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Institut
- Fakultät Wirtschaftswissenschaften (114) (entfernen)
Employee health is an important factor for individual and organizational performance. In particular the healthcare sector is characterized by high physical and mental demands that result in poor employee health and high levels of sick leave. One way to support employee health at the workplace is through leadership. By creating a healthy work environment and climate, leadership can promote employee health and well-being, in particular health-specific leadership. However, there has been scant insights into contextual factors that are relevant for health-specific leadership. This dissertation aims to investigate the relevance of contextual factors for health-specific leadership and its relationship with employee health. Three studies were conducted to identify relevant individual and work-related characteristics for health-specific leadership as well as to investigate the influence of specific individual and organizational factors. The first study is a questionnaire-based survey with 861 healthcare employees. Its findings show a positive relationship between health-specific leadership and employee health in the healthcare sector. Social demands and social resources are analysed as mediating factors. Furthermore, the affective commitment of employees is considered as an additional outcome of health-specific leadership. The second study identifies drivers and barriers for health-specific leadership in an explorative design based on 51 interviews with healthcare managers and collates these factors with the theoretical background. The findings show various influencing factors relating to leadership, employees, and the organization. The third study investigates the influence of individual factors on health-specific leadership and is based on a questionnaire survey among 525 healthcare employees. Managers personal initiative and employee self-care influence the relationship between health-specific leadership and employee burnout in different ways. In summary, this dissertation contributes to the literature by putting health-specific leadership into context and providing insights into influencing factors. The findings broaden the understanding of how health-specific leadership can influence employee health. The implications for theory and practice are discussed and directions for future research are outlined.
To be prepared for one´s own career is a major task during career development. However, existing research has primarily focused on adolescence in the transition from school to work while research on career preparation among university students, that are challenged by successfully transiting from university to work, are lacking so far. Thus, this cumulative dissertation studies career preparation in terms of career decidedness, planning, confidence, and career engagement using large samples of German university students and alumni as well as a variety of quantitative methods like latent state-trait analysis, cross-lagged analysis, and mediation analysis with multiple mediators. In the first paper, the stable component of career indecision is investigated with longitudinal data stemming from two samples with different time lags (Sample 1: N = 363, 7 weeks; Sample 2: N = 591, 6 months). Furthermore, the combined and unique effects of career indecisiveness and generalized indecisiveness on life satisfaction are examined using a sample consisting of 469 university students. Results indicate that career indecision is determined by a stable component (i.e., trait career indecisiveness) that is associated with lower core self-evaluations, lower occupational self-efficacy, and higher perception of career barriers. Additionally, results indicate that the stable career indecision component explains 5% of the variance in student life satisfaction beyond self-evaluated generalized indecisiveness. The second paper deals with the relationships of vocational interest characteristics - interest congruence, interest differentiation, and general interest level (elevation) - with several indicators of career preparedness (i.e., career planning, occupational self-efficacy beliefs, career decidedness, and career engagement) among a sample of 239 university students. Controlling for sociodemographic variables, multiple regression analyses revealed that differentiation is positively associated with career decidedness and career engagement and elevation is positively related to occupational self-efficacy beliefs and career engagement. The third paper investigates how protean career orientation (PCO) is related to vocational identity clarity and occupational self-efficacy. Study 1 reports a 1-year, three-wave cross-lagged study among 563 university students and established that PCO preceded changes in identity and self-efficacy - but not the other way around. Based on a 6-month longitudinal study of 202 employees, Study 2 shows that identity clarity and self-efficacy mediated the effects of PCO on career satisfaction and proactive career behaviors. PCO only possessed incremental predictive validity regarding proactive career behaviors. However, specific direct or mediated effects of PCO on job satisfaction could not be confirmed. The fourth paper explores the relationships between narcissism and two indicators of career success (i.e., salary and career satisfaction) among a group of young professionals (N = 314). A model proposing that the effect of narcissism on career success is mediated by increased occupational self-efficacy beliefs and career engagement was assessed. While correlations between narcissism and the two indicators of career success were minimal, the results show a significant indirect effect on salary via occupational self-efficacy and indirect effects on career satisfaction via self-efficacy and career engagement. Overall, the different studies corroborate the crucial role of career preparation for a successful start into working life. In sum, this dissertation contributes to literature on vocational psychology by providing novel insights in terms of facilitators and outcomes of career preparation among university students and graduates. Theoretical and practical implications are discussed, and promising directions for future research are identified.
