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V1E: A Kernel for Domain-specific Textual Variability Modelling Languages
Get PDFv1e is a language kernel for textual variability modelling built on top of the language-development system DjDSL. As a language kernel,v1e provides a minimal but extensible set of abstractions to implement families of domain-specific languages for textual variability modelling. v1e provides for a small and versatile abstract syntax to encode feature models using multiplicity constraints and canonical semantics. v1e offers built-in analysis support, such as configuration validation, by maintaining internal BDD representations. A derived language becomes realised as a collection of extensions dependent on the language kernel. v1e is designed to behighly extensible and embeddable, e.g., as a dynamic library or as aREPL shell. In this paper, we showcase a selected derived languageand the design decisions involved: a kernel implementation of TVL on top of v1e. We conclude the paper by pointing out current limitations (e.g., representing attributed variability models) and future directions (e.g., analysis support beyond BDD).Series: Technical Reports / Institute for Information Systems and New Medi
Studie zum gesellschaftlichen Mehrwert des OekoBusinessWien-Kofinanzierungsprogramms mittels einer Social Return on Investment (SROI) - Analyse
Get PDFVDD: A Visual Drift Detection System for Process Mining
Get PDFResearch on concept drift detection has inspired recent advancements of process mining and expanding the growing arsenal of process analysis tools. What has so far been missing in this new research stream are techniques that support comprehensive process drift analysis in terms of localizing, drillingdown, quantifying, and visualizing process drifts. In our research, we built on ideas from concept drift, process mining, and visualization research and present a novel web-based software tool to analyze process drifts, called Visual Drift Detection (VDD). Addressing the comprehensive analysis requirements, our tool is of benefit to researchers and practitioners in the business intelligence and process analytics area. It constitutes a valuable aid to those who are involved in business process redesign projects
Effective entrepreneurial marketing on Facebook - A longitudinal study
Get PDFSocial media offers a myriad of opportunities for entrepreneurial marketing strategies that leverage the power of communities, especially when they are combined with traditional approaches such as celebrity endorsement. The reach, frequency, and speed of communication on social media offer the ideal leverage for the drivers of entrepreneurial marketing. However, the rapid rate of change may threaten the effects of investments in entrepreneurial marketing on social media and they might become only short-lived. Employing structural equation modeling, we test the long-term effect of Facebook-based celebrity endorsement on purchase intention among 234 members of a Facebook fan community in a two-wave longitudinal design. We argue that this relationship is mediated by a sponsor's brand image and moderated by brand differentiation. This study is the first to investigate the long-term effects of entrepreneurial marketing on social media. We present the contributions and implications of our findings as they affect research and practice
Determinants and consequences of budget reallocations
Get PDFWe investigate the determinants and consequences of budget reallocations, i.e., corrective actions
to the budget made during the year. Using proprietary data of a large consumer goods
manufacturer, we analyze the extent to which allocation decisions regarding the initial budget drive
subsequent reallocations. Whenever scarce resources need to be allocated among a number of
individuals, power struggles and politicking behavior are likely to arise, which potentially affects
the outcome of the allocation process. We hypothesize and find that one important driver of
reallocation decisions is the firm's aim to correct for systematic deviations from the optimal initial
budget allocation that are driven by successful lobbying activities during the initial budgeting
process. In a more exploratory analysis, we show that such reallocations do not have the desired
effects on market-place performance. In particular, budget cuts are negatively associated with a
product's change in market share. More surprisingly, while budget boosts do help product lines
internally to achieve their sales targets in the last quarter, they do not have a (positive) effect on
the change in market share. Most importantly, our results demonstrate that efficient investment
planning ex ante is essential to achieve an improvement in market-place performance, highlighting
the value of budgeting.Series: Department of Strategy and Innovation Working Paper Serie
User consent modeling for ensuring transparency and compliance in smart cities
