A sample of thirty listed Australian gold producers is used to compare the financial perfor Mance measures provided by accounting‐based financial ratios, and production perfor Mance as measured by efficiency indices. The results indicate that simple ratios are unlikely to provide efficiency rankings similar to those obtained from multiple‐input, multiple‐output methodologies. However, whilst the two methods can disagree substantially on the relative perfor Mance of individual decision‐making units, when used jointly the results can offer valuable insights into the concept of firm perfor Mance.
Abriksten, R. & Forsund, F.1990, A productivity study of the Norwegian building industry, Journal of Productivity Analysis, vol. 2, pp 53–66
2.
Ali, A I & Seiford, L M. 1993, ‘The mathematical programming approach to efficiency analysis’, in The Measurement of Productive Efficiency, eds H O Fried, C.A.K Lovell & S S Schmidt, Oxford University Press, New York
3.
Athanassopoulos A.D. & Ballantine, J A1995, Ratio and frontier analysis for assessing corporate perfor Mance Evidence from the grocery industry in the UK, Journal of the Operational Research Society, vol. 46, 427–40
4.
Australian Stock Exchange, 1995a, Stock Exchange Financial and Profitability StudyVolume I, Gold, ASX, Sydney
5.
Australian Stock Exchange, 1995b, Gold Producers Handbook, ASX, Sydney
6.
Banker, R.D, Charnes, A. & Cooper, W.W1984, Some models for estimating technical and scale inefficiencies in data envelopment analysis, Management Science, vol. 30, 1,078–1,092
7.
Banker, R D & Johnston, H H1993, ‘Evaluating the impacts of operating strategies on efficiency in the US airline industry’, in Data Envelopment Analysis Theory, Methodology and Applications, eds A Charnes, W W Cooper, A Y Lewin & L M Seiford, Kluwer, Boston (Mass).
8.
Charnes, A, Cooper, W W, Lewin, A Y & Seiford, L M (eds) 1993, Data Envelopment Analysis Theory, Methodology and Applications, Kluwer, Boston
9.
Charnes, A., Cooper, W W & Rhodes, E1978, Measuring the efficiency of decision making units, European Journal of Operational Research, vol. 2, 429–44
10.
Farrell, M J1957, ‘The measurement of productive efficiency’, Journal of the Royal Statistical Society Series A (General), vol 120, 253–89
11.
Forsund, F1993, A comparison of parametric and nonparametric efficiency measures The case of Norwegian ferries, Journal of Productivity Analysis, vol. 3, 25–45
12.
Schefczyk, M1993, Industrial benchmarking A case study of perfor Mance analysis techniques, International Journal of Production Economics, vol. 32, 1–11
13.
Seiford, L M & Thrall, R M. 1990, Recent developments in DEA The mathematical approach to frontier analysis, Journal of Econometrics, vol. 46, 7–38
14.
Sickles, R C & Streitwieser, M.L. 1992, Technical inefficiency and productive decline in the US interstate natural gas pipeline industry under the Natural Gas Policy Act, The Journal of Productivity Analysis, vol. 3, 119–33
15.
Smith, P1990, Data envelopment analysis applied to financial statements, Omega, International Journal of Management Science, vol. 18, 131–38
16.
Thanassoulis, E, Boussofiane, A. & Dyson, R G1996, A comparison of data envelopment analysis and ratio analysis as tools for perfor Mance assessment, Omega, International Journal of Management Science, vol. 24, 229–44
17.
Thompson, R G, Dharmapala, P.S., Rothenberg, L J & Thrall, R M1994, DEA ARs and CRs applied to worldwide major oil companies, Journal of Productivity Analysis, vol. 5, 181–203
18.
Thompson, R G, Dharmapala, P S, Rothenberg, L J & Thrall, R M1996, DEA/AR efficiency and profitability of 14 major oil companies in US exploration and production, Computers and Operations Research, vol. 23, 357–73
19.
Thore, S., Kozmetsky, G & Phillips, F1994, DEA of financial statements data The US computer industry, The Journal of Productivity Analysis, vol. 5, 229–48
