Entwicklung von visual-analytics: Anwendungen zur raumzeitlichen analyse von kraftstoffpreisen

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Titel in ÜbersetzungDevelopment of visual analytics tools for spatiotemporal analysis of petrol prices
OriginalspracheDeutsch
Seiten (von - bis)256-261
Seitenumfang6
FachzeitschriftKartographische Nachrichten
Jahrgang66
Ausgabenummer5
PublikationsstatusVeröffentlicht - 1 Sept. 2016
Extern publiziertJa

Abstract

Since late 2013 German petrol stations have to report their prices to a register at the German Federal Cartel Office in real-time. An extract of these data was analyzed regarding local reactionary pricing behaviour between competitors. Typical pricing patterns were found per station and brand. Based on the hypothesis that pricing not fitting these patterns might induce reactions at the observant competitors, analysis regarding stations' irregular pricing and subsequent pricing reactions of their competitors was performed. For this purpose PostgreSQL/PostGIS (data management and calculations), Leaflet (maps) and various D3-based libraries (diagrams) were used to develop two web-based visual analytics tool prototypes.

Schlagwörter

    Petrol prices, Spatiotemporal analysis, Visual Analytics

ASJC Scopus Sachgebiete

Zitieren

Entwicklung von visual-analytics: Anwendungen zur raumzeitlichen analyse von kraftstoffpreisen. / Kröger, Johannes.
in: Kartographische Nachrichten, Jahrgang 66, Nr. 5, 01.09.2016, S. 256-261.

