Discussion

Chapter 4. Empirical Results and Analysis

4.4 Discussion

According to the efficiency scores (as in table 4), service-satisfaction index/pure technical efficiency cross-tabulation (as in figure 6), and attractive and progress scores for the retail stores in different evaluation context (as in table 7), we can draw a reorganization alternative map of 31 GWSM stores and the map shows us the whole picture of each GWSM store’s RTS and location.(as in figure 8) The Taiwan’s map will divide into North, West, South and East four parts and discuss the analysis results.

In North area, there have 14 GWSM stores because this area lives around one fourth populations in Taiwan announced by Ministry of the Interior 2004 annual report. Only in Taipei City has 5 GWSM stores but 4 of them belong to DRS, the reasons are Taipei is Capital in Taiwan and its economical and business activities are popular so the famous companies want to set up the big sale markets or outlets in Taipei city. In the meanwhile, GWSM stores will encounter the competition from the above big outlets so we suggest Beibei (CRS) needs to keep operating because of excellent performance and Beijhong (DRS), Beisi (DRS), Beidong(DRS), Beinan (DRS) four stores, Beisi and Beinan should reduce their size and improve their service to become CRS and deactivate Beijhong and Beidong owing to their poor TE in Taipei city. In Taipei County, Shuanghe (DRS) store is inefficient, we suggest it should merge in Banciao (CRS) let it becomes more competitive. In Taoyuan County, we suggest Taoyuan01 (DRS) store should shut down and re-allocated the resources to Taoyuan02 (IRS) because of the inefficiency and many deactivated military units. It can let Taoyuan02 increasing its size and become CRS. In Hsinchu, Hsinchu (CRS) store has good performance so it needs keep providing service to customers but Guangfu (IRS) store we suggest MND to keep this store and improve its size to ideal scale.

In West area, Miaoli store (IRS) in Miaoli County has a poor performance and not reach

constant scale but we suggest that should enlarge its scale and become constant return to scale because Miaoli only has one GWSM and GWSM belongs to nonprofit organization. Pinglin (DRS) store in Taichung city should deactivate because of its inefficiency and many troops are dissolved in Taichung. In Chiayi County, Chiayi (DRS) store should uphold and try to improve the poor performance because Chiayi, Yulin, Changhua and Nantou Counties only has this GWSM store and at the same time Chiayi has a lot of military bases including an air force base. Just like we mention in chapter 1 “GWSM retail store is a nonprofit organization and their main purpose is supporting soldiers, reservists, veterans and their dependents”.

In South area, Tainan County, Tainan01 (DRS) store should merge into Tainan02 (IRS) store and Tainan02 store can improve scale, performance and save the manpower cost. In Kaohsiuang and Pingtung, there are the key position of military units and schools in Taiwan so six of them can reach CRS only Gaosyong (IRS) store belongs to IRS and has the worst operation performance (Te=0.565) in South area. In Gaosyong, there has R.O.C. Air Force Academy, Air Force Institute of Technology, and Gaosyong Air Force Base etc. It should have enough loyal customers, but it has poor performance should have the problems of operation skills, so we need focus on the management skill. The remnants of the five GWSM stores, we suggest keep improving their Service-satisfaction to become the benchmark GWSM stores in Taiwan.

In East area, Taitung (DRS) store has the worst performance in 31 GWSM stores, but Taitung County has an AFB and a lot of military units, and it only has one GWSM so we suggest keeping this store and improving its service quality and operation performance. In Hualian, we suggest Hualian (DRS) store can merge into Meilun (CRS) store because of its inefficiency and Hualian population is less. In Ilan, we suggest keep Ilan (IRS) store because Ilan only has one GWSM store we need consider the purpose for supporting the military customers.

Hsinchu County

Figure 8. Map of GWSM”s RTS and Location.

Chapter 5. Concluding Remarks

5.1 Conclusions

Although the retail industry efficiency has been widely discussed in previous literature and DEA technique is frequently used, there are still some important points not touched.

Few research studies about the retail industry have been conducted in emerging countries (such as Taiwan) while applications of DEA for the evaluation of military retail stores have been very limited. This study provides a milestone analysis based on DEA to investigate Taiwan and assist the MND in improving the GWSM stores operational management with insights in resource allocation. Additionally, the application of context-dependent DEA thus far is rarely discussed in the literature of retail industry. This paper therefore aims to explore the operating efficiency of military retail stores and the application of context-dependent DEA from a more complete viewpoint.

