Analyzing Consumer Impulse Purchasing Behaviour Using Observational Data

2018 ◽  
Vol 3 (2) ◽  
pp. 16-28 ◽  
Author(s):  
Yuliia Kyrdoda ◽  
George Baltas ◽  
A.Malek Hammami
Keyword(s):  
Principal Component Analysis ◽  
Logistic Regression Model ◽  
Explanatory Power ◽  
Age Groups ◽  
Principal Component ◽  
Demographic Characteristics ◽  
Marketing Strategies ◽  
Purchasing Behavior ◽  
Purchasing Behaviour ◽  
Categorical Principal Component Analysis

This article identifies consumers' impulse purchasing behavior in supermarkets. The study includes an interpretation of the impulse decision relationship with the final purchase and an analysis of the distribution of impulse purchasers' demographic characteristics (age and shoppers' company). SPSS was used to analyze the observed data at a national retail supermarket chain. The logistic regression model was developed in order to identify the explanatory power of the variables. Categorical principal component analysis was employed to analyze the distribution of the variables. Empirical findings indicated that “impulsive decision” has a stronger intensity on “purchase” than “gender” does. Impulsive customers are split into three age groups and two company categories. These results could be used to design marketing strategies in order to increase sales. However, a few limitations occurred during the study such as: observation timing, unicity of location and observers' subjectivity.

Modelling and Analyzing Consumer Behaviour Employing Observational Data

2018 ◽  
Vol 3 (1) ◽  
pp. 42-57
Author(s):  
Yuliia Kyrdoda ◽  
A.Malek Hammami ◽  
Drakos Periklis ◽  
Panagiotis Kaldis
Keyword(s):  
Decision Making ◽  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Consumer Behaviour ◽  
Explanatory Power ◽  
Demographic Characteristics ◽  
Marketing Strategies ◽  
Purchase Behavior ◽  
Factors Affecting

The purpose of this article is to investigate and model retail consumer purchase behavior and determine factors affecting the purchasing decision. The following hypotheses were verified: H1 tests the influence of “Decision-making Time” over “Final Purchase”. H2 tests “Promotion” over “Final Purchase”. H3, H4 and H5 were established to test the influence of demographic characteristics (respectively: Age, Nationality, Gender) over “Final Purchase”. SPSS 23 was used to analyze the collected data from the observations completed in the supermarket. In order to identify the explanatory power of the variables, a Logistic Regression model was developed. Empirical findings indicated that demographic characteristics (Age, Nationality, Gender), as well as “Time” and “Promotion,” have a significant effect on “Purchase” and that “Time” has a greater impact on “Purchase.” These results could be used to design marketing strategies in order to increase sales. However, a few limitations occurred during the study such as observation timing, the unicity of location and observers' subjectivity.

scholarly journals Assessment of the Heterogeneity Influencing the Superior of Non-Banking Finance Company for Assisting Consumer Durable Loans

2021 ◽  
pp. 14-21
Keyword(s):  
Principal Component Analysis ◽  
Factor Analysis ◽  
Principal Component ◽  
Marketing Strategies ◽  
Purchasing Behavior ◽  
Essential Information ◽  
Finance Company ◽  
Consumer Durable ◽  
Major Factors ◽  
Financial Company

Customers purchasing behavior has changed radically in the course of the most recent couple of years. The study aimed to identify major factors determining consumer's choice rules of the non-banking financial company (NBFC) for availing consumer durable loans (CDLs). Essential information was gathered from 100 respondents by utilizing a survey including eight factors, recognized dependent on an audit of writing. Principal Component Analysis (PCA) was utilized as an extraction strategy by utilizing factor analysis. Three factors were isolated by using Eigenvalues standards and these three factors were assigned names such as service delivery, terms & conditions, and safety and security of fund respectively. It was suggested from the study that the non-banking financial companies aimed to expand their business should take cognizance of these factors in their marketing strategies.

scholarly journals COVID-19 Pandemic and Adaptive Shopping Patterns: An Insight from Indonesian Consumers

2021 ◽  
pp. 097215092110135
Author(s):  
Arif Hartono ◽  
Asma'i Ishak ◽  
Agus Abdurrahman ◽  
Budi Astuti ◽  
Endy Gunanto Marsasi ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Principal Component ◽  
Demographic Characteristics ◽  
Depth Information ◽  
Factor Scores ◽  
Consumer Spending ◽  
Consumer Responses ◽  
Buying Behaviour ◽  
Manova Analysis

