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An Experimental Comparison of Two Interactive Visualization Methods for Multicriteria Portfolio Selection

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Book cover Portfolio Decision Analysis

Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 162))

Abstract

We compare two visualization methods for interactive portfolio selection: heatmaps and parallel coordinates. To this end, we conducted an experiment to analyze differences in terms of subjective user evaluations and in terms of objective measures referring to effort, convergence, and the structure of the search process. Results indicate that subjects who used the parallel coordinates visualization found the method easier to use, perceived the selection process as being less effortful, and experienced less decisional conflict than subjects who used the heatmap visualization. Concerning objective measures, we did not find significant differences in the time taken to complete the selection task. However, we found that subjects who used parallel coordinates engaged in a more exploratory approach when investigating the space of efficient portfolios. Finally, the experiments clearly showed that decision-making styles play an important role in users’ attitude toward the visualization method. Our findings suggest that the choice of visualization method has a considerable impact on both the users’ subjective experiences when using a decision support system for portfolio selection, and on their objective performance.

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References

  • Aloysius JA, Davis FD, Wilson DD, Taylor AR, Kottemann JE (2006) User acceptance of multi-criteria decision support systems: the impact of preference elicitation techniques. Eur J Oper Res 169(1):273–285

    Article  Google Scholar 

  • Anderson E (1960) A semigraphical method for the analysis of complex problems. Technometrics 2(3):387–391

    Article  Google Scholar 

  • Andrews D (1972) Plots of high-dimensional data. Biometrics 28(1):125–136

    Article  Google Scholar 

  • Auman JT, Boorman GA, Wilson RE, Travlos GS, Paules RS (2007) Heat map visualization of high-density clinical chemistry data. Physiol Genomics 31(2):352–356

    Article  Google Scholar 

  • Baiocco R, Laghi F, D’Alessio M (2009) Decision-making style among adolescents: relationship with sensation seeking and locus of control. J Adolesc 32(4):963–976

    Article  Google Scholar 

  • Bierstaker JL, Brody RG (2001) Presentation format, relevant task experience and task performance. Manag Audit J 16(3):124–128

    Article  Google Scholar 

  • Borthick AF, Bowen PL, Jones DR, Tse MHK (2001) The effects of information request ambiguity and construct incongruence on query development. Decis Support Syst 32(1):3–25

    Article  Google Scholar 

  • Buchanan JT (1994) An experimental evaluation of interactive MCDM methods and the decision making process. J Oper Res Soc 45(9):1050–1059

    Google Scholar 

  • Bystroem K, Jaervelin K (1995) Task complexity affects information seeking and use. Inform Process Manag 31(2):191–213

    Article  Google Scholar 

  • Campbell DJ (1988) Task complexity: a review and analysis. Acad Manag Rev 13(1):40–52

    Google Scholar 

  • Chernoff H (1973) The use of faces to represent points in k-dimensional space graphically. J Am Stat Assoc 68(342):361–368

    Article  Google Scholar 

  • Chu PC, Spires EE (2000) The joint effects of effort and quality on decision strategy choice with computerized decision aids. Decis Sci 31(2):259–292

    Article  Google Scholar 

  • Coll R, Thyagarajan A, Chopra S (1991) An experimental study comparing the effectiveness of computer graphics data versus computer tabular data. IEEE Trans Syst Man Cybern 21(4): 897–900

    Article  Google Scholar 

  • Coll R, Coll J, Thakur G (1994) Graphs and tables: a four-factor experiment. Commun ACM 37(4):77–86

    Article  Google Scholar 

  • Cook D, Hofman H, Lee EK, Yang H, Nikolau B, Wurtele E (2007) Exploring gene expression data, using plots. J Data Sci 5(2):151–182

    Google Scholar 

  • Davis F (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quart 13(3):319–340

    Article  Google Scholar 

  • De P, Sinha AP, Vessey I (2001) An empirical investigation of factors influencing object-oriented database querying. Inform Technol Manag 2(1):71–93

    Article  Google Scholar 

  • Dickson G, DeSanctis G, McBride DJ (1986) Understanding the effectiveness of computer graphics for decision support: a cumulative experimental approach. Commun ACM 29(1): 40–47

    Article  Google Scholar 

  • Eisen MB, Spellman PT, Brown PO, Botstein D (1998) Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci U S A 95(25):14863–14868

