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Prof. Dr. Diane Ahrens

Supply Chain Management, Planning & Design Einkauf und Beschaffungslogistik Produktions- und Distributionslogistik Unternehmensplanspiele Strategieentwicklung Internationales Management

Fakultät Angewandte Wirtschaftswissenschaften (School of Management)

Professorinnen und Professoren

Professorin

Beauftragte für die Gleichstellung von Frauen in Wissenschaft und Kunst der Fakultät AWW, Leitung Technologie Campus Grafenau

A 205

0991/3615-150

Sprechzeiten

Montags, 13.30-14.30 Uhr (A205). Bitte vorherige Anmeldung per E-Mail.

Sortierung:
Monographie
  • Diane Ahrens

Terminplanung und -steuerung patientenbezogener Leistungen im Krankenhaus. Dissertationsschrift (Universität Passau, 2000).

Aachen: Shaker

(2001)

Zeitschriftenartikel
  • Diane Ahrens
  • F. Schupp
  • B. Köppel

Nimm zwei.

In: LOG.Punkt , pg. 44-45

(2008)

Zeitschriftenartikel
  • Diane Ahrens

Internationaler Einkäufer. Immense Bedeutung für die Wettbewerbsfähigkeit von Unternehmen..

In: All About Sourcing , pg. 21

(2012)

Beitrag in Sammelwerk/Tagungsband
  • R. Morvai
  • Z. Szegedi
  • Diane Ahrens

Present Day Problems of SME-Partnerships in Hungarian Food Supply Chains.

pg. 95-104

(2013)

Beitrag in Sammelwerk/Tagungsband
  • Nari Arunraj
  • Diane Ahrens
  • Michael Fernandes
  • M. Müller

Time series sales forecasting to reduce food waste in retail industry.

  • In:
  • International Institute of Forecasters

(2014)

Vortrag
  • Nari Arunraj
  • Diane Ahrens
  • Michael Fernandes
  • Martin Müller

Time series sales forecasting to reduce food waste in retail industry.

Rotterdam 29.06.-02.07.2014.

(2014)

Vortrag
  • Diane Ahrens

Dem Einkaufsverhalten auf der Spur - intelligente Prognosesysteme für den Lebensmitteleinzelhandel.

München/Kulmbach 24.07.2014.

(2014)

Zeitschriftenartikel
  • Nari Arunraj
  • Diane Ahrens

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

In: International Journal of Production Economics (vol. 170) , pg. 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.
Zeitschriftenartikel
  • Diane Ahrens
  • I. Häberle
  • P. Muranyi

Zu große Energiemengen landen im Müll. Energieverluste durch Lebensmittelverschwendung - Experten zeigen Einsparpotentiale auf.

In: Fleischwirtschaft (vol. 96) , pg. 70-75

(2016)

Zeitschriftenartikel
  • Nari Arunraj
  • Diane Ahrens
  • Michael Fernandes

Application of SARIMAX model to forecast daily sales in retail industry.

In: International Journal of Operations Research and Information Systems (IJORIS) (vol. 7) , pg. 1-20

(2016)

DOI: 10.4018/IJORIS.2016040101

Abstract anzeigen

Abstract During retail stage of food supply chain (FSC), food waste and stock-outs occur mainly due to inaccurate sales forecasting which leads to inappropriate ordering of products. The daily demand for a fresh food product is affected by external factors, such as seasonality, price reductions and holidays. In order to overcome this complexity and inaccuracy, the sales forecasting should try to consider all the possible demand influencing factors. The objective of this study is to develop a Seasonal Autoregressive Integrated Moving Average with external variables (SARIMAX) model which tries to account all the effects due to the demand influencing factors, to forecast the daily sales of perishable foods in a retail store. With respect to performance measures, it is found that the proposed SARIMAX model improves the traditional Seasonal Autoregressive Integrated Moving Average (SARIMA) model. Article Preview 1. Introduction Discount retail stores have been a noticeable feature of German retail market since the 1980s. In particular, the growth in number of discount retail stores have significantly increased after reunification of Germany. Recently, there is a growing trend of increasing varieties of fruits and vegetables with year-around availability across all the German discount retail outlets rather than just in their traditional growing season. In order to attract customers and remain competitive in the market, the fruits and vegetables are exported from foreign countries and stocked for longer periods. Particularly, increase in number of retail stores, availability of varieties of fruits and vegetables (in stock) with short shelf-lives, frequent price variations, and different storage conditions increase the complexity and results in huge amount of food waste. In Germany, the retail sector produces the food waste of around 0.5 million tons per year (Kranert et al., 2012). Although the retail sector contributes only 5% of the total food waste in food supply chain, mostly they are avoidable food waste (wasting food which is fit for consumption). The quantity of food waste that occurs in the home (61%) is partially due to the management decisions in the retail sector (e.g. frequent promotions) that stimulate the consumer’s eagerness to purchase, and distract them to equate their demand with the purchase (Arunraj et al., 2014; Gooch et al., 2010). Hence, the proper decision making in the retail sector can help the suppliers and consumers to avoid the food waste. The role of sales forecasting in reducing the food waste in retail stores is a significant topic of discussion in the recent food waste related studies (Mena et al., 2011; Mena et al., 2014). According to Mena et al. (2011) and Stenmarck et al. (2011), the improvement of forecast accuracy is one of the essential remedial measures to reduce the food waste in the retail sector of food supply chain.
Zeitschriftenartikel
  • Ali Fallah-Tehrani
  • Diane Ahrens

Supervised Regression Clustering: A Case Study for Fashion Products.

