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Institute
- Wirtschaftswissenschaften (824) (remove)
Algorithmic management
(2022)
Algorithmic management
(2022)
The organisation of legislative chambers and the consequences of parliamentary procedures have been among the most prominent research questions in legislative studies. Even though democratic elections not only lead to the formation of a government but also result in an opposition, the literature has mostly neglected oppositions and their role in legislative chambers. This paper proposes to fill this gap by looking at the legislative organisation from the perspective of opposition players. The paper focuses on the potential influence of opposition players in the policy-making process and presents data on more than 50 legislative chambers. The paper shows considerable variance of the formal power granted to opposition players. Furthermore, the degree of institutionalisation of opposition rights is connected to electoral systems and not necessarily correlated with other institutional characteristics such as regime type or the size of legislative chambers.
This article merges theoretical literature on non-controlling minority shareholdings (NCMS) in a coherent model to study the effects of NCMS on competition and collusion. The model encompasses both the case of a common owner holding shares of rival firms as well as the case of cross ownership among rivals. We find that by softening competition, NCMS weaken the sustainability of collusion under a greater variety of situations than was indicated by earlier literature. Such effects exist, in particular, in the presence of an effective competition authority.
Volatile supply and sales markets, coupled with increasing product individualization and complex production processes, present significant challenges for manufacturing companies. These must navigate and adapt to ever-shifting external and internal factors while ensuring robustness against process variabilities and unforeseen events. This has a pronounced impact on production control, which serves as the operational intersection between production planning and the shop- floor resources, and necessitates the capability to manage intricate process interdependencies effectively. Considering the increasing dynamics and product diversification, alongside the need to maintain constant production performances, the implementation of innovative control strategies becomes crucial.
In recent years, the integration of Industry 4.0 technologies and machine learning methods has gained prominence in addressing emerging challenges in production applications. Within this context, this cumulative thesis analyzes deep learning based production systems based on five publications. Particular attention is paid to the applications of deep reinforcement learning, aiming to explore its potential in dynamic control contexts. Analysis reveal that deep reinforcement learning excels in various applications, especially in dynamic production control tasks. Its efficacy can be attributed to its interactive learning and real-time operational model. However, despite its evident utility, there are notable structural, organizational, and algorithmic gaps in the prevailing research. A predominant portion of deep reinforcement learning based approaches is limited to specific job shop scenarios and often overlooks the potential synergies in combined resources. Furthermore, it highlights the rare implementation of multi-agent systems and semi-heterarchical systems in practical settings. A notable gap remains in the integration of deep reinforcement learning into a hyper-heuristic.
To bridge these research gaps, this thesis introduces a deep reinforcement learning based hyper- heuristic for the control of modular production systems, developed in accordance with the design science research methodology. Implemented within a semi-heterarchical multi-agent framework, this approach achieves a threefold reduction in control and optimisation complexity while ensuring high scalability, adaptability, and robustness of the system. In comparative benchmarks, this control methodology outperforms rule-based heuristics, reducing throughput times and tardiness, and effectively incorporates customer and order-centric metrics. The control artifact facilitates a rapid scenario generation, motivating for further research efforts and bridging the gap to real-world applications. The overarching goal is to foster a synergy between theoretical insights and practical solutions, thereby enriching scientific discourse and addressing current industrial challenges.
States, in their conflicts with militant groups embedded in civilian populations, often resort to policies of collective punishment to erode civilian support for the militants. We attempt to evaluate the efficacy of such policies in the context of the Gaza Strip, where Israel's blockade and military interventions, purportedly intended to erode support for Hamas, have inflicted hardship on the civilian population.
We combine Palestinian public opinion data, Palestinian labor force surveys, and Palestinian fatalities data, to understand the relationship between exposure to Israeli policies and Palestinian support for militant factions.
Our baseline strategy is a difference-in-differences specification that compares the gap in public opinion between the Gaza Strip and the West Bank during periods of intense punishment with the gap during periods when punishment is eased. Consistent with previous research, we find that Palestinian fatalities are associated with Palestinian support for more militant political factions. The effect is short-lived, however, dissipating after merely one quarter.
Moreover, the blockade of Gaza itself appears to be only weakly associated with support for militant factions. Overall, we find little evidence to suggest that Israeli security policies toward the Gaza Strip have any substantial lasting effect on Gazan support for militant factions, neither deterring nor provoking them relative to their West Bank counterparts.
Our findings therefore call into question the logic of Israel's continued security policies toward Gaza, while prompting a wider re-examination of the efficacy of deterrence strategies in other asymmetric conflicts.
One for all, all for one
(2022)
We propose a conceptual model of acceptance of contact tracing apps based on the privacy calculus perspective. Moving beyond the duality of personal benefits and privacy risks, we theorize that users hold social considerations (i.e., social benefits and risks) that underlie their acceptance decisions. To test our propositions, we chose the context of COVID-19 contact tracing apps and conducted a qualitative pre-study and longitudinal quantitative main study with 589 participants from Germany and Switzerland. Our findings confirm the prominence of individual privacy calculus in explaining intention to use and actual behavior. While privacy risks are a significant determinant of intention to use, social risks (operationalized as fear of mass surveillance) have a notably stronger impact. Our mediation analysis suggests that social risks represent the underlying mechanism behind the observed negative link between individual privacy risks and contact tracing apps' acceptance. Furthermore, we find a substantial intention–behavior gap.
