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  • Alhamdan, Haitham S.
     
     Subjects
     
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  • Internet advertising.
     
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  • Internet marketing
     
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  • Consumer behavior
     
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  • Marketing research
     
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  • MSEM Thesis.
     
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  •  How online purchase ...
     
     
     
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    How online purchase decisions are made : analyzing the consumer decision-making process in an online purchasing environment / Haitham S. Alhamdan.
    by Alhamdan, Haitham S.
    Subjects
  • Internet advertising.
  •  
  • Internet marketing
  •  
  • Consumer behavior
  •  
  • Marketing research
  •  
  • MSEM Thesis.
  • Description: 
    139 leaves : ill. ; 29 cm.
    Contents: 
    Advisor: Gene Wright.
    Committee Members: Gene Wright, David Tietyen, Bruce Thompson.
    Introduction -- Random utility theory -- Discrete choice models -- Theory of consumer behavior -- Online purchase decisions -- Model development -- Data collection -- Simulation and estimation -- Models estimation -- Strategy for online marketing -- Conclusion and recommendations -- Bibliography -- Appendix A: Charts and figures -- B: Tables -- Cix C: Survey instrument.
    There have been a number of research studies with the aim of understanding how consumers make purchase decisions. The major assumption in these studies is that decision makers analyze product offerings from different retailers and make a tradeoff decision among all offers to select the offer that delivers the greatest utility.
    With the advent of Internet shopping, consumers are faced with an overwhelming amount of product offerings, and consequently have a greater degree of freedom to choose among many different alternatives. Internet shopping carries a number of different characteristics than traditional shopping methods. In an online shopping environment, there are many variables that the decision maker evaluated which appear to be different from that of "classical" methods of shopping. These variables enter into the decision maker's utility functions and are evaluated on the basis of their importance to him or her. Unfortunately, the researcher does not have immediate access to those variables and cannot evaluate each one in isolation of the others. Hence, a bundle of these variables should be analyzed for different decision makers to assess the importance of each attribute and understand the implication of varying each attribute's level on the final decision of the consumer.
    There have been numerous research studies that looked into how consumers make purchase decisions. However, only a few have focused on analyzing the decision process of consumers and what attributes they usually consider and/or evaluate when shopping on the World Wide Web. This study analyzes this process and develops an empirical choice model for individual consumers in a particular market segment buying a particular product. This study's main contribution to the marketing literature is its consideration of behavioral attributes that show strong influence on the online buying behavior of consumers, such as attitudes, perceptions, memory, and learning. In order to keep the variables in the model at a manageable level, the author considers the perception variable as an influential behavioral attribute in the consumer's choice of online retailers. Specifically, the author tests the significance of the consumer's "perception of web retailer trustworthiness" on the choice of retailer.
    Historically, there has been a divide among the scientific community on the significance of behavioral attributes in influencing human decisions. In the economics and statistics literature, such soft attributes have not been modeled explicitly into consumer choice models with the assumption that consumers behave rationally. Consequently, the consumer was always assumed to choose an alternative that yeilds him or her maximum utility – given the attributes of the alternatives and attributes that are explicit to him or her, such as income. In addition, the evidence against the theory of rational behavior has been accumulating, leading researchers in the field to search for alternatives. Recently, however, there have been a few papers that looked into explicitly modeling softer attributes such as attitudes, perceptions, memory, and satisfaction into choice models. Evidently the results were improved models-fit, and a richer and a more behaviorally-realistic representation of the choice made by human decision makers.
    The theory of rational behavior makes the assumption that humans make decisions based on the attainable level of utility from making a decision. This implies that the decision making process follows a systematic, step-by-step process where the decision is planned and rational. The other theory is based on the psychology and cognitive science view of human behavior, in that human behavior is far from rational. It is learned, dynamic, and evolving, and therefore, unpredictable.
    This paper presents an overview of both theories. It portrays how each theory pertains to the online marketing problem. In addition, the paper presents a mathematical model for consumers' choice of web retailers. Attributes relating to the web retailer as well as the individual consumer are considered in building the model. Accordingly the author combines softer attributes of the decision maker (consumer) with other tangible attributes as they relate to the web retailer.
    A number of estimation techniques were used in the estimation of the proposed models, namely Maximum Likelihood Estimation (MLE), Maximum Simulated Likelihood Estimation (MSLE), and Bayesian estimation. Results from the estimation are presented, along with other measures of statistical significance. The results of the estimation confirm that softer attributes do indeed influence the choice of web retailer, particularly the consumer's perception of web retailer trustworthiness. Furthermore, models that incorporate softer attributes do I fact produce a better fit, as judged by goodness-of-fit statistics.
    Next, the paper presents a strategy for online marketing based on model outcomes. Strategies for segmenting, targeting, and positioning to the online consumer are presented in the strategy sections of the paper. Recommendations for applying the presented strategies are also discussed.
    The paper finally concludes by giving recommendations on the aspects discussed, particularly those pertaining to online marketing strategy and research. Moreover, a recommendation for integrating marketing information systems and intelligence is given in the recommendations section.
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