Learning from Exemplary Service Providers

Twelve exemplary service providers from the most highly-acclaimed resorts discussed and demonstrated how they deliver award-winning service. Three emergent themes offer insights to improve service quality: emotional generosity, exemplary communication, and effective interactions of culture, tradition and control. These themes support current literature on human resource development and service quality.

Public Service Motivation in Public and Nonprofit Service Providers: The Cases of Belarus and Poland

The work motivation construct is central to the theory and practice of many social science disciplines. Yet, due to the novelty of validated measures appropriate for a deep cross-national comparison, studies that contrast different administrative regimes remain scarce. This study represents an initial empirical effort to validate the Public Service Motivation (PSM) instrument proposed by Kim and colleagues (2013) in a previously unstudied context. The two former communist countries analyzed in this dissertation—Belarus and Poland— followed diametrically opposite development strategies: a fully decentralized administrative regime in Poland and a highly centralized regime in Belarus. The employees (n = 677) of public and nonprofit organizations in the border regions of Podlaskie Wojewodstwo (Poland) and Hrodna Voblasc (Belarus) are the subjects of study. Confirmatory factor analysis revealed three dimensions of public service motivation in the two regions: compassion, self-sacrifice, and attraction to public service. The statistical models tested in this dissertation suggest that nonprofit sector employees exhibit higher levels of PSM than their public sector counterparts. Nonprofit sector employees also reveal a similar set of values and work attitudes across the countries. Thus, the study concludes that in terms of PSM, employees of nonprofit organizations constitute a homogenous group that exists atop the administrative regimes. However, the findings propose significant differences between public sector agencies across the two countries. Contrary to expectations, data suggest that organization centralization in Poland is equal to—or for some items even higher than—that of Belarus. We can conclude that the absence of administrative decentralization of service provision in a country does not necessarily undermine decentralized practices within organizations. Further analysis reveals strong correlations between organization centralization and PSM for the Polish sample. Meanwhile, in Belarus, correlations between organization centralization items and PSM are weak and mostly insignificant. The analysis indicates other factors beyond organization centralization that significantly impact PSM in both sectors. PSM of the employees in the studied region is highly correlated with their participation in religious practices, political parties, or labor unions as well as location of their organization in a capital and type of social service provided.

Public service motivation in public and nonprofit service providers: The cases of Belarus and Poland

The work motivation construct is central to the theory and practice of many social science disciplines. Yet, due to the novelty of validated measures appropriate for a deep cross-national comparison, studies that contrast different administrative regimes remain scarce. This study represents an initial empirical effort to validate the Public Service Motivation (PSM) instrument proposed by Kim and colleagues (2013) in a previously unstudied context. The two former communist countries analyzed in this dissertation—Belarus and Poland—followed diametrically opposite development strategies: a fully decentralized administrative regime in Poland and a highly centralized regime in Belarus. The employees (n = 677) of public and nonprofit organizations in the border regions of Podlaskie Wojewodstwo (Poland) and Hrodna Voblasc (Belarus) are the subjects of study. ^ Confirmatory factor analysis revealed three dimensions of public service motivation in the two regions: compassion, self-sacrifice, and attraction to public service. The statistical models tested in this dissertation suggest that nonprofit sector employees exhibit higher levels of PSM than their public sector counterparts. Nonprofit sector employees also reveal a similar set of values and work attitudes across the countries. Thus, the study concludes that in terms of PSM, employees of nonprofit organizations constitute a homogenous group that exists atop the administrative regimes. ^ However, the findings propose significant differences between public sector agencies across the two countries. Contrary to expectations, data suggest that organization centralization in Poland is equal to—or for some items even higher than—that of Belarus. We can conclude that the absence of administrative decentralization of service provision in a country does not necessarily undermine decentralized practices within organizations. Further analysis reveals strong correlations between organization centralization and PSM for the Polish sample. Meanwhile, in Belarus, correlations between organization centralization items and PSM are weak and mostly insignificant. ^ The analysis indicates other factors beyond organization centralization that significantly impact PSM in both sectors. PSM of the employees in the studied region is highly correlated with their participation in religious practices, political parties, or labor unions as well as location of their organization in a capital and type of social service provided.^

