InformaApp - Publikationen

Vortrag

Marion Kohlmeier

Big Data in the Supply Chain Management

1. Bayerisch-Tschechische Wissenschaftskonferenz "Datenanalyse", Jindřichův Hradec, Tschechische Republik

2015

Nari Arunraj, Diane Ahrens

Vortrag

Nari Arunraj

Time Series Sales Forecasting in Food Retail Industry

1. Bayerisch-Tschechische Wissenschaftskonferenz "Datenanalyse", Jindřichův Hradec, Tschechische Republik

2015

Nachhaltig Sonstige

Zeitschriftenartikel

A Hybrid Seasonal Autoregressive Integrated Moving Average and Quantile Regression for Daily Food Sales Forecasting

International Journal of Production Economics, vol. 170, no. Part A, pp. 321-335

2015

DOI: 10.1016/j.ijpe.2015.09.039

Abstract anzeigen

In the retail stage of a food supply chain, food waste and stock-outs occur mainly due to inaccurate forecasting of sales which leads to incorrect ordering of products. The time series sales in food retail industry are characterized by high volatility and skewness, which vary by time. So, the interval forecasts are required by the retail companies to set appropriate inventory policy (reorder point or safety stock level). This paper attempts to develop a seasonal autoregressive integrated moving average with external variables (SARIMAX) model to forecast daily sales of a perishable food. The process of fitting a SARIMAX model in this study involves: (i) the development of Seasonal Autoregressive Integrated Moving Average (SARIMA) model and (ii) combining the SARIMA model and the demand influencing factors using linear regression. As the SARIMAX using multiple linear regression (SARIMA-MLR) model produces only mean forecast, the possibility of underestimation and overestimation is very high due to high service level, peak, and sparse sales in food retail industry. Therefore, a hybrid SARIMA and Quantile Regression (SARIMA-QR) is developed to construct high and low quantile predictions. Instead of extrapolating the quantiles from the mean point forecasts of SARIMA-MLR model based on the assumption of normality, the SARIMA-QR model directly forecasts the quantiles. The developed SARIMA-MLR and SARIMA-QR models are applied in modeling and forecasting of sales data, i.e., the daily sales of banana from a discount retail store in Lower Bavaria, Germany. The results show that the SARIMA-MLR and -QR models yield better forecasts at out-sample data when compared to seasonal naïve forecasting, traditional SARIMA, and multi-layered perceptron neural network (MLPNN) models. Unlike the SARIMA-MLR model, the SARIMA-QR model provides better prediction intervals and a deep insight into the effects of demand influencing factors for different quantiles.

Mobil Sonstige

Zeitschriftenartikel

Marc Türnau

Assessing the impact of long-term mobility choice motivation and short-term mobility means connotation on the use intention of electric cars in rural areas

Transportation Research Part A: Policy and Practice, vol. 75, no. May, pp. 16-29

2015

DOI: 10.1016/j.tra.2015.03.006

Abstract anzeigen

In this study several hypotheses comprising a heuristic framework derived from rational-choice (RC) premises and regarding some potentially influencing variables on future use intention of different vehicle types are tested with a rural area sample. Especially the differentiation between long-term vs. short-term as well as functional/rational vs. extra-functional/emotional motivators is assessed. Results suggest a predominance of functional motivators and rational connotations over extra-functional/emotional ones. The models to check whether short-term or long-term effects dominate did not clearly confirm a predominance of long-term factors as hypothesized. In several regression models a moderating effect of rational short-term connotations on different long-term motivators was found, thus contributing notably to the prediction of future vehicle use-intention. The need for further research and theory-driven modeling is briefly discussed.

Andreas Gegenfurtner, M. Baker, L. Guérin

Vortrag

Assessing transitions of learning with mixed methods

Symposium (Peer-reviewed)

European Association for Research on Learning and Instruction (EARLI) SIG 4 & SIG 17 Conference, Leuven, Belgien

2014

Vortrag

Chancen und Risiken von Meta-Analysen in der pädagogischen Forschung

2014

Vortrag

Lesen fördern in der Grundschule: Was sagt die IGLU-Studie?

Invited Talk/Keynote

2014

Vortrag

Do teachers see everything? How experts and novices perceive classroom information

Invited Talk/Keynote

2014

Andreas Gegenfurtner, M. Vauras

Vortrag

Mixed methods in motivational research: Are more methods always better?

Symposium (Peer-reviewed)

14th International Conference on Motivation 2014: "Understanding and Facilitating the Passion to Learn", Helsinki, Finnland

2014

Abschlussbericht des DFG-Berichts "Teacher Noticing"

2014

S. Brand-Gruwel, L. Testers, Andreas Gegenfurtner

Beitrag (Sammelband oder Tagungsband)

Motivation to transfer: Factors influencing transfer of learned competences to the job

New technologies and the future of teaching, Krakau, Polen

2014

Andreas Gegenfurtner, C. Quesada Pallarès, M. Knogler

Zeitschriftenartikel

Digital simulation-based training: A meta-analysis

British Journal of Educational Technology, vol. 45, no. 6, pp. 1097-1114

2014

Beitrag (Sammelband oder Tagungsband)

Marc Türnau

Ausgewählte Ergebnisse einer Befragung von Elektrofahrzeug-MieterInnen

Mobilität, Gesellschaft und Technik, Deggendorf, vol. 1

2014

Beitrag (Sammelband oder Tagungsband)

Marc Türnau

Subjektiver Nutzen beim Gebrauch von Elektrofahrzeugen im ländlichen Raum

Liegt die Zukunft der Elektromobilität im ländlichen Raum?, Köln

2014

ISBN: 9783940685841

Vortrag

Christoph Karon

LBS Innovation Adoption Factors in Germany: An Expert Review

11. GI/ITG KuVS Fachgespräch Ortsbezogene Anwendungen und Dienste, Darmstadt

2014

Zeitschriftenartikel

Christoph Karon, S. Kang, H.-D. Yang, K. Lee

Voluntary Adoption of the Upgraded Version of Package Software: Kano's Three Factor Perspective

International Journal of Software Engineering and Its Applications, vol. 8, no. 8, pp. 43-54

2014

Abstract anzeigen

Drawing upon Kano’s three factor model of customer satisfaction, this research investigates the differentiated influences of beliefs on negative and positive attitudes that lead to the intention of using the upgraded version of package software. Particularly, we are interested in MS Office that takes up the status of de facto standard in the office automation software market but has rarely attracted the attention of academia. Our focus is on how users come to move to the new upgraded version of the package software that they are almost accustomed to use through previous versions. We find that result demonstrability enhance all the three beliefs (i.e., basic, performance, and excitement factors), meanwhile trialability and social influence demonstrate the mixed-up impacts on these three beliefs. We also found that all these three factors lead to both the negative and positive attitudes unexpectedly from our hypotheses . Meanwhile, we found that positive aspect route starting from compatibility to relative advantage to positive attitude has dominant influence on use intention than the negative aspect does.

Vortrag

Eye movement modeling in medical education

Invited Talk/Keynote

2013

Vortrag