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Kröger J. Entwicklung von visual-analytics: Anwendungen zur raumzeitlichen analyse von kraftstoffpreisen. Kartographische Nachrichten. 2016 Sep 1;66(5):256-261. doi: 10.1007/BF03545283
Kröger, Johannes. / Entwicklung von visual-analytics : Anwendungen zur raumzeitlichen analyse von kraftstoffpreisen. in: Kartographische Nachrichten. 2016 ; Jahrgang 66, Nr. 5. S. 256-261.
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title = "Entwicklung von visual-analytics: Anwendungen zur raumzeitlichen analyse von kraftstoffpreisen",
abstract = "Since late 2013 German petrol stations have to report their prices to a register at the German Federal Cartel Office in real-time. An extract of these data was analyzed regarding local reactionary pricing behaviour between competitors. Typical pricing patterns were found per station and brand. Based on the hypothesis that pricing not fitting these patterns might induce reactions at the observant competitors, analysis regarding stations' irregular pricing and subsequent pricing reactions of their competitors was performed. For this purpose PostgreSQL/PostGIS (data management and calculations), Leaflet (maps) and various D3-based libraries (diagrams) were used to develop two web-based visual analytics tool prototypes.",
keywords = "Petrol prices, Spatiotemporal analysis, Visual Analytics",
author = "Johannes Kr{\"o}ger",
note = "Funding Information: Abuzaid, A. H.; Mohamed, I. B.; Hussin, A. G. (2012): Boxplot for circular variables. In: Computational Statistics 2012, 27(3):381-392. doi:10.1007/s00180-011-0261-5 Andrienko, N.; Andrienko, G.; Gatalsky, P. (2003): Exploratory Spatio-Temporal Visualization: an Analytical Review. In: Journal of Visual Languages and Computing, Vol. 14 No. 6, December 2003, pp. 503–541 Andrienko, N.; Andrienko, G. (2006): Exploratory Analysis of Spatial and Temporal Data: A Systematic Approach. Springer Berlin Heidelberg Bostock, M.; Ogievetsky, V.; Heer, J. (2011): D3: Data-Driven Documents. In: IEEE Trans. Visualization & Comp. Graphics (Proc. InfoVis) Bundesgesetzblatt (2012): Gesetz zur Einrichtung einer Markttransparenzstelle f{\"u}r den Gro{\ss}handel mit Strom und Gas. Bundesgesetzblatt Jahrgang 2012 Teil I Nr. 57, ausgegeben zu Bonn am 11. Dezember 2012 Bundesgesetzblatt (2013): Verordnung zur Markt-transparenzstelle f{\"u}r Kraftstoffe (MTS-Kraftstoff-Verordnung). 2013, Bonn. Bundesgesetzblatt Jahr-gang 2013 Teil I Nr. 15, ausgegeben zu Bonn am 28.3.2013 Bundeskartellamt (2011): Sektoruntersuchung Kraft-stoffe – Abschlussbericht Mai 2011 – Zusammenfas-sung Bundeskartellamt (2014a): Das Bundeskartellamt, Jahresbericht 2013 Bundeskartellamt (2014b): Ein Jahr Markttranspa-renzstelle f{\"u}r Kraftstoffe (MTS-K): Eine erste Zwi-schenbilanz Bundeskartellamt (2015): Das 2. Jahr Markttranspa-renzstelle f{\"u}r Kraftstoffe (MTS-K) Dewenter, R.; Haucap, J.; Heimeshoff, U. (2012): Ma{\ss}nahmen zur Steigerung des Wettbewerbs auf den Kraftstoffm{\"a}rkten in Deutschland. ADAC Studie zur Mobilit{\"a}t. ADAC, Ressort Verkehr. 2012 ADAC e. V. M{\"u}nchen/Heinrich-Heine-Universit{\"a}t D{\"u}ssel-dorf Fisher, N. I. (1993): Statistical Analysis of Circular Data. Cambridge University Press, 1993. ISBN 9780521350181 G{\"u}nther, A. (2014): Standortverteilungen von Tank-stellenanlagen – als Beispiel f{\"u}r Auswirkungen von technischen und organisatorischen Innovationen auf Dienstleistungsstandorte. Dissertation, Humboldt-Universit{\"a}t zu Berlin, Mathematisch-Naturwissen-schaftliche Fakult{\"a}t II, publiziert am 28.7.2014, urn:nbn:de:kobv:11-100219459 Haucap, J.; Heimeshoff, U.; Siekmann, M. (2015): Price Dispersion and Station Heterogenity on German Retail Gasoline Markets. In: No 171, DICE Discussion Papers, Heinrich‐Heine‐Universit{\"a}t D{\"u}s-seldorf, D{\"u}sseldorf Institute for Competition Economics (DICE) Iglesias, F.; Kastner, W. (2013): Analysis of Similarity Measures in Times Series Clustering for the Discovery of Building Energy Patterns. In: Energies 2013, 6, 579–597 Liao, T. W. (2005): Clustering of time series data – a survey. In: Pattern Recognition 38 (2005) 1857– 1874 Morse, M.; Patel, J. M. (2007): An Efficient and Accurate Method for Evaluating Time Series Similarity. University of Michigan. Ann Arbor, MI. SIGMOD{\textquoteright}07, June 11–14, 2007, Beijing, China Neumeier, S. (2012). Modellierung der Erreichbarkeit von Stra{\ss}entankstellen - Untersuchung zum regio-nalen Versorgungsgrad mit Dienstleistungen der Grundversorgung. Arbeitsberichte aus der vTI-Agrar{\"o}konomie, 9/2012 Rani, S.; Sikka, G. (2012): Recent Techniques of Clustering of Time Series Data: A Survey. In: International Journal of Computer Applications (0975– 8887). Volume 52, No. 15, August 2012 Roberts, J. C. (2007): State of the Art: Coordinated & Multiple Views in Exploratory Visualization. In: Coordinated and Multiple Views in Exploratory Visualization, 2007. CMV '07 Robinson, A. C.; Weaver, C. (2006): Re-visualization: Interactive visualization of the progress of visual analytics. In Proceedings of GIScience Workshop Visual Analytics & Spatial Decision Support, M{\"u}ns-ter, 2006 Schober, D.; Woll, O. (2014): Analyse abgestimmten Verhaltens in Tankstellenm{\"a}rkten: Auswirkungen h{\"o}herer Markttransparenz auf den Wettbewerb. ZEW policy brief, No. 2/2014 Serr{\`a}, J.; Arcos, J. (2014): An Empirical Evaluation of Similarity Measures for Time Series Classification. Artificial Intelligence Research Institute (IIIA-CSIC), Spanish National Research Council, 08193 Bellater-ra, Barcelona, Spain Shen, Z.; Ma, K.-L. (2008): Mobivis: A visualization system for exploring mobile data. In: Visualization Symposium, 2008. PacificVIS {\textquoteright}08. IEEE Pacific, pages 175–182, March Slingsby, A.; Beecham, R.; Wood, J. (2013): Visual analysis of social networks in space and time using smartphone logs. In: Pervasive and Mobile Computing, 9(6), pp. 848-864. doi: 10.1016/j.pmcj.2013.07. 002 Wang, X.; Mueen, A.; Ding, H.; Trajcevski, G.; Scheuermann, P.; Keogh, E. (2013): Experimental Comparison of Representation Methods and Distance Measures for Time Series Data. In: Data Min. Knowl. Discov. Volume 26, Number 2, Pages 275–309. Kluwer Academic Publishers",
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Download

