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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.
This article examines public service resilience during the COVID-19 pandemic and studies the switch to telework due to social distancing measures. We argue that the pandemic and related policies led to increasing demands on public organisations and their employees. Following the job demands-resources model, we argue that resilience only can arise in the presence of resources for buffering these demands. Survey data were collected from 1,189 German public employees, 380 participants were included for analysis. The results suggest that the public service was resilient against the crisis and that the shift to telework was not as demanding as expected.
Business incubators hatch start-ups, helping them to survive their early stage and to create a solid foundation for sustainable growth by providing services and access to knowledge. The great practical relevance led to a strong interest of researchers and a high output of scholarly publications, which made the field complex and scattered. To organize the research on incubators and provide a systematic overview of the field, we conducted bibliometric performance analyses and science mappings. The performance analyses depict the temporal development of the number of incubator publications and their citations, the most cited and most productive journals, countries, and authors, and the 20 most cited articles. The author keyword co-occurrence analysis distinguishes six, and the bibliographic coupling seven research themes. Based on a content analysis of the science mappings, we propose a research framework for future research on business incubators.
Doing good by doing bad
(2022)
This study investigates how tone at the top, implemented by top management, and tone at the bottom, in an employee's immediate work environment, determine noncompliance. We focus on the disallowed actions of employees that improve their own and, in turn, the company's performance, referred to as performance-improving noncompliant behavior (PINC behavior). We conduct a survey of German sales employees to investigate specifically how, on the one hand, (1) corporate rules and (2) performance pressure, both implemented by top management, and, on the other hand, (3) others' PINC expectations and (4) others' PINC behavior, both arising from the employee's immediate work environment, influence PINC behavior. When considered in isolation, we find that corporate rules, as top management's main instrument to guide employee behavior, decrease employee PINC behavior. However, this effect is negatively influenced by the employees' immediate work environment when employees are expected to engage in PINC or when others engage in PINC. In contrast, even though top management places great performance pressure on employees, that by itself does not increase PINC behavior. Overall, our study informs practitioners and researchers about whether and how the four determinants increase or decrease employees' PINC behavior, which is important to comprehend triggers and to counteract such misconduct.
Sharing marketplaces emerged as the new Holy Grail of value creation by enabling exchanges between strangers. Identity reveal, encouraged by platforms, cuts both ways: While inducing pre-transaction confidence, it is suspected of backfiring on the information senders with its discriminative potential. This study employs a discrete choice experiment to explore the role of names as signifiers of discriminative peculiarities and the importance of accompanying cues in peer choices of a ridesharing offer. We quantify users' preferences for quality signals in monetary terms and evidence comparative disadvantage of Middle Eastern descent male names for drivers and co-travelers. It translates into a lower willingness to accept and pay for an offer. Market simulations confirm the robustness of the findings. Further, we discover that females are choosier and include more signifiers of involuntary personal attributes in their decision-making. Price discounts and positive information only partly compensate for the initial disadvantage, and identity concealment is perceived negatively.
Nowadays, production planning and control must cope with mass customization, increased fluctuations in demand, and high competition pressures. Despite prevailing market risks, planning accuracy and increased adaptability in the event of disruptions or failures must be ensured, while simultaneously optimizing key process indicators. To manage that complex task, neural networks that can process large quantities of high-dimensional data in real time have been widely adopted in recent years. Although these are already extensively deployed in production systems, a systematic review of applications and implemented agent embeddings and architectures has not yet been conducted. The main contribution of this paper is to provide researchers and practitioners with an overview of applications and applied embeddings and to motivate further research in neural agent-based production. Findings indicate that neural agents are not only deployed in diverse applications, but are also increasingly implemented in multi-agent environments or in combination with conventional methods — leveraging performances compared to benchmarks and reducing dependence on human experience. This not only implies a more sophisticated focus on distributed production resources, but also broadening the perspective from a local to a global scale. Nevertheless, future research must further increase scalability and reproducibility to guarantee a simplified transfer of results to reality.
Algorithmic management
(2022)
Entrepreneurial failure
(2022)
Although entrepreneurial failure (EF) is a fairly recent topic in entrepreneurship literature, the number of publications has been growing dynamically and particularly rapidly. Our systematic review maps and integrates the research on EF based on a multi-method approach to give structure and consistency to this fragmented field of research. The results reveal that the field revolves around six thematic clusters of EF: 1) Soft underpinnings of EF, 2) Contextuality of EF, 3) Perception of EF, 4) Two-sided effects of EF, 5) Multi-stage EF effects, and 6) Institutional drivers of EF. An integrative framework of the positive and negative effects of entrepreneurial failure is proposed, and a research agenda is suggested.