Get PDFSmart city infrastructures such as transportation and energy networks are evolving into so-called cyber physical social systems (CPSSs), which collect and leverage citizens’ data in order to adapt services to citizens’ needs. The privacy implications of such systems are, however, significant and need to be addressed. Current systems either try to escape the privacy challenge via anonymization or use very rigid, hard-coded workflows that have been agreed with a data protection authority. In the case of the latter, there is a severe impact on data quality and richness, whereas in the former, only these hard-coded flows are permitted resulting in diminished functionality and potential. We address these limitations via user modeling in terms of investigating how to model and semantically represent user consent, preferences, and data usage policies that will guide the processing of said data in the data lake. Data protection is a horizontal field and consequently very wide. Therefore, we focus on a concrete setting where we extend the domain-agnostic SPECIAL policy language for a smart mobility use case supplied by Vienna’s largest utility provider. To that end, (1) we create an extension of SPECIAL in terms of a core CPSS vocabulary that lowers the semantic gap between the domain agnostic terms of SPECIAL and the vocabulary of the use case; (2) we propose a workflow that supports defining domain-specific vocabularies for complex CPSSs; and (3) show that these two contributions allow successfully achieving the goals of our setting
Ausgewählte Faktoren für den Verbleib bei einem Kfz-Haftpflichtversicherer - Ergebnisse einer empirischen Studie (152 Probanden/-innen) einschließlich aller Datensätze / Selected Factors for Remaining with a Motor Vehicle Third-Party Liability Insurer - Results from an Empirical Study (152 Respondents) Including the Complete Database / Nr. 17 der „Wiener Beiträge zur Betriebswirtschaftlichen Versicherungswissenschaft“ (WrBtrgBwVersWiss)
Get PDFPotential applications of unmanned ground and aerial vehicles to mitigate challenges of transport and logistics-related critical success factors in the humanitarian supply chain
Get PDFThe present decade has seen an upsurge in the research on the applications ofautonomous vehicles and drones to present innovative and sustainable solutions fortraditional transportation and logistical challenges. Similarly, in this study, we proposeusing autonomous cars and drones to resolve conventional logistics and transportchallenges faced by international humanitarian organizations (IHOs) during a reliefoperation. We do so by identifying, shortlisting, and elaborating critical successfactors or key transport and logistics challenges from the existing humanitarianliterature and present a conceptual model to mitigate these challenges byintegrating unmanned ground (UGVs) and aerial vehicles (UAVs) in the humanitariansupply chain. To understand how this novel idea of using UGVs and UAVs could helpIHOs, we drafted three research questions, first focusing on the identification ofexisting challenges, second concentrating on remediation of these challenges, andthe third to understand realization timeline for UGVs and UAVs. This lead to thedevelopment of a semi-structured, open-ended questionnaire to record therespondents’perspectives on the existing challenges and their potential solutions.We gathered data form, ten interviewees, with substantial experience in thehumanitarian sector from six IHOs stationed in Pakistan and Austria. In light of thefeedback for the second research question, we present a conceptual model ofintegrating UAVs and UGVs in the relief chain. The results of the study indicate thattechnological advancement in mobility withholds the potential to mitigate theexisting challenges faced by IHOs. However, IHOs tend to be reluctant in adaptingUGVs compared to UAVs. The results also indicate that the adaptation of thesetechnologies is subject to their technical maturity, and there are no significantdifferences in opinions found between the IHOs from Pakistan and Austria
Opening the black box: Unpacking board involvement in innovation
Get PDFCorporate governance research suggests that boards of directors play key roles in governing company
strategy. Although qualitative research has examined board-management relationships to describe board
involvement in strategy, we lack detailed insights into how directors engage with organizational members
for governing a complex and long-term issue such as product innovation. Our multiple-case study of four
listed pharmaceutical firms reveals a sequential process of board involvement: Directors with deep expertise
govern scientific innovation, followed by the full board's involvement in its strategic aspects. The nature of
director involvement varies across board levels in terms of the direction (proactive or reactive), timing
(regular or spontaneous), and the extent of formality of exchanges between directors and organizational
members. Our study contributes to corporate governance research by introducing the concept of board
behavioral diversity and by theorizing about the multilevel, structural, and temporal dimensions of board
behavior and its relational characteristics
Model-driven decision support to facilitate efficient fresh food deliveries
Get PDFThe delivery of fresh food is challenged by various uncertainties present in daily logistics operations. To facilitate successful operations, this work reviews the recent work on model-driven decision support systems to identify research gaps and derive implications. Introduced systems in literature mainly employ simulation or optimization methods and focus on the consideration of industry specifics such as short shelf lives and the importance of efficient temperature control. Therefore, food quality models are often integrated to enable one to monitor quality throughout supply chain operations and adjust planning procedure respectively. To strengthen research, future work focusing on a stronger consideration of customer-related factors and holistic approaches considering various interdependencies present in fresh food logistics operations are required