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Visual design evaluation of consumers’ responses to bottled shower gel packaging
Published in Artde D.K.T. Lam, Stephen D. Prior, Siu-Tsen Shen, Sheng-Joue Young, Liang-Wen Ji, Smart Science, Design & Technology, 2019
Hungyuan Chen, Kuoli Huang, Cheni Huang
The Conjoint analysis (CA) is a popular research technique with the discrete choice analysis (Rohae, 2003) and it is often used to build the correlation between product attributes and the consumers’ evaluations. In the present study, the independent variables in the CA model correspond to the attributes/features of the bottled shower gel packaging, while the dependent variables correspond to the 3 CR descriptions shown in used to characterize the consumer response to the shower gel packaging. Referring to the morphological definitions of the 16 shower gel packaging samples shown in Table 2 and the 3 CR descriptions used to evaluate the consumers’ responses. Table 3 indicates the three CA models that are the relationships between the shower gel packaging and the corresponding 3 CR descriptions. These models also show that the Adjusted R2 values is 0.792 (Cosy and Refreshing), 0.874(Aesthetic and Attractive) and 0.836(Easy to use), respectively. As a consequence, the overall fits of these models are good. The 3 CA models provide designers with the means to obtain the predictive value of likely single CR description to shower gel packaging in terms of its “Cosy and Refreshing”, “Aesthetic and Attractive” and “Easy to use” characteristics if only offer the number coding of corresponding feature for each of its eight attributes.
Test
Published in Walter R. Paczkowski, Deep Data Analytics for New Product Development, 2020
In this section, I will describe the fundamental principles for a discrete choice study. A study is called “discrete choice” because a customer is observed to choose one product over one or more other products in some type of setting, hence the choice is discrete. The setting could be part of a market research survey so the choice is a stated preference choice: the customer states his or her preference for one product over another. This framework was developed to mimic actual market choices in a consumer market in which a consumer goes to a store, sees several products on a store shelf (e.g., cereals) and selects just one to buy on that shopping occasion.
Hunting for treasure: a systematic literature review on urban logistics and e-commerce data
Published in Transport Reviews, 2023
Heleen Buldeo Rai, Laetitia Dablanc
All but 16 inaccessible articles were read, reviewed and analysed in a spreadsheet file, leaving a total of 127 articles to form the review’s corpus. This file was set up to include general article information (i.e., title, publication year, publication source), information about the city or cities studied in the article (i.e., number and name of city/cities), information on the applied research methodology, whether the article was considered on topic and whether the article included e-commerce data. When urban e-commerce logistics data were available, the file allowed to include information on mentioned data sources, number of respondents in case a survey method was used and the year of data collection. We used a categorisation of seven research methodologies, based on Lagorio et al. (2016): (1) case study, (2) conceptual study, (3) interview, (4) literature review, (5) quantitative modelling, (6) simulation and (7) survey. Only the methodology that was considered most important was mentioned in the file. Given the provision of city-specific data, many articles could be considered case studies, yet this category was only allocated when the article discussed application-specific or company-specific assessments, as well as pilot studies. Conceptual articles were added to label methodological approach propositions. The quantitative modelling category is mainly composed out of vehicle routing problems, location analysis and (external) cost modelling. The survey category includes traditional survey articles, as well as discrete choice models that are based on revealed and stated preferences.
How to categorize individuals on the basis of underlying attitudes? A discussion on latent variables, latent classes and hybrid choice models
Published in Transportmetrica A: Transport Science, 2021
Francisco J. Bahamonde-Birke, Juan de Dios Ortúzar
Since the introduction of latent class (LC) models (Kamakura and Russell 1989), classifying individuals into distinctive behavioural groups has become a standard procedure in discrete choice modelling work. LC models consider a discrete mixture distribution, allowing to associate every step of it with a distinctive behavioural class, establishing a probability that an individual belongs to each class. Initially, these models were developed to form groups with clear potentially-identifiable behavioural patterns and differently specified utility functions (e.g. individuals without all alternatives available or ignoring a given attribute in the decision). Now, in practice, LC models have been extended to represent preference heterogeneity by simply allowing different estimators in otherwise equally specified classes following a somewhat exploratory approach. Then, after careful observation of the estimated parameters, the different classes are associated with underlying unobservable characteristics of decision-makers, such as attitudes or perceptions (e.g. DeSarbo, Ramaswamy, and Cohen 1995; Bujosa, Riera, and Hicks 2010). However, this means that the latent classes identified by the model (as their identification improves the adjustment) may be associated with preconceived ideas in a rather ad-hoc fashion.
Role of perception of bicycle infrastructure on the choice of the bicycle as a train feeder mode
Published in International Journal of Sustainable Transportation, 2021
Lissy La Paix, Elisabetta Cherchi, Karst Geurs
The model structure used in this paper is a hybrid choice model (Ben-Akiva et al., 2002). Two parts form this model: (1) the mixed logit model, which is rooted in the microeconomic theory, and it is used to model the discrete choice. (2) The latent variable model that is rooted in the psychological theory, and it is used to account for the latent effect of attitudes and perceptions. Differently, from the majority of the hybrid choice models in the literature, we assumed that attitudes toward cycling do not directly influence the utility of cycling, but it affects the users’ perception of the cycling infrastructure, which in turn affects the utility of cycling. Let be Uqjtthe utility that individual q (q ∈ Q) associates to alternative mode j (j ∈ Cqj) in the choice task t (t ∈ T). As previously mentioned, the choice set Cqj in our model includes four modes to access the train station (MTB, walk, bicycle and car), plus an opt-out alternative that consists in not using the train. The utility specification Uqjt takes the following general form: