The Relationship Between Leisure Traveler's hotel Attribute Satisfaction and Overall Satisfaction

Manystudies have been conducted about hotel attributesrelated tothehotel choice decision as a part ofacustomer’s pre- purchase behavior(Dolnicar&Otter, 2003). Althoughit iscritical for hotel managerstounderstand post-trip behavior because such behaviorsmaydirectlyinfluence their futurebehavior, therearefew researchstudieswhich examine hotel attributesrelated to acustomer’spost-trip behavior.This studyteststhe relationship between leisure traveler’shotel attribute satisfaction and overall satisfaction in the post-trip behaviorperspectiveina hotel setting andexaminestherelative impactofhotel attributesatisfaction in influencing overall satisfaction. Multiple regressionwas used totestthe relationship and hotel attribute satisfaction isan important antecedent tooverall satisfaction. Theoretical and practical implications ofthe studyare discussed.

A study to identify the motivation compelling the business traveler to choose a specific airline in the Miami to Atlanta market and to develop a marketing strategy

The purpose of this study was to determine if the business traveler's behavior is influenced by brand loyalty. This brand loyalty, which became evident through the use of a survey, was then to be thoroughly evaluated. In order for this information to be best understood and utilized as the basis of future marketing strategies, much research was undertaken and its significance explained in relation to the airline industry as it exists at present. The results and conclusions of this study indicate that the airline industry is, for the most part, taking a successful approach in attracting business travelers. These travelers' business is highly valued due to the frequency with which they pay full-fare rates. The airlines view business travelers as a potential for great profit and their actions are in line with these philosophies.

Factors affecting emergency department length of stay of patients admitted to telemetry and critical care units

The purpose of this study was to determine the emergency department (ED) length of stay (LOS) of patients admitted to inpatient telemetry and critical care units and to identify the factors that contribute to a prolonged ED LOS. It also examined whether there was a difference in ED LOS between clients evaluated by an ED physician, an Advanced Registered Nurse Practitioner (ARNP) or a Physician's Assistant (PA).^ A data collection tool was devised and used to record data obtained by retrospectively reviewing 110 charts of patients from this sample. The mean ED LOS was 286.75 minutes. Multiple factors were recorded as affecting the ED LOS of this sample, including: age, diagnosis, consultations, multiple radiographs, pending admission orders, nurse unable to call report/busy, relatives at bedside, observation or stabilization necessary, bed not ready and infusion in progress. No significant difference in ED LOS was noted between subjects initially evaluated by a physician, an ARNP or a PA. ^

Development of prediction models for freeway incident durations using data mining techniques

The nation's freeway systems are becoming increasingly congested. A major contribution to traffic congestion on freeways is due to traffic incidents. Traffic incidents are non-recurring events such as accidents or stranded vehicles that cause a temporary roadway capacity reduction, and they can account for as much as 60 percent of all traffic congestion on freeways. One major freeway incident management strategy involves diverting traffic to avoid incident locations by relaying timely information through Intelligent Transportation Systems (ITS) devices such as dynamic message signs or real-time traveler information systems. The decision to divert traffic depends foremost on the expected duration of an incident, which is difficult to predict. In addition, the duration of an incident is affected by many contributing factors. Determining and understanding these factors can help the process of identifying and developing better strategies to reduce incident durations and alleviate traffic congestion. A number of research studies have attempted to develop models to predict incident durations, yet with limited success. ^ This dissertation research attempts to improve on this previous effort by applying data mining techniques to a comprehensive incident database maintained by the District 4 ITS Office of the Florida Department of Transportation (FDOT). Two categories of incident duration prediction models were developed: "offline" models designed for use in the performance evaluation of incident management programs, and "online" models for real-time prediction of incident duration to aid in the decision making of traffic diversion in the event of an ongoing incident. Multiple data mining analysis techniques were applied and evaluated in the research. The multiple linear regression analysis and decision tree based method were applied to develop the offline models, and the rule-based method and a tree algorithm called M5P were used to develop the online models. ^ The results show that the models in general can achieve high prediction accuracy within acceptable time intervals of the actual durations. The research also identifies some new contributing factors that have not been examined in past studies. As part of the research effort, software code was developed to implement the models in the existing software system of District 4 FDOT for actual applications. ^