Corporate Social Responsibility (CSR) has been established in recent years as an essential component of the economic system, demanded and promoted by a wide variety of stakeholder groups. The present dissertation shows that organizations face major communicative challenges with regard to CSR. CSR is not only determined by organizations themselves, but rather arises in the interplay with economic and social discourses. It is assumed that boundarys of organizational action are under constant change, so that CSR actors inevitably initiate constitutive communication processes. The resulting polyphony requires an understanding of the underlying communication processes. Hence, the performative character of CSR communication is taken up by this dissertation and thus the constitution of both the communicating actors and their relationships in the network is illustrated. The presented scientific papers are united by the overarching assumption that communication does not accompany and describe organizational action, but unfolds its own power.
Detecting and Assessing Road Damages for Autonomous Driving Utilizing Conventional Vehicle Sensors
(2021)
Environmental perception is one of the biggest challenges in autonomous driving to move inside complex traffic situations properly. Perceiving the road's condition is necessary to calculate the drivable space; in manual driving, this is realized by the human visual cortex. Enabling the vehicle to detect road conditions is a critical and complex task from many perspectives. The complexity lies on the one hand in the development of tools for detecting damage, ideally using sensors already installed in the vehicle, and on the other hand, in integrating detected damages into the autonomous driving task and thus into the subsystems of autonomous driving. High-Definition Feature Maps, for instance, should be prepared for mapping road damages, which includes online and in-vehicle implementation. Furthermore, the motion planning system should react based on the detected damages to increase driving comfort and safety actively. Road damage detection is essential, especially in areas with poor infrastructure, and should be integrated as early as possible to enable even less developed countries to reap the benefits of autonomous driving systems. Besides the application in autonomous driving, an up-to-date solution on assessing road conditions is likewise desirable for the infrastructure planning of municipalities and federal states to make optimal use of the limited resources available for maintaining infrastructure quality. Addressing the challenges mentioned above, the research approach of this work is pragmatic and problem-solving. In designing technical solutions for road damage detection, the researchers conduct applied research methods in engineering, including modeling, prototyping, and field studies. They utilize design science research to integrate road damages in an end-to-end concept for autonomous driving while drawing on previous knowledge, the application domain requirements, and expert workshops. This thesis provides various contributions to theory and practice. The investigators design two individual solutions to assess road conditions with existing vehicle sensor technology. The first solution is based on calculating the quarter-vehicle model utilizing the vehicle level sensor and an acceleration sensor. The novel model-based calculation measures the road elevation under the tires, enabling common vehicles to assess road conditions with standard hardware. The second solution utilizes images from front-facing vehicle cameras to detect road damages with deep neural networks. Despite other research in this area, the algorithms are designed to be applicable on edge devices in autonomous vehicles with limited computational resources while still delivering cutting-edge performance. In addition, the analyses of deep learning tools and the introduction of new data into training provide valuable opportunities for researchers in other application areas to develop deep learning algorithms to optimize detection performance and runtime. Besides detecting road damages, the authors provide novel algorithms for classifying the severity of road damages to deliver additional information for improved motion planning. Alongside the technical solutions, they address the lack of an end-to-end solution for road damages in autonomous driving by providing a concept that starts from data generation and ends with servicing the vehicle motion planning. This includes solutions for detecting road damages, assessing their severity, aggregating the data in the vehicle and a cloud platform, and making the data available via that platform to other vehicles. Fundamental limitations in this dissertation are due to boundaries in modeling. The pragmatic approach simplifies reality, which always distorts the degree of truth in the result.
