M

Maas, A. & Wakker, P. (1994). Additive conjoint measurement for multiattribute utility. Journal of Mathematical Psychology, 38, 86-101.

MacCrimmon, K.R. & Siu, J.K. (1974). Making trade-offs. Decision Sciences, 5, 680-704.

MacKenzie, J. (1992). Evaluating recreation trip attributes and travel time via conjoint analysis. Journal of Leisure Research, 24 (2), 171-184.

MacKenzie, J. (1993). A comparison of contingent preference models. American Journal of Agriculture Economics, 75, 593-603.

MacLachlan, D.L. & Mulhern, M.G. (1991). Measuring brand equity with conjoint analysis. In M. Metegrano (Ed.), 1991 Sawtooth Software Conference Proceedings (pp. 127-140). Ketchum, ID: Sawtooth Software.

MacLachlan, D.L., Mulhern, M.G. & Shocker, A.D. (1988). Attribute selection and representation in conjoint analysis: Reliability and validity issues. In R.M. Johnson (Ed.), Proceedings of the Sawtooth Software Conference of Perceptual Mapping, Conjoint Analysis, and Computer Interviewing (No. 2, pp. 25-35). Ketchum, ID: Sawtooth Software.

MacLauchlan, W.G. (1991a). Scaling prior utilities in Sawtooth Software's adaptive conjoint analysis. In M. Metegrano (Ed.), 1991 Sawtooth Software Conference Proceedings (pp. 251-268). Ketchum, ID: Sawtooth Software.

MacLauchlan, W.G. (1991b). Comment on Chrzan. In M. Metegrano (Ed.), 1991 Sawtooth Software Conference Proceedings (pp. 229-230). Ketchum, ID: Sawtooth Software.

Madansky, A. (1980). On conjoint analysis and quantal choice models. Journal of Business, 53 (3), 537-544.

Madhav, N.S. (1982). Reliability of conjoint analysis: Contrasting data collection procedures. Journal of Marketing Research, 19, 139-143.

Magat, W.A., Viskusi, W.K. & Huber, J. (1988). Paired comparison and contingent valuation approaches to morbidity risk valuation. Journal of Environmental Economics and Management, 15, 395-411.

Mahajan, V., Green, P.E. & Goldberg, S.M. (1982). A conjoint model for measuring self- and cross-price/ demand relationsships. Journal of Marketing Research, 19, 334-342.

Malhotra, N.K. & Jain, A.K. (1982). A conjoint analysis approach to health care marketing and planning. Journal of Health Care Marketing, 2, 35-44.

Malhotra, N.K. (1982). Stuctural reliability and stability of nonmetric conjoint analysis. Journal of Marketing Research, 19, 199-207.

Mallou, J.V., Boubeta, A.R. & Tobio, T.B. (2001). Consumer preferences and brand equity measurement of Spanish national daily newspapers: A conjoint analysis approach. Spanish Journal of Psychology, 4 (1), 48-54.

Manrai, A.K. (1995). Mathematical models of brand choice behavior. European Journal of Operational Research, 82 (1), 1-17.

Manrai, A.K., Manrai, L.A. & Jagpal, S. (1993). Heteroscedasticity in conjoint analysis: Problem, diagnosis, and treatment. Paper presented at the Marketing Science Conference, Washington University, St. Louis, MO.

Manrai, A.K., Manrai, L.A. & Jagpal, S. (1993). Is the OLS driven conjoint analysis adequate for product design, product positioning, and market segmentation? In Chias et al. (Eds.), Marketing for the new Europe: Dealing with complexity (22^nd Annual conference) (pp. 1653-1657). European Marketing Academy.

Mantrale, M.K., Sinha, P. & Zoltners, A.A. (1994). Structuring a multiproduct sales quota-bonus plan for a heterogeneous sales force: A practical model-based approach. Marketing Science, 13, 121-144.

Marcel, G.J., Youngkin, H. & Anthony, B. (1996). Reposable medical device development - creatively meeting customers' needs (applied conjoint analysis & QFD). Paper Presentation, The Eighth Symposium on Quality Function Deployment and International Symposium on QFD '96, Novi, Michigan, June 9-11, 1996.

Marcus, B.H. & Tauber, E.M. (1979). "Trade-off analysis" in marketing analysis and decision making. Boston, MA: Little, Brown and Company, pp. 274-280.???