Freeway travel time estimation and prediction using dynamic neural networks

Providing transportation system operators and travelers with accurate travel time information allows them to make more informed decisions, yielding benefits for individual travelers and for the entire transportation system. Most existing advanced traveler information systems (ATIS) and advanced traffic management systems (ATMS) use instantaneous travel time values estimated based on the current measurements, assuming that traffic conditions remain constant in the near future. For more effective applications, it has been proposed that ATIS and ATMS should use travel times predicted for short-term future conditions rather than instantaneous travel times measured or estimated for current conditions. ^ This dissertation research investigates short-term freeway travel time prediction using Dynamic Neural Networks (DNN) based on traffic detector data collected by radar traffic detectors installed along a freeway corridor. DNN comprises a class of neural networks that are particularly suitable for predicting variables like travel time, but has not been adequately investigated for this purpose. Before this investigation, it was necessary to identifying methods for data imputation to account for missing data usually encountered when collecting data using traffic detectors. It was also necessary to identify a method to estimate the travel time on the freeway corridor based on data collected using point traffic detectors. A new travel time estimation method referred to as the Piecewise Constant Acceleration Based (PCAB) method was developed and compared with other methods reported in the literatures. The results show that one of the simple travel time estimation methods (the average speed method) can work as well as the PCAB method, and both of them out-perform other methods. This study also compared the travel time prediction performance of three different DNN topologies with different memory setups. The results show that one DNN topology (the time-delay neural networks) out-performs the other two DNN topologies for the investigated prediction problem. This topology also performs slightly better than the simple multilayer perceptron (MLP) neural network topology that has been used in a number of previous studies for travel time prediction.^

Hybrid approaches to estimating freeway travel times using point traffic detector data

The accurate and reliable estimation of travel time based on point detector data is needed to support Intelligent Transportation System (ITS) applications. It has been found that the quality of travel time estimation is a function of the method used in the estimation and varies for different traffic conditions. In this study, two hybrid on-line travel time estimation models, and their corresponding off-line methods, were developed to achieve better estimation performance under various traffic conditions, including recurrent congestion and incidents. The first model combines the Mid-Point method, which is a speed-based method, with a traffic flow-based method. The second model integrates two speed-based methods: the Mid-Point method and the Minimum Speed method. In both models, the switch between travel time estimation methods is based on the congestion level and queue status automatically identified by clustering analysis. During incident conditions with rapidly changing queue lengths, shock wave analysis-based refinements are applied for on-line estimation to capture the fast queue propagation and recovery. Travel time estimates obtained from existing speed-based methods, traffic flow-based methods, and the models developed were tested using both simulation and real-world data. The results indicate that all tested methods performed at an acceptable level during periods of low congestion. However, their performances vary with an increase in congestion. Comparisons with other estimation methods also show that the developed hybrid models perform well in all cases. Further comparisons between the on-line and off-line travel time estimation methods reveal that off-line methods perform significantly better only during fast-changing congested conditions, such as during incidents. The impacts of major influential factors on the performance of travel time estimation, including data preprocessing procedures, detector errors, detector spacing, frequency of travel time updates to traveler information devices, travel time link length, and posted travel time range, were investigated in this study. The results show that these factors have more significant impacts on the estimation accuracy and reliability under congested conditions than during uncongested conditions. For the incident conditions, the estimation quality improves with the use of a short rolling period for data smoothing, more accurate detector data, and frequent travel time updates.

