Service Quality and Black Customer Satisfaction - A Perspective on the United States Restaurant Industry

This paper examines the issue of racial discrimination of Black United States (U.S.) restaurant patrons from a service quality and customer satisfaction perspective. In spite of the progress the industry has made in recent years to alleviate this problem, many contemporary examples clearly demonstrate that racial discrimination is still of great concern. The articles stresses the importance of an ethical approach in human resource management-intensive and offers suggestions for reducing discriminatory practices in U.S. restaurant service delivery.

Placement for Profit: Menu Item Arrangement on Customer-Activated Computer Screens

Can profitable menu items be placed on a computer screen where they will be selected more readily than other items? The author examines whether printed menu theories and techniques can be applied, with the same results, to a computer menu screen

Customer Perception of Drive-Thru Service

The rapid growth of off-premise dining and, consequently, drive- thru service, presents the challenge of building customer loyalty in a highly competitive marketplace. In this study, customer perceptions of drive-thru service associated with quick service restaurants were examined. Results suggest that service time appears to differ among quick service restaurants, even those within the same chain. Employee courtesy was rated positively at all restaurants, as was food quality. The implications of these results for restaurateurs who offer drive-thru service are discussed.

Restaurant Customer Loyalty: A Qualitative Assessment of Niche Brands

Using the Loyalty Triangle framework developed by Lewis and Shoemaker (1999) and focus group methodology, the study examined how a niche brand restaurant best achieved long-term loyalty. Results indicate that customers are loyal to a niche brand because of the unique characteristics inherent to the brand. Customers have higher perceptions of such qualities as the presentation of service, consistency of product, and the benefits offered by the loyalty program than characteristics that are shared across all brands. Niche brand restaurants can be more effective in developing these qualities to promote customer loyalty.

A Customer's Expectation and Perception of Hotel Service Quality in Cyprus

In recent years, hotels in Cyprus have encountered difficult economic times due to increasing customer demands and strong internal industry development competition. The hospitality industry’s main concern globally is to serve its customer S needs and desires, most of which are addressed through personal services. Hence, the hotel businesses that are able to provide quality services to its ever-demanding customers in a warm and efficient manner are those businesses which will be more likely to obtain a long term competitive advantage over their rivals. Ironically, the quality of services frequently cannot fully appreciated until something goes wrong, and then, the poor quality of services can have long lasting lingering effects on the customer base and, hence, often is translated into a loss of business. Nevertheless, since the issue of delivery of hospitality services always involves people, this issue must center around the management of the human resource factor, and in particular, on the way which interacts with itself and with guests, as service encounters. In the eyes of guests, hospitality businesses will be viewed successful or failure, depending on [he cumulative impact of the service encounters they have experienced on a personal level. Finally, since hotels are offering intangible and perishable personal service encounters, managing these services must be a paramount concern of any hotel business. As a preliminary exercise, visualize when you have last visited a hotel, or a restaurant, and then, ask yourself these questions: What did you feel about the quality of the experience? Was it a memorable one, which you would recommend it to others, or there were certain things, which could have made the difference? Thus, the way personalized services are provided can make the deference in attracting arid retaining long-term customers

A Comparative Study of Customer Perceptions Regarding Green Restaurant Practices: Fast Food vs. Upscale Casual

The current exploratory study was designed to determine the impact that green restaurant practices may have on intention to visit a restaurant and willingness to pay more because of those green practices. The study analyzed a convenience sample of 260 surveys from customers in fast food restaurants and 501 surveys from customers in upscale casual restaurants in the Midwestern United States (U.S.) in order to determine if there were differences in the perception of guests regarding these types of restaurants and their green practices. The findings showed that upscale casual restaurant customers believed they are knowledgeable at a higher level than the fast food restaurant customers about green restaurant practices, have a higher mean rating on the importance of environmental record and recycling in restaurants, and believed that restaurants should use local products when they can. In both groups of customers, there was a positive relationship between green practices utilized at home and customers’ willingness to pay more for green restaurant practices as well as their intention to visit the restaurant using green practices. Management implications are discussed.