Best practices in exemplary service delivery: A multiple case study of service quality

The purpose of this study was to explain how exemplary service providers in luxury hotels provide consistently excellent service. Using a case study framework, the study investigated the service provider's strategies and concepts of service delivery, the importance and implementation of organizational and individual controls, and the role of training and learning. The study identified barriers to service provision and characteristics of the exemplary individuals that affect their ability to deliver luxury service. This study sought to better understand how exemplary service providers learn, think about, and do their work. The sample population of three Five-Diamond-Award winning resorts was selected for their potential for learning about the phenomenon of interest. The results demonstrate that exemplary service providers possess individual characteristics that are enhanced by the organizations for which they work. Exemplary service providers are often exemplary communicators who are emotionally generous and genuinely enjoy helping and serving others. Exemplary service organizations treat their employees as they treat their customers, as suggested by the Service-Profit Chain (Heskett, Sasser & Schlesinger, 1997). Further, they have systems and standards to guarantee satisfactory service experiences for every guest. They also encourage their service providers to personalize their service delivery and to seek opportunities to delight their guests, using a combination of controls, traditions and cultural values. Several customer service theories are discussed in relationship to whether they were or were not supported by the data. The study concluded that the delivery of exemplary service is a complex phenomenon that requires successful interactions between guests, service providers and the organization. A Model of Exemplary Service Delivery is presented and discussed that demonstrates the components of service quality as shown in the data. The model can be used by practitioners seeking to create, enhance, or evaluate their service quality, and by researchers seeking insights into the complex concepts in service quality research. Implications for future research are discussed.

Event mining for system and service management

Modern IT infrastructures are constructed by large scale computing systems and administered by IT service providers. Manually maintaining such large computing systems is costly and inefficient. Service providers often seek automatic or semi-automatic methodologies of detecting and resolving system issues to improve their service quality and efficiency. This dissertation investigates several data-driven approaches for assisting service providers in achieving this goal. The detailed problems studied by these approaches can be categorized into the three aspects in the service workflow: 1) preprocessing raw textual system logs to structural events; 2) refining monitoring configurations for eliminating false positives and false negatives; 3) improving the efficiency of system diagnosis on detected alerts. Solving these problems usually requires a huge amount of domain knowledge about the particular computing systems. The approaches investigated by this dissertation are developed based on event mining algorithms, which are able to automatically derive part of that knowledge from the historical system logs, events and tickets. ^ In particular, two textual clustering algorithms are developed for converting raw textual logs into system events. For refining the monitoring configuration, a rule based alert prediction algorithm is proposed for eliminating false alerts (false positives) without losing any real alert and a textual classification method is applied to identify the missing alerts (false negatives) from manual incident tickets. For system diagnosis, this dissertation presents an efficient algorithm for discovering the temporal dependencies between system events with corresponding time lags, which can help the administrators to determine the redundancies of deployed monitoring situations and dependencies of system components. To improve the efficiency of incident ticket resolving, several KNN-based algorithms that recommend relevant historical tickets with resolutions for incoming tickets are investigated. Finally, this dissertation offers a novel algorithm for searching similar textual event segments over large system logs that assists administrators to locate similar system behaviors in the logs. Extensive empirical evaluation on system logs, events and tickets from real IT infrastructures demonstrates the effectiveness and efficiency of the proposed approaches.^

