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Institute
- Fakultät Wirtschaftswissenschaften (38) (remove)
The choice to continue working until or even beyond retirement is a function of the interplay of factors on micro, meso, and macro levels. Research within this area has grown significantly over the last years. I contribute to this line of research with the studies conducted within the scope of this cumulative habilitation thesis. More specifically, the aim of the research presented here is to add to the literature on later life work with the investigation of individual (micro level) as well as job and organizational (meso level) factors that have the potential to contribute to prolonged working lives. I was guided by the general research interest on how individual, job, and organizational factors contribute to later life work, and more specifically to retirement timing and work-related activities beyond normal retirement age. My research was directed by the following research questions: (1) What is the work activity potential of older people in Germany and what characterizes different types of later life work potential? (2) Which role do individual psychological factors such as personality, values, and beliefs play in the context of later life work? (3) How do specific job characteristics interact or align with individual psychological factors with regard to later life work? (4) What characterizes a holistic organizational approach to later life work that helps the alignment of the work environment to older workers’ (individual) needs and abilities?
Following an introduction, I give an overview on the theoretical framework of my research in Chapter 2 (“Theoretical Background”). I describe the conceptualization of later life work before I go into multilevel antecedents of later life work and present key theoretical approaches to a person-environment fit perspective of later life work. In the following four chapters, I present ten studies corresponding to the ten scientific publications that constitute the basis of the cumulative habilitation thesis.
In Chapter 3 (“Later Life Work: Work Activity Potential”) I present research on the extent as well as different types of later life work potential in Germany to describe the context for most of my research. With the two studies presented here (Büsch, Zohr, Brusch, Deller, Schermuly, Stamov-Roßnagel, & Wöhrmann, 2015; Mergenthaler, Wöhrmann, & Staudinger; 2015), I also intend to provide answers to the research question on the later life work potential in Germany and the characteristics of different later life work potential constellations. In Chapter 4 (“Later Life Work: Individual Psychological Factors”) the role of stable as well as malleable individual psychological factors for later life work is explored in two studies (Fasbender, Wöhrmann, Wang, & Klehe, 2019; Wöhrmann, Fasbender, & Deller, 2016). Thus, with the studies presented in this chapter, I contribute to the research question on the role of individual psychological factors in the context of later life work. In Chapter 5 (“Later Life Work: Job Characteristics Corresponding to Older Workers’ Needs and Abilities”) I present three studies exploring the interplay of individual factors and job characteristics for later life work to address the research question on the interaction or alignment of specific job characteristics with individual psychological factors with regard to later life work (Pundt, Wöhrmann, Deller, & Shultz, 2015; Wöhrmann, Brauner, & Michel, 2020; Wöhrmann, Fasbender, & Deller; 2017). Chapter 6 (“Later Life Work: A Holistic Organizational Approach”) reports the development of the Later Life Workplace Index (LLWI) as a multidimensional tool to holistically assess organizational practices and working conditions targeted at the promotion of later life work through the maintenance and enhancement of older employees’ health, work ability, and motivation (Wilckens, Wöhrmann, Adams, Deller, & Finkelstein, 2020; Wilckens, Wöhrmann, Deller, & Wang, 2020; Wöhrmann, Pundt, & Deller, 2018. With the LLWI, I intend to provide an answer to the research question on the characteristics of a holistic organizational approach to later life work that helps the alignment of the work environment to older workers’ (individual) needs and abilities. Finally, in Chapter 7 (“General Discussion”) I discuss the contributions, implications, and limitations of my research presented here.
This doctoral thesis deals with the topic of organizational misconduct and covers the three salient research streams in this area by addressing its performance outcomes, antecedents, and preventive measures. Specifically, it is concerned with the question of how different forms of misconduct are reflected in the stock performance of related organizations, thereby, covering the three pillars of corporate sustainability environmental, social, and governance (ESG). Furthermore, it aims to conceptualize how individual cognitive biases may lead to misconduct, therefore, potentially representing an antecedent and how existing management control systems can be enhanced to effectively address specific forms of misconduct, respectively.
