James V. Jucker

A Response

Although Allen Rappaport is critical of many things, including authors, editors, and referees, it seems that his principal concerns with the article which Meir Rosenblatt and I wrote have to do with our interpretation of the data presented in Table 1 of that article. Rosenblatt and I looked at these data and concluded that “the trend is unmistakable... the rate of adoption of the use of discounting techniques may be slower than some would wish, but the trend is significant and in the right direction.

International plant location under price and exchange rate uncertainty

Abstract The problem of locating plants internationally under price and exchange rate uncertainty is formulated for a mean-variance decision maker. This formulation results in a mixed-integer quadratic programming problem. It is shown that, for a given integer solution, the resulting quadratic programming problem is amenable to a very simple solution procedure. Thus, reasonably large problems can be solved using existing branch-and-bound techniques while still incorporating price and exchange rate uncertainty. It is also likely that solution of models with even more complex forms of uncertainty will also be feasible using this approach.

An economic view of project coordination

We introduce current thinking from the field of coordination economics and apply it to the coordination needs of construction firms working on a project. A view of construction from an economic lens provides a different view of construction from that normally taken by practitioners and researchers. Combined with cost-time-capacity models of construction firms, we are able to offer a new paradigm for coordination policy in construction. This new paradigm provides an economic basis for the development and adoption of information technology by construction firms.

The Simple Plant-Location Problem under Uncertainty

There is a class of simple plant-location problems under uncertainty that can be decomposed into two simpler problems that can be solved sequentially with surprising ease. The salient characteristic of this class of problems is that for any demand generating region, one plant dominates all others as a supply source. We develop and discuss the conditions required for this dominance. The risk-averse nature of the firm is incorporated into this model with a mean-variance formulation of the objective function. The general formulation is particularized to four paradigms of firms characterized by a range of behavioral and market assumptions.

A simple plant-location model for quantity-setting firms subject to price uncertainty

Abstract The uncapacitated plant location problem under uncertainty is formulated in a mean-variance framework with prices in various markets correlated via their response to a common random factor. This formulation results in a mixed-integer quadratic programming problem. However, for a given integer solution, the resulting quadratic programming problem is amenable to a very simple solution procedure. The simplicity of this algorithm means that reasonably large problems should be solvable using existing branch-and-bound techniques.

The Simultaneous Determination of Plant and Leased Warehouse Capacities for a Firm Facing Uncertain Demand in Several Regions

Abstract For each of several regions a firm has forecasted a probability distribution of future annual demand, and the plan is to build a single production facility to serve this demand. Each region is served by a simple leased warehouse with a lease cost which is a linear function of capacity. Any regional demand exceeding warehouse capacity is lost. The cost of building the plant is a nonlinear function of its capacity, and the unit cost of producing the product and supplying it to a region is constant. We develop an efficient algorithm based on the Kuhn-Tucker conditions for simultaneously determining the plant and warehouse capacities which will maximize the firms expected profit. The paper includes a numerical example demonstrating the use of this algorithm.

A Simple Algorithm for Stone's Version of the Portfolio Selection Problem

More than twenty years ago the portfolio selection problem was stated as a parametric quadratic programming problem [3]. Since that time there has been an ongoing search for methods that would allow reductions in both the data and the computational effort required to implement the Markowitz formulation. Markowitz himself developed a special algorithm for the problem [4] Sharpe followed with his famous diagonal model [6], a linear programming approximation for the special case of mutual funds [7], and a linear programming approximation for the general problem [0]. And during this period there were substantial advances in quadratic programming computer codes. A very fast code is now widely available [1], but the size of the code itself (a listing of the annotated program runs to more than 3,000 lines) makes its everyday use for portfolio selection somewhat unattractive.

The Transfer of Domestic-Market Production to a Foreign Site

Abstract The process of transferring production for a domestic market from a domestic site to a lower-cost foreign site is analyzed to determine under what conditions the firm will realize an economic benefit from such a transference. Assumptions are made concerning the particular production technology of interest, and models of both foreign and domestic costs are drawn from these assumptions. The managerial decision of whether or not to move production to the overseas location is framed in terms of a planning model, but the emphasis is on determining the breakeven times for domestic versus foreign operations as functions of the parameters of the various cases which comprise the off-shore sourcing possibilities.

The Selection of International Borrowing Sources

In the evaluation of investment opportunities risk is often a primary con? sideration, Risk is usually not a factor of such importance, however, in the evaluation of borrowing opportunities. But when the borrowing opportunities in? clude the borrowing of foreign currencies, then the possibility of exchange rate fluctuations during the loan period may introduce a significant component of risk. It is our purpose to develop a method for evaluating and selecting inter? national borrowing sources in the face of exchange rate uncertainties. Previous quantitative work on the problem of selecting international bor? rowing sources has been almost entirely deterministic. Textbooks such as those of Robinson [11] and Zenoff and Zwick [14] discuss the choice between borrowing from the local country and borrowing from a foreign source given that the devaluation of local currency relative to that of the foreign currency during the loan period is known. In a previous paper de Faro and Jucker [1] also discuss this problem in the context of certainty and show that some of the earlier explanations were incorrect. Rutenberg [12] and Ness [8] have developed linear programming models of multinational corporations that allow for international borrowing (via inter-subsidiary transfers of funds) under certain exchange rate fluctuations. Exchange rate uncertainties have been considered primarily in the context of currency speculation and the purchase of forward exchange by Feldstein [2], Leland [5], and Folks [3]. These authors have all used the maximization of expected utility as the criterion for determining optimal forward ex? change positions. Lietaer [6] has also used the maximization of expected utility as the criterion in his programming model for generating an efficient set of policies for hedging against devaluation(s). The models of Feldstein, Leland, and Lietaer are all based on the portfolio selection model of Markowitz, and like the Markowitz model they all require the specification of a potentially large number of covariances. The model developed here is also based on the Mar? kowitz model. In an attempt to make the model operational, a substantial part

Simple solution procedures for nonlinear programming problems that are derivative decomposable

Abstract This paper describes a set of relatively simple procedures that are useful for solving a number of nonlinear programming problems. These problems are characterized by objective and constraint functions that are what we call “derivative decomposable”. Starting with a relaxed problem, we show how derivative decomposability yields a simple solution procedure. Then we demonstrate how slightly modified procedures can solve a variety of more complex problems displaying derivative decomposability. The solution procedures are easily understood in terms of their graphical representations. Furthermore, their simplicity and flexibility promise significant computational advantages for a variety of applications.