TY - JOUR

T1 - Entwicklung von visual-analytics

T2 - Anwendungen zur raumzeitlichen analyse von kraftstoffpreisen

AU - Kröger, Johannes

N1 - Funding Information: Abuzaid, A. H.; Mohamed, I. B.; Hussin, A. G. (2012): Boxplot for circular variables. In: Computational Statistics 2012, 27(3):381-392. doi:10.1007/s00180-011-0261-5 Andrienko, N.; Andrienko, G.; Gatalsky, P. (2003): Exploratory Spatio-Temporal Visualization: an Analytical Review. In: Journal of Visual Languages and Computing, Vol. 14 No. 6, December 2003, pp. 503–541 Andrienko, N.; Andrienko, G. (2006): Exploratory Analysis of Spatial and Temporal Data: A Systematic Approach. Springer Berlin Heidelberg Bostock, M.; Ogievetsky, V.; Heer, J. (2011): D3: Data-Driven Documents. In: IEEE Trans. Visualization & Comp. Graphics (Proc. InfoVis) Bundesgesetzblatt (2012): Gesetz zur Einrichtung einer Markttransparenzstelle für den Großhandel mit Strom und Gas. Bundesgesetzblatt Jahrgang 2012 Teil I Nr. 57, ausgegeben zu Bonn am 11. Dezember 2012 Bundesgesetzblatt (2013): Verordnung zur Markt-transparenzstelle für Kraftstoffe (MTS-Kraftstoff-Verordnung). 2013, Bonn. Bundesgesetzblatt Jahr-gang 2013 Teil I Nr. 15, ausgegeben zu Bonn am 28.3.2013 Bundeskartellamt (2011): Sektoruntersuchung Kraft-stoffe – Abschlussbericht Mai 2011 – Zusammenfas-sung Bundeskartellamt (2014a): Das Bundeskartellamt, Jahresbericht 2013 Bundeskartellamt (2014b): Ein Jahr Markttranspa-renzstelle für Kraftstoffe (MTS-K): Eine erste Zwi-schenbilanz Bundeskartellamt (2015): Das 2. Jahr Markttranspa-renzstelle für Kraftstoffe (MTS-K) Dewenter, R.; Haucap, J.; Heimeshoff, U. (2012): Maßnahmen zur Steigerung des Wettbewerbs auf den Kraftstoffmärkten in Deutschland. ADAC Studie zur Mobilität. ADAC, Ressort Verkehr. 2012 ADAC e. V. München/Heinrich-Heine-Universität Düssel-dorf Fisher, N. I. (1993): Statistical Analysis of Circular Data. Cambridge University Press, 1993. ISBN 9780521350181 Günther, A. (2014): Standortverteilungen von Tank-stellenanlagen – als Beispiel für Auswirkungen von technischen und organisatorischen Innovationen auf Dienstleistungsstandorte. Dissertation, Humboldt-Universität zu Berlin, Mathematisch-Naturwissen-schaftliche Fakultät II, publiziert am 28.7.2014, urn:nbn:de:kobv:11-100219459 Haucap, J.; Heimeshoff, U.; Siekmann, M. (2015): Price Dispersion and Station Heterogenity on German Retail Gasoline Markets. In: No 171, DICE Discussion Papers, Heinrich‐Heine‐Universität Düs-seldorf, Düsseldorf Institute for Competition Economics (DICE) Iglesias, F.; Kastner, W. (2013): Analysis of Similarity Measures in Times Series Clustering for the Discovery of Building Energy Patterns. In: Energies 2013, 6, 579–597 Liao, T. W. (2005): Clustering of time series data – a survey. In: Pattern Recognition 38 (2005) 1857– 1874 Morse, M.; Patel, J. M. (2007): An Efficient and Accurate Method for Evaluating Time Series Similarity. University of Michigan. Ann Arbor, MI. SIGMOD’07, June 11–14, 2007, Beijing, China Neumeier, S. (2012). Modellierung der Erreichbarkeit von Straßentankstellen - Untersuchung zum regio-nalen Versorgungsgrad mit Dienstleistungen der Grundversorgung. Arbeitsberichte aus der vTI-Agrarökonomie, 9/2012 Rani, S.; Sikka, G. (2012): Recent Techniques of Clustering of Time Series Data: A Survey. In: International Journal of Computer Applications (0975– 8887). Volume 52, No. 15, August 2012 Roberts, J. C. (2007): State of the Art: Coordinated & Multiple Views in Exploratory Visualization. In: Coordinated and Multiple Views in Exploratory Visualization, 2007. CMV '07 Robinson, A. C.; Weaver, C. (2006): Re-visualization: Interactive visualization of the progress of visual analytics. In Proceedings of GIScience Workshop Visual Analytics & Spatial Decision Support, Müns-ter, 2006 Schober, D.; Woll, O. (2014): Analyse abgestimmten Verhaltens in Tankstellenmärkten: Auswirkungen höherer Markttransparenz auf den Wettbewerb. ZEW policy brief, No. 2/2014 Serrà, J.; Arcos, J. (2014): An Empirical Evaluation of Similarity Measures for Time Series Classification. Artificial Intelligence Research Institute (IIIA-CSIC), Spanish National Research Council, 08193 Bellater-ra, Barcelona, Spain Shen, Z.; Ma, K.-L. (2008): Mobivis: A visualization system for exploring mobile data. In: Visualization Symposium, 2008. PacificVIS ’08. IEEE Pacific, pages 175–182, March Slingsby, A.; Beecham, R.; Wood, J. (2013): Visual analysis of social networks in space and time using smartphone logs. In: Pervasive and Mobile Computing, 9(6), pp. 848-864. doi: 10.1016/j.pmcj.2013.07. 002 Wang, X.; Mueen, A.; Ding, H.; Trajcevski, G.; Scheuermann, P.; Keogh, E. (2013): Experimental Comparison of Representation Methods and Distance Measures for Time Series Data. In: Data Min. Knowl. Discov. Volume 26, Number 2, Pages 275–309. Kluwer Academic Publishers

