Keywords

Perception, Perceived Brand Image, Dissonance, Brand Loyalty, Post Purchase Regrets, Potential Consumption, Marketing Research.

Introduction

Since marketing research started to concentrate on consumer needs and wants, customer satisfaction and the post purchase experience got more attention. A scientific evaluation of consumption behaviour will help the producer to have a clear picture of customer buying decision. There are number of factors they have certain influence on consumption behaviour like cultural, social, economic, psychological and personal factors. Few of these factors are beyond the control of the marketer and fully depended to the psychological behaviour of consumers generating through his perception. However, a detailed examination of buying behaviour is necessary to tackle all the hurdles in the marketing process.

Brand image has been placed as the hot concept in the modern marketing world and it is a magical network which control and connect the entire buying and selling process. Concept of branding got more attention in the market 1970 when producers and marketers start associating their products with some idea. Later the process has led to the creation of brand equity and finally producers were able to acquire brand loyal customers in the market. In late 1980’s globally producers started enjoying the leverage of their successful brand in the turnover and profit. This awareness has pushed them to invest more in developing brand that has a place in the customers mind globally and slowly brand got a place in the balance sheet of almost all large manufacturers with a volume of millions.

Buying decision of a customer is a cyclical process which passes through five different stages most of the time and the purchase decision is happening in the fourth stage. All the customers are not passing through theses stages in the cycle as the nature of the products and behaviour of buyers are different from one to another. Moreover, majority of journey may not end up in a purchase decision. Consumer buying decision process is illustrated below in Figure 1.

Exposure of buyers throughout the buying process and the post purchase experience may have greater impact on the customer perception of brand image. Obviously post purchase experience is the factor that may lead to frequent buying by a customer and it will attract some new customers through the recommendation of satisfied buyer. In the case of mobile phones, post purchase exposure consists all the encounters happened between owners and sellers after the purchase of a device. Purchase of an electronic gadget recently involves a moderately high level of mental and financial commitments by the customer; and their opinions and evaluations are extremely significant as they decide the future of that particular model. Customers may think in the following ways before and after the buying decision Figure 2.

Most of the buying decision of now a days has impacted from the review written by the existing users, especially in the case of online purchases particularly for mobile phones. Through this paper researcher tries to trace out the influence of customer reactions after the actual use mobile phones on the brand image perception in his mind. Analysis of the data reveals that post purchase exposure of a customer has a significant role in deciding the future of a brand.

Research Objectives

Perceived brand image is an important phenomenon that has a direct relationship with sales turnover and success of the brand. When we are looking to the market, consumers are bombarded with number of choices and they are confused about selection criteria. So the selection is based on something other than the tangibles related with the product and that criteria are brand image on most of the occasions. Through this study, researcher aims to analyze the brand image perception in the mind of mobile phone users before and after actual use of the device. Secondary to the main objective researcher attempts to evaluate the personal and demographic profile of the buyers and also the changes happening in their behaviour due to some post purchase regrets.

Literature Review

Gerald (1967) had analyzed feelings of a brand new product owner and examined the reactions of the customer when he starts experiencing the product. He concluded his study by stating that post purchase behaviour of a customer depended to his personality type and quality of the utility he gained from the product.

Park et al. (1986) mentioned that there are two determinants for the proper brand management of a brand namely construction of brand and maintenance of brand image. Brand image is established through functional, symbolic or experimental elements. There are number of opinions on the definition of brand image. But the previous literature reveals that its definition has four perspectives like blanket definition, meaning and message, personification and cognitive or psychological elements.

Keller (1993) has initiated a new concept in marketing called “customer based brand equity (CBBE), as the reaction of consumers against the branding campaign of producers. As per this concept two basic point of production of brand equity are the brand image and brand awareness. A strategic and complete marketing campaign helps to build a positive brand image by linking unique and strong brand association with customer experience on that brand. It is necessary to create good brand knowledge in the mind of potential buyers to generate a positive response among them. There is a need of building good brand knowledge in the mind of potential buyers to create a positive response among them. It will help the producer to reduce cost of brand extension while trying to achieve more shares in the existing market.