Delay-sensitive service request scheduling for cloud computing

Cloud computing realizes the long-held dream of converting computing capability into a type of utility. It has the potential to fundamentally change the landscape of the IT industry and our way of life. However, as cloud computing expanding substantially in both scale and scope, ensuring its sustainable growth is a critical problem. Service providers have long been suffering from high operational costs. Especially the costs associated with the skyrocketing power consumption of large data centers. In the meantime, while efficient power/energy utilization is indispensable for the sustainable growth of cloud computing, service providers must also satisfy a user's quality of service (QoS) requirements. This problem becomes even more challenging considering the increasingly stringent power/energy and QoS constraints, as well as other factors such as the highly dynamic, heterogeneous, and distributed nature of the computing infrastructures, etc. ^ In this dissertation, we study the problem of delay-sensitive cloud service scheduling for the sustainable development of cloud computing. We first focus our research on the development of scheduling methods for delay-sensitive cloud services on a single server with the goal of maximizing a service provider's profit. We then extend our study to scheduling cloud services in distributed environments. In particular, we develop a queue-based model and derive efficient request dispatching and processing decisions in a multi-electricity-market environment to improve the profits for service providers. We next study a problem of multi-tier service scheduling. By carefully assigning sub deadlines to the service tiers, our approach can significantly improve resource usage efficiencies with statistically guaranteed QoS. Finally, we study the power conscious resource provision problem for service requests with different QoS requirements. By properly sharing computing resources among different requests, our method statistically guarantees all QoS requirements with a minimized number of powered-on servers and thus the power consumptions. The significance of our research is that it is one part of the integrated effort from both industry and academia to ensure the sustainable growth of cloud computing as it continues to evolve and change our society profoundly.^

Delay-Sensitive Service Request Scheduling for Cloud Computing

Cloud computing realizes the long-held dream of converting computing capability into a type of utility. It has the potential to fundamentally change the landscape of the IT industry and our way of life. However, as cloud computing expanding substantially in both scale and scope, ensuring its sustainable growth is a critical problem. Service providers have long been suffering from high operational costs. Especially the costs associated with the skyrocketing power consumption of large data centers. In the meantime, while efficient power/energy utilization is indispensable for the sustainable growth of cloud computing, service providers must also satisfy a user's quality of service (QoS) requirements. This problem becomes even more challenging considering the increasingly stringent power/energy and QoS constraints, as well as other factors such as the highly dynamic, heterogeneous, and distributed nature of the computing infrastructures, etc. In this dissertation, we study the problem of delay-sensitive cloud service scheduling for the sustainable development of cloud computing. We first focus our research on the development of scheduling methods for delay-sensitive cloud services on a single server with the goal of maximizing a service provider's profit. We then extend our study to scheduling cloud services in distributed environments. In particular, we develop a queue-based model and derive efficient request dispatching and processing decisions in a multi-electricity-market environment to improve the profits for service providers. We next study a problem of multi-tier service scheduling. By carefully assigning sub deadlines to the service tiers, our approach can significantly improve resource usage efficiencies with statistically guaranteed QoS. Finally, we study the power conscious resource provision problem for service requests with different QoS requirements. By properly sharing computing resources among different requests, our method statistically guarantees all QoS requirements with a minimized number of powered-on servers and thus the power consumptions. The significance of our research is that it is one part of the integrated effort from both industry and academia to ensure the sustainable growth of cloud computing as it continues to evolve and change our society profoundly.

Abstractions to support dynamic adaptation of communication frameworks for user-centric communication

The convergence of data, audio and video on IP networks is changing the way individuals, groups and organizations communicate. This diversity of communication media presents opportunities for creating synergistic collaborative communications. This form of collaborative communication is however not without its challenges. The increasing number of communication service providers coupled with a combinatorial mix of offered services, varying Quality-of-Service and oscillating pricing of services increases the complexity for the user to manage and maintain ‘always best’ priced or performance services. Consumers have to manually manage and adapt their communication in line with differences in services across devices, networks and media while ensuring that the usage remain consistent with their intended goals. This dissertation proposes a novel user-centric approach to address this problem. The proposed approach aims to reduce the aforementioned complexity to the user by (1) providing high-level abstractions and a policy based methodology for automated selection of the communication services guided by high-level user policies and (2) providing services through the seamless integration of multiple communication service providers and providing an extensible framework to support the integration of multiple communication service providers. The approach was implemented in the Communication Virtual Machine (CVM), a model-driven technology for realizing communication applications. The CVM includes the Network Communication Broker, the layer responsible for providing a network-independent API to the upper layers of CVM. The initial prototype for the NCB supported only a single communication framework which limited the number, quality and types of services available. Experimental evaluation of the approach show the additional overhead of the approach is minimal compared to the individual communication services frameworks. Additionally the automated approach proposed out performed the individual communication services frameworks for cross framework switching.

