.
24.
SmolanR.ErwittJ. (2012) The human face of big data, Sausalito, CA: Against All Odds Production.
25.
Tonidandel, S., King, E. B., & Cortina, J. M. (2016, November 16). Big data methods leveraging modern data analytic techniques to build organizational science. Organizational Research Methods (Published Online). doi:1094428116677299.
26.
Tripathi, P., & Burleson, W. (2012, February 11–15). Predicting creativity in the wild: Experience sample and sociometric modeling of teams. Paper presented at the ACM 2012 conference on Computer Supported Cooperative Work, Seattle, WA.
27.
TukeyJ. (1997) More honest foundations for data analysis. Journal of Statistical Planning and Inference57(1): 21–28.
28.
VarianH. R. (2016) Causal inference in economics and marketing. Proceedings of the National Academy of Sciences113(27): 7310–7315.
29.
WallerM. A.FawcettS. E. (2013) Data science, predictive analytics, and big data: A revolution that will transform supply chain design and management. Journal of Business Logistics34(2): 77–84.
ZhangZ.GuoC.GóesP. B. (2013) Product comparison networks for competitive analysis of online word-of-mouth. ACM Transactions on Management Information Systems3(4): 1–22.
32.
ZhangZ.LiX.ChenY. (2012) Deciphering word-of-mouth in social media: Text-based metrics of consumer reviews. ACM Transactions on Management Information Systems3(1): Article 5.