Effects of Management-Development Practices on Hospitality Management Graduates' Job Satisfaction and Intention to Stay

Companies have long recognized the importance of training and developing their managers to prepare them for their short- and long-term careers. Formal management-development programs and other less formal means of management development abound in the hospitality industry. Therefore, one may ask whether the entry-level managers for whom these programs are designed perceive them to be effective. The present study explores management-development practices, procedures, and techniques, and their effects on job satisfaction and organizational commitment

Recreational Foodservice management: A Delphi study of needed competencies

The purpose of this study was to identify the needed competencies of a Recreational Foodservice manager. A three round Delphi method of iteration was used. Delphi is a research method that utilizes iterating rounds to elicit the opinion of a panel of experts regarding a specific subject.^ A nominating committee of 22 industry leaders was consulted to establish a panel of 40 management experts, of which 35 (87.5%) completed all three rounds of the Delphi study.^ Round One of the study identified 17 specific job functions of a Recreational Foodservice manager. The researcher prepared an instrument detailing 60 competencies derived from an analysis of Round One results and distributed it as a Round Two instrument requesting the panel opinion regarding the relative importance of each listed competency on a five point Likert scale.^ The results of Round Two were tabulated and analyzed to ascertain areas of consensus. A Round Three instrument was prepared advising panelists of all areas of consensus, their dissenting opinions, if any, and a request for a revised opinion.^ A final report was prepared listing the 60 competencies and the panel opinion that eight were of highest priority, 29 of above average priority, and 23 of average priority. No item received two other available ratings, below average priority and lowest priority.^ The implications of these findings suggest necessary areas of curriculum development and industry management development to implement professionalism for Recreational Foodservice managers. ^

Development of ``HealthServe'': A measure of customer service orientation in healthcare

An assessment tool designed to measure a customer service orientation among RN's and LPN's was developed using a content-oriented approach. Critical incidents were first developed by asking two samples of healthcare managers (n = 52 and 25) to identify various customer-contact situations. The critical incidents were then used to formulate a 121-item instrument. Patient-contact workers from 3 hospitals (n = 102) completed the instrument along with the NEO-FFI, a measure of the Big Five personality factors. Concurrently, managers completed a performance evaluation scale on the employees participating in the study in order to determine the predictive validity of the instrument.^ Through a criterion-keying approach, the instrument was scaled down to 38 items. The correlation between HealthServe and the supervisory ratings of performance evaluation data supported the instrument's criterion-related validity (r =.66, p $<$.0001). Incremental validity of HealthServe over the Big Five was found with HealthServe accounting for 46% of the variance.^ The NEO-FFI was used to assess the correlation between personality traits and HealthServe. A factor analysis of HealthServe suggested 4 factors which were correlated with the NEO-FFI scores. Results indicated that HealthServe was related to Extraversion, Openness to Experience, Agreeableness, Conscientiousness and negatively related to Neuroticism.^ The benefits of the test construction procedure used here over the use of broad-based measures of personality were discussed as well as the limitations of using a concurrent validation strategy. Recommendations for future studies were provided. ^

Actionable pattern analysis in computing and business intelligence systems

With advances in science and technology, computing and business intelligence (BI) systems are steadily becoming more complex with an increasing variety of heterogeneous software and hardware components. They are thus becoming progressively more difficult to monitor, manage and maintain. Traditional approaches to system management have largely relied on domain experts through a knowledge acquisition process that translates domain knowledge into operating rules and policies. It is widely acknowledged as a cumbersome, labor intensive, and error prone process, besides being difficult to keep up with the rapidly changing environments. In addition, many traditional business systems deliver primarily pre-defined historic metrics for a long-term strategic or mid-term tactical analysis, and lack the necessary flexibility to support evolving metrics or data collection for real-time operational analysis. There is thus a pressing need for automatic and efficient approaches to monitor and manage complex computing and BI systems. To realize the goal of autonomic management and enable self-management capabilities, we propose to mine system historical log data generated by computing and BI systems, and automatically extract actionable patterns from this data. This dissertation focuses on the development of different data mining techniques to extract actionable patterns from various types of log data in computing and BI systems. Four key problems—Log data categorization and event summarization, Leading indicator identification , Pattern prioritization by exploring the link structures , and Tensor model for three-way log data are studied. Case studies and comprehensive experiments on real application scenarios and datasets are conducted to show the effectiveness of our proposed approaches.