Markham, F.W., Diamond, J.J. & Hermansen, C.L. (1999). The use of conjoint analysis to study patient satisfaction. Evaluation & the Health Professions, 22 (3), 371-378.

Marshall, D. (1999). Convention interviewing - convenience or reality? In Proceedings of the Sawtooth Software Conference (No. 7, pp. 33-42). Sequim, WA: Sawtooth Software.

Martin, J. & Moore, T.E. (1993). Conjoint analysis: A tool for designing degree programs. Journal of Marketing for Higher Education, 4 (1-2), 379-403.

Marzocchi, G.L., Brasini, S. & Rimessi, M. (2000). New product development in the software industry: The role of conjoint analysis. In A. Gustafsson, A. Herrmann & F. Huber (Eds.), Conjoint measurement - methods and applications (pp. 135-160). Berlin: Springer.

Maser, R. (1997). Wann ist ein Preis optimal? Beispiele empirischer Preisfindung. Planung und Analyse, 5, 48-51.

Matanovich, T., Lilien, G.L. & Rangaswamy, A. (1999). Engineering the price-value relationship. Marketing Management, 8 (1), 48-53.

Mattila, A. (1999). Consumers' value judgements. Cornell Hotel and Restaurant Administration Quarterly, 40 (1), 40-46.

Maurice, H., Horst, H.S., Horne, P.L.M. van &Dijkhuizen, A.A. (1999). Economic analysis of animal welfare aspects in the broiler production chain. Society for Veterinary Epidemiology and Preventive Medicine Proceedings, 182-196.

Mayall, P.D. & Winzar, H.F. (1993a, December). Inter-bank comparison of criteria affecting loan assessment. Paper presented at the Australian Finance Educators' Conference, University of New South Wales.

Mayall, P.D. & Winzar, H.F. (1993b). Loan officer loan assessment: A conjoint analysis (Commerce Faculty Seminar Series). Murdoch University.

Mayall, P.D. & Winzar, H.F. (1995, July). Measuring the adherence of corporate loan officers to bank lending guidelines: An Australian study. Paper presented at the Proceedings of the Third Management Control Systems Symposium, London.

Mazanec, J. (1980). Über den Einsatz der Verbundmessung zur indirekten Erfassung der Präferenzwirksamkeit einzelner Produkteigenschaften. Ein Anwendungsbeispiel für "Sparformen". Zeitschrift für Markt-, Meinungs- und Zukunftsforschung, 23-24, 5261-5289.

Mazumdar, T. (1993). A value-based orientation to new product planning. Journal of Consumer Marketing, 10 (1), 28-41.

McClain, J.O. & Rao, V.R. (1974). Trade-offs and conflicts in evaluation of health system alternatives: Methodology for analysis. Health Service Research, 9, 35.

McCullough, D. (1999). The number of levels effect: A proposed solution. In Proceedings of the Sawtooth Software Conference (No. 7, pp. 109-116). Sequim, WA: Sawtooth Software.

McCullough, D. (2000). An examination of the components of the NOL effect in full-profile conjoint models. In Proceedings of the Sawtooth Software Conference (No. 8, pp. 125-139). Sequim, WA: Sawtooth Software.

McCullough, J. & Best, R. (1979). Conjoint measurement: Temporal stability and structural reliability. Journal of Marketing Research, 19, 26-31.

McCullough, J. & Mundy, W. (1977). Identification of housing market segments using partial preference patterns. In Proceedings of the Southwestern Marketing Association (p. 39). Southwestern Marketing Association.

McCullough, J.M. (1978). Identification of preference through conjoint measurement. Working Paper, University of Arizona, College of Business Administration.

McDermott, J., Bacon, J.R., Pesek, J., Gempesaw, C.M. & Tilmon, H.D. (1999). A conjoint analysis of paper demand by commercial graphic designers. Agricultural and Resource Economics Review, 28 (2), 182-189.

McFadden, D. (1970). Conditional logit analysis of qualitative choice behavior. In P. Zarembka (Ed.), Frontiers in econometrics (pp. 105-142). New York: Academic Press.

McFadden, D. (1976). Quantal choice analysis: A survey. Annals of Economic and Social Measurement, 5, 363-390.

McFadden, D. (1986). The choice theory approach to market research. Marketing Science, 5, 275-295.

