Pop-up retail was first introduced as a new marketing concept in 2003, but it only appeared in South Africa in 2008. Pop-up retail is still viewed as an innovation in South Africa. It entails the opening of a tentative store, located in a unique space or venue, offering the opportunity for product trial and “one-of-a-kind” store experiences through the use of unique venues. Pop-up stores are temporary and their opening is mostly unannounced (OPEN TEXT CORPORATION, 2008c:4). Consumers are forced to make quick decisions to either visit the store or not, as these stores have a limited lifespan. Pop-up retail offers an entertaining and satisfactory retail environment and may provide a solution for retailers to survive fierce competition. The purpose of this study was to explore the relationships between characteristics of the innovation (relative advantage, trialability, observability, low complexity, compatibility), internal factors (mood or emotional state, hedonic desires, consumer innovativeness), an external factor (exterior store design) on the one hand, and young South African consumers‟ impulse intention to visit a pop-up store on the other. An exploratory survey research design was followed. Data was collected by means of a structured, self-administered questionnaire developed from existing scales. It was administered to a convenience sample of 523 South African students. Confirmatory factor analyses were done to validate the latent underlying variables for the hybrid model. Pearson‟s correlation coefficient test was run for testing various hypotheses, establishing the correlation between the independent variables and the dependent variable. Values of the correlation coefficient ranged between 0.39 and 0.61, indicating a positive correlation between the independent variables and the impulse intention to visit a pop-up store. All the correlations were significant at the 1% level (p-value < 0.0001). Multiple regression analysis was employed to test and quantify the relative contribution of the multiple independent variables to predicting impulse intention to visit a pop-up store. The findings indicated that all the hypotheses developed for the study were supported. Characteristics of an innovation, internal factors and external factors were proven to play a role in young South African consumers‟ impulse intention toward pop-up retail. Observability, compatibility, consumer innovativeness and exterior store design appeared to be more predictive of consumers‟ impulse intention to visit pop-up stores. The study was limited to students enrolled at only two tertiary institutions in South Africa. Further research is needed at tertiary institutions in other cities in the country. The study focused only on impulse intention to visit pop-up stores in South Africa and future research is needed to study the different forms of pop-up retail to determine the most effective ones locally, as well as the behaviour of consumers visiting an actual pop-up store. Retailers making use of pop-up stores should include unique products, engaging experiences, signage and trial opportunities for consumers. Store design should be eye-catching, hedonically pleasing and explorative, with moderate complexity to attract innovative consumers and result in optimum success. / Dissertation (MConsumer Science)--University of Pretoria, 2012. / gm2014 / Consumer Science / unrestricted

A study of consumer cooperation in the United States relating to education, labor, business, religion, and government.

This thesis consists of three papers in optimization and revenue management over complex networks: Robust Linear Control in Transmission Systems, Online Learning and Optimization Under a New Linear-Threshold Model with Negative Influence, and Revenue Management with Complementarity Products. This thesis contributes to analytical methods for optimization problems in complex networks, namely, power network, social network and product network. In Chapter 2, we describe a robust multiperiod transmission planning model including renewables and batteries, where battery output is used to partly offset renewable output deviations from forecast. A central element is a nonconvex battery operation model plus a robust model of forecast errors and a linear control scheme. Even though the problem is nonconvex we provide an efficient and theoretically valid algorithm that effectively solves cases on large transmission systems. In Chapter 3, we propose a new class of Linear Threshold Model-based information-diffusion model that incorporates the formation and spread of negative attitude. We call such models negativity-aware. We show that in these models, the expected positive influence is a monotone sub-modular function of the seed set. Thus we can use a greedy algorithm to construct a solution with constant approximation guarantee when the objective is to select a seed set of fixed size to maximize positive influence. Our models are flexible enough to account for both the features of local users and the features of the information being propagated in the diffusion. We analyze an online-learning setting for a multi-round influence-maximization problem, where an agent is actively learning the diffusion parameters over time while trying to maximize total cumulative positive influence. We develop a class of online learning algorithms and provide the theoretical upper bound on the regret. In Chapter 4, we propose a tractable information-diffusion-based framework to capture complementary relationships among products. Using this framework, we investigate how various revenue-management decisions can be optimized. In particular, we prove that several fundamental problems involving complementary products, such as promotional pricing, product recommendation, and category planning, can be formulated as sub-modular maximization problems, and can be solved by tractable greedy algorithms with guarantees on the quality of the solutions. We validate our model using a dataset that contains product reviews and metadata from Amazon from May 1996 to July 2014. We also analyze an online-learning setting for revenue-maximization with complementary products. In this setting, we assume that the retailer has access only to sales observations. That is, she can only observe whether a product is purchased from her. This assumption leads to diffusion models with novel node-level feedback, in contrast to classical models that have edge-level feedback. We conduct confidence region analysis on the maximum likelihood estimator for our models, develop online-learning algorithms, and analyze their performance in both theoretical and practical perspectives.