Small farmer market knowledge and specialty coffee commodity chains in Western Highlands Guatemala

For producers motivated by their new status as self-employed, landowning, capitalist coffee growers, specialty coffee presents an opportunity to proactively change the way they participate in the international market. Now responsible for determining their own path, many producers have jumped at the chance to enhance the value of their product and participate in the new "fair trade" market. But recent trends in the international coffee price have led many producers to wonder why their efforts to produce a certified Fair Trade and organic product are not generating the price advantage they had anticipated. My study incorporates data collected in eighteen months of fieldwork, including more than 45 interviews with coffee producers and fair trade roasters, 90 surveys of coffee growers, and ongoing participant observation to understand how fair trade certification, as both a market system and development program, meets the expectations of the coffee growers. By comparing three coffee cooperatives that have engaged the Fair Trade system to disparate ends, the results of this investigation are three case studies that demonstrate how global processes of certification, commodity trade, market interaction, and development aid effect social and cultural change within communities. This study frames several lessons learned in terms of (1) socioeconomic impacts of fair trade, (2) characteristics associated with positive development encounters, and (3) potential for commodity producers to capture value further along their global value chain. Commodity chain comparisons indicate the Fair Trade certified cooperative receives the highest per-pound price, though these findings are complicated by costs associate with certification and producers' perceptions of an "unjust" system. Fair trade-supported projects are demonstrated as more "successful" in the eyes of recipients, though their attention to detail can just as easily result in "failure". Finally, survey results reveal just how limited is the market knowledge of producers in each cooperative, though fair trade does, in fact, provide a rare opportunity for producers to learn about consumer demand for coffee quality. Though bittersweet, the fair trade experiences described here present a learning opportunity for a wide range of audiences, from the certified to the certifiers to the concerned public and conscientious consumer.

Student Achievement of Experiential Learning Objectives

Experiential learning is an important component of undergraduate hospitality programs, but most of the research in this area has focused on administrative and design issues. The author reports on a study undertaken to ascertain student perceptions as they relate to three commonly stated goals of experiential programs: the application of classroom studies, technical training, and management development.

Elemental analysis of biological matrices by laser ablation high resolution inductively coupled plasma mass spectrometry (LA-HR-ICP-MS) and high resolution inductively coupled plasma mass spectrometry (HR -ICP -MS)

The need for elemental analysis of biological matrices such as bone, teeth, and plant matter for sourcing purposes has emerged within the forensic and geochemical laboratories. Trace elemental analyses for the comparison of materials such as glass by inductively coupled plasma mass spectrometry (ICP-MS) and laser ablation ICP-MS has been shown to offer a high degree of discrimination between different manufacturing sources. Unit resolution ICP-MS instruments may suffer from some polyatomic interferences including 40Ar16O+, 40Ar 16O1H+, and 40Ca 16O+ that affect iron measurement at trace levels. Iron is an important element in the analysis of glass and also of interest for the analysis of several biological matrices. A comparison of the analytical performance of two different ICP-MS systems for iron analysis in glass for determining the method detection limits (MDLs), accuracy, and precision of the measurement is presented. Acid digestion and laser ablation methods are also compared. Iron polyatomic interferences were reduced or resolved by using dynamic reaction cell and high resolution ICP-MS. MDLs as low as 0.03 μg g-1 and 0.14 μg g-1 for laser ablation and solution based analyses respectively were achieved. The use of helium as a carrier gas demonstrated improvement in the detection limits of both iron isotopes (56Fe and 57Fe) in medium resolution for the HR-ICP-MS and with a dynamic reaction cell (DRC) coupled to a quadrupole ICP-MS system. ^ The development and application of robust analytical methods for the quantification of trace elements in biological matrices has lead to a better understanding of the potential utility of these measurements in forensic chemical analyses. Standard reference materials (SRMs) were used in the development of an analytical method using HR-ICP-MS and LA-HR-ICP-MS that was subsequently applied on the analysis of real samples. Bone, teeth and ashed marijuana samples were analyzed with the developed method. ^ Elemental analysis of bone samples from 12 different individuals provided discrimination between individuals, when femur and humerus bones were considered separately. Discrimination of 14 teeth samples based on elemental composition was achieved with the exception of one case where samples from the same individual were not associated with each other. The discrimination of 49 different ashed plant (cannabis) samples was achieved using the developed method. ^

