Research Summary Health science firms have long product development horizons and need regulatory approval for market entry. In communicating with investors, they may use entrepreneurial orientation (EO) rhetoric to emphasize their strategic and behavioral commitment to product innovation and market entry. However, because EO rhetoric constitutes a soft‐information signal rather than evidence of substantive commitment, investors may suspect firm insiders using such rhetoric of impression management. The solution, we argue, is EO rhetoric sustained over time, which produces more reliable information for investors—in contrast to occasional increases in EO rhetoric, which invite skeptical scrutiny. Nevertheless, investors' potential concerns regarding changes in EO rhetoric can be mitigated by concurrent hard‐information signals that carry signaling costs or penalty costs for false signaling. Managerial Summary Entrepreneurial orientation (EO) rhetoric can reduce information asymmetry between managers and investors. In strictly regulated contexts such as health science industries, using such rhetoric may be challenging. For firms embracing entrepreneurial strategies and behaviors, maintaining EO rhetoric over time is critical to overcoming skepticism that it is merely “cheap talk.” For investors, this study also suggests that health science firms maintaining higher EO rhetoric over time deserve higher valuations, given the variety of benefits an EO can have for health science firms. If a health science firm aims to ramp up its EO rhetoric, managers should be aware that investors may interpret the increase as impression management and should confront this interpretation head‐on—for instance, by simultaneously increasing entry commitment or corporate social responsibility.

Our primary aim in this paper is to develop and demonstrate a mixed integer programming model that utilizes activity-based cost information to determine optimal product mix and product cost in a multi-product manufacturing environment. The model permits interesting insights to be gained into the evaluation of marginal cost of products and marginal worth of resources for decision making involving product mix, product costing and capacity expansiodcontraction. It also addresses the issue of how to determine the cost of idle capacity and attribute it to the different products. An example is presented to demonstrate the findings of the model, which we then compare with analogous results from a traditional linear programming-based approach. Extensions to the mixed integer programming model are also provided.

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