SMS Special Conference in Frankfurt

Some decision makers are much more effective at managing uncertainty in than others. While some individuals are occasionally lucky in their strategic decisions, others seem to hit the jackpot much more consistently. But what distinguishes the consistent winners from their occasionally lucky counterparts? Specifically, why are some individuals better at minimizing uncertainty? Even when uncertainty is irreducible, what individual factors trump pure luck? What biological, psychological and or social influences impact decision-makers perceptions of uncertainty, problem representation, decision-making and ability to lead change? How do decision-makers learn in a world with unreliable feedback? We value cross-disciplinary theoretical pieces and empirical studies.

Innovating is about speculating on the potential future uses of knowledge and technology, meaning that uncertainty is at the very heart of innovation. This uncertainty manifests itself in different ways, all of which provide viable avenues for research. How do firms and managers allocate resources when faced with the uncertainty of innovation? How do firms seek to minimize the uncertainty associated with attempts at innovation, or their commercialization? How do firms handle uncertainty that arises due to different opinions from different managers within the firm? We welcome all research proposals that look at the underlying uncertainty of innovation across a variety of methodological and theoretical perspectives.

We invite submissions that examine how firms adapt and learn in uncertain and ambiguous environments. We welcome papers that look at both internal sources of ambiguity such as goals, preferences, feedback and learning and external sources of uncertainty such as digital disruptions, regulatory, or other macroeconomic shocks. Questions can include (but are not limited to): How do firms purse and achieve multiple goals? How do decision-makers interpret performance feedback and how does this influence change and risk taking? What are the performance implications of learning in an uncertain environment? What factors are critical for adaptation amidst weak, conflicting or ambiguous signals? How does organizational structure enable or constrain learning in dynamic environments? We welcome diverse methodologies – from in-depth case studies to those that use big data and/or machine learning tools.

In response to accelerating product and factor markets, companies must utilize an array of powerful but often risky corporate strategies–such as M&A, alliances, licensing, corporate venturing, and divestitures–to renew and redeploy their capabilities. They must fundamentally rethink their organizational structures and supply chains so as to enable internal arbitrage while remaining responsive to external changes. And they must design incentive and governance systems that guide managerial risk-taking and decision-making, while remaining focused on sustainable, long-term profitability. This track welcomes submissions related to these broad themes, exploring decisions, implementation, and outcomes of firms’ corporate strategies under uncertainty.