Spitzenlastpreisbildung bei natürlichen Monopolen wurde bisher nur mit einer Produktionsstufe und konstanten Durchschnittskosten untersucht. Elektrischer Strom unterliegt jedoch einem mehrstufigen Produktionsprozeß, auf dem mindestens eine Stufe sinkende Durchschnittskosten aufweist. Ein privater, vertikal separierter Stromnetzbetreiber wird gewinnmaximale Spitzenlastpreise nehmen und aufgrund seiner Monopolstellung einen hohen Wohlfahrtsverlust verursachen. Das Papier untersucht in einem zweistufigen Modell mit sinkenden Durchschnittskosten auf der Transportstufe, wie sich das Verbot für den Netzmonopolisten, verschiedene Preise zu nehmen, auswirkt. In der beschriebenen Situation erhöht das Verbot, verschiedene Preise zu nehmen, die Wohlfahrt, wenn der Monopolist weiterhin beide Märkte (Peak und Off-Peak) bedient. Die untersuchte Regulierungsregel "nur ein Preis erlaubt" hat den Vorteil der einfachen Anwendung und Überwachung; sie ist somit praxistauglich und sehr kostengünstig.
This cumulative dissertation deals with the association between corporate governance, corporate finance and corporate tax avoidance in four scientific articles. The aim of this dissertation is to explain corporate tax avoidance by (a) focusing on corporate governance institutions as determinants of tax avoidance and (b) focusing on financial consequences of tax avoidance. Due to the close association between corporate governance and the concept of corporate social responsibility (CSR), the relationship between CSR and tax avoidance is also addressed. The first article using structured literature review methodology, analyzes extant research on the association between corporate governance and tax avoidance based on stakeholder-agency theory. However, also classical principal-agent theory is taken into account as its classical foundation. The first article identifies a number of open research questions and thereby serves as a theoretical basis for the subsequent articles. The second article also using structured literature review methodology, analyzes extant research on the association between CSR and tax avoidance. This article is also based on stakeholder-agency theory and identifies open research questions. The third article based on results of the first article, investigates tax avoidance by German private family firms as a specific variant of corporate governance, using an empirical quantitative approach. The article finds that (a) German private family firms avoid more tax than non-family firms, that (b) tax avoidance is positively associated with the capital stake of the family and that (c) tax avoidance is positively associated with the number of shareholders in both family and non-family firms. Results reinforce that corporate tax avoidance is associated to conflicts among the shareholders of private firms. The fourth article investigates the cost of debt of German public firms as a function of tax avoidance and tax risk. The article finds that (a) tax avoidance is negatively associated to the cost of debt, that (b) tax risk is positively associated to the cost of debt and that (c) the association between tax avoidance and the cost of debt becomes negative when a high level of tax risk is present.