In: International Journal of Business Analytics (IJBAN) (vol. 3) , pg. 21-40

(2016)

DOI: 10.4018/IJBAN.2016100102

Abstract anzeigen

Clustering techniques typically group similar instances underlying individual attributes by supposing that similar instances have similar attributes characteristic. On contrary, clustering similar instances given a specific behavior is framed through supervised learning. For instance, which fashion products have similar behavior in term of sales. Unfortunately, conventional clustering methods cannot tackle this case, since they handle attributes by a same manner. In fact, conventional clustering approaches do not consider any response, and moreover they assume attributes act by the same importance. However, clustering instances with respect to responses leads to a better data analytics. In this research, the authors introduce an approach for the goal supervised clustering and show its advantage in terms of data analytics as well as prediction. To verify the feasibility and the performance of this approach the authors conducted several experiments on a real dataset derived from an apparel industry.
Beitrag in Sammelwerk/Tagungsband
  • Ali Fallah-Tehrani
  • Diane Ahrens

Improved Forecasting and Purchasing of Fashion Products based on the Use of Big Data Techniques.

  • In:
  • R. Bogaschewsky
  • R. Lasch
  • M. Eßig
  • W. Stölzle

Wiesbaden: Gabler pg. 293-310

DOI: 10.1007/978-3-658-08809-5_13

(2016)

Zeitschriftenartikel
  • Ali Fallah-Tehrani
  • Diane Ahrens

Enhanced predictive models for purchasing in the fashion field by using kernel machine regression equipped with ordinal logistic regression.

In: Journal of Retailing and Consumer Services (vol. 32) , pg. 131-138

(2016)

Abstract anzeigen

Identifying the products which are highly sold in the fashion apparel industry is one of the challenging tasks, which leads to reduce the write off and increases the revenue. In fact, beyond of sales forecasting in general a crucial question remains whether a product may sell well or not. Assuming three classes as substantial, middle and inconsiderable, the forecasting problem comes down to a classification problem, where the task is to predict the class of a product. In this research, we present a probabilistic approach to identify the class of fashion products in terms of sale. Thereafter, we combine kernel machines with a probabilistic approach to empower the performance of kernel machines and eventually to make use of it to predicting the number of sales. The proposed approach is more robust to outliers (in the case of highly sold products) and in addition uses prior knowledge, hence it serves more reliable results. In order to verify the proposed approach, we conducted several experiments on a real data extracted from an apparel retailer in Germany.
Zeitschriftenartikel
  • Nari Arunraj
  • Diane Ahrens

Estimation of Non-Catastrophic Weather Impacts for Retail Industry.

In: International Journal of Retail & Distribution Management (vol. 44) , pg. 731-753

(2016)

Abstract anzeigen

Purpose Weather is often referred as an uncontrollable factor, which influences customer’s buying decisions and causes the demand to move in any direction. Such a risk usually leads to loss to industries. However, only few research studies about weather and retail shopping are available in literature. This study aims at developing a model and to analyse the relationship between weather and retail shopping behavior (i.e., store traffic and sales). Design/methodology/approach. The data set for this research study is obtained from two food retail stores and a fashion retail store located in Lower Bavaria, Germany. All these three retail stores are in same geographical location. The weather data set was provided by a German weather service agency and is from a weather station nearer to the retail stores under study. The analysis for the study was drawn using multiple linear regression with autoregressive elements (MLR-AR). The estimated coefficients of weather variables using MLR-AR model represent corresponding weather impacts on the store traffic and the sales. Findings The snowfall has a significant effect on the store traffic and the sales in both food and fashion retail stores. In food retail store, the risk due to snowfall varies depending on the location of stores. There are also significant lagging effects of snowfall in the fashion retail store. However, the rainfall has a significant effect only on the store traffic in the food retail stores. In addition to these effects, the sales in the fashion retail store are highly affected by the temperature deviation. Research limitations/implications Limitations in availability of data for the weather variables and other demand influencing factors (e.g. promotion, tourism, online shopping, demography of customers etc.) may reduce efficiency of the proposed MLR-AR model. In spite of these limitations, this study can be able to quantify the effects of weather variables on the store traffic and the sales Originality/value. This study contributes to the field of retail distribution by providing significant evidence of relationship between weather and retail business. Unlike previous studies, the proposed model tries to consider autocorrelation property, main and interaction effects between weather variables, temperature deviation and lagging effects of snowfall on the store traffic or the sales. The estimated weather impacts from this model can act as a reliable tool for retailers to explain the importance of different non-catastrophic weather events.
Vortrag
  • Diane Ahrens

Intelligente Warenwirtschaftssysteme mit praktischen Umsetzungsbeispielen im Handel.

  • Fraunhofer-Institut für Verfahrenstechnik und Verpackung.

Bayerisches Staatsministerium für Ernährung, Landwirtschaft und Forsten 17.02.2016.

(2016)

Vortrag
  • Diane Ahrens

Impulses for Economics and Region by Means of Decentralization of Research.

České Budějovice, Tschechien 31.03.-01.04.2016.

(2016)

Zeitschriftenartikel
  • Ali Fallah-Tehrani
  • Diane Ahrens

Modeling Label Dependence for Multi-Label Classification Using the Choquistic Regression.

In: Pattern Recognition Letters (vol. 92) , pg. 75-80

(2017)

DOI: 10.1016/j.patrec.2017.04.018

Abstract anzeigen

While an incorrect identification of underlying dependency in data can lead to a flawed conclusion, recognizing legitimate dependency allows for the opportunity to adapt a model in a correct manner. In this regard, modeling the inter-dependencies in multi-label classification (multi target prediction) is one of the challenging tasks from a machine learning point of view. While common approaches seek to exploit so-called correlated information from labels, this can be improved by assuming the interactions between labels. A well-known tool to model the interaction between attributes is the Choquet integral; it enables one to model non-linear dependencies between attributes. Beyond identifying proper prior knowledge in data (if such knowledge exists), establishing suitable models that are in agreement with prior knowledge is not always a trivial task. In this paper, we propose a first step towards modeling label dependencies for multi-target classifications in terms of positive and negative interactions. In the experimental, we demonstrate real gains by applying this approach.
Beitrag in Sammelwerk/Tagungsband
  • Nari Arunraj
  • Diane Ahrens

Improving food supply chain using hybrid semiparametric regression model.

