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| 2. |
- Aagerup, Ulf, 1969-
(author)
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Accessible luxury fashion brand building via fat discrimination
- 2018
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In: Journal of Fashion Marketing and Management. - Bingley : Emerald Group Publishing Limited. - 1361-2026 .- 1758-7433. ; 22:1, s. 2-16
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Journal article (peer-reviewed)abstract
- Purpose: To investigate if accessible luxury fashion brands discriminate overweight and obese consumers.Design/methodology/approach: The physical sizes of garments are surveyed in-store and compared to the body sizes of the population. A gap analysis is carried out in order to determine whether the supply of clothes match the demand of each market segment.Findings: The surveyed accessible luxury garments come in very small sizes compared to the individuals that make up the population.Research limitations/implications: The survey is limited to London while the corresponding population is British. It is therefore possible that the mismatch between assortments and the population is in part attributable to geographic and demographic factors. The study’s results are however so strikingly clear that even if some of the effect were due to extraneous variables, it would be hard to disregard the poor match between overweight and obese women and the clothes offered to them.Practical implications: For symbolic/expressive brands that are conspicuously consumed, that narrowly target distinct and homogenous groups of people in industries where elitist practices are acceptable, companies can build brands via customer rejection.Social implications: The results highlight ongoing discrimination of overweight and obese fashion consumers.Originality/value: The study is the first to provide quantitative evidence for brand building via customer rejection, and it delineates under which conditions this may occur. This extends the theory of typical user imagery.
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| 3. |
- Aagerup, Ulf, 1969, et al.
(author)
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Green consumer behavior: Being good or seeming good?
- 2016
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In: Journal of Product & Brand Management. - Bingley : Emerald Group Publishing Limited. - 1061-0421. ; 25:3, s. 274-284
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Journal article (peer-reviewed)abstract
- Purpose This paper aims to expand the emerging field of symbolic green consumer behavior (GCB) by investigating the impact of anticipated conspicuousness of the consumption situation on consumers’ choice of organic products. In addition, the paper also explores whether self-monitoring ability and attention to social comparison information (ATSCI) influence GCB in situations of anticipated high conspicuousness. Design/methodology/approach Two experiments test the study’s hypotheses. Findings The results of both experiments show that the anticipation of conspicuousness has a significant effect on GCB. Moreover, in Experiment 2, this effect is moderated by consumers’ level of ATSCI but not by their self-monitoring ability. Research limitations/implications Because ATSCI significantly interacts with green consumption because of the anticipation of a conspicuous setting, although self-monitoring ability does not, we conclude that social identification is an important determinant of green consumption. Practical implications Marketers who focus on building green brands could consider designing conspicuous consumption situations to increase GCB. Social implications Policymakers could enact change by making the environmental unfriendliness of non-eco-friendly products visible to the public and thus increase the potential for GCB. Originality/value The results validate the emerging understanding that green products are consumed for self-enhancement, but also expand the literature by highlighting that a key motivating factor of GCB is the desire to fit in.
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| 4. |
- Aagerup, Ulf, 1969-
(author)
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Intermediate Luxury Fashion : Brand Building via Fat Discrimination
- 2016
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In: 11th Global Brand Conference. - Saltaire, UK : Greenleaf Publishing. ; , s. 23-28
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Conference paper (peer-reviewed)abstract
- Purpose: The purpose of this paper is to investigate if intermediate luxury fashion brands discriminate overweight and obese consumers.Design/methodology/approach: 1,454 intermediate luxury garments were tallied and measured in-store in London. The physical sizes of the garments were matched to the body sizes of the population, and a gap analysis was carried out in order to determine whether the supply of clothes match the relative importance of each market segment.Findings: While previous research shows that mass-market fashion companies do not discriminate overweight and obese consumers, intermediate luxury garments come in very small sizes compared to the individuals that make up the population.Research limitations/implications: The findings show that purveyors of intermediate luxury fashion limit assortments of garments so they avoid fat typical user imagery.Practical implications: Companies that market products that are sensitive to the typical user imagery can optimize their brands by limiting undesirable customer types access to their brands, provided that 1) they have the financial strength to reject customers whose image would be detrimental to the brand, 2) the companies are active in an industry in which people would tolerate customer rejection, and 3) they sell a product that actually can be denied undesirable customers.Social implications: The study shows that fat consumers are relegated to mass-market fashion but are excluded from intermediate luxury fashion. This constitutes a social inequality.Originality/value: The result of this study provides quantitative evidence that companies control assortments to exclude undesirable typical user imagery. It also delineates under which conditions they do it. This adds to the theory of user imagery.
