Thesis (Ph. D.)--University of Texas at Austin, 2004. / Supervisor: Ehud Ronn. Vita. Includes bibliographical references and index.

published_or_final_version / Business Administration / Master / Master of Business Administration

There is large body of research that has investigated inter-firm technology transfer and technological learning within direct producer-user relationships within the context of developing countries. However, due to the growth in the technology transfer market, there has also been an increasing tendency for users to become isolated from producers, as new actors have emerged, which have been named technology intermediaries. The motivation for this thesis is driven by the absence of both theoretical and empirical studies examining technology transfer and learning through intermediaries, particularly in emerging nation contexts, what factors influence the functions of intermediaries along the process, and how those factors influence the recipients' learning. By learning from the technology transfer experiences of the two main users of technologies in the Omani oil and gas sector, namely Petroleum Development Oman (PDO), and Oman Liquefied Natural Gas (OLNG), this research tries to address this theoretical and empirical gap. Through semi-structured interviews, this study explored technological learning during the technology transfer through intermediaries from the perspective of 48 employees (Omani and expatriates) at different levels of hierarchy (managers, section heads/team leaders, site engineers) and from different departments across the two firms. The perspectives of those employees are supplemented by data such as annual reports, which also serves as important triangulation instruments to validate the data collected from respondents. Within-cases and cross-cases qualitative and interpretive content analysis was employed to analyse the empirical data gathered from the two firms. The empirical evidence identified five main factors that influence the functions of intermediaries along the transfer process. These are the proximity of intermediaries with users (geographical and cognitive), specialization of intermediaries (industrial or technological), characteristics of technologies (tacitness, complexity, newness), recipient firm's absorptive capacity, and recipients firm's technology strategy. A good understanding of these factors can increase the ability of firms to reap the maximum potential of inward technology transfer for local learning through intermediaries.

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Business under-performance in the upstream oil and gas industry, and the failure of many decisions to return anticipated results, has led to a growing interest over the past few years in understanding the impacts of current decision-making tools and processes and their relationship with decision outcomes. Improving oil and gas decision-making is thus, increasingly, seen as reliant on an understanding of what types of decisions are involved and how they actually are made in the “real world”. There has been significant work carried out within the discipline of cognitive psychology, observing how people actually make decisions. However, little is known as to whether these general observations apply to decision-making in the upstream oil and gas industry. Nor has there been work on how the results might be used to improve decision-making in the industry. This research is a step towards filling this gap by developing two themes – decision-making process and decision type. It distils a “real world” oil and gas decision-making model together with a theoretical decision-making model. Comparing and contrasting the two models yields several prescriptions for improved decision-making in the upstream oil and gas industry. This research also documents the development of an oil and gas decision making taxonomy that lays a decision space within which to judge the processes of decision-making. The taxonomy builds on established ideas in the human decision-making literature, but is itself novel, and involves four different dimensions: 1) complexity; 2) task constraint; 3) value functions; and 4) structure of the information environment. A primary observation is that decision-making processes are tailored to the various types of decisions. It is argued that maximising the chances of a good outcome in “real world” decisions requires the implementation of such tailoring. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1298439 / Thesis (Ph.D.) - University of Adelaide, Australian School of Petroleum, 2007

Universiẗat, Diss., 2005/2006.

In the offshore oil and gas industry in the UK, one of the most common forms of structure is the fixed steel jacket type of offshore platform. These are highly redundant structures subject to many random or uncertain factors. In particular, they are subject to uncertainties in the load distribution through the components, and to time-varying and cyclic loads leading to deterioration through fatigue. Operators are required to ensure the integrity of these structures by carrying out periodic inspections and repairing when necessary. Decisions on inspection, repair and maintenance (IRM) actions on structures involves making use of various tools and can be a complex problem. Traditionally, engineering judgement is employed to schedule inspections and deterministic analyses are used to confirm decisions. The use of structural reliability methods may lead to more rational scheduling of IRM actions. Applying structural reliability analysis to the production of rational inspection strategies, however, requires understanding the inspection procedure and making use of the appropriate information on inspection techniques. There are difficulties in collecting input data and the interpreted results need to be combined to form a rational global solution for the structure which takes into account practical constraints. The development of a knowledge base system (KBS) for reliability based inspection scheduling (RISC) provides a way of making use of complex quantitative objective analyses for scheduling. This thesis describes the development of a demonstrator RISC KBS. The general problems of knowledge representation and scheduling are discussed and schemes from Artificial Intelligence are proposed. Additionally, a system for automated inspection is described and its role in IRM of platforms is considered. A RISC System integrating suitable databases with fatigue fracture mechanics based reliability analysis within a KBS framework will enable operators to develop rational IRM scheduling strategies.

This study examines the relationships between entrepreneurial orientation (EO) and four sub-dimensions of corporate governance structures (CGS) in a sample of 173 senior decision-makers representing companies in the South African oil and gas industry. The four attributes of CGS include: board effectiveness and competence, board knowledge and experience, board commitment and recognition of complexities and board involvement in decision-making processes. A series of Canonical correlation analyses assess the strength of relationships between the dimensions of EO and CGS at both univariate and multivariate levels. The results of this study support a positive significant relationship between EO dimensions namely, innovation, proactiveness and risk-taking; and the dimensions of CGS namely, board effectiveness and competence, board knowledge and experience, board commitment and recognition of complexities, and board involvement in decision-making processes. It also indicates a positive link between EO and CGS. The synthesis gleaned from this study is based on the expansive literature review on EO and CGS which provided an insight on the existing knowledge on the relevance of EO in organisational growth and CGS with respect to the nature of the boards, executives and decision-makers roles and responsibilities in strategic entrepreneurial activities within the organisation. This study is of practical use to organisations, enabling them to think and act entrepreneurially, and to policy makers to assist them to keep track of the regulatory guidelines, adopted by boards and executives in monitoring and implementing entrepreneurial culture in their respective organisations. Finally, to researchers and academics, this study allows an extension of knowledge to the EO and CGS and its applicability in one distinct industrial context.

In the present quasi-experimental study, the relationships among individual executive characteristics, top management group processes, the business environment, and organizational performance for the gas and computer industries were investigated. Data were collected through a questionnaire using several published instruments measuring work locus of control, self-monitoring, group innovation/improvement, collaboration, and task management, environmental uncertainty, and perceptions of organizational performance. Return on assets data and sales data for several years were obtained from a business database. A total of 204 executives, 135 from the gas industry and 69 from the computer industry, returned completed questionnaires. Group processes were positively correlated with the average return on assets over three years. In addition, based on regression analyses, group processes predicted the average return on assets over three years. Work locus of control was positively correlated with group processes. However, none of the hypothesized moderator relationships were supported due to collinearity difficulties with one of the measures. Also, there were no differences between the gas and computer industries with regard to the uncertainty of the business environment.