  • In:
  • R. Bogaschewsky
  • R. Lasch
  • M. Eßig
  • W. Stölzle

Wiesbaden: Gabler pg. 213-238

(2017)

Zeitschriftenartikel
  • Ali Fallah-Tehrani
  • Diane Ahrens

Modified Sequential k‐means Clustering by Utilizing Response: A Case Study for Fashion Products.

In: Expert Systems (vol. 34) , pg. e12226

(2017)

DOI: 10.1111/exsy.12226

Abstract anzeigen

Modified sequential k‐means clustering concerns a k‐means clustering problem in which the clustering machine utilizes output similarity in addition. While conventional clustering methods commonly recognize similar instances at features‐level modified sequential clustering takes advantage of response, too. To this end, the approach we pursue is to enhance the quality of clustering by using some proper information. The information enables the clustering machine to detect more patterns and dependencies that may be relevant. This allows one to determine, for instance, which fashion products exhibit similar behaviour in terms of sales. Unfortunately, conventional clustering methods cannot tackle such cases, because they handle attributes solely at the feature level without considering any response. In this study, we introduce a novel approach underlying minimum conditional entropy clustering and show its advantages in terms of data analytics. In particular, we achieve this by modifying the conventional sequential k‐means algorithm. This modified clustering approach has the ability to reflect the response effect in a consistent manner. To verify the feasibility and the performance of this approach, we conducted several experiments based on real data from the apparel industry.
Vortrag
  • Diane Ahrens

Digital Village - A Bavarian Initiative.

Eindhoven, Niederlande 23.03.2017.

(2017)

Vortrag
  • Diane Ahrens

Digitales Dorf - Von der Vision zur Modellregion.

  • Wirtschafts- und Verkehrsausschuss des Bayerischen Landkreistages.

Neuruppin 25.04.2017.

(2017)

Vortrag
  • Diane Ahrens

Digitales Dorf - Von der Vision zur Modellregion.

  • Wirtschafts- und Verkehrsausschuss des Bayerischen Landkreistages.

Weißenburg i. Bay. 20.06.2017.

(2017)

Vortrag
  • Diane Ahrens

Digitalisierung als Chance für ländliche Gemeinden.

  • Netzwerk Oberösterreich.

Stift Reichersberg, Hausruck/Innviertel, Österreich 02.10.2017.

(2017)

Vortrag
  • Diane Ahrens

Märkte im Wandel - Anforderungen an die Logistik.

Regensburg 09.10.2017.

(2017)

Vortrag
  • Diane Ahrens

Digitalisierung als Chance für ländliche Gemeinden.

  • Netzwerk Oberösterreich.

Kirchschlag bei Linz, Oberösterreich 23.10.2017.

(2017)

Vortrag
  • Diane Ahrens

Prognosen im Lebensmittelkonsum: Weniger Lebensmittelverluste durch Optimierung von Prognosen und Disposition.

Grafenau 06.11.2017.

(2017)

Beitrag in Sammelwerk/Tagungsband
  • Ali Fallah-Tehrani
  • Diane Ahrens

Enhanced Predictive Models for Purchasing in the Fashion Field by Applying Regression Trees Equipped with Ordinal Logistic Regression.

  • In:
  • S. Thomassey
  • X. Zeng

Singapore: Springer pg. 27-45

DOI: 10.1007/978-981-13-0080-6_3

(2018)

Zeitschriftenartikel
  • Mohammed Alnahhal
  • Diane Ahrens

A Simulation-Based System for Calculating Optimal Numbers of Forklift Drivers in Industrial Plants.

In: Bavarian Journal of Applied Sciences (vol. 4) , pg. 354-369

(2018)

DOI: 10.25929/bjas.v4i1.53

Abstract anzeigen

Dieser Artikel beschreibt eine Optimierungsmethode für ein Materialtransportsystem von Gabelstaplern mittels Warteschlangentheorie und Simulation. Ziel ist es, verschiedene Arten von Verschwendung bei den Kapazitätskosten, verspäteten Arbeitsaufträgen und Transportkosten zu reduzieren. Es wird eine gewisse ITInfrastruktur angenommen, wie etwa die Verwendung von Monitoren, um die aktuellen Arbeitsaufträge von verschiedenen Arbeitsplätzen anzuzeigen. Mathematische Gleichungen werden benutzt, um anfängliche obere und untere Grenzen für die benötigten Kapazitätsniveaus zu finden. Danach wird eine Simulation für verschiedene Kapazitätsniveaus innerhalb des Bereichs der theoretischen Ergebnisse durchgeführt, um die genau benötigte Mannzeit für verschiedene Jobsequenzierungsstrategien zu finden. Mit Hilfe der Statistiksoftware R wird ein Tool erstellt, welches Unternehmen für verschiedene Parameter Ergebnisse liefert. Diese Ergebnisse zeigen die Auswirkungen der Verwendung von Batching, unter Berücksichtigung der Begrenzung des Zeilenseitenraums und der Reduzierung der Leerfahrtstrategie für Leistungsmessungen. Die Strategie, das Leerfahren zu reduzieren, indem nach dem nächsten Arbeitsplatz gesucht wird, der einen Auftrag benötigt, ist nicht so effizient, da es die benötigte Kapazität erhöht. Dies liegt daran, dass es die Variabilität der Wartezeit vergrößert und somit den Prozentsatz der verspäteten Bestellungen steigert.
Zeitschriftenartikel
  • Diane Ahrens

Frauenau und Spiegelau werden digital.

In: Der Bayerische Bürgermeister (vol. 71) , pg. 290-293

(2018)

Vortrag
  • Diane Ahrens

Digitale Hörnerdörfer.

06.03.2018.

