A qualitative cross-impact approach to find the key technology

This article presents a qualitative analysis method based on fuzzy relations for a cross-impact model designed for a technology impact assessment. The cross-impact knowledge is often uncertain or fuzzy when dealing with future events. Assessing the cross-impact relationships among future technologies creates a more uncertain or fuzzy situation because of the time and the uncertainty involved in evaluating future technologies. In addition, experts prefer to use linguistic terms or fuzzy values in their predictions. Thus a cross-impact matrix is represented as fuzzy relations on causal concepts. We therefore develop inference algorithms based on fuzzy relations and show a simple technology assessment example to illustrate this approach. This approach is useful in finding the key technology because it considers not only the direct impact but also the indirect impact.     

A cross-impact model applicable to forecasts for long-range planning

A methodology is developed, which is based on cross-impact analysis and which is useful in estimating the effects of uncertainty in future sales programs and the effects of program interaction on long-range sales forecasts. The utility of the cross-impact methodology vis-a-vis the conventional decision-tree approach lies in the reduction of complexity made possible when a large number of programs must be considered.     

A Primer on Logistic Growth and Substitution: The Mathematics of the Loglet Lab Software

This article describes the mathematics underlying the Loglet Lab software package for loglet analysis. “Loglet analysis” refers to the decomposition of growth and diffusion into S-shaped logistic components, roughly analogous to wavelet analysis, popular for signal processing and compression. The term “loglet” joins “logistic” and “wavelet.” Loglet analysis comprises two models: the first is the component logistic model, in which autonomous systems exhibit logistic growth. The second is the logistic substitution model, which models the effects of competitions within a market. An appendix describes the current status of the software.     

Technological generalizations and leitbilder—the anticipation of technological opportunities

Recent national technology foresight studies as well as the Millennium Project of the American Council for the United Nations University are very much based on “nodes of discussion.” These short statements are called, e.g., topics, issues, or developments. This article provides a framework for the classification and analysis of nodes related to future technological development. Key concepts of the article are “technological generalization” and “leitbild.” The topics in the technology foresight Delphi studies can be seen as different kinds of generalizations from already realized technological developments. Leitbild is a German word. Its most general meaning is a guiding image. Like a common vision, a leitbild creates a shared overall goal, offers orientation toward one long-term overall goal, and provides a basis for different professions and disciplines to work in the same direction. The analysis of leitbilder and emerging technological paradigms might contribute to the construction of topics and issues and to the argumentation processes related to them.     

A reliability engineering approach for forecasting technological breakthroughs

One of the major attributes determining system reliability, the one that has received the most thorough and systematic study for many years, is system survival function. A “survival function” is a mathematical formula relating the probability of satisfactory performance of a system to time. Here, probability of satisfactory performance is synonymous with probability of nonfailure or probability of survival of a performing system.In breakthrough analysis of complex technological systems, the situation is somewhat similar but opposite to the above system reliability case. For breakthrough forecasting, the problem is to determine the probability of occurrence of success of a nonperforming system. Thus this paper presents a quantitative methodology for forecasting technological breakthroughs using a new concept of “attainability function,” derived in a similar fashion as the “reliability function.”     

The elusive Phillips curve

The empirical evidence that has accumulated over the past twenty years for major countries, and especially the United States, Canada, and the U.K., suggests three distinct “phases” for the Phillips curve. In the “early” phase the coefficient on the unemployment variable was correctly signed and statistically significant; in the “middle” phase, as further studies were made and the data period extended, the unemployment coefficient tended to become numerically smaller and often to be statistically insignificant; in the “late” phase, as yet more studies accumulated and the data period was extended into the seventies, the unemployment coefficient was sometimes perversely signed and also statistically significant. This paper offers a possible theoretical interpretation of this phenomenon. The theoretical analysis is supplemented with some empirical simulations.     

Explaining the economic trajectories of civilizations: The systemic approach

A civilization constitutes a durable social system of complementary traits. Some of the complementarities of any given civilization are between elements of “material” life and ones commonly treated as integral to “culture.” Identifying the mechanisms responsible for a civilization's observed trajectory involves, therefore, causal relationships that cross the often-postulated “cultural–material” divide. Complementarities make it difficult to transplant institutions across civilizations on a piecemeal basis. They imply that reforms designed to jump-start an economy will fail unless they are comprehensive. Civilizational analysis can benefit, therefore, from attention to institutional complementarities, including ones involving both cultural and material variables.     

Societal aspects of technology assessment

Despite earnest admonitions in most technology assessments that institutional arrangements, social impacts, and societal implications be taken into account, the methodology commonly used not only systematically and systematically excludes these very dimensions but often creates a distorted focus. The paradigm dominating structural modeling in technology assessment is technically-oriented; the techniques, lineal descendants of systems analysis, are no more reliable for “assessing” the uncertain future than have been their ancestors in “managing” the present.     

Is man doomed to progress?