McIntosh, E. & Donaldson, C. & Ryan, M. (1999). Recent advances in the methods of cost-benefit analysis in healthcare - Matching the art to the science. Pharmacoeconomics, 15 (4), 357-367.

McLauchlan, W.G. (1991). Scaling prior utilities in Sawtooth Software´s Adaptive Conjoint Analysis. In M. Metegrano (Ed.), 1991 Sawtooth Software Conference Proceedings (pp. 251-268). Sun Valley, ID: Sawtooth Software.

McLauchlan, W.G. (1992). The predictive validity of derived versus stated importance. In M. Metegrano (Ed.), 1992 Sawtooth Software Conference Proceedings (pp. 285-311). Ketchum, ID: Sawtooth Software.

Mehta, R., Moore, W.L., Pavia, T.M. (1992). An examination of the use of unacceptable levels in conjoint analysis. Journal of Consumer Research, 19 (3), 470-476.

Melikides, G. (1998). Schätzverfahren der Präferenzmessung. Unveröffentlichte Diplomarbeit, Westfälische Wilhelms-Universität Münster.

Melles, T. & Holling, H. (1998). Einsatz der Conjoint Analyse in Deutschland. Eine Befragung von Anwendern. Unveröffentlichtes Manuskript, Westfälische Wilhelms-Universität Münster.

Melles, T. & Luzar, M. (1999). Einsatz der Conjoint-Analyse zur Messung individueller Präferenzen via Internet. Manuskript und Präsentation zur 3. German Online Research Tagung vom 28.-29. Oktober in Nürnberg.

Melles, T. (1996). Optimierung der Paarvergleichsaufgabe im Rahmen der adaptiven Conjoint Analyse. Unveröffentlichte Diplomarbeit, Westfälische Wilhelms-Universität Münster.

Melles, T., Laumann, R. & Holling, H. (2000). Validity and reliability of online conjoint analysis. In Proceedings of the Sawtooth Software Conference (No. 8, pp. 31-40). Sequim, WA: Sawtooth Software.

Melles, T. & Möhle, K. (2002). Mehrwertkonzepte und Marktforschung: Der Nutzen von Conjoint-Analysen. SMarkt, 2/02, 19-22.

Melles, T. & Schweitzer, A. (2002). Akzeptanz von alternativen Modellen der Schadenregulierung. Kernergebnisse einer Untersuchung im Auftrag der avanturo GmbH. IVW Management Information, St. Gallener Trendmonitor für Risiko- und Finanzmärkte, 5/02, 3-7.

Memoli, R. (1995). Analyses of homogeneity and multidimensional analyses of preferences: An application for the sociology of tourism [Italian]. Sociologia e Ricerca Sociale, 16 (47-48), 179-203.

Mengen, A. & Tacke, G. (1995). Methodengestütztes Automobil-Pricing mit Conjoint-Measurement. In H. Reuss (Hrsg.), Wettberwerbsvorteile im Automobilhandel. Frankfurt a.M.: Campus-Verlag.

Mengen, A. (1993). Konzeptgestaltung von Dienstleistungsprodukten - Eine Conjoint-Analyse im Luftfrachtmarkt unter Berücksichtigung der Qualitätsunsicherheit beim Dienstleistungskauf. Stuttgart: Schäffer-Poeschl.

Menges, R. (1996). Unsichere Präferenzen und der Gebrauch von Informationsstrategien: Eine experimentelle Untersuchung am Beispiel "Kaffee". Neuried: Ars Una.

Messier, W. & Emery, D. (1980). Some cautionary notes on the use of conjoint measurement for human judgment modeling. Decision Sciences, 11, 678-690.

Meulen, H.A.B. van der, de Snoo, G.R. & Wossink, G.A.A. (1996). Farmers' perception of unsprayed crop edges in the Netherlands. Journal of Environmental Management, 47 (3), 241-255.

Mevorach, B. (1997). The business of elections. Quality & Quantity, 31 (4), 325-335.

Meyer, L. (1998). Predictive accuracy of conjoint analysis by means of World Wide Web survey [Online]. Available: http://www.lucameyer.com/kul/menu.htm.

Meyer, R. & Johnson, E.J. (1995). Empirical generalization in the modeling of consumer choice. Marketing Science, 14 (3 Pt. 2/2), G180-???.