In this thesis, I explore in two essays how to augment thin historical purchase data with other sources of information using Bayesian and probabilistic machine learning frameworks to better infer customers' preferences and their future behavior. In the first essay, I posit that firms can better manage recently-acquired customers by using the information from acquisition to inform future demand preferences for those customers. I develop a probabilistic machine learning model based on Deep Exponential Families to relate multiple acquisition characteristics with individual level demand parameters, and I show that the model is able to capture flexibly non-linear relationships between acquisition behaviors and demand parameters. I estimate the model using data from a retail context and show that firms can better identify which new customers are the most valuable. In the second essay, I explore how to combine the information collected through the customer journey—search queries, clicks and purchases; both within-journeys and across journeys—to infer the customer’s preferences and likelihood of buying, in settings in which there is thin purchase history and where preferences might change from one purchase journey to another. I propose a non-parametric Bayesian model that combines these different sources of information and accounts for what I call context heterogeneity, which are journey-specific preferences that depend on the context of the specific journey. I apply the model in the context of airline ticket purchases using data from one of the largest travel search websites and show that the model is able to accurately infer preferences and predict choice in an environment characterized by very thin historical data. I find strong context heterogeneity across journeys, reinforcing the idea that treating all journeys as stemming from the same set of preferences may lead to erroneous inferences.

The main objective of this study was to describe the restaurant dining patterns of a representative random sample of adults 65 years of age and older and to evaluate the impact that their health concerns and special diets have on their restaurant dining patterns. In addition, the specific features of food service products and services that are important to aged individuals when selecting a restaurant were examined. The phrase '<i>dining patterns</i>' refers to both <i>food intake</i> (the specific foods consumed) and individual <i>consumption patterns</i> (time, frequency, location of meals, and dining companions). Four different measures were used to quantify <i>food intake</i>: (1) entree items most often selected; (2) preferred method of preparation; (3) frequency of dessert purchases; and (4) type of dessert most often selected. <i>Consumption patterns</i> were quantified as: (1) type of restaurant patronized for each meal period; (2) frequency of restaurant visits per meal period; (3) dollar value of purchases per meal period; and (4) restaurant dining companions. A mail survey of 1000 adults age 65 and older, was conducted in order to obtain information about the restaurant menu selections and consumption patterns of aged individuals living in the Commonwealth of Virginia. / Master of Science

No description available.

Riding the crest of the torrent of verbal altruism which flooded in the New Deal came a malnurtured little fellow, the consumer-the same timid, mistreated, gullible little fellow with the battered derby hat whom cartoonists have so aptly pictured on the stool peering meekly over the counter at the big bruiser, the producer, who stood behind it. Put now he was to be such rejuvenated personage. The hair shirt in which one writer has so smartly dresed him was to be miraculously transformed into finest armor of an impregnable protective allogy which was to be composed of nemerous ethical abstractions. Prominent among these was to be thorough education as to his enemies' methods of attack and manners of exploitation, which was to include insturction in the arts and practies of the skull-duggery of advertising, which is perhaps the most effective weapon of his adversary.

The purpose of this study was to define the messages related to food preparation that are conveyed by women's magazines to homemakers as consumers during the post-World War II period, and to analyze any changes of those messages over time. A content analysis of food related articles and advertisements in representative issues of Ladies' Home Journal and Good Housekeeping magazines from 1947 to 1986 was conducted. Both manifest and latent content were coded and agreement between the two measures was analyzed. Of eighteen messages defined, five were found to account for 78.9 percent of the messages conveyed,. The five messages, listed in descending order, were (1) taste and visual appeal, (2) convenience and versatility, (3) nutrition, (4) quality, and (5) expertise in homemaking and hostessing skills. Using a test of chi-square, no significant difference in the distribution of the messages conveyed from year to year was found. Nevertheless, changes in presentation of the messages were found. Changes were geared to changing technological orientations, economic conditions, and gender roles.

A research report submitted to the Faculty of Commerce, Law and Management, University of the Witwatersrand, in partial fulfilment of the requirements for the degree of Master of Management in the field of Strategic Marketing, Johannesburg 2019 / There is increased usage of self-service technology in efforts to deliver superior service quality in business schools. This transition from face-to-face interaction has led to both satisfaction and dissatisfaction with service quality delivered. This study sought to ascertain the impact self-service technologies have on the perception of service quality (Servqual) dimensions of reliability, tangibility, assurance, responsiveness and empathy. A survey research instrument based on an adapted Servqual questionnaire that was self-administered was employed. Convenience sampling was utilised on the Wits Business School campus, with 210 students’ views captured. Then, the data was analysed using GAP analysis and descriptive statistics extrapolated from the data. The results of the study indicate that a transition to self-service portals does not lead to customers having a positive view of all the service quality dimensions as most customers were neutral in their perceptions. Students, therefore, need to have both self-service technologies and walk-in centres for face-to-face interaction. The study contributes to the ever-increasing knowledge on the usage of self-service technology in higher education in emerging markets. While there are significant shifts towards usage of the portals in business schools, there is a need to control the pace of change and avoid drastic adoption without other options as it may not lead to positive customer perceptions. The study recommends that transition not be drastic, that focus be on user-friendliness of the portals, that there be increased use of interactive technologies such as chatbots to increase responsiveness as well as a provision of people to engage with when there is need for escalation of issues aiding service recovery. / XL2019

Health motivation is found to be a significant driver of local foods purchase (Maples et al., 2013; Onozaka, Nurse, and McFadden, 2010), yet it remains unclear what specific health aspects determine consumer purchase decisions. We study the specific health factors focusing on six particular diseases: cancer, heart disease, diabetes, obesity, back/joint pain and Alzheimer’s/dementia to find out whether a relationship exists between disease incidences and consumer decisions to buy local foods. We examine two separate decisions of whether and how frequently southeastern consumers buy local foods in a two-step decision framework known as Double Hurdle model. Results indicate that cancer, diabetes, obesity and back/joint pain are statistically significant to purchase foods at farm stands. Findings might help local food sellers and product marketers in the southeastern United States to gain a deeper understanding of how consumers’ health background and health concerns affect their choice of local food outlets.