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In nowadays production, fluctuations in demand, shortening product life-cycles, and highly configurable products require an adaptive and robust control approach to maintain competitiveness. This approach must not only optimise desired production objectives but also cope with unforeseen machine failures, rush orders, and changes in short-term demand. Previous control approaches were often implemented using a single operations layer and a standalone deep learning approach, which may not adequately address the complex organisational demands of modern manufacturing systems. To address this challenge, we propose a hyper-heuristics control model within a semi-heterarchical production system, in which multiple manufacturing and distribution agents are spread across pre-defined modules. The agents employ a deep reinforcement learning algorithm to learn a policy for selecting low-level heuristics in a situation-specific manner, thereby leveraging system performance and adaptability. We tested our approach in simulation and transferred it to a hybrid production environment. By that, we were able to demonstrate its multi-objective optimisation capabilities compared to conventional approaches in terms of mean throughput time, tardiness, and processing of prioritised orders in a multi-layered production system. The modular design is promising in reducing the overall system complexity and facilitates a quick and seamless integration into other scenarios.
In nowadays production, fluctuations in demand, shortening product life-cycles, and highly configurable products require an adaptive and robust control approach to maintain competitiveness. This approach must not only optimise desired production objectives but also cope with unforeseen machine failures, rush orders, and changes in short-term demand. Previous control approaches were often implemented using a single operations layer and a standalone deep learning approach, which may not adequately address the complex organisational demands of modern manufacturing systems. To address this challenge, we propose a hyper-heuristics control model within a semi-heterarchical production system, in which multiple manufacturing and distribution agents are spread across pre-defined modules. The agents employ a deep reinforcement learning algorithm to learn a policy for selecting low-level heuristics in a situation-specific manner, thereby leveraging system performance and adaptability. We tested our approach in simulation and transferred it to a hybrid production environment. By that, we were able to demonstrate its multi-objective optimisation capabilities compared to conventional approaches in terms of mean throughput time, tardiness, and processing of prioritised orders in a multi-layered production system. The modular design is promising in reducing the overall system complexity and facilitates a quick and seamless integration into other scenarios.
Our study applies legitimacy theorizing to service research, zooming in on co-prosumption service business models, which reside on significant direct contacts among provider-actors and customers as well as fellow customers in the service space. Our findings are based on a longitudinal flexible pattern matching method on 17 coworking spaces. The service cocreation nuances the double role of customers as evaluators and cocreators of legitimacy. This is because customers can have immediate perceptions of the actions and values of the services in their legitimacy evaluation while cocreating the service. Legitimacy shaped via social and recursive processes occurs in three stages: provisional, calibrated, and affirmed legitimacy. Findings inform four trajectory mechanisms of value-in-use pattern provenance, emergent Business Model development adaptive to the spatial context and loyal customers, visible trances as well as inside-out and outside-in identification processes. Further, the processes in the micro-ecosystem of an interstitial service space can develop a superordinate logic which overlays the potentially present coopetive and heterogenous institutional logics and interests of service customers.
Purpose – Design thinking has become an omnipresent process to foster innovativeness in various fields. Due to its popularity in both practice and theory, the number of publications has been growing rapidly. The authors aim to develop a research framework that reflects the current state of research and allows for the identification of research gaps.
Design/methodology/approach – The authors conduct a systematic literature review based on 164 scholarly articles on design thinking.
Findings – This study proposes a framework, which identifies individual and organizational context factors, the stages of a typical design thinking process with its underlying principles and tools, and the individual as well as organizational outcomes of a design thinking project.
Originality/value – Whereas previous reviews focused on particular aspects of design thinking, such as its characteristics, the organizational culture as a context factor or its role on new product development, the authors provide a holistic overview of the current state of research.
Strategic social media use positively influences organizational goals such as the long-term accrual of social capital, and thus social media information governance has become an increasingly important organizational objective. It is particularly important for humanitarian nongovernmental organizations (HNGOs), whose work relies on accurate and timely information regarding socially altruistic behavior (donations, volunteerism, etc.). Despite the potential of social media for increasing social capital, tensions in governing social media information across an organization's different operational levels (regional, intermediate, and national) pose a difficult challenge. Prominent governance frameworks offer little guidance, as their focus on control and incremental policymaking is largely incompatible with the processes, roles, standards, and metrics needed for managing self-governing social media. This study offers a notion of dynamic and co-evolutionary process management of multi-level organizations as a means of conceptualizing social media information governance for the accrual of organizational social capital. Based on interviews with members of HNGOs, this study reveals tensions that emerge within eight focus areas of accruing social capital in multi-level organizations, explains how dynamic process management can ease those tensions, and proposes corresponding strategy recommendations.
Many international organisations (IOs) are currently challenged, yet are they also in decline? Despite much debate on the crisis of liberal international order, con-testation, loss of legitimacy, gridlock, pathologies and exiting member states, there is little research on IO decline. This article seeks to clarify this concept and argues that decline can be considered in absolute and relative terms. Absolute decline involves a decrease in the number of IOs and their authority, member-ship and output, whereas relative decline concerns a decrease in the centrality of IOs in international relations. Reviewing a wide range of indicators, this article argues that, whereas there is limited decline in absolute terms since 1945, there may well be important decline in relative terms. Relative decline is more difficult to measure, but to probe its significance this article presents data from speeches during the United Nations General Assembly General Debate. It shows that IOs were most often mentioned in 1996 and that there has been a decline since. These findings indicate that, whereas IOs might survive as institutions, they are decreasingly central to international relations.