The present work introduces four theoretical papers, which primarily focus on R&D, interindustrial linkages, and their policy implications. All in all, three issues basically motivated conception and realization: At first, previous NEG models do not incorporate endogenous R&D activities of firms. Existing models include R&D only in a growth context, which increases the formal complexity and departs from the simple core-periphery formulation. Second, vertical linkages are extensively considered in the class of international models. In face of its formal simplicity, the majority of publications refer to the standard model of Krugman and Venables (1995) utilizing intra-industry trade in which the manufacturing sector produces its own intermediates. However, the results are similar to the core-periphery model, but the implications of vertical linkages, especially in terms of specialization, cannot be reproduced. In contrast, the more challenging version of Venables (1996), which considers an inter-industry framework of an explicit upstream and downstream sector, is often cited (143 citations according to IDEAS/RePEc), but only few papers were directly built on it: Puga and Venables (1996), Amiti (2005), Alonso-Villar (2005). The third issue concerns the calibration of real economies. Although, hundreds of numerical simulations have been done in order to display the modeling outcomes, an application to particular industries in terms of their spatial formation and evolution is still a neglected field of research. Against this background, the present work aims to make a contribution to these topics. For a summary, all four papers are briefly to be summarized at this point. The first paper, entitled 'Too Much R&D? – Vertical Differentiation and Monopolistic Competition,' discusses whether product R&D in developed economies tends to be too high compared with the socially desired level. In this context, a model of vertical and horizontal product differentiation within the Dixit-Stiglitz (1977) framework of monopolistic competition is set up where firms compete in horizontal attributes of their products, and also in quality that can be controlled by R&D investments. The paper reveals that in monopolistic-competitive industries, R&D intensity is positively correlated with market concentration. Furthermore, welfare and policy analysis demonstrate an overinvestment in R&D with the result that vertical differentiation is too high and horizontal differentiation is too low. The only effective policy instrument in order to contain welfare losses turns out to be a price control of R&D services. The main contribution of this closed economy model in the course of the present work is a modeling framework, which can easily be adapted to the New Economic Geography. This has been approached in the second paper: ‘R&D and the Agglomeration of Industries' in which the seminal core-periphery model of Krugman (1991) is extended by endogenous research activities. Beyond the common ‘anonymous' consideration of R&D expenditures within fixed costs, this model introduces vertical product differentiation, which requires services provided by an additional R&D sector. In the context of international factor mobility, the destabilizing effects of a mobile scientific workforce are analyzed. In combination with a welfare analysis and a consideration of R&D promoting policy instruments and their spatial implications, this paper also makes a contribution to the brain-drain debate. In contrast to this migration based approach, the third paper 'Agglomeration, Vertical Specialization, and the Strength of Industrial Linkages' focuses on vertical linkages in their capacity as an additional agglomeration force. The paper picks up the seminal model of Venables (1996) and provides a quantifying concept for the sectoral coherence in vertical-linkage models of the New Economic Geography. Based upon an alternative approach to solve the model and to determine critical trade cost values, this paper focuses on the interdependencies between agglomeration, specialization and the strength of vertical linkages. A central concern is the idea of an 'industrial base,' which is attracting linked industries but is persistent to relocation. As a main finding, the intermediate cost share and substitution elasticity basically determine the strength of linkages. Thus, these parameters affect how strong the industrial base responds to changes in trade costs, relative wages and market size. The fourth paper 'The Spatial Dynamics of the European Biotech Industry' presents a simulation study of the R&D intensive biotech industry using the standard Venables model. Thus, it connects all three preceding papers and puts them into the real economic context of the European integration. The paper reviews the potential development of the European biotech industry with respect to its spatial structure. On the first stage, the present industrial situation as object of investigation is described and evaluated with respect to a further model implementation. In this context, the article introduces the findings of an online survey concerning international trade, conducted with German biotech firms in 2006. On the second stage, the results are completed by the outcomes of a numerical simulation within the New Economic Geography (NEG), considering vertical linkages between the biotech and pharmaceutical industries as an agglomerative force. The analysis reveals only a slight relocation tendency to the European periphery, constrained by market size, infrastructure and factor supply. In the final conclusions, central results of all four papers are summarized with respect to economic policy. Against the background of general legitimization and the impact of political intervention, Chapter 6 draws the main conclusions for location and innovation policies. In this regard, the industrial-base concept as well as the mobility of R&D play a central role during this discussion.