Advancing digitalization is changing society and has far-reaching effects on people and companies. Fundamental to these changes are the new technological possibilities for processing data on an ever-increasing scale and for various purposes. The availability of large and high-quality data sets, especially those based on personal data, is crucial. They are used either to improve the productivity, quality, and individuality of products and services or to develop new types of services. Today, user behavior is tracked more actively and comprehensively than ever despite increasing legal requirements for protecting personal data worldwide. That increasingly raises ethical, moral, and social questions, which have moved to the forefront of the political debate, not least due to popular cases of data misuse. Given this discourse and the legal requirements, today's data management must fulfill three conditions: Legality or legal conformity of use and ethical legitimacy. Thirdly, the use of data should add value from a business perspective. Within the framework of these conditions, this cumulative dissertation pursues four research objectives with a focus on gaining a better understanding of
(1) the challenges of implementing privacy laws,
(2) the factors that influence customers' willingness to share personal data,
(3) the role of data protection for digital entrepreneurship, and
(4) the interdisciplinary scientific significance, its development, and its interrelationships.
This study investigates the effect of different anticonsumption constructs on consumer wellbeing. The study assumes that people will only lower their level of consumption if doing so does not also lower personal wellbeing. More precisely, this research investigates how specific subtypes of sustainable anticonsumption (e.g., voluntary simplicity, collaborative consumption, and debt-free living) relate to different states of consumer's wellbeing (e.g., financial, psychosocial, and subjective wellbeing). This work also examines whether consumer empowerment can improve personal wellbeing and strengthen the anticonsumption wellbeing relationship. The results show that voluntarily foregoing consumption does not reduce wellbeing and consumer empowerment plays a significant role in supporting sustainable pathways to consumer wellbeing. This study reasons that empowerment improves consumer sovereignty, but may be detrimental for consumers heavily concerned about debt-free living. The present investigation concludes by proposing implications for public and consumer policymakers wishing to promote appropriate sustainable (anticonsumption) pathways to consumer wellbeing.
Immigrant integration has become a primary political concern for leaders in Germany and the United States. The information systems (IS) community has begun to research how information and communications technologies can assist immigrants and refugees, such as by examining how countries can facilitate social-inclusion processes. Migrants face the challenge of joining closed communities that cannot integrate or fear doing so. We conducted a panel discussion at the 2019 Americas Conference on Information Systems (AMCIS) in Cancun, Mexico, to introduce multiple viewpoints on immigration. In particular, the panel discussed how technology can both support and prevent immigrants from succeeding in their quest. We conducted the panel to stimulate a thoughtful and dynamic discussion on best practices and recommendations to enhance the discipline's impact on alleviating the challenges that occur for immigrants in their host countries. In this panel report, we introduce the topic of using ICT to help immigrants integrate and identify differences between North/Central America and Europe. We also discuss how immigrants (particularly refugees) use ICT to connect with others, feel that they belong, and maintain their identity. We also uncover the dark and bright sides of how governments use ICT to deter illegal immigration. Finally, we present recommendations for researchers and practitioners on how to best use ICT to assist with immigration.
The coronavirus disease of 2019 (COVID-19) pandemic has forced most academics to work from home. This sudden venue change can affect academics' productivity and exacerbate the challenges that confront universities as they face an uncertain future. In this paper, we identify factors that influence academics' productivity while working from home during the mandate to self-isolate. From analyzing results from a global survey we conducted, we found that both personal and technology-related factors affect an individual's attitude toward working from home and productivity. Our results should prove valuable to university administrators to better address the work-life challenges that academics face.
Helping overcome distance, the use of videoconferencing tools has surged during the pandemic. To shed light on the consequences of videoconferencing at work, this study takes a granular look at the implications of the self-view feature for meeting outcomes. Building on self-awareness research and self-regulation theory, we argue that by heightening the state of self-awareness, self-view engagement depletes participants’ mental resources and thereby can undermine online meeting outcomes. Evaluation of our theoretical model on a sample of 179 employees reveals a nuanced picture. Self-view engagement while speaking and while listening is positively associated with self-awareness, which, in turn, is negatively associated with satisfaction with meeting process, perceived productivity, and meeting enjoyment. The criticality of the communication role is put forward: looking at self while listening to other attendees has a negative direct and indirect effect on meeting outcomes; however, looking at self while speaking produces equivocal effects.
