partner selection in international joint ventures : a ...

PARTNER SELECTION IN INTERNATIONAL JOINT VENTURES : A MULTI-OBJECTIVE APPROACH YANNIS A. HAJIDIMITRIOU & ANDREAS C. GEORGIOU Department of Business Administration, University of Macedonia 156 Egnatia Str., 54006 Thessaloniki, Greece

ABSTRACT

PROBLEM DESCRIPTION

The formation of International Joint Ventures (IJVs) has become a widely used mode of international expansion. The selection of the appropriate partner constitutes one of the major factors of success for the IJV. There have been several research efforts which were concerned with the study of criteria for the selection of a partner. Nevertheless, to the best of our knowledge, there has not been any contribution that recommends a quantitative model which can evaluate potential candidates and lead to the selection of the optimal partner. The objective of this paper is to develop a quantitative model, based on the goal programming technique, that would make such recommendations.

The facts presented in the previous paragraphs have contributed significantly to the rapidly rising strategic importance of IJVs. As a result, IJVs have become a critical concern for international business and that, in turn, has instigated extensive relevant research since late 60s - early 70s. Furthermore, an intriguing research result, that is supported by several studies, is that many IJVs have had unsatisfactory performance, with the rate ranging from 37% to 70% [9] [7] [5]. Although there are many reasons for such a high rate of unsatisfactory performance, one of the most common factors cited by managers as contributing significantly to unsatisfactory performance, is the unsuccessful selection of partners. There are several issues that render the process of selecting the right partner critical for the success of the IJV. According to Geringer [4] and Brouthers et al [2] some of the most important issues are the financial, human and technical capabilities desired by the firm who is looking for a partner, the involvement of all partners in major strategic decisions concerning the IJV, and the strong need for compatibility of their strategic objectives, management styles and cultures.

INTRODUCTION International Joint Ventures (IJVs) are described as business entities that are created by two or more legally distinct organizations (the parents) among which at least one is headquartered outside the venture’s country of operation. All parents actively participate in the decision making activities of the jointly owned entity [5]. The formation of IJVs is becoming one of the most commonly used modes of international expansion. There are many reasons that motivate firms to use IJVs so extensively. Apart from gaining access to new markets, other reasons for the increasing popularity of IJVs is the sharing of business risks and resources among the partners, attaining ec of scale or scope, and gaining knowledge from each other [4]. The rising popularity of IJVs is also supported by empirical research. As the literature shows, the number of joint ventures formed by U.S. firms increased by 423% over the period of 1986-1995 [8]. Another research effort has shown that, as international co-operation becomes increasingly complex, IJVs are preferred to other contractual agreements [3]. Generally, as the global economy is becoming a reality, firms that wish to remain competitive in the international business environment need to expand internationally and the formation of IJVs has become an excellent vehicle to bear the enormous costs and risks implied by such an undertaking.

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There are several research efforts which investigate the process of selecting the right partner [1] [5] [2] [10]. Most of these papers focus their attention on the significance of using the appropriate selection criteria for the success of the IJV. In addition, the research results show that i) it is not possible to develop a widely applicable list of selection criteria, ii) the nature of selection criteria shows a dynamic behavior, and iii) the criteria differ even for the partners of the same IJV. Furthermore, our research revealed that current literature lacks a quantitative approach that could indicate who is the most appropriate partner. Therefore our objective is to develop a quantitative model based on the goal programming technique that would make such recommendations. The same technique was first applied by Schniederjans & Hoffman [12] to study the problem of selecting a firm for acquisition or merger in the international environment, and also by Min & Melachrinoudis [11] to study the international site selection problem.