A methodology to estimate time varying user responses to travel time and travel time reliability in a road pricing environment

Road pricing has emerged as an effective means of managing road traffic demand while simultaneously raising additional revenues to transportation agencies. Research on the factors that govern travel decisions has shown that user preferences may be a function of the demographic characteristics of the individuals and the perceived trip attributes. However, it is not clear what are the actual trip attributes considered in the travel decision- making process, how these attributes are perceived by travelers, and how the set of trip attributes change as a function of the time of the day or from day to day. In this study, operational Intelligent Transportation Systems (ITS) archives are mined and the aggregated preferences for a priced system are extracted at a fine time aggregation level for an extended number of days. The resulting information is related to corresponding time-varying trip attributes such as travel time, travel time reliability, charged toll, and other parameters. The time-varying user preferences and trip attributes are linked together by means of a binary choice model (Logit) with a linear utility function on trip attributes. The trip attributes weights in the utility function are then dynamically estimated for each time of day by means of an adaptive, limited-memory discrete Kalman filter (ALMF). The relationship between traveler choices and travel time is assessed using different rules to capture the logic that best represents the traveler perception and the effect of the real-time information on the observed preferences. The impact of travel time reliability on traveler choices is investigated considering its multiple definitions. It can be concluded based on the results that using the ALMF algorithm allows a robust estimation of time-varying weights in the utility function at fine time aggregation levels. The high correlations among the trip attributes severely constrain the simultaneous estimation of their weights in the utility function. Despite the data limitations, it is found that, the ALMF algorithm can provide stable estimates of the choice parameters for some periods of the day. Finally, it is found that the daily variation of the user sensitivities for different periods of the day resembles a well-defined normal distribution.

The Relationship between Leisure Traveler’s Hotel Attribute Satisfaction and Overall Satisfaction

Manystudies have been conducted about hotel attributesrelated tothehotel choice decision as a part ofacustomer’s pre- purchase behavior(Dolnicar&Otter, 2003). Althoughit iscritical for hotel managerstounderstand post-trip behavior because such behaviorsmaydirectlyinfluence their futurebehavior, therearefew researchstudieswhich examine hotel attributesrelated to acustomer’spost-trip behavior.This studyteststhe relationship between leisure traveler’shotel attribute satisfaction and overall satisfaction in the post-trip behaviorperspectiveina hotel setting andexaminestherelative impactofhotel attributesatisfaction in influencing overall satisfaction. Multiple regressionwas used totestthe relationship and hotel attribute satisfaction isan important antecedent tooverall satisfaction. Theoretical and practical implications ofthe studyare discussed.

Travel Marketing: Industry Relationships and Benefits

In the discussion - Travel Marketing: Industry Relationships and Benefits - by Andrew Vladimir, Visiting Assistant Professor, School of Hospitality Management at Florida International University, the author initially states: “A symbiotic relationship exists among the various segments of the travel and tourism industry. The author has solicited the thinking of 37experts and leaders in the field in a book dealing with these relationships and how they can be developed to benefit the industry. This article provides some salient points from those contributors.” This article could be considered a primer on networking for the hospitality industry. It has everything to do with marketing and the relationships between varied systems in the field of travel and tourism. Vladimir points to instances of success and failure in marketing for the industry at large. And there are points of view from thirty-seven contributing sources here. “Miami Beach remains a fitting example of a leisure product that has been unable to get its act together,” Vladimir shares a view. “There are some first class hotels, a few good restaurants, alluring beaches, and a splendid convention center, but there is no synergism between them, no real affinity, and so while visitors admire the Fontainebleau Hilton and enjoy the food at Joe's Stone Crabs, the reputation of Miami Beach as a resort remains sullied,” the author makes a point. In describing cohesiveness between exclusive systems, Vladimir says, “If each system can get a better understanding of the inner workings of neighboring related systems, each will ultimately be more successful in achieving its goals.” The article is suggesting that exclusive systems aren’t really exclusive at all; or at least they shouldn’t be. In a word – competition – drives the market, and in order for a property to stay afloat, aggressive marketing integrated with all attendant resources is crucial. “Tisch [Preston Robert Tisch, currently – at the time of this writing - the Postmaster General of the United States and formerly president of Lowe’s Hotels and the New York Visitors and Convention Bureau], in talking about the need for aggressive marketing says: “Never...ever...take anything for granted. Never...not for a moment...think that any product or any place will survive strictly on its own merits.” Vladimir not only sources several knowledgeable representatives in the field of hospitality and tourism, but he also links elements as disparate as real estate, car rental, cruise and airlines, travel agencies and traveler profiles to illustrate his points on marketing integration. In closing, Vladimir quotes the Honorable Donna Tuttle, Undersecretary of Commerce for Travel and Tourism, “Uniting the components of this industry in an effective marketing coalition that can compete on an equal footing with often publicly-owned foreign tourism conglomerates and multi-national consortia must be a high priority as the United States struggles to maintain and expand its share of a rapidly changing global market.”

