Faculty Profile

Ulf Henning Olsson

Professor - Research and Academic Resources

Biography

I have worked within the following research areas: Structural Equation Modeling (SE); Statistical Modeling (SM); Psychometrics (P); Econometrics (E); and Marketing Research (M).

My teaching areas are the following: Mathematics; Marketing Research; Statistics; Multivariate Statistics; Operational Research; Decision Analysis; Business Research Methods; and Psychometrics.

Publications

Jøreskog, Karl Gustaf; Olsson, Ulf H. & Wallentin, Fan Yang (2016)

Multivariate Analysis with LISREL

Springer.

Foldnes, Njål & Olsson, Ulf H. (2016)

A simple simulation technique for non-normal data with pre-specified skewness, kurtosis and covariance matrix

Multivariate Behavioral Research, 51(2-3), s. 207- 219. Doi: 10.1080/00273171.2015.1133274

Foldnes, Njål & Olsson, Ulf (2015)

Correcting too much or too little? The performance of three chi-square corrections

Multivariate Behavioral Research, 50(5), s. 533- 543. Doi: 10.1080/00273171.2015.1036964

Foldnes, Njål; Foss, Tron & Olsson, Ulf H. (2012)

Residuals and the Residual-Based Statistic for Testing Goodness of Fit of Structural Equation Models

Journal of educational and behavioral statistics, 37(3), s. 367- 386. Doi: 10.3102/1076998611411920

Foldnes, Njål; Olsson, Ulf H. & Foss, Tron (2012)

The effect of kurtosis on the power of two test statistics in covariance structure analysis

British Journal of Mathematical & Statistical Psychology, 65(1), s. 1- 18. Doi: 10.1111/j.2044-8317.2010.02010.x

Hammervold, Randi & Olsson, Ulf (2012)

Testing structural equation models: the impact of error variances in the data generating process

Quality and Quantity, 46(5), s. 1547- 1570. Doi: 10.1007/s11135-011-9466-5

Foss, Tron; Jøreskog, Karl Gustaf & Olsson, Ulf H. (2011)

Testing structural equation models: The effect of kurtosis

Computational Statistics & Data Analysis, 55(7), s. 2263- 2275. Doi: 10.1016/j.csda.2011.01.012

Lofquist, Eric Arne; Greve, Arent & Olsson, Ulf H. (2011)

Modeling attitudes and perceptions as predictors for changing safety margins during organizational change

Safety Science, 49(3), s. 531- 541. Doi: 10.1016/j.ssci.2010.11.007

Gripsrud, Geir; Nes, Erik B. & Olsson, Ulf Henning (2010)

Effects of Hosting a Mega-Sport Event on Country Image

Event Management, 14, s. 193- 204.

Auruskeviciene, Vilte; Pundziene, Asta, Skudiene, Vida, Gripsrud, Geir, Nes, Erik B. & Olsson, Ulf Henning (2010)

Change of Attitudes and Country Image after Hosting Major Sport Events

Engineering Economics, 21(1), s. 53- 59.

Solberg, Carl Arthur & Olsson, Ulf H. (2010)

Management orientation and export performance: the case of Norwegian ICT companies

Baltic Journal of Management, 5(1), s. 28- 50. Doi: 10.1108/17465261011016540

Andreassen, Tor W.; Lorentzen, Bengt G. & Olsson, Ulf Henning (2006)

The impact of non-normality and estimation methods in SEM on satisfaction research in marketing

Quality and Quantity, 40

This paper discusses consequences of violating the normal distribution assumption imbedded in Structural Equation Modeling (SEM). Based on real data from a large sample customer satisfaction survey we follow the procedures as suggested in leading textbooks. We document consequences of this practice and discuss its impact on decision making in marketing.

Olsen, S.O.; Wilcox, J. & Olsson, Ulf Henning (2005)

Consequences of Ambivalence on Satisfaction and Loyalty

Psychology & Marketing, 22(3), s. 247- 269.

Olsson, Ulf Henning; Olsson, Ulf Henning, Foss, Tron & Breivik, Einar (2004)

Two equivalent discrepancy functions for maximum likelihood estimation: Do their test statistics follow a non-central Chi-square distribution under model misspecification?

Sociological Methods & Research, 32(4), s. 453- 500.