Cagla Hirschman (1995) explains that in early 1990’s there was a sudden paradigm shift in the buying behaviour of customers from static mode to dynamic mode. Evidences are available to show the impact of previous consumption on the current choices of the customers. Besides previous choices brand equity also plays an important role in this buying process. Previous direct or indirect experiences with different brands have certain influence on selection among from different choices.

Lassar et al. (1995) was in the opinion that customer’s confidence on the performance of a particular brand generates brand equity and brand loyalty. Moreover, customers are ready to pay more if they are much confident on the utility of the brand. There are five determinants of customer confidence in a particular brand; they are; functioning as designed for, image in the society as an owner of a particular brand, recognition and emotional attachment towards the product, balanced brand value and its functionalities and customers trust on brand.

Tsiotsou (2006) has investigated the impact of perceived product quality on the overall satisfaction of purchase intention of a customer. He identified the direct and indirect relationship of perceived brand image and buying intention and concluded that perceived quality has a direct and indirect influence on purchase decision.

Rahman (2014) has conducted a detailed study on the telecommunication sector of Bangladesh to analyze the choices of people in the preference of mobile network services. The examination was held among 450 randomly selected mobile network users of the capital city Dhaka. Main objective of the study was to identify the most influencing factor of perceived brand image and he reached in a conclusion that service quality of the network is the most influencing factor in creating brand image in the mind of consumers.

Marnik et al. (2013) conducted a study regarding brand loyalty among the customers and its role in retaining customers. The result of the study indicates that brand loyal customers are very less price sensitive comparing others in the market. So the loyal group of customers provides some strength to the brand in the competitive world. Study also reveals that cost of searching and finding new customers is very high when comparing the cost of maintaining the existing customers; sometimes it is six times higher than the previous one.

Tenna Heesch Jorgensen (2013) was trying to identify the difference in brand equity of local brand and that of an international brand. A comparative analysis of two coffee brands Tim Hortons and Starbucks in Canada was conducted to find the difference in brand equity. Study was based on an indigenous brand Tim Hortons and a multinational brand Starbucks from the same industry. Her investigation reveals that there is no such difference in brand equity of both local and global brand and customers of both brands have strong association with their own brand.

Nusrat-Jahan Abubakar et al. (2017) went for study at University of Ghana on factors contributing to cognitive dissonance and this study developed a model for explaining the post purchase regrets. Study explains that there are independent and depended variable related to post purchase regrets. The relationships between these variables are depicted in Figure 3 below.

Methodology

This research is an exploratory study and population consists of mobile users from state of Kerala. Purposive sampling method was used to identify the samples from the population and samples are selected from two districts of Kerala, Alappuzha from south side and Kannur from north Kerala. Total 300 mobile phone users were selected from the two districts using purposive sampling technique. A well-structured questionnaire consisting items to measure owners satisfaction, post purchase experience and brand loyalty was prepared and distributed to sample respondents for data collection Table 1.

Table 1 Source: Primary Data
Demographic Features	Category	No. of Sample Respondents	Percentage
Age	Up to 20 year	18	6.00
	21 – 40 Years	160	53.33
	41- 60 years	96	32.00
	Above 60 Years	26	8.67
	Total	300	100.00
Gender	Female	121	40.33
	Male	178	59.34
	Transgender	1	00.33
	Total	300	100.00
Education	Up to 12th Std.	67	22.33
	Graduates	142	47.33
	Post Graduates	41	13.67
	Others	50	16.67
	Total	300	100.00
Occupation	Students	34	11.33
	Business	98	32.67
	Profession	43	14.33
	Employed	88	29.33
	Agriculturists	17	5.67
	Home Makers	11	3.67
	Retired	9	3.00
	Total	300	100.00
Annual Family Income	Up to 5 lakh	123	41.00
	5 lakh to 10 lakh	136	45.33
	Above 10 lakh	41	13.67
	Total	300	100.00

Data Analysis and Interpretation

Demographic profile of the respondents shows that majority of them belonging to age group 20 - 40 years. A considerable portion of the respondents are male and 40.33% of the respondents are female, a transgender has also been selected as sample. When we are analyzing the educational background of the sample respondents 78% of the respondents have a qualification of graduation or above that and 22.33% of them are under graduates. Occupational status of the sample respondents shows that there are representative form all the category in our society like students, business people, professionals, employees, agriculturalist, house wives and retired hands. An analysis of annual family income of the sample respondents reveals that majority of them belong to an annual income lass of 5 to 10 lakh.