PY - 2016/9/1

Y1 - 2016/9/1

N2 - Since late 2013 German petrol stations have to report their prices to a register at the German Federal Cartel Office in real-time. An extract of these data was analyzed regarding local reactionary pricing behaviour between competitors. Typical pricing patterns were found per station and brand. Based on the hypothesis that pricing not fitting these patterns might induce reactions at the observant competitors, analysis regarding stations' irregular pricing and subsequent pricing reactions of their competitors was performed. For this purpose PostgreSQL/PostGIS (data management and calculations), Leaflet (maps) and various D3-based libraries (diagrams) were used to develop two web-based visual analytics tool prototypes.

AB - Since late 2013 German petrol stations have to report their prices to a register at the German Federal Cartel Office in real-time. An extract of these data was analyzed regarding local reactionary pricing behaviour between competitors. Typical pricing patterns were found per station and brand. Based on the hypothesis that pricing not fitting these patterns might induce reactions at the observant competitors, analysis regarding stations' irregular pricing and subsequent pricing reactions of their competitors was performed. For this purpose PostgreSQL/PostGIS (data management and calculations), Leaflet (maps) and various D3-based libraries (diagrams) were used to develop two web-based visual analytics tool prototypes.

KW - Petrol prices

KW - Spatiotemporal analysis

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JO - Kartographische Nachrichten

JF - Kartographische Nachrichten

SN - 0022-9164

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ER -

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