An Empirical Study to Understand the Consumer Buying Behaviour in Ethnicwear Market in India through the Application of Factor and Cluster Analysis

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Sougata Banerjee ◽  
Sankar Sarkar
Keyword(s):  
Cluster Analysis ◽  
Factor Analysis ◽  
Exploratory Factor Analysis ◽  
Reference Group ◽  
Factor Loading ◽  
Cluster Method ◽  
Store Attributes ◽  
Group 5 ◽  
And Cluster Analysis ◽  
Buying Behaviour

In the study the researchers tried to cover up the present scenario of ethnic wear market in India and the consumer behaviorism. Thirty-one variables were selected from the study of (Gurunathan & Krishnakumar, 2013). 10 variables were taken on consumer characteristics, 3 variables on promotional techniques of the brand, 5 on influence of reference group, 5 on product attributes and 8 on store attributes were chosen from the study and Five point Likert Scale for opinion and responses. Exploratory factor analysis was run to understand the consumer buying styles in ethnic wear market and to identify the important indicators behind the purchase decision. Ten components or ten distinct types of customers were extracted through Varimax method and rotated component matrix namely Rational Purchasers, Influenced Shoppers, Quality Gift Purchasers, Promotion Driven Customers, Unplanned Purchasers, Passionate Consumers, Planned Purchasers, Customers looking for Card Facilities, Customers having Brand Knowledge and Brand Aware Customers. Four indicators on the basis of highest factor loading extracted from exploratory factor analysis were chosen for cluster analysis namely parking facilities, brand consciousness, preferences of parents and advertisement. Cluster analysis was done first by hierarchical method to deduce number of clusters which can be formed, and then the data was further processed through Ward Method in K-Means Cluster Method. Four distinct and differentiating segment namely emotional, rational, value driven and traditional modern were concluded with discrete characteristics.

Symptom clusters in newly-diagnosed brain tumor patients

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 8587-8587
Author(s):  
J. Gleason ◽  
D. Case ◽  
S. Rapp ◽  
E. Ip ◽  
M. Naughton ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Factor Analysis ◽  
Brain Tumor ◽  
Exploratory Factor Analysis ◽  
Expressive Language ◽  
Symptom Clusters ◽  
Phase Iii ◽  
Newly Diagnosed ◽  
Tumor Patients ◽  
And Cluster Analysis

8587 Background: A symptom cluster is 2 or more co-occurring symptoms. Patients with brain tumors experience disease and treatment-related symptoms that impact their health-related quality of life (QOL). Identifying symptom clusters will facilitate treatment and improve QOL outcomes. Methods: 66 patients were enrolled in a phase III, placebo-controlled, double-blind, prospective randomized clinical trial assessing the effect of prophylactic d-methylphenidate (d-MPH) on QOL in newly diagnosed brain tumor patients receiving brain radiation therapy (RT). Inclusion criteria were: age ≥ 13 years, primary or metastatic brain tumor, partial or whole brain RT with a total dose of ≥ 2,500 cGy in ≥ 10 fractions, KPS ≥ 70, and life expectancy ≥ 3 months. Patients received d-MPH 5–15 mg BID (or placebo) starting week 1 of RT and continuing for 8 weeks post-RT. QOL data were collected at baseline, the end of RT, and 4, 8, and 12 weeks following RT using the Functional Assessment of Cancer Therapy-Brain (FACT-Br) and the Center for Epidemiologic Studies Depression Scale (CES-D). Symptom data were analyzed using exploratory factor analysis, multi-dimensional scaling (MDS), and cluster analysis. Results: The study failed to show a treatment effect for d-MPH (Butler J et al, Int J Radiat Oncol Biol Physics 63 [Supp1]:80, 2005).Thus, both d-MPH and placebo patients were analyzed together. 58 and 48 patients were analyzed at baseline and the end of RT, respectively. Two symptom clusters were identified using exploratory factor analysis and supported by MDS and cluster analysis: an expressive language cluster including difficulty reading, writing, and finding the right words, and a mood cluster including feeling sad, anxious, and having depressed mood. Conclusions: Two symptom clusters were identified in patients undergoing brain RT: an expressive language cluster and a mood cluster. This suggests that interventions that target both cognitive function and mood should be utilized. Further research on symptom clusters in cancer patients is needed. This study was supported by NCI grant 1 U10 CA81851. No significant financial relationships to disclose.