    Article  Google Scholar 

  • Gambetti E, Fabbri M, Bensi L, Tonetti L (2008) A contribution to the Italian validation of the general decision-making style inventory. Pers Indiv Differ 44(4):842–852

    Article  Google Scholar 

  • Gefen D, Straub D (1997) Gender differences in the perception and use of e-mail: an extension to the technology acceptance model. MIS Quart 21(4):389–400

    Article  Google Scholar 

  • Gehlenborg N, Dietzsch J, Nieselt K (2005) A framework for visualization of microarray data and integrated meta information. Inf Vis 4(3):164–175

    Article  Google Scholar 

  • Hair JF (2010) Multivariate data analysis, 7th edn. Pearson, Upper Saddle River

    Google Scholar 

  • Inselberg A (1985) The plane with parallel coordinates. Vis Comput 1(2):69–91

    Article  Google Scholar 

  • Inselberg A (2009) Parallel coordinates – visual multidimensional geometry and its applications. Springer, Berlin

    Google Scholar 

  • Inselberg A, Dimsdale B (1990) Parallel coordinates: a tool for visualizing multi-dimensional geometry. In: Proceedings of the first conference on visualization. IEEE Computer Society Press, Los Alamitos, CA, USA, pp 361–378

    Google Scholar 

  • Kamis A, Stohr E (2006) Parametric search engines: what makes them effective when shopping online for differential products? Inform Manag 43(7):904–918

    Article  Google Scholar 

  • Kibbey C, Calvet A (2005) Molecular property explorer: a novel approach to visualizing SAR using tree-maps and heatmaps. J Chem Inform Model 45(2):523–532

    Article  Google Scholar 

  • Kleiner B, Hartigan JA (1981) Representing points in many dimensions by trees and castles. J Am Stat Assoc 76(374):260–269

    Article  Google Scholar 

  • Koedoot N, Molenaar S, Oosterveld P, Bakker P, de Graeff A, Nooy M, Varekamp I, de Haes H (2001) The decisional conflict scale: further validation in two samples of dutch oncology patients. Patient Educ Couns 45(3):187–193

    Article  Google Scholar 

  • Korhonen P (1991) Using harmonious houses for visual pairwise comparison of multiple criteria alternatives. Decis Support Syst 7(1):47–54

    Article  Google Scholar 

  • Korhonen P, Moskowitz H, Wallenius J (1990) Choice behavior in interactive multiple-criteria decision making. Ann Oper Res 23(1):161–179

    Article  Google Scholar 

  • Korhonen P, Alexander O, Mechitov A, Moshkovich H, Wallenius J (1997) Choice behaviour in a computer-aided multiattribute decision task. J Multi-Crit Decis Anal 6(4):233–246

    Article  Google Scholar 

  • Kottemann J, Davis F (1991) Decisional conflict and user acceptance of multicriteria decision-making aids. Decis Sci 22(4):918–926

    Article  Google Scholar 

  • Larkin J, Simon H (1987) Why a diagram is (sometimes) worth ten thousand words. Cogn Sci 11(1):65–100

    Article  Google Scholar 

  • Lee Z, Wagner C, Shin HK (2008) The effect of decision support system expertise on system use behavior and performance. Inform Manag 45(6):349–358

    Article  Google Scholar 

  • Loo R (2000) A psychometric evaluation of the general decision-making style inventory. Pers Indiv Differ 29(5):895–905

    Article  Google Scholar 

  • Lotov A, Miettinen K (2008) Visualizing the Pareto frontier. In: Branke J, Deb K, Miettinen K, Slowinski R (eds) Multiobjective optimization (LNCS 5252). Springer, Berlin, Heidelberg, New York, pp 213–243

    Chapter  Google Scholar 

  • Lotov A, Bushenkov V, Chernov A (1997) Internet, GIS and interactive decision maps. J Geogr Inform Decis Anal 1(2):118–149

    Google Scholar 

  • Lotov AV, Bushenkov VA, Kamenev GK (2004) Interactive decision maps, approximation and visualization of Pareto frontier. Kluwer, Dordrecht

    Google Scholar 

  • Lusk E, Kersnick M (1979) The effect of cognitive style and report performance on task performance: the MIS design consequences. Manag Sci 25(8):787–798

    Article  Google Scholar 

  • Mennecke B, Crossland M, Killingsworth B (2000) Is a map more than a picture? The role of SDSS technology, subject characteristics, and problem complexity on map reading and problem solving. MIS Quart 24(4):601–629