Governance abhors a vacuum
(2023)
International organisations have become increasingly contested resulting in worries about their decline and termination. While international organisation termination is indeed a regular event in international relations, this article shows that other institutions carry the legacy of terminated international organisations. We develop the novel concept of international organisation afterlife and suggest indicators to systematically assess it. Our analysis of 26 major terminated international organisations reveals legal-institutional and asset continuity in 21 cases. To further illustrate this point, the article zooms in on the afterlife of the International Institute of Agriculture in the Food and Agriculture Organization, the International Refugee Organization in the United Nations High Commissioner for Refugees, and the Western European Union in the European Union. In these three cases, international organisation afterlife inspired and structured the design of their successor institutions. While specific international organisations might be terminated, international cooperation therefore often lives on in other institutions.
The synthesis and the crystal structure of the double cluster compound [Nb6Cl14(MeCN)(4)][Nb6Cl14(pyz)(4)]middot6CH(3)CN are described. The synthesis is based on a partial ligand exchange reaction, which proceeds upon dissolving [Nb6Cl14(pyz)(4)]middot2CH(2)Cl(2) in acetonitrile. The compound is built up of two discrete neutral cluster units, which consist of octahedra of Nb-6 atoms coordinated by 12 edge-bridging chlorido and two terminal chlorido ligands, and four acetonitrile ligands on one and four pyrazine ligands on the other cluster unit. Co-crystallized acetonitrile molecules are also present. The single-crystal structure determination has revealed a cluster arrangement in which the [Nb6Cl14(pyz)(4)] units are connected by (halogen) lone-pair-(pyrazine) pi interactions. These lead to chains of [Nb6Cl14(pyz)(4)] clusters. These chains are further connected to cluster layers by (nitrile-halogen) dipole-dipole interactions, in which the [Nb6Cl14(MeCN)(4)] and co-crystallized MeCN molecules are also involved. These cluster layers are arranged parallel to the crystallographic {011} plane.
Design thinking is a well-established practical and educational approach to fostering high-level creativity and innovation, which has been refined since the 1950s with the participation of experts like Joy Paul Guilford and Abraham Maslow. Through real-world projects, trainees learn to optimize their creative outcomes by developing and practicing creative cognition and metacognition. This paper provides a holistic perspective on creativity, enabling the formulation of a comprehensive theoretical framework of creative metacognition. It focuses on the design thinking approach to creativity and explores the role of metacognition in four areas of creativity expertise: Products, Processes, People, and Places. The analysis includes task-outcome relationships (product metacognition), the monitoring of strategy effectiveness (process metacognition), an understanding of individual or group strengths and weaknesses (people metacognition), and an examination of the mutual impact between environments and creativity (place metacognition). It also reviews measures taken in design thinking education, including a distribution of cognition and metacognition, to support students in their development of creative mastery. On these grounds, we propose extended methods for measuring creative metacognition with the goal of enhancing comprehensive assessments of the phenomenon. Proposed methodological advancements include accuracy sub-scales, experimental tasks where examinees explore problem and solution spaces, combinations of naturalistic observations with capability testing, as well as physiological assessments as indirect measures of creative metacognition.
Case report
(2023)
The increasing prevalence of Long COVID is an imminent public health disaster, and established approaches have not provided adequate diagnostics or treatments. Recently, anesthetic blockade of the stellate ganglion was reported to improve Long COVID symptoms in a small case series, purportedly by "rebooting" the autonomic nervous system. Here, we present a novel diagnostic approach based on the Adaptive Force (AF), and report sustained positive outcome for one severely affected Long COVID patient using individualized pulsed electromagnetic field (PEMF) at the area C7/T1. AF reflects the capacity of the neuromuscular system to adapt adequately to external forces in an isometric holding manner. In case, maximal isometric AF (AFiso(max)) is exceeded, the muscle merges into eccentric muscle action. Thereby, the force usually increases further until maximal AF (AFmax) is reached. In case adaptation is optimal, AFiso(max) is similar to 99-100% of AFmax. This holding capacity (AFiso(max)) was found to be vulnerable to disruption by unpleasant stimulus and, hence, was regarded as functional parameter. AF was assessed by an objectified manual muscle test using a handheld device. Prior to treatment, AFiso(max) was considerably lower than AFmax for hip flexors (62 N = similar to 28% AFmax) and elbow flexors (71 N = similar to 44% AFmax); i.e., maximal holding capacity was significantly reduced, indicating dysfunctional motor control. We tested PEMF at C7/T1, identified a frequency that improved neuromuscular function, and applied it for similar to 15 min. Immediately post-treatment, AFiso(max) increased to similar to 210 N (similar to 100% AFmax) at hip and 184 N (similar to 100% AFmax) at elbow. Subjective Long COVID symptoms resolved the following day. At 4 weeks post-treatment, maximal holding capacity was still on a similarly high level as for immediately post-treatment (similar to 100% AFmax) and patient was symptom-free. At 6 months the patient's Long COVID symptoms have not returned. This case report suggests (1) AF could be a promising diagnostic for post-infectious illness, (2) AF can be used to test effective treatments for post-infectious illness, and (3) individualized PEMF may resolve post-infectious symptoms.