(2018)

Vortrag
  • Diane Ahrens

Digitalisierung als Chance für ländliche Gemeinden.

Kundl in Tirol, Österreich 15.03.2018.

(2018)

Vortrag
  • Diane Ahrens

Digitalisierung als Chance für ländliche Gemeinden.

  • Netzwerk Oberösterreich.

Vorchdorf, Oberösterreich 19.03.2018.

(2018)

Vortrag
  • Diane Ahrens

Digitales Dorf - Gemeinsam digitale Zukunft schaffen.

  • Bayerischer Städtetag.

Bad Aibling 19.04.2018.

(2018)

Vortrag
  • Diane Ahrens

Anhörung als Sachverständige im Bayerischen Landtag zum Thema "Sicherung der wohnortnahen Versorgung in der Kommune".

  • Ausschuss für Kommunale Fragen, Innere Sicherheit und Sport.

München 25.04.2018.

(2018)

Vortrag
  • Diane Ahrens

Digitale Hörnerdörfer.

Balderschwang/Obermaiselstein 10.09.2018.

(2018)

Vortrag
  • Diane Ahrens

Digitales Dorf.

Nürnberg 17.09.2018.

(2018)

Vortrag
  • Diane Ahrens

Digitales Dorf.

Linz, Österreich 22.10.2018.

(2018)

Vortrag
  • Diane Ahrens

Mega-Trend Digitalisierung.

Grafenau 16.11.2018.

(2018)

Zeitschriftenartikel
  • Diane Ahrens
  • Dietmar Jakob

Digitale Wege erkunden mit BLADL.

In: Der Bayerische Bürgermeister (vol. 102) , pg. 160-161

(2019)

Zeitschriftenartikel
  • Diane Ahrens
  • Sandra Gabert

Ländliche Wege in die digitale Zukunft. Was ist bislang in den digitalen Dörfern passiert?.

In: Der Bayerische Bürgermeister (vol. 102) , pg. 155-159

(2019)

Monographie
  • Akademie für Politische Bildung Tutzing
  • Bayerischer Landtag
  • Diane Ahrens

Akademiegespräche im Bayerischen Landtag. Diane Ahrens: Zukunftsdörfer - Digitalisierung als Chance für den ländlichen Raum. Veranstaltung vom 9. April 2019.

(2019)

Zeitschriftenartikel
  • Diane Ahrens
  • Stefanie Seidenhofer
  • Gudrun Fischer

Die Technik macht es möglich.

In: Altenheim - Lösungen fürs Management , pg. 42-44

(2019)

Beitrag in Sammelwerk/Tagungsband
  • Bernhard Bauer
  • Diane Ahrens

Datenbasierte Gäste- und Speiseprognosen in der Gemeinschaftsverpflegung.

  • In:
  • R. Bogaschewsky
  • C. Bode
  • R. Lasch
  • M. Eßig
  • W. Stölzle

Springer Gabler pg. 225-245

DOI: 10.1007/978-3-658-26954-8_11

(2019)

Vortrag
  • Diane Ahrens

Digitale Daseinsfürsorge in Stadt und Land.

  • Akademie für Politische Bildung Tutzing.

Tutzing 01.02.2019.

(2019)

Vortrag
  • Diane Ahrens

Digitales Dorf - "Alles Smart!?".

Salzburg, Österreich 25.02.2019.

(2019)

Vortrag
  • Diane Ahrens
  • Bernhard Bauer

Prognose und Monitoring in der Gemeinschaftsverpflegung - Optimierter Wareneinsatz durch Big Data.

  • Bundesverband Materialwirtschaft, Einkauf und Logistik.

Mannheim 26.03.2019.

(2019)

Vortrag
  • Diane Ahrens

Zukunftsdörfer - Digitalisierung als Chance für den ländlichen Raum. Keynote.

  • Bayerischer Landtag.

München 09.04.2019.

(2019)

Vortrag
  • Diane Ahrens

Digitalisierung des ländlichen Raums.

Landshut 18.09.2019.

(2019)

Vortrag
  • Diane Ahrens

Smart Villages in Bavaria: A Living Lab Approach to Prevent Urbanization.

Ras Al Khaimah, Vereinigte Arabische Emirate 06.11.2019.

(2019)

Vortrag
  • Diane Ahrens

Zukunftsdörfer: Digitalisierung im ländlichen Raum.

St. Quirin am Tegernsee 21.11.2019.

(2019)

Beitrag in Sammelwerk/Tagungsband
  • Lisa-Marie Hanninger
  • Jessica Laxa
  • Diane Ahrens

Rural Areas on Their Way to a Smart Village - Experiences from Living Labs in Bavaria.

  • In:
  • et al.
  • Andreja Pucihar

Maribor: University Press pg. 107-119

(2020)

Beitrag in Sammelwerk/Tagungsband
  • Sebastian Wilhelm
  • Dietmar Jakob
  • Diane Ahrens

Human Presence Detection by monitoring the indoor CO2 concentration.

pg. 199-203

DOI: 10.1145/3404983.3409991

(2020)

Beitrag in Sammelwerk/Tagungsband
  • Sebastian Wilhelm
  • Dietmar Jakob
  • Jakob Kasbauer
  • Melanie Dietmeier
  • A. Gerl
  • Benedikt Elser
  • Diane Ahrens

Organizational, Technical, Ethical and Legal Requirements of Capturing Household Electricity Data for Use as an AAL System.

Singapore: Springer International Publishing

DOI: 10.1007/978-981-15-5856-6_38

(2020)

Beitrag in Sammelwerk/Tagungsband
  • Diane Ahrens

Digitale Dörfer. Gleichwertige Lebensverhältnisse durch Digitalisierung im ländlichen Raum?.

  • In:
  • M. Franz
  • G. Kellermann

München pg. 65-78

(2020)

Zeitschriftenartikel
  • Ali Fallah-Tehrani
  • M. Strickert
  • Diane Ahrens

Class of Monotone Kernelized Classifiers on the basis of the Choquet Integral.

