Editorial Board

A Refereed Monthly International Journal of Management

Perceptual Mapping of SED and Brand Choice to Purchase Car

Author

Madhusmita Choudhury Research Scholar Centurion University of Technology & Management

Prof Dr Bidhu Bhusan Mishra Professor & HOD Dept. of Business Administration, Professor Utkal University Bhubaneswar, Odisha

Dr P. K. Mohanty Dean School of Management, Centurion University of Technology & Management Bhubaneswar, Odisha

Abstract

India is one among the world’s quickest growing automobile markets and is poised to become the third largest passenger’s automobile market by 2020 (Philip, L. 2016, Economic Times). The recorded sales growth of four wheelers like car & utility vehicle has additionally up up-to 7.87 % and 6.25% severally throughout April-March 2016 (SIAM, 2015-16). however what makes an automobile maker like Japan’s Maruti Suzuki and Korea’s Hyundai enjoys quite 67% of market share whereas others like United States of America automobile manufacturers Ford Republic of India and General Motors combined market share is simply 4-5%(Philip,L.2016,The Economic Times). Sales within the North & East region have proven solely 5%of changes within the FY16 that is relatively under the west & south region (Khan,A.N,2016, The Economic Times). The Japanese automobile makers(Honda, Hyundai, Isuzu Motors, Nisan &Toyota) achieved a median of forty eight.01% of growth until Gregorian calendar month 2016 having an improved stand from the Indian automobile manufacturers (Hindustan Motors, M&M,M&S, Tata & Force motors) i.e. 6.74% (Autocar professional News table, July 2016). During this study the investigator explored the SED factors and its effect on Brand choice of prospective automobile patrons and existing automobile users at dealer purpose and facilitate dealer to form an excellent “moment of truth” (Pioneered by JanCarlzon) once a client encounter with company.(Madge, Davidson & Beaujean, 2006)

Keywords: Service Quality, Service recovery, Moment of Truth, Dealer satisfaction, Brand Choice, Brand Image

Introduction

Customer brand preference or choice is a basic advance towards comprehension, customer decision behaviour and has along these lines always received incredible consideration from advertisers. In any case, the investigation of brand choice has been restricted to customary advertising concentrating on utilitarian ascribes to augment utility. Be that as it may, now the move to experiential promoting expands the part of the brand from a heap of credits to encounters. The inclination for comfort, originality/newness, chance experiences, and collection purchasing behaviour are however a few purposes behind redundant purchase designs (de Chernatony, Harris, and Christodoulides, 2004). Brand inclination/preference is the predisposition a client holds toward a specific brand. Cobb-Walgren et al. (1995) and Myers (2003) have focused on the significance of building brand equity (value), which brings the upside of more buyer brand inclination and customer's buy intention to the firm. Hellier, Geursen, Carr, and Rickard (2003) characterized brand inclination as 'the degree to which the client supports the service gave by his or her present organization, in contrast with the service gave by different organizations in his or her mind set'. The purchase intentions are a client's intent to purchase a particular brand and have as of now been the focal point of extensive consideration. Results from investigation of Jamal, A., & Al-Marri, M. (2007) offer help for a solid connection between mental self-image compatibility and brand fulfilment and between brand preference and brand fulfilment among clients of cars by and large. As such, both mental self-image compatibility and brand preference have all the earmarks of being solid indicators of brand fulfilment in the vehicle showcase. This is in accordance with earlier research which has revealed comparative discoveries in the travel destination market (Sirgy et al. 1997), retail banking (Jamal 2004) and valuable jewellery industry (Jamal and Goode 2001). We can likewise presume that, when all is said in done, self-concept assumes an imperative part in deciding customer decision and that a few purchasers may lean toward brands that have images good with their perception of self (Belk, et al. 1982; Ericksen 1996, Mehta 1999, Sirgy et al. 1985; 1997; Zinkham and Hong 1991; Jamal 2004; Jamal and Goode 2001). Brand fulfilment is the inclination a client towards a brand after it has been utilized; it can be driven by a scope of components, including brand preference, on the grounds that the measurements basic fulfilment judgments are worldwide as opposed to particular (Rust and Oliver 1994). We contend that brand fulfilment is probably going to be more prominent for most favoured brands than for slightest favoured brands. Brand preference mirrors certain intellectual judgments and additionally some positive full of feeling emotions, which are probably going to be held in the memory. Escalated rivalry exists inside the vehicle advertise with wide assortment and decision for clients inside every product marketed. Because of the exceptionally focused nature of the market, numerous understand that having a solid corporate brand could be a basic piece of an upper hand for a firm (de Chernatony and McDonald 1998; McDonald et. al. 2001). A solid corporate image is regularly the best type of separation as solid brands develop clients' trust and empower clients to better envision and comprehend brand (Berry 2000). Brand promoting has its impact by affecting convictions about a brand with a view to create brand preference the item class. Psychologists see choice as a learning construct and characterize knowledge and processing of information as the two principle wellsprings of buyer preference learning (Amir and Levav, 2008; Howard and Sheth, 1969; Sheth, 1968). Howard and Sheth (1969) recommend that brand choice alludes to purchasers' inclination towards specific brands that compress their subjective data preparing towards brand stimuli. This theory and other information processing models (Bettman, Capon, and Lutz, 1975) underline both the focal control unit and the psychological capacities of purchasers. In this manner, it takes after that a buyer's discernment about brand ascribes prompts preferences or attitudes, which influences his/her purchase intentions and brand decisions (Bagozzi, 1982). Along these lines, inclination/preferences speak to a progress state between the input of information and yields of the customer decision model. It is the connection between information input and the outcome of expectation to really buy or select a specific brand (Bagozzi, 1983). It is recommended that experience ought to be joined with the brand importance put away in purchasers' brains to create inclinations. As an immediate wellspring of buyer inclinations, it is recommended that experience advances better memory with striking and solid information (Paivio, 1971). Schwarz (2004) shows that purchasers depend on their experiences as trusted wellsprings of information, to judge amongst alternative products and settle on decision to purchase. Customers favour brand that give an important experience while they personally visit store/location/places (Goode, Dahl, and Moreau, 2010).