Decoding the psychological dimensions of human odor perception has long been a central issue of olfactory research. As odor percepts could not be linked to a few measurable physicochemical features of odorous compounds or physiological characteristics of the olfactory system, odor qualities have often been assessed by perception–based ratings. Although these approaches have been promising, none of the proposed system has sustained empirical validation. In a review of 28 studies, the authors assessed how basic characteristics of study design have been biasing perception–based classification systems: (1) interindividual differences in perceptual and verbal abilities of subjects, (2) stimuli characteristics, (3) approaches of data collection, and (4) methods of data analysis. Remarkably, many of the difficulties in establishing these systems have been rooted in one underlying issue: the puzzling relationship between language and olfaction in general. While the reference from odors to language is weak, the reverse impact of verbal processing on olfaction seems powerful. Odor perception is biased by verbal–semantic processes when cues of an odor's source are readily available from the context. At the same time, olfaction has been characterized as basically sensation driven when this information is absent. The authors examined whether language effects occur when verbal cues are absent and how expectations about an odor's identity shape odor evaluations. Subjects were asked to rate 20 unlabeled odor samples on perceptual dimensions as well as quality attributes and to eventually provide an odor source name. In a subsequent session, they performed the same rating tasks on a set of written odor labels that was compiled individually for each participant. It included both the 20 correct odor names (true labels) and – in any case of incorrect odor naming in the first session – the self–generated labels (identified labels). The authors compared odor ratings to ratings of both types of labels and found higher consistencies between the evaluation of an odor and its identified label than between the description of an odor and its true (yet not associated) label. These results indicate that basic perceptual as well as quality ratings are affected by semantic information about an odor's source – even in absence of source cues. That is, odor sensation may activate a semantic mental representation of an odorous object that affects odor processing and may in turn relate to further multimodal properties. That means, associations between odors and stimuli from other sensory modalities should not only be stable, but these mappings should be mediated by an odor’s identity. The authors asked subjects to visualize their odor associations on a drawing tablet, freely deciding on color and shape. Additionally, they provided a verbal label for each sample. Color mappings were odor-specific, they reflected the imagery of a natural source and seemed to change with assumed odor identity. Shape mappings changed with odor identifications as well, as drawings frequently displayed concrete objects that reflected visual features of an odor's source. The influence of verbal identity codes on quality ratings or crossmodal mappings is rooted in the very same problem that perception–based classification systems have tried to solve – a terminology that relates to abstract mental categories. The less specific we communicate, the more we need to resort to source–related analogies – in scientific endeavors and everyday life alike.
Corporate irresponsibility is often the result of intentionally irresponsible strategies, decisions, or actions, which negatively affect an identifiable stakeholder or environment. For instance, these range from the violation of the human rights and labor standards to environmental damages. Organizations enacting irresponsible practices rely on different factors upon multiple levels (field, organizational, individual) and its interrelations as well as processes evolving within the organization leading to such behavior. However, reasons for the occurrence of and explanations for corporate irresponsibility so far have been limited, leaving a fragmented understanding of this phenomenon. This dissertation helps to improve the understanding and explanation of corporate irresponsibility by identifying driving patterns of corporate irresponsibility and showing how the interactions across multiple levels add to this phenomenon. Chapter 1 provides an overview of the topic of corporate irresponsibility, the theoretical approaches of this dissertation and an introduction to the chapters. The second chapter offers a review and analysis of the corporate irresponsibility literature. The chapter presents a variance model outlining the concept, antecedents, moderators and outcomes of recent corporate irresponsibility literature as well as the different factors across levels (field, organizational, individual). Chapter 2 offers a critical analysis of what we know by referring to current literature and offers insights on what we don't know by deriving main implications for future research on corporate irresponsibility. Chapter 3 enlarges the understanding of corporate irresponsibility introducing a process approach to explain how corporate irresponsibility evolves over time and under which conditions. Based on a qualitative meta-analysis findings converge around two distinct process paths of corporate irresponsibility, the opportunistic-proactive, and, the emerging-reactive, subdivided into three phases. Chapter 3 sheds different lights upon the phases of corporate irresponsibility and its underlying mechanisms. The final chapter 4 focuses on different underlying mechanisms driving the final downfall or demise of organizations, organizational failure. Chapter 4 offers an alternative explanation to the competing extremism and inertia mechanisms driving organizational failure in recent studies by suggesting that these explanations are rather complementary. In addition, chapter 4 enlarges the explanation of organizational failure identifying the role of conflict mechanisms and its interplay with rigidity mechanisms. In sum, this dissertation contributes to a better understanding of what causes and increases corporate irresponsibility, and a better explanation of how and why corporate irresponsibility and organizational failure emerges, develops, grows or terminates over time.