Temporal Mining for Distributed Systems

Many systems and applications are continuously producing events. These events are used to record the status of the system and trace the behaviors of the systems. By examining these events, system administrators can check the potential problems of these systems. If the temporal dynamics of the systems are further investigated, the underlying patterns can be discovered. The uncovered knowledge can be leveraged to predict the future system behaviors or to mitigate the potential risks of the systems. Moreover, the system administrators can utilize the temporal patterns to set up event management rules to make the system more intelligent. With the popularity of data mining techniques in recent years, these events grad- ually become more and more useful. Despite the recent advances of the data mining techniques, the application to system event mining is still in a rudimentary stage. Most of works are still focusing on episodes mining or frequent pattern discovering. These methods are unable to provide a brief yet comprehensible summary to reveal the valuable information from the high level perspective. Moreover, these methods provide little actionable knowledge to help the system administrators to better man- age the systems. To better make use of the recorded events, more practical techniques are required. From the perspective of data mining, three correlated directions are considered to be helpful for system management: (1) Provide concise yet comprehensive summaries about the running status of the systems; (2) Make the systems more intelligence and autonomous; (3) Effectively detect the abnormal behaviors of the systems. Due to the richness of the event logs, all these directions can be solved in the data-driven manner. And in this way, the robustness of the systems can be enhanced and the goal of autonomous management can be approached. This dissertation mainly focuses on the foregoing directions that leverage tem- poral mining techniques to facilitate system management. More specifically, three concrete topics will be discussed, including event, resource demand prediction, and streaming anomaly detection. Besides the theoretic contributions, the experimental evaluation will also be presented to demonstrate the effectiveness and efficacy of the corresponding solutions.

Elemental Analysis of Biological Matrices by Laser Ablation High Resolution Inductively Coupled Plasma Mass Spectrometry (LA-HR-ICP-MS) and High Resolution Inductively Coupled Plasma Mass Spectrometry (HR-ICP-MS)

The need for elemental analysis of biological matrices such as bone, teeth, and plant matter for sourcing purposes has emerged within the forensic and geochemical laboratories. Trace elemental analyses for the comparison of aterials such as glass by inductively coupled plasma mass spectrometry (ICP-MS) and laser ablation ICP-MS has been shown to offer a high degree of discrimination between different manufacturing sources. Unit resolution ICP-MS instruments may suffer from some polyatomic interferences including 40Ar16O+, 40Ar16O1H+, and 40Ca16O+ that affect iron measurement at trace levels. Iron is an important element in the analysis of glass and also of interest for the analysis of several biological matrices. A comparison of the nalytical performance of two different ICP-MS systems for iron analysis in glass for determining the method detection limits (MDLs), accuracy, and precision of the measurement is presented. Acid digestion and laser ablation methods are also compared. Iron polyatomic interferences were reduced or resolved by using dynamic reaction cell and high resolution ICP-MS. MDLs as low as 0.03 ìg g-1 and 0.14 ìg g-1 for laser ablation and solution based analyses respectively were achieved. The use of helium as a carrier gas demonstrated improvement in the detection limits of both iron isotopes (56Fe and 57Fe) in medium resolution for the HR-ICP-MS and with a dynamic reaction cell (DRC) coupled to a quadrupole ICP-MS system. The development and application of robust analytical methods for the quantification of trace elements in biological matrices has lead to a better understanding of the potential utility of these measurements in forensic chemical analyses. Standard reference materials (SRMs) were used in the development of an analytical method using HR-ICP-MS and LA-HR-ICP-MS that was subsequently applied on the analysis of real samples. Bone, teeth and ashed marijuana samples were analyzed with the developed method. Elemental analysis of bone samples from 12 different individuals provided discrimination between individuals, when femur and humerus bones were considered separately. Discrimination of 14 teeth samples based on elemental composition was achieved with the exception of one case where samples from the same individual were not associated with each other. The discrimination of 49 different ashed plant (cannabis)samples was achieved using the developed method.