All or nothing
(2020)
This paper develops a new perspective on stranded assets in climate policy using a partial equilibrium model of the energy sector. Political-economy related aspects are considered in the government's objective function. Lobbying power of firms or fiscal considerations by the government lead to time inconsistency: The government will deviate from a previously announced carbon tax which creates stranded assets. Under rational expectations, we show that a time-consistent policy outcome exists with either a zero carbon tax or a prohibitive carbon tax that leads to zero fossil investments - an "all-or-nothing" policy. Although stranded assets are crucial to such a bipolar outcome, they disappear again under time-consistent policy. Which of the two outcomes (all or nothing) prevails depends on the lobbying power of owners of fixed factors (land and fossil resources) but not on fiscal revenue considerations or on the lobbying power of renewable or fossil energy firms.
Do internships pay off?
(2022)
We study the causal effect of student internship experience in firms on earnings later in life. We use mandatory firm internships at German universities as an instrument for doing a firm internship while attending university. Employing longitudinal data from graduate surveys, we find positive and significant earnings returns of about 6 percent in both ordinary least squares (OLS) and instrumental variables (IV) regressions. The positive returns are particularly pronounced for individuals and areas of study that are characterized by a weak labor market orientation. The empirical findings show that graduates who completed a firm internship face a lower risk of unemployment during the first year of their careers, suggesting a smoother transition to the labor market.
Internships during tertiary education have become substantially more common over the past decades in many industrialised countries. This study examines the impact of a voluntary intra-curricular internship experience during university studies on the probability of being invited to a job interview. To estimate a causal relationship, we conducted a randomised field experiment in which we sent 1248 fictitious, but realistic, resumes to real job openings. We find that applicants with internship experience have, on average, a 12.6% higher probability of being invited to a job interview.
Childhood obesity is one of the most serious public health challenges of the twenty-first century. While small-scale experiments change behaviors among adults in the short run, we know little about the effectiveness of large-scale policies or the longer-run impacts. To nudge primary school children into a long-term habit of exercising, the German state of Saxony distributed sports club membership vouchers among all 33,000 third graders in 2009. In 2018, we carried out a register-based survey to evaluate the policy. Even after a decade, awareness of the voucher program was significantly higher in the treatment group. We also find that youth received and redeemed the vouchers. However, we do not find significant short- or long-term effects on sports club membership, physical activity, overweightness, or motor skills. Apparently, membership vouchers for children are not a strong enough policy tool to overcome barriers to exercise regularly.
Inequality of opportunity, particularly when overlaid with socioeconomic, ethnic, or cultural differences, may limit the scope of cooperation between individuals. A central question, then, is how to overcome such obstacles to cooperation. We study this question in the context of Germany, by asking whether the propensity of immigrant youth to cooperate with native peers was affected by a major integration reform: the introduction of birthright citizenship. Our unique setup exploits data from a large-scale lab-in-the-field experiment in a quasi-experimental evaluation framework. We find that the policy caused male, but not female, immigrants to significantly increase their cooperativeness toward natives. We show that the increase in out-group cooperation among immigrant boys is an outcome of more trust rather than a reflection of stronger other-regarding preferences towards natives. In exploring factors that may explain these behavioral effects, we present evidence that the policy also led to a near-closure of the educational achievement gap between young immigrant men and their native peers. Our results high -light that, through integration interventions, governments can modify prosocial behavior in a way that generates higher levels of efficiency in the interaction between social groups.
Recent debates in international relations increasingly focus on bureaucratic apparatuses of international organizations and highlight their role, influence, and autonomy in global public policy. In this contribution we follow the recent call made by Moloney and Rosenbloom in this journal to make use of “public administrative theory and empirically based knowledge in analyzing the behavior of international and regional organizations” and offer a systematic analysis of the inner structures of these administrative bodies. Changes in these structures can reflect both the (re-)assignment of responsibilities, competencies, and expertise, but also the (re)allocation of resources, staff, and corresponding signalling of priorities. Based on organizational charts, we study structural changes within 46 international bureaucracies in the UN system. Tracing formal changes to all internal units over two decades, this contribution provides the first longitudinal assessment of structural change at the international level. We demonstrate that the inner structures of international bureaucracies in the UN system became more fragmented over time but also experienced considerable volatility with periods of structural growth and retrenchment. The analysis also suggests that IO's political features yield stronger explanatory power for explaining these structural changes than bureaucratic determinants. We conclude that the politics of structural change in international bureaucracies is a missing piece in the current debate on international public administrations that complements existing research perspectives by reiterating the importance of the political context of international bureaucracies as actors in global governance.
This paper studies the impact of a ban on late-night off-premise alcohol sales between 10 p.m. and 5 a.m. in Germany. We use three large administrative data sets: (i) German diagnosis related groups-Statistik, (ii) data from a large social health insurance, and (iii) Road Traffic Accident Statistics. Applying difference-in-differences and synthetic-control-group methods, we find that the ban had no effects on alcohol-related road casualties, but significantly reduced alcohol-related hospitalizations (doctor visits) among young people by around 9 (18) percent. The decrease is driven by fewer hospitalizations due to acute alcohol intoxication during the night—when the ban is in place—but not during the day.
