A Model for Candidate Selection of Strategic Alliances: Case on Industry of
Department Store
Chia-Nan wang'*, Kun-Zhong Li
2,Cheng-Ter HO', K.-L. yang3, Chih-Hong wang4
' ~ e ~ a r t m e n t
of Industrial Engineering and Management
National Kaohsiung University of Applied Sciences
en. wang@cc. kuas. edu. tw
2
Kainan University, Tauyuan,
338, Taiwan
3 ~ a t i o n a l
Defense University, Taipei, 106, Taiwan
4 ~ e w f a n c y
Technology Inc., Taipei, 106, Taiwan
Abstract
In a globally competitive environment, how corporations use strategic alliances to gain a competitive advantage has become an important topic. Based on data envelopment analysis (DEA) and the heuristic technique, this study proposes a model which is termed the candidate selection of strategic alliance (CSSA). The objective is to find the most proper partner for strategic alliance. Realistic data for the
industry of department store are collected from Taiwan published stock market. The results are sound by review of many industrial managers and indicate that CSSA can effectively provide recommendations for enterprises to find the proper candidates of alliance.
Key Words: Data Envelopment Analysis, Eficiency,
Strategic Alliance
1. Introduction
With the rapid growth in the new models from channels, the department store industry has changed from the traditional commercial operation model. Many enterprises are commencing implementation of strategic alliances and multi-sector development. The department store industry is transforming its direction from concentrating on consumers to channels of
delivering products and services. This has also
prompted an increase in interaction among enterprises and more emphasis on the arrangement of marketing channel as well as strategic alliances.
In this globally competitive market, it becomes more and more difficult for enterprises to retain their advantages for long periods of time. This is the reason for many enterprises starting to search for strategic alliance partners in order to strengthen their competitive advantage for remaining success in their
markets. However, facing a future of uncertainty,
choosing the proper partner for the "strategic alliance" has become a difficult challenge.
Therefore, the objective of this study is to propose a model of candidate selection of strategic alliance (CSSA) to assist decision makers in choosing the perfectly match partner for an alliance. CSSA can assist enterprises in starting at the right place even in
the early planning stage. A clear direction of
improving operational efficiency following the alliance is also presented in this model.
DEA was first proposed by Charnes, Cooper and Rhodes (CCR) [I]. Its original idea comes from the measurement model of production efficiency proposed by Farrell [2]. DEA itself is a non-parametric method for assessing the relative efficiency of decision malting units (DMUs) based upon multiple inputs and outputs. The primitive DEA model adopts the concept of
production in microeconomics: efficiency = output I
input. Banker, Charnes, and Cooper (BCC) [3]
developed a new model from the CCR model to understand the problems of pure technical efficiency (PTE) and scale efficiency (SE).
Most of DEA applications are focused on
performance evaluation. Durand and Vargas [4]
analyze the ownership, organization, and private firms' efficient by DEA. However, DEA can not only be used in performance evaluation and can be extended more.
Some researches extend DMU combination in DEA to study strategy. Wang and Wang [5] provide an application model for merger evaluation in high-tech business. Delmas and Tokat [6] use DEA to analyze how the process of retail deregulation affects the comparative efficiency of governance structures. To our best knowledge, there are no researches reported that use DEA to select strategic alliance candidates.
The remaining sections of this paper are organized
as followed. Section 2 develops the DEA-based
heuristic method for CSSA. Section 3 shows the
implementation and analysis by the realistic data for
industry of department store in Taiwan. Finally,
conclusion and recommendations are made in section 4.
IETMall
A: Strategic alliance possessing reciprocal advantageous resources (I point)
B: Strategic alliance beneficial to advantageous expansion of project company (1 point)
C: Provision of key resources and data (1 point)
D: When in Alliance, project company possessing objectivity and superiority (I point)
In regard to the evaluation scores, the results and priority order of the groups are:
Group 2 has score of 4 points and is first priority.
Both the target company and candidate company can reach the best efficacy in the industry. This alliance increases the operational capacity for both the target
and candidate company. The assessment of key
resources and virtual channels are strengthened.
Furthermore, the target company reaches an
advantageous condition through possessing more sovereignty, independence and superiority.
The second and consideration is Group 1 and it has
3 points. The operation capacity for both companies
has increased. The material and virtual channels
cooperation are also increased. However, since the candidate company is in the state of optimum operation efficiency, it might have less incentive to form an alliance. The target company requires more time to communicate with Group 1 candidates for the purpose of trying to persuade them to cooperate.
The third consideration is Group 3. The target company obtains key resources advantage through cooperation of the material and distribution channel, but negatively affects the earning results. The target company can thus use scale variables analysis for adjustment in inputs and outputs. Once adjustment is achieved, this combination can reach the best state of operational results and the target company can also use its own superiority to gain more control of direction, independence and superiority during strategic alliance.
Group 4 is the worst choice. This combination only
increases the key resources of the target company and does not increase the competitive advantages for any member of the alliance. This research does not recommend this kind of alliance.
4. Concluding Remarks
This study provides an effective search for the most
suitable strategic partner when a corporation
implementing strategic alliance, as well as the analysis of the operational efficiency after the forming of the alliance. The realistic data of Taiwan department store industry were experimental and the results were discussed in a forum with several industrial managers (including the managers from ETMall) and their
feedback was sound. CSSA is recognized to
effectively provide all essential analysis and
recommendations to enterprises for strategic alliance. Future studies should find a more profound collection of variables in order to strengthen the feasibility and relevance of the research, including any element that influences operational results, such as total capital, number of stores, etc. Moreover, studying the company products strategy (a single product or a brand) and including this in kture research can make assessment more valuable.
1.
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