A policy lapsation model

O m e g a , Vol. 4, No. 4 important as primary initiating factors, and components relatively important in the type of innovations; in this sense, computers are probably a Stage II product. But in terms of the cost and inventiveness of the innovations, computers are the most strongly Stage I product area of them all. Finally, computer supply companies do almost fit completely into Stage L except that their innovations are relatively inexpensive. Thus, the Utterback/Abernathy model is not wholly consistent with the different patterns of innovation observed by Myers and Marquis in the five product areas. Even if it was, it can still be argued (as the authors themselves recognise on p. 17) that a crosssectional analysis of innovations does not show the dynamics of change within any process segment from one stage to the next. We are doubtful whether patterns of innovation can, as Utterback and Abernathy claim, be explained independently of the specific characteristics of each sector. For example, there are probably very strong reasons specific to the railroad companies, that cause them to concentrate on process innovations: regulatory constraints, physical constraints, and company strategy immediately spring to mind. Similarly, since railroad and housing suppliers make intermediate goods, there are strong pressures on them to improve the quality and the performance of their products, even if the lack of scientific and technical opportunities mean that they tend to concentrate on adaptive innovations. On the other hand computer manufacturers have a much richer scientific and technical base (particularly in componentry) on which to draw in order to make expensive innovations, whilst computer suppliers can make such innovations more cheaply. Examples from other sectors also suggest that the specific characteristics of particular products, their use and their manufacture have a strong influence on the pattern of innovation, and that this pattern may be relatively constant through time. At one extreme, process innovation has always been

important in the manufacture of steel, of bulk plastics and of synthetic fibres. At the other, extreme heavy electrical generating equipment has always been made on a oneoff basis and has required continuous and important product innovation. We therefore conclude that a framework for explaining different patterns of innovation in different process segments must embrace a far larger number of variables than those identified by Utterback and Abernathy; for example, the degree to which product and process technology is sciencebased; the end use of the product; the opportunities for static and dynamic economies of scale in processes, or of economies of scale in product; the relative size and technical capabilities of suppliers, manufacturers and users; the dynamics of competition; and regulatory and physical constraints. We share the wish of Utterback and Abernathy to be able to move to higher levels of generalisation about innovation processes in industry but fear that, given their complexities and specificities, this will be an arduous task.

REFERENCES 1. HtRSCH S electronics trade. Natn. 2. MYERS and

(1965) The United States industry in international Inst. Econ. R. (34), 92-97. MARQUIS (1969)Successful Industrial Innovations. NSF, Washington DC. 3. UTTERBACK JM and ABERNATHY WJ (1975) A dynamic model of process and product innovation. Omega 3(6), 639656. K PAVI'I-Tt R ROTHWELL

1Science Policy Research Unit The University of Sussex ?¢lantell Building Falmer Brighton, Sussex B N I 9 RF UK

A Policy Lapsation Model VARDE'S paper demonstrates how much can be done towards improved measurement by constructing a model of the situation under review. It is in the concluding remarks that the key to progress lies. More extensive

data will allow the lapse rates of different classes of insurance policies to be investigated by duration and by volume. This may give important clues as to the major factors leading to early lapsation. Having established

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Feedback these factors it will be much easier to alter the method of paying commission so that categories of policy with a high lapse rate receive a lower commission payment. The agent will thus be encouraged to sell categories with a low lapse rate. In the U K the balance between initial and renewal commission has always provided fertile ground for argument about rewards to agents. We have a self-compensating system where higher commission will always attract more new business but will leave less of the competitive gross premium to build up the necessary reserves. A rapidly expanding life office therefore develops weak reserves. In India there is presumably less difficulty in gathering the extensive statistics needed to analyse each class of business by lapse rate and duration but in the U K the collating of data from several offices is made difficult by the varying methods of keeping records and a general reluctance to reveal methods or standards to a competitor. 7here is a primary belief among insurers that any competitor will draw advantage from a comparison with his own performance statistics and that this will exceed any advantage gained by the insurer submitting data for comparison. This desire for secrecy means that it is impractic-

able to carry out any satisfacto~ analysis by duration because of shortage of data. When this work by the Life Insurance Corporation is developed to the next stage it will be of considerable interest to smaller countries like the United Kingdom where individual companies will be able to compare the effects of each cause of lapse with their own intuitive unmeasured ideas. An attempt has been made in the Transactions of the Faculty of Actuaries Vol. 31 p. 56 to measure the effects of age and duration on lapse rates in spite of shortage of data.

REFERENCE 1. VARDE V (1976) A policy lapsation model. Omega4 (3), 331-338.

P GILES

Scottish Amicable Life Assurance Society Service and Systems Division Craigforth PO Box 25 Stifling FK9 4 UE UK

A Note on "A Linear Programming Model for Determining an Optimal Regional Distribution of Petroleum Products" by C Moore and Z Zoltners t THE VERY interesting paper by Moore and Zoltners [6] exemplifies recent efforts in the United States to apply the tools of Operations Research and Systems Analysis to energy planning. But it cannot be over-emphasized that in the United States, as elsewhere, energy planning is inexorably intertwined with the political process; and, as such, poses some formidable obstacles to the analyst seeking to apply quantitative tools. This is so for three reasons; first, the public, and therefore the political image of economists and econometricians is none too good these days; second, the essentially qualitative nature of political decisions and legislative directives poses some serious barriers to quantitative modelling efforts; and, finally, criteria important to political feasibility and public acceptability--such as ease of administrative implementation and enforcement, or the

visibility of equity2--are very difficult to formalize within the confines of a quantitative framework. This note was originally presented as a discussion paper at the International Conference on Regional Science, Energy and Environment, Catholic University Leuven, Belgium, 22-24 May, 1975. These remarks reflect the personal judgements of the writer, and should not be viewed as the position of either the Brookhaven National Laboratory nor the US Energy Research and Development Administration. z In a Federal system of government, interregional equity is one of the more important political considerations, with inter-regional trade-offs often spanning several pieces of legislation. See e.g. [41.

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