Over the years several discrepancy,functions have been introduced both in the literature and in the software of Structural Equation Modeling (SEM). The test statistics for the discrepancy functions associated with Maximum Likelihood (ML), Generalized Least Squares (GLS), and Normal Theory Weighted Least Squares (NWLS) are all asymptotically equivalent. These test statistics are all approximately distributed as central chi-square under correct model specification and if the observed variables are multivariate normally distributed. However, it is known that the distribution of these test statistics will not approximate a central Chi-square distribution for models containing specification error, but is more likely to follow a non-central Chi-square distribution (Browne 1984). This study investigates the empirical distributions of the ML and NWLS discrepancy functions. The study includes 13 different factor models with different types and degrees of specification error It is found, except for small samples, that the empirical distribution of the ML-test statistic outperforms the empirical distribution of the NWLS-test statistic in terms of approximation to the theoretical non-central Chi-square distribution. Furthermore, in some cases, it turned out that the non-central Chi-square approximation was not appropriate even for models that contained minor and moderate degrees of specification error. Abstract: Over the years several discrepancy,functions have been introduced both in the literature and in the softwareof Structural Equation Modeling (SEM). The test statistics for the discrepancy functions associated with Maximum Likelihood (ML), Generalized Least Squares (GLS), and Normal Theory Weighted Least Squares (NWLS) are all asymptotically equivalent. These test statistics are all approximately distributed ascentral chi-square under correct model specification and if the observed variables are multivariate normally distributed.However, it is known that the distribution of these test statistics will not approximate a central Chi-square distribution for models containing specification error, but is more likely to follow a non-central Chi-square distribution (Browne 1984). This study investigates the empirical distributions of the ML and NWLS discrepancy functions. The study includes 13 different factor models with different types and degrees of specification error It is found, except for small samples, thattheempirical distribution of the ML-test statistic outperforms the empirical distribution of the NWLS-test statistic in terms of approximation to the theoretical non-central Chi-square distribution. Furthermore, in some cases, itturned out that the non-central Chi-square approximation was not appropriate even for models that contained minor and moderate degrees of specification error.

Olsson, Ulf Henning; Olsson, Ulf Henning, Foss, Tron & Troye, Sigurd Villads (2003)

Does the ADF fit function decrease when the kurtosis increases?

British Journal of Mathematical & Statistical Psychology, 56(2), s. 289- 303.

Olsson, Ulf Henning & Olsen, Svein Ottar (2002)

The Effect Of Alternative Multientity Scaling Formats on The Consistency of Country-Of-Origin Attitudes

Journal of International Business Studies, 33(1), s. 149- 167. Doi: 10.1057/palgrave.jibs.8491009

This study was particularly designed to respond to Jaffe and Nebenzahl's (1984) suggestion to test whether and how entity-based and attribute-based semantic differential scaling formats could predict purchasing behaviour within a country-of-origin setting. The study includes recent research on survey context effects in order to explain and extend our analysis, and uses attitude consistency theory as a conceptual framework. A comparison of the fit statistics between the two scaling formats on each entity (country) indicates that the attribute-based format estimates a higher attitude response consistency and predictive validity by giving better predictors of global country image (evaluation) and buying frequency of products from the different countries investigated. This study uses data collected from a probability sample of industrial buyers within the seafood industry.

Olsson, Ulf Henning & Breivik, Einar (2001)

Adding variables to improve fit: the effect of model size on fit assessment in LISREL

Structural equation model : present and future : a festschrift in honor of Karl Jöreskog/Robert Cudeck, Stephen du Toit, Dag Sörbom (eds.)

Myrtveit, Ingunn; Stensrud, Erik & Olsson, Ulf Henning (2001)

Analysing data sets with missing data: an empirical evaluation of imputation methods and likelihood-based methods

IEEE Transactions on Software Engineering, 27(11), s. 999- 1013.

Breivik, Einar; Olsson, Ulf H. & Olsson, Ulf H. (2001)

Adding variables to improve fit: the effect of model size on fit assessment in LISREL

Structural equation model : present and future : a festschrift in honor of Karl Jöreskog/Robert Cudeck, Stephen du Toit, Dag Sörbom (eds.)

This paper focuses on the effect of model size on the performance of various fit indices in structural equation models. In particular, the paper contrasts the performance of the root mean square error of approximation index (RMSEA) and the goodness-of-fit index (GFI). RMSEA contains a parsimony adjustment whereas GFI does not. Parsimony correction has been found to work well when comparing alterntive models for the same set of variables (Mulaik, et al., 1989; Williams & Holohan, 1994). However, parsimony ratios also appear to show better overall fit when more observed and latent variables are added to the model. To investigate effects of model size, we examine the fit of models that vary with respect to the number of included variables. Different types and degrees of specification errors are also examined. The findings suggest that RMSEA tends to favor models that include more variables and constructs over models that are simpler. Similar patterns were found for other indices correcting for parsimony. GFI was found to decrease with increasing model size for models containing specification errors that involved the same method factor(s) across submodels. The results suggest that in addition to parsimony, i.e., the number of fixed parameters in relation to the number of free parameters, researchers should also consider model size, i.e.,the number of variables when assessing model fit.