We conduct a laboratory experiment to study how locus of control operates through people's preferences and beliefs to influence their decisions. Using the principal-agent setting of the delegation game, we test four key channels that conceptually link locus of control to decision-making: (i) preference for agency; (ii) optimism and (iii) confidence regarding the return to effort; and (iv) illusion of control. Knowing the return and cost of stated effort, principals either retain or delegate the right to make an investment decision that generates payoffs for themselves and their agents. Extending the game to the context in which the return to stated effort is unknown allows us to explicitly study the relationship between locus of control and beliefs about the return to effort. We find that internal locus of control is linked to the preference for agency, an effect that is driven by women. We find no evidence that locus of control influences optimism and confidence about the return to stated effort, or that it operates through an illusion of control.
Paid parental leave schemes have been shown to increase women’s employment rates but to decrease their wages in case of extended leave duration. In view of these potential trade-offs, many countries are discussing the optimal design of parental leave policies. We analyze the impact of a major parental leave reform on mothers’ long-term earnings. The 2007 German parental leave reform replaced a means-tested benefit with a more generous earnings-related benefit that is granted for a shorter period of time. Additionally, a ”daddy quota” of two months was introduced. To identify the causal effect of this policy mix on long-run earnings of mothers, we use a difference-in-differences approach that compares labor market outcomes of mothers who gave birth just before and right after the reform and nets out seasonal effects by including the year before. Using administrative social security data, we confirm previous findings and show that the average duration of employment interruptions increased for mothers with high pre-birth earnings. Nevertheless, we find a positive long-run effect on earnings for mothers in this group. This effect cannot be explained by changes in the selection of working mothers, working hours or changes in employer stability. Descriptive evidence suggests that the stronger involvement of fathers, incentivized by the ”daddy months”, could have facilitated mothers’ re-entry into the labor market and thereby increased earnings. For mothers with low pre-birth earnings, however, we do not find beneficial long-run effects of this parental leave reform.
Predicting entrepreneurial development based on individual and business-related characteristics is a key objective of entrepreneurship research. In this context, we investigate whether the motives of becoming an entrepreneur influence the subsequent entrepreneurial development. In our analysis, we examine a broad range of business outcomes including survival and income, as well as job creation, and expansion and innovation activities for up to 40 months after business formation. Using the self-determination theory as conceptual background, we aggregate the start-up motives into a continuous motivational index. We show – based on a unique dataset of German start-ups from unemployment and non-unemployment – that the later business performance is better, the higher they score on this index. Effects are particularly strong for growth-oriented outcomes like innovation and expansion activities. In a next step, we examine three underlying motivational categories that we term opportunity, career ambition, and necessity. We show that individuals driven by opportunity motives perform better in terms of innovation and business expansion activities, while career ambition is positively associated with survival, income, and the probability of hiring employees. All effects are robust to the inclusion of a large battery of covariates that are proven to be important determinants of entrepreneurial performance.
Objective:
Following a life course perspective, this study examines the link between partnership trajectories and three dimensions of psychological well-being: psychological health, overall sense of self-worth and quality of life.
Background:
Assuming that life outcomes are the result of prior decisions, experiences and events, partnership histories can be seen as a resource for psychological well-being. Furthermore, advantages or disadvantages from living with or without a partner should accumulate over time. While previous cross-sectional research has mainly focused on the influence of partnership status or a status change on well-being, prior longitudinal studies could not control for reverse causality of well-being and partnership trajectories. This research addresses the question of how different patterns of partnership biographies are related to a person's well-being in middle adulthood. Selection effects of pre-trajectory well-being as well as current life conditions are also taken into account.
Method:
Using data from the German LifE Study, the partnership trajectories between ages of 16 and 45 are classified by sequence and cluster analysis. OLS regression is then used to examine the link between types of partnership trajectories and depression, self-esteem and overall life satisfaction at age 45.
Results:
For women, well-being declined when experiencing unstable non-cohabitational union trajectories or divorce followed by unpartnered post-marital trajectories. Men suffered most from being long-term single. The results could not be explained by selection effects of pre-trajectory well-being.
Conclusion:
While women seem to 'recover' from most of the negative effects of unstable partnership trajectories through a new partnership, for men it was shown that being mainly unpartnered has long-lasting effects on their psychological well-being.
Carbon nitride semiconductors: properties and application as photocatalysts in organic synthesis
(2023)
Graphitic carbon nitrides (g-CNs) are represented by melon-type g-CN, poly(heptazine imides) (PHIs), triazine-based g-CN and poly(triazine imide) with intercalated LiCl (PTI/Li+Cl‒). These materials are composed of sp2-hybridized carbon and nitrogen atoms; C:N ratio is close to 3:4; the building unit is 1,3,5-triazine or tri-s-triazine; the building units are interconnected covalently via sp2-hybridized nitrogen atoms or NH-moieties; the layers are assembled into a stack via weak van der Waals forces as in graphite. Due to medium band gap (~2.7 eV) g-CNs, such as melon-type g-CN and PHIs, are excited by photons with wavelength ≤ 460 nm. Since 2009 g-CNs have been actively studied as photocatalysts in evolution of hydrogen and oxygen – two half-reactions of full water splitting, by employing corresponding sacrificial agents. At the same time application of g-CNs as photocatalysts in organic synthesis has been remaining limited to few reactions only. Cumulative Habilitation summarizes research work conducted by the group ‘Innovative Heterogeneous Photocatalysis’ between 2017-2023 in the field of carbon nitride organic photocatalysis, which is led by Dr. Oleksandr Savatieiev.
