Thesis (Ph. D.)--University of Oregon, 2001. / Typescript. Includes vita and abstract. Includes bibliographical references (leaves 141-147). Also available for download via the World Wide Web; free to University of Oregon users.

Thesis (MA)--University of Montana, 2010. / Title from author supplied metadata. Includes bibliographical references.

Thesis (M.S.)--The University of North Carolina at Greensboro, 2008. / Directed by Kittichai Watchravesringkan; submitted to the Dept. of Consumer, Apparel and Retail Studies. Title from PDF t.p. (viewed Jan. 28, 2010). Includes bibliographical references (p. 108-121).

Thesis (Ph. D.)--Florida State University, 2003. / Advisor: Dr. Brenda Pitts, Florida State University, College of Education, Dept. of Recreation Management, Sport Management, and Physical Education. Title and description from dissertation home page (viewed Oct. 7, 2003). Includes bibliographical references.

Thesis (Ph. D.)--University of Queensland, 2001. / Includes bibliographical references.

In recent years, social commerce sites such as Groupon and LivingSocial have achieved great success in attracting new consumers and increasing store traffic for a growing number of businesses. However, it is still unclear how the information flow to reach new consumers is generated. Understanding this information flow is the key to the question of what lead to the success of these companies. In the online context, the key information disseminators can have both a large-scale network and a decisive influence on the nodes that are connected closely to them, indicating an important pattern of consumer purchase process. Here, we argue that one of the prominent advantages of social commerce is the information dissemination process, during which word of mouth (WOM) is generated to boost consumer traffic. In the present study, we conduct a cluster analysis to segment online shoppers according to their information dissemination contribution. Gatekeeping theory was used for conceptualizing consumers who tend to disseminate more commercial information and WOM in social commerce, providing us the theoretical basis for clustering consumers. Our findings suggest that a sizable proportion of consumers constituted the gatekeeper group (approximately 25%). Gatekeepers tend to be highly active in both finding the outside source of information and connecting it with inside social networks. In addition, different aspects of the potential to become gatekeepers divide the rest of the consumers into two groups. To date, the present research is the first to explore online consumer segmentations using the gatekeeping perspective. / text

The primary hypothesis of this study was that low-income individuals purchase more packaged foods of lower healthiness and lower price compared to similar packaged foods of higher healthiness and higher price. The Nutrition Metric was chosen as the system to measure the nutritional value of foods because it is in the public domain and uses nutrients common to the Nutrition Facts panel; however, prior to use, the validity of the Nutrition Metric needed to be tested. The convergent validation of the Nutrition Metric was tested with four systems (NuVal, Guiding Stars, WXYfm, Go-Slow-Whoa) that met the study criteria. A sample of 600 foods that were purchased over a 104 week period that ended in November 2009 by 34,407 low-income households was drawn to achieve at least 168 items having scores available for each system. The Nutrition Metric had a positive correlation with all scoring systems for the 174 foods (P<0.01) that verified its validity as a tool to assess food healthiness. The Nutrition Metric was used to measure the healthiness of packaged products from the list of low-income food purchases (n=316). Products had a negative mean healthiness score of -0.88 ± 1.72 and low levels (<5% Daily Value) of dietary fiber, vitamin A and C, iron, and cholesterol. The majority of the products (n=305) did not have a nutrient claim on product packaging. The Nutrition Metric was a successful tool that can be utilized to assess the healthiness differences between products with and without nutrient claims purchased by low-income shoppers with counterpart products at the supermarket. Food price and healthiness differences were evaluated for the list of packaged products (n=305 (minus 11 single ingredient cooking staples)) commonly purchased by low-income shoppers to counterpart products of the same brand and package size with or without nutrient claims. Products with nutrient claims (n=77), on average, had higher healthiness scores and prices than products without claims (n=77) (P<0.01). Research and education initiatives that promote the selection of products with claims instead of products without claims are potential options to improve the diets of low-income consumers. / text