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| 5. |
- Aagerup, Ulf, 1969-
(author)
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Obese models’ effect on fashion brand attractiveness
- 2018
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In: Journal of Fashion Marketing and Management. - Bingley : Emerald Group Publishing Limited. - 1361-2026 .- 1758-7433. ; 22:4, s. 557-570
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Journal article (peer-reviewed)abstract
- Purpose: To investigate the effect of obese models vs. normal weight models on fashion brands’ attractiveness.Design/methodology/approach: An experiment was carried out in which 1,225 university students in Sweden and Brazil rated the attractiveness of a fashion brand worn by a normal weight model and an obese model.Findings: The overall effect of obese models’ effect on fashion brand attractiveness was insignificant. Further, neither culture, nor the consumer’s own weight had a significant effect. There was, however, a significant effect of the participant’s own gender; women rate fashion brands worn by obese models significantly higher on attractiveness than they did fashion brands worn by normal weight models. Men displayed the inverse response.Research limitations/implications: The effect of the model’s ethnicity was beyond the scope of the experiment, and the brand attractiveness scale captured only one aspect of brand character, leaving other potential brand effects for future studies.Practical implications: Companies can use obese models with no overall brand attractiveness penalty across markets and for marketing to women of all sizes. Given men’s negative reactions, such models might however be unsuitable for the male-to-female gift market.Social implications: The results support the use of obese models, which can lead to greater representation of larger women in the media, and consequently, reduced fat stigma.Originality/value: The study validates the theory of user imagery, and it extends the theory by examining how different target consumers react to user imagery traits and thus provides evidence for gender bias towards obese models.
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| 6. |
- Aagerup, Ulf, 1969-, et al.
(author)
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The persuasive effects of emotional green packaging claims
- 2019
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In: British Food Journal. - Bingley : Emerald Group Publishing Limited. - 0007-070X .- 1758-4108. ; 121:12, s. 3233-3246
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Journal article (peer-reviewed)abstract
- Purpose - The purpose of this paper is to investigate the effects of rational green packaging claims vs emotional green packaging claims on consumers' purchase propensity for organic coffee.Design/methodology/approach - Three within-subjects experiment were carried out (N=87, N=245, N=60). The experimental design encompasses packaging with rational green claims, emotional green claims, as well as a neutral (control) claim. Measured variables are introduced to assess participants' environmental commitment and information processing ability. A manipulated between-subjects variable is introduced to test how distraction interacts with preference for the claims.Findings - Overall, consumers prefer products with green claims over those with neutral (control) claims, and products with emotional green claims to those with rational green claims. The studies also reveal that this effect is moderated by participants' environmental commitment, information processing ability and by distraction. The findings were statistically significant (p<0.05).Research limitations/implications - As a lab experiment, the study provides limited generalizability and external validity. Practical implications - For most organic FMCG products, it is advisable to employ emotional packaging claims.Social implications - The presented findings provide marketers with tools to influence consumer behavior toward sustainable choices.Originality/value - The paper validates previous contributions on the effects of product claim types, and extends them by introducing comprehensive empirical data on all the Elaboration Likelihood Model's criteria for rational decision-making; motivation, opportunity and ability.
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| 7. |
- Abbas, Taimoor, et al.
(author)
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A Measurement Based Shadow Fading Model for Vehicle-to-Vehicle Network Simulations
- 2015
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In: International Journal of Antennas and Propagation. - : Hindawi Publishing Corporation. - 1687-5869 .- 1687-5877.