The findings are now briefly enumerated as follows. Firstly, the overall technical inefficiencies of GWSM retail stores are primarily due to the pure technical inefficiencies rather than the scale inefficiencies. This also suggests that managers should focus on removing the pure technical inefficiency of retail stores, before improving their scale efficiencies. Secondly, the retail stores located on north on the average operate better than those in the other three regions. The findings show that the retail store’s region plays key role which affect its operating performance. Thirdly, the customer/facilities satisfaction levels do have a very significant influence upon retail store’ performance. Therefore, managers should expect to spend most of their efforts in this area for inefficient retail stores.

Fourthly, the attractiveness measure shows that Hsinying retail store is the most attractive retail store, i.e. global leader, no matter which evaluation context is chosen, and the progress measure shows that Taitung retail store is the worst retail store. Fifthly, the

context-dependent DEA successfully draws the GWSM retail stores’ benchmark-learning roadmap to improve the inefficient retail stores progressively and can identify the best retail store. Last, the assessment herein can assist the Ministry of National Defense to improve the operational management of GWSM and contribute to the GWSM retail stores in delivering better and efficient services to the soldiers, veterans, and their dependents.

5.2 Suggestions

In real situation for improving GWSM performance, we suggest that MND needs focus on the future priorities as follows:

1. Sales Promotion:

Even though GWSM services for specific customers, it still needs for attracting the people’s sighting and purchasing desire. Because of the competition by civilian’s big sales market such as Kmart, Carrefour, RT-Mart, MATSUSEI etc., customers want to compare the price, quality of products with the big market store. If GWSM does not use the fancy way to attract and maintain the customers, they will be closed very soon because no people want to walk in GWSM.

2. Enhance Quality Control Process:

Because the living standard of military already promoted in recent years, the customers do not care the little price difference but they do more care about the quality of merchandise. So GWSM needs effectively control over the suppliers’ merchandise, it can fit normal standards fresh, good looking and high quality, that we can hold the customers for a long time. If customers met one time for buying an unqualified products, they will never walk in your store again.

3. Integrated sale market conditions:

Integrating GWSM’s marketing information and avoiding duplicated investments, different area has different operating strategies. For example, GWSM in Taipei, the merchandises need sale delicate products, otherwise, it will lose the competition powers, but in low income areas, it should sale par goods, if not, GWSM will threaten the customers. Therefore, MND should integrate each GWSM conditions and share the information to improve operation efficiency.

4. Merge and deactivate the inefficient GWSM:

MND should refer to the GWSM efficiencies by above research, then; can decide which retail store should merge and deactivate because of the poor efficiency, bad location, and low competition. MND can relocated the resources and maintain the efficient stores, therefore, GWSM can survive in the future and support for military soldiers (including cadets in military academies), reservists, veterans and their dependents.

A further investigation would be the examination of performance over time (panel data) by using the Malmquist productivity change index techniques. Such an approach would allow a dynamic view of the multidimensional performance of retail stores. It is also hoped that the models and methods implemented in this study can bring about other related researches to a variety of industries.

References

[1] Andersen, P. and Petersen, N.C. (1993), A procedure for ranking efficient units in data envelopment analysis, Management Science 39 (10), 1261-1264.

[2] Angulo-Meza, L. and Lins, M.P.E. (2002), Review of methods for increasing discrimination in data envelopment analysis, Annals of Operations Research 116 (1), 225-242.

[3] Baker, R.C. and Talluri, S. (1997), A closer look at the use of data envelopment analysis for technology selection, Computers Industry and Engineering 32 (10), 101-108.

[4] Banker, R.D., Charnes, A. and Cooper, W.W. (1984), Some models for estimating technical and scale inefficiencies in data envelopment analysis, Management Science 30 (9), 1078-1092.

[5] Banker, R.D. and Thrall, R.M. (1992), Estimation of returns to scale using data envelopment analysis, European Journal of Operational Research 62 (1), 74-84.

[6] Banker, R.D., Bardhan, I. and Cooper, W.W. (1995), A note on returns to scale in DEA, European Journal of Operational Research 88 (3), 583-585.

[7] Banker, R.D., Chang, H. and Cooper, W.W. (1996), Equivalence and implementation of alternative methods for determining returns to scale in data envelopment analysis, European Journal of Operational Research 89 (3), 473-481.

[8] Brockett, P.L. and Golany, B. (1996), Using rank statistics for determining programmatic efficiency differences in data envelopment analysis, Management Science 42 (3), 466-472.

[9] Barros, C P and Alves C (2003), Hypermarket retail store efficiency in Portugal, International Journal of Retail and Distribution Management 31(11), 549-560.

