Global plant capacity and product allocation with pricing decisions

doi:10.1016/j.ejor.2003.12.022

European Journal of Operational Research

Volume 165, Issue 1, 16 August 2005, Pages 157-181

https://doi.org/10.1016/j.ejor.2003.12.022 Get rights and content

Abstract

Trade-offs in global manufacturing decisions involve markets, resource costs, trade-barriers, currency exchange rates, joint ventures and investments. We develop a model that optimizes plant investment decisions, while ensuring that the plant investment overhead is optimally absorbed by products produced from that plant. The model also, simultaneously, determines prices by products and countries. The special structure of the model is exploited to construct a fast solution procedure. The model is used to study the implications of labor cost, transportation cost, demand, and import tariff on production quantities, investment, and overhead absorption pattern. Implications of changes in other global parameters such as local-content rule, local taxes, size of the market in a country, and long-term exchange rates are also studied.

Introduction

The phenomenal growth in foreign direct investments (FDI) in the last three decades (Ferdows, 1993), points to their overwhelming attractiveness. The pattern of investment, however, has changed from being primarily in the developing countries to mainly in the industrialized countries, in the last 10 years (Flaherty, 1996; Chakravarty, 1999). This shift in investment emphasis has been explained by Dunning (1993), as a shift from a resource-seeking to a market-seeking orientation. However, this is not to imply that market size is all that matters in FDI. Importance of factors such as tariffs, taxes, currency exchange rates, shipping, supplies, trade-barriers, local resources, and local demands have been discussed extensively in the literature (Cohen and Lee, 1989; Tombak, 1995; Dasu and Li, 1997; MacCormack et al., 1994; Hadjinicola and Kumar, 2002). Kanter (1995), describing Gillette's operations, reports that 70% of company's sales of $6 billion is outside the US, and that it has 58 facilities in 28 countries to serve markets in 200 countries.

The question, therefore, is how should a company configure its plants around the world to supply a global market with variations in customer preferences, resource availability, and cost structures from country to country (Cohen et al., 1989; Naik and Chakravarty, 1994). It is obvious that such a plant configuration must allow for multiple products, country and product specific pricing, and export and import of products between countries (Grunwald and Flamm, 1985). It is also clear that for investment in a manufacturing plant in a country to be viable, it must be completely recoverable from the outputs of that plant during its life cycle. To ensure investment recovery, accountants allocate overheads to products, based on some formula, and then add a mark-up percentage to determine the product's unit price. Pavia (1995) has shown how overhead allocation can be optimized, based on product demands and unit costs, for given mark-up percentages, and shows that some products may not absorb any overhead at all. Bhutta et al. (2003) considers integrated decision making for investment, production, and distribution, assuming fixed prices. Taylor (1997) discusses a model that integrates product choices with global plant capacities, assuming known unit prices and nonexistence of trade barriers. Unit prices are assumed to be known and global trade-barriers are not included in this model, however. Syam (2000), similarly, assumes fixed unit prices and ignores trade-barriers, in his model of regional capacity planning. These three models are similar in that they assume fixed unit prices, enabling formulation of linear models with mixed integer variables.

We argue, in this paper, that while plant investment creates manufacturing capacity, it also creates an overhead burden. Thus, if a country is positioned to supply to a large regional demand, it must also be prepared to absorb a large overhead. Clearly, a high overhead absorption by a product would be detrimental to its export, especially to countries with high import tariffs. It should, therefore, be apparent that adding capacity might reduce the “real” profit margin, which is inclusive of overhead cost. What may not be obvious, however, is the way the overhead allocation decision is intertwined with decisions related to how much and where (country) to invest, how much of each product to produce, how much of it to export to other countries (which countries?), and what prices to charge for products in different countries.

