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Examination of Factors Affecting
Repurchase Intention of Fitness Equipment
By: Chris and Andrew
Background
• What:
• Fitness Equipment
• So What:
• Fitness (Sports) Equipment is expected to grow 6.18% per year over the next 5 years.
• Covid has changed how people exercise and has increased the use of home gyms (Martin,
Champ, and Franklin 2021).
• What’s New:
• Breakdown of detailed demographics affects on repurchase intention
Research Objective
• Exploratory examination of Factors affecting repurpose intention
of fitness equipment
Research Aims
• What factors will affect a consumers repurchase intention of fitness
equipment?
• What demographic variables influence fitness equipment purchase intention?
Variable Explanation
• Consumer Trust is the propensity to believe “the word, promise, verbal or
written statement of another individual or group can be relied upon” (Rotter
1967, p. 653)
Variable Explanation
• Gender is the behavioral, cultural, or psychological traits typically associated
with one sex (Merriam-Webster).
Variable Explanation
• Educational levels are defined by the developmental differences of students and
how the learning environments are structured.
• https://safesupportivelearning.ed.gov/training-technical-
assistance/education-level
Variable Explanation
• Income is a gain or recurrent benefit usually measured in money that derives
from capital or labor (Merriam-Webster).
Variable Explanation
• Customer satisfaction arises when consumers compare their perceptions of
the performance of a product or service to both their desires and
expectations. This comparison process produces not only feelings of
satisfaction with the product or service, but also feelings of satisfaction with
the information on which their expectations are based.
• Spreng RA, MacKenzie SB, Olshavsky RW. A reexamination of the
determinants of consumer satisfaction. Journal of Marketing. 1996;60(3):15.
doi:10.1177/002224299606000302
Variable Explanation
• Service Quality involves three main dimensions (interaction, environment,
and outcome) and each has subdimensions. Furthermore, customers
aggregate their evaluations of the subdimensions to form their perceptions
of an organization's performance on each of the three primary dimensions.
Those perceptions then lead to an overall service quality perception.
• Brady MK. Some New Thoughts on Conceptualizing Perceived
Service Quality: A Hierarchical Approach. Journal of Marketing.
2001;65(3):34-49. doi:10.1509/jmkg.65.3.34.18334
Variable Explanation
• Repurchase Intention - Determination to act in a certain way, in this case to purchase
products again from the same company (Collins 1980).
Topic: Examination of
Factors affecting
repurchase intention
of fitness equipment
Repurchase
Intention
[DV]
Consumer
Trust
[IV]
Gender
[IV]
Education
[IV]
Income
[IV]
Consumer
Satisfaction
[IV]
Service
Quality
[IV]
Variable classification Variable name Purpose
A. Continuous variables
(numerical)
1.Repurchase intention One sample t-test, Two-sample t-test,
ANOVA, Regression
2. Service Quality Regression
3. Consumer Trust
4. Consumer Satisfaction
B. Discrete variables
(categorical)
5. Gender Two-sample t-test, ANOVA, Regression
Male
Female
6. Education ANOVA, Regression
a) No education
b) High School
c) Bachelors
d) Masters
e) Ph.D.
7. Income ANOVA, Regression
a) Poor
b) Lower income
c) Middle income
d) Upper middle income
e) Upper
Descriptive Statistics
N Minimum Maximum Mean
Std.
Deviation
Gender 368 1 2 1.58 0.494
Education 368 1 5 4.04 0.839
Income 368 1.0 5.0 2.465 1.4080
Service quality 368 2.00 7.00 5.5103 0.90406
Customer
satisfaction
368 1.75 7.00 4.8811 1.01904
Trust 368 1.00 7.00 4.6848 1.38314
Repurchase
Intention
368 1.50 7.00 4.8098 1.10323
Selection Criteria and Data Manipulation
• Sample Selection Criteria:
• Unknown as we are using open-sourced pre-collected data. Believed to be convenience
sampling.
• Data Manipulation
• Being samples have complete data sets, no manipulation such as list wise deletion will
occur.
• Data Transformation:
• We will use Log and Ln Transformation methods to achieve normal distribution.
Modeling approach
• Regression model: A predictive model designed to analyze
the relationship between independent and dependent
variables. We will use mostly linear modeling. This model
helps determine the relationship between variables,
forecasting, and modeling.