Das Recht der Freileitung im Spannungsfeld planerischer, technischer und ökologischer Anforderungen
(2019)
Die Energiepolitik in Deutschland hat in den letzten Jahren umfassende Veränderungen erfahren. In den Fokus rücken dabei immer mehr die erneuerbaren Energien. Deren Anteil an der gesamten Energieerzeugung wird in Zukunft weiter ansteigen. Hintergrund ist die Umsetzung der klimapolitischen Ziele der Bundesregierung: Im Energiekonzept für eine umweltschonende, zuverlässige und bezahlbare Energieversorgung von 2010 wird eine Reduktion der Treibhausgasemissionen um 40% bis zum Jahr 2020 und bis zum Jahr 2050 sogar um 80% gegenüber dem Stand von 1990 angestrebt. Neben dem Energiekonzept der Bundesregierung stellen das Reaktorunglück von Fukushima und die damit verbundene Energiewende 2011 eine wesentliche Zäsur für die Energiepolitik in Deutschland dar. Die Folge war ein beschleunigter Ausstieg aus der Kernenergie sowie die sofortige Abschaltung von acht Kernkraftwerken. Neben der Laufzeitverkürzung und Stilllegung von Atomkraftwerken wurde auch das aus mehreren neuen Gesetzen und Gesetzesänderungen bestehende Energiepaket verabschiedet. Dort wurde mit der Einführung der §§ 12a ff. Energiewirtschaftsgesetz erstmalig eine bundesweite Bedarfsplanung für den Bau von Höchstspannungsleitungen festgelegt. Zudem erfolgte mit der Einführung des Netzausbaubeschleunigungsgesetzes Übertragungsnetz (NABEG) erstmalig ein bundesweit gültiges Gesetz für die Planung von Vorhaben auf der Ebene der Höchstspannungsnetze. Die vorliegende Arbeit untersucht vor diesem Hintergrund die Frage, ob durch die neu geschaffenen Regelungen des NABEG für Höchstspannungsleitungen eine Beschleunigung innerhalb des Planungsverfahrens erreicht werden kann und ob die mit dem NABEG verfolgten Ziele umgesetzt worden sind. Dabei wird aufgezeigt, wie sich die Zielsetzungen des NABEG zu denjenigen Zielen der im Rahmen der Abwägung der öffentlichen und privaten Belange zu beachtenden, sonstigen fachspezifischen Gesetzen verhalten. Der Beschleunigungsgedanke darf nicht dazu führen, dass umwelt-, immissionsrechtliche und sonstige fachgesetzliche Aspekte an Gewicht verlieren. Dabei werden auch mögliche Probleme der jetzigen Gesetzeslage beim Freileitungsausbau sowie weitere gesetzliche Möglichkeiten, die Beschleunigung des Netzausbaus zu erreichen, aufgezeigt.