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Journal article (peer-reviewed)abstract
- The vehicle-to-vehicle (V2V) propagation channel has significant implications on the design and performance of novel communication protocols for vehicular ad hoc networks (VANETs). Extensive research efforts have been made to develop V2V channel models to be implemented in advanced VANET system simulators for performance evaluation. The impact of shadowing caused by other vehicles has, however, largely been neglected in most of the models, as well as in the system simulations. In this paper we present a shadow fading model targeting system simulations based on real measurements performed in urban and highway scenarios. The measurement data is separated into three categories, line-of-sight (LOS), obstructed line-of-sight (OLOS) by vehicles, and non-line-of-sight due to buildings, with the help of video information recorded during the measurements. It is observed that vehicles obstructing the LOS induce an additional average attenuation of about 10 dB in the received signal power. An approach to incorporate the LOS/OLOS model into existing VANET simulators is also provided. Finally, system level VANET simulation results are presented, showing the difference between the LOS/OLOS model and a channel model based on Nakagami-m fading.
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| 8. |
- Abdeljaber, Osama, et al.
(author)
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Dynamic Testing of a Laboratory Stadium Structure
- 2016
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In: Geotechnical and Structural Engineering Congress 2016. - Reston, VA : American Society of Civil Engineers (ASCE). - 9780784479742 ; , s. 1719-1728
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Conference paper (other academic/artistic)abstract
- Studies with large physical models are a vital link between the theoretical work and field applications provided that these models are designed to represent real structures where various types and levels of uncertainties can be incorporated. While comprehensive analytical and laboratory joint studies are ongoing at Qatar University, University of Central Florida and University of Alberta, this paper presents the initial findings of dynamic testing at Qatar University. A laboratory stadium structure (grandstand simulator) has been constructed at Qatar University. Capable of housing thirty spectators, Qatar University grandstand simulator is arguably the largest laboratory stadium in the world. The structure is designed in a way that several different structural configurations can be tested in laboratory conditions to enable researchers to test newly developed damage detection algorithms. The study presented in this paper covers the finite element modeling and modal testing of the test structure.
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| 9. |
- Abiri, Najmeh, et al.
(author)
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Establishing strong imputation performance of a denoising autoencoder in a wide range of missing data problems
- 2019
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In: Neurocomputing. - Amsterdam : Elsevier BV. - 0925-2312 .- 1872-8286. ; 365, s. 137-146
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Journal article (peer-reviewed)abstract
- Dealing with missing data in data analysis is inevitable. Although powerful imputation methods that address this problem exist, there is still much room for improvement. In this study, we examined single imputation based on deep autoencoders, motivated by the apparent success of deep learning to efficiently extract useful dataset features. We have developed a consistent framework for both training and imputation. Moreover, we benchmarked the results against state-of-the-art imputation methods on different data sizes and characteristics. The work was not limited to the one-type variable dataset; we also imputed missing data with multi-type variables, e.g., a combination of binary, categorical, and continuous attributes. To evaluate the imputation methods, we randomly corrupted the complete data, with varying degrees of corruption, and then compared the imputed and original values. In all experiments, the developed autoencoder obtained the smallest error for all ranges of initial data corruption.
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| 10. |
- Abiri, Najmeh, et al.
(author)
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Variational auto-encoders with Student’s t-prior
- 2019
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In: ESANN 2019 - Proceedings : The 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning - The 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. - Bruges : ESANN. - 9782875870650
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Conference paper (peer-reviewed)abstract
- We propose a new structure for the variational auto-encoders (VAEs) prior, with the weakly informative multivariate Student’s t-distribution. In the proposed model all distribution parameters are trained, thereby allowing for a more robust approximation of the underlying data distribution. We used Fashion-MNIST data in two experiments to compare the proposed VAEs with the standard Gaussian priors. Both experiments showed a better reconstruction of the images with VAEs using Student’s t-prior distribution.
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