[10] Barros, C P and C Alves (2004), An empirical analysis of productivity growth in a

Portuguese retail chain using Malmquist productivity index, Journal of Retailing and Consumer Services 11, 269-278.

[11] Barros, C P (2005), Efficiency in hypermarket retailing: a stochastic frontier model, The International Review of Retail, Distribution and Consumer Research 15(2), 171-189.

[12] Brockett, P L and B Golany (1996), Using rank statistics for determining programmatic efficiency differences in data envelopment analysis, Management Science 42, 466-472.

[13] Bush, R P , A J Bush, D J Ortinau, and J F Hair (1990), Developing a behavior-based scale to assess retail salesperson performance, Journal of Retailing 66, 119-136.

[14] Byrnes, P., Färe, R. and Grosskopf, S. (1984), Measuring productive efficiency: An application to Illinois strip mines, Management Science 30 (6), 671-681.

[15] Charnes, A., Cooper, W.W. and Rhodes, E. (1978), Measuring the efficiency of decision making units, European Journal of Operational Research 2 (6), 429-444.

[16] Charnes, A., Clark, C.T., Cooper, W.W. and Golany B. (1985), A development study of data envelopment analysis in measuring the efficiency of maintenance units in the U.S.

Air Forces, Annals of Operations Research 2, 95-112.

[17] Charnes, A., Cooper, W.W. and Li, S. (1989), Using DEA to evaluate relative efficiencies in the economic performance of Chinese key cities, Socio-Economic Planning Sciences 23 (6), 325-344.

[18] Charnes, A., Lewin, A., Cooper, W.W. and Seiford, L.M. (1994), Data envelopment analysis: theory, methodology and application, Boston: Kluwer Academic Publishers.

[19] Chen, Y, H Morita, and J Zhu (2005), Context-dependent DEA with an application to Tokyo public libraries, International Journal of Information Technology and Decision Making 4(3), 385-394

[20] Cooper, W.W., Seiford, L.M. and Tone, K. (2000), Data envelopment analysis: a comprehensive text with models, applications, references and DEA-solver software,

Boston: Kluwer Academic Publishers.

[21] Cooper, W.W., Li, S., Seiford, L.M., Tone, K., Thrall, R.M. and Zhu, J. (2001), Sensitivity and stability analysis in DEA: some recent developments, Journal of Productivity Analysis 15 (3), 217-246.

[22] Cooper, W.W., Deng, H., Gu, B., Li, S. and Thrall, R.M. (2001), Using DEA to improve the management of congestion in Chinese industries (1981–1997), Socio-Economic Planning Science 35 (4), 227-242.

[23] Doyle, J. and Green, R. (1994), Efficiency and cross-efficiency in DEA: Derivation, meanings and uses, Journal of Operational Research Society 45 (5), 567-578.

[24] Enz, C. and Canina, L. (2002), Best of times, the worst of times: difference in hotel performance following 9/11, Cornell Hotel & Restaurant Administration Quarterly 43 (5), 22-32.

[25] Färe, R., Grosskopf, S. and Lovell, C.A.K. (1985), The Measurement of Efficiency of Production, Kluwer Nijhoff, Boston.

[26] Färe, R., Grosskopf, S., Lindgren, B. and Roos, P. (1992), Productivity Changes in Swedish Pharmacies 1980-1989: a non-parametric malmquist approach, Journal of Productivity Analysis 3 (1), 85-101.

[27] Färe, R. and Grosskopf, S. (1994), Estimation of returns to scale using data envelopment analysis: A comment, European Journal of Operational Research 79 (2), 379-382.

[28] Fay, C.T., Rhoads, R.C. and Rosenblatt, R.L. (1971), Managerial Accounting for Hospitality Service Industries, Bubuque, Iowa, William C. Brown Publishers.

[29] Gattoufi, S., Oral, M. and Reisman, A. (2004), Data envelopment analysis literature:

bibliography update (1951-2001), Socio-Economic Planning Sciences 38 (2-3),159-229.

[30] General Welfare Service Ministry (2003), The operating annual report of retail stores in General Welfare Service Ministry, Ministry of National Defense, Taiwan, 2004. (In

Chinese)

[31] Good, W S (1984), Productivity in the retail grocery trade, Journal of Retailing 60, 91-97.

[32] Ismail, J., Dalor, M. and Mills, J. (2002), Using RevPar to analyze lodging-segment variability, Cornell Hotel & Restaurant Administration Quarterly 43 (6), 73-80.

[33] Jaedicke, R.K. and Robichek, A.A. (1975), Cost-volume-profit analysis under conditions of uncertainty. In A. Rappaport (ed.), Information for Decision-Making-Quantative and Behavioural Dimensions (2nd Edition), Prentice-Hall, Englewood, Cliffs, NJ.

