A Critical Investigation into Identifying Key Focus Areas for the Implementation of Blockchain Technology in the Mining Industry

Thesis (PhD)--University of Pretoria, 2023.The value of digital information is ever-increasing as more companies utilize digital technologies such as Artificial Intelligence (AI) and the Internet of Things (IoT) to gain deeper insight into their business operations and drive productivity gains. It is therefore important to safeguard and ensure the integrity of digital information exchange. Blockchain technology (BCT) was identified as potentially providing the mining industry with a trusted system for securely exchanging digital value. However, there is little evidence or understanding of how/where BCT can be implemented and what benefits the industry could obtain. This research study provides a fundamental understanding of what the technology is in order to identify the associated capabilities and potential application benefits for the mining industry. From a technology push perspective, blockchain capabilities are used to evaluate how the technology’s value drivers map to the mining industries core value chain processes. This was done to identify potential focus areas within the mining enterprise for further research and development of blockchain applications.ARMMining EngineeringMEngUnrestricte

Unemployment in Germany: Reasons and Remedies

This paper discusses the reasons for the dismal labor market performance of Germany over the last three decades along with potential remedies. It argues that labor market rigidities along with a generous welfare state in conjunction with certain changes in the economic environment are important in explaining this development but cannot solely account for it. Barriers to entrepreneurship, to setting up new firms and to innovations which are prevalent on goods and capital markets also play an important role in explaining the lackluster German economic performance of which rising unemployment is only one part. Comprehensive institutional reforms are therefore called for.unemployment, Germany, labor market reforms, venture capital, innovations

Asset Ownership and Foreign-Market Entry

This paper examines the link between a firm’s ownership of productive assets and its choice of foreign-market entry strategy. We find that, controlling for industry- and country-specific characteristics, the most productive firms (i.e., those owning the most assets) will enter through greenfield investment, less productive ones will choose M&A, and the least productive ones will export. In addition, the most productive firms are shown to prefer whole ownership to a joint venture. These predictions are confirmed in an econometric analysis of Japanese firm-level data.foreign direct investment, merger and acquisition, joint venture, greenfield investment, firm heterogeneity, productivity

Data-driven & Theory-driven Science : Artificial Realities and Applications to Savings Groups

Paper I and Paper II is not published yet. They are excluded from the dissertation until they will be published.The scientific process is neither unique nor nomic. Two processes of scientific inquiry are theory-driven and data-driven science. This dissertation analyzes savings groups using theory-driven and data-driven methods. Simulated realities-based on data-driven theory-are used to understand the emerging dynamics of savings groups. Savings groups are grassroots, community-based organizations composed of 15 to 30 members. These organizations-usually supported by international development agencies-have weekly meetings during a cycle of operations that typically lasts a year. In the groups, savings are kept in two funds: a fund for loans and a social welfare fund that covers life-cycle events. The findings of Papers A to D in this dissertation provide new large-sample evidence about savings groups, their dynamics, and the factors affecting their financial performance. In practice, the results of Paper A to D shed light on the best policies to promote sustainable development with informal finance in a cost-effective way. A theory-driven approach indicates that the social fund in savings groups stimulates loan allocation among risk-sharing members, while implicitly covering idiosyncratic risks (Paper A). A data-driven approach based on Bayesian data-mining reveals that the macroeconomic environment and the facilitation model of development agencies have a strong influence on the profit-generating capacity of savings groups (Paper B). Machine-learning methods further show that business training is not the most frequent program implemented by development agencies, but it is in fact the most powerful intervention to encourage profits, particularly when a development agency stops working with a group and leaves a community (Paper C). Finally, the simulation of a village with artificial agents indicates that the businesses of savings groups can have higher profits due to the consolidation of social capital and the competitive advantage created through a process of homophily (Paper D). Metatheoretically, the theory-driven and data-driven approaches of this dissertation-and the complementarity between these approaches-contribute to the epistemology of data-intensive science. The dissertation concludes that the gelstaltic and quasi-teleological explanations of the data-driven approach help to the formulation of theories through inductive and abductive reasoning.publishedVersio

The importance of fraud detection techniques from the Enron case and the T.J. Maxx data breach

This thesis examines the issue of fraud detection and its causes and solutions. After a description of two fraudulent cases Enron scandal (internal fraud), and T.J. Maxx Data Breach (external fraud), it discusses the causes of these two fraud cases using Cressey’s “fraud triangle” theory and Albrecht’s three-stage theory. It then describes various fraud detection techniques in internal and external fraud. Finally, the recommendations for the improvements of both internal and external fraud detection systems are explained

A New Capital Regulation For Large Financial Institutions

We design a new, implementable capital requirement for large financial institutions (LFIs) that are too big to fail. Our mechanism mimics the operation of margin accounts. To ensure that LFIs do not default on either their deposits or their derivative contracts, we require that they maintain an equity cushion sufficiently great that their own credit default swap price stays below a threshold level, and a cushion of long term bonds sufficiently large that, even if the equity is wiped out, the systemically relevant obligations are safe. If the CDS price goes above the threshold, the LFI regulator forces the LFI to issue equity until the CDS price moves back down. If this does not happen within a predetermined period of time, the regulator intervenes. We show that this mechanism ensures that LFIs are always solvent, while preserving some of the disciplinary effects of debt.Banks, Capital Requirement, Too Big to Fail