Alliances and the innovation performance of corporate and public research spin-off firms

We explore the innovation performance benefits of alliances for spin-off firms, in particular spin-offs either from other firms or from public research organizations. During the early years of the emerging combinatorial chemistry industry, the industry on which our empirical analysis focuses, spin-offs engaged in alliances with large and established partners, partners of similar type and size, and with public research organizations, often for different reasons. We seek to understand to what extent alliances of spin-offs with other firms (either large- or small- and medium-sized firms) affected their innovation performance and also how this performance may have been affected by their corporate or public research background. We find evidence that in general alliances of spin-offs with other firms, in particular alliances with large firms, increased their innovation performance. Corporate spin-offs that formed alliances with other firms outperformed public research spin-offs with such alliances. This suggests that, in terms of their innovation performance, corporate spin-offs that engaged in alliances with other firms seemed to have benefitted from their prior corporate background. Interestingly, it turns out that the negative impact of alliances on the innovation performance of public research spin-offs was largely affected by their alliances with small- and medium-sized firms.     

Sources, uses, and forms of data in the new product development process

This paper presents qualitative and exploratory research investigating the role that managing knowledge and information plays in new product development (NPD). A set of 20 in-depth interviews uncovered eight basic types of information used throughout the NPD process and three general approaches to managing information needed in the NPD process. Although some exemplary companies seem to do an outstanding job of collecting and disseminating information, the majority of firms struggle. NPD process automation solutions tackle part of the problem, ignoring nonquantitative data forms and the full picture of information use throughout the entire development process.     

Efficiency in agricultural production: the case of peasant farmers in eastern Paraguay

This paper contributes to the productivity literature in developing country agriculture by quantifying the level of efficiency for a sample of peasant farmers from Eastern Paraguay. A stochastic efficiency decomposition methodology is used to derive technical, allocative and economic efficiency measures separately for cotton and cassava. An average economic efficiency of 40.1% for cotton and of 52.3% for cassava is found, which suggests considerable room for productivity gains for the farms in the sample through better use of available resources given the state of technology. Gains in output through productivity growth have become increasingly important to Paraguay as the opportunities to bring additional virgin lands into cultivation have significantly diminished in recent years. No clear strategy to improve farm productivity could be gleaned from an examination of the relationship between efficiency and various socioeconomic variables. One possible explanation for this finding is the existence of a stage of development threshold below which there is no consistent relationship between socioeconomic variables and productivity. If this is the case, then our results suggest that this sample of Paraguayan peasants are yet to reach such a threshold. Hence, improvements in educational and extension services, for example, would be needed to go beyond this threshold. Once this is accomplished, additional productivity gains would be obtained by further investments in human capital and related factors.     

The “swing of the pendulum” from public to market support for science and technology: Is the U.S. leading the way?

The structure and financing of science and technology activities are undergoing a slow, but profound, change. This change can be briefly characterized as a shift from relying and supporting public science to a stronger emphasis on “market-based” incentives for science and technology. In this paper we analyze this shift in a historical perspective, discussing both the theoretical explanations and the empirical trends of the ongoing change. While we do not claim to provide a comprehensive and exhaustive identification of the causes of this shift, we argue that it is largely driven by the perception of a shift of the U.S. policy towards market-based, rather than publicly supported, incentives for science and technology. This, in turn—given the strong economic performance of the United States over the 1990s—has influenced policies in most OECD countries, especially in Europe.We conclude by analyzing the evolution of research in U.S. higher education and find two major trends: an increasing diversity in the number of institutions of different types other than universities and a steady and continuous public funding of the leading U.S. universities. This has allowed the construction of an infrastructure now used largely by the private sector, but it also noted that the United States has not compromised public support for core areas or in those fields in which there is a clear perception that market incentives are not sufficient for meeting the strategic targets of the U.S. policy. The implication is that there is a considerable policy diversity in the U.S. practice and that all aspects of this diversity should be considered when using the United States as a reference.     