Although existing studies on consumers typology are extensively conducted, insights on consumers typology in adapting their shopping attitude and behaviour during the COVID-19 pandemic remain unexplored. Current studies on consumer responses to the COVID-19 pandemic tend to focus on the following themes: panic buying behaviour, consumer spending and consumer consumption. This study explores a typology of adaptive shopping patterns in response to the COVID-19 pandemic. The study involved a survey of 465 Indonesian consumers. Principal component analysis is used to identify the variables related to adaptive shopping patterns. Cluster analysis of the factor scores obtained on the adaptive shopping attitude and behaviour revealed the typology of Indonesian shoppers’ adaptive patterns. Multivariate Analysis of Variance (MANOVA) analysis is used to profile the identified clusters based on attitude, behaviour and demographic characteristics. Results revealed five adaptive shopping patterns with substantial differences among them. This study provides in-depth information about the profile of Indonesian shoppers’ adaptive patterns that would help retailers in understanding consumers and choosing their target group. The major contribution of this study is providing segmentation on shopping adaptive patterns in the context of the COVID-19 pandemic which presents interesting differences compared with previous studies. This study reveals new insights on shoppers’ adaptive attitude and behaviour as consumers coped with the pandemic.

scholarly journals Principal Component Analysis of Morphometric Traits of West African Dwarf Goats

2019 ◽  
Vol 1 ◽  
pp. 26-32 ◽  
Author(s):  
I O Dudusola ◽  
S O Oseni ◽  
M A Popoola ◽  
A Jenyo
Keyword(s):  
Principal Component Analysis ◽  
Body Weight ◽  
Total Variation ◽  
Age Groups ◽  
Principal Component ◽  
Component Analysis ◽  
West African ◽  
Age Group ◽  
Morphometric Traits ◽  
West African Dwarf

The study was conducted to evaluate the principal component analysis of phenotypic attributes of West African Dwarf (WAD) goat. Data collected on the live body weight and twelve morphometric traits of the goats which were categorised into four age groups based on their dentition. The age groups were: less than 2years old, 2- 3years old, 3-4 years old and 4 years old. The data were subjected to a PCA and Cluster analyses using the multivariate procedure components of SAS (2003). Result revealed that highest values of morphometric traits were obtained in goats that of 4 years old. The rate of increase in body weight and other morphometric traits was high in age group of ˂2 years to age 2-3years compared to differences observed in others across the age group. Heart Girth had the highest correlation with body weight. Foreleg, neck, ear and hind leg lengths; wither height and rump height were weakly correlated with the body weight of the goats. Result revealed that two Principal components were retained in the first age group (age group˂2years) which accounted for 72.99% of the total variation. The first PC alone accounted for 63.13% of the total variation while PC2 accounted for the remaining 9.86%. From this study, it was concluded that there is interdependence among body weight and morphometric traits and that morphometric traits can be used in predicting live weight of WAD goats; PCA and Cluster could be exploited in breeding and selection programmes to acquire highly coordinated animal bodies using fewer measurements.

Clustering and Profiling Consumer Buying Behavior

2021 ◽  
Vol 11 (1) ◽  
pp. 50-66
Author(s):  
Lambros Nikolaos Tsourgiannis ◽  
Stavros Ioannis Valsamidis
Keyword(s):  
Cluster Analysis ◽  
Principal Component ◽  
Nonparametric Tests ◽  
Demographic Characteristics ◽  
Behavior Patterns ◽  
Purchasing Behavior ◽  
Buying Behavior ◽  
Product Features ◽  
Main Factors ◽  
Shopping Basket

This paper aims to identify the factors that affect consumers' buying behavior towards goods of consumers' shopping basket to classify them into groups according to their similar buying behavior patterns and to profile each group of consumers. A primary survey conducted to 242 consumers in Greece. Principal component analysis (PCA) conducted to identify the main factors that affect consumers purchasing behavior. Cluster analysis performed to classify consumers into groups with similar purchasing behavior whilst discriminant analysis conducted to check cluster predictability. Nonparametric tests are performed to profile each group of consumers according to their demographic characteristics and other factors. PCA identified six main factors: (1) price, (2) entertainment during shopping, (3) advertisement, (4) public relationships, (5) product features, (6) promotion activities. Cluster analysis classified consumers into three groups: (1) advertisement-orientated consumers, (2) promotion-orientated consumers, and (3) entertainment-orientated consumers.

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