Small business owners need effective strategies to increase profitability. One such strategy is the adoption of information technology (IT). The purpose of this multiple case study was to explore the strategies used by small business enterprise (SBE) owners to implement IT solutions for increased profitability within 3 years of opening their business. The population consisted of 3 small business owners in Orange County Southern California who were profitable by their third year of business. The conceptual framework for this study was based upon general systems theory. Data for this study were collected through semistructured interviews and a review of company documents. Transcript review and member checking were included for validity and reliability purposes. Methodological triangulation, achieved through analysis of business plans, financial documents, and probability trends documents allowed identification of 4 emergent themes: Essential strategies small business owners use to implement IT solutions for increased profitability, the essential relationship between network orientation and successful IT implementation, the relationship between IT consultants and successful implementation, and the relationship between internal IT resources and successful implementation. The findings from this study could impact social change because when SBEs are profitable, SBE owners will contribute to the affluence of their workers, communities, local economies, and society.

For information technology (IT) professionals, the average turnover rate of voluntary employees is approximately 21.5% and occurs in fewer than 5 years. The purpose of this single case study was to explore strategies IT outsourcing business executives used to retain key IT employees in the New England region of the United States. Three IT business leaders from a single organization were selected to participate because they had implemented strategies to retain key IT employees. Herzberg's 2-factor theory of motivation was used as the conceptual framework for this doctoral study. Data were collected using semistructured interviews and review of company policies and personnel handbooks. Clarke and Braun's thematic analysis was used for data analysis, including assembling the data, creating codes from the data, compiling codes to generate themes, and interpreting and presenting themes. Member checking and triangulation processes helped increase study validity and reliability. Three themes emerged from the study: building personal relationships, creating positive company culture, and investing in employee training. The findings of this study may help IT leaders increase employee retention by focusing on work relationships, company culture, and employee training. Findings may contribute to social change by helping IT leaders so they can be civically engaged and address issues of public concern by increasing community volunteering, participating in charitable activities and philanthropy, and becoming politically active through petitioning and collaborating with local authorities.

The development of novel software applications on digital platforms differs from traditional software development and provides unique challenges to the software development manager and team. Application producers must achieve application-platform match, application-market match, value propositions exceeding platform’s core value propositions, and novelty. These desired properties support a new vision of the software development team as entrepreneurs with a goal of developing novel applications on digital platforms. Digital platforms are characterized by an uncertain, risky, and resource-constrained environment, where existing approaches—plan-driven, ad-hoc, and controlled-flexible—have limited applicability. Building on the theoretical basis of the theory of effectuation from the entrepreneurship domain, this dissertation proposes an effectual approach to software development. Preliminary studies are conducted to provide prima facia evidence of effectual thinking in software development teams. Also, pilot interviews at local organizations are conducted to augment the approach. Finally, two case studies are conducted to validate the approach. We find conclusive evidence for the efficacy of effectual software development to develop novel applications on digital platforms. We also find that novel ideas are identified, honed, and incorporated, in the application, using effectual thinking. This study contributes to information systems literature by proposing and validating an effectual approach to software development. This study contributes to entrepreneurship literature by illustrating the role of planning and visionary approaches in effectuation settings. This study also contributes to practitioners by highlighting the theoretical underpinnings of existing approaches and the effectual approach which allows software development teams to incorporate effectual thinking and develop novel software applications. Finally, we conclude with a discussion on the theoretical contributions of this study, limitations, and future research avenues.

A materialized view is a derived data collecton stored in a database. When the source data for a materialized view is updated, the materialized view also needs to be updated. The process of updating a materialized view in response to changes in the source data is called view maintenance. There are two methods for maintaining a materialized view - recomputation and incremental computation. Recomputation computes the new view instance from scratch using the updated sources data. Incremental computation on the other hand, computes the new view instance by using the update to the source data, the old view instance, and possibly some source data. Incremental computation is widely accepted as a less expensive mathod of maintaining a view when the size of the update to the source data is small in relation to the size of the source data. / thesis (PhD)--University of South Australia, 2000