In: Expert Systems (vol. 37) , pg. 1-15

(2020)

DOI: 10.1111/exsy.12506

Abstract anzeigen

The key property of monotone classifiers is that increasing (decreasing) input values lead to increasing (decreasing) the output value. Preserving monotonicity for a classifier typically requires many constraints to be respected by modeling approaches such as artificial intelligence techniques. The type of constraints strongly depends on the modeling assumptions. Of course, for sophisticated models such conditions might be very complex. In this study we present a new family of kernels that we call it Choquet kernels. Henceforth it allows for employing popular kernel‐based methods such as support vector machines. Instead of a naïve approach with exponential computational complexity we propose an equivalent formulation with quadratic time in the number of attributes. Furthermore, since coefficients derived from kernel solutions are not necessarily monotone in the dual form, different approaches are proposed to monotonize coefficients. Finally experiments illustrate beneficial properties of the Choquet kernels.
Monographie
  • S. Sczogiel
  • A. Busch
  • A. Göller
  • A. Gabber
  • B. Williger
  • S. Schmitt-Rüth
  • Diane Ahrens
  • Dietmar Jakob
  • Sebastian Wilhelm

Digital fit im Alter. Handlungsempfehlung für Gemeinden zu Bildungsangeboten für Senioren (Hg.: Fraunhofer-Institut für Integrierte Schaltungen [IIS]; Technische Hochschule Deggendorf [THD]).

(2020)

Vortrag
  • Diane Ahrens

Vortrag zum laufenden Projekt „MeDiLand – Medizin Digital zur Verbesserung der Versorgung auf dem Land“.

München 23.01.2020.

(2020)

Vortrag
  • Diane Ahrens

Ride hailing, car sharing and the car ownership of tomorrow: operating in the shifting global shared mobility market.

Dubai, VAE 25.02.2020.

(2020)

Vortrag
  • Diane Ahrens

Räumliche Unabhängigkeit Dank Digitalisierung.

München 13.07.2020.

(2020)

Vortrag
  • Diane Ahrens

Teilnahme Diskussionspanel „Digitale Kompetenzen als Schlüssel für den Erfolg“.

Online 26.11.2020.

(2020)

Zeitschriftenartikel
  • Lisa-Marie Hanninger
  • Jessica Laxa
  • Diane Ahrens

A roadmap to becoming a smart village: Experiences from living labs in rural Bavaria.

In: eJournal of eDemocracy & Open Government (JeDEM) (vol. 13) , pg. 89-109

(2021)

DOI: 10.29379/jedem.v13i2.635

Abstract anzeigen

This paper illustrates the measures and digital integrations being made in the course of digitalization, using the example of existing rural pilot communities in Bavaria, Germany. The participating communities were selected as part of the government-funded project "Digitales Dorf" (Engl. digital village). Since 2016, digital solutions as well as complementary actions have been identified and implemented to make everyday life in the community equal to that in the city: the main intention is to push digitalization to create equivalent living conditions to urban areas. This paper is intended to provide an overview of the requirements and steps that need to be taken in digital transformation, in order to develop a generalized blueprint for other communities. Furthermore, it introduces the pilot projects, provides an insight into best practices to promote digitalization in traditional rural areas, and focuses on the transformation process rather than on digital solutions.
Zeitschriftenartikel
  • M. Alnahhal
  • Diane Ahrens
  • B. Salah

Dynamic Lead-Time Forecasting Using Machine Learning in a Make-to-Order Supply Chain.

In: Applied Sciences (vol. 11) , pg. 10105

(2021)

DOI: 10.3390/app112110105

Abstract anzeigen

This paper investigates the dynamic forecasting of lead-time, which can be performed by a logistics company for optimizing temporal shipment consolidation. Shipment consolidation is usually utilized to reduce outbound shipments costs, but it can increase the lead time. Forecasting in this paper is performed in a make-to-order supply chain using real data, where the logistics company does not know the internal production data of manufacturers. Forecasting was performed in several steps using machine-learning methods such as linear regression and logistic regression. The last step checks if the order will come in the next delivery week or not. Forecasting is evaluated after each shipment delivery to check the possibility of delaying the current arriving orders for a certain customer until the next week or making the delivery to the customer immediately. The results showed reasonable accuracy expressed in different ways, and one of them depends on a type I error with an average value of 0.07. This is the first paper that performs dynamic forecasting for the purpose of shipment temporal consolidation optimization in the consolidation center.
Beitrag in Sammelwerk/Tagungsband
  • Bernhard Daffner
  • Michael Scholz
  • Jörg Bauer
  • Diane Ahrens

Kapazitäts- und zeitrestringierte Tourenplanung am Beispiel eines mittelständischen Großhändlers.

  • In:
  • G. Reiner
  • F. Starkl
  • M. Prandtstetter
  • T. Walkolbinger
  • U. Brunner
  • S. Stein

Linz, Österreich: Trauner Verlag pg. 207-218

(2021)

Beitrag in Sammelwerk/Tagungsband
  • Dietmar Jakob
  • Sebastian Wilhelm
  • A. Gerl
  • Diane Ahrens

A Quantitative Study on Awareness, Usage and Reservations of Voice Control Interfaces by Elderly People.

(2021)

Zeitschriftenartikel
  • M. Alnahhal
  • Diane Ahrens
  • B. Salah

Modeling Freight Consolidation in a Make-to-Order Supply Chain: A Simulation Approach.