Beyond good faith
(2021)
The ambitious climate targets set by industrialized nations worldwide cannot be met without decarbonizing the building stock. Using Germany as a case study, this paper takes stock of the extensive set of energy efficiency policies that are already in place and clarifies that they have been designed “in good faith” but lack in overall effectiveness as well as cost-efficiency in achieving these climate targets. We map out the market failures and behavioural considerations that are potential reasons for why realized energy savings fall below expectations and why the household adoption of energy-efficient and low-carbon technologies has remained low. We highlight the pressing need for data and modern empirical research to develop targeted and cost-effective policies seeking to correct these market failures. To this end, we identify some key research questions and identify gaps in the data required for evidence-based policy.
Climate-related costs and benefits may not be evenly distributed across the population. We study distributional implications of seasonal weather and climate on within-country inequality in rural India. Utilizing a first difference approach, we find that the poor are more sensitive to weather variations than the non-poor. The poor respond more strongly to (seasonal) temperature changes: negatively in the (warm) spring season, more positively in the (cold) rabi season. Less precipitation is harmful to the poor in the monsoon kharif season and beneficial in the winter and spring seasons. We show that adverse weather aggravates inequality by reducing consumption of the poor farming households. Future global warming predicted under RCP8.5 is likely to exacerbate these effects, reducing consumption of poor farming households by one third until the year 2100. We also find inequality in consumption across seasons with higher consumption during the harvest and lower consumption during the sowing seasons.
How assets get stranded
(2020)
Internalizing external costs of carbon is a fundamental goal of climate policy. Since the seminal work of Arthur Pigou in 1920, economic theory has analyzed the efficiency gains arising from various instruments that internalize externalities and lead to Pareto-improvements. It is widely recognized in environmental economics that a carbon price would effectively reflect the scarcity of the atmospheric disposal space for carbon depending on the temperature target that is to be achieved. The question of how to organize the transition process, i.e. moving from inefficient to efficient allocations, and implementing the necessary policies, has gained increasing attention in recent years. Arguably, the transition process is tightly interwoven with political processes that include complex interactions between societal stakeholders, such as households and firms, on the one hand, and political decision makers, on the other. Accordingly, understanding political-economy aspects of the transition process, including distributional outcomes, is becoming increasingly relevant. While a growing literature discusses the distributional implications of climate policy on households, it is less well understood how asset owners might be affected by climate policy and how these potential impacts would interact with the transition process. This Special Section focuses on public policy challenges related to this transition problem, with special emphasis on asset owners. A core theme is the special role of stranded assets, i.e. a devaluation of capital stocks or financial assets either by introducing a stringent carbon price or by omitting a pre-announced policy of this kind.
We present a novel data set of subnational economic output, Gross Regional Product (GRP), for more than 1500 regions in 77 countries that allows us to empirically estimate historic climate impacts at different time scales. Employing annual panel models, long-difference regressions and cross-sectional regressions, we identify effects on productivity levels and productivity growth. We do not find evidence for permanent growth rate impacts but we find robust evidence that temperature affects productivity levels considerably. An increase in global mean surface temperature by about 3.5°C until the end of the century would reduce global output by 7–14% in 2100, with even higher damages in tropical and poor regions. Updating the DICE damage function with our estimates suggests that the social cost of carbon from temperature-induced productivity losses is on the order of 73–142$/tCO2 in 2020, rising to 92–181$/tCO2 in 2030. These numbers exclude non-market damages and damages from extreme weather events or sea-level rise.
The crises of both the climate and the biosphere are manifestations of the imbalance between human extractive, and polluting activities and the Earth’s regenerative capacity. Planetary boundaries define limits for biophysical systems and processes that regulate the stability and life support capacity of the Earth system, and thereby also define a safe operating space for humanity on Earth. Budgets associated to planetary boundaries can be understood as global commons: common pool resources that can be utilized within finite limits. Despite the analytical interpretation of planetary boundaries as global commons, the planetary boundaries framework is missing a thorough integration into economic theory. We aim to bridge the gap between welfare economic theory and planetary boundaries as derived in the natural sciences by presenting a unified theory of cost-benefit and cost-effectiveness analysis. Our pragmatic approach aims to overcome shortcomings of the practical applications of CEA and CBA to environmental problems of a planetary scale. To do so, we develop a model framework and explore decision paradigms that give guidance to setting limits on human activities. This conceptual framework is then applied to planetary boundaries. We conclude by using the realized insights to derive a research agenda that builds on the understanding of planetary boundaries as global commons.
