Many organizations have difficulty adopting advanced software development practices. Some software development project managers in large organizations are not aligned with the relationship between performance expectancy, effort expectancy, social influence, and facilitating conditions, as moderated by experience, with intent to adopt the DevOps practice of continuous delivery. The purpose of this study was to examine the statistical relationships between the independent variables—performance expectancy, effort expectancy, social influence, and facilitating conditions, as moderated by experience—and the dependent variable of behavioral intent to adopt a continuous delivery system. Venkatesh, Morris, Davis, and Davis's unified theory of acceptance and use of technology provided the theoretical framework. A stepwise multiple linear regression analysis was performed on survey data from 85 technical project managers affiliated with LinkedIn project management groups. The analysis reflected that only performance expectancy was significant in predicting intent to adopt continuous delivery. The findings may contribute to social change by providing project managers with the information they need to support organizational change, collaboration, and facilitation. The knowledge gained may additionally help organizations develop operational efficiency, competitive advantage, and generate higher value to their clients and society.

Researchers have found that a positive correlation exists between information technology (IT) flexibility, IT effectiveness, and strategic alignment in organizations. It has been determined that within inflexible IT environments maintainability is reduced and key business factors become at risk. An IT flexibility measurement matrix was developed to assess IT flexibility however leadership characteristics were not identified for measurement with that model. Determining the leadership characteristics needed for IT flexibility was the purpose of this multiple case study. Leveraging the empowerment, situational leadership, IT-business equilibrium, and complexity change theories, the research questions were focused on the leadership characteristics exhibited by organizational and project team leadership. A purposeful sample of 20 IT nonmanagers participated in in-depth interviews and provided insights into leadership characteristics that were observed and practiced in flexible IT environments. Using deductive a priori coding and inductive data analysis, communication was identified as the leadership characteristic required by both organizational and team leadership. Other emergent leadership characteristics were having a vision, managing change, and servant leadership. The implications for positive social change are for organizations to use the results to develop leaders and teams to successfully manage flexible IT environments, enabling improved IT-business alignment. Academic institutions can provide structured training and cooperative education programs, partnering with IT organizations to develop and retain top IT talent. In addition, individuals can build knowledge and gain experience in these areas to strengthen personal and professional skills, thus increasing career potential.

Healthcare in the US continues to suffer from the poor data quality practices processes that would ensure accuracy of patient health care records and information. A lack of current scholarly research on best practices in data quality and records management has failed to identify potential flaws within the relatively new electronic health records environment that affect not only patient safety but also cost, reimbursements, services, and most importantly, patient safety. The focus of this study was to current best practices using a panel of 25 health care industry data quality experts. The conceptual lens was developed from the International Monetary Fund's Data Quality Management model. The key research question asked how practices contribute to identifying improvements healthcare data, data quality, and integrity. The study consisted of 3 Delphi rounds. Each round was analyzed to identify consensus on proposed data quality strategies from previous rounds that met or exceeded the acceptance threshold to construct subsequent round questions. The 2 best practices identified to improve data collection were user training and clear processes. One significant and unanticipated finding was that the previous gold standard practices have become outdated with technological advances, leading to a higher potential for flawed or inaccurate patient healthcare data. There is an urgent need for health care leaders to maintain heightened awareness of the need to continually evaluate data collection and management policies, particularly as technology advances such as artificial intelligence matures. Developing national standards to address accurate and timely management of patient care data is critical for appropriate health care delivery decisions by health care providers.

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The unprecedented ubiquity with which technological advancements, such as blockchain, the Internet of things (IoT), big data, machine learning, and artificial intelligence (AI), are impacting the world has forced large organizations to rethink their information technology roadmaps. Their decisions about how they invest in technology have become more important. It is against this backdrop that companies must decide how much to invest in their aging technologies versus these new potentially transformational ones. A decision is only as good as the information available to the decision-makers when they make it. This research project seeks to understand the effects that information asymmetry has on strategic information technology (IT) investment decisions within large complex organizations. The data collected for this study was gathered from six executives. The conceptual model was grounded in Akerlof’s (1978) seminal paper on information asymmetry. This study followed an Action Design Research (ADR) approach to formulate the problem and an elaborated Action Design Research (eADR) process model to create a solution. Results indicate that using the proposed solution will result in organizations making more informed strategic IT investment decisions.

Health information technology (HIT), which includes electronic health record (EHR) systems and clinical data analytics, has become a major component of all health care delivery and care management. The adoption of HIT by physicians, hospitals, post-acute care organizations, pharmacies and other health care providers has been accepted as a necessary (and recently, a government required) step toward improved quality, care coordination and reduced costs: “Better coordination of care provides a path to improving communication, improving quality of care, and reducing unnecessary emergency room use and hospital readmissions. LTPAC providers play a critical role in achieving these goals” (HealthIT.gov, 2013). Though some of the impacts of evolving HIT and EHRs have been studied in acute care hospitals and physician office settings, a dearth of information exists about the deployment and effectiveness of HIT and EHRs in long-term and post-acute care facilities, places where they are becoming more essential. This dissertation examines how and to what extent health information technology and electronic health record implementation and use affects certain measurable outcomes in long term and post-acute care facilities. Monthly data were obtained for the period beginning January 1, 2016 through June 30, 2017, a total of 18 months. The level of EHR adoption was found to positively impact hospital readmission rates, employee engagement, complaint deficiencies, failed revisit surveys, staff overtime (partial EHR), staff turnover rate (full EHR) and United States Centers for Medicare and Medicaid Services (CMS) Five Star Quality score. The level of EHR adoption was found to negatively impact CMS Five Star Total score, staff retention rate (full EHR) and staff overtime (full EHR group higher than partial EHR).

Volunteer organizations face two challenges not found in non-volunteer organizations: recruiting and retaining volunteers. While social media use is increasing amongst individuals, its use and effectiveness for volunteer recruitment and retention by volunteer organizations is unknown. The dissertation reports the results of three studies to investigate this important question. Using a mixed-methods approach, it addressed the dual nature of social media and its effectiveness by including volunteer organizations and social media users. This dissertation found that although volunteer organizations are not using social media effectively, they could virtualize requirements of the recruitment process by focusing on relatable events instead of sterile marketing. This dissertation contributes to information systems literature by extending the post-acceptance model of IS continuance to show that social media mediates volunteer continuance. It further contributes by revealing a potential new area of research, i.e., the use and effectiveness of online social media for volunteer organizations.

Abstract not available

An essential motivation behind concurrent object-oriented systems is to exploit the software modularity and reuse potential of object-oriented features in the development of concurrent systems. However, the marriage between the two disciplines has not been a happy one. In this work we propose a model that reduces the problems associated with introducing concurrency into object-oriented languages. We explore techniques for reasoning about synchronisation requirements in composite object systems operating in a concurrent environment. Furthermore we investigate safe locking strategies, where the locks may be distributed over the components of the system and identify conditions for such locks to be non-redundant. Through the recognition of a Galois connection, we achieve an elegant mathematical characterisation of the lock-distribution problem, which allows us to identify efficient strategies and tools for assisting developers with lock selection.

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