Foresight and innovation in the context of industrial clusters: The case of some Italian districts

The “territory” is widely recognized in the literature on business strategy as a critical driver of industrial competitiveness (see, as an example, Porter, The Competitive Advantage of Nations). The generation and exploitation of new knowledge, both tacit and explicit, through the process of socialization, articulation, combination and internalization (see Nonaka and Takeuchi, The Knowledge-Creating Company) is essential to enable innovation of processes and products of “local” firms.Our recent Foresight exercises in the metal working and machinery district of Lecco and in the silk district of Como show that Foresight can play an important role in creating and exploiting new knowledge, and that different methodologies can be more or less effective to this aim.Critical technology list and interactive workshops, with the participation of entrepreneurs of SMEs and technologists, are more suited to foster the transfer of technologies that have overcome the initial stage of the life cycle and that have been already applied in other sectors. However, when radical innovations are needed in order to face the challenges posed by global competition, other methodologies, as Scenarios, are more appropriate. Even if these approaches are complex and time and resource consuming, they may be very effective in actively involving the most relevant private and public stakeholders of a district, and in making them to envisage the long term future of the economic, social, and cultural structure of their district. In this way Foresight drives the small entrepreneurs, the district stakeholders and the medium and large size firms to play the critical roles of Nonaka and Takeuchi's “frontline employees”, “senior managers” and “middle managers” in their “knowledge creating company”: the first ones grasp what the district is; the second ones build the vision of what it ought to be; the third ones, serve as a bridge between the future and the present.     

Developing post-normal technologies for sustainability

The last two decades have seen the development of an array of techniques and practices aimed at promoting sustainability. For many, results have been disappointing. There are charges that supposedly new organisational approaches remain embedded in managerialist, functionalist and anti-dialogic frameworks that are a significant part of the problem. Similarly the technocratic scientization of public policy is viewed as ill-equipped to deal with the social, economic and ecological issues currently facing neo-liberal societies. In this paper we seek to interpret these frustrations and identify pathways that move beyond this. Specifically, we argue that the gap between sustainability rhetoric and sustainability practices can be reconceptualised through the practice of science as post-normal and through developing the notion of post-normal sustainability technologies (PNSTs). The exponents of post-normal science show why stakeholder engagement in sustainability (and other scientific) issues is critical for the legitimacy and quality of decisions and the admission of complexity in decision-making and accountability processes. Building on this now well-established foundation we seek to characterise, and give examples of, PNSTs as tools for achieving this participation; wherein stakeholders assume expertise and interact with those possessing more traditional forms of expertise in order to co-produce knowledge about sustainability. Recognition of ideological and value diversity is also central to the post-normal sustainability agenda and with PNSTs, the values-based nature of the issues involved is articulated in a way that seeks to bring politics openly into the picture. To this end we identify processes that are emerging in the literature and in practice that will enable PNSTs. These include extended peer communities and multi-actor heuristics, agonistic processes and new characterisations of citizenship that support moves to sustainability. In so doing, we believe that PNSTs offer “clumsy solutions” for “wicked problems” that can be engaged with in both the research and practice arenas as significant contributions to addressing urgent needs.     

Measuring emerging categories of innovation: Modularity and business model

The oft-cited dichotomy between incremental and radical innovations is less important when we have to analyze how a new technology and its social institution coevolve. In this context, besides incremental and radical innovations, C. Freeman added two more categories of technical change: one is change in the technology system and the other is change in the technoeconomic paradigm.However, as the information technology (IT) revolution progresses further, we come to need more categories of innovations. In the computer industry, the concept of “module” is becoming a solution to growing complexity. In the new IT environment, we can be proactive in demand creation. It becomes crucial, therefore, whether the creation of new “business models” has followed technical innovations. In this article, we will try to demonstrate how these different categories of innovations, i.e., modularization and new business model creation, can be measured.     