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MODEL FORMULATION Let us now assume that a firm has chosen the country where it wishes to expand its activities and is looking to find a partner among several local candidates to set-up a joint venture. The equity share of the local firm in the joint venture has been determined by the foreign firm in advance and it is the same for all candidates. We will proceed now with a formulation which uses selection criteria similar to those presented by Beamish [1] and Geringer [5]. Some of these criteria are quantitative and measurable, while, some others are qualitative in nature and depend on the subjective opinion of the management. An indicative list of such criteria, reflecting what each candidate partner could contribute to the achievement of the foreign firm’s strategic objectives, is the following: faster entry into the local market, local political advantages, inexpensive labor, raw material supply, knowledge of current business practices, availability of experienced managerial or technical personnel, access to local financial resources, knowledge of local economy, politics and customs, export opportunities, availability of patents, licenses or other proprietary knowledge, existence of marketing or distribution systems etc. For each of the S criteria used in this selection process, a relevant goal is set by the management of the firm by defining an aspiration level. The proposed model assumes that there are I potential partners and that the IJV will sell its product in J countries, including the home market of the joint venture. Let us also assume that, in addition to the S selection criteria, there is a top priority criterion for the firm which is the achievement of a profit aspiration level. Then, the profit goal takes the following form:

∑∑ [(e p I

J

i =1 j =1

j

j

− ci − mi − t j )X ij ]

I

K

i =1

k =1

− ∑ ( Ei + TRCi + ∑ rik ek Fk )Yi + d p− − d p+ = bp . In the above expression, the decision variables are: i) the X ij ’s, which represent the quantities produced and shipped to country j when partner i is chosen, and ii) the Yi ’s, which are binary variables taking a value of 1 if partner i is selected and 0 otherwise. Concerning the parameters included in the same expression, e j is the exchange rate between the currency of country j and the local currency, p j is the product unit price in country j,

ci stands for the unit production cost (apart from material and transportation costs), m i corresponds to the cost of raw materials per unit of product, and t j is the unit transportation cost to country j. Furthermore, Ei is Proceedings Decision Sciences Institute Conference

the establishment cost of the joint venture given that partner i is selected (net of financial incentives and subsidies that the local government might offer), TRCi is the total personnel training cost if partner i is chosen, rik is the interest rate for loans in currency k available to the joint venture when partner i is selected, ek corresponds to the exchange rate between currency k and the local currency, and Fk is the amount of loan granted to the joint venture in currency k. In the same expression, parameter bp denotes the aspiration level for the profit goal. The latter could be either a utopian value or a realistic amount set by the management of the foreign firm. In addition to the two sets of decision variables described in the previous paragraph, there are two more deviational variables which accompany the aspiration level for profits, denoted by d p− and d p+ . These variables represent the underachievement or overachievement of the profit aspiration level, respectively. In goal programming, the objective is usually the minimization of undesirable deviations from various clearly defined goals. In this respect, the objective function consists of these deviational variables. Consequently, since in this case the undesirable deviational variable is the − underachievement of the profit goal, d p should be minimized and therefore it will be included in the objective function. The mathematical expressions for the goals defined for the remaining selection criteria, may take the following general form: aisYi + d s− − d s+ = bs for s ∈ S .

∑ i∈I

Each parameter ais reflects the contribution of the corresponding criterion s to the achievement of the aspiration level of the relevant goal, provided that partner i is chosen. Furthermore, these goals can be categorized in m priority groups and finally form the following lexicographic objective function: LexMin z = z p , z1 ,..., zm where z P = d P− .

{

}

All remaining m objective functions are sums of the appropriate deviational variables taken from the mathematical expressions for the S goals. The deviational variables included in each of the m priority groups, could also be weighted according to the relative importance of the corresponding criteria. The lexicographic minimization is restrained by a set of rigid constraints regarding product demand ( Dij ), production capacity (CAP), and the number of partners to be selected. In this case, it is assumed that the firm wishes to select only one partner. The mathematical formulations for these constraints are the following:

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I

I

∑ X ≤ ∑Y D ij

i =1 J

∑X j =1

I

∑Y i =1

i

i =1

ij

i

ij

for all J countries,

≤ CAP ∗ Yi for all I partners, and

= 1.

