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The purpose of this paper is to detect market segments where consumers have a different knowledge of domestic and imported Parmesan cheese in USA and Canada. The results may be helpful in understanding to what extend North America consumers appreciate Parmesan cheese and brands, Parmesan consumption and price while recognizing market segments according to consumer awareness, involvement and covariate effects.

A class of mixture models, known as combination uniform binomial (CUB), is applied to survey data collected in USA and Canada. A questionnaire, filled out by 540 restaurant customers, collects opinions about consumption, purchase features and price. The CUB model estimates the two latent variables, known as feeling and uncertainty, explaining the respondent’s behavior as awareness and involvement variability while the CUB clustering procedure detects market segments.

CUB results show that the Parmesan is a well-known cheese but also that a small share of consumers look for the place of origin. The model detects market segments where consumers express better awareness on taste, price and origin while the knowledge of imported Parmesan brands is lacking. Most of consumers, not paying attention to the origin, would hardly switch to the imported Parmesan because of higher price or because they are already satisfied of the domestic cheese.

The results suffer some restrictions in the sample representativeness. A further analysis, where the survey is done at retail and advances in CUB models, may improve the market segmentation procedure allowing a better generalization of results.

The survey results highlights the appreciation and consumption of Parmesan cheese, especially for its taste, as well as a low perception of Italian brands. Consequently, trade companies should focussed their communication strategy on activities encouraging North American consumers to taste Italian Parmesan brands (e.g. tasting sessions, price promotions) instead of costly and less effective advertising campaigns.

Parmesan brand misunderstandings are often associated with market information asymmetry. The paper results show a market segmentation where purchases are mainly driven by Parmesan taste regardless of domestic or imported brands. Likely, the consumption of domestic Parmesan is well consolidated and it is not a consequence of brand information asymmetry.

The CUB model is an innovative and flexible no parametric approach for evaluating consumer behavior and for segmenting the market while dealing with complex problems of food knowledge.

Packaging features have been shown to be of great importance for the consumer final choice of fresh products (Silayoi and Speece, 2007). Packaging is an extrinsic attribute, which consumers tend to rely on, when relevant intrinsic attributes of the product are not available. In the current literature, studies on the influences of packaging features on consumer preferences are mainly related to classical preference evaluation methods like conjoint analysis (CA). The purpose of this paper is to apply both CA and the less known combination of uniform discrete and shifted binomial distributions (CUB) models to food packaging evaluations.

Starting from a real case study in this field, along with CA, the author apply CUB models (Iannario and Piccolo, 2010) as a useful tool to evaluate preferences. CUB models can grasp some psychological characteristics of consumers related to the “feeling” toward packaging attributes and related to an inherently “uncertainty” that affects the consumers’ choices. Both psychological characteristics “feeling” and “uncertainty” can be linked to relevant subject’s information. At first we detect preferred packaging attributes of fresh food by means of CA, then we apply CUB models to some relevant attributes from the CA study.

Results show that attributes like packaging material and size/shape of packaging are the most important attributes and that biodegradable packaging, reclosable trays/bags and long “best by” date are also valuable features for consumers. The introduction of covariates showed that specific demographic characteristics are linked to both feeling and uncertainty.

The “data driven” segmentation results give to the integrated approach “CUB models and Conjoint Analysis” the most important added value.

A different framework based on a parametric version of the process generating the hedonic scores is adopted. More precisely, a probability distribution for ordinal responses is proposed as a mixture of two components, denoted as feeling (as expressed preference) and uncertainty component (as inherent indecision). The purpose of this paper is to analyse the effect of covariates on the consumers’ behaviour pattern according to a statistical model.

Sample data come from a multidisciplinary research aimed to improve the quality and marketability of soft fruits. Then, a stochastic model with subjects’ and objects’ covariates is built and the interpretation of significant results is discussed.

The joint effects of personal characteristics and chemical contents of juice on the hedonic scores given by consumers are examined and graphically depicted by means of a significant model.

The paper suggests a multi-product approach to expressed hedonic scores by means of a generalization of CUB models.

The study jointly investigates sustainability and authenticity concepts in the food context during the COVID-19 outbreak with a fourfold objective: (1) understanding whether sustainability and authenticity are equivalent concepts in consumers' perceptions; (2) advancing knowledge on the role played by them about food frauds' perception; (3) investigating whether these concepts are considered as “risk relievers” by consumers, (4) comparing the concepts to understand which one has a greater weight on the consumer's perception.

The study adopts a Combination of a Uniform and a shifted Binomial distribution (CUB models) on data gathered in Spain between June and August 2020 through an online questionnaire.

The findings reveal that: (1) consumers perceive sustainability and authenticity as different concepts in the food context and (2) as two important indicators of fraud protection of a product for consumers; (3) besides, authenticity is seen as a “risk reliever” in buying a food product, as well as sustainability, (4) although results underline high uncertainty in the latter case.

By considering that the COVID-19 outbreak seriously threatens food safety, security and nutrition, this research elucidates the relevant role of food sustainability and authenticity concepts as “risk relievers” in terms of food frauds and negative issues related to COVID-19.

The aim of the study was to develop a practical construction time model for public building projects in Addis Ababa, Ethiopia.

This research work used regression analysis and also exploratory scatter and residual plot techniques. Simple and multiple regressions were used for the investigation of the best fit time model. The analyses were carried out using IBM SPSS statistical software, version 20.