The choice of innovation policy instruments

The purpose of this article is to discuss the different types of instruments of innovation policy, to examine how governments and public agencies in different countries and different times have used these instruments differently, to explore the political nature of instrument choice and design (and associated issues), and to elaborate a set of criteria for the selection and design of the instruments in relation to the formulation of innovation policy. The article argues that innovation policy instruments must be designed and combined into mixes in ways that address the problems of the innovation system. These mixes are often called “policy mix”. The problem-oriented nature of the design of instrument mixes is what makes innovation policy instruments ‘systemic’.     

Strategic foresight in corporate organizations: Handling the effect and response uncertainty of technology and social drivers of change

Today many companies in many industries put a lot of efforts into monitoring and investigating emerging drivers of change in their business environment, particularly in relation to new technologies and events in the social, economic, political and ecological landscapes which surround their industry. So far scholars in the literature on foresight and future studies focused on the techniques and practices for analysing the “state” uncertainty about the likely path of evolution of emerging drivers of change. Anyway, less attention was devoted to the “effect” uncertainty about the impact of drivers of change on the competitive position of the firm and to the “response” uncertainty about how to take advantage of these drivers. These are the main issues we take into account, through a field research on firms that, notwithstanding they were able to properly assess the likely evolution (state uncertainty) of relevant drivers of change in their industry, either were successful or dramatically failed in handling the effect and response uncertainty of these drivers. Moreover, we carried out multiple case studies of some large companies that have established an organizational unit dedicated to strategic foresight. Overall, the results of our research may contribute to improve the effectiveness of strategic foresight and to increase its value added to the planning process of corporate firms, while providing helpful insight to public organizations that promote foresight exercises for enhancing the competitiveness of local firms.     

Toward an experimental foundation for benefit-cost analysis

Empirical results from experimental economics and neuroscience have uncovered regularities in human behavior that may provide a base for new approaches to welfare theory and economic policy. These empirical findings do not challenge basic economic concepts but they do imply that our assumptions about “rational behavior”, “opportunity cost”, and “social welfare” should be revised using sound scientific evidence and methods. This research has the potential to make benefit-cost analysis more reflective of how people value gains and losses, and more responsive to considerations of environmental and social responsibility.     

The origins of the concept of ‘foresight’ in science and technology: An insider's perspective

This article explores how the term ‘foresight’ originally came to be used in connection with science and technology by the author and SPRU colleagues in 1983. It analyses how the rationale for its use evolved over time, first providing a ‘catchy’ title for a study (‘Project Foresight’), and then a convenient shorthand for the focus of that study, before eventually coming to formally signify a new approach to looking systematically into the future of science and technology, an inclusive and wide-ranging process that differed appreciably from that of traditional ‘technology forecasting’. The paper reflects on the importance of concepts and terminology in the field of science policy research, providing examples of how an inappropriate term or phrase can damn the prospects of the research having an impact on policy, while a more politically astute use of terminology can greatly enhance the probability of making a significant impact. The paper also examines other early uses of the concept of ‘foresight’ in the United States and Canada at about the same time. In addition, it highlights the conceptual similarities between foresight and la prospective, a novel approach developed in France not just for looking into the future but also for shaping or even ‘constructing’ the future of our choice, an ambitious aspiration that it shares with foresight. This case-study on the origins and early evolution of ‘technology foresight’ illustrates the essential importance of terminology in differentiating key concepts in social sciences (where it sometimes gives rise to unfortunate priority disputes), and particularly in the case of policy research.     

The digital economy: Where do we stand?

