Florida Turnpike Service - Retail Store Project

This report summarizes the findings of the Florida Turnpike Service Plaza retail Store survey, which was conducted October/2010- February 2011. Customers were surveyed in five service plazas, specifically Turkey Lake, Port St. Lucie/Ft. Pierce, West Palm Beach, Canoe Creek, and Fort Drum. A focused group research was also conducted by the Rosen College Faculty. Rosen\u27s College- University of Central Florida- graduate and undergraduate students collected data using intercept method of data collection. Customers inside the 5 plazas were randomly selected to participate in the study. A total of 419 surveys were collected across the 5 plazas, after removing the outliers and the incomplete surveys 415 surveys were used for data analysis

Comparative Assessment of Structural Equation Modeling and Multiple Regression Research Methodologies: E-commerce Context

Structural equation modeling (SEM) is a powerful statistical technique that establishes measurement models and structural models. On the other hand, multiple regression (MR) is considered a sophisticated and well-developed modeling approach to data analysis with a history of more than 100 years. This paper empirically compares SEM and MR by testing a model of commitment in a B-to-C e-commerce travel context, shedding light on applications of these two popular methods in tourism research. The findings indicate that only two significant relationships are justified by MR. In comparison, SEM results reveal more statistically significant relationships after the “best-fitting” measurement model with model D being the “best-fitting” model. The findings support some key empirical limitations of MR as a widely used statistical technique in the tourism research

Comparative Assessment of Structural Equation Modeling and Multiple Regression Research Methodologies: E-commerce Context

Structural equation modeling (SEM) is a powerful statistical technique that establishes measurement models and structural models. On the other hand, multiple regression (MR) is considered a sophisticated and well-developed modeling approach to data analysis with a history of more than 100 years. This paper empirically compares SEM and MR by testing a model of commitment in a B-to-C e-commerce travel context, shedding light on applications of these two popular methods in tourism research. The findings indicate that only two significant relationships are justified by MR. In comparison, SEM results reveal more statistically significant relationships after the “best-fitting” measurement model with model D being the “best-fitting” model. The findings support some key empirical limitations of MR as a widely used statistical technique in the tourism research

Building A Model Of Commitment For Generation Y: An Empirical Study On E-Travel Retailers

The primary goal of this study was to develop a theory-based model of relationship commitment in an online travel context. Leaning on the foundations of marketing literature and the two theories of relationship commitment (organizational commitment theory, and investment model), this study develops a conceptual framework that explains how Generation Y develops commitment to a travel web vendor. Affective commitment and calculative commitment were found to vary in terms of their impart on word-of-mouth communications. The results showed that the affective commitment was most effective for developing and maintaining long-term relationships with Generation Y. In addition, the study suggested that investment size was positively related both to affective commitment and calculative commitment. Finally, satisfaction was found positively related to affective commitment and negatively related to calculative commitment. The theoretical and managerial implications were discussed as well. © 2010 Elsevier Ltd. All rights reserved

The Impact Of Wi-Fi Service In Restaurants On Customers\u27 Likelihood Of Return To A Restaurant

The purpose of this study is to explore the impact of wireless internet (Wi-Fi) service on customers\u27 likelihood of returning to a restaurant. Data was collected via an online structured questionnaire from randomly chosen 1000 restaurant customers in the U.S. The results showed that (1) Wi-Fi access has become an important amenity in restaurants and cafes in the United States; (2) Technology-savvy customers prefer restaurants or cafes with Wi-Fi service; (3) Customers prefer free Wi-Fi in restaurants over paid models; and (4) A multiple regression model supported that Wi-Fi service availability, Wi-Fi service quality, price of Wi-Fi service, perceived risk of using Wi-Fi service, and perceived value of Wi-Fi are predictors of likelihood of a customer\u27s return to a restaurant. The research findings highlight the importance of internet amenities in restaurants. It shows that providing Wi-Fi service in a restaurant is a predictor of the likelihood of customers returning to a restaurant. © 2012 Copyright Taylor and Francis Group, LLC

Effect of Price Discount Frames and Levels on Consumers\u27 Perceptions in Low‐End Service Industries

Purpose– The purpose of this study is to investigate the effects of price discount frames and price discount levels on consumer perceptions about the quality of the service product, the value of the discount, their purchase intentions and their willingness to spread the word of mouth about the discount savings across different types of services. Design/methodology/approach The study uses an experiment design method using three interesting variables: discount format, discount level and service industry type. The experiment included four different types of low‐end price service levels: restaurants, hotels, mailing services, and retail services. Findings– The findings indicate that price discount frames and discount levels do affect consumers\u27 perceptions on the value of the discount, the quality of the service, their intention to purchase and their willingness to engage in WOM advertising. Practical implicationsThe practical implication for service firms that want to use price discount promotions to encourage sales and increase revenue is that they should carefully consider the price range and the value or quality of image they intend to signal when using these different price discount frames and the service they are selling to determine the discount level to use. Originality/value– This paper is valuable to low‐end service marketers that seek to use price discount promotions to encourage sales and increase revenue

Effect of Price Discount Frames and Levels on Consumers\u27 Perceptions in Low‐End Service Industries

Purpose– The purpose of this study is to investigate the effects of price discount frames and price discount levels on consumer perceptions about the quality of the service product, the value of the discount, their purchase intentions and their willingness to spread the word of mouth about the discount savings across different types of services. Design/methodology/approach The study uses an experiment design method using three interesting variables: discount format, discount level and service industry type. The experiment included four different types of low‐end price service levels: restaurants, hotels, mailing services, and retail services. Findings– The findings indicate that price discount frames and discount levels do affect consumers\u27 perceptions on the value of the discount, the quality of the service, their intention to purchase and their willingness to engage in WOM advertising. Practical implicationsThe practical implication for service firms that want to use price discount promotions to encourage sales and increase revenue is that they should carefully consider the price range and the value or quality of image they intend to signal when using these different price discount frames and the service they are selling to determine the discount level to use. Originality/value– This paper is valuable to low‐end service marketers that seek to use price discount promotions to encourage sales and increase revenue

Measuring the Effects of Tourists\u27 Relative Willingness to Spend and Third-degree Price Discrimination on Inbound Tourism Expenditure Differentials

Tourism expenditures are determined by a set of antecedents that reflect tourists\u27 willingness and ability to spend, and de facto incremental monetary outlays at which willingness and ability is transformed into total expenditures. Based on the neoclassical theoretical argument of utility-constrained expenditure minimization, we extend the current literature by applying a sustainability-based segmentation criterion, namely, the Legatum Prosperity IndexTM to the decomposition of a total expenditure differential into tourists\u27 relative willingness to spend and an upper bound of third-degree price discrimination, using mean-level and conditional quantile estimates. Our results indicate that understanding the price–quantity composition of international inbound tourism expenditure differentials assists agents in the tourism industry in their quest for profit maximization