This paper is dedicated to the empirical exploration of the welfare effect of expectations and progress per se. Using 10 waves of the Russian Longitudinal Monitoring Survey (RLMS), a panel household survey rich in subjective variables, the analysis suggests that for a given total stock of inter-temporal consumption, agents are more satisfied with an increasing time profile of consumption: they seem to have a strong “taste for improvement”. This contributes to qualify the “Easterlin paradox” that income growth does not make people happy.     

Structure and understanding: Some observations on current activities in the field of structural modeling

Structural modeling has been under study in recent years as a method for dealing with complex societal problems, and is growing in acceptance as a tool for understanding complex social phenomena. Structural models demonstrate the interactions of the separate elements of a system and their combined overall effect. Thus, the nature of the problem for which this method of analysis is appropriate is different from complex problems of the traditional disciplines which lend themselves to reductionist approaches. This is because complex policy problems of society cannot be “solved” with precise analysis. Kenneth Boulding suggests that there are two ways to cope with a complex policy problem, either to “slice” the problem into partial equilibrium sections or “squeeze” it by aggregating numerous variables into a single index or macho variable. Structural modeling is an approach which comes under the general strategy of squeezing the problem and is promising because of the ability to include a range of macro variables which provide insights about social change. The articles in this issue treat several interesting aspects of this approach. In this article we wish to recall for consideration a central purpose for developing such methods. We have taken a historical approach to indicate some of the roots of the concern for the effect of technological process on social change. Within this context, we discuss the nature of the contributions made by the articles in this issue and what promise the methods offer to addressing the historical concern.     

An interactive computer-based approach to aid group problem formulation

The size, cost, and complexity of quantitative modeling in the social and physical sciences demand that the modeler focus attention on premodeling phases of analysis, specifically on formulation and definition of “problems.” This is especially true in the “softer” or less “well-structured” problem areas of futures research and technology assessment. At this stage of modeling, a key factor is communication among modelers. This paper briefly discusses approaches to classifying and formulating problems that illustrate the role of communication in modeling. It then describes a computer-based communication system as one possible aid in the problem-formulation process.     

Causality: Its characterization in system dynamics and KSIM models of socioeconomic systems

Two methodologies—Kane's KSIM and Forrester's system dynamics—for modeling socioeconomic systems are compared and contrasted with regard to the manner in which each characterizes and classifies casuality in socioeconomic systems. The equivalence of the so-called casual diagram used in system dynamics to the cross-impact matrix used in KSIM is indicated. Each method identifies exactly two classes of casual links—the similarity between the classes distinguished in system dynamics with those employed in KSIM is suggested. Then the assumptions regarding the nature of causality that are implicit within the two methodologies are compared. In this context techniques for translating linear system-dynamics models to KSIM-like models (and vice versa) are provided. Examples are provided to illustrate the notions discussed in the article.     

Interdisciplinary problems in doing impact assessment : The case of Lake Shelbyville

A multidisciplinary team of biologists, economists, engineers, planners, and sociologists were assembled to do an ex-post facto analysis of a flood control reservoir ten years after initial operations. Within the context of a research university, the authors suggest ways to 1) improve project administration, 2) combat disciplinary chauvinism, 3) facilitate the understanding and exchange of data across disciplines, 4) reward the work of graduate students in a fair and equitable manner, and 5) assist the principal investigator in achieving the goal of an interdisciplinary study. The importance of project associates in the day-to-day operation of the study is reviewed in detail.This paper details the administrative problems of the University of Illinois' interdisciplinary effort to examine the “real” environmental impacts of the Lake Shelbyville reservoir 10 years after it had begun operation. Lake Shelbyville is a U.S. Army Corps of Engineers reservoir located in east-central Illinois. Land acquisition began in 1962 and the reservoir was in operation by 1971. While not implying that “apples and oranges” don't mix, problems do result when we try to bring together a group of disciplinary researchers. We write with the hope that the suggestions outlined here will keep environmental impact assessment research interdisciplinary. One of the reasons for the present “environmental fix” is the single discipline approach to environmental problems.A true interdisciplinary effort is necessary for a comprehensive assessment of the impacted physical and social environments, yet “interdisciplinary” can easily become a false label. If the principal investigator and researchers are not attentive to project administration on a day-to-day basis, the old saying about integrating findings “with a staple” can easily result. Rather than integrated assessment, the study report may resemble a series of miniature discipline based projects that read like the list of university departments.     

Can Japan succeed in “Chigyo-ka” (intelprise-formation)?