Relationship Between Demographic Profile and Brand Selection

This section of the paper analyses the relationship between demographic features of the sample respondents and their preferences on branded mobile phones. It is identified that demographic features like age, gender, education, occupation and annual family income are associated with the selection of mobile phones. This relationship between demographic features and selection are identified through Chi-square tests. Findings of the Chi-square analysis are explained in the table.2 given below Table 2.

Table 2 Source: Primary Data (Own Calculation)
Demographic Profile	Calculated Value	Table value	Inference
Age	14.97	12.90	Significant at 5% level
Gender	14.83	11.27	Significant at 5% level
Education	26.52	34.80	Not significant
Occupation	59.40	58.70	Significant at 1% level
Annual Family Income	33.93	36.42	Significant at 5% level

H0: “Demographic profile of the sample respondents has no significant impact on the purchase of branded
mobile phones”.

From the above analysis it is observed that demographic profiles of the sample respondents are very significant in their buying behaviour. From the above listed Chi-squire results it is very clear that features like age, gender, occupation and annual family income of the respondents have prominent role in their selection of branded mobile phones, but the sample data show that educational qualification of the respondents has not impacted more in their choices. Hence the hypothesis “demographic profile of the respondents have no significant impact on the purchase of branded mobile phones” has been rejected with respect to educational qualification and H0 has been accepted in connection with features like age, gender, occupation and annual family income of the respondents Armstrong et al. (2008) Table 3.

Table 3 Source: Primary Data
Specifications	Category	No. of Respondents	Percentage
Brand Owned	Samsung	126	42.00
	Xiaomi	68	22.67
	Vivo	37	12.33
	Oppo	29	9.67
	Apple	21	7.00
	Others	19	6.33
	Total	300	100.00
Type	5G	48	16.00
	4G	234	78.00
	Feature	18	6.00
	Total	300	100.00
Body Colour	Black	142	47.33
	Blue	67	22.33
	Gray	34	11.33
	Silver	29	9.67
	White	11	3.67
	Others	12	4.00
	Total	300	100.00
Camera Size	Up to 8 MP	60	20.00
	8 MP to 20 MP	154	51.33
	20 MP to 64 MP	68	22.67
	Above 64 MP	18	6.00
	Total	300`	100.00
Memory	Up to 16 GB	28	9.33
	32 GB	48	16.00
	64 GB	132	44.00
	128 GB	78	26.00
	Above 128 GB	14	4.66
	Total	300	100.00
RAM	2 GB	41	13.67
	4 GB	192	64.00
	6 GB	39	13.00
	8 GB or More	28	9.33
	Total	300	100.00

Features of Devices Owned by The Sample Respondents

Above tabulation explains the specifications of mobile phones owned by the sample respondents. Samsung, Xiaomi, Vivo, Oppo and Apple are the most preferred brand in the market. Primary data reveals that Samsung is the most accepted brand in the market followed by Xiaomi. 75% of the sample respondents own 4G phones and still 6% of them are using old model feature phones. Black is most preferred colour in the market and blue comes in the second position. From the analysis it is very clear that camera size 8 MP to 20 MP are widely preferred segment and 51.33% of the sample respondents own these type devices. Most preferred combination of memory size by the respondents is 64GB – 4 GB (RAM).

Uses of Mobile Phones- Multiple Responses

Respondents have been requested to disclose the intended purposes of mobile phone. Questionnaire provides facility to express multiple responses against this and the respondents were allowed to rank their uses, frequent uses have been ranked as first (Rank 1) and the less important one as four (Rank 4) Dekimpe (1996). Most of the respondents have multiple opinions on this question and respondents were allowed to rank their uses according to their preferences. For analyzing the responses provided Francis Sekar (2013) mean score of the responses are calculates as given in the table.4. Personal purpose got the highest rank with a mean score of 1.37 and office purpose got the lowest rank with a mean score 3.83 Chatterjee & Hadi (2006) Table 4.

