JSSPRM will create an award system this year, based on the author's review on the mission of the Society. Our interest lies in management and policy issues related to science and technology as practical and interdisciplinary researches. Research of this kind is susceptible to criticism for alleged "uselessness" and "lack of scientific self-sufficiency". We should counter this by presenting consequent research results. This "consequence" must be a criterion for the awards. The practical interdisciplinary research is a field where discipline-based approaches are integrated with mission-oriented development. What should be pursued here is usefulness in more fundamental, more generic, and wider and longer-term view, supported by logical consequence. More specifically, analyses on dynamic processes and for the future are of prime importance, and development of concepts, models, tools, instruments and methodology for that purpose will form a substantial part of our efforts. Accumulation of such activities should lead to maturity of the field in which a new paradigm, comprising new specific disciplines, will be established.

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Panel data often serve as the basis for innovation analysis on corporate R&D activities and their economic impacts. Unlike simple time series or cross section data, panel data permit analysis of dynamic aspects of innovation activities involving cross-sectional (e.g. cross-enterprise) developments. This article reviews the methodology of panel data analysis as exemplified by an estimation of production function at the corporate level. The explanatory variables in the production function at the corporate level may include factors of production, such as labor and capital, quality of the management and employees, brand image, organizational management, and many more. Such qualitative factors are not usually treated as explicit explanatory variables in estimation of the production function because of difficulty in statistical treatment, but they do bias estimation. An advantage of estimation based on panel data is freedom from such biases. In practice, "fixed effect" models are often used in which unobserved variables are assumed to be constant over the period of observation. It is known, however, that the fixed effect model enlarges the influence of errors in explanatory variables on the estimation results. The article describes a model for evaluating the relative influences of unobserved variables and of data errors. It also presents an overview of the instrumental variable technique, which is indispensable for dealing with the problem of endogenicity of explanatory variables, taking into account the characteristics of panel data. Since the estimated production function is highly dependent of the estimation technique used, choosing an appropriate method is of prime importance in statistical estimation using panel data.

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The present article overviews the covariance structure analysis, gives a summary of its important concepts, and answers some common questions, before describing as an example a covariance structure analysis conducted by the authors on a questionnaire survey on the national projects. The article intends to illustrate the applicability of the technique to innovation studies, and to stimulate interested analysts to better assimilation of it. The example presented here analyzes the management of national projects in terms of their ripple effects that help the R&D and business in participant companies. More specifically, the effects of open discussion on the subjects and tasks in an early stage of a project are compared with those of modifications in the subjects, resources distribution or general policy based on an intermediate evaluation, with some discussion of the results.

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The article reviews scientometrics as a methodology for policy science. Science and technology policy necessitates measurement and evaluation of the current scientific activities in order to develop future steps. Scientometrics, which studies methods, objects and effectiveness of measuring scientific activities, should therefore be an important constituent of policy science. The term "scientometrics" was coined after "psychometrics" and "sociometrics", which share quantitative view of the subject of study. The present work first shows how scientometrics differs from bibliometrics or library and information science to indicate the need of a theory on what aspect of scientific activity is measured quantitatively. It then presents a historical overview of scientometrics in four phases: pre-history, establishment of the principle, development and institutionalization of indicators, and application to evaluation. The article further reviews practical methods including analysis of the number of reports, citation and co-citation analysis, term and co-term analysis, and forming and combination of indicators. Discussion on the possibility of and potential issues on quantification concludes the article.

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The purpose of this paper is to propose a framework of standard procedures for a basic exploratory social network analysis. Social network researches have experienced a great change in 1998. Inspired by Watts and Strogatz, huge number of natural scientists started to pay attention to networks and have searched for common behaviors of and laws governing social, natural, informational and various kinds of networks. Both social network analysts with sociological or organizational backgrounds and natural or engineering scientists (e.g. physicists, mathematician, medical scientists, information scientists, AI researchers) who share their interest in network feel the need for mutual collaboration. The need is serious, yet there exist many obstacles for successful collaboration. Lack of attention to prior researches and differences in definition of concepts, in usage of parameters, in authorships are the examples. For successful interdisciplinary collaboration, I propose a framework of standard procedures for a basic exploratory social network analysis. My framework does not require any prior knowledge of programming nor super-high-power computing system. As I assume users of this framework to be beginners or middle-class network analysts, required are middle-class windows machine, UCINET, Pajek, EXCEL and common statistical package.

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Technology foresight has been practiced in various levels including enterprises, industrial organizations, scientific associations, local authorities, government agencies, states, and even on an international level. It varies in time scale from near to far future, as well as in participants, processes and techniques according to different purposes. Technology foresight in Japan has been applied to prioritizing R&D investments in Science and Technology Basic Plan. Foresight methodologies have evolved reflecting changes in social and economic circumstances of science and technology, including the recent global trend to emphasis on innovation which demands outcomeoriented science and technology policy. Each methodology has its own merits and demerits; the fittest for the purpose of a study must be chosen. Sometimes more than one methodology is combined in a complementary manner, as in the eighth Technology Foresight Survey, which comprised socio-economic needs analysis (vision of society in future and its needs by nonscientists), study on rapidly developing research areas (based on bibliometric analysis), and scenario analysis of major areas in science and technology by outstanding individuals, in addition to the standard Delphi survey. This was the first attempt of comprehensive foresight on a national level based on a combination of various methodologies. Science and technology foresight should evolve to cope with the everchanging environment as an important tool of policymaking.

