Meta-Analysis in Finance: Applications and Advances

The volume of empirical research in finance exhibits a strong upward trajectory. On the one hand, the large number of research publications often produces contradictory results for the same phenomenon under examination. On the other hand, a credibility crisis calls into question the reliability of empirical research findings and the transparency of the academic research process that produces the results. Consequently, there is a need to objectively reflect and consolidate previous empirical research results and to correct biases that affect the validity of scientific evidence. Meta-analysis is a research approach that comes with this capability. Meta-analysis is a secondary research method used to synthesize existing empirical results, to detect and explain consistencies and inconsistencies among research findings, and to identify and filter out distorting effects related to publication selection and model misspecification. Although meta-analysis is a standard tool for research synthesis and evidence-based decision-making in many related research disciplines such as economics and management science, it has rarely been applied in finance. The aim of this thesis is to structurally introduce meta-analysis in finance as a complement to primary research and traditional narrative reviews by providing an objective and statistical approach to the accumulation of scientific knowledge. Chapter 2 provides a comprehensive overview of the opportunities that meta-analysis offers for finance research, recent applications of meta-analysis in finance, and the challenges and limitations associated with it. Chapter 3 presents an applied meta-analysis of 1,016 empirical effects obtained from 71 previous studies that estimate the impact of corporate financial hedging on firm value. In Chapter 4, a Monte Carlo simulation is conducted to compare the statistical properties of common weighting schemes in meta-regression analysis under the practical condition that multiple and dependent estimates are reported in the same study, which is the norm in finance. By introducing, applying, and further advancing meta-analysis in the context of finance research, this thesis aims to increase the awareness and acceptance of meta-analysis as well as to promote its future application in the field

Process Mining: Why You Need It?

For as long as Information Systems (IS) field has existed, it has had an active interesting understanding and enhancing organizational as well as business processes. In 1970’s the research focused on streamlining processes for administrative control and to improve banking operations. The term Business Process Management (BPM) and Business Process Reengineering (BPR) has since evolved and often used as a catch-all terms for a variety of domains dealing with process orientation. Information System has often struggled to explain interaction of business value, processes, and IT systems. The results of IT investments on productivity and business value have been mixed and inconclusive and the theoretical lens behind these studies remain fragmented. Emergence of the new set of techniques, namely process mining has the potential unlock the mechanism behind value creation enabled by information systems as well as explain it from a theoretical standpoint. It can open new possibilities for businesses as well as IS discipline and modify its approach to BPM/BPR from teaching and research standpoint. Process mining promises to go beyond traditional Business Process Modeling Notation (BPMN) and Lean/Six Sigma approaches. The potential of process mining lies in the fact that it leverages the underlying information systems like Enterprise Resource Planning (ERP). Instead of guessing or deducting business processes in an abstract manner, businesses now can discover/reverse-engineer their process flow and find deviations from the desired flow. Commercial applications have given rise to firms like Celonis, Signavio and many others. This TREO talk is aimed at making IS academics aware of this rapidly growing field and opportunities and challenges it preset to Information Systems (IS) in terms of research and teaching. The presentation will focus on evolution of process mining, avenues to get involved in process mining research, and diverse ways to incorporate in IS curriculum to bolster and future-proof B-school course offerings

Process Selection in RPA Projects – Towards a Quantifiable Method of Decision Making

The digital age requires companies to invest in value-creating rather than routine activities to drive innovation as a future source of competitiveness and business success. Thus, many companies are reluctant to invest in large-scale, costly backend integration projects and seek adaptable solutions to automate their front-office activities. Bridging artificial intelligence and business process management, robotic process automation (RPA) provides the promise of robots as a virtual workforce that performs these tasks in a self-determined manner. Many studies have highlighted potential benefits of RPA. However, little data is available on operationalizing and automating RPA to maximize its benefits. In this paper, we shed light on the automation potential of processes with RPA and operationalize it. Based on process mining techniques, we propose an automatable indicator system as well as present and evaluate decision support for companies that seek to better prioritize their RPA activities and to maximize their return on investment

Reporting guidelines for meta-analysis in economics

Meta‐analysis has become the conventional approach to synthesizing the results of empirical economics research. To further improve the transparency and replicability of the reported results and to raise the quality of meta‐analyses, the Meta‐Analysis of Economics Research Network has updated the reporting guidelines that were published by this Journal in 2013. Future meta‐analyses in economics will be expected to follow these updated guidelines or give valid reasons why a meta‐analysis should deviate from them

Einsatz der Celonis Intelligent Business Cloud in der Lehre

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