To these ends, I first review the research stream of stock price reactions to environmental pollution events in terms of the underlying research samples, methodological specifications, and theoretical underpinnings. Based on the findings of the systematic literature review (SLR), I perform three stock-based event studies of the Volkswagen diesel emissions scandal (Dieselgate), workplace sexual harassment (#MeToo accusations), and the 2003 blackout in the US to cove the three ESG dimensions, respectively. In line with the SLR, my event studies reveal substantial stock losses to firms involved in misconduct that are eventually even accompanied by a spillover effect to uninvolved bystanders.
Then, I review the extant literature conceptually to develop a framework outlining how moral licensing as an individual cognitive bias might lead to a self-attribution of corporate sustainability, a consecutive accumulation of moral credit, and a later exchange of this credit by engaging in misconduct afterward.
Finally, I assess existing workplace sexual harassment management controls, such as awareness training and grievance procedures critically in another conceptual analysis. Based on the shortcomings stemming from management controls’ focus on compliance and negligence of moral duties, I introduce five specific nudges firms should consider to enhance their existing management controls and eventually prevent occurrences of workplace sexual harassment.
Based on the six distinct articles within this doctoral thesis, I outline its limitations and point at directions for future research. These mainly address providing further evidence on the long-term performance effects of organizational misconduct, enriching our knowledge on further cognitive biases eventually leading to misconduct, and conceptualizing nudging beyond the use-case of workplace sexual harassment.
Consisting of three articles and a framework manuscript, this cumulative dissertation deals with sustainable compensation of chief executive officer (CEO) with a focus on climate-related aspects. Against the backdrop of the European action for sustainability and the EU Green Deal, the dissertation pays special attention to the consideration of climate-related aspects of corporate performance in CEO compensation. In this context, sustainable compensation is characterized by the consideration of long-term interests and sustainability of the company as well as by the inclusion of financial and non-financial aspects of environmental, social and governance performance (ESG) in compensation agreements. While this novel instrument of corporate governance aims to incentivize the implementation of sustainability-oriented corporate strategy, it is particularly important to unfold this incentive effect at the individual CEO level in view of their managerial discretion. The framework manuscript discusses the research objectives, the regulatory and theoretical background, the results of the dissertation and their implications in the context of regulation, research, and business practice. The essence of the dissertation are the three articles. The first article, "Determinants and effects of sustainable CEO compensation: a structured literature review of empirical evidence," examines the current state of empirical research based on 37 articles that were published between 1992 and 2018. Based on a multidimensional research framework, the structured literature review compiles past research findings, identifies contentual and methodological foci in the research area, and derives questions for future research. The second article, "Mapping the determinants of carbon-related CEO compensation: a multidimensional approach," addresses the topic from a conceptual perspective. Taking the existing work as a starting point, a conceptual framework is derived, which organizes the determinants of carbon-related CEO compensation at societal, organizational, group and individual levels of analysis. On this basis, eight propositions are presented that seek to distinguish between the determinants which support and challenge the implementation of carbon-related CEO compensation. The third article, "Climate change policies and carbon-related CEO compensation systems: an exploratory study of European companies," focuses on the use of CO2-oriented performance indicators in CEO compensation. The empirical-qualitative study analyzes corporate disclosure of the 65 largest companies in the EU for the years 2018 and 2019. The study addresses the use of CO2-oriented performance indicators in corporate strategy and CEO compensation. It also examines which compensation components are determined with the help of CO2-oriented performance indicators, which type of performance indicators are used, and whether CO2-intensive and less CO2-intensive companies differ in this regard.