There are two aspects in today's information revolution that started in the late 1970s. The first is an aspect referred to as “the third industrial revolution,” which triggers the transition to the “21st century system of Industrialization.” The information revolution in this sense brings the creation of new “breakthrough industries (new multimedia industries).” And the second aspect of the information revolution possesses the characteristics of both a technological revolution and a social revolution and brings about the arrival of the third phase of the historical evolutionary process of the modern civilization, which proceeds through three phases, namely “militarization, industrialization, and then informatization.”If the bearers of modern industrialization are a “group of enterprises” that have been engaged in the race in order to gain “wealth” (generalized means of exchange/exploitation power), and if these enterprises' activities have been exercised in the world market where their products have been sold, then it is appropriate to call the bearers of informatization a “group of intelprises.” They will be engaged in the race to gain “wisdom” (generalized means of persuasion/induction power), then stages of their activities can be called a “global intelplace” where “sharables,” that is, information and knowledge, will be disseminated. And now, toward the 21st century, the third phase of modernization, which can be called the “informatization/intelprise formation” or the “wisdom game” (intellectualism), is about to begin.Japan's “ie society (a society based on the ie principle—literally, it means “house” but here it is interpreted as cultural principle for organizing a society), which has been going through the process of evolution on the Japan Archipelago, has developed a network-based organization with little stratification within its infrastructure. In this sense, Japanese society can be characterized as a “network-oriented society” in which intelprises and an intelplace in the broad sense have functioned as the essential components of the society since Middle Ages. In general, an intelplace and intelprises that operate actively within this framework serve as the flexible bases for different types of social relations and institutions, such as states and markets and eventually integrate these into the society to a certain extent. In fact, it took place quite regularly during the modernization “in the narrow sense,” or Westernization of Japanese society after the Meiji Restoration. There exist some problems, however. Some of the characteristics found in Japanese society may become obstacles to activities aimed at the sharing and promotion of information and knowledge in the global intelplace and Japanese participation in the “wisdom game.” Badly needed are serious efforts for Japanese intelprise-formation to reduce these obstacles as much as possible.     

What crises could teach us about complexity and systemic management: The case of the Nestucca oil spill

In this article we attempt to uncover some systemic management principles for the better management of complex issues. Taking a pragmatic approach we have expanded the case methodology proposed by John Dewey to the case study of a major crisis. By proposing that crises allow for a better apprehension of complexity, we study the changes which were carried out or not, to this day, after the 1988 Nestucca oil spill that occurred in Canada only three months prior to the Exxon-Valdez disaster. After conducting a linear and systemic analysis of the crisis, we propose that the changes institutionalized thus far spring mostly from what we call “behavioral” and “paradigmatic” learning which are weak for addressing complex issues. Proposing that 15% of the people we have interviewed where able to derive a “systemic learning” from this crisis, we suggest several unlocking strategies that allow these systemic lessons to be institutionalized.     

Discussion of Coates' commentary

Joseph Coates argues against the analysis presented in “A Possible Declining Trend for Worldwide Innovation” in a commentary published in Research-Technology Management. His arguments display a lack of understanding of this analysis, a lack of supporting data and an ignorance of the information contained in Bunch and Hellemans' reference work that forms the foundation for the analysis. A response is provided to these arguments with clarifications of the original analysis, as others may have the same misconceptions as Coates.     

On the value of human resources

One challenge for planners is to discover conditions under which a society has a positive and growing “net worth” in terms of its human resources and to bring about and maintain those conditions. We discuss the utility and validity of the concept of people as “assets” or “liabilities”, the structure and cultural contexts for a proposed model of the dynamics of value that account for opportunity costs; and links between information technologies and human resources management, including planned development of these resources.     

Increasing returns and the share economy

Under imperfect competition, profit maximization by firms results in the market price exceeding the marginal cost of production; Weitzman terms this “excess supply” Weitzman wishes to replicate in the cost function (in terms of labor) the properties of the revenue function (in terms of output), thus generating “excess demand” for labor. A revenue-sharing scheme will achieve this if and only if there are decreasing returns to scale. Hence increasing returns apparently play no role in Weitzman's analysis.     

Knightian uncertainty and poverty trap in a model of economic growth

This paper explores how Knightian uncertainty affects dynamic properties in an economic growth model. The decision-making theory employed in the analysis is the theory of expected utility under a non-additive probability measure, i.e., the Choquet expected utility model of preference. We apply this decision-making theory to an overlapping generations model where producers face “uncertainty” in their technologies. When the producer is averse to uncertainty, the firm's profit function may not be differentiable. Therefore, the firm's decision to invest and hire labor becomes rigid for a certain measurable range of real interest rates. In dynamic equilibrium, the existence of firm-level rigidity causes discontinuity in the wage function; this makes multiple equilibria the more likely outcomes under the log utility and Cobb–Douglas production functions. In this paper, we show that even if aversion to uncertainty is small, the “poverty trap” can arise for a wide range of parameter values.     

Influence of decision styles on use of decision models

This article discusses how the “decision style” of an administrator influences the adoption and use of particular decision models. Several “interactive” and “analytical” decision models often used to guide decision making are described and critiqued to point out their virtues and deficiencies. Propositions are suggested that contend that “systematic,” “judicial”, “speculative”, and “intuitive” styles have clear-cut preferences for a particular decision model. This model seems to be used, even when another would be more suitable. Effective decision makers are postulated to adapt their styles, or at least to see the benefits of different styles. Mixed-mode models are proposed that seem to simulate the behavior of successful decision makers.