The Algorithm and the Crowd: Considering the Materiality of Service Innovation

Abstract

This special issue acknowledges important innovations in the world of service and within this domain we are particularly interested in exploring the rise and influence of web-based crowd-sourcing and algorithmic rating and ranking mechanisms. We suggest that a useful way to make sense of these digital service innovations and their novel implications is to recognize that they are materialized in practice. We thus need effective conceptual and analytical tools that allow us to take materiality seriously in our studies of service innovation. To this end, we propose some theoretical ideas relating to a sociomaterial perspective, and then highlight empirically how this perspective helps us analyze the specific service materializations enacted through the algorithmic configuring of crowd-sourced data, and how these make a difference in practice to the outcomes produced.3

Digital data, dynamic capability and financial performance: an empirical investigation in the era of Big Data

“…Indeed, among the possible technologies that can sustain a competitive advantage, the advent of Big Data opened up substantial debate around technologies used for generating, processing, and streaming digital data, as digital data are at the very foundation of this Big Data trend (George et al, 2014;Mayer-Schönberger & Cukier, 2013;Lynch, 2008;Orlikowski & Scott, 2015;Watson, 2014). We contributed to this debate because we argue that the digital nature of data constitutes a fundamental characteristic of data itself, with unique properties in terms of sharing, replication, combination and obsolescence.…”

“…Firms capture enormous amounts of fine-grained data on social media activity, RFID tags, web browsing patterns, consumer sentiment, and mobile phone usage, and the analysis of these data promises to produce insights that will revolutionise managerial decision-making" (Tambe, 2014(Tambe, , p. 1452. These finegrained data play an additional economic function: generating wishful content and unwitting meta-data surrounding main content (Orlikowski, 2015;Kallinikos et al, 2010).…”

“…Research on the business value of Information Technology (IT) has characterised the past two decades by focusing on patterns of theoretical development and on empirical findings (Melville et al, 2004). Recent studies have focused on particular IT artefacts to manage data-related problems related to business practices and strategies and, in particular, the Big Data trend (Lynch, 2008;George et al, 2014;Orlikowski and Scott, 2015;Watson, 2014;Mayer-Schönberger and Cukier, 2013). Big Data is the umbrella term for this evolving trend.…”

Digital Service Innovation Enabled by Big Data Analytics - A Review and the Way Forward

“…Between those ends lies a continuum of re-programmability and self-reference of platforms, which promotes innovation but also raises issues of integrity and structural flexibility [17,72].…”

Alliance strategy: context, process, and requirements

“…First, in some markets, the performance (products, services, solutions) itself becomes so complex that organizations need new processes to dynamically design, execute and deliver value (Caldwell and Howard, 2010). Second, linear value chain relationships tend to be replaced by multi-sided, reciprocal networks, for instance the network of hotels -brokering sites -customers (Wynstra et al, 2015;Rysman, 2009;Orlikowski and Scott, 2015). 'Who gives and receives what to and from whom' is no longer a transactional quid-pro-quo matter but embedded in a complex network.…”