Showing papers on "Productivity model published in 1973"

Technology, productivity and economic analysis

Abstract: A commonly held view is that innovation, deriving directly from expenditure on research and development, brings increased productivity, lower costs, increased profitability and growth, and that these relationships form a economically virtuous circle. However, this view is not supported either by the research results reported here or by other empirical findings. A richer and deeper framework of analysis than this “mythology” provides is required for management decision making in innovation and in this and the subsequent paper the author outlines the necessary features of such a framework. A model of a “network of productivity relationships” with six components is described which traces the effects of innovation, at any point in the network, on input productivities. The model points up the futility of single input measures of innovatory effects. This network is then combined with cost factors to show the effect on categories of unit costs and on total unit cost. Finally, profitability is related to the physical and cost factors to provide managerial control ratios which offer the relevent criteria by which innovation many be appraised. The history of innovation in the U.S. Basic Steel Industry is examined in the light of the model described above and hypotheses are proposed to identify possible productivity and cost effects of innovation with a view ot improving general predictive capability of the results of any given type of innovation.

On measures of productivity

Abstract: The welfare of an individual enterprise, as well as that of the national economy, very much depends on productivity. But it appears that methods for determining measures of productivity are lamentably unsophisticated and lead to many ambiguities and inconsistencies. It is generally suggested that productivity represents some ratio of output to input, but existing measures of inputs and outputs are unsatisfactory, largely because they gloss over the difficulties of reducing multi-inputs and multi-outputs to single denominators. This paper examines certain approaches that may be developed to handle some of the measurement problems involved in this area.

An industrial dynamics model for start-up management

Abstract: Efficient start-up management can result in considerable productivity increases compared to improvements possible in `steady-state' activities. Provided adequate targets are set and updated in accordance with realistic productivity expectation, management can interact rapidly in order to achieve optimum performance. Such a management process is dependent on the availability of suitable methods of predicting future productivity and estimating present productivity in the presence of random fluctuation due to many causes. This paper develops a predictive start-up model which performs both these functions. At each observation time, observed productivity is compared with predicted productivity as estimated from previous data, the difference being used to update the model parameters in a manner analogous to exponential smoothing. The model is applied to a number of start-up problems and is shown to track the parameters in an acceptable fashion. Long- and short-term productivity predictions resulting from the model are shown to be a useful management aid.