On the Dimensionality of Measuring Tourist Satisfaction towards Homestay

2015 ◽  
Vol 8 (2) ◽  
Author(s):  
Gangaram Biswakarma
Keyword(s):  
Factor Analysis ◽  
Data Collection ◽  
Exploratory Factor Analysis ◽  
Life Style ◽  
Factor Loading ◽  
Primary Data ◽  
Cultural Performance ◽  
Latent Construct ◽  
Tourist Satisfaction ◽  
The Relationship

This study focuses on measuring tourist satisfaction towards home stay. This paper emphasized to identify the variables that are related to tourist satisfaction during tourist homestay. It is also focused on analyzing the relationship and impact of these latent construct of factors to overall tourist satisfaction towards home stay. In an attempt to visualize the purpose, tourists satisfaction in a homestay in Nepal has taken into as a case, with an aim to identify the underlying dimensions of tourist satisfaction during tourist homestay. Twenty six (26) manifest variables of homestay has been formulated to understand the dimensions. Likewise, for a conforming the latent construct (1) statement as dependent variable of overall satisfaction was developed for the purpose of the primary data collection. The manifest variables are basically focused on aspects of home stay attributes namely cultural attraction, hospitality, amenities and safety & security at the home stay destination. Post Exploratory Factor Analysis indicates factor loading for twenty two (22) items manifest variables as significant, loaded with five (5) factors of home stay attributes named as Amenities & Safety, Reception, Local Cuisine & Accommodation, Local Life style & Costumes, and Cultural Performance. This study contributes to the development of survey instrument for exploring tourist satisfaction for Home stay for future researchers.

scholarly journals Typology and characterization of the pampean beekeeping systems

2020 ◽  
Vol 51 (2) ◽  
pp. 299-318
Author(s):  
Tomás Bragulat ◽  
Elena Angón ◽  
Alberto Giorgis ◽  
José Perea
Keyword(s):  
Cluster Analysis ◽  
Factor Analysis ◽  
Rural Areas ◽  
Export Market ◽  
Multivariate Techniques ◽  
High Productivity ◽  
Selection Of Variables ◽  
Socially Relevant ◽  
And Cluster Analysis ◽  
Random Survey

Objective: Identify and characterize the beekeeping systems of La Pampa (Argentina) using multivariate techniques based on the main structural, productive and economic characteristics. Methodology: The data was collected through a random survey of 80 beekeepers. The classification and description of the apicultural systems was based on a multivariate sequence comprising three stages: review and selection of variables, factor analysis and cluster analysis. Results: Factor analysis revealed that the size of the farm and the productive and economic performance of beekeeping jointly explained 66% of the variability. Through cluster analysis, three types of beekeeping have been identified: (i) Subsistence beekeeping grouped 55% of the farms, mainly characterized by small sizes and low productive and economic yields. (ii) Industrial beekeeping concentrated 54% of production in 15% of farms, mainly characterized by large sizes and high productive and economic yields. (iii) Commercial beekeeping grouped 30% of the farms, mainly characterized by high productivity with intermediate sizes. Limitations: The study has been carried out on a few farms due to the difficulty of obtaining answers to all the variables included in the survey. Practical implications: Beekeeping in La Pampa is generally a highly heterogeneous complement of income or family subsistence, with low productivity and low input use. Subsistence beekeeping is a socially relevant system for its contribution to family employment and income in rural areas. Industrial beekeeping is oriented to the export market and has a more competitive scale. Commercial beekeeping is situated on an intermediate scale.

scholarly journals Behavioral patterns of consumers participating in food safety and social co-governance: consumption choices and environmental improvement

2019 ◽  
Vol 131 ◽  
pp. 01086
Author(s):  
Menghui Qiu ◽  
Zhijing Zhao
Keyword(s):  
Cluster Analysis ◽  
Factor Analysis ◽  
Food Safety ◽  
Behavioral Patterns ◽  
Chinese Consumers ◽  
Consumption Choices ◽  
The Social ◽  
The Government ◽  
And Cluster Analysis ◽  
Behavior Models

Consumers are the most direct stakeholders of food safety, and their effective participation is the key to the social Co-governance of food safety. Based on the specific behaviors of Chinese consumers participating directly and indirectly in the social Co-governance of food safety, using the data of 350 consumers’ behavior survey and factor analysis and cluster analysis, this paper extracts two kinds of behavior models of Chinese consumers participating in the social Co-governance of food safety, namely, consumption choices model and environment improvement model. It is found that Chinese consumers are inclined to adopt the “environment improvement” model at this stage, which is the inevitable result of the current food safety pressure in China. The government should formulate corresponding policies to better guide consumers to participate in the social Co-governance of food safety.

Typology of online shoppers

2003 ◽  
Vol 20 (2) ◽  
pp. 139-156 ◽  
Author(s):  
Ah Keng Kau ◽  
Yingchan E. Tang ◽  
Sanjoy Ghose
Keyword(s):  
Cluster Analysis ◽  
Factor Analysis ◽  
Information Seeking ◽  
Online Shopping ◽  
Demographic Information ◽  
Buying Behavior ◽  
Internet Users ◽  
Online Shoppers ◽  
And Cluster Analysis ◽  
Online Buying

This article aims to examine the online buying behavior among a group of Internet users. Based on a sample of over 3,700 Internet users, this study explores their information‐seeking patterns as well as their motivations and concerns for online shopping. Factor analysis and cluster analysis were used to classify the respondents into six types of online shoppers. Coupled with their demographic information and actual buying behavior, it was possible to constitute a distinct profile for each of the segments. Discriminant analysis was also conducted to seek out the important attitudinal variables that differentiated the various clusters of online shoppers. The implications of such classification are also discussed.

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