Improving resource management in virtualized data centers using application performance models

The rapid growth of virtualized data centers and cloud hosting services is making the management of physical resources such as CPU, memory, and I/O bandwidth in data center servers increasingly important. Server management now involves dealing with multiple dissimilar applications with varying Service-Level-Agreements (SLAs) and multiple resource dimensions. The multiplicity and diversity of resources and applications are rendering administrative tasks more complex and challenging. This thesis aimed to develop a framework and techniques that would help substantially reduce data center management complexity.^ We specifically addressed two crucial data center operations. First, we precisely estimated capacity requirements of client virtual machines (VMs) while renting server space in cloud environment. Second, we proposed a systematic process to efficiently allocate physical resources to hosted VMs in a data center. To realize these dual objectives, accurately capturing the effects of resource allocations on application performance is vital. The benefits of accurate application performance modeling are multifold. Cloud users can size their VMs appropriately and pay only for the resources that they need; service providers can also offer a new charging model based on the VMs performance instead of their configured sizes. As a result, clients will pay exactly for the performance they are actually experiencing; on the other hand, administrators will be able to maximize their total revenue by utilizing application performance models and SLAs. ^ This thesis made the following contributions. First, we identified resource control parameters crucial for distributing physical resources and characterizing contention for virtualized applications in a shared hosting environment. Second, we explored several modeling techniques and confirmed the suitability of two machine learning tools, Artificial Neural Network and Support Vector Machine, to accurately model the performance of virtualized applications. Moreover, we suggested and evaluated modeling optimizations necessary to improve prediction accuracy when using these modeling tools. Third, we presented an approach to optimal VM sizing by employing the performance models we created. Finally, we proposed a revenue-driven resource allocation algorithm which maximizes the SLA-generated revenue for a data center.^

Demographic, Behavioral and Perceptual Comparisons of U.S Visitor Experience with Group Package Tours and Free Independent Travel to China

U.S. visitor demand for the China travel experience is anticipated to rise significantly through 2105, causing the Chinese government to employ 100 million service providers over the next six years and raising concern about service delivery and perceptions of the on-site China experience. In an effort to better understand these issues concerning U.S. visitors, this study investigated two specific types of U.S. travelers to China: Group Package Tour (GPT) visitors and Free Independent Travel (FIT) visitors. Results indicated that GPT visitors were more likely to be older and have higher household income than FIT visitors. Four trip-related characteristics of GPT and FIT visitors were found to be significantly different, with GPT visitors showing higher levels of satisfaction with the overall China on-site travel experience.

*Postsecondary access for individuals with psychological disabilities: An analysis of federal rulings and institutional philosophies, *policies, and practices

This study was a qualitative investigation, with demographic quantitative features, of post-secondary educational access and legal guidelines for individuals with psychological disabilities. Although disability laws have positively influenced post-secondary educational attitudes and practices relative to accommodating many individuals with disabilities, prevailing stigmas regarding mental illness have discouraged the equal access to higher education for individuals with psychological disabilities. Little research concentrating on this area was found.^ Thirty-six relevant legal case decisions, focusing on a variety of realms of higher education, were scrutinized. The policies, procedures, and practices of six Southeastern United States universities were analyzed through official documents and participant responses from disability service providers and other university employees. Comparisons were made between legal cases, and within and between universities. Case findings also provided standards through which participating university practices could be studied.^ The legal analysis revealed that most institutions did not discriminate against individuals with psychological disabilities. Practices of a few of these institutions, however, suggested non-compliance despite favorable decisions on their behalf. Institutions found to have discriminatory practices were cited for inadequate procedures, or for presumptive assessments of the educational functioning levels of individuals with psychological disabilities.^ Participant university practices generally suggested disability law compliance; however, certain campus interventions were determined to be ineffective in identifying, addressing, and communicating about the educational needs of individuals with psychological disabilities. The most effective services for these individuals, who were described as rapidly increasing in number but lagging in self-advocacy and acceptance by others, went beyond legal requirements.^ Recommendations were made for institutional practices concerning disability-related documentation, written standards and operations, and student identification and referral. Directions for future research focused on study skills training for students; exposure of mental health professionals to client educational needs; and expansion of the current research, on a nationwide collegiate level, and a parallel analysis focusing on business and industry. ^

