7.2 Four cases
7.2.4 Case 4: Application of industrial engineering to “promotion” strategy
156 Handbook of industrial and systems engineering 7.2.3.9 Conclusion
This study demonstrates broad guidelines for developing agricultural e-shops. The anal- ysis model of this study is recommended for those who want to develop agricultural e-shops in their own countries, taking into consideration the three flows (cash flow, physi- cal flow, and information flow) from the consumer’s viewpoint. The subdivisions of each of the three flows must be based on the properties of the agricultural products, consumer behavior, and the current e-shop trend in one’s own country so as to develop the most appropriate agricultural e-shop mode.
The industry attractiveness/business strength matrix analyzes two dimensions:
industry attractiveness and business strength, and the influential factors are shown in Table 7.5. Figure 7.1 shows different strategies for different industry attractiveness and business strength.
7.2.4.3 Questionnaire design 1.Content of questionnaire:
We have designed five policies—issuing membership cards, conforming to fresh- food stocking time, providing cooked food service, holding sales at specific times, and increasing the number of unique products—each of which is analyzed with the industry attractiveness/business strength matrix. Table 7.6 shows that each dimen- sion has five key success factors, and an extra factor, “others,” is included. The man- agers of each supermarket score the current strength of the supermarket according to the 11 key success factors, and conclude with the final strength of the two dimen- sions. In this way, we can find the relative position of each policy from the matrix.
2.Transforming questionnaire scores:
In the industry attractiveness/business strength matrix, “high” means the total score range is 11–15, “middle” is 6–10, and “low” is 1–5 (Graph 7.2). The cur- rent strengths of each policy regarding each factor of the supermarkets are trans- formed into scores; that is, “favorable,” “neutral,” and “unfavorable” are transformed into 3, 2, and 1, respectively. The total scores of each dimension are computed to
Industry attractiveness High
High
Middle
Low
Enter into investment
Selective growth
Selective growth
Continue to cultivate
Continue to cultivate
Calculate profit + terminate investment
Continue to cultivate
Calculate profit + terminate investment
Retreat from investment
Business strength
Middle Low
Figure 7.1 Industry attractiveness/business strength matrix.
Table 7.5 Influential Factors for Industry Attractiveness–Business Strength
Industry attractiveness Business strength
Existing competition condition Cost advantage
Bargaining ability to supplier and customer Promotion of efficiency
Demand technology Raw material supply
Profit Market share
Market growth rate Manpower
158 Handbook of industrial and systems engineering
find their corresponding positions in the industry attractiveness/business strength matrix. “Enter into investment” means that the current operation of the supermarket matches the 11 key success factors, so it is very likely that investment will be suc- cessful. “Selective growth” means that this policy can be invested and cultivated, but since some of the key success factors fail to match the current condition, it is necessary to selectively strengthen the weaker factors. “Continue to cultivate” means that the current operation of the supermarket fails to match the key success factors in some aspects, and further investment is held back. After evaluation by high-level managers, if there is a chance to invest successfully, they can choose “Continue to cultivate or no interference.” “Cultivate profit+terminate investment” means that once there is investment in the policy, the investment should be completed once prof- its are made because there may be losses rather than profits with further investment.
“Retreat from investment” means that the policy fails to match the current condition of the supermarket, and there is no way to retrieve capital with further investment, so the investment must be retreated from or withdrawn immediately.
Table 7.6 Key Success Factors Industry attractiveness 1. Existing competition condition
2. Bargaining ability to supplier and customer 3. Demand technology
4. Profit
5. Market growth rate Business strength 6. Cost advantage
7. Promotion efficiency 8. Raw material supply 9. Market share 10. Manpower 11. Others
Business strength Enter into investment
Selective growth Continue to cultivate
Selective growth
Continue to cultivate
Cultivate profit + terminate investment
Continue to cultivate
Cultivate profit + terminate investment
Retreat from investment Policy 4
Policy 2 Policy 5 Policy 3 Policy 1 High (11–15)
Middle (6–10)
Low (1–5)
Figure 7.2 The corresponding positions of policies of the supermarket of Farmers’ Association in the strategy matrix.
7.2.4.4 Analysis results
This study takes the supermarket of a Farmers’ Association as the subject, and transforms the three items “favorable,” “neutral,” and “unfavorable” in the questionnaires into scores of 3, 2, and 1, respectively. After totaling the scores of each dimension, we find that policies 1, 3, and 5 belong to “enter into investment,” whereas policies 2 and 4 belong to “selective growth.” The corresponding positions of each policy in the strategy matrix are shown in Graph 7.2.
7.2.4.5 Conclusion
This study uses the industry attractiveness/business strength matrix to help traditional supermarkets pinpoint the most advantageous promotion strategies or improvements so as to upgrade the overall operation performance.
References
Berson, A., Smith, S., and Thearling, K., Building Data Mining Applications for CRM, Translated by Ye, L.-C., McGraw-Hill, Taipei, 2000.
Chen, R.S., The introduction to auction system—a flower case, The Management and Automatic of Wholesale Agricultural Products Market, Taiwan Agricultural Mechanization Research &
Development Center, Taipei, 1997, pp. 28–42.
Chen, X.-Z., Strategy Management, Taipei Publisher, Taipei, 1987.
Han, J. and Kamber, M., Eds., Data Mining: Concepts and Techniques, Academic Press, San Diego, CA, 2001.
Hedley, B., Strategy and the business portfolio, Long Range Planning, 10(1), Feb 1977, pp. 9–15.
Hsiao, S.W., The Theory and the Application of Quantitative Decision, Course Handouts, National Cheng Kung University, Taiwan, 2000. (Cited in Chen, C.N. and Ting, S.C., A study using the grey system theory to evaluate the importance of various service quality factors, Int. J. Qual. Reliabil.
Manage., 19, 838–861, 2002. NIST, E-Commerce: The Future is Now, Nation Institute of Standard and Technology, 1999.)
Shen, J.C., Shi, T.H., and Wang, S.C., An evaluation study using grey relational analysis in travel risks,Proceedings of the Conference on The Grey System Theory and its Applications, Taiwan, 1998, pp. 185–193. (Cited in Chen, C.N. and Ting, S.C., A study using the grey system theory to evalu- ate the importance of various service quality factors, Int. J. Qual. Reliabil. Manage., 19, 838–861, 2002.)
Turban, E., Jae, L., David King, H., and Michael, C., Electronic Commerce: A Managerial Perspective, Prentice Hall, Upper Saddle River, NJ, 2000.
Yesil, M., Creating the Virtual Store, Wiley, New York, 1997.
Wu, H.-H., Deng, J.-L., and Wen, K.-L., Introduction to Grey Analysis, Kao-Li Publisher, Taipei, 1996.
161