Retail centers for community : addressing both pedestrian and car traffic

The purpose of this thesis was to redesign a commercial center in Miami, Florida in a manner that incorporates the needs of pedestrians as well as the automobile. In my research, I studied projects that had been successful at integrating cars in retail design. I applied the strategies learned from this research to the design of a center that creates a positive interaction of pedestrian and car traffic, addressing the needs of the surrounding community. I designed a master plan that includes a mix of residential, retail, commercial and parking space. The parking is designed so that the retail center is not dominated by surface parking. Rather, the automobile is introduced into the different layers of the proposed buildings. The design focused on connecting pedestrian plazas and parking areas beneath them through the introduction of light and greenery. The findings show how a shopping center might transform the area around it by including spaces for residential, civic, cultural and social functions, as well as for the automotive infrastructure that make those functions possible.

Who and Why? Demographic and psychographic differences between consumers who have altered their shopping behaviour during a recession and those who have not

Research suggests that people differ in terms of changing their shopping behaviour during a recession. This paper reports on a preliminary descriptive study assessing what influences those consumers who have altered their shopping behaviour during such times. Driving the alteration of shopping behaviour were both demographic (age, gender, education, and nationality) and psychographic variables (attitudes, and head vs. heart decision making). Overall, the findings show that there are statistically significant differences between the two groups’ that marketers can address in their marketing strategies during the recession.

Including airport duty-free shopping in arriving passenger simulation and the opportunities this presents

Simulating passenger flows within airports is very important as it can provide an indication of queue lengths, bottlenecks, system capacity and overall level of service. To date, visual simulation tools such as agent based models have focused on processing formalities such as check-in, and not incorporate discretionary activities such as duty-free shopping. As airport retail contributes greatly to airport revenue generation, but also has potentially detrimental effects on facilitation efficiency benchmarks, this study developed a simplistic simulation model which captures common duty-free purchasing opportunities, as well as high-level behaviours of passengers. It is argued that such a model enables more realistic simulation of passenger facilitation, and provides a platform for simulating real-time revenue generation as well as more complex passenger behaviours within the airport. Simulations are conducted to verify the suitability of the model for inclusion in the international arrivals process for assessing passenger flow and infrastructure utilization.

An exploration of Online Shopping Cart Abandonment Syndrome – a matter of risk and reputation

ABSRACT. Despite the surge in online retail sales in recent years there still remains reluctance by consumers to complete the online shopping process. A number of authors have attributed consumers’ reluctance to purchase online to apparent barriers. However, such barriers as yet have not been fully examined within a theoretical context. This research explores the application of the perceived risk theoretical framework. Specifically, performance risk and the influence of perceived performance risk has on the phenomenon of Internet Abandoned Cart Syndrome (ACS) is evaluated. To explore this phenomenon, a number of extrinsic cues are identified as playing a major role in the performance evaluation process of online purchases. The results of this study suggest the extrinsic cues of brand, reputation, design and price have an overall impact on the performance evaluation process just prior to an online purchase. Varying these cues either positively or negatively had a strong impact on performance evaluation. Further, it was found that positive or negative reputation was heavily associated with shopping cart abandonment.

A stranger's touch : effects of accidental interpersonal touch on consumer evaluations and shopping time

This article examines an unexplored area of consumer research—the effect of accidental interpersonal touch (AIT) from a stranger on consumer evaluations and shopping times. The research presents a field experiment in a retail setting. This study shows that men and women who have been touched by another consumer when examining products report more negative brand evaluations, negative product beliefs, less willingness to pay, and spend less time in-store than their control (no-touch) counterparts. Our findings indicate that the AIT effect is especially negative for touch from a male stranger for both men (same-sex touch) and women (opposite-sex touch). Directions are provided for future study that highlight potential moderators and process explanations underlying the AIT effect.

