Complementarities in Learning from Data: Insights from General Search

Sapi, Geza; Schaefer, Maximilian

doi:10.2139/ssrn.4460899

Cited by 1 publication

(2 citation statements)

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“…Moreover, by running experiments, CSPs can test the effects of incremental updates and identify new relevant offerings, thus increasing the rate of innovation through data collection and analysis (Manyika et al, 2011). In the context of online search, tracking user behavior enables search engine operators to refine their algorithms, thus improving search quality and the relevance of search results (Schaefer and Sapi, 2022; Yao and Mela, 2011).…”

Section: Business Value Creation From Big Data Usementioning

confidence: 99%

“…Here, rare search terms (which increase with the total number of queries) contribute disproportionately to quality improvements, because they are more likely to contain new information (Argenton and Prüfer, 2012). In addition, individual-level data about users' search history can significantly improve search quality (Schaefer and Sapi, 2022). More generally, preliminary empirical evidence indicates that in many predictive analytics applications of big data, (i) there are benefits from larger data sets, (ii) these benefits are marginally decreasing as data sets become very large, and (iii) there is a minimum required scale.…”

Section: Facilitating Factors Of Data-driven Competitive Advantages A...mentioning

confidence: 99%

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Regulation of data-driven market power in the digital economy: Business value creation and competitive advantages from big data

Fast

Schnurr

Wohlfarth

2023

Journal of Information Technology

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Recent high-profile antitrust cases and policy proposals have put a spotlight on the relationship between firms’ access to big data and sustained competitive advantages in digital markets. In Europe, concerns about data-driven market power have led policy makers to propose far-reaching regulations of information technology (IT) in these markets. Despite the global policy relevance, the regulation of big data and its competitive effects has so far received little attention in information systems (IS) research. This article addresses this research gap by developing an overarching framework for future IS research on the role of IT for the regulation of data-driven market power. The proposed research framework builds upon a three-part analysis: First, we review the academic literature and show that there is extensive, although nuanced, empirical evidence for business value creation from big (user) data. Second, we draw on the resource-based view of the firm and recent policy reports to derive six facilitating factors that enable firms to establish market power based on sustained data-driven competitive advantages. Third, we characterize three regulatory approaches to govern market power and competition in data-driven digital markets: (i) empowering consumers, (ii) data openness and (iii) limiting data scale. For each of these approaches, we highlight the key role of IT artifacts in mediating the effect of regulatory rules on actual practice.

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Section: Business Value Creation From Big Data Usementioning

confidence: 99%

Section: Facilitating Factors Of Data-driven Competitive Advantages A...mentioning

confidence: 99%