[34] Kimes, S.E. (1989), The basics of yield management, Cornell Hotel & Restaurant Administration Quarterly 30 (3), 14-19.

[35] Keh, H. T. and S. Chu (2003), Retail productivity and scale economies at the firm level:

a DEA approach, Omega, International Journal of Management Science 31, 75-82.

[36] Lewin, A.Y., Morey, R.C. and Cook, T.J. (1982), Evaluating the administrative efficiency of courts, Omega, International Journal of Management Science 10 (4), 401-411.

[37] Li, X.B. and Reeves, G.R. (1999), A multiple criteria approach to data envelopment analysis, European Journal of Operational Research 115 (3), 507-517.

[38] Seiford, L.M. (1997), A bibliography for data envelopment analysis (1978-1996), Annals of Operations Research 73, 393-438.

[39] Seiford, L.M. and Zhu, J. (1999), Infeasibility of super-efficiency data envelopment analysis, INFOR 37 (2), 174-187.

[40] Sexton, T., Silkman, R. and Hogan, A. (1986), Data Envelopment Analysis: Critique and Extensions, Measuring Efficiency: An Assessment of Data Envelopment Analysis, New Directions for Program Evaluation, San Francisco: Jossey-Bass.

[41] Sherman, H.D. (1986), Managing productivity of health care organizations in R.H.

Silkman (eds.), San Francisco, Jossey-Bass Inc., Publishers.

[42] Smith, P. and Mayston, D. (1987), Measuring efficiency in the public sector, Omega, International Journal of Management Science 20 (3), 181-189.

[43] Sueyoshi, T. (1999), Data envelopment analysis non-parametric ranking test and index measurement: Slack-adjust DEA and an application to Japanese agriculture cooperatives, Omega, International Journal of Management Science 27 (3), 315-326.

[44] Thomas, R. R., R. S. Barr, W. L. Cron, and J. W. Slocum Jr (1998), A process for evaluating retail store efficiency: a restricted DEA approach, International Journal of Research in Marketing 15, 487-503.

[45] Thrall, R.M. (1996), Duality, classification and slacks in DEA, Annals of Operations Research 66, 109-138.

[46] Tone, K. (2001), A slacks-based measure of efficiency in data envelopment analysis, European Journal of Operational Research 130 (3), 498-509.

[47] Tone, K. (2002), A slacks-based measure of super-efficiency in data envelopment analysis, European Journal of Operational Research 143 (1), 32-41.

[48] Torgersen, A.M., Førsund, F.R. and Kittelsen, S.A.C. (1996), Slack-adjusted efficiency measures and ranking of efficient units, Journal of Productivity Analysis 7 (4), 379-398.

[49] Van Doren, C.S. and Gustke, L.D. (1982), Spatial analysis of the U.S. lodging industry, Annals of Tourism Research 9 (4), 543-563.

[50] Wassenaar, K. and Stafford, E.R. (1991), The lodging index: an economic indicator for the hotel/motel industry, Journal of Travel Research 30(1), 81-21.

[51] Wijeysingle, B.S. (1993), Breakeven occupancy for a hotel operation, Management Accounting 71 (2), 32-33.

[52] Zhu, J. (1996a), DEA/AR analysis of the 1988-1989 performance of the Nanjing Textiles Corporation, Annals of Operations Research 66, 311-335.

[53] Zhu, J. (1996b), Robustness of the efficient DMUs in data envelopment analysis,

European Journal of Operational Research 90 (3), 451-460.

[54] Zhu, J. (2000), Multi-factor performance measure model with an application to Fortune 500 companies, European Journal of Operational Research 123 (1), 105-124.

[55] Zhu, J. and Shen, Z. (1995), A discussion of testing DMUs' returns to scale, European Journal of Operational Research 81 (3), 590-596.

[56] Zhu, J. (2003), Quantitative Models for Performance Evaluation and Benchmarking:

Data Envelopment Analysis with Spreadsheets, Kluwer Academic Publishers, Boston

Appendix A: Service-Satisfaction Questionnaire

國軍福利站滿意度問卷調查

親愛的顧客您好!