Meyer, R.J. (1982). A dynamic multiattribute model of consumer repeated choice behavior? In R.K. Srivastava & A.D. Shocker (Eds.), Analytic approaches to product and marketing planning: The second conference (Report No. 82-109, pp. 199-227). Cambridge, MA: Marketing Science Institute.

Michell, J. (1988). Theoretical note. Some problems in testing the double cancellation condition in conjoint measurement. Journal of Mathematical Psychology, 32, 466-473.

Michell, J. (1990). An introduction to the logic of psychological measurement. Hillsdale, NJ: Lawrence Erlbaum Associates, Inc., Publishers.

Michell, J. (1999). Measurement in psychology: A critical history of a methodological concept. New York, NY: Cambridge University Press.

Miller, J.T., Ogden, J.R. & Latshaw, C.A. (1998). Using trade-off analysis to determine value-price sensitivity of custom calling features. American Business Review, 1, 8-13.

Minno, J. (1986). Software replaces paper in questionnaire writing / software updated to meet growing market. Marketing News, 20 (1), 66-67.

Minor, L., Klopfenstein, K. & Miller, R.V. (1992). Integrating conjoint results into decision making. In M. Metegrano (Ed.), 1992 Sawtooth Software Conference Proceedings (pp. 191-196). Ketchum, ID: Sawtooth Software.

Mishra, S., Umesh, U.N. & Stem, D.E. (1989). Attribute importance weights in conjoint analysis: Bias and precision. In T.K. Srull (Ed.), Advances in consumer research (No. 16, pp. 605-611). Provo, UT: Association for Consumer Research.

Missler-Behr, M. (2000). Constructing fuzzy utility values in conjoint analysis. Beiträge zur OR 2000 in Dresden, Gesellschaft für Operations Research.

Mittal, V., Katrichis, J.M., Forkin, F. & Konkel, M. (1994). Does satisfaction with multi-attribute products vary over time? In C.T. Allen & D.R. John (Eds.), Advances in consumer research (No. 21, pp. 412-417). Provo, UT: Association for Consumer Research.

Mizuno, M. (1997). Conjoint analysis of consumer preferences in cyber space. Advances in Human Factors Ergonomics, 21 (B), 475-478.

Mohn, N.C. (1989). Comparing simulated purchase 'chip' testing and trade-off (conjoint) analysis. In Proceedings of the Sawtooth Software Conference. Gaining a competitive advantage through PC-based interviewing and analysis (Vol. 1, pp. 53-63). Ketchum, ID: Sawtooth Software.

Mohn, N.C. (1990). Simulated purchase 'chip' testing vs. tradeoff (conjoint) analysis - Coca Cola's experience. Marketing Research, 2 (March), 49-54.

Mohn, N.C. (1995). Price research for decision making. When setting prices, don't rely on judgement alone. Marketing Research, 7 (1), 11-19.

Molin, E.J.E., Oppewal, H. & Timmermans, H.J.P. (2000). A comparison of full profile and hierarchical information integration conjoint methods to modeling group preferences. Marketing Letters, 11 (2), 169-179.

Monroe, K.B. (1973). Buyer's subjective perceptions of price. In Perspectives In H.H. Kassarjian & T.S. Robertson, Consumer behavior (pp. 23-42). Glenview, IL: Scott, Foreman and Company.

Montgomery, D.B. & Wittink, D.R. (1980). The predictive validity of conjoint analysis for alternative aggregation schemes. In D.B. Montgomery & D.R. Wittink (Eds.), Preceedings of the first ORSA/ TIMS special interest conference on market measurement and analysis (pp. 298-309). Cambridge, MA: Marketing Science Institute.

Montgomery, D.B. (1986). Conjoint calibration of the customer/competitor interface in industrial markets. In K. Backhaus & D.T. Wilson (Eds.), Industrial marketing: A German-American perspective (pp 297-319). Berlin: Springer.

Montgomery, D.B., Wittink, D.R. & Glaze, T. (1977). A predictive test of individual level concept evaluation and trade-off analysis (Research Paper No. 415). Stanford, CA: Stanford University, Graduate School of Business.

Mooney, G. (2000). Judging goodness must come before judging quality - But what is the good of health care. International Journal for Quality in Health Care, 12 (5), 389-394.