The rapid transition towards a “digital economy” was enabled by a converging set of innovations. Computing saw the development of the semiconductor transistor, integrated circuit, personal computers (PCs), operating systems, and graphical interfaces. The physical layer of telecommunication was enabled via the emergence of optical fiber and new wireless communication technologies, while networking saw the development of the Internet (essentially packet switching) and the World Wide Web. These advances combined to realize a series of new applications of information and communications technologies (ICTs) such as business software, e-mail, and e-commerce. However, progress seriously stumbled with the collapse of the dot com bubble, which among other things revealed a huge amount of misdirected investment that could have been used more productively. The question of the day is thus how to realize new “killer apps” to stimulate a new round of growth. The use of cell phones for communicating text, pictures, and video is a rapidly expanding area, but it seems unlikely that these applications will have a macroeconomic impact. Entertainment is a key industry whose fortunes are entwined with ICTs. Indeed, the application of ICT to innovating entertainment products is an important driver for the continued growth of the industry. Distribution of music and video via the Web could significantly stimulate demand but also raises the thorny question of how to protect intellectual property rights (IPR) of content providers. Another possible killer apps are interactive video-on-demand and telecalls/teleconferencing. The latter would, among other things, stimulate adoption of telework. The current Internet is capable of handing neither one-way transmissions of high-quality video nor interactive video-on-demand. There are bottlenecks both for the “last mile” connection from Internet service provider (ISP) to the home but also the “first miles” from originating server to ISP. The effective first miles bandwidth has not increased along with improvements in equipment, essentially because demand increases with capacity and thus traffic jams on the net continue. Digital subscriber line (DSL) technologies over telephone wires, and possibly wireless networks, will play important roles in getting over the last mile hurdle. Upgrading the first miles will probably require new networking protocols beyond TCP/IP that support multimedia and also changes in the economic model of information transfer via the Net.     

On S-curves and tipping points

In his discussion in this journal of Kurzweil's The Singularity is Near, Modis criticizes Kurzweil's loose characterization of the “knee” of a growth curve. Likewise, the “tipping points” described by Gladwell (The Tipping Point) are clearly relevant to forecasting systems, but Gladwell did not mathematically identify such points. Both concepts refer to a point on the curve where growth accelerates dramatically and sustains itself. What can be said in a rigorous way about knees and tipping points in growth systems?The answer has to do with the number of parameters of the growth curve, and the (probabilistic) model underlying the growth curve. Using probability theory and computational experiments, this paper clarifies these points for the logistic and Bass curves (identifying an unambiguous tipping point for the latter), and explores the merits of a 3-parameter model of innovation adoption. It concludes that if forecasters are to deal scientifically with the now-established management notion of “tipping points,” a 3-parameter model is needed. The paper also resolves four minor but annoying paradoxes in the growth curve literature.     

Differences and similarities between ecological and economic models for biodiversity conservation

In this paper we investigate an important obstacle which substantially complicates co-operation between ecologists and economists but which has received little attention so far: differences between the modelling approaches in economics and ecology. To understand these differences, 60 models addressing issues relevant to biodiversity conservation have been selected randomly from eight international economic and ecological journals. The models have been compared according to a number of criteria including the models' level of generality; the mathematical techniques employed for formulation and solution of the models; the level of complexity and the way time, space and uncertainty are taken into account. The economic models sampled are formulated and analysed analytically, tend to be relatively simple and are mostly used to investigate general questions. Furthermore, they often ignore space, dynamics and uncertainty. Although some ecological models have similar properties, there is also a substantial number of another type of ecological models that are relatively complex and analysed by simulation. These models tend to be rather specific and often explicitly consider dynamics, space and uncertainty. The integrated ecological-economic models are observed to lie “in the middle” between ecological and economic models. An unexpected result is that they are not more complex than ecological and economic models (as one could have expected from a simple “merger” of models from both disciplines), but have an intermediate complexity.     

Analysis of barriers in the transition toward sustainable mobility in the Netherlands

The transition toward a sustainable transportation system in the Netherlands takes place in the context of the Dutch “Transition management policy framework”. We study four technological routes that the “Platform Sustainable Mobility” has selected for this goal: (1) hybridization of vehicles, (2) liquid biofuels, (3) natural gas as a transportation fuel and (4) hydrogen as a transportation fuel. These technological routes all envision large-scale changes in vehicle propulsion technology and fuel infrastructure. Furthermore, they compete for the scarce resources available to invest in new (fuel) infrastructures, which implicates that these ‘transition paths’ are also interdependent at the level of the mobility system. The main outcome of the analysis is the identification of barriers that are currently blocking the transition toward sustainable mobility. Barriers are classified as being related to (1) technology and vehicle development, (2) the availability of (fuel) infrastructures, and (3) elements of the institutional infrastructure. The transition management framework currently misses guidelines for coping with (competing) technologies that each require large infrastructural investments. We further argue that avoiding undesired lock-ins and creating a beneficial institutional context for sustainable mobility cannot be pursued at the transition path level. Therefore, we recommend that a more systemic approach should be taken to the transition to sustainable mobility, in which the interdependencies between the transition paths are critically assessed and in which the possibilities to legitimize sustainable mobility as a whole should be used.     