Seabourn Cruise Line: A Case Study in Achieving Quality

Just about everyone who ranks cruise lines puts Seabourn first on the list. The readers of Conde Nast Traveler ranked it the world's top cruise line for three consecutive years and fifth in their survey of the top 100 overall travel experiences. Of special interest to hospitality professionals is Seabourn's 98.5 percent score for service- higher than any other vacation experience in the world.

A profile of travelers who are willing to stay in environmentally friendly hotel

The purpose of this study is to describe travelers that have indicated they are willing to stay in green hotel in order to better understand the market segment. There is very little knowledge about these types of travelers, thus making it difficult for hoteliers to know how to create marketing campaigns that target them. Data were collected via an online survey company. Behavior characteristics provided a more distinguishing profile of the traveler than did demographics or psychographics. Most travelers were willing to pay the same amount for a green hotel as a traditional hotel. Implications, future research, and limitations are discussed.

World-Class Service

In the discussion - World-Class Service - by W. Gerald Glover, Associate Professor, Restaurant, Hotel and Resort Management at Appalachian State University and Germaine W. Shames, Hilton International, New York, Glover and Shames initially state: “Providing world-class service to today's traveler may be the key for hospitality managers in the current competitive market. Although an ideal, this type of service provides a mandate for culturally aware managers. The authors provide insight into several areas of cultures in collision.” Up to the time this essay is written, the authors point to a less-than-ideal level of service as being the standard in the hospitality industry and experience. “Let's face it - if we're ever to resurrect service, it will not be by going back to anything,” Glover and Shames exclaim. “Whatever it was we did back then has contributed to the dilemma in which we find ourselves today, handicapped by a reactive service culture in an age that calls for adaptiveness and global strategies,” the authors fortify that thought. In amplifying the concept of world-class service Glover and Shames elaborate: “World-class service is an ideal. Proactive and adaptive, world-class service feels equally right to the North American dignitary occupying the Presidential Suite, and the Japanese tourist staying in a standard room in the same hotel.” To bracket that model the authors offer: “At a minimum, it is service perceived by each customer as appropriate and adequate. At its best, it may also make the customer feel at home, among friends, or pampered. Finally, it is service as if culture matters,” Glover and Shames expand and capture the rule of world-class service. Glover and Shames consider the link between cultures and service an imperative one. They say it is a principle lost on most hospitality managers. “Most [managers] have received service management education in the people are people school that teaches us to disregard cultural differences and assume that everyone we manage or serve is pretty much like ourselves,” say Glover and Shames. “Is it any wonder that we persist in setting service standards, marketing services, and managing service staff not only as if culture didn't matter, but as if it didn't exist?!” To offer legitimacy to their effort Glover and Shames present the case of the Sun and Sea Hotel, a 500-room first class hotel located on the outskirts of the capital city of a small Caribbean island nation. It is a bit difficult to tell whether this is a dramatization or a reality. It does, however, serve to illustrate their point in regard to management’s cognizance, or lack thereof, of culture when it comes to cordial service and guest satisfaction. Even more apropos is the tale of the Palace Hotel, “…one of the grande dames of hospitality constructed in the boom years of the 1920s in a mid-sized Midwestern city in the United States.” The authors relate what transpired during its takeover in mid-1980 by a U.S.-based international hotel corporation. The story makes for an interesting and informative case study.