Coal transitions - part 1
(2021)
A rapid coal phase-out is needed to meet the goals of the Paris Agreement, but is hindered by serious challenges ranging from vested interests to the risks of social disruption. To understand how to organize a global coal phase-out, it is crucial to go beyond cost-effective climate mitigation scenarios and learn from the experience of previous coal transitions. Despite the relevance of the topic, evidence remains fragmented throughout different research fields, and not easily accessible. To address this gap, this paper provides a systematic map and comprehensive review of the literature on historical coal transitions. We use computer-assisted systematic mapping and review methods to chart and evaluate the available evidence on historical declines in coal production and consumption. We extracted a dataset of 278 case studies from 194 publications, covering coal transitions in 44 countries and ranging from the end of the 19th century until 2021. We find a relatively recent and rapidly expanding body of literature reflecting the growing importance of an early coal phase-out in scientific and political debates. Previous evidence has primarily focused on the United Kingdom, the United States, and Germany, while other countries that experienced large coal declines, like those in Eastern Europe, are strongly underrepresented. An increasing number of studies, mostly published in the last 5 years, has been focusing on China. Most of the countries successfully reducing coal dependency have undergone both demand-side and supply-side transitions. This supports the use of policy approaches targeting both demand and supply to achieve a complete coal phase-out. From a political economy perspective, our dataset highlights that most transitions are driven by rising production costs for coal, falling prices for alternative energies, or local environmental concerns, especially regarding air pollution. The main challenges for coal-dependent regions are structural change transformations, in particular for industry and labor. Rising unemployment is the most largely documented outcome in the sample. Policymakers at multiple levels are instrumental in facilitating coal transitions. They rely mainly on regulatory instruments to foster the transitions and compensation schemes or investment plans to deal with their transformative processes. Even though many models suggest that coal phase-outs are among the low-hanging fruits on the way to climate neutrality and meeting the international climate goals, our case studies analysis highlights the intricate political economy at work that needs to be addressed through well-designed and just policies.
Elevated annual average temperature has been found to impact macro-economic growth. However, various fundamental elements of the economy are affected by deviations of daily temperature from seasonal expectations which are not well reflected in annual averages. Here we show that increases in seasonally adjusted day-to-day temperature variability reduce macro-economic growth independent of and in addition to changes in annual average temperature. Combining observed day-to-day temperature variability with subnational economic data for 1,537 regions worldwide over 40 years in fixed-effects panel models, we find that an extra degree of variability results in a five percentage-point reduction in regional growth rates on average. The impact of day-to-day variability is modulated by seasonal temperature difference and income, resulting in highest vulnerability in low-latitude, low-income regions (12 percentage-point reduction). These findings illuminate a new, global-impact channel in the climate–economy relationship that demands a more comprehensive assessment in both climate and integrated assessment models.
Pigou in the 21st century
(2021)
The year 2020 marks the centennial of the publication of Arthur Cecil Pigou's magnum opus The Economics of Welfare. Pigou's pricing principles have had an enduring influence on the academic debate, with a widespread consensus having emerged among economists that Pigouvian taxes or subsidies are theoretically desirable, but politically infeasible. In this article, we revisit Pigou's contribution and argue that this consensus is somewhat spurious, particularly in two ways: (1) Economists are too quick to ignore the theoretical problems and subtleties that Pigouvian pricing still faces; (2) The wholesale skepticism concerning the political viability of Pigouvian pricing is at odds with its recent practical achievements. These two points are made by, first, outlining the theoretical and political challenges that include uncertainty about the social cost of carbon, the unclear relationship between the cost-benefit and cost-effectiveness approaches, distributional concerns, fragmented ministerial responsibilities, an unstable tax base, commitment problems, lack of acceptance and trust between government and citizens as well as incomplete international cooperation. Secondly, we discuss the recent political success of Pigouvian pricing, as evidenced by the German government's 2019 climate policy reform and the EU's Green Deal. We conclude by presenting a research agenda for addressing the remaining barriers that need to be overcome to make Pigouvian pricing a common political practice.
Limiting global warming to well below 2 degrees C may pose threats to macroeconomic and financial stability. In an estimated Euro Area New Keynesian model with financial frictions and climate policy, we study the possible perils of a low-carbon transition and evaluate the role of monetary policy and financial regulation. We show that, even for very ambitious climate targets, transition costs are moderate along a timely and gradual mitigation pathway. Inflation volatility strongly increases for disorderly climate policy, demanding a strong monetary response by central banks. In reaction to an adverse financial shock originating in the fossil sector, a green quantitative easing policy can provide an effective stimulus to the economy, but its stabilizing properties do not significantly differ from those of market neutral asset purchase programs. A financial regulation, encouraging the decarbonization of the banks' balance sheets via ad hoc capital requirements, can significantly reduce the severity of a financial crisis, but prolongs the recovery phase. Our results suggest that the involvement of central banks in climate actions must be carefully designed to be in compliance with their mandate and to avoid unintended trade-offs.
We examine the relationship between different types of power investments and regional economic dynamics. We construct a novel panel dataset combining data on regional GDP and power capacity additions for different technologies between 1960 and 2015, which covers 65% of the global power capacity that has been installed in this period. We use an event study design to identify the effect of power capacity addition on GDP per capita, exploiting the fact that the exact amount of power capacity coming online each year is determined by random construction delays. We find evidence that GDP per capita increases by 0.2% in the 6 years around the coming online of 100 MW coal-fired power capacity. We find similar effects for hydropower capacity, but not for any other type of power capacity. The positive effects are regionally bounded and stronger for projects on new sites (green-field). The magnitude of this effect might not be comparable to the total external costs of building new coal-fired power capacity, yet our results help to explain why policymakers favor coal investments for spurring regional growth.
