An attention-augmented real options approach to public R&D investments

Real options theory has gained momentum in the field of strategic management, both as a means for strategic reasoning and as a formal modeling method simulating real option valuation. In terms of real options, R&D investments offer a valuable learning space enhancing the upward potential and limiting downward risk of a firm’s innovative activities, provided that attentional constraints are taken into account. Specifically, public R&D investments exert particular attentional constraints on public managers, as they involve externally distributed intelligence for tailored investments endowed with strong asset specificity aimed at increasing public value. To grasp the learning space provided by public R&D investments, we adopt an attention-augmented perspective to real options, which considers the bi-directional linkages between real options and the heterogeneity of public agencies, defined as the openness of their attention structures. We first reflect on how the learning space for real options can emerge from the heterogeneity of public agencies. We then reverse the relationship by considering that the strategic management of real options, when successfully taking into consideration behavioral biases, increases feedback learning processes, which enhance the heterogeneity of public agencies. Our framework is illustrated in the context of the Small Business Innovation Research program in the USA and its equivalent in Europe, the Pre-Commercial Procurement scheme.