Problems, theories, and governing the crowd

Research and recommendations on innovation through crowdsourcing are diverse and often contradictory, providing little guidance on when, where, and under what conditions to use various forms of crowdsourcing. This article responds by arguing that focal economic actors, as organization designers, catalyze innovation when they efficiently match attributes of the problem or attributes of a domain of problems to modes of organizing problem finding and solution search. Four basic insights drive this approach. First, sourcing from the crowd is, fundamentally, a governance choice. Second, crowdsourcing is an amalgam of both problem finding and problem solving through the crowd. Third, the attributes of focal actors, including the theories of value creation they possess, shape problem formulation, solution-search, and the governance of these processes. Fourth, the act of defining problems reveals, and often generates, a vast residual domain of problems—often unseen by the focal economic actor—that is implicitly deferred to the crowd to find and potentially solve.

Organizational governance of inter-firm resource combinations: The impact of structural embeddedness and vertical resource relatedness

Firms not only combine resources within firm boundaries but tap into, acquire, or consolidate resources outside firm boundaries. Alliances and mergers and acquisitions (M&A) are distinct vehicles for governing inter-firm resource combinations. Prior studies on the governance choice between them have relied on firm- or dyad-level attributes to explicate the choice firms make about the governance. However, any firm or dyad is a micro-structure embedded in networks that shape the flow of information and resources to the focal firm or dyad. In addition, although alliances and mergers and acquisitions involve either horizontal or vertical resource combinations, the vertical dimension of resource relatedness has been largely neglected in prior research. This study examines the impact of structural embeddedness and vertical resource relatedness on governance choice. We find that structural embeddedness is an important driver of governance choice and that a significant portion of resource combinations occurs along the vertical dimension of relatedness.

Governance of algorithms: options and limitations

Purpose – The purpose of this paper is to contribute to a better understanding of governance choice in the area of algorithmic selection. Algorithms on the Internet shape our daily lives and realities. They select information, automatically assign relevance to them and keep people from drowning in an information flood. The benefits of algorithms are accompanied by risks and governance challenges. Design/methodology/approach – Based on empirical case analyses and a review of the literature, the paper chooses a risk-based governance approach. It identifies and categorizes applications of algorithmic selection and attendant risks. Then, it explores the range of institutional governance options and discusses applied and proposed governance measures for algorithmic selection and the limitations of governance options. Findings – Analyses reveal that there are no one-size-fits-all solutions for the governance of algorithms. Attention has to shift to multi-dimensional solutions and combinations of governance measures that mutually enable and complement each other. Limited knowledge about the developments of markets, risks and the effects of governance interventions hampers the choice of an adequate governance mix. Uncertainties call for risk and technology assessment to strengthen the foundations for evidence-based governance. Originality/value – The paper furthers the understanding of governance choice in the area of algorithmic selection with a structured synopsis on rationales, options and limitations for the governance of algorithms. It provides a functional typology of applications of algorithmic selection, a comprehensive overview of the risks of algorithmic selection and a systematic discussion of governance options and its limitations.