Understanding that entrepreneurship can be better modeled from a systemic point of view is a primordial aspect that determines the important role of universities in entrepreneurial ecosystems. What makes the ecosystem approach a valuable tool for understanding social
systems is that, from a holistic perspective, their behavior seems to have emerging characteristics. The impact of this “research object” can only be revealed through interrelated causal chains similar to the behavior of natural ecosystems (Mars et al., 2012). Therefore, the
entrepreneurial ecosystem concept provides a unique perspective that complements previous studies on networked economic activity with a clear focus on the systemic elements that support entrepreneurship, and an emphasis on policy that promote the entrepreneurial process.
This dissertation presents a dual scientific account of the entrepreneurship phenomenon in universities. The work is divided into two equal parts, each of which is composed of two research papers. The narrative of the first half takes on a macro perspective view, consisting of one theoretical and one empirically-based conceptual case study. This part conceptually depicts a systematic approach to entrepreneurialism in higher education, namely an ecosystems
perspective. The second half concentrates on the meso- and micro levels of study from the university’s point of view, comprising of a case study as historical account for the emergence of the entrepreneurial university, and of a metasynthesis of empirical case studies in entrepreneurial universities, which serves as the basis for the development of entrepreneurial university archetypes.
This doctoral work contributes to an in-depth understanding of Entrepreneurship in universities regarding its systemic qualities and archetypal characteristics of entrepreneurial universities. It argues for an ecosystem’s perspective on the phenomenon of entrepreneurial
activity, highlighting the fundamental role that universities play as the heart of entrepreneurial ecosystems. Furthermore, this research expands on the novel concept of the entrepreneurial university by using extensive case study literature to empirically identify distinct archetypes that better reflect the diverse reality of how universities engage as entrepreneurial actors by way of differentiated entrepreneurial structures, systems, and strategies.
The wide accessibility of the Internet and web-based programs enable an increased volume of online interventions for mental health treatment. In contrast to traditional face-to-face therapy, online treatment has the potential to overcome some of the barriers such as improved geographical accessibility, individual time planning, and reduced costs. The availability of clients’ treatment data fuels research to analyze the collected data to obtain a better understanding of the relationship among symptoms in mental disorders and derive outcome and symptom predictions. This research leads to predictive models that can be integrated into the online treatment process to assist clinicians and clients.
This dissertation discusses different aspects of the development of predictive modeling in online treatment: Categorization of predictive models, data analyses for predictive purposes, and model evaluation. Specifically, the categorization of predictive models and barriers against the uptake of mental health treatment are discussed in the first part of this dissertation. Data analysis and predictive modeling are emphasized in the second part by presenting methods for inference and prediction of mood as well as the prediction of treatment outcome and costs. Prediction of future and current mood can be beneficial in many aspects. Inference of users’ mood levels based on unobtrusive measures or diary data can provide crucial information for intervention scheduling. Prediction of future mood can be used to assess clients’ response to the treatment and expected treatment outcome. Prediction of the expected treatment costs and outcomes for different treatment types allows simultaneous optimization of these objectives and to increase the cost-effectiveness of the treatment. In the third part, a systematic predictive model evaluation incorporating simulation analyses is demonstrated and a method for model parameter estimation for computationally limited devices is presented.
This dissertation aims to overcome the current challenges of predictive model development and its use in online treatment. The development of predictive models for varies data collected in online treatment is demonstrated and how these models can be applied in practice. The derived results contribute to computer science and mental health research with client individual data analysis, the development ofpredictive models, and their statistical evaluation.
Analysis of user behavior
(2020)
Online behaviors analysis consists of extracting patterns from server-logs.
The works presented here were carried out within the “mBook” project which aimed to develop indicators of the quantity and quality of the learning process of pupils from their usage of an eponymous electronic textbook for History. In this thesis, we investigate several models that adopt different points of view on the data. The studied methods are either well established in the field of pattern mining or transferred from other fields of machine learning and data-mining.
