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• W1545448711 abstract "ABSTRACT This paper uses a Markov chain process to forecast a customer's behavior and combines the notions of collaborative prototyping and existence, relatedness, and growth (ERG) theory. Collaborative prototyping process allows two parties (e.g., customers and service providers) to anticipate the outcome of a design process. We also justify that the Markov chain within ERG theory would generate good performance in behavior prediction regardless of accuracy, precision, recall, and F1-measure. (ProQuest: ... denotes formulae omitted.) INTRODUCTION The processes of science and decision making share an important characteristic: success in each depends upon researchers or decision makers having some ability to anticipate the consequences of their actions. Conversely, be-ing predictive of unknown facts is essential to the process of related fields of research. Surely, the unknown facts could lie in the past or the future. Decision-making, generally, is forward looking, formulating alternative tracks of action extending into the future, and selecting among alternatives by expectations of how things will turn out (Lasswell and Kaplan, 1950). The predictive capacity of science holds great appeal for decision makers who are grappling with complex and controversial environmental issues. Furthermore, it promises to enhance the ability to determine a need for and outcomes of alternative decisions. Uncertainty is the condition of all human life for decision making which means more than one outcome is consistent with our expectations (Skidelsky, 2000). Expectations are a result of judgment, are occasionally based on technical mistakes and interpretive errors, and are shaped by values and interests (Pielke, 1999). Since uncertainty is a characteristic of each essential decision, it is no surprise that society looks to science and technology to assist in clarifying the expectations in ways that lead to desired outcomes. Hence, the qualified predictions which consider the uncertainty for superior decisions are significant. This paper utilizes the Markov chain process to forecast the needs and combines the notions of collaborative prototyping and ERG theory. Collaborative prototyping process allows two parties (e.g., customers and service providers) to anticipate the outcome of a design process. Furthermore, prototypes have two advantages: (1) they help customers evaluate unknown customized products and (2) guide both parties in searching for the optimal product specification. Furthermore, ERG theory, proposed by Alderfer in 1969, prioritizes user's needs in a hierarchy. The acronym ERG stands for three need levels-existence, relatedness, and growth. The ERG theory is based on the work of Maslow, who reduced the number of levels of needs to three. Nevertheless, ERG theory differs from Maslow's theory in three ways: (1) it allows different levels to be pursued simultaneously; (2) it allows the order of needs be different for different people; and, (3) when the highest level of needs remain unfulfilled, a person may regress to a lower level of needs that are relatively easier to satisfy. The remainder of the paper is organized as follows. In section 2 we explain the synthesis of three theories: collaborative prototyping, ERG theory, and Markov chain model. In section 3 and 4 developed an economic model and a method with proposed algorithm. In section 5 we demonstrate the evaluation of the proposed model. Ultimately, a conclusion is furnished in Section 6 to summarize the contributions of the research. RESEARCH BACKGROUND Collaborative Prototyping Costly information acquisition has remained an important topic in economic research since Stigler (1961) first addressed the issue. Economists have developed numerous equilibrium search models by citing several notions, such as information asymmetries and consumer search costs, to search for the lowest price. …" @default.
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• W1545448711 title "A Synthesized Model of Markov Chain and ERG Theory for Behavior Forecast in Collaborative Prototyping" @default.
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