In: Processes (vol. 9) , pg. 1554

(2021)

DOI: 10.3390/pr9091554

Abstract anzeigen

Shipment consolidation is one of main initiatives to reduce CO2 emissions and transportation cost. It reduces the number of shipments per customer and reduces transportation costs by using larger shipments. This paper investigates the temporal consolidation process in a central consolidation center in a make-to-order supply chain. This research was motivated by a case study of a design furniture company that has many suppliers and customers in large parts of Europe. Simulation was used to check the effect of a new and a special time-based temporal consolidation on the response time in outbound logistics. A soft delivery deadline that is less than the average lead time was used because of the long lead time. Arena Software was used to model the supply chain in order to find the best circumstances to use consolidation. Results showed that temporal consolidation could be more effective when order preparation time is with larger variability. The useful waiting is more when there is at least one order every four days. A formula that approximates the percent of reduced shipments was found. Furthermore, many shipments can be reduced without severely affecting the average response time. The value of the study is that it investigates consolidation problems in a high-mix low-volume environment that was overlooked by previous research.
Beitrag in Sammelwerk/Tagungsband
  • Diane Ahrens

Digitalisierung als Thema der Integrierten Ländlichen Entwicklung.

  • In:
  • Deutsche Landeskulturgesellschaft

pg. 15-36

(2021)

Zeitschriftenartikel
  • M. Alnahhal
  • M. Tabash
  • Diane Ahrens

Optimal selection of third-party logistics providers using integer programming: a case study of a furniture company storage and distribution.

In: Annals of Operations Research

(2021)

DOI: 10.1007/s10479-021-04034-y

Abstract anzeigen

This paper investigates the selection of third-party logistics providers (3PLs) based on the best prices offered by them. The focus is on outbound logistics where 3PLs must have their own distribution centres for storage and picking activities. They must also have suitable trucks for distribution to different small-scale customers. The motivation for this paper is a case study from Germany in which a furniture company with hundreds of small customers in ten zones is seeking one or more 3PLs to do the distribution. A mathematical programming model was built based on integer programming where demand per order can be expressed using exponential distribution in each customer zone. The main contribution of this paper is that it finds the best 3PLs based on the different pricing methods of the various providers; this means including the location problem indirectly using the new integer programming model. The model takes into consideration three different methods of pricing based on the offers of five 3PLs. These different methods make it difficult for the decision makers to choose the best solution, especially if specific trends in demand are expected in the future for some customer zones. The results show that future increases in demand in terms of the number of orders or order size could affect the optimal solution. The best pricing method with the lowest variability in cost over time is selected.
Zeitschriftenartikel
  • Domenic Sommer
  • Rainer Bomeisl
  • Diane Ahrens

Projekt: Medizin Digital zur Verbesserung der stationären Pflege auf dem Land. Technik überbrückt Distanzen.

In: CAREkonkret , pg. 8

(2021)

Abstract anzeigen

Informations- und Kommunikationstechnik überbrückt Distanzen zwischen Patienten, Ärzten und Pflegekräften. Während in anderen Studien häufig Einzelanwendungen wie Telediagnostik, Telemonitoring oder Tele-Notärzte untersucht wurden, verfolgte das Projekt MeDiLand einen ganzheitlichen Ansatz. In dem vom Bayerischen Gesundheitsministerium geförderten Projekt (Juli 2018 bis Oktober 2020) wurden neue digitale Wege zur Verbesserung der Gesundheitsversorgung auf dem Land erprobt sowieu.a. Use Cases für den Telemedizineinsatz in der stationären Pflege erfasst. So wurden in einem intersektoralen, patientenzentrierten Netzwerk aus Arztpraxen, Pflegeheimen, Pflegediensten, Kliniken und einer Bergschutzhütte die audiovisuelle Kommunikation und die Übertragung von Vitaldaten erprobt. Neben der Vernetzung heterogener Leistungserbringer sind diverse Use Cases in der Pflege hervorzuheben.
Vortrag
  • Diane Ahrens

Zukunftsdörfer – Digitalisierung als Chance für den ländlichen Raum.

  • Gemeinsames Fachforum der Bund-Länder-Arbeitsgemeinschaft Nachhaltige Landentwicklung (ArgeLandentwicklung) und der Deutschen Landeskulturgesellschaft.

20.01.2021.

(2021)

Vortrag
  • Diane Ahrens

Digitale Dörfer: ein Erfahrungsbericht aus Bayern.

Online 19.08.2021.

(2021)

Vortrag
  • Domenic Sommer
  • Rainer Bomeisl
  • Diane Ahrens

Projekt MeDiLand: Medizin Digital zur Verbesserung der Versorgung auf dem Land. Abstract und Poster.

  • Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V..

digital 26.-30.09.2021.

(2021)

Vortrag
  • Diane Ahrens

Digitalisierung als Thema der Integrierten Ländlichen Entwicklung.

Wiesbaden 13.10.2021.

(2021)

Vortrag
  • Diane Ahrens

Gibt es schon viele Digitale Dörfer?.

  • Deutsche ict + Medienakademie.

Köln 10.11.2021.

(2021)

Vortrag
  • Diane Ahrens

Digitale Dörfer - Digitalisierung als Chance für den Ländlichen Raum. Keynote.

  • Smart City Operations GmbH, Digitale Wirtschaft in Schleswig-Holstein e.V, Wirtschaftsförderung.

Kreis Herzogtum-Lauenburg 25.11.2021.

(2021)

Beitrag in Sammelwerk/Tagungsband
  • Sebastian Wilhelm
  • Dietmar Jakob
  • Jakob Kasbauer
  • Diane Ahrens

GeLaP: German Labeled Dataset for Power Consumption.

  • In:
  • Simon Sherratt
  • Amit Joshi
  • Xin-She Yang
  • Nilanjan Dey

Singapore: Springer Singapore vol. 235 pg. 21-33

DOI: 10.1007/978-981-16-2377-6_5

(2022)

Vortrag
  • Diane Ahrens

Digital Health als Chance für den ländlichen Raum: Erfahrung aus dem Projekt „MeDiLand“. Keynote.

  • Technische Hochschule Deggendorf.

Bad Kötzting 15.02.2022.