Data partitioning and replication management in distributed geographic information system (GIS) database

This research presents several components encompassing the scope of the objective of Data Partitioning and Replication Management in Distributed GIS Database. Modern Geographic Information Systems (GIS) databases are often large and complicated. Therefore data partitioning and replication management problems need to be addresses in development of an efficient and scalable solution. ^ Part of the research is to study the patterns of geographical raster data processing and to propose the algorithms to improve availability of such data. These algorithms and approaches are targeting granularity of geographic data objects as well as data partitioning in geographic databases to achieve high data availability and Quality of Service(QoS) considering distributed data delivery and processing. To achieve this goal a dynamic, real-time approach for mosaicking digital images of different temporal and spatial characteristics into tiles is proposed. This dynamic approach reuses digital images upon demand and generates mosaicked tiles only for the required region according to user's requirements such as resolution, temporal range, and target bands to reduce redundancy in storage and to utilize available computing and storage resources more efficiently. ^ Another part of the research pursued methods for efficient acquiring of GIS data from external heterogeneous databases and Web services as well as end-user GIS data delivery enhancements, automation and 3D virtual reality presentation. ^ There are vast numbers of computing, network, and storage resources idling or not fully utilized available on the Internet. Proposed "Crawling Distributed Operating System "(CDOS) approach employs such resources and creates benefits for the hosts that lend their CPU, network, and storage resources to be used in GIS database context. ^ The results of this dissertation demonstrate effective ways to develop a highly scalable GIS database. The approach developed in this dissertation has resulted in creation of TerraFly GIS database that is used by US government, researchers, and general public to facilitate Web access to remotely-sensed imagery and GIS vector information. ^

Development of an odor management plan for industrial stationary sources in an urban environment: A case study for Broward County, Florida

Objectionable odors remain at the top of air pollution complaints in urban areas such as Broward County that is subject to increasing residential and industrial developments. The odor complaints in Broward County escalated by 150 percent for the 2001 to 2004 period although the population increased by only 6 percent. It is estimated that in 2010 the population will increase to 2.5 million. Relying solely on enforcing the local odor ordinance is evidently not sufficient to manage the escalating odor complaint trends. An alternate approach similar to odor management plans (OMPs) that are successful in managing major malodor sources such as animal farms is required. ^ This study aims to develop and determine the feasibility of implementing a comprehensive odor management plan (COMP) for the entire Broward County. Unlike existing OMPs for single sources where the receptors (i.e. the complainants) are located beyond the boundary of the source, the COMP addresses a complex model of multiple sources and receptors coexisting within the boundary of the entire county. Each receptor is potentially subjected to malodor emissions from multiple sources within the county. Also, the quantity and quality of the source/receptor variables are continuously changing. ^ The results of this study show that it is feasible to develop a COMP that adopts a systematic procedure to: (1) Generate maps of existing odor complaint areas and malodor sources, (2) Identify potential odor sources (target sources) responsible for existing odor complaints, (3) Identify possible odor control strategies for target sources, (4) Determine the criteria for implementing odor control strategies, (5) Develop an odor complaint response protocol, and (6) Conduct odor impact analyses for new sources to prevent future odor related issues. Geographic Information System (GIS) is used to identify existing complaint areas. A COMP software that incorporates existing United States Environmental Protection Agency (EPA) air dispersion software is developed to determine the target sources, predict the likelihood of new complaints, and conduct odor impact analysis. The odor response protocol requires pre-planning field investigations and conducting surveys to optimize the local agency available resources while protecting the citizen's welfare, as required by the Clean Air Act. ^