58%
42%
Univariate Analysis
(Categorical variables)
40%
12%
17%
23%
8%
(Continuous variables)
Bivariate Analysis
Stats 2.1.pptx
Stats 2.1.pptx
Stats 2.1.pptx
Stats 2.1.pptx
Stats 2.1.pptx

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Stats 2.1.pptx

  • 1. Examination of Factors Affecting Repurchase Intention of Fitness Equipment By: Chris and Andrew
  • 2. Background • What: • Fitness Equipment • So What: • Fitness (Sports) Equipment is expected to grow 6.18% per year over the next 5 years. • Covid has changed how people exercise and has increased the use of home gyms (Martin, Champ, and Franklin 2021). • What’s New: • Breakdown of detailed demographics affects on repurchase intention
  • 3. Research Objective • Exploratory examination of Factors affecting repurpose intention of fitness equipment
  • 4. Research Aims • What factors will affect a consumers repurchase intention of fitness equipment? • What demographic variables influence fitness equipment purchase intention?
  • 5. Variable Explanation • Consumer Trust is the propensity to believe “the word, promise, verbal or written statement of another individual or group can be relied upon” (Rotter 1967, p. 653)
  • 6. Variable Explanation • Gender is the behavioral, cultural, or psychological traits typically associated with one sex (Merriam-Webster).
  • 7. Variable Explanation • Educational levels are defined by the developmental differences of students and how the learning environments are structured. • https://safesupportivelearning.ed.gov/training-technical- assistance/education-level
  • 8. Variable Explanation • Income is a gain or recurrent benefit usually measured in money that derives from capital or labor (Merriam-Webster).
  • 9. Variable Explanation • Customer satisfaction arises when consumers compare their perceptions of the performance of a product or service to both their desires and expectations. This comparison process produces not only feelings of satisfaction with the product or service, but also feelings of satisfaction with the information on which their expectations are based. • Spreng RA, MacKenzie SB, Olshavsky RW. A reexamination of the determinants of consumer satisfaction. Journal of Marketing. 1996;60(3):15. doi:10.1177/002224299606000302
  • 10. Variable Explanation • Service Quality involves three main dimensions (interaction, environment, and outcome) and each has subdimensions. Furthermore, customers aggregate their evaluations of the subdimensions to form their perceptions of an organization's performance on each of the three primary dimensions. Those perceptions then lead to an overall service quality perception. • Brady MK. Some New Thoughts on Conceptualizing Perceived Service Quality: A Hierarchical Approach. Journal of Marketing. 2001;65(3):34-49. doi:10.1509/jmkg.65.3.34.18334
  • 11. Variable Explanation • Repurchase Intention - Determination to act in a certain way, in this case to purchase products again from the same company (Collins 1980).
  • 12. Topic: Examination of Factors affecting repurchase intention of fitness equipment Repurchase Intention [DV] Consumer Trust [IV] Gender [IV] Education [IV] Income [IV] Consumer Satisfaction [IV] Service Quality [IV]
  • 13. Variable classification Variable name Purpose A. Continuous variables (numerical) 1.Repurchase intention One sample t-test, Two-sample t-test, ANOVA, Regression 2. Service Quality Regression 3. Consumer Trust 4. Consumer Satisfaction
  • 14. B. Discrete variables (categorical) 5. Gender Two-sample t-test, ANOVA, Regression Male Female 6. Education ANOVA, Regression a) No education b) High School c) Bachelors d) Masters e) Ph.D. 7. Income ANOVA, Regression a) Poor b) Lower income c) Middle income d) Upper middle income e) Upper
  • 15. Descriptive Statistics N Minimum Maximum Mean Std. Deviation Gender 368 1 2 1.58 0.494 Education 368 1 5 4.04 0.839 Income 368 1.0 5.0 2.465 1.4080 Service quality 368 2.00 7.00 5.5103 0.90406 Customer satisfaction 368 1.75 7.00 4.8811 1.01904 Trust 368 1.00 7.00 4.6848 1.38314 Repurchase Intention 368 1.50 7.00 4.8098 1.10323
  • 16. Selection Criteria and Data Manipulation • Sample Selection Criteria: • Unknown as we are using open-sourced pre-collected data. Believed to be convenience sampling. • Data Manipulation • Being samples have complete data sets, no manipulation such as list wise deletion will occur. • Data Transformation: • We will use Log and Ln Transformation methods to achieve normal distribution.
  • 17. Modeling approach • Regression model: A predictive model designed to analyze the relationship between independent and dependent variables. We will use mostly linear modeling. This model helps determine the relationship between variables, forecasting, and modeling.
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