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.
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.
Enterprise systems have long played an important role in businesses of various sizes. With the increasing complexity of today’s business relationships, pecialized application systems are being used more and more. Moreover, emerging technologies such as artificial intelligence are becoming accessible for enterprise systems. This raises the question of the future role of enterprise systems. This minitrack covers novel ideas that contribute to and shape the future role of enterprise systems with five contributions.
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.
Entrepreneurship education (EE) has attracted much scholarly attention, showing exponential growth in publication and citation numbers. The research field has become broad, complex, and fragmented, making it increasingly difficult to oversee. Our research goal is to organise and integrate the previous literature. To this end, we use bibliometric analyses, differing from prior analyses, which are outdated or have a different focus. Our results show an immense growth in publications and citations over the last decade and an almost equal involvement of business and educational research. We identify the most productive and influential journals and authors. Our co-citation analysis reveals two research clusters, one focusing on psychological constructs relating to EE, and the other on entrepreneurial behaviour and new venture creation. Based on a review of the 25 most-cited articles on an annual basis, we identify and quantify the most relevant research themes and integrate them into a research framework that we propose for future research. A major finding is that extant research centres around the outcomes of entrepreneurship education, whereas its pedagogy is still mainly a black box.
Real options are widely applied in strategic and operational decision-making, allowing for managerial flexibility in uncertaincontexts. Increased scholarly interest has led to an extensive but fragmented research landscape. We aim to measure andsystematize the research field quantitatively. To achieve this goal, we conduct bibliometric performance analyses and bibliographiccoupling analyses with an in-depth content review. The results of the performance analyses show an increasing interest in realoptions since the beginning of the 2000s and identify the most influential journals and authors. The science mappings reveal sixand seven research clusters over the last two decades. Based on an in-depth analysis of their themes, we develop a researchframework comprising antecedents, application areas, internal and external contingencies, and uncertainty resolution throughreal option valuation or reasoning. We identify several gaps in that framework, which we propose to tackle in future research.
Diet analysis of bats killed at wind turbines suggests large-scale losses of trophic interactions
(2022)
Agricultural practice has led to landscape simplification and biodiversity decline, yet recently, energy-producing infrastructures, such as wind turbines, have been added to these simplified agroecosystems, turning them into multi-functional energy-agroecosystems. Here, we studied the trophic interactions of bats killed at wind turbines using a DNA metabarcoding approach to shed light on how turbine-related bat fatalities may possibly affect local habitats. Specifically, we identified insect DNA in the stomachs of common noctule bats (Nyctalus noctula) killed by wind turbines in Germany to infer in which habitats these bats hunted. Common noctule bats consumed a wide variety of insects from different habitats, ranging from aquatic to terrestrial ecosystems (e.g., wetlands, farmland, forests, and grasslands). Agricultural and silvicultural pest insects made up about 20% of insect species consumed by the studied bats. Our study suggests that the potential damage of wind energy production goes beyond the loss of bats and the decline of bat populations. Bat fatalities at wind turbines may lead to the loss of trophic interactions and ecosystem services provided by bats, which may add to the functional simplification and impaired crop production, respectively, in multi-functional ecosystems.
The development of speaking competence is widely regarded as a central aspect of second language (L2) learning. It may be questioned, however, if the currently predominant ways of conceptualising the term fully satisfy the complexity of the construct: Although there is growing recognition that language primarily constitutes a tool for communication and participation in social life, as yet it is rare for conceptualisations of speaking competence to incorporate the ability to inter-act and co-construct meaning with co-participants. Accordingly, skills allowing for the successful accomplishment of interactional tasks (such as orderly speaker change, and resolving hearing and understanding trouble) also remain largely unrepresented in language teaching and assessment. As fostering the ability to successfully use the L2 within social interaction should arguably be a main objective of language teaching, it appears pertinent to broaden the construct of speaking competence by incorporating interactional competence (IC). Despite there being a growing research interest in the conceptualisation and development of (L2) IC, much of the materials and instruments required for its teaching and assessment, and thus for fostering a broader understanding of speaking competence in the L2 classroom, still await development. This book introduces an approach to the identification of candidate criterial features for the assessment of EFL learners’ L2 repair skills. Based on a corpus of video-recorded interaction between EFL learners, and following conversation-analytic and interactional-linguistic methodology as well as drawing on basic premises of research in the framework of Conversation Analysis for Second Language Acquisition, differences between (groups of) learners in terms of their L2 repair conduct are investigated through qualitative and inductive analyses. Candidate criterial features are derived from the analysis results. This book does not only contribute to the operationalisation of L2 IC (and of L2 repair skills in particular), but also lays groundwork for the construction of assessment scales and rubrics geared towards the evaluation of EFL learners’ L2 interactional skills.