g-CN photocatalysts activate molecules, i.e. generate their more reactive open-shell intermediates, via three modes: i) Photoinduced electron transfer (PET); ii) Excited state proton-coupled electron transfer (ES-PCET) or direct hydrogen atom transfer (dHAT); iii) Energy transfer (EnT). The scope of reactions that proceed via oxidative PET, i.e. one-electron oxidation of a substrate to the corresponding radical cation, are represented by synthesis of sulfonylchlorides from S-acetylthiophenols. The scope of reactions that proceed via reductive PET, i.e. one-electron reduction of a substrate to the corresponding radical anion, are represented by synthesis of γ,γ-dichloroketones from the enones and chloroform.
Due to abundance of sp2-hybridized nitrogen atoms in the structure of g-CN materials, they are able to cleave X-H bonds in organic molecules and store temporary hydrogen atom. ES-PCET or dHAT mode of organic molecules activation to the corresponding radicals is implemented for substrates featuring relatively acidic X-H bonds and those that are characterized by low bond dissociation energy, such as C-H bond next to the heteroelements. On the other hand, reductively quenched g-CN carrying hydrogen atom reduces a carbonyl compound to the ketyl radical via PCET that is thermodynamically more favorable pathway compared to the electron transfer. The scope of these reactions is represented by cyclodimerization of α,β-unsaturated ketones to cyclopentanoles.
g-CN excited state demonstrates complex dynamics with the initial formation of singlet excited state, which upon intersystem crossing produces triplet excited state that is characterized by the lifetime > 2 μs. Due to long lifetime, g-CN activate organic molecules via EnT. For example, g-CN sensitizes singlet oxygen, which is the key intermediate in the dehydrogenation of aldoximes to nitrileoxides. The transient nitrileoxide undergoes [3+2]-cycloaddition to nitriles and gives oxadiazoles-1,2,4.
PET, ES-PCET and EnT are fundamental phenomena that are applied beyond organic photocatalysis. Hybrid composite is formed by combining conductive polymers, such as poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) with potassium poly(heptazine imide) (K-PHI). Upon PET, K-PHI modulated population of polarons and therefore conductivity of PEDOT:PSS. The initial state of PEDOT:PSS is recovered upon material exposure to O2. K-PHI:PEDOT:PSS may be applied in O2 sensing.
In the presence of electron donors, such as tertiary amines and alcohols, and irradiation with light, K-PHI undergoes photocharging – the g-CN material accumulates electrons and charge-compensating cations. Such photocharged state is stable under anaerobic conditions for weeks, but at the same time it is a strong reductant. This feature allows decoupling in time light harvesting and energy storage in the form of electron-proton couples from utilization in organic synthesis. The photocharged state of K-PHI reduces nitrobenzene to aniline, and enables dimerization of α,β-unsaturated ketones to hexadienones in dark.
The conception of property at the basis of Hegel’s conception of abstract right seems committed to a problematic form of “possessive individualism.” It seems to conceive of right as the expression of human mastery over nature and as based upon an irreducible opposition of person and nature, rightful will, and rightless thing. However, this chapter argues that Hegel starts with a form of possessive individualism only to show that it undermines itself. This is evident in the way Hegel unfolds the nature of property as it applies to external things as well as in the way he explains our self-ownership of our own bodies and lives. Hegel develops the idea of property to a point where it reaches a critical limit and encounters the “true right” that life possesses against the “formal” and “abstract right” of property. Ultimately, Hegel’s account suggests that nature should precisely not be treated as a rightless object at our arbitrary disposal but acknowledged as the inorganic body of right.
An increasing number of clinicians (i.e., nurses and physicians) suffer from mental health-related issues like depression and burnout. These, in turn, stress communication, collaboration, and decision- making—areas in which Conversational Agents (CAs) have shown to be useful. Thus, in this work, we followed a mixed-method approach and systematically analysed the literature on factors affecting the well-being of clinicians and CAs’ potential to improve said well-being by relieving support in communication, collaboration, and decision-making in hospitals. In this respect, we are guided by Brigham et al. (2018)’s model of factors influencing well-being. Based on an initial number of 840 articles, we further analysed 52 papers in more detail and identified the influences of CAs’ fields of application on external and individual factors affecting clinicians’ well-being. As our second method, we will conduct interviews with clinicians and experts on CAs to verify and extend these influencing factors.
Digital Platforms (DPs) has established themself in recent years as a central concept of the Information Technology Science. Due to the great diversity of digital platform concepts, clear definitions are still required. Furthermore, DPs are subject to dynamic changes from internal and external factors, which pose challenges for digital platform operators, developers and customers. Which current digital platform research directions should be taken to address these challenges remains open so far. The following paper aims to contribute to this by outlining a systematic literature review (SLR) on digital platform concepts in the context of the Industrial Internet of Things (IIoT) for manufacturing companies and provides a basis for (1) a selection of definitions of current digital platform and ecosystem concepts and (2) a selection of current digital platform research directions. These directions are diverted into (a) occurrence of digital platforms, (b) emergence of digital platforms, (c) evaluation of digital platforms, (d) development of digital platforms, and (e) selection of digital platforms.
