Multi-Factor Optimization and Factor Interactions during Product Innovation
AbstractIn this paper, we develop core of an expert system for planning of innovation. The practical outcome of the paper is based on rules determination for search of perspective innovation and its distinguish from commercially unperceptive innovation. The second practical outcome of the paper is a research of interactions between factors during optimization of the product. In general, we gain process synergy, which can be a source of competitive advantage during product innovation in the presence of organizational complexity by systematically moving through the process definition, control, and improvement elements. The improvement elements can cause interactions between these elements (or factors/process parameters). First, we have to distinguish between synergistic and antagonistic interactions. For synergistic interaction can be used graphic illustration - lines on the plot do not cross each other. In contrast, for antagonistic interaction, the lines on the plot cross each other. In this case, the change in mean response for factor at low level is noticeable high compared to high level. Searching for positive interactions leading to the creation of synergies in the performances we can do at each stage of management innovations. At first, we realize only part of the possible gain, with unrealized potential remaining. Using process control, over time, we stabilize our process and obtain additional limited gain. Using process improvement, we can realize additional gain (it looks as short vertical line during the time), with some potential gain remaining. When new, feasible options develop, we can redefined our process and continue with our control and improvement efforts. Hence, each process-related issue definition, control, improvement has a distinct role to play. Confusion between roles or the omission of any of the roles creates disharmony and frustration in the production system, which ultimately limits production system effectiveness and efficiency. Sometimes, in the presence of confusion, it is possible that effectiveness and efficiency may decrease. In this situation, we hope to learn from our negative factor interactions (or failures) and subsequently improvement trends in long term with using sophisticated methods and own intuition. This paper objective is to create rules for planning innovation expert system. According to this rules will be possible to distinguish perspective innovation from commercially unperceptive innovation. The second paper objective is to explore interactions between factors during a product optimization. For this purpose will be used the methodology based on minimization of logic functions and design of experiments (analytical tools of DOE).
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Bibliographic InfoPaper provided by European Association of Agricultural Economists in its series 131st Seminar, September 18-19, 2012, Prague, Czech Republic with number 135787.
Date of creation: 18 Sep 2012
Date of revision:
Innovation; expert system; multi-criteria optimization; effectiveness; efficiency; synergy; process improvement; logic function; redundancy factor; design of experiments; Agribusiness; Agricultural and Food Policy;
This paper has been announced in the following NEP Reports:
- NEP-AGR-2012-11-24 (Agricultural Economics)
- NEP-ALL-2012-11-24 (All new papers)
- NEP-INO-2012-11-24 (Innovation)
- NEP-KNM-2012-11-24 (Knowledge Management & Knowledge Economy)
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