Table 4 Source: Primary Data (Own Calculation)
Usage	Mean Score of Ranks
Personal Purpose	1.32
Family Purpose	1.87
Business Purpose	2.98
Office Purpose	3.83

Factors Influenced in Selection of Brand Multiple Responses

Marketing researches reveal that there are certain factors which have certain influence in the selection of branded mobile phones. Fifteen key factors were identified by the researcher through the review of literature, discussion with marketing experts and own observation. Result of this study also reveals that these factors are much influential in buying decision of branded mobile phones. As far as buyer is concerned these factors are Landman (1987) very significant since the decision is an irreversible one with long-term impact and the fund committed is moderately high. Participants of the survey were asked to rank the influencing factors according to the relevance of these factors in their buying decision. Rank 1 is assigned to the most relevant factor Zeelenberg & Pieters (1999) and least relevant one is requested rank as Rank 15. Below given table reveals the relevance of these factors in the buying decision of sample respondents Bell (1967) Table 5.

Table 5 Source: Primary Data (Own Calculation)
Factors	Means Score of Ranks
Price	3.98
Memory	4.20
Camera	5.03
After sales service	6.16
Brand name	6.92
Color	7.12
Portability	7.82
Review of owners	7.90
Add on features	8.63
Previous experience	8.78
Offer	9.10
Design	9.73
Add on Accessories	10.12
Convenience	11.30
Power backup	13.21

The mean scores analysis given in the table reveals that price is most influencing factor in the buying decision of mobile phones with a mean score of 3.98. Storage capacity is the second factor that influences the buying decision with a mean score of 4.20 and mega pixel of both front and rear camera comes next as the third influencing factor. After sales service, brand name, color, portability and review of existing users are almost equally important in the buying decisions. Convenience and power backup got least consideration while thinking about purchase of a mobile phone.

Relationship between Post Purchase Experience and Frequency in Usage

Another attempt was made by the researcher to identify the relationship between post purchase experience of the buyers on product features like memory, camera quality, portability and handy with frequency of usage. Obviously the buying decision is based on certain expectation of various features of mobile phones and the actual experiences very important in the future of the brand in the market. A Chi-square analysis has been conducted to identify the relationship between actual performance of the gadget and its frequency of usage. The relationship is explained in the given below Hirschman (2004) Table 6.

Table 6 Source: Primary Data (Own Calculation)
Owner’s Experience	Calculated Value	Table Value	Inference
Memory	23.04	25.252	Not significant
Camera quality	22.017	21.731	Significant at 1% level
Portability	9.45	7.569	Significant at 5% level
Handy	31.67	24.371	Significant at 1% level

H0: “Actual experience on features like memory capacity, camera quality, portability and handy of mobile phones have no significant association with frequency of usage”

Given Chi-square analysis reveals that features of mobile phone like camera quality, portability and handy are significantly related with frequency of its use. Hence the hypothesis “Actual experience on features like memory, capacity, camera quality, portability and handy of mobile phones have no significant association Jørgensen (2013) with frequency of usage” has been rejected Hosseini & Jayashree (2014).

Comparison of Pre-Purchase Opinion and Post Purchase Opinion

A comparative analysis of pre-purchase opinion and post purchase opinion collected from the owners were conducted to identify the perceptional differences. Factors that may cause for differences in opinion among from the most influencing factors were considered for collecting opinion. Pre-purchase and post purchase opinion on factors that may have more chances for the variation in actual and expected performance have been used for analyzing situations Table 7.