Knowledge graphs are structured repositories of knowledge that store facts
about the general world or a particular domain in terms of entities and
their relationships. Owing to the heterogeneity of use cases that are served
by them, there arises a need for the automated construction of domain-
specific knowledge graphs from texts. While there have been many research
efforts towards open information extraction for automated knowledge graph
construction, these techniques do not perform well in domain-specific settings.
Furthermore, regardless of whether they are constructed automatically from
specific texts or based on real-world facts that are constantly evolving, all
knowledge graphs inherently suffer from incompleteness as well as errors in
the information they hold.
This thesis investigates the challenges encountered during knowledge graph
construction and proposes techniques for their curation (a.k.a. refinement)
including the correction of semantic ambiguities and the completion of missing
facts. Firstly, we leverage existing approaches for the automatic construction
of a knowledge graph in the art domain with open information extraction
techniques and analyse their limitations. In particular, we focus on the
challenging task of named entity recognition for artwork titles and show
empirical evidence of performance improvement with our proposed solution
for the generation of annotated training data.
Towards the curation of existing knowledge graphs, we identify the issue of
polysemous relations that represent different semantics based on the context.
Having concrete semantics for relations is important for downstream appli-
cations (e.g. question answering) that are supported by knowledge graphs.
Therefore, we define the novel task of finding fine-grained relation semantics
in knowledge graphs and propose FineGReS, a data-driven technique that
discovers potential sub-relations with fine-grained meaning from existing pol-
ysemous relations. We leverage knowledge representation learning methods
that generate low-dimensional vectors (or embeddings) for knowledge graphs
to capture their semantics and structure. The efficacy and utility of the
proposed technique are demonstrated by comparing it with several baselines
on the entity classification use case.
Further, we explore the semantic representations in knowledge graph embed-
ding models. In the past decade, these models have shown state-of-the-art
results for the task of link prediction in the context of knowledge graph comple-
tion. In view of the popularity and widespread application of the embedding
techniques not only for link prediction but also for different semantic tasks,
this thesis presents a critical analysis of the embeddings by quantitatively
measuring their semantic capabilities. We investigate and discuss the reasons
for the shortcomings of embeddings in terms of the characteristics of the
underlying knowledge graph datasets and the training techniques used by
popular models.
Following up on this, we propose ReasonKGE, a novel method for generating
semantically enriched knowledge graph embeddings by taking into account the
semantics of the facts that are encapsulated by an ontology accompanying the
knowledge graph. With a targeted, reasoning-based method for generating
negative samples during the training of the models, ReasonKGE is able to
not only enhance the link prediction performance, but also reduce the number
of semantically inconsistent predictions made by the resultant embeddings,
thus improving the quality of knowledge graphs.
The “HPI Future SOC Lab” is a cooperation of the Hasso Plattner Institute (HPI) and industry partners. Its mission is to enable and promote exchange and interaction between the research community and the industry partners.
The HPI Future SOC Lab provides researchers with free of charge access to a complete infrastructure of state of the art hard and software. This infrastructure includes components, which might be too expensive for an ordinary research environment, such as servers with up to 64 cores and 2 TB main memory. The offerings address researchers particularly from but not limited to the areas of computer science and business information systems. Main areas of research include cloud computing, parallelization, and In-Memory technologies.
This technical report presents results of research projects executed in 2018. Selected projects have presented their results on April 17th and November 14th 2017 at the Future SOC Lab Day events.
During his trip to New Spain in 1803, Alexander von Humboldt visited large tracts of New Spanish territory, which includes modern Mexico and part of the United States. This trip provided the data for his geographical Atlas of the region, as well as information about the ancient Mexican cultures that he would later include in the general Atlas and in other major works, such as Vues des Cordillères. Likewise, Humboldt’s Political Essay on the Kingdom of New Spain displayed a comprehensive physical, natural, economic, and social description of Mexico in the colonial period, which will also be analysed. With these works, Humboldt presented a new geographical and cultural image of New Spain to the European audiences. In addition to this, his work made important contributions to cartographic knowledge.
Distances affect economic decision-making in numerous situations. The time at which we make a decision about future consumption has an impact on our consumption behavior. The spatial distance to employer, school or university impacts the place where we live and vice versa. The emotional closeness to other individuals influences our willingness to give money to them. This cumulative thesis aims to enrich the literature on the role of distance for economic decision-making. Thereby, each of my research projects sheds light on the impact of one kind of distance for efficient decision-making.