Olsson, Ulf H.; Troye, Sigurd Villads, Foss, Tron & Howell, Roy D. (2000)

The Performance of ML, GLS, and WLS Estimation in Structural Equation Modeling under Conditions of Misspecification and Non-normality

Structural Equation Modeling, 7(4), s. 557- 595.

Breivik, Einar; Olsson, Ulf Henning, Cudeck, Robert, du Toit, Stephen & Sørbom, Dag (2000)

Adding Variables to improve fit: the effect of model size on fit assessment in LISRE

Structural Equation Modeling: The Present and Future. A Festchrift in honor of Karl G. Jøreskog

Olsson, Ulf Henning; Olsson, Ulf Henning, Villads Troye, Sigurd & Howell, Roy D. (1999)

Theoretic Fit and Empirical Fit: The Performance of Maximum Likelihood versus Generalized Least Squares Estima-tion in Structural Equation Models

Multivariate Behavioral Research, 34(1), s. 31- 59.

Olsson, Ulf H.; Heide, Morten & Engeset, Marit Gundersen (1996)

Hotel Guest Satisfaction among Business Travelers

The Cornell Hotel and Restaurant Administration Quarterly, s. 72- 81.

Olsson, Ulf Henning & Grønhaug, Kjell (2011)

Supervising doctorial students. Some experiences, tentative conclusions and advices

[Academic lecture]. FIBE 2011.

Iversen, Nina M.; Hem, Leif Egil, Olsson, Ulf Henning & Olsson, Ulf Henning (2008)

Examining Animosity, Consumer Ethnocentrism as facts of General Country Imgae on Willigness to Buy Foreign Products

[Academic lecture]. Professor Johan Arndt Markedsføringskonferanse.

Gripsrud, Geir; Nes, Erik Bertin & Olsson, Ulf (2006)

Effects on country image by hosting a major sports event

[Academic lecture]. Anziba.

Gripsrud, Geir; Olsson, Ulf Henning & Silkoset, Ragnhild (2004)

Metode og Dataanalyse. Med fokus på beslutninger i bedrifter

[Textbook]. Høyskoleforlaget AS.

Olsson, Ulf Henning (2003)

Do the test statistic for ML, NWLS and GLS follow a non-central chi-square distribution under model mis-specification?

[Academic lecture]. IMPS (The 13. International meeting and the 68. annuaql meeting of the psychometric society.

Bjørnestad, Harald; Olsson, Ulf H., Søyland, Svein & Tolcsiner, Frank (2001)

Matematikk for økonomi og samfunnsfag

[Textbook]. Cappelen Damm Høyskoleforlaget.

Myrtveit, Ingunn; Stensrud, Erik & Olsson, Ulf Henning (2001)

Assessing the Benefits of Imputing ERP Projects with Missing Data

[Academic lecture]. 7th International Software Metrics Symposium.

Solberg, Carl Arthur & Olsson, Ulf H. (2001)

Export Performance and Management Orientation, The Case of Norwegian IT Exporters

[Academic lecture]. The EIBA Conference.

Olsson, Ulf Henning (1999)

Three approaches for assessing performance in structural equation modeling: Evidence from simulated data and application on three models of customer satisfaction

[Academic lecture]. Advanced Research Teqniques Forum.

Gripsrud, Geir & Olsson, Ulf Henning (1999)

Markedsanalyse

[Textbook]. Cappelen Damm Høyskoleforlaget.

Engeset, Marit Gundersen; Troye, Sigurd Villads, Olsson, Ulf Henning, Olsson, Ulf Henning & Heide, Morten (1995)

The structure of satisfaction judgments in a hospitality setting

[Academic lecture]. Fagkonferansen i bedriftsøkonomiske emner (FIBE).

Academic Degrees
Year Academic Department Degree
1996 Agricultural University of Norway Ph.D Dr. Scient.
1981 University of Oslo Master of Science
Work Experience
Year Employer Job Title
2014 - Present BI Norwegian Business School Provost - Research and Academic Resources
2003 - Present BI Norwegian Business School Professor
2010 - 2014 BI Norwegian Business School Vice President - Research and Academic Resources
2004 - 2010 BI Norwegian Business School Dean Graduate Programs
1996 - 2003 Agricultural Universtiy of Norway Assistant Professor
1996 - 2003 Norwegian School of Economics and Business Administration (NHH) Senior lecturer (20%)
1996 - 2003 BI Norwegian Business School Associate Professor/Associate Dean of Undergraduate Studies
1985 - 2003 BI Norwegian Business School Associate professor
1987 - 1995 Buskerud College, Norway Lecturer
1982 - 1986 Hokksund Gymnas Lecturer