Table 7 Source: Primary Data (Own Calculation)
Pre- Purchase and Post Purchase Opinion on:	Z score	p value
Memory	1.8336	0.0334
Camera quality	0.588	0.278
Power backup	0.456	0.174
After sales service	2.89	0.004

For analyzing the difference in expected memory capacity and actual memory of the mobile phone Z value has been calculated. Z score is 1.8336 with p 0.0334, it implies that there is no significant difference in expected and actual memory of the device since the p value is (p<0.05). In the case of camera quality of mobile phones Z score is 0.588 with p 0.278, which indicates that there is significant difference in expected camera quality and actual camera quality. In the case of power backup of mobile phones Z score is 0.456with p 0.174, which indicates that there is significant difference in expected power backup and actual power backup of the device.

Comparison of expected and observed satisfaction level of after sales services gives a Z score of 1.34 with p 0.180, in this case Z score is less than 1.96, the significance is greater than 0.05 and it implies that there is no significant difference in expected and observed quality of after sales services provided by the manufacturer through dealers.

Influence of Post Purchase Regret on Owners Behaviour

Previous section of the study has identified some post purchase regrets among the users of mobile phones. This has motivated the researcher to conduct a deep analysis on the relationship between post purchase regrets and its impact on the perception of a brand in the mind of customers. Previous analysis reveals that a considerable amount of customers are not satisfied with camera quality of their device and power backup. Few important statements were included in the questionnaire to estimate post purchase regrets of mobile phone users and to identify their behavioural deviation after the purchase leading to post purchase regrets. On the basis of these statements below given hypotheses are built to examine the changes in consumer behavior Table 8.

Table 8 Source: Primary Data (Own Calculation)
Test	Correlation Coefficient ®
Karl Pearson’s Correlation	0.5120

H0: There is no significant relationship between post purchase experience and recommending the brand to
other potential buyers.

Value of Pearson’s correlation coefficient is calculated as 0.5120 and it indicates a moderately strong correlation exists between the variables. A major portion of the existing customers are not satisfied with some of the features of their devices, so that they are not willing to suggest the same brand to others. So the hypothesis “There is no significant relationship between post purchase experience and recommending the brand to other potential buyers” has been rejected Table 9.

Table 9 Source: Primary Data (Own Calculation)
Test	Score
One Sample T test	p value = 0.06748

H0: There is no significant relationship between post purchase regret of customers and frequency of using
mobile phones.

P value of the above one sample T test is > 0.05, so the null hypothesis “There is no significant relationship between post purchase regret of customers and frequency of using mobile phones” has been accepted and the analysis reveals that there is no significant association between post purchase regrets and frequency of usage of mobile phones Table 10.

Table 10 Source: Primary Data (Own Calculation)
Test	Correlation Coefficient®
Karl Pearson’s Correlation	0.5713

H0: There is no association between post purchase regrets and willingness to purchase gadgets of same
manufacturer.

Pearson’s correlation (r) coefficient is calculates as 0.5713, which is less than 0.6. It indicates that a moderately strong correlation exists between post purchase regrets and purchase of gadgets of same manufacturer. Since some of the customers have different opinion on the performance of their device and they are not ready to buy the products of same manufacturer when they replace their device or when they prefer a second one.

Conclusion

Consumers of any companies are the main element of the market and all the efforts and attention should be given to them. Each and every company should implement different strategies to keep up with the changing market conditions and to reach the consumers who constantly change their purchasing tendencies and expectations. Statistical analysis of the data obtained under this study reveals that, factors influencing the buying intention of customers of mobile phones have been mostly found to be matching with the available literature. Since the perceived brand image indicates information about quality of product, satisfaction of customer expectations, management of brand image may turn into repetitive purchase behaviour. Producers and sellers should employ all the creative ways to maintain the image perceived by the customers, this will help to reduce the risk involved in shopping. The result of this study may provide some cues to the producers and marketers for making some changes in their targeted segments. This research still predicts that further studies are needed with additional samples from most of the corners of the world before generalization can be made.

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Received: 31-May-2022, Manuscript No. AMSJ-22-12111; Editor assigned: 04-Jun-2022, PreQC No. AMSJ-22-12111(PQ); Reviewed: 18-Jun-2022, QC No. AMSJ-22-12111; Revised: 20-Jul-2022, Manuscript No. AMSJ-22-12111(R); Published: 27-Jul-2022