Reaching an Underserved Wine Customer: Connecting with the African American Wine Consumer

Marketing strategies addressing underserved African American wine customers’ needs that also positively impact producers’ and retailers’ clientele was the impetus for this exploratory, qualitative paper. African Americans demonstrate a thirst to elevate their education about and be more involved in the wine industry as evidenced by the proliferation of African American wine-tasting groups designed to help educate and expose their membership to a variety of wines. Moreover, compared to the average adult, African-American wine drinkers are 241% more likely to have spent $20 or more on a bottle of store bought wine (Arbitron, 2005). Despite African Americans’ representation as one of the fastest growing ethnic minority segments in the U.S., wine industry strategies don't appear to connect with this market segment. Like Alice in Wonderland, we characterize this phenomenon by suggesting this market segment is ‘peering through the looking glass’. Three focus groups were conducted to specify possible targeted media strategies as well as to identify attitudes and opinions that influence this segment's wine purchasing and consumption behaviors. Industry strategies were suggested that would appear to benefit producers, retailers, and this customer segment. The results of the research will be used to inform a quantitative instrument in order to generalize findings beyond the context of the exploratory setting.

Statistical dialog management for health interventions

Research endeavors on spoken dialogue systems in the 1990s and 2000s have led to the deployment of commercial spoken dialogue systems (SDS) in microdomains such as customer service automation, reservation/booking and question answering systems. Recent research in SDS has been focused on the development of applications in different domains (e.g. virtual counseling, personal coaches, social companions) which requires more sophistication than the previous generation of commercial SDS. The focus of this research project is the delivery of behavior change interventions based on the brief intervention counseling style via spoken dialogue systems. ^ Brief interventions (BI) are evidence-based, short, well structured, one-on-one counseling sessions. Many challenges are involved in delivering BIs to people in need, such as finding the time to administer them in busy doctors' offices, obtaining the extra training that helps staff become comfortable providing these interventions, and managing the cost of delivering the interventions. Fortunately, recent developments in spoken dialogue systems make the development of systems that can deliver brief interventions possible. ^ The overall objective of this research is to develop a data-driven, adaptable dialogue system for brief interventions for problematic drinking behavior, based on reinforcement learning methods. The implications of this research project includes, but are not limited to, assessing the feasibility of delivering structured brief health interventions with a data-driven spoken dialogue system. Furthermore, while the experimental system focuses on harmful alcohol drinking as a target behavior in this project, the produced knowledge and experience may also lead to implementation of similarly structured health interventions and assessments other than the alcohol domain (e.g. obesity, drug use, lack of exercise), using statistical machine learning approaches. ^ In addition to designing a dialog system, the semantic and emotional meanings of user utterances have high impact on interaction. To perform domain specific reasoning and recognize concepts in user utterances, a named-entity recognizer and an ontology are designed and evaluated. To understand affective information conveyed through text, lexicons and sentiment analysis module are developed and tested.^

Customer Satisfaction and Behavioral Intentions: The Case of Aruba-- Small Island Nation

Tourism studies related to small island destinations have become a research stream amongst many academics in recent years. The current study investigates tourist satisfaction related to a tour operator on the island of Aruba that specializes in jeep and bus tours. As there is an increased expenditure pattern for these types of activities, companies are looking for ways to improve customer satisfaction and behavioral intentions. Results indicate that tourists are generally satisfied with the tour company; however a difference in satisfaction ratings was obtained for respondents 61 years old or above. Four factors were extracted from tourists’ satisfaction attributes and three of these factors, including the overall tour value, tour guide, and sound systems used during these tours, were found to be strong predictors of behavioral intentions measured by the likelihood to rebook and the likelihood to recommend the tour company to family and friends. Operational and marketing strategies were suggested based on the findings of the study.

Division of Research Annual Customer Survey

Customer survey results for 2012-2013.