Moore, R. (1989). Using conjoint strategically to enhance business engineering. In Proceedings of the Sawtooth Software Conference. Gaining a competitive advantage through PC-based interviewing and analysis (Vol. 1, pp. 241-249). Ketchum, ID: Sawtooth Software.

Moore, R. (1992). Doing conjoint analysis on the telephone. In M. Metegrano (Ed.), 1992 Sawtooth Software Conference Proceedings (pp. 245-251). Sun Valley, ID: Sawtooth Software.

Moore, W.L. & Holbrook, M.B. (1990). Conjoint analysis on objects with environmentally correlated attributes: The questionable importance of representative design. Journal of Consumer Research, 16, 490-497.

Moore, W.L. & Semenik, R.J. (1988). Measuring preference with hybrid conjoint analysis: The impact of a different number of attributes in the master design. Journal of Business Research, 16, 261-274.

Moore, W.L. (1980). Levels of aggregation in conjoint analysis: An empirical comparison. Journal of Marketing Research, 17, 516-523.

Moore, W.L. (1990). Factorial preference structure. Journal of Consumer Research, 17, 94-104.

Moore, W.L., Gray-Lee, J. & Louviere, J.J. (1998). A cross-validity comparison of conjoint analysis and choice models at different levels of aggregation. Marketing Letters, 9 (2), 195-208.

Moore, W.L., Louviere, J.J. & Verma, R. (1999). Using conjoint analysis to help design product platforms. Journal of Product Innovation Management, 16 (1), 27-39.

Moore, W.L., Myhta, R.B. & Pavia, T.M. (1994). A simplified method of constrained parameter estimation in conjoint analysis. Marketing Letters, 5 (2), 173-181.

Morgan, A., Shackley, P., Pickin, M. & Brazier, J. (2000). Quantifying patient preferences for out-of-hours primary care. Journal of Health Services Research and Policy, 5 (4), 214-218.

Morgan, J.P. (1995). Computer simulation predicts employee response to contemplated plan redesigns. Employee Benefit Plan Review, 24-27.

Morrison, M., Bennett, J., Blamey, R. & Louviere, J. (2002). Choice modeling and tests of benefit transfer. American Journal of Agricultural Economics, 84 (1), 161-170.

Morton, J. & Devine, H.J. Jr. (1985) How to diagnose what buyers really want. Business Marketing, Oct., 71-83.

Morton, J. & Dubanoski, T.J. (1987). New behavioral model measures price elasticity. Marketing News, 27 (February), 27.

Morton, J. & Rys, M.E. (1987). Price elasticity prediction: New research tool for the competitive '80s, Marketing News, 2 (January), 18.

Moskowitz, H., Cohen, D., Krieger, B. & Rabino, S. (2001). Interest and reaction time analysis of credit card offers: Managerial implications of high level research procedures. Journal of Financial Services Marketing, 6 (2), 172-189.

Moskowitz, H.R. & Cohen, D. (1999). How features of pictures in concepts drive semantic scales profiles and purchase intent utilities in a conjoint task: The case of coffee. Canadian Journal of Market Research, in press.

Moskowitz, H.R. & Gofman, A. (2000, April). Research, politics and the web can mix! Considerations, experiences, trials, tribulations in adapting conjoint measurement to optimising a political position as if it were a consumer product. Paper presented at The Worldwide Internet Conference and Exhibition Net Effects 3, Dublin, Ireland.

Moskowitz, H.R. & Martin, J.G. (1993). How computer aided design and presentation of concept speeds up the product development process. In Proceedings of the 46^th ESOMAR Conference (pp. 405-419). Copenhagen: ESOMAR.

Moskowitz, H.R. (1994). Incorporating consumer feedback into package description and presentation: A multi-media approach. Paper presented at the Conference of Packaging Research with Consumers of the American Society for Testing & Materials, Montreal, Canada.

Moskowitz, H.R. (1996a). Segmenting consumers on the basis of their responses to concept elements: An approach derived from product research. Canadian Journal of Market Research,???.

Moskowitz, H.R. (1996b). Segmenting consumers world-wide by multi-media conjoint methods. Unpublished Paper, White Plains, New York: Moskowitz Jacobs Inc.

Moskowitz, H.R. (1996c). Segmenting consumers world-wide: An application of multiple media conjoint methods. Proceedings of the 49^th E.S.O.M.A.R. Congress (pp. 535-552). Istanbul: ESOMAR.