國軍福利站之設立宗旨是為服務勞苦功高的三軍同胞、軍事院校學生、退伍榮民及上述人員眷屬，為提升福利站之服務品質以提高顧客滿意度，本研究針對福利站之硬體設施及服務品質之滿意度，設計下列問卷，敬請親愛的顧客能以您自身的體驗填答下列問卷，俟問卷分析完畢後，即將及結果交送福利總處，供其作為改善設施及服務品質之參考，再次感謝您的協助。

敬祝購物愉快

交通大學管理學院管理科學系敬上指導教授: 楊千

研究生: 王宗誠，盧文民

Eail:jamesw0728@yahoo.com.tw

第一部分基本資料

1. 性別：

□ 男 □ 女 2. 年齡：

□18 歲~30 歲 □30~50 歲 □50~60 歲 □60~歲以上 3. 職業：

□軍公教人員 □軍校學生 □ 榮民 □ 眷屬 □ 其他 4. 每月收入：

□ 10,000 元以下 □ 10,001~30,000 元 □ 30,001~50,000 元 □ 50,001~100,000 元 □ 100,000 元以上

5. 教育程度：

□ 小學 □ 國中 □ 高中、職 □ 大專院校 □ 研究所以上

第二部份消費狀況

1.請問您會到福利站消費的原因

□較近□服務項目多樣化□商品的多樣化□服務度態度 □較便宜 □其他_____

2.請問您多久到福利站去消費

□每週一次□每週 2-3 次□每月一次以上 □其他_____

3.您平均每次到福利站消費的金額

□300 以下 □500 以下 □1000 以下 □2000 以下 □2000 以上 4.下列幾家販售商店,您比較喜歡到哪一家便利商店消費(請按照優先順

填寫)

______福利站 ______家樂福______大潤發______松青_____愛買 5. 大潤發與松青一天經營 24 小時對你來說有比較方便嗎?

□ 沒差 □方便 □非常方便 6. 你覺得上述超商會取代福利站嗎?

□會 □不會 □不知道 7.你滿意目前福利站整體提供的服務嗎?

□滿意 □不滿意 □沒意見 8.你覺得福利站有需要改進的地方嗎?

非常滿意

滿意

無意見

不太滿意

很不滿意

第三部份服務滿意度

1、店員的親切度 □1 □2 □3 □4 □5 2、店員的衣著及服儀 □1 □2 □3 □4 □5 3、店員的結帳速度 □1 □2 □3 □4 □5 4、商品是否多樣化--包含熱食、飲料、零食 □1 □2 □3 □4 □5

、蔬果，生鮮及日用品等等

5、商品是否新鮮每天是否定時更新食品 □1 □2 □3 □4 □5 6、是否經常推出特惠商品 □1 □2 □3 □4 □5 7、過年過節之禮盒及禮品供應式樣是否滿意 □1 □2 □3 □4 □5 8、商品是否維持良好品質及外觀 □1 □2 □3 □4 □5 9、商品退換手續是否簡便，服務員態度是否 □1 □2 □3 □4 □5 良好

10、商品價格與大賣場比是否具競爭力 □1 □2 □3 □4 □5

設施滿意度

1、福利站是否座落在住家、辦公室的附近 □1 □2 □3 □4 □5 2、汽機車停車是否方便 □1 □2 □3 □4 □5 3、是否有接駁轉運之服務 □1 □2 □3 □4 □5 4、福利站外觀是否明顯美觀 □1 □2 □3 □4 □5 5、是否設置儲物箱或物品代管之服務 □1 □2 □3 □4 □5 6、商場面積是否足夠與舒適 □1 □2 □3 □4 □5 7、內部動線設計是否順暢舒適 □1 □2 □3 □4 □5 8、商品陳列是否整齊及以相同商品歸類陳列 □1 □2 □3 □4 □5 9、商場內光線是否充足 □1 □2 □3 □4 □5 10 整體設施及地面是否清潔舒適 □1 □2 □3 □4 □5

感謝您接受我們的問卷調查，更謝謝您的寶貴意見！

APPENDX B: Ranking Extensions to DEA Model

1. Super Efficiency (Andersen and Petersen, 1993)

Andersen and Petersen (1993) developed a new procedure for ranking efficient units.

The methodology enables an extreme efficient unit to achieve an efficiency score greater than one by removing the constraint in the multiplier model, as shown in model (a.1).

The dual formulation of the super-efficient model, as seen in model (a.2), computes the distance between the Pareto frontier, evaluated without unit , and the unit itself i.e. for k

{

^1, ^{, ,}

}

However, there are two problematic areas with this methodology. First, the super-efficient methodology can give “specialized” DMUs an excessively high ranking (Sueyoshi, 1999).

The second problem lies with an infeasibility issue, which if it occurs, means that the super-efficient technique cannot provide a complete ranking of all DMUs (Seiford and Zhu,

在文檔中經營績效評估之綜合管理架構研究-應用於國軍零售供應站 (頁 49-0)