The hare and the hedgehog
(2021)
Against the background of the speed-accuracy trade-off, we explored whether the Pace of Life can be used to identify heterogeneity in the strategy to place more weight on either fast or accurate accomplishments. The Pace of Life approaches an individual's exposure to time and is an intensively studied concept in the evolutionary biology research. Albeit overall rarely, it is increasingly used to understand human behavior and may fulfill many criteria of a personal trait. In a controlled laboratory environment, we measured the participants' Pace of Life, as well as their performance on a real-effort task. In the real-effort task, the participants had to encode words, whereby each word encoded correctly was associated with a monetary reward. We found that individuals with a faster Pace of Life accomplished more tasks in total. At the same time, they were less accurate and made more mistakes (in absolute terms) than those with a slower Pace of Life. Thus, the Pace of Life seems to be useful to identify an individual's stance on the speed-accuracy continuum. In our specific task, placing more weight on speed instead of accuracy paid off: Individuals with a faster Pace of Life were ultimately more successful (with regard to their monetary revenue).
Objective We propose a data-driven method to detect temporal patterns of disease progression in high-dimensional claims data based on gradient boosting with stability selection. Materials and methods We identified patients with chronic obstructive pulmonary disease in a German health insurance claims database with 6.5 million individuals and divided them into a group of patients with the highest disease severity and a group of control patients with lower severity. We then used gradient boosting with stability selection to determine variables correlating with a chronic obstructive pulmonary disease diagnosis of highest severity and subsequently model the temporal progression of the disease using the selected variables. Results We identified a network of 20 diagnoses (e.g. respiratory failure), medications (e.g. anticholinergic drugs) and procedures associated with a subsequent chronic obstructive pulmonary disease diagnosis of highest severity. Furthermore, the network successfully captured temporal patterns, such as disease progressions from lower to higher severity grades. Discussion The temporal trajectories identified by our data-driven approach are compatible with existing knowledge about chronic obstructive pulmonary disease showing that the method can reliably select relevant variables in a high-dimensional context. Conclusion We provide a generalizable approach for the automatic detection of disease trajectories in claims data. This could help to diagnose diseases early, identify unknown risk factors and optimize treatment plans.
We examine the determinants of the disclosure of value-based (VB) performance measures in Germany. We argue that firms are more likely to disclose VB performance measures when information asymmetry is greater, as greater information asymmetry means firms have a greater need to credibly signal a shareholder value orientation. Using a hand-collected dataset of German listed firms covering 1,528 firm-years from 2004 to 2011, we demonstrate that firms are more likely to disclose a VB performance measure if the free float is larger than the blocking minority and also, when firms are large, if they have high foreign sales to total sales ratios and are not cross-listed internationally. Our results indicate that German firms use VB performance measures to improve investor communication and to substantiate their shareholder value orientation. Our results should be interpreted against a background of increased shareholder value orientation and sophisticated cost accounting in German firms.
Carbon dioxide removal (CDR) moves atmospheric carbon to geological or land-based sinks. In a first-best setting, the optimal use of CDR is achieved by a removal subsidy that equals the optimal carbon tax and marginal damages. We derive second-best policy rules for CDR subsidies and carbon taxes when no global carbon price exists but a national government implements a unilateral climate policy. We find that the optimal carbon tax differs from an optimal CDR subsidy because of carbon leakage and a balance of resource trade effect. First, the optimal removal subsidy tends to be larger than the carbon tax because of lower supply-side leakage on fossil resource markets. Second, net carbon exporters exacerbate this wedge to increase producer surplus of their carbon resource producers, implying even larger removal subsidies. Third, net carbon importers may set their removal subsidy even below their carbon tax when marginal environmental damages are small, to appropriate producer surplus from carbon exporters.
We use panel data from Germany to analyze the effect of population density on urban air pollution (nitrogen oxides, particulate matter, ozone, and an aggregate index for bad air quality [AQI]). To address unobserved heterogeneity and omitted variables, we present long difference/fixed effects estimates and instrumental variables estimates, using historical population and soil quality as instruments. Using our preferred estimates, we find that the concentration increases with density for NO2 with an elasticity of 0.25 and particulate matter with elasticity of 0.08. The O-3 concentration decreases with density with an elasticity of -0.14. The AQI increases with density, with an elasticity of 0.11-0.13. We also present a variety of robustness tests. Overall, the paper shows that higher population density worsens local air quality.
The study explores differences between three user types in the top tweets about the 2015 “refugee crisis” in Germany and presents the results of a quantitative content analysis. All tweets with the keyword “Flüchtlinge” posted for a monthlong period following September 13, 2015, the day Germany decided to implement border controls, were collected (N = 763,752). The top 2,495 tweets according to number of retweets were selected for analysis. Differences between news media, public and private actor tweets in topics, tweet characteristics such as tone and opinion expression, links, and specific sentiments toward refugees were analyzed. We found strong differences between the tweets. Public actor tweets were the main source of positive sentiment toward refugees and the main information source on refugee support. News media tweets mostly reflected traditional journalistic norms of impartiality and objectivity, whereas private actor tweets were more diverse in sentiments toward refugees.