Effect of Hydrologic Restoration on the Habitat of The Cape Sable Seaside Sparrow, Annual Report of 2002-2003

After developing field sampling protocols and making a series of consultations with investigators involved in research in CSSS habitat, we determined that vegetationhydrology interactions within this landscape are best sampled at a combination of scales. At the finer scale, we decided to sample at 100 m intervals along transects that cross the range of habitats present, and at the coarser scale, to conduct an extensive survey of vegetation at sites of known sparrow density dispersed throughout the range of the CSSS. We initiated sampling in the first week of January 2003 and continued it through the last week of May. During this period, we established 6 transects, one in each CSSS subpopulation, completed topographic survey along the Transects A, C, D, and F, and sampled herb and shrub stratum vegetation, soil depth and periphyton along Transects A, and at 179 census points. We also conducted topographic surveys and completed vegetation and soil depth sampling along two of five transects used by ENP researchers for monitoring long-term vegetation change in Taylor Slough. We analyzed the data by summarizing the compositional and structural measures and by using cluster analysis, ordination, weighted averaging regression, and weighted averaging calibration. The mean elevation of transects decreased from north to south, and Transect F had greater variation than other transects. We identified eight vegetation assemblages that can be grouped into two broad categories, ‘wet prairie’ and ‘marsh’. In the 2003 survey, wet prairies were most dominant in the northeastern sub-populations, and had shorter inferred-hydroperiod, higher species richness and shallower soils than marshes, which were common in Subpopulations A, D, and the southernmost regions of Sub-population B. Most of the sites at which birds were observed during 2001 or 2002 had an inferred-hydroperiod of 120-150 days, while no birds were observed at sites with an inferred-hydroperiod less than 120 days or more than 300 days. Management-induced water level changes in Taylor Slought during the 1980’s and 1990’s appeared to elicit parallel changes in vegetation. The results described in detail in the following pages serve as a basis for evaluating and modifying, if necessary, the sampling design and analytical techniques to be used in the next three years of the project.

Freeway Travel Time Estimation and Prediction Using Dynamic Neural Networks

Providing transportation system operators and travelers with accurate travel time information allows them to make more informed decisions, yielding benefits for individual travelers and for the entire transportation system. Most existing advanced traveler information systems (ATIS) and advanced traffic management systems (ATMS) use instantaneous travel time values estimated based on the current measurements, assuming that traffic conditions remain constant in the near future. For more effective applications, it has been proposed that ATIS and ATMS should use travel times predicted for short-term future conditions rather than instantaneous travel times measured or estimated for current conditions. This dissertation research investigates short-term freeway travel time prediction using Dynamic Neural Networks (DNN) based on traffic detector data collected by radar traffic detectors installed along a freeway corridor. DNN comprises a class of neural networks that are particularly suitable for predicting variables like travel time, but has not been adequately investigated for this purpose. Before this investigation, it was necessary to identifying methods for data imputation to account for missing data usually encountered when collecting data using traffic detectors. It was also necessary to identify a method to estimate the travel time on the freeway corridor based on data collected using point traffic detectors. A new travel time estimation method referred to as the Piecewise Constant Acceleration Based (PCAB) method was developed and compared with other methods reported in the literatures. The results show that one of the simple travel time estimation methods (the average speed method) can work as well as the PCAB method, and both of them out-perform other methods. This study also compared the travel time prediction performance of three different DNN topologies with different memory setups. The results show that one DNN topology (the time-delay neural networks) out-performs the other two DNN topologies for the investigated prediction problem. This topology also performs slightly better than the simple multilayer perceptron (MLP) neural network topology that has been used in a number of previous studies for travel time prediction.

A study to determine whether the needs of the physically handicapped are being met by the hotels in the city of Miami Beach, Florida

The purpose of this study was to determine whether the needs of the physically handicapped traveler are being met by the hotels in the City of Miami Beach, Florida. A sample was drawn from the hotel population. Mail questionnaires and personal interviews were used as the methods for collecting the data from the sample. The data was compiled and a hotel mean was computed. A mean was also calculated from the standards recommended by the American National Standards Institute to the American Hotel and Motel Association. The statistical test, The Significance of Difference Between Two Means, was used to test the hypothesis. A significance of difference was found and the hypothesis: The hotels in the City of Miami Beach, Florida, are not meeting the needs of the physically handicapped traveler, was accepted.