Invention
(2023)
This entry addresses invention from five different perspectives: (i) definition of the term, (ii) mechanisms underlying invention processes, (iii) (pre-)history of human inventions, (iv) intellectual property protection vs open innovation, and (v) case studies of great inventors. Regarding the definition, an invention is the outcome of a creative process taking place within a technological milieu, which is recognized as successful in terms of its effectiveness as an original technology. In the process of invention, a technological possibility becomes realized. Inventions are distinct from either discovery or innovation. In human creative processes, seven mechanisms of invention can be observed, yielding characteristic outcomes: (1) basic inventions, (2) invention branches, (3) invention combinations, (4) invention toolkits, (5) invention exaptations, (6) invention values, and (7) game-changing inventions. The development of humanity has been strongly shaped by inventions ever since early stone tools and the conception of agriculture. An “explosion of creativity” has been associated with Homo sapiens, and inventions in all fields of human endeavor have followed suit, engendering an exponential growth of cumulative culture. This culture development emerges essentially through a reuse of previous inventions, their revision, amendment and rededication. In sociocultural terms, humans have increasingly regulated processes of invention and invention-reuse through concepts such as intellectual property, patents, open innovation and licensing methods. Finally, three case studies of great inventors are considered: Edison, Marconi, and Montessori, next to a discussion of human invention processes as collaborative endeavors.
Widespread on social networking sites (SNSs), envy has been linked to an array of detrimental outcomes for users’ well-being. While envy has been considered a status-related emotion and is likely to be experienced in response to perceiving another’s higher status, there is a lack of research exploring how status perceptions influence the emergence of envy on SNSs. This is important because SNSs typically quantify social interactions and reach with metrics that indicate users’ relative rank and status in the network. To understand how status perceptions impact SNS users, we introduce a new form of metric-based digital status rooted in SNS metrics that are available and visible on a platform. Drawing on social comparison theory and status literature, we conducted an online experiment to investigate how different forms of status contribute to the proliferation of envy on SNSs. Our findings shed light on how metric-based digital status influences feelings of envy on SNSs. Specifically, we could show that metric-based digital status impacts envy through increasing perceptions of others’ socioeconomic and sociometric statuses. Our study contributes to the growing discourse on the negative outcomes associated with SNS use and its consequences for users and society.
Charitable giving
(2023)
We investigate how different levels of information influence the allocation decisions of donors who are entitled to freely distribute a fixed monetary endowment between themselves and a charitable organization in both giving and taking frames. Participants donate significantly higher amounts, when the decision is described as taking rather than giving. This framing effect becomes smaller if more information about the charity is provided.
Labor unions’ greatest potential for political influence likely arises from their direct connection to millions of individuals at the workplace. There, they may change the ideological positions of both unionizing workers and their non-unionizing management. In this paper, we analyze the workplace-level impact of unionization on workers’ and managers’ political campaign contributions over the 1980-2016 period in the United States. To do so, we link establishment-level union election data with transaction-level campaign contributions to federal and local candidates. In a difference-in-differences design that we validate with regression discontinuity tests and a novel instrumental variables approach, we find that unionization leads to a leftward shift of campaign contributions. Unionization increases the support for Democrats relative to Republicans not only among workers but also among managers, which speaks against an increase in political cleavages between the two groups. We provide evidence that our results are not driven by compositional changes of the workforce and are weaker in states with Right-to-Work laws where unions can invest fewer resources in political activities.
Many phenomena of high relevance for economic development such as human capital, geography and climate vary considerably within countries as well as between them. Yet, global data sets of economic output are typically available at the national level only, thereby limiting the accuracy and precision of insights gained through empirical analyses. Recent work has used interpolation and downscaling to yield estimates of sub-national economic output at a global scale, but respective data sets based on official, reported values only are lacking. We here present DOSE — the MCC-PIK Database Of Sub-national Economic Output. DOSE contains harmonised data on reported economic output from 1,661 sub-national regions across 83 countries from 1960 to 2020. To avoid interpolation, values are assembled from numerous statistical agencies, yearbooks and the literature and harmonised for both aggregate and sectoral output. Moreover, we provide temporally- and spatially-consistent data for regional boundaries, enabling matching with geo-spatial data such as climate observations. DOSE provides the opportunity for detailed analyses of economic development at the subnational level, consistent with reported values.
Income inequality and taxes
(2023)
Economic literature offers several distinct explanations for the raising income inequality observed in several countries. In the debate about the causes of inequality a growing strand of research focuses on the effects of taxation on income inequality. We contribute to this literature by providing a systematic empirical account of the relationship between income inequality and personal income taxation (PIT) for a set of countries over the period 1981–2005. In order to take alternative explanations into account and to isolate the effects of tax progressivity, we include a wide range of control variables. We address potential reverse causality between inequality and PIT by using the variation in tax schedules of neighbouring countries. Our results confirm a statistically significant negative association between the progressivity of PIT and income inequality. Overall, we find that especially the average and the marginal tax rate have the potential to reduce income inequality. This finding is qualitatively robust across various different empirical specifications.
Although the literature on the determinants of training has considered individual and firm-related characteristics, it has generally neglected regional factors. This is surprising, given the fact that labour markets differ by regions. Regional factors are often ignored because (both in Germany and abroad) many data sets covering training information do not include detailed geographical identifiers that would allow a merging of information on the regional level. The regional identifiers of the National Educational Panel Study (Starting Cohort 6) offer opportunities to advance research on several regional factors. This article summarizes the results from two studies that exploit these unique opportunities to investigate the relationship between training participation and (a) the local level of firm competition for workers within specific sectors of the economy and (b) the regional supply of training measured as the number of firms offering courses or seminars for potential training participants.