We analyze to what extent climate conditions affect the prevalence of sharecropping as a form of traditional land tenure. We investigate how sharecropping tenure is related to climate risk and how it interacts with fertilizer use and livestock ownership that both influence production risk. We first develop a stylized theoretical model to illustrate the role of climate for land tenure and production. Our empirical analysis is based on more than 9000 households with considerable heterogeneity in climate conditions across several African countries. We find that farmers in areas with low precipitation are more likely to be sharecroppers. We further find evidence for risk management interaction effects as sharecropping farmers are less likely to own livestock and more likely to use fertilizer. In economies where formal kinds of insurance are unavailable, sharecropping thus functions as a form of insurance and reduces the need for potentially costly risk management strategies.
Data sharing requires researchers to publish their (primary) data and any supporting research materials. With increased attention on reproducibility and more transparent research requiring sharing of data, the issues surrounding data sharing are moving beyond whether data sharing is beneficial, to what kind of research data should be shared and how. However, despite its benefits, data sharing still is not common practice in Information Systems (IS) research. The panel seeks to discuss the controversies related to data sharing in research, specifically focusing on the IS discipline. It remains unclear how the positive effects of data sharing that are often framed as extending beyond the individual researcher (e.g., openness for innovation) can be utilized while reducing the downsides often associated with negative consequences for the individual researcher (e.g., losing a competitive advantage). To foster data sharing practices in IS, the panel will address this dilemma by drawing on the panelists’ expertise.
Coming back for more
(2022)
Recent spikes in social networking site (SNS) usage times have launched investigations into reasons for excessive SNS usage. Extending research on social factors (i.e., fear of missing out), this study considers the News Feed setup. More specifically, we suggest that the order of the News Feed (chronological vs. algorithmically assembled posts) affects usage behaviors. Against the background of the variable reward schedule, this study hypothesizes that the different orders exert serendipity differently. Serendipity, termed as unexpected lucky encounters with information, resembles variable rewards. Studies have evidenced a relation between variable rewards and excessive behaviors. Similarly, we hypothesize that order-induced serendipitous encounters affect SNS usage times and explore this link in a two-wave survey with an experimental setup (users using either chronological or algorithmic News Feeds). While theoretically extending explanations for increased SNS usage times by considering the News Feed order, practically the study will offer recommendations for relevant stakeholders.
Active use of social networking sites (SNSs) has long been assumed to benefit users' well-being. However, this established hypothesis is increasingly being challenged, with scholars criticizing its lack of empirical support and the imprecise conceptualization of active use. Nevertheless, with considerable heterogeneity among existing studies on the hypothesis and causal evidence still limited, a final verdict on its robustness is still pending. To contribute to this ongoing debate, we conducted a week-long randomized control trial with N = 381 adult Instagram users recruited via Prolific. Specifically, we tested how active SNS use, operationalized as picture postings on Instagram, affects different dimensions of well-being. The results depicted a positive effect on users' positive affect but null findings for other well-being outcomes. The findings broadly align with the recent criticism against the active use hypothesis and support the call for a more nuanced view on the impact of SNSs. <br /> Lay Summary Active use of social networking sites (SNSs) has long been assumed to benefit users' well-being. However, this established assumption is increasingly being challenged, with scholars criticizing its lack of empirical support and the imprecise conceptualization of active use. Nevertheless, with great diversity among conducted studies on the hypothesis and a lack of causal evidence, a final verdict on its viability is still pending. To contribute to this ongoing debate, we conducted a week-long experimental investigation with 381 adult Instagram users. Specifically, we tested how posting pictures on Instagram affects different aspects of well-being. The results of this study depicted a positive effect of posting Instagram pictures on users' experienced positive emotions but no effects on other aspects of well-being. The findings broadly align with the recent criticism against the active use hypothesis and support the call for a more nuanced view on the impact of SNSs on users.
Long-term value creation is expected not only to be concerned with maximizing shareholder value but also includes the impact on other stakeholders and the environment. Environmental, social, and governance (ESG) issues are therefore gaining increasing importance, in line with the growing demand for corporate sustainability. ESG ratings foster the comparison of companies with respect to their sustainable practices. This study aims to investigate how ESG ratings impact financial performance in the European food industry. Ordinary least squares regression is applied to analyze the relation between ESG ratings and financial performance over a 4-year period from 2017 to 2020. The profitability measures Return on Assets (ROA) and Return on Equity (ROE) are employed as financial performance measures, while ESG ratings are obtained from the database CSRHub. Results show that higher ESG ratings are associated with better financial performance. Although the effect is modest in the present study, the findings support previous results that ESG ratings are positively related to financial performance. Nonetheless, they also highlight that ESG ratings strongly converge to the mean, which depicts the need to reassess whether ESG ratings are able to measure actual ESG behavior.