The result revealed that the Bromilow time-cost principle was moderately applicable. However, the cubic regression model (CUB) was found a better time-cost relationship. On the contrary, the study has shown a poor relationship between actual time and gross floor area. Furthermore, multiple linear regression analysis (MLR) consists of three statistically significant variables were found a better fit time model.

The study is limited to only six project scope factors. Further research is recommended to include more building projects of similar type and implications of other factors to improve the reliability of the models.

The developed model was not intended as a replacement for detailed construction scheduling techniques. The resulting model is applicable for front-end predictions of construction duration.

The main parties involved in the building projects should apply the model for benchmarking a precise construction time during the early planning phase.

The purpose of this paper is to identify and assess the factors that consumers evaluate significant in the assessment of food authenticity and guide them to make safe food choices.

In this respect, a mixture model for consumer preferences, namely CUB, was employed due to the ability of discriminate features that are rated similarly allowing the detection of significant similarities and differences in consumers’ judgments. Moreover, introducing covariates in CUB models allow studying the influence that consumers’ socio-demographic characteristics have on the importance of the attributes used in the assessment of food authenticity.

The results demonstrate that organic certificate, traditional and homemade production practices, origin certificate as well as information about product’s origin country and raw materials production region are significant quality cues enable consumers to judge food authenticity. In addition, consumers further segmentation according to socio-demographic characteristics indicate that country of origin information are mainly used by middle-aged consumers, highly educated and paid, whereas production techniques and organic certification constitute the most effective indicators for judging food authenticity by older consumers.

The paper confirms that consumers can use extrinsic and intrinsic quality cues to judge food’s authenticity.

Time is an important factor in any project, especially in construction projects. Although using detailed scheduling techniques is unavoidable, a model to predict or benchmark time performance has interested many researchers. For an exploratory purpose, this paper aims to investigate the time‐cost relationship proposed by Bromilow with data from construction projects in Korea.

The data are collected from 34 historical building projects in Korea. Construction cost is adjusted using a building price index. Analysis is carried out on variety of project characteristics.

It is shown that a time‐cost relationship is applicable to the Korean construction industry. Further analysis indicates that the original Bromilow time‐cost model is not the best fit regression form, and alternative models are proposed.

The data are limited to a small sample of 34 building projects. This limitation arises because of the data collection approach, which is direct contact with historical project documents supplied by construction firms.

Models from this study can serve as a reference tool for practitioners in the early stages of building projects in Korea. The results from this study are not intended to reject or replace detailed construction scheduling techniques.

Although the Net Promoter Score (NPS) index is simple, NPS has weaknesses that make NPS's interpretation misleading. The main criticism is that identical index values can correspond to different levels of customer loyalty. This makes difficult to determine whether the company is improving/deteriorating in two different years. The authors describe the application of statistical tools to establish whether identical values may/may not be considered similar under statistical hypotheses.

Equal NPSs with a “similar” component composition should have a two-way table satisfying marginal homogeneity hypothesis. The authors compare the marginals using a cumulative marginal logit model that assumes a proportional odds structure: the model has the same effect for each logit. Marginal homogeneity corresponds to null effect. If the marginal homogeneity hypothesis is rejected, the cumulative odds ratio becomes a tool for measuring the proportionality between the odds.

The authors propose an algorithm that helps managers in their decision-making process. The authors' methodology provides a statistical tool to recognize customer base compositions. The authors suggest a statistical test of the marginal distribution homogeneity of the table representing the index compositions at two times. Through the calculation of cumulative odds ratios, the authors discriminate against the hypothesis of equality of the NPS.

The authors' contribution provides a statistical alternative that can be easily implemented by business operators to fill the known shortcomings of the index in the customer satisfaction's context. This paper confirms that although a single number summarizes and communicates a complex situation very quickly, the number is ambiguous and unreliable if not accompanied by other tools.

This study aims to establish a bio-inspired controller for realizing the bounding gait of a quadruped robot system presented in this paper.

The bio-inspired controller is divided into three levels to mimic the biological patterns of animals. First, the high-level sub-controller is equivalent to the cerebellum, which could plan and control the motion of animals. Second, the effect of the middle-level sub-controller corresponds to the central nervous system. The central pattern generators in the spine generate the stable and cyclic signals as the fundamental rhythm for periodic motion of the leg and spine joints. Third, the low-level sub-controller is equal to the end effector, which adopts the simple proportional-derivative (PD) control to realize the specific motion trajectory of the legs and spine.

Combined with the stability criterion presented previously and the delayed feedback control method, the bounding gait of the cheetah virtual prototype could be actuated and stabilized by the bio-inspired controller. Moreover, the bio-inspired controller is applied to realize the bounding gait of an SQBot, which is a quadruped robot with a spine joint. Meanwhile, the validity and practicability of the bio-inspired controller for the control of quadruped robot have been verified against different forward velocities.

The bio-inspired controller and bionic quadruped robot system are instructive for the designing and actuating of the real quadruped robot.

Carboy filters The tilter seen in Fig. 1 has been specially designed for dispensing from the new type of polythene carboys now widely used in place of glass carboys. Models are available to suit 10‐ and 12‐gal containers, and both are finished with two coats of anti‐corrosive paint.