Atwood analyzes the effects of the 1963 U.S. measles vaccination on long-run labor market outcomes, using a generalized difference-in-differences approach. We reproduce the results of this paper and perform a battery of robustness checks. Overall, we confirm that the measles vaccination had positive labor market effects. While the negative effect on the likelihood of living in poverty and the positive effect on the probability of being employed are very robust across the different specifications, the headline estimate—the effect on earnings—is more sensitive to the exclusion of certain regions and survey years.
House price expectations
(2023)
This study examines short-, medium-, and long-run price expectations in housing markets. At the heart of our analysis is the combination of data from a tailored in-person household survey, past sale offerings, satellite imagery on developable land, and an information treatment (RCT). As novel finding, we show that price expectations show no evidence for momentum-effects in the long run. We also do not find much evidence for behavioural biases in expectations related to individual housing tenure decisions. Confirming existing findings, we find momentum-effects in the short-run and that individuals, to a limited extend, use aggregate price information to update local expectations. Lastly, we provide suggestive evidence corroborating existing findings that expectations are relevant for portfolio choice.
This study is dedicated to the interdependencies between digital sovereignty and sustainable digitalization, which need to be explicitly linked to an increasing degree in political discourse, academia, and societal debates. Digital skills are the prerequisites for shaping digitalization in the interest of society and sustainable development.
The management of knowledge in organizations considers both established long-term
processes and cooperation in agile project teams. Since knowledge can be both tacit and explicit, its transfer from the individual to the organizational knowledge base poses a challenge in organizations. This challenge increases when the fluctuation of knowledge carriers is exceptionally high. Especially in large projects in which external consultants are involved, there is a risk that critical, company-relevant knowledge generated in the project will leave the company with the external knowledge carrier and thus be lost. In this paper, we show the advantages of an early warning system for knowledge management to avoid this loss. In particular, the potential of visual analytics in the context of knowledge management systems is presented and discussed. We present a project for the development of a business-critical software system and discuss the first implementations and results.
Intrinsic motivation is widely considered essential to creativity because it facilitates more divergent thinking during problem solving. However, we argue that intrinsic motivation has been theorized too heavily as a unitary construct, overlooking various internal factors of a task that can shape the baseline level of intrinsic motivation people have for working on the task. Drawing on theories of cognitive styles, we develop a new scale that measures individual preferences for three different creative thinking styles that we call divergent thinking, bricoleurgent thinking, and emergent thinking. Through a multi-study approach consisting of exploratory factor analysis, confirmatory factor analysis, and convergent validity, we provide psychometric evidence showing that people can have distinct preferences for each cognitive process when generating ideas. Furthermore, when validating this scale through an experiment, we find that each style becomes more dominant in predicting overall enjoyment, engagement, and creativity based on different underlying structures of a task. Therefore, this paper makes both theoretical and empirical contributions to literature by unpacking intrinsic motivation, showing how the alignment between different creative thinking styles and task can be essential to predicting intrinsic motivation, thus reversing the direction of causality between the motivational and cognitive components of creativity typically assumed in literature.
Developing a new product generation requires the transfer of knowledge among various knowledge carriers. Several factors influence knowledge transfer, e.g., the complexity of engineering tasks or the competence of employees, which can decrease the efficiency and effectiveness of knowledge transfers in product engineering. Hence, improving those knowledge transfers obtains great potential, especially against the backdrop of experienced employees leaving the company due to retirement, so far, research results show, that the knowledge transfer velocity can be raised by following the Knowledge Transfer Velocity Model and implementing so-called interventions in a product engineering context. In most cases, the implemented interventions have a positive effect on knowledge transfer speed improvement. In addition to that, initial theoretical findings describe factors influencing the quality of knowledge transfers and outline a setting to empirically investigate how the quality can be improved by introducing a general description of knowledge transfer reference situations and principles to measure the quality of knowledge artifacts. To assess the quality of knowledge transfers in a product engineering context, the Knowledge Transfer Quality Model (KTQM) is created, which serves as a basis to develop and implement quality-dependent interventions for different knowledge transfer situations. As a result, this paper introduces the specifications of eight situation-adequate interventions to improve the quality of knowledge transfers in product engineering following an intervention template. Those interventions are intended to be implemented in an industrial setting to measure the quality of knowledge transfers and validate their effect.
Droughts in São Paulo
(2023)
Literature has suggested that droughts and societies are mutually shaped and, therefore, both require a better understanding of their coevolution on risk reduction and water adaptation. Although the Sao Paulo Metropolitan Region drew attention because of the 2013-2015 drought, this was not the first event. This paper revisits this event and the 1985-1986 drought to compare the evolution of drought risk management aspects. Documents and hydrological records are analyzed to evaluate the hazard intensity, preparedness, exposure, vulnerability, responses, and mitigation aspects of both events. Although the hazard intensity and exposure of the latter event were larger than the former one, the policy implementation delay and the dependency of service areas in a single reservoir exposed the region to higher vulnerability. In addition to the structural and non-structural tools implemented just after the events, this work raises the possibility of rainwater reuse for reducing the stress in reservoirs.