Simple economic logic tells us that the major reasons for investing in a foreign country are weak currency, low labor cost, high import tariff, low local taxes, and high demand for the product (Dunning, 1993). Local content rules, on the other hand, may lead to increase in investment in some countries at the expense of countries that impose too many barriers. Foreign investments in Asia and in EEC countries are examples of companies seeking low labor cost, and low tariffs, respectively. In certain scenarios, special factors such as first-mover advantage, emerging markets, and joint-venture opportunities, may also impact global investment decisions (Bartlett and Ghoshal, 1991). We do not analyze such scenarios in our model.

The decisions usually under a company's control are (a) where and how much to invest, (b) what quantities of which products to produce in a plant, (c) which products to absorb (and how much) the plant investment overhead, in a country, (d) what quantities of which products to export from a country, and (e) how to price the products in each country of operation. Investment decisions are generally made only once during a plant's life cycle, based on average parameter values. Actual values of parameters may, however, vary during the plant's life cycle. Thus the decisions in (b) to (e) will need to be reestablished each period for given plant sizes, in different countries.

In this paper, we first develop and solve a quantitative model to determine specific values related to the above decisions. We then use this model to generate managerial insights, such as, (i) how do tariff rates impact overhead allocation decisions, (ii) should products with low variable cost absorb a higher share of overheads, (iii) during a period of trade liberalization (as is now) should a company increase its foreign direct investment, (iv) when does it make sense to invest in improving plant productivity, and (v) how does a weakening of currency in a country impact investment, production, and export/import decisions from that country. The salient issues in the context of investment in plants, and globalization are discussed in Section 2. In Section 3 we outline the mathematical model, and establish its properties. Approaches for solving the model are discussed in Section 4. Results related to the sensitivity of profit and investment with respect to parameter values are studied in Section 5. In Section 6 we discuss the impact of country specific costs such as fixed cost of setting up a plant, and the exchange rates. Issues related to market size and local content rules are discussed in Section 7, and conclusions are outlined in Section 8.

Section snippets

Major issues in investment decisions

As mentioned earlier, the country-specific factors such as resources, markets, and trade-barriers would be crucial to global investment in facilities (Vernon, 1966). The attribute of “resource” is very similar to that of Porter's (1990) factor conditions. In our model we interpret this as direct costs, and it is inclusive of labor and material costs. We model the “market” attribute by three sub-attributes: distance of the country from other countries under consideration, customer-preferences

Profit maximization

The decision facing a company is how to maximize its profits over a planning horizon, accruing from sales of products manufactured in several countries. We assume that the company has a fixed sum (F) available for investment in plants at the start of the planning horizon.

Based on earlier discussion, the optimization model can now be stated as
Program P₁ $Maximize z=∑_{j∈J} ∑_{i∈I} ∑_{k∈K} q_{ijk} a_{ijk}^{1/n} −(1+t_{ik})x_{ij} −T_{ijk} q_{ijk}$ $subject to ∑ i∈I ∑_{k∈K} {x_{ij} −v_{ij}}q_{ijk} ⩾F_{j}, ∀j,$ $∑ i∈I ∑_{k∈K} β_{ij} q_{ijk} ⩽w_{j} F_{j}, ∀j,$ $x_{ij} ⩾v_{ij}, ∀i and j,$ $∑_{j∈J} F_{j} ⩽F,$ where F

Solving the optimization model for tariff and no-tariff scenarios

One of the objectives of this research is to investigate whether or not the global plant location problem requires new modeling and/or solution approaches. Note that by assuming the tariff rate t_ik to be zero for all i and k, our model can be applied directly to a domestic (one country with multiple regions) setting. We next investigate the implications of setting t_ik=0 to the model, and its solution approach.

Profit and investment sensitivity

To study the variations in profit and investment with parameter values, a small experiment with ten products and five countries was conducted. It is assumed that a prescreen of potential sites disqualified two of the five possible sites from plant location. The product could be sold in all five countries, however. The parameter values were generated randomly within specified ranges. The chosen ranges were: v_ij (5–15); T_ijk (2–8); a_ijk (500,000–1,000,000); and β_ij (4–10).

