Technical resource management : quantitative methods

236 p., fig., ref. bib. : 13 p.1/2Traditional research management methods, the authors contend, are too unsystematic to continue to control the funding and allocation of men, money, and materials in research. Today, research and development (R&D) funds total $25 billion, of which federal funds account for 80%. If only because of researchers' responsibility for this cost, the authors say, "there must be a logical, rational way to select the tasks to be worked on and the resources to be expended on the effort." In fact, over the past decade a wide range of planning tools have been developed and tested; the authors believe they work; and this book gives an overview of the most significant resource allocation techniques now being used in government and industry. Among the suggested strategies for planning are rigorous goal identification, sample budgeting, time apportionment, and selection of those research paths which give the greatest over-all payoffs. The authors emphasize that hard choices must be made, and that research projects must be assigned a "value" rating so that the most promising ones are given priority, while less important ones are deferred. The allocation of funds represents one of the most difficult but also one of the most fruitful aspects of the decision-making process. One of the methods for making such decision is the Methodology for Allocating Corporate Resources to Objectives (MACRO) which has been used in Europe as well as in the U.S. Another procedure, now being employed by the Air Force Flight Dynamics Laboratory, involves the use of computerized planning programs. Only research that has been carefully planned will yield the most significant technological advances. Yet development must be just as carefully managed, for its cost may be phenomenal, and a wrong start could be catastrophic. Finally, the authors consider technological forecasting, which must be accurate enough to provide the judgment necessary to prevent overextension of resources on the one hand, and incipient obsolescence on the other. Here, as in current planning, rigorous management control must be practiced

The impact of market size and users' sophistication on innovation: the patterns of demand

The aim of this paper is an investigation on the role of demand upon innovation. Despite the decades-long debate on demand and innovation, theory still lacks an analytical formulation. This paper proposes a model where demand is conceived as a peculiar blend of two conditions, market size, and users' sophistication. These conditions drive firms' incentives to innovate. As the main outcome, the paper explores the underlying mechanisms of demand-pull theories and proposes a theoretical taxonomy of industries.innovation, demand,

Relational, interactive service innovation : Building branding competence

Original article can be found at: http://mtq.sagepub.com/ Copyright Sage [Full text of this article is not available in the UHRA]In this paper we discuss how to develop service innovation through building branding competence. We demonstrate that using relationships in a process of sharing adds value to the service innovation process. We draw upon two distinct perspectives in the literature. We agree that value in new service development comes from incorporating the consumer. Yet we also deduce that it is the firm's core competencies that provide optimal resources for innovation. We then conceptualize how these two perspectives on service innovation can be integrated around relationships incorporating the 'customer resource'. This process is relational, interactive service innovation. The conceptual framework we have developed offers a different approach for companies to view the new service development process in general and the building of branding competence in particular. We suggest that organizations may be able to improve their new service development process by emphasizing the internal and external linkages within the management of innovation.Peer reviewe

Searching for new breakthroughs in science: How effective are computerised detection algorithms?

In this study we design, develop, implement and test an analytical framework and measurement model to detect scientific discoveries with 'breakthrough' characteristics. To do so we have developed a series of computerized search algorithms  that data mine large quantities of research publications. These algorithms facilitate early-stage detection of 'breakout' papers  that  emerge as highly cited and distinctive and are considered to be potential breakthroughs. Combining computer-aided data  mining with decision heuristics, enabled us to assess structural changes within citation patterns with the international scientific literature. In our case studies we applied a citation  impact  time  window  of 24--36 months after publication of each research paper.  In this paper, we report on our test results, in which five algorithms were applied to the entire Web of Science database. We analysed the citation impact patterns of all research articles from the period 1990--1994. We succeeded in detecting many papers with distinctive impact profiles (breakouts). A small subset of these breakouts is classified as 'breakthroughs': Nobel Prize research papers; papers occurring in Nature's Top-100 Most Cited Papers Ever; papers still (highly) cited by review papers or patents; or those frequently mentioned in today's social media. We also compare the outcomes of our algorithms with the results of a 'baseline' detection algorithm developed by Redner in 2005, which selects the world's most highly cited 'hot papers'.The detection rates of the algorithms vary, but overall, they present a powerful tool for tracing breakout papers in science. The wider applicability of these algorithms, across all science fields, has not yet been ascertained. Whether or not our early-stage breakout papers present a 'breakthrough' remains a matter of opinion, where input from subject experts is needed for verification and confirmation, but our detection approach certain helps to limit the search domain to trace and track important emerging topics in science.Merit, Expertise and Measuremen