This study utilizes cross-country survey data to analyze differences in attitudes toward cryptocurrency as an alternative to traditional money issued by a central bank. Particularly, we investigate women’s general attitude toward cryptocurrency systems. Results suggest that women invest less into cryptocurrency, show less interest in the future cryptocurrency investment, and see less economic potential in these systems than men do. Further evidence shows that these attitudes are directly connected with lower literacy in cryptocurrency systems. These findings support theory on gender differences in investment behavior. We contribute to the existing literature by conducting a cross-country survey on cryptocurrency attitudes in Europe and Asia, and hence show that this gender effect is robust across these cultures.
In virtual collaboration at the workplace, a growing number of teams apply supportive conversational agents (CAs). They take on different work-related tasks for teams and single users such as scheduling meetings or stimulating creativity. Previous research merely focused on these positive aspects of introducing CAs at the workplace, omitting ethical challenges faced by teams using these often artificial intelligence (AI)-enabled technologies. Thus, on the one hand, CAs can present themselves as benevolent teammates, but on the other hand, they can collect user data, reduce worker autonomy, or foster social isolation by their service. In this work, we conducted 15 expert interviews with senior researchers from the fields of ethics, collaboration, and computer science in order to derive ethical guidelines for introducing CAs in virtual team collaboration. We derived 14 guidelines and seven research questions to pave the way for future research on the dark sides of human–agent interaction in organizations.
The CH2Cl2/MeOH (1:1) extract of Zanthoxylum holstzianum stem bark showed good antiplasmodial activity (IC50 2.5 +/- 0.3 and 2.6 +/- 0.3 mu g/mL against the W2 and D6 strains of Plasmodium falciparum, respectively). From the extract five benzophenanthridine alkaloids [8-acetonyldihydrochelerythrine (1), nitidine (2), dihydrochelerythine (3), norchelerythrine (5), arnottianamide (8)]; a 2-quinolone alkaloid [N-methylflindersine (4)]; a lignan [4,4 '-dihydroxy-3,3 '-dimethoxylignan-9,9 '-diyl diacetate (7)] and a dimer of a benzophenanthridine and 2-quinoline [holstzianoquinoline (6)] were isolated. The CH2Cl2/MeOH (1:1) extract of the root bark afforded 1, 3-6, 8, chelerythridimerine (9) and 9-demethyloxychelerythrine (10). Holstzianoquinoline (6) is new, and is the second dimer linked by a C-C bond of a benzophenanthridine and a 2-quinoline reported thus far. The compounds were identified based on spectroscopic evidence. Amongst five compounds (1-5) tested against two strains of P. falciparum, nitidine (IC50 0.11 +/- 0.01 mu g/mL against W2 and D6 strains) and norchelerythrine (IC50 value of 0.15 +/- 0.01 mu g/mL against D6 strain) were the most active.
Keep on scrolling?
(2023)
Smartphones are an integral part of daily life for many people worldwide. However, concerns have been raised that long usage times and the fragmentation of daily life through smartphone usage are detrimental to well-being. This preregistered study assesses (1) whether differences in smartphone usage behaviors between individuals predict differences in a variety of well-being measures (between-person effects) and (2) whether differences in smartphone usage behaviors between situations predict whether an individual is feeling better or worse (within-person effects). In addition to total usage time, several indicators capturing the fragmentation of usage/nonusage time were developed. The study combines objectively measured smartphone usage with self-reports of well-being in surveys (N = 236) and an experience sampling period (N = 378, n = 5775 datapoints). To ensure the robustness of the results, we replicated our analyses in a second measurement period (surveys: N = 305; experience sampling: N = 534, n = 7287 datapoints) and considered the pattern of effects across different operational definitions and constructs. Results show that individuals who use their smartphone more report slightly lower well-being (between-person effect) but no evidence for within-person effects of total usage time emerged. With respect to fragmentation, we found no robust association with well-being.
Artificial intelligence (AI)-based technologies can increasingly perform knowledge work tasks, such as medical diagnosis. Thereby, it is expected that humans will not be replaced by AI but work closely with AI-based technology (“augmentation”). Augmentation has ethical implications for humans (e.g., impact on autonomy, opportunities to flourish through work), thus, developers and managers of AI-based technology have a responsibility to anticipate and mitigate risks to human workers. However, doing so can be difficult as AI encompasses a wide range of technologies, some of which enable fundamentally new forms of interaction. In this research-in-progress paper, we propose the development of a taxonomy to categorize unique characteristics of AI-based technology that influence the interaction and have ethical implications for human workers. The completed taxonomy will support researchers in forming cumulative knowledge on the ethical implications of augmentation and assist practitioners in the ethical design and management of AI-based technology in knowledge work.
With larger artificial neural networks (ANN) and deeper neural architectures, common methods for training ANN, such as backpropagation, are key to learning success. Their role becomes particularly important when interpreting and controlling structures that evolve through machine learning. This work aims to extend previous research on backpropagation-based methods by presenting a modified, full-gradient version of the backpropagation learning algorithm that preserves (or rather crystallizes) selected neural weights while leaving other weights adaptable (or rather fluid). In a design-science-oriented manner, a prototype of a feedforward ANN is demonstrated and refined using the new learning method. The results show that the so-called crystallizing backpropagation increases the control possibilities of neural structures and interpretation chances, while learning can be carried out as usual. Since neural hierarchies are established because of the algorithm, ANN compartments start to function in terms of cognitive levels. This study shows the importance of dealing with ANN in hierarchies through backpropagation and brings in learning methods as novel ways of interacting with ANN. Practitioners will benefit from this interactive process because they can restrict neural learning to specific architectural components of ANN and can focus further development on specific areas of higher cognitive levels without the risk of destroying valuable ANN structures.