(2022)

Vortrag
  • Diane Ahrens

Smarte Kommunen für eine lebenswerte Zukunft. Ländliche Entwicklung unterstützt digitale Transformation von Kommunen.

Online 18.02.2022.

(2022)

Vortrag
  • Diane Ahrens

Impulsvortrag: „Digitalisierung im ländlichen Raum“.

  • Akademie für politische Bildung Tutzing in Kooperation mit der Bayerischen Landeszentrale für politische Bildungsarbeit und dem Bayerischen Volkshochschulverband e.V..

Online 09.03.2022.

(2022)

Vortrag
  • Diane Ahrens

Erkenntnisse aus dem Digitalen Dorf im Handlungsfeld Bildung-Lernen.

  • BDKJ Freyung-Grafenau.

Freyung 16.11.2022.

(2022)

Vortrag
  • Diane Ahrens

Keynote „Digitalisierung in Bayerischen Kommunen“.

  • Bayerisches Staatsministerium für Digitales.

München 24.11.2022.

(2022)

Beitrag in Sammelwerk/Tagungsband
  • Diane Ahrens

Digitale Modelldörfer: vom Konzept zur Umsetzung.

  • In:
  • Diane Ahrens

Wiesbaden: Springer Fachmedien Wiesbaden pg. 45-59

(2023)

Beitrag in Sammelwerk/Tagungsband
  • Frank Edenharter

Der digitale Pflegekompass. Ein kommunales Unterstützungsangebot für Senior:innen in ländlichen Regionen.

  • In:
  • Diane Ahrens

Wiesbaden: Springer Fachmedien Wiesbaden pg. 287-299

DOI: 10.1007/978-3-658-38236-0_18

(2023)

Beitrag in Sammelwerk/Tagungsband
  • Frank Edenharter

Zielgruppenzentrierte Projektarbeit als Erfolgsfaktor für nachhaltige Digitalisierung in ländlichen Räumen.

  • In:
  • Diane Ahrens

Wiesbaden: Springer Fachmedien Wiesbaden pg. 303-309

DOI: 10.1007/978-3-658-38236-0_19

(2023)

Beitrag in Sammelwerk/Tagungsband
  • Domenic Sommer
  • Sebastian Wilhelm
  • Diane Ahrens
  • Florian Wahl

Implementing an Intersectoral Telemedicine Network in Rural Areas: Evaluation from the Point of View of Telemedicine Users.

pg. 15-27

DOI: 10.5220/0011755500003476

(2023)

Beitrag in Sammelwerk/Tagungsband
  • Sandra Gabert
  • Diane Ahrens

Tue Gutes und rede darüber: Sichtbarkeit herstellen.

  • In:
  • Diane Ahrens

Wiesbaden: Springer Fachmedien Wiesbaden pg. 311-328

(2023)

Beitrag in Sammelwerk/Tagungsband
  • Hanna Schürzinger

Die Arbeit im Dorf lassen – Coworking als Perspektive für ländliche Regionen.

  • In:
  • Diane Ahrens

Wiesbaden: Springer Fachmedien Wiesbaden pg. 245-264

DOI: 10.1007/978-3-658-38236-0_16

(2023)

Beitrag in Sammelwerk/Tagungsband
  • Maximilian Geisberger

Smarte Regionen – Ländlicher Raum als Chancenraum?.

  • In:
  • Diane Ahrens

Wiesbaden: Springer Fachmedien Wiesbaden pg. 25-41

DOI: 10.1007/978-3-658-38236-0_3

(2023)

Beitrag in Sammelwerk/Tagungsband
  • Hanna Schürzinger

Digitale Unterstützung der Kommunikation und Zusammenarbeit im Verein.

  • In:
  • Diane Ahrens

Wiesbaden: Springer Fachmedien Wiesbaden pg. 213-225

DOI: 10.1007/978-3-658-38236-0_14

(2023)

Beitrag in Sammelwerk/Tagungsband
  • Tobias Ruscheinski

Herausforderungen ländlicher Räume – das Ziel gleichwertiger Lebensverhältnisse.

  • In:
  • Diane Ahrens

Wiesbaden: Springer Fachmedien Wiesbaden pg. 9-23

DOI: 10.1007/978-3-658-38236-0_2

(2023)

Beitrag in Sammelwerk/Tagungsband
  • Diane Ahrens

Digitales Dorf zum Nachmachen.

  • In:
  • Diane Ahrens

Wiesbaden: Springer Fachmedien Wiesbaden pg. 401-412

(2023)

Zeitschriftenartikel
  • Sebastian Wilhelm
  • Jakob Kasbauer
  • Dietmar Jakob
  • Benedikt Elser
  • Diane Ahrens

Exploiting Smart Meter Water Consumption Measurements for Human Activity Event Recognition.

In: Journal of Sensor and Actuator Networks (Special Issue Smart Cities and Homes: Current Status and Future Possibilities) (vol. 12)

(2023)

DOI: 10.3390/jsan12030046

Abstract anzeigen

Human activity event recognition (HAER) within a residence is a topic of significant interest in the field of ambient assisted living (AAL). Commonly, various sensors are installed within a residence to enable the monitoring of people. This work presents a new approach for HAER within a residence by (re-)using measurements from commercial smart water meters. Our approach is based on the assumption that changes in water flow within a residence, specifically the transition from no flow to flow above a certain threshold, indicate human activity. Using a separate, labeled evaluation data set from three households that was collected under controlled/laboratory-like conditions, we assess the performance of our HAER method. Our results showed that the approach has a high precision (0.86) and recall (1.00). Within this work, we further recorded a new open data set of water consumption data in 17 German households with a median sample rate of 0.083̲ Hz to demonstrate that water flow data are sufficient to detect activity events within a regular daily routine. Overall, this article demonstrates that smart water meter data can be effectively used for HAER within a residence.
Beitrag in Sammelwerk/Tagungsband
  • Dietmar Jakob
  • Sebastian Wilhelm
  • A. Gerl
  • Florian Wahl
  • Diane Ahrens

Voice Controlled Devices: A Comparative Study of Awareness, Ownership, Usage, and Reservations Between Young and Older Adults.