We improve the performance of archetypal analysis in large dimensions and apply it to unveil correlations between visibility time of particular objects in the e-textbook and pupils’ motivation. We present next two models based on mixtures of Markov chains. The first extracts users’weekly browsing patterns. The second is designed to process essions at a fine resolution, which is sine qua non to reveal the significance of scrolling behaviors. We also propose a new paradigm for online behaviors analysis that interprets sessions as trajectories within the page-graph. In this respect, we establish a general framework for the study of similarity measures between spatio-temporal trajectories, for which the study of sessions is a particular case. Finally, we construct two centroid-based clustering methods using neural networks and thus lay the foundations for unsupervised behaviors analysis using neural networks.
Keywords: online behaviors analysis, educational data mining, Markov models, archetypal analysis, spatio-temporal trajectories, neural network
Due to increased life expectancy, a growing number of retirees are spending more and more time in retirement. Life satisfaction in later life therefore becomes an increasingly important societal issue. Good work ability and health are prerequisites for a self-determined transition to retirement, for example allowing for a continuation of gainful employment beyond retirement age. Such continued employment is one way of dealing with the consequences of a historically unique long retirement phase: a self-determined continued employment can have a positive effect on individual well-being, on societal level relieve the burden on the pension insurance system, and on meso-level provide companies with urgently needed human capital. The self-determination of life circumstances is postulated by Self-Determination Theory (SDT) as a basic psychological need with effects on individual well-being. This dissertation investigates work ability as a concept that supports workers, employers, and societies in the extension of working lives, and how work ability is related to the level of self-determination in the transition to retirement, and ultimately life satisfaction.
In the first study of this dissertation, the Work Ability Survey-R (WAS-R) was translated from English into German and then evaluated regarding its psychometric properties and construct validity. The WAS-R operationalizes work ability as the interplay of personal and organizational resources and thus allows companies to derive targeted interventions to maintain work ability.
In the second study, the WAS-R was examined together with the questionnaire Work-Related Behavior and Experience Pattern (Arbeitsbezogenes Verhaltens- und Erlebensmuster, AVEM) regarding its construct validity. A striking feature of this study was the high number of participants with the answering pattern indicating low work-related ambitions and protection. Persons with this pattern are in danger of entering the risk pattern for burnout in the future. The findings support the validity of the WAS-R.
In the third contribution, two studies examined the experience of control (i.e., autonomy) in the transition to retirement as a mediator between previous work ability, health, and financial well-being, and later life satisfaction in retirement. Control was found to partially mediate the relationship between work ability and later life satisfaction. Different mechanisms on later life satisfaction of work ability and health, and the subjective and objective financial situation were found.
This dissertation contributes to research on and practice with aging workers in two ways: (1) The German translation of the WAS-R is presented as a useful instrument for measuring work ability, assessing individual and organizational aspects and therefore enabling employers to make targeted interventions to maintain and improve work ability, and eventually enable control during later work life, the retirement transition and even old age. (2) This dissertation corroborates the importance of good work ability and health, even in old age, as well as control in these phases of life. Work ability is indirectly related to life satisfaction in the long period of retirement, mediated by a sense of control in the transition to retirement. This emphasizes the importance of the need for control as postulated by the SDT also in the transition to retirement.
Network analysis methods have long been used in the social sciences. About 25 years ago, these methods gained popularity in various other domains and many real-world phenomena have been modeled using networks. Well-known examples include (online) social networks, economic networks, web graphs, metabolic networks, infrastructure networks, and many more.
Technological development made it possible to store and process data on a scale not imaginable decades ago — a development that also includes network data. A particular characteristic of network data is that, unlike standard data, the objects of interest, called nodes, have relationships to (possibly all) other objects in the network. Collecting empirical data is often complicated and cumbersome, hence, the observed data are typically incomplete and might also contain other types of errors. Because of the interdependent structure of network data, these errors have a severe impact on network analysis methods.
This cumulative dissertation is about the impact of erroneous network data on centrality measures, which are methods to assess the position of an object, for example a person, with respect to all other objects in a network. Existing studies have shown that even small errors can substantially alter these positions. The impact of errors on centrality measures is typically quantified using a concept called robustness.