Faced with the triad of time-cost-quality, the realization of production tasks under economic conditions is not trivial. Since the number of Artificial-Intelligence-(AI)-based applications in business processes is increasing more and more nowadays, the efficient design of AI cases for production processes as well as their target-oriented improvement is essential, so that production outcomes satisfy high quality criteria and economic requirements. Both challenge production management and data scientists, aiming to assign ideal manifestations of artificial neural networks (ANNs) to a certain task. Faced with new attempts of ANN-based production process improvements [8], this paper continues research about the optimal creation, provision and utilization of ANNs. Moreover, it presents a mechanism for AI case-based reasoning for ANNs. Experiments clarify continuously improving ANN knowledge bases by this mechanism empirically. Its proof-of-concept is demonstrated by the example of four production simulation scenarios, which cover the most relevant use cases and will be the basis for examining AI cases on a quantitative level.
A growing number of studies have recently postulated a so-called local turn in the study of immigrant and refugee integration policy. A fundamental, yet untested, assumption of this body of research is that local (sub-national) policies and administrations shape how migrants and refugees integrate into society. We develop and apply an analytical model using multilevel modeling techniques based on large-N, longitudinal survey data (N > 9000) with refugees (2012–2018) in a highly decentralized country (Germany) to estimate the scope for local policy effects net of individual-level and state- and district-level characteristics. We show that region and district-level variation in integration outcomes across multiple dimensions (employment, education, language, housing, social) is limited (∼5%) within 4–8 years after immigration. We find modest variation in policy indicators (∼10%), which do not appear to directly translate into outcomes. We discuss implications for the study of local policies and the potential for greater convergence between administrative and political science, interested in governance structures and policy variation, and sociology and economics, interested primarily in integration outcomes.
In a comparison of three human service organisations in which the human body plays a key role, we examine how organisations regulate religious body practices. We concentrate on Muslim norms of dressing and undressing as a potential focal point of cultural and religious diversity. Inspired by Ray’s (2019) idea of racialized organizations, we assume that state-run organizations in Germany are characterized by a strong commitment to religious tolerance and non-discrimination but also marked by anti- Muslim sentiment prevalent among the German population. Our study looks for mechanism that explain how Human Service Organizations accommodate Muslim body practices. It draws on qualitative empirical data collected in state-run hospitals, schools and swimming pools in Germany. Our analyses show that the organizations draw on formal and informal rules at the organizational level to accommodate Islam. We identify five general organizational mechanisms that may hinder Muslim accommodation in human service organizations. In particular, we see a risk of decoupling between the expectation of religious tolerance and processes that lead to informal discrimination, driven mainly by the difficulty of controlling group dynamics among users.
The digitization process has triggered a profound transformation of modern societies. It encompasses a broad spectrum of technical, social, political, cultural and economic developments related to the mass use of computer- and internet-based technologies. It is now becoming increasingly clear that digitization is also changing existing structures of social inequality and that new structures of digital inequality are emerging. This is shown by a growing number of recent individual studies. In this paper, we set ourselves the task of systematizing this new research within the framework of an empirically supported literature review. To do so, we use the PRISMA model for literature reviews and focus on three central dimensions of inequality - ethnicity, gender, and age - and their relevance within the discourse on digitization and inequality. The empirical basis consists of journal articles published between 2000 and 2020 and listed on the Web of Science, as well as an additional Google Scholar search, through which we attempt to include important monographs and contributions to edited volumes in our analyses. Our text corpus thus comprises a total of 281 articles. Empirically, our literature review shows that unequal access to digital resources largely reproduces existing structures of inequality; in some cases, studies report a reduction in social inequalities as a result of the digitization process.
Virtual reality can have advantages for education and learning. However, it must be adequately designed so that the learner benefits from the technological possibilities. Understanding the underlying effects of the virtual learning environment and the learner’s prior experience with virtual reality or prior knowledge of the content is necessary to design a proper virtual learning environment. This article presents a pre-study testing the design of a virtual learning environment for engineering vocational training courses. In the pre-study, 12 employees of two companies joined the training course in one of the two degrees of immersion (desktop VR and VR HMD). Quantitative results on learning success, cognitive load, usability, and motivation and qualitative learning process data were presented. The qualitative data assessment shows that overall, the employees were satisfied with the learning environment regardless of the level of immersion and that the participants asked for more guidance and structure accompanying the learning process. Further research is needed to test for solid group differences.
Focusing on the passive use of Instagram, we apply the affordance perspective to deeply explore its use and use-related outcomes. In the qualitative study, we uncover the affordances of focal social media features. Two distinct groups of affordances (self- and others-oriented) emerge. Following the grounded theory methodology, we develop the affordances-actualizations-outcomes model, explaining how immediate goals associated with features translate into outcomes. In the quantitative study, we test the model by applying structural equation modeling. Our findings confirm that actualizations of self- and others-oriented affordances are associated with distinct outcomes: social connectedness, positive affect, and overall satisfaction with Instagram experience.