Variations in profit and

Fixed cost of setting up plants

Assume that there is a fixed cost of A_j for setting up a plant in country j (Hodder, 1984). It is clear that the objective function (11) will be augmented as $Maximize y=z−∑_{j∈J} A_{j} θ_{j},$ where θ_j is a 0,1 binary variable. θ_j=1 if a plant is constructed in country j; 0 otherwise. In addition to constraints , we would have $F_{j} ⩽Mθ_{j},$ where M is a large number.

Unlike program P₁, where it was optimal to produce in all three countries considered, the impact of including the fixed cost A_j, would be to not produce

Market size and local content

Observe that the demand curve used in the model, D_ijk=a_ijkp_ijkⁿ, is asymptotic in both demand and price axes. That is, demand shoots up rapidly with decreasing price. Although, a_ijk can be estimated for the demand curve to hold over a wide range of price, the predicted demand at very low prices may be absurd, as the size of the buying population (market size) may vary tremendously from country to country. In any case, the total demand may not exceed the country's population. For example, the

Conclusions

We have clearly demonstrated how plant location, production quantities and export/import quantities can be determined simultaneously with pricing (inclusive of overhead allocation). We have also established why plant related fixed cost do not directly influence the above relationship. The clear distinction between domestic and international plant location scenarios and their solution approaches is striking.

In a domestic setting (Section 4) where tariffs are zero, we show that the optimal

References (30)

C. Bartlett et al.
Managing Across Borders: The Transnational Solution
(1991)
K. Bhutta et al.
An integrated location, production, and investment model for a multinational corporation
International Journal of Production Economics
(2003)
A. Chakravarty
Profit margin, process improvement and capacity decisions in global manufacturing
International Journal of Production Research
(1999)
M. Cohen et al.
Resource deployment analysis of global manufacturing and distribution network
Journal of Manufacturing and Operations Management
(1989)
M. Cohen et al.
International manufacturing and distribution networks: A narrative model framework
S. Dasu et al.
Optimal operating policies in the presence of exchange rate variability
Management Science
(1997)
J. Dunning
The Globalization of Business
(1993)
Ferdows, K., 1993. Leveraging America's foreign production assets. In: Proceedings of the Symposium on Globalization of...
K. Ferdows
Making the most of foreign factories
Harvard Business Review
(1997)
T. Flaherty
Global Operations Management
(1996)

V. Govindrajan et al.

How firms use data in price decisions

Management Accounting

(1983)

J. Grunwald et al.

The Global Factory: Foreign Assembly and International Trade

(1985)

G. Hadjinicola et al.

Modeling manufacturing and marketing options in international operations

International Journal of Production Economics

(2002)

R. Hayes et al.

Restoring Competitive Edge: Competing Through Manufacturing

(1984)

J. Henderson et al.

Microeconomic Theory: A Mathematical Approach

(1980)

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Production, Manufacturing and LogisticsGlobal plant capacity and product allocation with pricing decisions

Abstract

Introduction

Section snippets

Major issues in investment decisions

Profit maximization

Solving the optimization model for tariff and no-tariff scenarios

Profit and investment sensitivity

Fixed cost of setting up plants

Market size and local content

Conclusions

Managing Across Borders: The Transnational Solution

An integrated location, production, and investment model for a multinational corporation

International Journal of Production Economics

Profit margin, process improvement and capacity decisions in global manufacturing

International Journal of Production Research

Resource deployment analysis of global manufacturing and distribution network

Journal of Manufacturing and Operations Management

International manufacturing and distribution networks: A narrative model framework

Optimal operating policies in the presence of exchange rate variability

Management Science

The Globalization of Business

Making the most of foreign factories

Harvard Business Review

Global Operations Management

How firms use data in price decisions

Management Accounting

The Global Factory: Foreign Assembly and International Trade

Modeling manufacturing and marketing options in international operations

International Journal of Production Economics

Restoring Competitive Edge: Competing Through Manufacturing

Microeconomic Theory: A Mathematical Approach

Production, Manufacturing and Logistics
Global plant capacity and product allocation with pricing decisions