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Li-Chun Huang and Yen-Chun Lin

satisfactory level, being a Cronbach’s α higher than 0.70, the minimum acceptable level for scale reliability ( Hair et al., 2010 ). Multinomial logistic regression analysis was applied to investigate the effects of the independent variables on the likelihood

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Yen-Chun Lai and Li-Chun Huang

profile the sample. Multinomial logistic regression analysis was used to evaluate the influence of the development stage, affection, and satisfaction level of a romantic relationship on the purchase decision of whether to buy fresh flowers as a romantic

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Li-Chun Huang

Product behavior represents how consumers perceive and use a product. Its importance in predicting consumer buying behavior is well documented in marketing research. There are, however, no data available investigating the role of product behavior in the floral market. This study addressed this deficiency. Data were first analyzed using factor analysis to extract the principal determinants of product behavior in the floral market. As a result, six primary behavioral factors were identified and named as: “using flowers as daily essentials,” “perceived product value,” “negative attitude toward flowers,” “using flowers as gifts,” “eventbased usage,” and “experience in receiving flowers.” The effects of these extracted behavioral factors on consumer flower purchase frequency were then further investigated with multinomial logistic regression analysis. Analytical results revealed that behaviors “using flowers as daily essentials” and “using flowers as gifts” forced consumers to become heavy users in the floral market. Conversely, “negative attitude toward flowers” negatively affected the floral purchase frequency. Experimental results in this study also suggest that promoting a positive attitude toward flowers is essential in encouraging consumers to become flower users. The intended use of flower product purchase, whether for personal use or as gifts, was the main factor affecting the frequent purchasing of flowers.