Research on motivational and cognitive processes in entrepreneurship has commonly relied on a static approach, investigating entrepreneurs' motivation and cognition at only one point in time. However, entrepreneurs' motivation and cognition are dynamic processes that considerably change over time. The goal of this dissertation is thus to adopt a dynamic perspective on motivational and cognitive processes in entrepreneurship. In three different chapters, the work examines dynamic changes in the level and impact of three different processes, i.e., creativity, entrepreneurial passion, and opportunity identification. In Chapter 2, the thesis develops a theoretical model on the alternating role of creativity in the course of the entrepreneurial process. The model emphasizes that the effects of two components underlying creativity, i.e., divergent and convergent thinking, considerably change both in magnitude and in direction throughout the entrepreneurial process. In Chapter 3, the author establishs and empirically tests a theoretical model on entrepreneurial passion. The theoretical analysis and empirical results show that the relationships between feelings of entrepreneurial passion, entrepreneurial self-efficacy, and entrepreneurial success are dynamic and reciprocal rather than static and unidirectional. In Chapter 4, the author develops and tests a theoretical model on the effect of entrepreneurship training on opportunity identification over time. The theoretical and empirical investigation indicates that entrepreneurship training effects systematically decay over time and that action planning and entrepreneurial action sustain the effects in the long term.
Extracting meaningful representations of data is a fundamental problem in machine learning. Those representations can be viewed from two different perspectives. First, there is the representation of data in terms of the number of data points. Representative subsets that compactly summarize the data without superfluous redundancies help to reduce the data size. Those subsets allow for scaling existing learning algorithms up without approximating their solution. Second, there is the representation of every individual data point in terms of its dimensions. Often, not all dimensions carry meaningful information for the learning task, or the information is implicitly embedded in a low-dimensional subspace. A change of representation can also simplify important learning tasks such as density estimation and data generation. This thesis deals with the aforementioned views on data representation and contributes to them. The authors first focus on computing representative subsets for a matrix factorization technique called archetypal analysis and the setting of optimal experimental design. For these problems, they motivate and investigate the usability of the data boundary as a representative subset. The authors also present novel methods to efficiently compute the data boundary, even in kernel-induced feature spaces. Based on the coreset principle, they derive another representative subset for archetypal analysis, which provides additional theoretical guarantees on the approximation error. Empirical results confirm that all compact representations of data derived in this thesis perform significantly better than uniform subsets of data. In the second part of the thesis, the research group is concerned with efficient data representations for density estimation. The researchers analyze spatio-temporal problems, which arise, for example, in sports analytics, and demonstrate how to learn (contextual) probabilistic movement models of objects using trajectory data. Furthermore, they highlight issues of interpolating data in normalizing flows, a technique that changes the representation of data to follow a specific distribution. The authors show how to solve this issue and obtain more natural transitions on the example of image data.
Zusammenfassung Der vorliegende Bericht informiert über die Ergebnisse einer empirischen Studie zur Personalarbeit in wissenschaftlichen Buchverlagen. Als Grundlage der Erhebung dienten verschiedene theoretische Konzepte, die sich mit der Frage befassen, welche Grundmuster das Personalgeschehen von Unternehmen prägen. Das primäre Ziel unserer Studie bestand entsprechend darin, zu erkunden, inwieweit es gelingen kann – mit Hilfe einer Unternehmensbefragung – etwas über diese Grundmuster zu erfahren. Das Ergebnis stimmt zuversichtlich. Die theoretische Fundierung unserer Umfrage erwies sich als sehr tragfähig und empfiehlt sich für weiterführende und branchenübergreifende Vergleichsstudien. Leider war es uns an dieser Stelle noch nicht möglich, eine „großzahlige“ Erhebung durchzuführen, die Datenbasis, auf der unsere Ergebnisse beruhen, ist mit 12 Unternehmen denn auch einigermaßen schmal. Angesichts unserer Zielsetzung ist dies aber nur bedingt ein Mangel. Inhaltlich zeigt sich, dass die Personalpolitik der Verlage im Großen und Ganzen einem Schema folgt, das sich aus den branchentypischen Anforderungen ableitet. Andererseits findet man aber auch verlagsspezifische Akzentuierungen. In manchen Verlagen dominiert eher eine gemeinschaftliche Orientierung (in ihren jeweiligen Varianten), in anderen werden die leistungs- und managementorientierten Aspekte der Personalarbeit stärker betont.