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In this paper, we focus on the hybrid social simulation that is a combination of gaming simulation by human agents and agent based simulation by machine agents. The hybrid social simulation makes it possible to develop social informed and consent process by extending our communication mode. An agent based simulation supports construction, simulation and evaluation of our decision scenarios. However, a gaming simulation supports human understanding the scenarios. Social simulation gives not the model depending on the universal low but the model for the exploration of future possibilities. It gives a constructed social reality that should be shared and used for planning and evaluating the future scenarios. In other words, the social & organizational planning should gives a shared internal model for understanding the future scenarios. The hybridization of agent based simulation and gaming simulation will help us to share the simulated internal model for the scenario.

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今日,半導体ユーザーである設計技術者の関心事が,個々の半導体デバイスに対してというよりは,自分達が機器に盛り込もうとしている機能・性能を実現する上で最適な半導体や部品の組み合わせ,いわゆるソリューション提供に移ってきていることで,半導体業界における付加価値の一部は,メーカーよりもユーザーに近い半導体商社の方にシフトしてきていると考えられる。大手半導体商社は,この顧客価値のシフトを,自社の付加価値として取り込めるような仕組み作りを行っている。公表されている半導体商社各社の経営方針や経営戦略の内容を見ると,ほとんどの企業が共通して技術商社を標榜し,顧客に対し提案型で営業を行うソリューション提供力の強化を掲げている。各社ともソリューション提供機能を強化するために開発要員を揃え,設計機能を強化し,メーカー系商社でさえも,仕入れ元の多様化,新規商材の開拓を経営目標の一つとして掲げている。各社ともほぼ同様のビジネスモデルを志向しているが,収益性を比較すると,収益性が相対的に勝っている企業は,メーカー系商社よりも独立系商社が多い。この要因としては,志向しているビジネスモデルはばぼ同様であっても,それを実行に移す上で必要な要件をどの程度備えているかで,結果として出来上がっているビジネスシステムに差が生じ,収益性に差が出ている一因となっていると考えられる。

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公的機関の推進する研究開発プロジェクトが効率的かつ効果的に成果を発揮するためには,適切な目標設定とそのマネジメントが極めて重要となる。本稿では,具体的な事例を基に,公的機関における研究開発プロジェクトの目標設定の現状を調査検討した。その結果,数値目標化については徹底されている一方で,目標設定段階における前提条件や背景の明示,プロジェクトの性格に応じた目標設定,意欲的な目標を設けつつ,機動的に目標を見直す必要性等の問題があることが明確になった。そこで,本研究では,公的研究機関が実施する研究開発プロジェクトにおいて,技術的観点,経済的観点,社会的観点および政策的観点から望ましい目標設定及び管理方法の在り方について提案する。

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本稿では,生命の設計図を解明する巨大科学プロジェクトであったヒトゲノム計画を日米比較する事により,日本の科学技術政策決定過程を分析する。高度な専門知識を有する科学者が,政治アクターにどの様に関わり,科学技術分野で政策決定が行われているかを,境界組織を含むプリンシパル・エージェントのフレームワークで検証する。具体的には,米国では,科学技術関連省庁内の政策決定に権限を持つ地位に専門知識を有する科学者を配置する制度や,複数の科学評価機関が「統制された科学的市場(Regulated Scientific Market)」をプリンシパルに提供する制度が,政治と科学の媒介機能を生み出している。しかし,こうした機能を持つ制度が日本にはまだ整備されていない事を指摘する。

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我が国の製造業に従事している生産・技能職及び専門・技術職員を中心に,職務意欲が低下していることが問題になっている。本論文は,動機付けにおける組織の視点と個人の視点を融合させ,両者が互いにメリットを得られるような職務意欲向上のための動機付け施策を提示し,その効果を実証データに基づき分析することを目的としている。特に我々は研究・開発人材の未来志向的な欲求に注目し,マネジャーが仕事目標を通じて部下の将来的なキャリア向上欲求を刺激し夢を与えることが,部下の職務意欲を向上させることにつながることを,日産自動車の研究開発者に対するアンケート調査から明らかにしている。またアンケートデータを共分散構造分析した結果,マネジャーが部下の未来志向的な欲求を刺激するには(1)部下の夢の創造支援,(2)創造した夢と仕事の結びつけ支援,という2つのプロセスを完了することが重要であり,この2つのプロセスは未来志向的動機付けを行う際の最も重要なプロセスであることを,未来志向的欲求刺激と行動に関する仮説的なメカニズムをもとに示している。

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