Specifying “regime” — A framework for defining and describing regimes in transition research

It is more and more agreed by research and policy that a long-term sustainability of industrialized societies cannot be achieved without fundamental changes at the level of different societal subsystems, such as the agricultural, transportation or water management systems. This view has lead to an increase in the amount of research carried out about the so-called “transitions”. Transitions comprise long-term, fundamental change in societal subsystems and are seen as encompassing co-evolutionary and mutually reinforcing processes in the economic, technological, institutional and socio-cultural domains. Transition research aims at understanding transitions and at finding methods that facilitate change directed towards societal goals (so-called “transition management”).This paper adds to the growing body of concepts of this young research strand. It suggests a framework for defining and describing “regimes”, the systems resulting from the broad and interdisciplinary view taken by transition research. The concept “regime” is of central importance for transition research, since it defines the level of societal systems on which transitions are mainly analysed. What actually is “the regime” to be researched and possibly managed is however usually not given through clear system boundaries but is a matter of framing and deliberation. In order to guide processes of regime identification, the paper develops five defining characteristics of regimes and gives a definition based on them. Further a method useful to structure and graphically represent knowledge about a regime is introduced. Such a structuring of knowledge is an important first step to understand how a regime “works”.     

Study of population heterogeneity in innovation diffusion model: Estimation based on simulated annealing

Parameter variability randomness in diffusion (PVRD) models based on random differential equations have recently been developed to study stochastic evolution of adopters. Analysis of such models is found to generate multimodal life cycle patterns (or intervening slumps) besides the conventional unimodal pattern. Application of these models to real data sets necessitate estimation of parameters of the model. Nonlinear least squares estimation problem is formulated to deal with the minimization of high-dimensional cost function. Using the simulated annealing (SA) framework, effectiveness of the estimation approach and the fitting algorithm is demonstrated in terms of “fit statistics.” An important finding from empirical studies reveal that even in unimodal life cycle patterns, parameters of innovation diffusion process are found to possess considerable variability. This finding amply demonstrates the presence of heterogeneity on account of population variability.     

The future of drug discovery and development: Shifting emphasis towards personalized medicine

The drug discovery sector is being revolutionized by the current rate of advances in the public and private human genome projects and by the development of new technologies for biomarker testing. In effect, as the genetic roots of disease, disease progression and treatment effectiveness are uncovered, the demand for sophisticated prognostic, diagnostic and monitoring tests will be increasing. Already this has led to the development of innovative diagnostics products meeting the criteria of improved efficacy and safety as well as better cost-benefits. In order to achieve the ultimate goal of a more predictive and personalized medicine requires the drug discovery industry to implement more synergies between the two worlds of clinical research and diagnostics. The therapeutics that are enabled by that strategy are often called “theranostics” — highly specific tests that allow for the diagnosis of the disease, but to administer the most appropriate treatment regimen, and to monitor a patient's response to therapy. Biomarkers will constitute a critical component of the health care delivery system in order to detect, diagnose and monitor diseases and other medical conditions as well as to evaluate treatment options and effectiveness. While diagnostic breakthroughs typically precede therapeutic advances, the presence of new therapies can stimulate the demand for testing. The main question that remains to be answered is how will the biomarker paradigm alters these companies' innovation and commercialization strategies. Whereas developing drug targets may offer greater long-term value, initial commercial opportunities often arise in diagnostics.     