Development of a new client -server architecture for context aware mobile computing

This dissertation studies the context-aware application with its proposed algorithms at client side. The required context-aware infrastructure is discussed in depth to illustrate that such an infrastructure collects the mobile user’s context information, registers service providers, derives mobile user’s current context, distributes user context among context-aware applications, and provides tailored services. The approach proposed tries to strike a balance between the context server and mobile devices. The context acquisition is centralized at the server to ensure the reusability of context information among mobile devices, while context reasoning remains at the application level. Hence, a centralized context acquisition and distributed context reasoning are viewed as a better solution overall. The context-aware search application is designed and implemented at the server side. A new algorithm is proposed to take into consideration the user context profiles. By promoting feedback on the dynamics of the system, any prior user selection is now saved for further analysis such that it may contribute to help the results of a subsequent search. On the basis of these developments at the server side, various solutions are consequently provided at the client side. A proxy software-based component is set up for the purpose of data collection. This research endorses the belief that the proxy at the client side should contain the context reasoning component. Implementation of such a component provides credence to this belief in that the context applications are able to derive the user context profiles. Furthermore, a context cache scheme is implemented to manage the cache on the client device in order to minimize processing requirements and other resources (bandwidth, CPU cycle, power). Java and MySQL platforms are used to implement the proposed architecture and to test scenarios derived from user’s daily activities. To meet the practical demands required of a testing environment without the impositions of a heavy cost for establishing such a comprehensive infrastructure, a software simulation using a free Yahoo search API is provided as a means to evaluate the effectiveness of the design approach in a most realistic way. The integration of Yahoo search engine into the context-aware architecture design proves how context aware application can meet user demands for tailored services and products in and around the user’s environment. The test results show that the overall design is highly effective, providing new features and enriching the mobile user’s experience through a broad scope of potential applications.

Perceptions and experiences of intimate partner violence among Hispanic college students

Intimate partner violence (IPV) is recognized as a serious, growing problem on college campuses. IPV rates among college students exceed estimates reported for the general population. Few studies have examined the impact of IPV among the Hispanic college student (HCS) population or explored how HCSs perceive and experience IPV. Focusing on young adults (ages 18 to 25 years), this mixed methods study was designed to explore the perceptions and experiences of IPV focusing on levels of victimization and perpetration in relation to gender role attitudes and beliefs, exposure to parental IPV, acculturation, and religiosity. A sample of 120 HCSs was recruited from two south Florida universities. A subsample of 20 participants was randomly selected to provide qualitative responses. All participants completed a series of questionnaires including a demographic survey, the FPB, CTS2-CA, SASH, ERS and CTS2. Bivariate correlational techniques and multiple regressions were used to analyze data. Marked discrepancy between participants' perceived experience of IPV (N = 120) and their CTS2 responses (n = 116, 96.7%). Only 5% of the participants saw themselves as victims or perpetrators of IPV, yet 66% were victims or 67% were perpetrators of verbal aggression; and 31% were victims or 32.5% were perpetrators of sexual coercion based on their CTS2 scores. Qualitative responses elicited from the subsample of 20 students provided some insight regarding this disparity. There was rejection of traditional stratified gender roles. Few participants indicated that they were religious (20.8%, n = 25). Evidence for the theory of intergenerational transmission of violence was noted. Recall of parental IPV was a significant predictor of level of IPV victimization (β = 0.177, SE = 0.85, p = 0.041). Nursing and social service providers must be cognizant that contributing factors to either victimization and/or perpetration of IPV among college students must be addressed first (i.e., perceptions of IPV), both in acute (i.e., emergency department) and community (i.e., college and university) settings for optimum intervention outcome.

