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The issue under investigation in this study is to explore the drivers and suggest methods for environmental managers to integrate environmental issues in the top management strategic decision-making. In order to make the reading easy the whole study has been written following the principle of providing the minimum information to clarify the point under discussion, no more, no less. The conclusions, the analysis, the implications and the limitations are discussed on a chapter by chapter basis, making it easier for the reader to remember the issue under discussion. The closing chapter brings together the conclusions of each chapter of the study. The study is divided into two parts. Part I: Planning describes the planning and preparation for the research and consists of the following chapters: Chapter 1 provides an overview of the interest, relevance and importance of this study. Also it proposes, through the introduction of the relevant literature, an exact wording for the research problem and a framework for evaluating the effectiveness of each process step. Chapters 2 and 3 describe and justify the chosen framework that prompts managers during interviewing and organises the resulting contents in a way that will support effective decision making. This is the end of the planning part of the study and we now move into the action part where the case studies are explained in full. Part II: Intervention comprises the following chapters: Chapter 4 is where the action begins, the first phase of the process. This chapter discusses the reasons selection and participation in the research and the process for choosing a business unit. Chapter 5 details, justifies and discusses the choices of who to interview. It outlines how the interviews were conducted and summarises the resulting contents. In Chapter 6 the general issue of who to involve in interviews is explored further for the specific case of the environmental manager. The main objective is to discuss whether and why the environmental manager had more/less/different ideas from the rest of the management team. Chapter 7 deals with the first time that the people meet as a group. For this process step the choices were about how to display and generate discussion on the contents gathered during the interviews. Chapter 8 focuses on the environmental manager’s contribution to the objective Fine-tuning discussion. Chapter 9 describes the Indicator Building process and how this may be relevant for the environmental manager. Concluding Remarks wraps up the results and discusses the need for extending this research further.
This paper-based dissertation deals with the concepts of economic heterogeneity and environmental uncertainty from different perspectives, and at multiple levels of abstraction. At its core sits the observation that heterogeneity and uncertainty are deeply entangled, for there would be no uncertainty without heterogeneity of options to act regarding multiple future states of the world. At the same time, heterogeneity - in the form of diversification - has been suggested as a way to reduce uncertainty in portfolio theory (Markowitz 1952). The dissertation evolves around two research foci: (1) methodological implications of heterogeneity of scientific theories in the face of empirical data (Paper 1), and (2) two different forms of uncertainty are considered, environmental risk (Paper 2) and Knightian uncertainty (Paper 3). Paper 1 develops a new framework for model selection for the special case of fitting size distribution models to empirical data. It combines Bayesian and frequentist statistical approaches with the criterion of model microfoundation, which is to select, all other things considered being equal, the model that comes with a suitable micromodel, that explains, from the perspective of the individual constituent, the genesis of the overall size distribution. The approach is subsequently illustrated with size distribution data on commercial cattle farms in Namibia. We find that the double-Pareto lognormal distribution fits the data best. Our approach might have the potential to reconcile one of the oldest debates in current economics, i.e. the one about the best model to describe and explain the distribution of economic key variables such as income, wealth and city sizes in a country. The second paper revisits the Namibian commercial cattle farm data and uses it to put some theories from the agricultural economics literature regarding farm management under environmental risk to an empirical test. We focus on the relations between inter-annual variability in rainfall (environmental risk), risk preferences, farm size and stocking rate. We demonstrate that the Pareto distribution - which separates the distribution into two parts - is a statistically plausible description of the empirical farm size distribution when ´farm size´ is operationalized by herd size, but not by rangeland area. A statistical group comparison based on the two parts of the Pareto distribution shows that large farms are on average exposed to significantly lower environmental risk. Regarding risk preferences, we do not find any significant differences in mean risk attitude between the two branches. Our analysis confirms the central role of the stocking rate as farm management parameter, and shows that environmental risk and the farmer´s gender are key variables in explaining stocking rates in our data. Paper 3 develops a non-expected-utility approach to decision making under Knightian uncertainty which circumvents some of the conceptual problems of existing approaches. We understand Knightian uncertainty as income lotteries with known payoffs but unknown probabilities in each outcome. Based on seven axioms, we show that there uniquely (up to linear-affine transformations) exists an additive and extensive function from the set of Knightian lotteries to the real numbers that represents uncertainty preferences on the subset of lotteries with fixed positive sum of payoffs over all possible states of the world. We define the concept of uncertainty aversion such that it allows for interpersonal comparison of uncertainty attitudes. Furthermore, we propose Renyi´s (1961) generalized entropy as a one-parameter preference function, where the parameter measures the degree of uncertainty aversion. We illustrate it with a simple decision problem and compare it to other decision rules under uncertainty (maximin, maximax, Laplacian expected utility, minimum regret, Hurwicz).