The articles included in this dissertation contribute to a better understanding of the robustness of centrality measures in several aspects. It is argued why the robustness needs to be estimated and a new method is proposed. This method allows researchers to estimate the robustness of a centrality measure in a specific network and can be used as a basis for decision making. The relationship between network properties and the robustness of centrality measures is analyzed. Experimental and analytical approaches show that centrality measures are often more robust in networks with a larger average degree. The study of the impact of non-random errors on the robustness suggests that centrality measures are often more robust if missing nodes are more likely to belong to the same community compared to missingness completely at random. For the development of imputation procedures based on machine learning techniques, a process for the evaluation of node embedding methods is proposed.
My dissertation embraces four empirical papers addressing socio-economic issues relevant to policy-makers and society as a whole. These papers cover important aspects of human life including health at birth, life satisfaction, unemployment periods and retirement decisions, and are intended to provide a contribution to the respective research areas. The analyses are carried out applying advanced econometric methods and are based on data sets consisting of survey data as well as administrative records.
The joint paper with Alessandro Palma and Daniela Vuri "Prenatal Air Pollution Exposure and Neonatal Health" in Chapter 2 investigates the causal impact of prenatal exposure to air pollution on neonatal health in Italy in the 2000s combining detailed information on mother’s residential location from birth certificates with PM10 concentrations from air pollution monitors. Variation in local weekly rainfall is exploited as an instrumental variable for non-random air pollution exposure. Using quasi-experimental variation in rainfall shocks allows to identify the effect of PM10, ruling out potential bias due to confounder pollutants. The paper estimates the effect of exposure for both the entire pregnancy period and separately for each trimester to test whether the neonatal health effects are driven by pollution exposure during a particular gestation period. This information enhances our understanding of the mechanisms at work and help prevent pregnant mothers from most dangerous exposure periods. Additionally, the effects of prenatal exposure to PM10 are estimated by maternal labor market status and maternal education level to understand how the pollution burden is shared across different population groups. This decomposition allows to identify possible mechanisms through which environmental inequality reinforces the negative impact of early-life exposure to air pollution. This study finds that average PM10 and days with PM10 level above the hazard limit reduce birth weight, gestational age, and measures of overall newborn health. Effects are largest for third trimester exposure and for low-income and less educated mothers. These findings imply that further policy efforts are needed to fully protect fetuses from the adverse effects of air pollution and to mitigate the environmental inequality of health at birth.
The joint paper with Christian Pfeifer "Life Satisfaction in Germany After Reunification: Additional Insights on the Pattern of Convergence" in Chapter 3 updates previous findings on the total East-West gap in overall life satisfaction and its trend by using data from the German Socio-Economic Panel for the years 1992 to 2013. Additionally, the effects are separately analyzed for men and women as well as for four birth cohorts. The results indicate that reported life satisfaction is, on average, significantly lower in East than in West German federal states and that part of the raw East-West gap is due to differences in household income and unemployment status. The conditional East-West gap decreased in the first years after the German reunification and remained quite stable and sizable since the mid-nineties. The results further indicate that gender differences are small. Finally, the East-West gap is significantly smaller and shows a trend towards convergence for younger birth cohorts.
The joint paper with Christian Pfeifer "Unemployment Benefits Duration and Labor Market Outcomes: Evidence from a Natural Experiment in Germany" in Chapter 4 explores the effects
2
of a major reform of unemployment benefits in Germany on the labor market outcomes of individuals with some health impairment. The reform induced a substantial reduction in the potential duration of regular unemployment benefits for older workers. This work analyzes the reform in a wider framework of institutional interactions, which allows to distinguish between its intended and unintended effects. The results based on routine data collected by the German Statutory Pension Insurance and a Difference-in-Differences design provide causal evidence for a significant decrease in the number of days in unemployment benefits and increase in the number of days in employment. However, they also suggest a significant increase in the number of days in unemployment assistance, granted upon exhaustion of unemployment benefits. Transitions to unemployment assistance represent an unintended effect, limiting the success of a policy change that aims to increase labor supply via reductions in the generosity of the unemployment insurance system.
