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In a previous chapter (Klimberg, Ratick, & Smith, 2018), we introduced a novel approach in which cluster centroids were used as input data for the predictor variables of a multiple linear regression (MLR) used to forecast fleet maintenance costs. We applied this approach to a real data set and significantly improved the predictive accuracy of the MLR model. In this chapter, we develop a methodology for adjusting moving average forecasts of the future values of fleet service occurrences by interpolating those forecast values using their relative distances from cluster centroids. We illustrate and evaluate the efficacy of this approach with our previously used data set on fleet maintenance.

The authors link High-Involvement Work Systems (HIWS) with social network research both theoretically and methodologically by conceiving of these work systems as networks and by using network methods to better understand and evaluate these arrangements. Their approach is to integrate the institutional perspective of industrial relations with the analytical methodology of social network analysis. They use a longitudinal data set collected before and after the introduction of an HIWS in a pharmaceutical company to measure the impact on patterns of employee communication as well as communication between the union and management. Improvements were found in customer satisfaction, and positive effects were seen in the pattern and structure of organizational communication with an increase in the density of lateral and vertical interdepartmental communication, and a decrease in hierarchy. These results were confirmed using survey data on employee perceptions of particular types of communication and interviews with employees at various levels of authority.

This chapter presents a quantitative and qualitative review of research on the use of behavioral self-management (BSM) procedures with adolescents with learning disabilities or behavioral disorders (LD/BD). These procedures included self-monitoring, self-evaluation, self-reinforcement, self-instruction, and packages containing two or more BSM techniques. Twenty studies published from 1981 to 2002 were identified and analyzed. The analysis centered on a series of questions addressing overall effectiveness of the procedures, whether BSM produced socially valid changes, where the changes occurred (i.e. special education or general education setting), whether maintenance and generalization of the target behavior(s) occurred, and if students began to use BSM procedures on their own. Results showed a mean percentage of nonoverlapping data (PND) of 80 indicating that BSM procedures are, overall, an effective approach to behavior change. It also appears that in some instances, these changes are socially valid in that the performance of students with LD/BD can be improved to the level of nondisabled peers. Interventions consisting of a combination of self-management procedures appear to be the most effective, however self-monitoring alone has similar impact. BSM also appears to be effective with a wide variety of behaviors, albeit with relatively discrete behaviors (versus more complex chains of behaviors used in strategic problem-solving). While there is some evidence that target behaviors were generalized and maintained, many of the studies reviewed did not measure it. Also of concern was the apparent lack of student involvement in selecting target behaviors, goal setting, forms of recording etc as well as the fact that no study measured student ability to apply BSM procedures after intervention. Implications for future research and practice are discussed.

Implementation of accrual-based accounting systems and the related preparation of an initial balance sheet are stimulating a debate on valuation and management of fixed assets, emphasising how critical it is to have adequate asset information. This chapter aims to propose a framework to clarify the relationship between the asset inventory and the asset register by examining the objectives and characteristics of asset information systems, drawing from experience regarding the implementation of asset inventories and registers from four countries (Malaysia, South Africa, Switzerland, and Australia – State of Victoria).

Introduction: The insurance sector provides security to society by pooling resources to manage risks. Insurers’ improved ability to analyse risks by examining vast amounts of granular data has considerably refined this technique. Compiling and analysing the fine data sets is now transformed into the ‘Big Data’ technique. The introduction of big data analytics (BDA) is transforming the insurance industry and the role data plays in insurance.

Purpose: This chapter will attempt to examine the applications and role of big data in the insurance sector and how big data affects the different insurance segments like health insurance, property and casualty, and travel insurance. This chapter will also describe the disruptive impact of big data on the insurance market.

Methodology: Systematic research is carried out by analysing case studies and literature studies, emphasising how BDA is revolutionary for the insurance market. For this purpose, various articles and studies on BDA in the insurance market are selected and studied.

Findings: The execution of big data is continuously increasing in the insurance sector. The performance of big data in the insurance market results in cost reduction, better access to insurance services, and more fraud detection that benefits the customers and stakeholders. Therefore, big data has revolutionised the insurance market and assisted insurers in targeting customers more precisely.

Meeting accreditation requirements provides challenges for any size institution. One small, state-supported university found three solutions to problems associated with gaining accreditation: the creation of an accreditation “data pantry;” the use of common technological formats and technologically savvy faculty members to “work smarter, not harder” with accreditation tasks and data; and the participation of faculty members in new ways to revise curriculum, forge stronger relationships among faculty from different departments, and generate strong learning experiences for students. Two frustrations regarding the accreditation process remained: university responsibility for the performance of former education students long after they leave campus and competency testing that forces schools into reactionary leadership that may place gaining accreditation ahead of meeting students’ needs. Finally, the milieu of “teststeria” has a deleterious effect on faculty innovation, pulls faculty focus away from the students whom they desire to serve, and decreases the value of the teaching profession.

This chapter introduces Learning Health Systems (LHS) and the impact of data science on such systems. It also examines the necessary properties of data used in LHS and identifies patients who may benefit from a transition to palliative care. Finally, it examines the way LHS can be used to identify racial and social disparities in access to palliative care.

This study aims to understand the role of technology in relationship maintenance among romantic partners.

It takes a qualitative, inductive approach and collected data from in-depth interviews with 20 individuals who are married or in cohabiting relationships.

This study supports the extension of relationship maintenance typology derived from face-to-face relationship studies to technology-mediated communication, but highlights how technology use transforms the implementation of maintenance behaviors. Technology helps couples coordinate tasks and keep in touch with friends and families. Although technology-mediated communication cannot replace face-to-face interactions in relationship talk and sharing in-depth feelings, it plays an important role in redefining the ways in which couples interact positively, maintain mutual understanding, and secure the future of the relationship. Moreover, this study identifies a new maintenance behavior, communication coordination. These maintenance behaviors reflect a tension between maintaining connectivity and managing the boundary between work and home and between the public and private spheres.

This study builds on previous work on technology use and relationship maintenance, but takes a different qualitative, inductive approach to address the limitations in the survey research dominant in the literature. It helps us understand the advantages and challenges in maintaining relationships in the digital age and also explores the factors that influence the patterns of technology use in relationship maintenance.