Master of Science (MS)
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First Advisor's Name
Martha Aixchel Centeno
First Advisor's Committee Title
Second Advisor's Name
Third Advisor's Name
Date of Defense
As proven by many studies, non-industrial consumers perceive price as a strong quality indicator. However, the applicability of this behavior to an industrial setting has been long questioned. It is hypothesized in this research that the levels of price-perceived quality will decrease in an industrial setting as the technical knowledge of the buyer increases. Judgement Sampling method was used to select the most appropriate sample for this study. Since engineers are particularly important influencers in the purchase decision process in organization, engineering students and professors were chosen as the study population. A survey was administered to a sample population that consisted of 153 respondents out of which 3.3% were professors, 9.8% graduate students, and 76.4% undergraduate students; 70.6% males and 15.7% females; 13.7% Mechanical Engineering, 28.1% Industrial Engineering, 7.8% Civil Engineering, 34% Electrical Engineering, and 4.6% Computer Engineering students. We evaluated the relationship between technical knowledge and price-perceived quality in an industrial setting using various regression models and other statistical models. Findings indicate that the price-perceived quality effect moves from an almost linear behavior to a nonlinear one as the technical knowledge increases. However, the transition from linear to nonlinear seems to be random. Further studies are needed. In our specific experiment, technical attributes, such as processing speed, RAM size, hard drive size, and CD-ROM speed, possess a strong positive relationship with quality (i.e. a "the faster, the better; the more, the merrier" type of situation); on other hand, our experiment indicates that price loses its significance as an indicator of quality as the buyer's technical knowledge increases.
Caicedo, Jeannie Helen, "Relationship between technical knowledge and price-perceived quality in an industrial setting" (1994). FIU Electronic Theses and Dissertations. 1967.
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