A study on the relationship between technology diffusion and new product diffusion

This study investigates the relationship between “technology diffusion” and “new product diffusion”. We define “technology diffusion” as a knowledge spillover process, which is represented by patent citation, and “new product diffusion” as the spread of a new product that has been developed by the application of patented technology. To investigate the relationship between the two types of diffusion, we use patent citation data of code division multiple access (CDMA) technology and market sales data of mobile phones in South Korea for the analysis. The results show that the diffusion of technology through patent citation could be successfully explained by empirical analysis, for which the Bass diffusion model was used. Moreover, we can find out if technology diffusion can be the leading indicator of a new product's diffusion before its launching; in other words, before the commercialization of the patent.     

Arbitrage-free valuation of interest rate securities under forward curves with stochastic speed and acceleration

Arbitrage-free models for valuing interest rate securities posit that stochastic changes in spot or forward interest rates (forward rate “speed”) follow a diffusion process. This paper extends the Heath, Jarrow and Morton [Bond pricing and the term structure of interest rates: a new methodology for contingent claims valuations, Econometrica 60 (1992) 77-105], HJM framework by allowing diffusive shocks to both the “speed” and “acceleration” of forward rates. The arbitrage-free restriction on forward rates is identified and involves volatilities of the speed and acceleration dynamics and their correlation. Although the extended forward rates remain in the diffusive framework and evolve continuously, they may exhibit large changes over short intervals (as with jumps) due to stochastic acceleration. Comparisons of bond prices show that the proposed model generates more complex and intricate shapes for the restricted forward curve with the same number of stochastic factors and volatility.     

Scenarios of technology and innovation policies in Europe: Investigating future governance

In Europe, public research, technology and innovation policies are no longer exclusively in the hands of national authorities: increasingly, national initiatives are supplemented by, or even competing with, regional innovation policies or transnational programmes, in particular the activities of the European Union. At the same time, industrial innovation increasingly occurs within international networks. Are we witnessing a change of governance in European innovation policy? Based on some theoretical assumptions concerning the relationship between the “political systems” and “innovation systems” in Europe, the paper speculates about the future governance of innovation policies, trying to pave ways for empirical analyses. It sketches three scenarios stretching from (1) the idea of an increasingly centralised and dominating European innovation policy arena to (2) the opposite, i.e., a progressive decentralisation and open competition between partly strengthened, partly weakened national or regional innovation systems and finally to (3) the vision of a centrally “mediated” mixture of competition and cooperation between diverse regional innovation cultures and a related governance structure.     

Self-control in peer groups

Social influences on self-control underlie both self-help groups and many peer interactions among youths. To understand these phenomena, we analyze how observing each other's behavior affects individuals’ ability to deal with their own impulses. These endogenous informational spillovers lead to either a unique “good news” equilibrium that ameliorates behavior, a unique “bad news equilibrium” that worsens it, or to the coexistence of both. A welfare analysis shows that people will find social interactions valuable only when they have enough confidence in their own and others’ ability to resist temptation. The ideal partner, however, is someone with a slightly worse self-control problem than one's own: this makes his successes more encouraging, and his failures less discouraging.     

A taxonomic review of methods and tools applied in technology assessment

Technology Assessment (TA) has been a growing field of management study for the past four decades. An increasing number of studies have been carried out over the years contributing to the development of TA literature. Some of these studies summarized the history and growth of the field during its evolution. However, there has been no effort made to present an overview of the methods and tools that have been cited in TA literature. This paper attempts to fill that void. A thorough review of the TA articles published in leading journals in the management of technology field is conducted to identify the research methods or tools in those studies. The paper provides an introductory review of the use of technology assessment terminology during its development, which helps the readers avoid the confusion of the TA concept since its origination in public decision making forty years ago and where it is now — widely adopted in other sectors. A thorough presentation of the approaches, methods and tools that have been introduced or employed in both mainstream TA and “inverted TA” studies is then provided. The main content of the paper is related to the works published in leading international journals that involve certain research methods or techniques.