  • In:
  • Q. Gao
  • J. Zhou

Cham: Springer Nature Switzerland vol. 14042 pg. 348-365

DOI: 10.1007/978-3-031-34866-2_25

(2023)

Beitrag in Sammelwerk/Tagungsband
  • Diane Ahrens

Vision: Zukunftsdörfer.

  • In:
  • Diane Ahrens

Wiesbaden: Springer Fachmedien Wiesbaden pg. 415-426

(2023)

Beitrag in Sammelwerk/Tagungsband
  • Diane Ahrens

Anforderungen der digitalen Transformation in ländlichen Räumen.

  • In:
  • Deutsche Landeskulturgesellschaft

pg. 19-30

(2023)

Beitrag in Sammelwerk/Tagungsband
  • Domenic Sommer

Projekt „MeDiLand“ – Medizin Digital zur Verbesserung der Versorgung auf dem Land.

  • In:
  • Diane Ahrens

Wiesbaden: Springer Fachmedien Wiesbaden pg. 187-211

DOI: 10.1007/978-3-658-38236-0_13

(2023)

Vortrag
  • Diane Ahrens

Bürgerpartizipation als Erfolgsgarant für digitale Transformation im ländlichen Raum. Keynote.

  • Institut für Kommunikations- und Medienwissenschaft der Universität Leipzig.

Online 27.03.2023.

(2023)

Vortrag
  • Diane Ahrens

Impulsvortrag „Kommunale Digitalität“.

  • Bayerisches Staatsministerium für Ernährung, Landwirtschaft und Forsten.

München 14.09.2023.

(2023)

Vortrag
  • Diane Ahrens

Digitalisierung im Ländlichen Raum.

Bad Kissingen 18.10.2023.

(2023)

Vortrag
  • Diane Ahrens

Requirements of digital transformation in rural areas.

München 26.10.2023.

(2023)

Beitrag in Sammelwerk/Tagungsband
  • Dietmar Jakob
  • Johannes Kuchler
  • Diane Ahrens
  • Florian Wahl

Activities to Encourage Older Adults’ Skills in the Use of Digital Technologies on the Example of Multigenerational Houses in Germany.

  • In:
  • Q. Gao
  • J. Zhou

Cham: Springer Nature Switzerland pg. 131-145

DOI: 10.1007/978-3-031-61543-6_10

(2024)

Vortrag
  • Diane Ahrens

KINO Handwerk - Künstliche Intelligenz Niederbayern-Oberpfalz im Handwerk.

München 29.02.2024.

(2024)

Vortrag
  • Diane Ahrens

Entwicklung des ländlichen Raums - Stärkung der touristischen Attraktivität mit digitalen Lösungen.

  • Bayerisches Staatsministerium für Ernährung, Landwirtschaft, Forsten und Tourismus.

München 10.07.2024.

(2024)

Zeitschriftenartikel
  • Dietmar Jakob
  • Sebastian Wilhelm
  • A. Gerl
  • Diane Ahrens
  • Florian Wahl

Adapting Voice Assistant Technology for Older Adults: A Comprehensive Study on Usability, Learning Patterns, and Acceptance.

In: Digital (vol. 5) , pg. 4

(2025)

DOI: 10.3390/digital5010004

Abstract anzeigen

This study investigates the integration, usability, and learning patterns associated with voice assistant technology among older adults, focusing on the “Amazon Echo Show 10, 3rd generation” as a case study. Conducted with 32 participants aged 55 and above in senior and complementary households, this research employs a mixed-method approach, incorporating qualitative interviews and quantitative voice command logging over a twelve-week period. Our findings reveal a high level of learnability and usability of the voice assistant, with 90% of participants finding the device easy to learn and use. The study further explores the patterns of voice assistant use, highlighting a preference for listening to music and seeking information, predominantly on weekends. Despite initial reservations, participants reported a high satisfaction level, with most not feeling monitored by the device. Key recommendations for manufacturers include prioritizing the design and user experience to cater to older adults’ needs, aiming to enhance their digital inclusion and participation. This study contributes to the human–computer interaction (HCI) field by providing insights into older adults’ interactions with voice assistant technology, emphasizing the importance of designing accessible and user-friendly digital solutions for the aging population.

Projekte

Mehrere, z.B. Industrie 4.0 Werkstatt Bayerischer Wald, MeDiLand, Digitales Dorf

Labore

Technologie Campus Grafenau

Kernkompetenzen

Supply Chain Management, Einkauf und Logistik Automatisierung von Planungs- und Steuerungsprozessen in Beschaffung und Produktion Strategieentwicklung Digitalisierung im ländlichen Raum

Vita

Prof. Dr. Diane Ahrens studierte Betriebswirtschaftslehre an der Universität Passau, an der sie auch zum Dr. rer. pol. promovierte (2000). Industrieerfahrung im Bereich Einkauf und Logistik sammelte sie zunächst als Fachreferentin, später als Direktorin der Abteilung Policies and Programs der Zentralstelle Global Supply Chain and Procurement der Siemens AG in München. Sie kann auf Lehr- und Forschungserfahrung in China, Ungarn, Russland, Indien und Australien zurückblicken. 2003 wurde sie an die Hochschule Hof als Professorin für Internationale Unternehmensführung und Logistik sowie 2009 an die Technische Hochschule Deggendorf berufen. Neben ihrer Lehre leitet sie dort am Technologie Campus Grafenau ein 50-köpfiges Forschungsteam, spezialisiert auf Digitalisierung und Künstliche Intelligenz, das unter anderem drei der fünf digitalen Modelldörfer in Bayern betreut.