Survey on Factors affectin­g consumer behavior of smartpho­ne user

ANOVA

What is the smartphone brand you are currently using?

Table 30: ANOVA table for accessories provided and current brand

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The following F-test is conducted to analyze if the selection of current brand by the smartphone user is influenced by accessories provided. So this test shows how influential the accessories provided is.

From the table 29, we can see F-value is 0.471 and p-value is 0.757. Here p-value is greater than significance level of 5%, so there is enough evidence to support that there is no significant relationship between accessories provided and current brand.

Therefore it can be said that there is no or less impact of accessories provided on the choice of current brand of smartphone among the given sampled 109 participants.

4.1.3.17 Performance and Current Brand

H0: There is no significant relationship between performance and current brand

H17: There is significant relationship between performance and current brand

ANOVA

What is the smartphone brand you are currently using?

Table 31: ANOVA table for performance and current brand

The following F-test is conducted to analyze if the selection of current brand by the smartphone user is influenced by performance. So this test shows how influential the performance is.

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From the table 31, we can see F-value is 0.675 and p-value is 0.611. Here p-value is greater than significance level of 5%, so there is enough evidence to support that there is no significant relationship between performance and current brand.

Therefore it can be said that there is no or less impact of performance on the choice of current brand of smartphone among the given sampled 109 participants.

4.1.3.18 Correlation Analysis among Factors Influencing Purchase Decision of Smartphone

Users

Correlations of Satisfaction with Various Factors

Table 32: Correlation Analysis of Factors Influencing Purchase Decision

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The above table shows the correlation among various variables. From the table we can see in general that, every variable are positively correlated to each other.

From table it can be seen that product feature and looks and design is mildly correlated with performance. However other factors are seen to have low correlation among each other.

From this we can interpret that there is less dependency of variables among each other in terms of satisfaction i.e. if 3an individual is satisfied with price, there is chance that he/she may not be equally satisfied with other factors.

4.1.3.19 Analysis of Income Level and Satisfaction from Pricing

H0: There is no significant relationship between income level and satisfaction from pricing

H18: There is significant relationship between income level and satisfaction from pricing

Satisfaction with pricing

Table 33: Descriptive analysis of income level and satisfaction from pricing

The above table shows the response of 109 respondents in regards to satisfaction from pricing. In the questionnaire the respondents were asked to give their response in regards to satisfaction level from pricing of smartphone with 1 being highly dissatisfied and 5 being highly satisfied.

In the table mean value of the response is shown among different income groups. It shows that income group of 10000-25000 has mean value of 3.56 which shows that they are satisfied with pricing. Similarly other income group also has shown satisfaction in regards to pricing. So, to test the given assumption, F-test is done.

ANOVA

Satisfaction

Table 34: ANOVA Table for income level and satisfaction from pricing

Here, from the table F-value is 0.371 and p-value is 0.774. Since p-value is greater than significance level of 0.05, we can conclude that there is no significant relationship between income group and satisfaction with pricing. Hence, it can be said that there is no difference in satisfaction with pricing in regards to income group.

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4.2 Findings and Result

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Chapter 5: Summary, Conclusion and Recommendation

5.1 Summary and Conclusion

Smartphone has not only been the want but also a need in this modern era (Nagarkoti, 2009). An average person spending at least 2 hours of the day for using smartphone prove that how smartphones have played a vital role in our daily life. Due to the multiple uses of smartphones, there has been a high demand of smartphones. It has been a part of life in Kathmandu Valley.

Companies have been spending millions in producing smartphones. From R&D to advertisement to after sales service, mobile phones have taken an access height in the market. From releasing a promo to introduction in the market, people are crazy about upcoming smartphones in the market. There has been a paradigm shift of smartphone, say it from design to product features over the past decades.

The Moore’s law seems to become true in context to smartphones too, as the years passes by the performance of smartphones is increasing while its Intel chips size is decreasing.

This study was conducted among the people in Kathmandu. Sample of 109 respondents were taken for the purpose of study which included 56% male and 44% male. The sample was further divided on the basis of income group, occupation and age group. Various factors were considered for the purpose of studying the consumer behavior of smartphone users. Apple was the most preferred brand followed by Samsung and Huawei.

The study showed that current brand of smartphone varies as per age and income group.

Similarly willingness to spend on a new smartphone varies according to age and income level.

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Though there is significant difference between age group and income and current brand, however there is no significant impact of age and income on preferred brand of smartphone.

Various factors such as price, brand image, etc. were studied to understand the consumer behavior of smartphone user. The study highlighted that on the basis of income level, difference was found among respondents when they considered the variables/factors like product features, looks and design and performance while making the purchase of smartphone. However there was no significant relationship between income level and other variables.

Similar study was done on the basis of gender. It was found that there was difference between male and female when they considered peer influence while making a purchase difference. On other factors they were independent.

Further statistical analysis was done to know if attitudes of respondents towards these mentioned variables affected the respondent use of current brand of smartphone. On the study it revealed that brand image had significant impact on respondent’s current brand of smartphone. Therefore, the difference in the attitudes of respondents towards brand image has significant impact towards consumer current choice of smartphone.

5.2 Recommendation

Consumer behavior and decision making is influenced by various factors. Similarly in the smartphone industry, consumer’s perception, attitudes, behavior and decision making are affected by these factors which include demographic factors as well as non-demographic factors like price, brand image, peer influence etc. So, it is important for the smartphone dealers to consider these factors when making strategies.

They need to understand how each factor impact

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on consumers’ perception towards particular smartphone brand thus affect their decision making and purchase behavior.

A recommendation for future research in this field is to conduct the study with a larger sample as larger sample will help in analyzing the consumer behavior more accurately. Also, it would be beneficial to conduct this study over a period of time, with a longitudinal time horizon, thus discovering trends in attitudes and behaviors. Finally, consumer attitude could be better understood if other factors which are driving consumer in purchasing a smartphone are taken into consideration.