The application of Operation and Technology Roadmapping to aid Singaporean SMEs identify and select emerging technologies

In order to aid Singaporean SMEs identify and select emerging technologies for business benefit, a modified process of the Cambridge T-Plan methodology has been introduced and applied to a pilot sample of 30 companies in a variety of manufacturing sectors. This fast and simple process takes the company through five key steps to enable them to create their first Operation and Technology Roadmap (OTR). The paper explains the background to the approach and focuses on the initial benefits identified by a survey of the pilot companies.     

A note on “Bed allocation techniques based on census data”

Capacity planning and resource allocation are crucial to the cost-effective delivery of health care services. In this paper, we present an analytic approach based on a modified version of the Holt-Winters multiplicative seasonality forecasting model to determine the frequency distribution associated with a hospital care unit's census. This paper is a follow-up to the census frequency distribution simulation model described in Lapierre et al. (Socio Econ. Plan. Sci. 33 (1999) 25). We demonstrate that our model can provide census frequency distributions equivalent to the simulation model of Lapierre et al. [1], but without the computational effort common to simulation models.     

The Falsification of Four Popular Hypotheses About the Asian Crisis

Various claims have been made about the causes of the Asian crisis and its spread. Here, we use data on the behaviour of capital flows during the crisis to test the strong forms of four such hypotheses, that portfolio investors and hedge funds played a dominant role in initiating and/or spreading the crisis; that moral hazard kept efficient markets from predicting the crisis; and, finally, the common lender hypothesis of Kaminsky and Reinhart. In the process we also test implications of the Calvo-Mendoza model of rational investor ignorance. All are falsified as monocausal explanations. For example, portfolio investments that could not have been subject to substantial moral hazard continued to flow into Asia until very shortly before the crisis. Likewise, banks were a much larger source of capital outflows during the crisis than were portfolio investors. While falsified in their strongest forms, several of these hypotheses in less strong forms should play a role in a more nuanced analysis. It is necessary to move past simple single-factor approaches in order to produce a more complete, synthetic explanation of this episode.     

Strategizing through analyzing and influencing the network horizon

How does a firm keep on being valuable in a network? One requirement is that the firm has a sufficient overview of the network and its dynamics. In other words, a firm's strategy depends on the firm's overview of the network—its network horizon. How comprehensive or limited should its network horizon be? Is it necessary to know the network beyond the direct counterparts? Such issues have not received much attention. In this article, we discuss network horizons and argue that limited network horizons are both inevitable and useful. However, such myopia requires that a firm's counterparts effectively and efficiently mediate between the firm and the rest of the network. Based on a case study, we introduce and discuss three mediating functions of counterparts: a joining, a relating, and an insulating function, and we claim that in order to support a firm's strategizing, managers need to analyze and influence counterparts' mediating functions and thereby the firm's network horizon.     

Multiple generation product life cycle predictions using a novel two-stage fuzzy piecewise regression analysis method

Product life cycle (PLC) prediction plays a crucial role in strategic planning and policy definition for high-technology products. Forecast methodologies which can predict PLCs accurately can help to achieve successful strategic decision-making, forecasting, and foresight activities in high-technology firms, research institutes, governments, and universities. Over the past few decades, even though analytic framework strategies have been proposed for production, marketing, R&D (research and development), and finance, aiming at each stage of PLCs, forecast methodologies with which to predict PLCs are few. The purpose of this research is to develop a novel forecast methodology to allow for predictions of product life time (PLT) and the annual shipment of products during the entire PLC of multiple generation products. A novel two-stage fuzzy piecewise regression analysis method is proposed in this paper. In the first stage, the product life-time of the specific generation to be analyzed will be predicted by the fuzzy piecewise regression line that is derived based upon the product life-time of earlier generations. In the second stage of the forecast methodology, the annual shipment of products of the specified generation will be predicted by deriving annual fuzzy regression lines for each generation, based upon the historical data on the earlier generations' products. An empirical study predicting the life-time and the annual shipment of the 16 Mb (Mega bit) DRAM (Dynamic Random Access Memory) PLC is illustrated to validate the analytical process. The results demonstrate that two-stage fuzzy piecewise regression analysis can predict multiple generation PLT and PLC precisely, thereby serving as a foundation for future strategic planning, policy definitions and foresights.