In this study, we contribute to the scholarly conversation on firm-level business model changes following a neoconfigurational approach. By exploring configurations of business model changes over time, we add the direction of business model changes-namely business model convergence or divergence-as a vital avenue to the business model innovation literature. We identify necessary business model convergence and divergence recipes in a sample of N = 217 strategic dyadic alliances. Firstly, technological proximity emerges as a single precondition to both converging and diverging business models. Secondly, business models between competitors either converge through complementarities or tend not to change relative to each other. Thirdly, equity participation enables business model divergence through co-specialization. We conclude with a discussion of business model trajectories and future research directions.
The sharing economy
(2020)
Purpose Quantitative bibliometric approaches were used to statistically and objectively explore patterns in the sharing economy literature. Design/methodology/approach Journal (co-)citation analysis, author (co-)citation analysis, institution citation and co-operation analysis, keyword co-occurrence analysis, document (co-)citation analysis and burst detection analysis were conducted based on a bibliometric data set relating to sharing economy publications. Findings Sharing economy research is multi- and interdisciplinary. Journals focused upon products liability, organizing framework, profile characteristics, diverse economies, consumption system and everyday life themes. Authors focused upon profile characteristics, sharing economy organization, social connections, first principle and diverse economy themes. No institution dominated the research field. Keyword co-occurrence analysis identified organizing framework, tourism industry, consumer behavior, food waste, generous exchange and quality cue as research themes. Document co-citation analysis found research themes relating to the tourism industry, exploring public acceptability, agri-food system, commercial orientation, products liability and social connection. Most cited authors, institutions and documents are reported. Research limitations/implications The study did not exclusively focus on publications in top-tier journals. Future studies could run analyses relating to top-tier journals alone, and then run analyses relating to less renowned journals alone. To address the potential fuzzy results concern, reviews could focus on business and/or management research alone. Longitudinal reviews conducted over several points in time are warranted. Future reviews could combine qualitative and quantitative approaches. Originality/value We contribute by analyzing information relating to the population of all sharing economy articles. In addition, we contribute by employing several quantitative bibliometric approaches that enable the identification of trends relating to the themes and patterns in the growing literature.
The impact of traits in entrepreneurship has been subject to intense discussion. Apart from favorable traits fostering opportunity recognition, entrepreneurial orientation, venture performance, and other variables, a younger research stream also addresses the role of negative traits. Among them, the dark triad, comprising of narcissism, Machiavellianism, and psychopathy, have gained specific attention. This systematic literature review aims to structure the field, identify current research themes, and provide a better understanding of prior research outcomes. Our results show that dark triad research addresses entrepreneurial activity, opportunity recognition, entrepreneurial orientation, entrepreneurial leadership, the and entrepreneurial motives. Among the dark triad traits, narcissism is stressed most in research so far. It relates to firm performance, risk, and leadership behavior, whereas Machiavellianism and psychopathy relate to opportunity recognition and exploitation. We also identify several research gaps, which can be addressed in future research.
Findings in the extant literature are mixed concerning when and how gender diversity benefits team performance. We develop and test a model that posits that gender-diverse teams outperform gender-homogeneous teams when perceived time pressure is low, whereas the opposite is the case when perceived time pressure is high. Drawing on the categorization-elaboration model (CEM; van Knippenberg, De Dreu, & Homan, 2004), we begin with the assumption that information elaboration is the process whereby gender diversity fosters positive effects on team performance. However, also in line with the CEM, we argue that this process can be disrupted by adverse team dynamics. Specifically, we argue that as time pressure increases, higher gender diversity leads to more team withdrawal, which, in turn, moderates the positive indirect effect of gender diversity on team performance via information elaboration such that this effect becomes weaker as team withdrawal increases. In an experimental study of 142 four-person teams, we found support for this model that explains why perceived time pressure affects the performance of gender-diverse teams more negatively than that of gender-homogeneous teams. Our study sheds new light on when and how gender diversity can become either an asset or a liability for team performance.
Time for change?
(2022)
Purpose:
This study aims to provide probable future developments in the form of holistic scenarios for business negotiations. In recent years, negotiation research did not put a lot of emphasis on external changes. Consequently, current challenges and trends are scarcely integrated, making it difficult to support negotiation practice perspectively.
Design/methodology/approach:
This paper applies the structured, multi-method approach of scenario analysis. To examine the future space of negotiations, this combines qualitative and quantitative measures to base our analysis on negotiation experts’ assessments, estimations and visions of the negotiation future.
Findings:
The results comprise an overview of five negotiation scenarios in the year 2030 and of their individual drivers. The five revealed scenarios are: digital intelligence, business as usual, powerful network – the route to collaboration, powerful network – the route to predominance and system crash.
Originality/value:
The scenario analysis is a suitable approach that enables to relate various factors of the negotiation environment to negotiations themselves and allows an examination of future changes in buyer–seller negotiations and the creation of possible future scenarios. The identified scenarios provide an orientation for business decisions in the field of negotiation.