Research on the influence of behavioral forces that motivate trader behavior and sentiment- a prospect theory exegesis

This study focuses on empirical investigations and seeks implications by utilizing three different methodologies to test various aspects of trader behavior. The first methodology utilizes Prospect Theory to determine trader behavior during periods of extreme wealth contracting periods. Secondly, a threshold model to examine the sentiment variable is formulated and thirdly a study is made of the contagion effect and trader behavior. The connection between consumers' sense of financial well-being or sentiment and stock market performance has been studied at length. However, without data on actual versus experimental performance, implications based on this relationship are meaningless. The empirical agenda included examining a proprietary file of daily trader activities over a five-year period. Overall, during periods of extreme wealth altering conditions, traders "satisfice" rather than choose the "best" alternative. A trader's degree of loss aversion depends on his/her prior investment performance. A model that explains the behavior of traders during periods of turmoil is developed. Prospect Theory and the data file influenced the design of the model. Additional research included testing a model that permitted the data to signal the crisis through a threshold model. The third empirical study sought to investigate the existence of contagion caused by declining global wealth effects using evidence from the mining industry in Canada. Contagion, where a financial crisis begins locally and subsequently spreads elsewhere, has been studied in terms of correlations among similar regions. The results provide support for Prospect Theory in two out of the three empirical studies. The dissertation emphasizes the need for specifying precise, testable models of investors' expectations by providing tools to identify paradoxical behavior patterns. True enhancements in this field must include empirical research utilizing reliable data sources to mitigate data mining problems and allow researchers to distinguish between expectations-based and risk-based explanations of behavior. Through this type of research, it may be possible to systematically exploit "irrational" market behavior.

Text analytics of social media: Sentiment analysis, event detection and summarization

In the last decade, large numbers of social media services have emerged and been widely used in people's daily life as important information sharing and acquisition tools. With a substantial amount of user-contributed text data on social media, it becomes a necessity to develop methods and tools for text analysis for this emerging data, in order to better utilize it to deliver meaningful information to users. ^ Previous work on text analytics in last several decades is mainly focused on traditional types of text like emails, news and academic literatures, and several critical issues to text data on social media have not been well explored: 1) how to detect sentiment from text on social media; 2) how to make use of social media's real-time nature; 3) how to address information overload for flexible information needs. ^ In this dissertation, we focus on these three problems. First, to detect sentiment of text on social media, we propose a non-negative matrix tri-factorization (tri-NMF) based dual active supervision method to minimize human labeling efforts for the new type of data. Second, to make use of social media's real-time nature, we propose approaches to detect events from text streams on social media. Third, to address information overload for flexible information needs, we propose two summarization framework, dominating set based summarization framework and learning-to-rank based summarization framework. The dominating set based summarization framework can be applied for different types of summarization problems, while the learning-to-rank based summarization framework helps utilize the existing training data to guild the new summarization tasks. In addition, we integrate these techneques in an application study of event summarization for sports games as an example of how to better utilize social media data. ^

Text Analytics of Social Media: Sentiment Analysis, Event Detection and Summarization

In the last decade, large numbers of social media services have emerged and been widely used in people's daily life as important information sharing and acquisition tools. With a substantial amount of user-contributed text data on social media, it becomes a necessity to develop methods and tools for text analysis for this emerging data, in order to better utilize it to deliver meaningful information to users. Previous work on text analytics in last several decades is mainly focused on traditional types of text like emails, news and academic literatures, and several critical issues to text data on social media have not been well explored: 1) how to detect sentiment from text on social media; 2) how to make use of social media's real-time nature; 3) how to address information overload for flexible information needs. In this dissertation, we focus on these three problems. First, to detect sentiment of text on social media, we propose a non-negative matrix tri-factorization (tri-NMF) based dual active supervision method to minimize human labeling efforts for the new type of data. Second, to make use of social media's real-time nature, we propose approaches to detect events from text streams on social media. Third, to address information overload for flexible information needs, we propose two summarization framework, dominating set based summarization framework and learning-to-rank based summarization framework. The dominating set based summarization framework can be applied for different types of summarization problems, while the learning-to-rank based summarization framework helps utilize the existing training data to guild the new summarization tasks. In addition, we integrate these techneques in an application study of event summarization for sports games as an example of how to better utilize social media data.

Sentiment-Topic Modelling in Text Mining

Peer reviewed

Sentiment-Topic Modelling in Text Mining

Peer reviewed