The goal of the project was to develop a functional prototype of an environmental risk assessment parameter database on the World-Wide Web. The ability to develop a consolidated environmental database has become possible due to the phenomenal growth of the Internet and the World-Wide Web over the past few years. A large number of environmental resources do currently exist; however, with the large volume of information available, access, management, reliability, and retrievability have become increasingly difficult. To illustrate the prototype database, a practical environmental concern and the tools necessary to evaluate and characterize that concern were needed. Uranium (�������U) daughters leaching from abandoned mill tailing piles at three abandoned uranium mines in southwestern Colorado were chosen to demonstrate the database concept. The RESRAD environmental pathway modeling code served as the evaluation and characterization tool. Due to the size and complexity of RESRAD, a single radionuclide release rate equation was isolated as a controllable component of the code. The equation was a small part of the water pathway factor and examined the rate at which radionuclides absorbed in soil were leached by infiltrating water. This serves as the source term for groundwater contamination and directly applies to the �������U progeny leaching from mill tailing piles scenario. Parameters selected from the equation dealt with the background data that directly influenced the mobility of contaminates in the environment. Environmental data for the three Colorado sites were gathered and interpreted. Probability Density Functions (PDFs) were developed for input parameters and the results were then incorporated into the web site. / Graduation date: 1998

Ph.D. / Computer Science and Engineering / Join-order optimization plays a central role in the processing of relational database queries. This dissertation presents two new algorithms for join-order optimization: a deterministic, exhaustive-search algorithm, and a stochastic algorithm that is based on the deterministic one. The deterministic algorithm achieves new complexity bounds for exhaustive search in join-order optimization; and in timing tests, both algorithms are shown to run many times faster than their predecessors. In addition, these new, fast algorithms search a larger space of join orders than is customary in join-order optimization. Not only do they consider all the so-called bushy join orders, rather than just the left-deep ones, but-what is more unusual-they also consider all join orders that contain Cartesian products. The novel construction of these algorithms enables them to search a space including Cartesian products without paying the performance penalty that is conventionally associated with such a search.

Support of order in query processing is a crucial component in relational database systems, not only because the output of a query is often required to be sorted in a specific order, but also because employing order properties can significantly reduce the query execution cost. Therefore, finding an effective approach to answer queries over ordered data is important to the efficiency of query processing in relational databases. In this dissertation, an ordered relational database model is proposed, which captures both data tuples of relations and tuple ordering in relations. Based on this conceptual model, ordered relational queries are formally defined in a two-sorted first-order calculus, which serves as a yardstick to evaluate expressive power of other ordered query representations. The primary purpose of this dissertation is to investigate the expressive power of different ordered query representations. Particularly, the completeness problem of ordered relational algebras is studied with respect to the first-order calculus: does there exist an ordered algebra such that any first-order expressible ordered relational query can be expressed by a finite sequence of ordered operations? The significance of studying the completeness problem of ordered relational algebras is in that the completeness of ordered relational algebras leads to the possibility of implementing a finite set of ordered operators to express all first-order expressible ordered queries in relational databases. The dissertation then focuses on the completeness problem of ordered conjunctive queries. This investigation is performed in an incremental manner: first, the ordered conjunctive queries with data-decided order is considered; then, the ordered conjunctive queries with t-decided order is studied; finally, the completeness problem for the general ordered conjunctive queries is explored. The completeness theorem of ordered algebras is proven for all three classes of ordered conjunctive queries. Although this ordered relational database model is only conceptual, and ordered operators are not implemented in this dissertation, we do prove that a complete set of ordered operators exists to retrieve all first order expressible ordered queries in the three classes of ordered conjunctive queries. This research sheds light on the possibility of implementing a complete set of ordered operators in relational databases to solve the performance problem of order-relevant queries.

Many incidents have occurred because industries have ignored past incidents or failed to learn lessons from the past. Incident databases provide an effective option for managing large amounts of information about the past incidents. Analysis of data stored in existing databases can lead to useful conclusions and reduction of chemical incidents and consequences of incidents. An incident database is a knowledge based system that can give an insight to the situation which led to an incident. Effective analysis of data from a database can help in development of information that can help reduce future incidents: cause of an incident, critical equipment, the type of chemical released, and the type of injury and victim. In this research, Hazardous Substances Emergency Events Surveillance (HSEES) database has been analyzed focusing on manufacturing events in Texas from 1993-2004. Between thirteen to sixteen states have participated in the HSEES incident reporting system and it does not include all the near miss incidents. Petroleum related incidents are also excluded from the HSEES system. Studies show that HSEES covers only 37% of all incidents in the US. This scaling ratio was used to estimate the total universe size.

Thesis ( M.L.A.) -- University of Texas at Arlington, 2008.

Thesis (Ph. D.)--University of Texas at Austin, 1999. / Vita. Includes bibliographical references (leaves 97-103). Available also in a digital version from Dissertation Abstracts.