To survive and thrive in the customer-oriented global market, retail companies have to make persistent efforts to provide customers with satisfactory shopping experience enriched by leisure process, interaction for merchandise information and personalised assistance. In traditional retail stores, customers’ needs cannot be fully satisfied due to difficulties in locating target products, out-of-stocks, a lack of professional assistance for product selection, and long waiting for payments. The relative visibility and traceability of individual items provided by the radio frequency identification (RFID) technology is helpful for enhancement of customer shopping experience (CSE). However, current RFID applications for retail business tend to be limited to inventory control and replenishment, with few implementations for CSE enhancement based on collection and analysis of real-time RFID data. To mitigate these limitations, this research project develops RFID applications for real-time collection and analysis of customer shopping behaviour (CSB) data in retail stores. Artificial intelligence (AI) is incorporated for data analysis to facilitate business decision-making and proactive individual marketing. Accordingly, an item-level RFID-based customer shopping experience enhancement (IRCSEE) system is developed to provide customers with leisure shopping process, interaction for merchandise information and personalised guidance for enhancement of CSE in apparel retail stores. The IRCSEE system incorporates RFID hardware devices installed in an apparel retail store to interrogate RFID-tagged apparel items to obtain data for subsequent sales processing and analysis. It is characterised with a programmable data format for unique identification of individual apparel items, together with a suite of software modules to control the RFID hardware devices at different locations of the apparel retail store for real-time collection of product information and CSB data. Moreover, an innovative fuzzy screening (FS) algorithm of AI techniques is developed to analyse the RFID-collected CSB data and the corresponding product information for generation of apparel collocation recommendations to provide customers with intelligent and personalised assistances in product selection. The algorithm considers not only the static fashion expertise, but also the dynamic customer preferences for collocation, such that the recommendations are more effective and adaptive for enhancement of CSE in the fast-changing apparel retail industry. The IRCSEE system is validated in an emulated RFID-based apparel retail store. Experimental results demonstrate that with appropriate RFID hardware settings, the proposed system is effective to help enhance CSE in apparel retail stores by providing customers with leisure shopping process, interaction for merchandise information and personalised apparel collocations. Furthermore, the approaches for collecting real-time CSB by RFID technology and analysing such data by AI techniques can be conveniently adapted for many other products to improve retail business management in general. / published_or_final_version / Industrial and Manufacturing Systems Engineering / Master / Master of Philosophy

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A new perspective on consumer behavior is proposed using theoretical predictions developed from behavioral ecology, economics, and evolutionary psychology. These predictions pose the possibility that consumers often make choices based on mental processing heuristics evolved long before the extensive human development of the cerebral cortex, and are therefore automatic, interrelated, and non-conscious. The literature review develops theoretical platforms that suggest consumer choice may be based on signal qualities that are expected to be honest indicators of the quality of the signaler and synthesized into the concept of 'Advertiser Fitness.' The construct of Advertiser Fitness is conceived as integrated perceptions of advertiser creativity (signal style) and perceptions of perceived quality of ad production (signal quality), and is statistically validated across two product categories, cell phone services and auto insurance. In addition, Advertiser Fitness is shown to have statistically significant positive associations with traditional measures of advertising effectiveness, including Attitude Toward the Ad, Attitude Toward the Brand, and Purchase Intent. The interrelated constructs of Perceived Honesty, Perceived Advertiser Status, Self-Relevance, and Potential Word of Mouth are also shown to be have statistically significant positive correlations with the Advertiser Fitness construct and with the traditional measures of advertising effectiveness: Attitude Toward the Ad, Attitude Toward the Brand, and Purchase Intent. These constructs appear to be inter-related and redundant rather than having causal, linear relationships. The results suggest that observable creative dimensions of advertiser signals convey signaler (advertiser) quality. Similarly, impressions of signaler (advertiser) status are important inputs for the formation of positive consumer perceptions and are associated with measures of potential action including purchase intention and predicted word-of-mouth. This work opens a new window into understanding consumer behavior by introducing contemporary observation to evolutionary sources of motivation for behavior, and views consumer markets as dynamic ecosystems which can potentially be illuminated by better understanding and application of phenomena in natural ecosystems for consumer behavior.