Refine
Year of publication
- 2021 (28) (remove)
Document Type
- Conference Proceeding (28) (remove)
Language
- English (28) (remove)
Is part of the Bibliography
- yes (28)
Keywords
- MOOC (2)
- Alpha-amylase (1)
- Browser Platform (1)
- Convergent thinking (1)
- Creative process (1)
- Discontinued Features (1)
- ERP (1)
- Enterprise Resource Planning (1)
- Enterprise System (1)
- Feature Removal (1)
Institute
- Fachgruppe Betriebswirtschaftslehre (11)
- Institut für Biochemie und Biologie (6)
- Department Psychologie (3)
- Institut für Ernährungswissenschaft (3)
- Institut für Chemie (2)
- Wirtschafts- und Sozialwissenschaftliche Fakultät (2)
- Hasso-Plattner-Institut für Digital Engineering GmbH (1)
- Weitere Einrichtungen (1)
- Wirtschaftswissenschaften (1)
Despite the phenomenal growth of Big Data Analytics in the last few years, little research is done to explicate the relationship between Big Data Analytics Capability (BDAC) and indirect strategic value derived from such digital capabilities. We attempt to address this gap by proposing a conceptual model of the BDAC - Innovation relationship using dynamic capability theory. The work expands on BDAC business value research and extends the nominal research done on BDAC – innovation. We focus on BDAC's relationship with different innovation objects, namely product, business process, and business model innovation, impacting all value chain activities. The insights gained will stimulate academic and practitioner interest in explicating strategic value generated from BDAC and serve as a framework for future research on the subject
Many prediction tasks can be done based on users’ trace data. In this paper, we explored convergent thinking as a personality-related attribute and its relation to features gathered in interactive and non-interactive tasks of an online course. This is an under-utilized attribute that could be used for adapting online courses according to the creativity level to enhance the motivation of learners. Therefore, we used the logfile data of a 60 minutes Moodle course with N=128 learners, combined with the Remote Associates Test (RAT). We explored the trace data and found a weak correlation between interactive tasks and the RAT score, which was the highest considering the overall dataset. We trained a Random Forest Regressor to predict convergent thinking based on the trace data and analyzed the feature importance. The result has shown that the interactive tasks have the highest importance in prediction, but the accuracy is very low. We discuss the potential for personalizing online courses and address further steps to improve the applicability.
The devil in disguise
(2021)
Envy constitutes a serious issue on Social Networking Sites (SNSs), as this painful emotion can severely diminish individuals' well-being. With prior research mainly focusing on the affective consequences of envy in the SNS context, its behavioral consequences remain puzzling. While negative interactions among SNS users are an alarming issue, it remains unclear to which extent the harmful emotion of malicious envy contributes to these toxic dynamics. This study constitutes a first step in understanding malicious envy’s causal impact on negative interactions within the SNS sphere. Within an online experiment, we experimentally induce malicious envy and measure its immediate impact on users’ negative behavior towards other users. Our findings show that malicious envy seems to be an essential factor fueling negativity among SNS users and further illustrate that this effect is especially pronounced when users are provided an objective factor to mask their envy and justify their norm-violating negative behavior.
Spectral detection enables multi-color fluorescence fluctuation spectroscopy studies in living cells
(2021)