The transition from products to solutions: External business model fit and dynamics

This article provides empirical evidence and contributes to theory building concerning business model fit and dynamics in the area of solutions business. Business models are seen in this context as going beyond considerations such as offerings and internal processes or even relationships, and as including network and market considerations. Indeed the paper highlights the fact that a business model is not firm-focused, nor dyad-focused, but rather network-, and even market-focused, demonstrating that a business model is not static, but dynamic. Manufacturer and customer continuously shift form and content of their respective business models to adapt both to the needs of the counterpart and to market context. A qualitative case study approach is adopted, with subsequent content analysis. The case study relates to the aerospace industry with focus on a complex engineering firm, one of the largest aircraft manufacturers in the world, its customer — a national airline — and their network partners of various kinds. The data were collected through multiple face-to-face interviews with managers in both companies, as a part and parcel of a network of actors that influences and is influenced by the supplier–buyer relationship. Relationships over time between these firms and network partners are described, highlighting the interplay of products and services related to the provision of solutions. Findings highlight the dynamic nature of business models over the relationship lifecycle between supplier and customer in a complex engineering environment, and the need for reciprocal adjustment of models.     

The Evaluation of Risk in Marine Capital Investments

Future costs and revenues in capital investment opportunities can seldom be predicted with certainty. As a result, there is usually some doubt as to the outcome of an investment. The chance that an investment may not prove profitable represents the investor's risk. This paper considers the problems which uncertainty and risk present in the evaluation of capital investments. Several traditional methods of dealing with uncertainty and risk are considered and shown to be deficient. A relatively new evaluation technique, which utilizes probability theory and computer simulation, is then described and its advantages highlighted. It is suggested that this technique will prove valuable in the evaluation of future marine capital investments.     

A review of “ Edited by Richard H. Bernhard,North Carolina State University ” THE BUSINESS OF RISK by Peter G. Moore,Cambridge University Press,New York, 1984, x + 244 pages,ISBN 0521-24174 X ( hard cover), List $ 44.50; ISBN 0521-28497 X (paperback), List $ 16.95

Four replacement scenarios were analyzed for a vehicle fleet designed to haul sensitive packages at two different customer locations. In addition to completing an economic replacement analysis study, each option was analyzed according to availability requirements and other intangible attributes. Finally, a thorough sensitivity analysis was performed to examine the impact of reliability assumptions on both life cycle costs and the expected economic life of each option. Once all factors were analyzed, each critical input was graded and scored, leading to the final recommendation to replace the current equipment with a new technology.     

Probability Distribution of the Project Payback Period Using the Equivalent Cash Flow Decomposition

For stochastic cash flows, probabilistic approaches to determine a complete distribution of payback period are very limited. The payback analysis based on the net present value (NPV) has several advantages. For annual cash flows, however, the NPV-based method does not provide a complete payback distribution. This article proposes a new technique, the equivalent cash flow decomposition (ECFD), which converts an annual cash flow into an equivalent subannual cash flow at a desired level of precision. The ECFD technique can be used in conjunction with any probabilistic cash flow technique. This article demonstrates that the ECFD technique overcomes the discontinuity limitation of the conventional NPV-based payback period method and generates a complete distribution of the payback period of annual cash flows. Examples indicate that the proposed method is robust with the accuracy comparable to Monte Carlo simulation.     

Shifting reactions to risks: a case study

Social science research in the field of risk analysis has emphasised evaluating the magnitude of individuals’ reactions to risks (e.g. strength and salience of concerns, frequency and forcefulness of behaviours that respond to risks). Fewer studies assess the factors that contribute to risk reactions or the types of risks to which reactions are directed (e.g. human health, wildlife health or ecosystem health risks; economic or aesthetic concerns). Theoretical and empirical research on amplification and attenuation of risk (e.g. the Social Amplification of Risk Framework) reveals that the strength of people’s reaction to risks can change markedly over time, as a function of new stimuli. We expand on this foundation to consider here how the types of risks members of the public react to may also shift over the course of their exposure to a hazard, particularly as more information about the hazard becomes available. This case study of risk reactions related to an outbreak of type E botulism in north-western Michigan, USA, demonstrates that the types of risks people react to can change substantially over time. We identify factors that contributed to changes in types of risk reactions, and then consider how these factors potentially distinguish the botulism outbreak from other outbreaks. This case study suggests that, under certain conditions, risk communication can meaningfully alter the types of risks that people react to in response to an environmental hazard. We discuss implications of these findings for risk research, risk communication and environmental conservation.     

Predicting bankruptcy using the discrete-time semiparametric hazard model

The usual bankruptcy prediction models are based on single-period data from firms. These models ignore the fact that the characteristics of firms change through time, and thus they may suffer from a loss of predictive power. In recent years, a discrete-time parametric hazard model has been proposed for bankruptcy prediction using panel data from firms. This model has been demonstrated by many examples to be more powerful than the traditional models. In this paper, we propose an extension of this approach allowing for a more flexible choice of hazard function. The new method does not require the assumption of a parametric model for the hazard function. In addition, it also provides a tool for checking the adequacy of the parametric model, if necessary. We use real panel datasets to illustrate the proposed method. The empirical results confirm that the new model compares favorably with the well-known discrete-time parametric hazard model.