In order to apply this model, the management of the foreign firm should i) determine the appropriate selection criteria, ii) prioritize them according to their importance, iii) set aspiration levels for each goal, and iv) collect the necessary data (scores) for all candidates. All these information could be tabulated in a table like the following: Table 1. Typical Data for the Partner Selection Model Selection Criteria

Criterion

Priority

Candidate Scores

Goal

Partner 1

… Partner I

The quantitative criteria can take various forms and measurement units such as monetary units or percentages. A five point scale can be used to convert management’s subjective opinions concerning qualitative selection criteria into quantitative scores for each candidate. In addition, the model is capable of taking into consideration conflicting and prioritized goals, thus providing the most satisfactory (in goal programming terms) solution. Finally, the model is quite flexible and it can accommodate changes related to goal priorities and parameter values, facilitating in this way, sensitivity analysis and the investigation of what-if scenarios. CONCLUSIONS In conclusion, the enhanced strategic importance of IJVs has made them a critical concern for international business and it has instigated extensive research on this topic. It is generally accepted that the successful performance of an IJV strongly depends on the choice of the right partner and that this selection is becoming an increasingly complex decision process. The nature of the partner selection problem justifies the application of multiple objective methods. The introduction of such techniques in the decision making process, creates significant potential for positive contribution to the partner selection process and therefore to the improvement of the performance of IJVs. There is of course great potential for further research. The model presented in this paper could be extended so that i) the selection of multiple partners can be considered, ii) the dynamic nature of the problem could be introduced, iii) the target country and the partner could be selected simultaneously, and of course iv) more than one goals

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could be introduced in the top priority group, such as the minimization of risk and the determination of the optimal mix of loans in various currencies. Preliminary results of our effort to apply the model in a Greek firm, as well as the application of similar goal programming models in the international site selection problem ([6] [11] [12]) provide significant evidence that such models can be very useful for the management of firms dealing with partner selection problems, as long as reliable data for all candidates can be collected. REFERENCES [1] Beamish, P.W. (1987), Joint ventures in LDCs: partner selection and performance, Management International Review, 27, 1, 23-37. [2] Brouthers, K.D., Brouthers, L.E., and Wilkinson, T.J. (1995), Strategic alliances: Choose your partners, Long Range Planning, 28, No3, 18-25. [3] Garcia-Canal, E. (1996), Contractual form in domestic and international strategic alliances, Organization Studies, 17/5, 773-794. [4] Geringer, J.M. (1988), Selection of partners for international joint ventures, Business Quarterly, Autumn 1998, 31-36. [5] Geringer, J.M. (1991), Strategic determinants of partner selection criteria in international joint ventures, Journal of International Business Studies, First Quarter, 41-62. [6] Hajidimitriou, Y.A. and Georgiou, A.C., Investigation of international location planning techniques for the Balkan region, Proceedings of the 4th Balkan Conference on Operational Research, Thessaloniki, October, 1997, (forthcoming). [7] Harrigan, K.R. (1985), Strategies for Joint Ventures, Lexington, Mass.:, Lexington [8] Hitt, M.A., Ireland, R.D., and Hosskison, R.E. (1997), Strategic Management: Competitiveness & Globalization, West. [9] Janger, A.R. (1980), Organization of International Joint Ventures, New York: Conference Board. [10] Kumar, B.M. (1995), Partner-selection-criteria and success of technology transfer: A model based on learning theory applied to the case of Indo-German technical collaborations, Management International Review, Special Issue, 1, 65-78. [11] Min, H., and Melachrinoudis, E. (1996), Dynamic location and entry mode selection of multinational manufacturing facilities under uncertainty: A chance-constrained goal programming approach, International Transactions in Operational Research, 3, No1, 65-76. [12] Schniederjans, M.J., and Hoffmann, J. (1992), Multinational acquisition analysis: A zero-one goal programming model, European Journal of Operational Research, 62, 175-185.

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