    Article  Google Scholar 

  • Meyer J, Shinar D, Leiser D (1997) Multiple factors that determine performance with tables and graphs. Hum Factors 39(2):268–286

    Article  Google Scholar 

  • Podowski RM (2006) Visualization of complementary systems biology data with parallel heatmaps. IBM J Res Dev 50(6):575–581

    Article  Google Scholar 

  • Pyrke A, Mostaghim S, Nazemi A (2007) Heatmap visualisation of population based multi objective algorithms. In: Obayashi S, Deb K, Poloni C, Hiroyasu T, Murata T (eds) Evolutionary multi-criterion optimization (LNCS 4403). Springer, Berlin, Heidelberg, New York, pp 361–375

    Chapter  Google Scholar 

  • Scott S, Bruce R (1995) Decision-making style: the development and assessment of a new measure. Educ Psychol Meas 55(5):818–831

    Article  Google Scholar 

  • Smelcer J, Carmel E (1997) The effectiveness of different representation for managerial problem solving: comparing tables and maps. Decis Sci 28(2):391–420

    Article  Google Scholar 

  • Spicer D, Sadler-Smith E (2005) An examination of the general decision making style questionnaire in two UK samples. J Manag Psychol 20(2):137–149

    Google Scholar 

  • Stummer C, Kiesling E, Gutjahr WJ (2009) A multicriteria decision support system for competence-driven project portfolio selection. Int J Inform Technol Decis Making 8(2):379–401

    Article  Google Scholar 

  • Swink M, Speier C (1999) Presenting geographic information: effects of data aggregation, dispersion, and users’ spatial orientation. Decis Sci 30(1):169–195

    Article  Google Scholar 

  • Thunholm P (2004) Decision-making style: habit, style or both? Pers Indiv Differ 36(4):931–944

    Article  Google Scholar 

  • Thunholm P (2008) Decision-making styles and physiological correlates of negative stress: is there a relation? Scand J Psychol 49(3):213–219

    Article  Google Scholar 

  • Venkatesh V, Davis F (2000) A theoretical extension of the technology acceptance model: four longitudinal field studies. Manag Sci 46(2):186–204

    Article  Google Scholar 

  • Venkatesh V, Morris M (2000) Why don’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quart 24(1):115–139

    Article  Google Scholar 

  • Vessey I (1991) Cogntive fit: a theory-based analysis of the graphs versus tables literature. Decis Sci 22(2):219–240

    Article  Google Scholar 

  • Wood R (1986) Task complexity: definition of the construct. Organ Behav Hum Decis Process 37(1):60–82

    Article  Google Scholar 

  • Zhang L, Kuljis J, Liu X (2008) Information visualization for DNA microarray data analysis: a critical review. IEEE Trans Syst Man Cybern C Appl Rev 38(1):42–54

    Article  Google Scholar 

Download references

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Authors and Affiliations

  1. Department of Business Administration, University of Vienna, Bruenner Str. 72, 1210, Vienna, Austria

    Elmar Kiesling & Rudolf Vetschera

  2. Institute of Management Science, Vienna University of Technology, Theresianumgasse 27, 1040, Vienna, Austria

    Johannes Gettinger

  3. Faculty of Business Administration and Economics, Universitaetsstr. 25, 33615, Bielefeld, Germany

    Christian Stummer

Authors
  1. Elmar Kiesling
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  2. Johannes Gettinger
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  3. Christian Stummer
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  4. Rudolf Vetschera
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Corresponding author

Correspondence to Christian Stummer .

Editor information

Editors and Affiliations

  1. , Systems Analysis Laboratory, Aalto University School of Science and T, Aalto, 00076, Finland

    Ahti Salo

  2. Dept. Management Science &, Information Systems, University of Massachusetts, Boston, Morrissey Blvd. 100, Boston, 02125, Massachusetts, USA

    Jeffrey Keisler

  3. , Department of Management, London School of Economics, Houghton Street, London, WC2A 2AE, Montserrat

    Alec Morton

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Kiesling, E., Gettinger, J., Stummer, C., Vetschera, R. (2011). An Experimental Comparison of Two Interactive Visualization Methods for Multicriteria Portfolio Selection. In: Salo, A., Keisler, J., Morton, A. (eds) Portfolio Decision Analysis. International Series in Operations Research & Management Science, vol 162. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-9943-6_9

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