Search

Problem definition: We examine how the presence of capital market frictions influences the decision to invest in production cost reduction and the resultant production volume. This investment can increase the firm’s cash flow by increasing the profit margin, but it can also decrease the firm’s risk-free cash reserves and thus affect its exposure to capital market frictions. Academic/practical relevance: Process improvement aimed at production cost reduction has generated myriad of theoretical questions about efficient investment options and capacity choices. From a managerial perspective, process improvement is a fundamental concern in operations strategy. Nevertheless, its analysis typically excludes financial constraints by assuming a perfect capital market. Methodology: We formulate a two-stage profit maximization model in which a capital-constrained firm commits to a cost-reduction investment in the first stage in anticipation of its production decision in the second stage of this two-stage decision process. The firm considers capital market frictions when making decisions at each stage, while considering uncertainty in demand for its offering and in reducing its unit production cost. Results: When a firm faces small initial capital and low preinvestment unit production costs, it can benefit from investing in production cost reduction in the presence of capital market frictions more so than in their absence. Moreover, uncertainty in the production cost reduction mitigates the impact of market frictions on the net benefit (i.e., additional profit), whereas demand uncertainty decreases the feasible parameter space, where investing in production cost reduction is optimal. Managerial implications: A firm’s decision to invest in production cost reduction affects its operational and financial capabilities. Managers should thus consider this investment as an operational hedge not only against the uncertainty of matching supply and demand but also against exposure to capital market frictions and the resultant financial risk.

Start-up firms, which are by nature cash-constrained, often consider launching an immediately available product to generate funds for developing more advanced products. However, this release could have an adverse effect on the perception of the firm’s future products. A key decision for the start-up firm in such an environment is: when should the first product be released? In this paper we consider the product development and introduction decisions for a start-up which has a product that is ready to launch and is also developing a more advanced product, whose launch readiness is uncertain. We model the tradeoff between the adverse effect of a first version on overall profitability and the valuable stream of revenue it generates for R&D funding. We characterize an optimal policy with cash thresholds to determine when the firm should launch the first version and whether it should continue development. We derive managerial insights by studying these cash thresholds under various technological and market scenarios. Our analysis underscores a fundamental difference between how a start-up and an established firm view commercialization: a start-up would delay the launch of a good first version longer while an established firm (without bankruptcy considerations) would accelerate its launch.

The climate change debate and economic recovery strategies in various industries demand transformational projects in clean technology. Transformation in this context refers to a nearly tenfold improvement in a key technical performance indicator that is typically conditioned upon making high risk scientific breakthroughs. These projects face multiple sources of uncertainty in high risk situations, and require specialized knowhow and longer periods for revenue growth than their counterparts in other industries. The risk profile of such projects makes them unattractive investments to conventional financiers like banks and venture capital funds. We use data from 36 clean technology projects funded by the U.S. Advanced Research Projects Agency-Energy, to examine how operations design can hedge risk and enhance project valuation during early start-up stages. For start-up managers who are attempting to develop transformational technologies, our findings clarify the valuation criteria in high risk, high reward circumstances and offer strategies for securing and assigning resources. We find that firms with an operations design to reduce business risk receive more project funding. On the other hand, the choice of market segments for deployment remains uncertain for such start-ups, and design choices related to market competitiveness show a negative correlation to the level of funding.

Whether to invest in process development that can reduce the unit cost and thereby raise future profits or to conserve cash and reduce the likelihood of bankruptcy is a key trade-off faced by many startup firms that have taken on debt. We explore this trade-off by examining the production quantity and cost reducing R&D investment decisions in a two period model wherein a startup firm must make a minimum level of profit at the end of the first period to survive and operate in the second period. We specify a probabilistic survival measure as a function of production and investment decisions to track and manage the risk exposure of the startup depending on three key market factors: technology, demand, and competitor's cost. We develop managerial insights by characterizing how to create operational hedges against the bankruptcy risk: if a startup makes a "conservative" investment decision, then it also selects an optimal quantity that is less than the monopoly level and hence sacrifices some of first period expected profits to increase its survival chances. If it decides to invest "aggressively," then it produces more than the monopoly level to cover the higher bankruptcy risk. We also illustrate that debt constraint shrinks the decision space, wherein such process investments are viable.

The price of professional portfolio management provided by the mutual fund adviser depends not only on the fund characteristics but also on the fund objective, the adviser's portfolio related and management based decisions, and the portfolio performance. We analyze the advisory fee, using a survivorship bias free data set of 176 equity funds managed by 125 different advisers. Advisers benchmark the objective average but this benefit the shareholders only when the objective trend is descending. Advisers tend to reduce the cost of their marginal product through the use of derivatives or manipulate by engaging in soft dollar agreements. We find that the advisers actively manage the advisory fee contracts responding to the outcome of their management decisions. The advisory fee increases after voluntary fee reimbursement or if the adviser is not fully reimbursed for the compensation of independent directors and officers. Risk taking behavior is the main motivation behind the structure of the advisory contracts. Advisers who adopt more linear contracts that would motivate them to take on more risk tend to use derivatives arguably for better risk management and are less likely to engage in research agreements that would require a reduction in the advisory fee.