Fehmi Tanrisever

Managing capacity flexibility in make-to-order production environments

This paper addresses the problem of managing flexible production capacity in a make-to-order (MTO) manufacturing environment. We present a multi-period capacity management model where we distinguish between process flexibility (the ability to produce multiple products on multiple production lines) and operational flexibility (the ability to dynamically change capacity allocations among different product families over time). For operational flexibility, we consider two polices: a fixed allocation policy where the capacity allocations are fixed throughout the planning horizon and a dynamic allocation policy where the capacity allocations change from period to period. The former approach is modeled as a single-stage stochastic program and solved using a cutting-plane method. The latter approach is modeled as a multi-stage stochastic program and a sampling-based decomposition method is presented to identify a feasible policy and assess the quality of that policy. A computational experiment quantifies the benefits of operational flexibility and demonstrates that it is most beneficial when the demand and capacity are well-balanced and the demand variability is high. Additionally, our results reveal that myopic operating policies may lead a firm to adopt more process flexibility and form denser flexibility configuration chains. That is, process flexibility may be over-valued in the literature since it is assumed that a firm will operate optimally after the process flexibility decision. We also show that the value of process flexibility increases with the number of periods in the planning horizon if an optimal operating policy is employed. This result is reversed if a myopic allocation policy is adopted instead.

Production, Process Investment and the Survival of Debt Financed Startup Firms

Over 70,000 firms are launched in the US alone every year. A sizable number of these startups require process investments to reduce their production cost. Whether to invest in process R&D to reduce unit cost and raise future profits, instead of conserving cash to reduce the likelihood of bankruptcy is a dilemma faced by many startups firms after launch. Fehmi Tanr sever, Sinan Erzurumlu, and Nitin Joglekar offer insights for managing this dilemma by examining the production quantity and cost-reducing R&D investment decisions in a two-period model. In this setting, the startup must make predetermined amount of profit at the end of this first period in order to survive and play in the second period. The authors show that with deterministic demand, it is optimal to deploy all-or-nothing R&D investment policy and to produce monopoly quantity. However, under a probabilistic survival constraint, the authors establish conditions when the startup can create operational hedges: make a “conservative” process R&D investment and then increase its survival chances by sacrificing some first period expected profits, i.e. produce less than the monopoly quantity. Alternatively, startups can invest “aggressively” and produce more than the monopoly quantity to cover the higher survival risk associated with aggressive R&D investment.

Integrated Options and Spot Procurement for Commodity Processors

We consider a firm that procures a commodity through a combination of options and spot contracts to process it and then distribute it to the downstream retailers to satisfy random demand. This commodity is traded on an organized exchange where evolution of prices offers no risk-free arbitrage. The firm incurs transportation costs when exercising the physical delivery of the contracts. Transportation cost in the spot market is higher than in options markets because spot purchases need to be expedited through an expensive means of transportation. Commodity purchased through options contract arrives with a lead time of one period while spot procurement has a zero lead time. The objective of the firm is to maximize the value for its stakeholders in a multi-period model. We demonstrate that the procurement options create value for a firm by managing demand risk in the presence of transportation costs. We characterize the optimal policy for options procurement, options exercise, and spot buying/selling in a multi-period model. In addition, we identify conditions under which the options contracts are more valuable than the forward contracts for the firm. We show that the value of procurement through options contract increases with demand volatility and decreases with price volatility.

Reverse Factoring for SME Finance

We present a mathematical model for integration, analysis, and optimization of operational and financial processes within a supply chain. Specifically, we consider commercial transactions of a large corporate customer with a small or medium-sized supplier. We show how application of reverse factoring influences the operational and financial decisions of these firms. While some empirical work on reverse factoring exists within research literature, our model constitutes the first analytic treatment of the problem, using the value framework of financial theory. We show how the value of reverse factoring results from, and is conditioned by (1) the spread in external financing costs, (2) the operating characteristics of the supplier, including the implied working capital policy, and (3) the risk-free interest rate. Thus, in addition to providing managerial insights that integrate operational and financial perspectives, our findings disclose an important relation of these elements to the broader macro-economic context.

Purchase Order Financing: Credit, Commitment, and Supply Chain Consequences

We study a supply chain where a retailer buys from a supplier who cannot fully �?nance her production. Informational problems about the supplier’s demand prospects and production capabilities restrict her access to capital. By committing to a minimum purchase quantity, the retailer can mitigate these informational problems and expand the supplier’s feasible production set. We assume a newsvendor model of operations and analyze the strategic interaction of the two parties as a sequential game. Key parameters in our model are the supplier’s ex-ante credit limit; her informational transparency (which conditions the amount of additional capital released by the commitment); and the demand characteristics of the �?nal market. We show that in equilibrium the supplier can benefit from a lower ex-ante credit limit or lower informational transparency. The retailer always benefits from an increase in these parameters. Moreover, the supplier’s ex-ante credit limit and informational transparency may be substitutes or complements with respect to her own pro�?t, but are always substitutes with respect to the retailer’s pro�?t. Our study provides a novel perspective on capital market frictions in supply chain contracting.

Purchase Order Finance: A Conceptual Model with Economic Insights

Purchase Order (PO) finance is a form of financial intermediation which can alleviate capital constraints in certain supply chains. PO finance is typically utilized by small and medium-sized enterprises (SMEs) that operate as importers, exporters, wholesalers, or distributors and have high sales growth. When applicable, PO finance creates value for the supply chain by providing capital that is not available through regular lending channels, due to informational problems. We provide a conceptual model that clarifies the value proposition of PO finance and describe how the transactions are carried out in practice. The conceptual model allows us to highlight the settings where economic conditions will favor the application of PO finance.

How Angel Know-How Shapes Ownership Sharing in Stage-Based Contracts:

We draw upon stewardship theory to formally derive bounds on the investment amount in a business prospect, and to characterize ownership sharing when investors offer two-stage financing along with know-how to increase the prospect’s valuation. In the early-development stage, we show that the direct effect of investor know-how increases the entrepreneur’s share while the indirect effect from that know-how due to its interaction with the investment size, decreases it. In the subsequent growth stage, the direct effect decreases the entrepreneur’s share while the indirect effect increases it. These tradeoffs offer theoretical and practical implications for writing investment contracts involving investor know-how.

Crowdfunding for Financing Wearable Technologies

We explore electronic crowdfunding platforms as a means of receiving money and other resources by an entrepreneur from many parties for financing wearable technology project. The electronic platform determines the cost of funding for the entrepreneur and the return investors will receive per period. This research aims to develop a framework to understand and evaluate the quantitative and qualitative implications of various crowdfunding platforms for the entrepreneur and his investment decisions in wearable technologies. We consider a debt financing based platform and examine its operational implications on the entrepreneurs decisions. In addition, we identify the incentive problems that occur in these models.