FACTOR ANALYSIS OF PRODUCT (SAMSUNG PHONE)

TITTLE– FACTOR ANALYSIS OF PRODUCT (SAMSUNG PHONE)

 

Authors

:

Dev Modi (021330024336) Ashutosh Shukla (021330024076) Aachman Dixit (021330024001)

• Introduction:

Samsung was founded by Lee Byung-Chul in 1938 as a trading company. Over the next three decades, the group diversified into areas including food processing, textiles, insurance, securities, and retail. Samsung entered the electronics industry in the late 1960s and the construction and shipbuilding industries in the mid-1970s; these areas would drive its subsequent growth. Following Lee’s death in 1987, Samsung was separated into five business groups – Samsung Group, Shinsekai Group, CJ Group, Hansol Group, and JoongAng Group.

• The 10 Characteristics of Samsung Phone are:

1. Innovative Display
2. Advanced Camera
3. Performance
4. Battery Life
5. Customization
6. 5G and Connectivity
7. Durability
8. S Pen Support
9. Security
10. Ecosystem Integration

 

• Objective- To reduce the dimension
• Data Collection– The survey was conducted using Google Forms to evaluate perceptions of Samsung Phone based on ten essential characteristics: Innovative Display, Advanced Camera, Performance, Battery Life, Customization, 5G and Connectivity, Durability, S Pen Support, Security, Ecosystem Integration. A total of 50 respondents, consisting of friends and relatives, participated in the survey. Each question targeted one of these specific characteristics, as outlined below-

1. Innovative Display: How important is having a high-resolution display (e.g., 4K, HDR) for you?
2. Advanced Camera: Would you prioritize a front camera with advanced features (e.g., portrait mode, 4K video)?
3. Performance: How important is having the latest processor?
4. Battery Life: Do you prefer fast charging or longer-lasting battery over time?
5. Customization: Do you like to customize the appearance of your device’s interface?
6. 5G and Connectivity: How important are additional connectivity features (e.g., Wi-Fi 6, Bluetooth 5.0)?
7. Durability: Would you invest in a more durable device, even if it increases the cost?
8. S Pen Support: Do you currently use, or would you consider using an S Pen or stylus?
9. Security: Would you prefer a device with advanced security features, even if it affects performance?
10. Ecosystem Integration: Would you prefer your device to work seamlessly across platforms (e.g., iOS and Android)?

Participants rated their responses on a Likert scale with the following values

–  lowest rating – One star

–  Moderate rating – Two star

– Highest rating – Three star

This approach enabled us to gather detailed feedback on each characteristic, providing comprehensive insights into the overall perception and satisfaction with Samsung Phone among the respondents.

• Data Analysis:

1. KMO AND BATLETTERS TEST

KMO and Bartlett’s Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.		.805
Bartlett’s Test of Sphericity	Approx. Chi-Square	234.324
	df	45
	Sig.	.000

 

• Interpretation: The KMO and Bartlett’s Test results suggest that the data is well-suited for factor analysis. The Kaiser-Meyer-Olkin (KMO) Measure of Sampling Adequacy value is 0.805, which falls into the “good” range (above 0.7). This indicates that the sample size is sufficient and that the variables share enough common variance to support reliable factor analysis. Additionally, Bartlett’s Test of Sphericity, with an approximate Chi-Square of 234.324 and a significance level of 0.000 (p < 0.05), confirms that the variables are not unrelated. This test’s significance suggests that there is sufficient correlation among the variables to allow for meaningful factor grouping. Overall, these results confirm that factor analysis is appropriate for this dataset, as it is likely to reveal interpretable underlying factors.

2. COMPONENT MATRIX

Component Matrix
	Component
	1	2
Battery Life	.815
5G and Connectivity	.784
Performance	.783
Durability	.751
Customization	.744
S Pen Support	.726
Advanced Camera	.672
Innovative Display	.590
Ecosystem Integration	.579	.521
Security	.621	.657

• Interpretation: The Component Matrix table presents the results of a Principal Component Analysis (PCA), where two main components have been extracted from the variables. Each variable has a loading, or correlation, with one of these components, indicating how strongly it associates with that component.

For Component 1, variables such as Battery Life (0.815), 5G and Connectivity (0.784), Performance (0.783), and Durability (0.751) have high loadings. This suggests that Component 1 likely represents attributes related to the device’s operational performance and reliability—those aspects that contribute directly to functionality, durability, and connectivity.

For Component 2, Security has high loadings on both components, with values of 0.621 on Component 1 and 0.657 on Component 2, indicating that security might span both operational performance and user experience. Ecosystem Integration also shows moderate loadings on both components (0.579 for Component 1 and 0.521 for Component 2), implying it has relevance to both dimensions. This overlap suggests that these two variables contribute across the operational and user experience dimensions.

 

3. Total Variance Explained

Total Variance Explained
Component	Extraction Sums of Squared Loadings			Rotation Sums of Squared Loadings
	Total	% of Variance	Cumulative %	Total	% of Variance	Cumulative %
1	5.058	50.580	50.580	3.807	38.074	38.074
2	1.069	10.692	61.273	2.320	23.199	61.273

 

• Interpretation: The “Total Variance Explained” table shows that the two components extracted in the Principal Component Analysis capture 61.27% of the total variance in the dataset, indicating a strong data structure. Initially, Component 1 explains 50.58% of the variance, and Component 2 adds 10.69%, capturing most of the information together. After rotation, Component 1 explains 38.07% and Component 2 explains 23.20%, balancing the variance across both components. This rotation improves interpretability, revealing two distinct factors that together summarize the majority of the original data’s variance.

4. Rotated Component Matrix

Rotated Component Matrix
	Component
	1	2
5G and Connectivity	.846
Advanced Camera	.740
Customization	.737
S Pen Support	.710
Battery Life	.704
Performance	.680
Durability	.584
Security		.893
Ecosystem Integration		.756
Innovative Display

 

• Interpretation: The Rotated Component Matrix indicates the loadings of each variable on the two extracted components after rotation, enhancing interpretability. Component 1 primarily represents attributes related to connectivity and performance, with high loadings for 5G and Connectivity (0.846), Advanced Camera (0.740), and Customization (0.737). This suggests that these features are strongly associated with the device’s operational capabilities. Conversely, Component 2 highlights aspects related to security and user experience, with Security loading at 0.893 and Ecosystem Integration at 0.756. The absence of loadings for Innovative Display indicates it may not align strongly with either component, suggesting a potential need for further exploration of its role. Overall, this matrix effectively differentiates between functional and experiential aspects of the device.