Energy-efficient virtual machine placement in data centers by genetic algorithm

Server consolidation using virtualization technology has become an important technology to improve the energy efficiency of data centers. Virtual machine placement is the key in the server consolidation. In the past few years, many approaches to the virtual machine placement have been proposed. However, existing virtual machine placement approaches to the virtual machine placement problem consider the energy consumption by physical machines in a data center only, but do not consider the energy consumption in communication network in the data center. However, the energy consumption in the communication network in a data center is not trivial, and therefore should be considered in the virtual machine placement in order to make the data center more energy-efficient. In this paper, we propose a genetic algorithm for a new virtual machine placement problem that considers the energy consumption in both the servers and the communication network in the data center. Experimental results show that the genetic algorithm performs well when tackling test problems of different kinds, and scales up well when the problem size increases.

Toward a shopping typology of primary male grocery shoppers

Purpose – The purpose of this paper is to segment primary male grocery shoppers based on store and product attribute evaluations. A rich profile for each segment is developed. These developed contemporary shopper typologies are contrasted against earlier works. Design/methodology/approach – Data of 280 male grocery shoppers was attained by a survey questionnaire. Factor analysis, cluster analysis and ANOVA were employed to develop specific segments of male shoppers. Findings – Four distinct cohorts of male shoppers emerge from the data of eight constructs, measured by 46 items. One new shopper type, not found in earlier typology literature, emerged from this research. This shopper presented as young, well educated, at the commencement of their career and family lifecycle, attracted by a strong value offer and willingness to share the family food shopping responsibilities. Practical implications – Research outcomes encourage supermarket retailers to implement targeted marketing and rationalized operational strategies that deliver on attributes of importance. Originality/value – This research makes a contribution to segmentation literature and grocery retail practice in several ways. It presents the first retail typology of male supermarket shoppers, employing a cluster analysis technique. The research provides insights into the modern family food shopping behaviour of men, a channel in which men are now recognised as equal contributors. The research provides the basis for further gender comparative and cross-contextual studies.

Energy efficient virtual machine placement in data centers

Electricity cost has become a major expense for running data centers and server consolidation using virtualization technology has been used as an important technology to improve the energy efficiency of data centers. In this research, a genetic algorithm and a simulation-annealing algorithm are proposed for the static virtual machine placement problem that considers the energy consumption in both the servers and the communication network, and a trading algorithm is proposed for dynamic virtual machine placement. Experimental results have shown that the proposed methods are more energy efficient than existing solutions.

A hybrid genetic algorithm for the energy-efficient virtual machine placement problem in data centers

Server consolidation using virtualization technology has become an important technology to improve the energy efficiency of data centers. Virtual machine placement is the key in the server consolidation technology. In the past few years, many approaches to the virtual machine placement have been proposed. However, existing virtual machine placement approaches consider the energy consumption by physical machines only, but do not consider the energy consumption in communication network, in a data center. However, the energy consumption in the communication network in a data center is not trivial, and therefore should be considered in the virtual machine placement. In our preliminary research, we have proposed a genetic algorithm for a new virtual machine placement problem that considers the energy consumption in both physical machines and the communication network in a data center. Aiming at improving the performance and efficiency of the genetic algorithm, this paper presents a hybrid genetic algorithm for the energy-efficient virtual machine placement problem. Experimental results show that the hybrid genetic algorithm significantly outperforms the original genetic algorithm, and that the hybrid genetic algorithm is scalable.

An instrument to assess the obesogenic environment of child care centers

OBJECTIVES To describe protocol and interobserver agreements of an instrument to evaluate nutrition and physical activity environments at child care. METHODS Interobserver data were collected from 9 child care centers, through direct observation and document review (17 observer pairs). RESULTS Mean agreement between observer pairs was 87.26% and 79.29% for the observation and document review, respectively. Items with lower agreement were primarily staff behavior, counting across the day/week, and policy classifications. CONCLUSIONS Although some revisions are required, the interobserver agreement for the environment and policy assessment and observation (EPAO instrument) appears to be quite good for assessing the nutrition and physical activity environment of child care centers.