Development of a New Client-Server Architecture for Context Aware Mobile Computing

This dissertation studies the context-aware application with its proposed algorithms at client side. The required context-aware infrastructure is discussed in depth to illustrate that such an infrastructure collects the mobile user’s context information, registers service providers, derives mobile user’s current context, distributes user context among context-aware applications, and provides tailored services. The approach proposed tries to strike a balance between the context server and mobile devices. The context acquisition is centralized at the server to ensure the usability of context information among mobile devices, while context reasoning remains at the application level. Hence, a centralized context acquisition and distributed context reasoning are viewed as a better solution overall. The context-aware search application is designed and implemented at the server side. A new algorithm is proposed to take into consideration the user context profiles. By promoting feedback on the dynamics of the system, any prior user selection is now saved for further analysis such that it may contribute to help the results of a subsequent search. On the basis of these developments at the server side, various solutions are consequently provided at the client side. A proxy software-based component is set up for the purpose of data collection. This research endorses the belief that the proxy at the client side should contain the context reasoning component. Implementation of such a component provides credence to this belief in that the context applications are able to derive the user context profiles. Furthermore, a context cache scheme is implemented to manage the cache on the client device in order to minimize processing requirements and other resources (bandwidth, CPU cycle, power). Java and MySQL platforms are used to implement the proposed architecture and to test scenarios derived from user’s daily activities. To meet the practical demands required of a testing environment without the impositions of a heavy cost for establishing such a comprehensive infrastructure, a software simulation using a free Yahoo search API is provided as a means to evaluate the effectiveness of the design approach in a most realistic way. The integration of Yahoo search engine into the context-aware architecture design proves how context aware application can meet user demands for tailored services and products in and around the user’s environment. The test results show that the overall design is highly effective,providing new features and enriching the mobile user’s experience through a broad scope of potential applications.

Improving Resource Management in Virtualized Data Centers using Application Performance Models

The rapid growth of virtualized data centers and cloud hosting services is making the management of physical resources such as CPU, memory, and I/O bandwidth in data center servers increasingly important. Server management now involves dealing with multiple dissimilar applications with varying Service-Level-Agreements (SLAs) and multiple resource dimensions. The multiplicity and diversity of resources and applications are rendering administrative tasks more complex and challenging. This thesis aimed to develop a framework and techniques that would help substantially reduce data center management complexity. We specifically addressed two crucial data center operations. First, we precisely estimated capacity requirements of client virtual machines (VMs) while renting server space in cloud environment. Second, we proposed a systematic process to efficiently allocate physical resources to hosted VMs in a data center. To realize these dual objectives, accurately capturing the effects of resource allocations on application performance is vital. The benefits of accurate application performance modeling are multifold. Cloud users can size their VMs appropriately and pay only for the resources that they need; service providers can also offer a new charging model based on the VMs performance instead of their configured sizes. As a result, clients will pay exactly for the performance they are actually experiencing; on the other hand, administrators will be able to maximize their total revenue by utilizing application performance models and SLAs. This thesis made the following contributions. First, we identified resource control parameters crucial for distributing physical resources and characterizing contention for virtualized applications in a shared hosting environment. Second, we explored several modeling techniques and confirmed the suitability of two machine learning tools, Artificial Neural Network and Support Vector Machine, to accurately model the performance of virtualized applications. Moreover, we suggested and evaluated modeling optimizations necessary to improve prediction accuracy when using these modeling tools. Third, we presented an approach to optimal VM sizing by employing the performance models we created. Finally, we proposed a revenue-driven resource allocation algorithm which maximizes the SLA-generated revenue for a data center.