The single-authored paper "How Older Workers Respond to Raised Early Retirement Age: Evidence from a Kink Design in Germany" in Chapter 5 explores how an increase in the early retirement age affects labor force participation of older workers. The analysis is based on a social security reform in Germany, which raised the early retirement age over several birth cohorts to boost employment of older people and ultimately alleviate the burden on the public pension system. Detailed administrative data from the Federal Employment Agency allow to distinguish between employment and unemployment as well as disability pensions and retirement benefits claims. Using a Regression Kink design in a quasi-experimental framework, I show that the raised early retirement age had positive employment effects and negative effects on retirement benefits claims. The reform did not affect unemployment benefits or disability pensions claims. My results also show that some population groups are more sensitive to a reduction in retirement options and more likely to seek benefits from other government programs. In this respect, I find that workers in manufacturing sector respond to the raised early retirement age by claiming benefits from the disability insurance program designed to compensate for reduced earnings capacity due to severe health problems. The treatment heterogeneity analysis further suggests that high-wage workers are more likely to delay exits from employment, which is in line with incentives but might also indicate an increased inequality within the affected birth cohorts induced by the reform. Finally, women seem to rely on alternative sources of income such as retirement benefits for women, or spouse's or partner's income not observed in the data. All things considered, workers did not adjust to the increased early retirement age by substituting early retirement with other government programs but rather responded to the reform in line with the policy intent. At the same time, the findings point to heterogeneous behavioral responses across different population groups. This implies that raising the early retirement age is an effective policy tool to increase employment only among older people who have the real choice to delay employment exits. Therefore, reforms that raise statutory ages should ensure social support for workers only marginally attached to the labor market or not able to work longer due to potential health problems or other circumstances.
In sub-Saharan Africa, women own or partly own one third of all businesses, thereby having a large potential to contribute to the economic development and societal well-being in this region. However, women-owned businesses tend to lag behind men-owned businesses in that they make lower profits, grow more slowly, and create fewer jobs. To identify reasons for this gap and effective means to promote women entrepreneurs, large parts of the entrepreneurship literature have compared male and female entrepreneurs with regard to individual characteristics, paying only limited attention to the underlying environmental conditions. This is problematic as women entrepreneurs operate under different conditions than men, with particularly pronounced differences in sub-Saharan Africa. Against this backdrop, the goal of this dissertation is to contribute to a more profound understanding of women entrepreneurship in sub-Saharan Africa and its promotion through training by examining critical context factors. Specifically, I analyze two context factors that influence women’s entrepreneurial performance and the success of training interventions: 1) women entrepreneurs’ husbands and 2) the entrepreneurship trainer. These analyses are embedded in considerations of the cultural, social, and economic conditions women entrepreneurs in sub-Saharan Africa are facing. In Chapter 2, I conduct a systematic literature review on spousal influence in entrepreneurship and identify six recurrent types of influence. Complementing the literature originating from Western settings, I develop propositions on how the sub-Saharan context affects husbands’ influence on women entrepreneurship in this region. In Chapter 3, I build on a cultural theory and an economic theory of the household to develop and empirically test a theoretical model of husbands’ constraining and supportive influences on women entrepreneurship in sub-Saharan Africa. The empirical results point to three distinct types of husbands that differ significantly in their impact on women entrepreneurs’ business success. In Chapter 4, I explore the influence of the trainer on the effectiveness of entrepreneurship training in sub-Saharan Africa by drawing on an unsuccessful training implementation. Qualitative analyses indicate that the use of adequate teaching methods is critical towards training success. Overall, this dissertation makes an important contribution towards a better understanding of women entrepreneurs in sub-Saharan Africa and their promotion by shifting the perspective from a purely individualist to a more contextualized view of women entrepreneurship.