TY  - CHAP
A1  - Diekmann, Julian
A1  - Eggert, Mathias
T1  - Is a Progressive Web App an Alternative for Native App Development?
T2  - 3. Wissenschaftsforum: Digitale Transformation (WiFo21) (Lecture Notes in Informatics ; P-319)
N2  - The  existence  of  several  mobile  operating  systems,  such  as  Android  and  iOS,  is  a  challenge for developers because the individual platforms are not compatible with each other and require separate app developments. For this reason, cross-platform approaches have become popular but lack in cloning the native behavior of the different operating systems. Out of the plenty cross-platform approaches, the progressive web app (PWA) approach is perceived as promising but needs further investigation. Therefore, the paper at hand aims at investigating whether PWAs are a suitable alternative  for  native  apps  by  developing  a  PWA  clone  of  an  existing  app.  Two  surveys  are  conducted in which potential users test and evaluate the PWA prototype with regard to its usability. The  survey  results  indicate  that  PWAs  have  great  potential,  but  cannot  be  treated  as  a  general  alternative  to  native  apps.  For  guiding  developers  when  and  how  to  use  PWAs,  four  design guidelines for the development of PWA-based apps are derived based on the results.
KW  - Progressive Web App
KW  - PWA
KW  - Cross-platform
KW  - Evaluation
KW  - Mobile web
Y1  - 2021
SN  - 978-3-88579-713-5
SP  - 35
EP  - 48
PB  - Gesellschaft für Informatik
CY  - Darmstadt
ER  - 
TY  - JOUR
A1  - Bernecker, Andreas
A1  - Boyer, Pierre C.
A1  - Gathmann, Christina
T1  - The Role of Electoral Incentives for Policy Innovation: Evidence from the US Welfare Reform
JF  - American Economic Journal: Economic Policy
Y1  - 2021
U6  - http://dx.doi.org/10.1257/pol.20190690
SN  - 1945-774X
VL  - 13
IS  - 2
SP  - 26
EP  - 57
PB  - American Economic Association
CY  - Nashville, Tenn.
ER  - 
TY  - CHAP
A1  - Schulte, Maximilian
A1  - Eggert, Mathias
T1  - Predicting hourly bitcoin prices based on long short-term memory neural networks
T2  - Proceedings of the International Conference on Wirtschaftsinformatik (WI) 2021
N2  - Bitcoin is a cryptocurrency and is considered a high-risk asset
class whose price changes are difficult to predict. Current research focusses
on daily price movements with a limited number of predictors. The paper at
hand aims at identifying measurable indicators for Bitcoin price movement s
and the development of a suitable forecasting model for hourly changes. The
paper provides three research contributions. First, a set of significant
indicators for predicting the Bitcoin price is identified. Second, the results of
a trained Long Short-term Memory (LSTM) neural network that predicts
price changes on an hourly basis is presented and compared with other
algorithms. Third, the results foster discussions of the applicability of neural
nets for stock price predictions. In total, 47 input features for a period of
over 10 months could be retrieved to train a neural net that predicts the
Bitcoin price movements with an error rate of 3.52 %.
Y1  - 2021
N1  - 16th International Conference on Wirtschaftsinformatik,
March 2021, Essen, Germany
ER  -