By Ronald Klimberg

ISBN-10: 0762312211

ISBN-13: 9780762312214

Quantity 12 of the "Applications of administration technological know-how" sequence is directed towards the purposes of administration technology to: Multi-Criteria determination Making, Operations and provide Chain administration, productiveness administration (DEA), and fiscal administration. This quantity will end up important to researchers, practitioners and scholars of administration technological know-how and operations learn. It presents an outline of a few of the main crucial elements of the self-discipline and is a superb aspect of reference for individuals drawn to administration or administration technological know-how. It specializes in 4 key functions of administration technological know-how, and is focused in the direction of a large viewers of researchers, practitioners, and scholars.

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The current state of business disciplines, (Vol. 2, pp. 519–535). Mohtak, India: Spellbound Publications, Ltd. 38 N. K. KWAK ET AL. Kwak, N. , Choi, T. , & Kim, S. H. (2001). Efﬁciency evaluation of research university libraries using data envelopment analysis. In: K. D. Lawrence, G. R. Reeves & J. B. Guerard, Jr. ), Advances in Mathematical Programming and Financial Planning, (Vol. 6, pp. 3–18). The Netherlands: Elsevier Science/JAI Press, Amsterdam. Land, K. , Lovell, C. A. , & Thore, S. (1993).

L. (1978). Measuring the efﬁciency of decision making units. European Journal of Operational Research, 2(6), 429–444. Cooper, W. , Li, S. , & Olesen, O. B. (1998). Chance constrained programming formulations for stochastic characterizations of efﬁciency and dominance in DEA. Journal of Productivity Analysis, 9(1), 53–79. Efron, B. (1979). Bootstrap methods: Another look at the Jackknife. Annals of Statistics, 7(1), 1–26. , & Tibshirani, R. J. (1993). An introduction to the bootstrap, Monographs on Statistics and Applied Probability, No.

International Railway Statistics, (Statistics of Individual Railways), Paris, France. APPENDIX Simar and Wilson (1998) suggested a bootstrap procedure for analyzing the sampling properties of DEA efﬁciency index, which is based on the smoothing and reﬂection method in the resampling. The bootstrap procedure can be summarized as follows: (1) For each railway ðxk ; yk Þ of the original data calculate the operational efﬁciency index y^ k by the DEA, and transform the input–output vectors ðxk ; yk Þ; k ¼ 1; 2; :::; n using the DEA efﬁciency indices y^ k ; k ¼ 1; 2; :::; n as ðx^ fk ; yk Þ ¼ ðy^ k Á xk ; yk Þ: (2) Initialize the bootstrap replication index b as b ¼ 0: (3) Increment the value of bootstrap replication index b as b ¼ b þ 1: Evaluating the Operational Efficiency of Railway Systems 39 (4)Generate a random sample of size n; yÃ1;b ; yÃ2;b ; :::; yÃn;b ; from y^ 1 ;y^ 2 ; :::; y^ n as follows: (4a) Given the set of calculated DEA efﬁciency indices y^ 1 ; y^ 2 ; :::; y^ n ; obtain the bandwidth parameter h such that h ¼ 0:9nÀ1=5 minfs^ y^ ; R13 =1:34g where s^ y^ denotes the plug-in standard deviation of the DEA efﬁciency indices y^ 1 ; y^ 2 ; :::; y^ n ; and R13 denotes the interquartile range of the empirical distribution of y^ 1 ; y^ 2 ; :::; y^ n : (4b) Generate bÃ1;b ; bÃ2;b ; :::; bÃn;b by resampling with replacement from the empirical distribution of y^ 1 ;y^ 2 ; :::; y^ n : Ã Ã Ã (4c) Deﬁne the sequence y~ 1 ; y~ 2 ; :::; y~ n using the following: ( Ã bj ; if bÃj þ hÃj 1 Ã y~ j ¼ ; j ¼ 1; 2; :::; n Ã Ã 2 À bj À hj ; otherwise (4d) Deﬁne the bootstrap sequence yÃ1;b ; yÃ2;b ; .

### Applications of Management Science by Ronald Klimberg

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