Multiple Correspondence and Hierarchical Cluster Analyses for the Profiling of Fresh Apple Customers Using Data from Two Marketplaces

Bejaei, Masoumeh; Cliff, Margaret A.; Singh, Amritpal S.

doi:10.3390/foods9070873

Cited by 17 publications

(9 citation statements)

References 14 publications

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“…PCA can compress the original information through dimensionality reduction data and present the screening of effective indicators. They had been effectively applied in comprehensive quality evaluation and variety pedigree division (Bejaei et al, 2020;Huang et al, 2019). In our study, cluster analysis classified fruit texture traits according to an accurate algorithm, and 23 plum cultivars were divided into three distinct categories.…”

Section: Discussionmentioning

confidence: 99%

Fruit Textural Characteristics of 23 Plum (Prunus salicina Lindl) Cultivars: Evaluation and Cluster Analysis

Qiu¹,

Zhang²,

Zhang³

et al. 2021

horts

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Fruit textural characteristics can affect the storage, transportation, and processing of plum (Prunus salicina Lindl) in commercial production. We analyzed 23 plum cultivars with marked differences in fruit traits. Basic physicochemical indicators and textural characteristics of the fruits were determined using puncture testing and texture profile analysis. Furthermore, through the combined application of cluster analysis and principal component analysis, the indexes were simplified to three relatively independent dimensions, comprehensively reflecting the hardness, size, and flexibility of plum fruit. Our results show a high positive correlation among textural characteristics such as hardness, springiness, gumminess, and chewiness, whereas toughness and brittleness were negatively correlated. In addition, physicochemical properties were correlated to the texture traits. The weight and size of the plum fruit were related to hardness, adhesiveness, and chewiness. The soluble solids and water content contributed to the hardness, cohesiveness, and resistance to chewing. Cluster analysis revealed three distinct clusters: Cluster I represented by ‘Meiguihong’ with high hardness and a chewable texture; Cluster II represented by ‘Siyuecui’, ‘Cuimi’, and ‘Qingcui’ with a hard and brittle texture; and Cluster III represented by ‘Jinmi’, ‘Taoli’, and ‘Oishiwase’ with a soft and tough texture. The results of this study provide a significant theoretical foundation for quality evaluation, and classification of plum fruit characteristics, thus providing insights for further breeding of plum varieties.

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Section: Discussionmentioning

confidence: 99%

Fruit Textural Characteristics of 23 Plum (Prunus salicina Lindl) Cultivars: Evaluation and Cluster Analysis

Qiu¹,

Zhang²,

Zhang³

et al. 2021

horts

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“…Similarly, Wen and Chen (2010) explored the competitive positions of international air travellers, Brida et al (2014) studied sociodemographic and travel-related characteristics of cruises, whilst Diana and Pronello (2010) defined a set of different customer profiles regarding travellers' social status and characteristics and efficiency of transportation networks. Bejaei, Cliff, and Singh (2020) and Nicolosi, Fava, and Marcianò (2018) examined purchasing habits and preferences for fruit and fishery, respectively.…”

Section: Literature Reviewmentioning

confidence: 99%

Framing coworking spaces marketing strategies via social media indices

Vagianos¹,

Κουτσουπιάς²

2021

Econometrics

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In this paper an investigation of social media marketing techniques of Coworking spaces' type of business is performed, using datasets acquired using social media monitoring tools. Mediatoolkit has been used to scrap data deriving from the activity of the WeWork Instagram and Twitter accounts which were collected on a 24/7 basis from varying locations and in multiple languages in a fifteen-day time window. Indices related to sentiment, reach, influence, number of followers, retweets, likes, comments, and view scores formed the datasets that were examined by applying multiple correspondence analysis as well as the hierarchical clustering method. The aim of this paper was to explore the inherent properties of the multiple indices describing the general realm of social media marketing tools, and more specifically aspires to provide digital marketers with an alternative perspective of social media marketing strategies related to the emerging coworking spaces type of business. The authors identified three classes/segments of posts, whereas post polarity tends to relate to geographic location, regardless of the social media channel used for posting.

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“…The variables with p-values higher than 0.05 were discarded. A minimum number of latent variables (or components) with linear combinations of the original variables that are independent from each other were defined (24). The number of dimensions in the analysis was selected according to the percentage of inertia.…”

Section: Multivariate Analysismentioning

confidence: 99%

“…The number of dimensions in the analysis was selected according to the percentage of inertia. MCA was also used in pre-processing to transform categorical variables into continuous ones in order to perform a cluster analysis by ascending hierarchical classification (Ward's method and Euclidean similarity distance between observations) (24,25). Homogeneous subject profiles based on the MCA dimensions assuming that they have substantive coherence (24,26) were defined.…”

Section: Multivariate Analysismentioning

confidence: 99%

Knowledge, Attitudes, and Risk Perception Toward Avian Influenza Virus Exposure Among Cuban Hunters

Delgado-Hernández

Mugica

Acosta

et al. 2021

Front. Public Health

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A critical step for decreasing zoonotic disease threats is to have a good understanding of the associated risks. Hunters frequently handle potentially infected birds, so they are more at risk of being exposed to zoonotic avian pathogens, including avian influenza viruses (AIVs). The objective of the current study was to gain a better understanding of Cuban hunters' general hunting practices, focusing on their knowledge and risk perception on avian influenza. An anonymous and voluntary semi-structured questionnaire was designed and applied to 398 hunters. Multiple correspondence analyses found relationships with potential exposure of AIVs to people and domestic animals. The main associated risks factors identified were not taking the annual flu vaccine (60.1%) and not cleaning hunting knives (26.3%); Direct contact with water (32.1%), cleaning wild birds at home (33.2%); receiving assistance during bird cleaning (41.9%), keeping poultry at home (56.5%) and feeding domestic animals with wild bird leftovers (30.3%) were also identified as significant risk factors. The lack of use of some protective measures reported by hunters had no relationship with their awareness on avian influenza, which may imply a lack of such knowledge. The results evidenced that more effective risk communication strategies about the consequences of AIVs infecting human or other animals, and the importance of reducing such risks, are urgently needed.

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Multiple Correspondence and Hierarchical Cluster Analyses for the Profiling of Fresh Apple Customers Using Data from Two Marketplaces

Cited by 17 publications

References 14 publications

Fruit Textural Characteristics of 23 Plum (Prunus salicina Lindl) Cultivars: Evaluation and Cluster Analysis

Fruit Textural Characteristics of 23 Plum (Prunus salicina Lindl) Cultivars: Evaluation and Cluster Analysis

Framing coworking spaces marketing strategies via social media indices

Knowledge, Attitudes, and Risk Perception Toward Avian Influenza Virus Exposure Among Cuban Hunters

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