Moskowitz, H.R., Cofman, A. & Krieger, B. (1996). Accelerating development at the fuzzy front end: Combing ideation & evaluation in a consumer based paradigm. Paper submitted at the 1996 PDMA Research Conference.

Moskowitz, H.R., Gofman, A. & Tungaturthy, P. (1996). Multi-media development and optimization of concepts for a fast food restaurant. Unpublished Paper, Moskowitz Jacobs Inc., White Plains, New York.

Moyo, P.S. (2002). Discrete choice analysis of the feed technology decisions of smallholder dairy farmers in Zimbabwe. Microfiche, National Library of Canada, Ottawa.

Muhlbacher, H. & Botschen, G. (1988). The use of trade-off analysis for the design of holiday travel packages. Journal of Business Research, 17, 117-131.

Mühlbacher, H. & Botschen, G. (1988). The use of trade-off analysis for the design of holiday travel packages. Journal of Business Research, 17, 117-131.

Mühlbacher, H. (1988). Conjoint-Analyse: Präferenzforschung für Marketing-Mix-Entscheidungen. Viertel-Jahresheft für Media- und Werbewirkung, 2, 11-16.

Mukhopadhyay, S.K. & Bhandari, C. (1997). Conjoint measurement approach for machine part grouping in manufacturing cell formation. International Journal of Production Research, 35 (8), 2237-2251.

Mulhern, M.G. (1999). Assessing the relative efficiency of fixed and randomized experimental designs. In Proceedings of the Sawtooth Software Conference (No. 7, pp. 225-232). Sequim, WA: Sawtooth Software.

Müller, J.C. (2001). Empirische Überprüfung der gebrückten Conjoint-Analyse anhand von Präferenzen für Supermärkte. Diplomarbeit, Universität Eichstätt, Wirtschaftswissenschaftliche Fakultät Ingolstadt.

Müller, M. & Schmitz, P.M. (1999). Pricing the environment: Measurement of preferences and willingness to pay for selected landscape functions by the conjoint analysis. Zeitschrift für Kulturtechnik und Landentwicklung, 40 (5/6), 213-219.

Müller, M., Thiele, H. & Wronka, T.C. (1999). Forschungsansätze zur Ermittlung regionaler Präferenzen für Landschaftsfunktionen: Conjoint-Analyse und Contingent-Valuation-Methode. Agrarwirtschaft, 48 (10), 386-388.

Müller, S. & Kesselmann, P. (1994). Die Preisbereitschaft von Konsumenten bei umweltfreundlich verpackten Produkten - Ergebnisse einer Conjoint-Analyse. Zeitschrift für betriebswirtschaftliche Forschung, 3, 260-278.

Müller, S. & Kesselmann, P. (1995). Made in Sachsen: Das Eigenschaftsprofil der "Konsumpatrioten". Jahrbuch für Absatz- und Verbrauchsforschung, 41, 407-421.

Müller, S. & Kesselmann, P. (1996). Buy Regional: Der Stellenwert des "Made in Sachsen" für die Kaufentscheidung ostdeutscher Konsumenten. Die Betriebswirtschaft, 56 (3), 363-377.

Müller-Hagedorn, L., Sewing, E. & Toporowski, W. (1993). Zur Validität von Conjoint-Analysen. Zeitschrift für betriebswirtschaftliche Forschung, 45 (2), 123-148.

Mullet, G.M. & Karson, M.J. (1986). Percentiles of LINMAP conjoint indices of fit for various orthogonal arrays: A simulation study. Journal of Marketing Research, 23, 286-290.

Mulye, R. (1998). An empirical comparison of three variants of the AHP and two variants of conjoint analysis. Journal of Behavioral Decision Making, 11 (4), 263-280.

Mummalaneni, V., Dubas, K.M. & Chao, C. (1996). Chinese purchasing managers' preferences and trade-offs in supplier selection and performance evaluation. Industrial Marketing Management, 25, 115-124.

Musiol, G. & Sladkowski, A. (1998). Beurteilung von Risikofaktoren beim Versandkauf mittels Conjoint- bzw. Clusteranalyse (Beiträge des Instituts für Empirische Wirtschaftsforschung, Nr. 64). Osnabrück: Universität, Institut für empirische Wirtschaftsforschung.