1.2 Research Objective
a.	To explore the role of demographic factors & its influences on Brand choice in automotive sector. 
b.	To find out the effect of economic factors on Brand choice in automotive sector.
c.	To find out the effect of societal factors on Brand Choice in automotive sector.

1.3 Literature review

Demographic factors dependably impact advertising applications affecting showcasing marketing segmentations (Frank et al. 1972). A few researchers (Allenby and Rossi 1991; Chiang 1991; Gupta and Chintagunta, 1991) have fused brand choice model with demographic factors utilizing scanner panel data. Among the numerous variables that can impact a customer’s decision making thoughts, one of the central points is gender. People do shopping thinking about various thought processes, points of view, justifications, and contemplations. The impact of gender on shopping behaviour has turned into a conspicuous theme in the field of marketing (Hernández et al. 2011) beforehand; shopping was a characteristically female movement which has changed now (Buttle 1992). Presently, men are connecting more in shopping exercises (Otnes and McGrath 2001). Advertising utilizes the role of gender to advance distinctive brands (Dominick and Rauch, 1972; McArthur and Resko, 1975 ;Eisend, M., Dens, N., and De, P.,2019). Anderson, S. T., Kellogg, R., Langer, An., and Sallee, J. M. (2013) explored and found that there is a solid relationship amongst age and brand decision (Kotler et al. 2001). Customer’s age analysis has turned into a significant point these days (Harrison and Rainer Jr 1992). Youngsters and matured individuals have an alternate assessment in their way of life and decision of brand. Occupation is one of the extensive components (Onyeagwara, C. An., Agu, G. An., and Aja, E. E. ,2019). Individual nourishment decision conduct relies upon calling moreover. Housewife, government job holder, businessman or occupied with an alternate work may have diverse recognition (Ahuja 2011). Individuals with family-oriented lifestyle; will in general pick brands dependent on their requirements (LeClerc, Schmitt, and Dube, 1994; Mohamad, Ahmed, Honeycutt Jr., and Tyebkhan, 2000). By and large, age; wage; level of education affect customer to buy distinctive brands of decision (Kotler et al. 2001). Socio-statistic factors (age, instruction, and pay) likewise found to affect real purchasing conduct and selection of brands (Singh and Verma 2017). It is a business rationality based on thoughts of rising purchaser riches and dimensions of optional salary and brand decision. Salary influences (Yalcin, 2005 ;Onyeagwara, C,An., Agu, G. An., and Aja, E. E. ,2019 )the significance of inclinations for various sustenance characteristics. A study directed by Steptoe, Pollard and Wardle (1995) showed that, in the wake of controlling for cost (and in this manner for spending requirements), the revealed significance of inclinations for good taste and smell in nourishment is lower for low-pay people than for high-salary customers. Onyeagwara, C. An., Agu, G. An., and Aja, E. E. (2019) in his examinations found that Income, training, occupation and Marital status is critical in selection of brands and spot of purchasing. Cuneo, A., Milberg, S. J., del Carmen Alarcon-del-Amo, M., and Lopez-Belbeze, P. (2019) likewise bolsters that social class influences selection of brands.

1.4 Hypotheses
H1-There is an association between demographic characteristics of consumers and Brand Choice to purchase car.
H1a: There is no perceptual difference towards Brand Choice across Gender
H1b: There is no difference between age and Brand Choice.
H2-There is an association between economic characteristics of consumers and Brand Choiceto purchase car.
H20 - There is no difference between income level and Brand Choice.
H3-There is an association between societal characteristics of consumers and Brand Choiceto purchase car.
H3a: There is no perceptual difference towards Brand Choiceacross married & unmarried
H3b: There is no difference between occupation and Brand Choice.
H3c: There is no difference between Family size and Brand Choice.
H3d: There is no difference between Education and Brand Choice.
H3e There is no difference between Social class &Brand Choice.

1.5 Research design

Research design is the master plan of any research study focusing on thestructure, procedures and data analysis of the research given the limited amount of information on SED and Brand Choice in India, it was decided to study effectsof SED and Brand Choiceand test the established hypothetical relationship between different factors and the construct with the help of appropriate tools and techniques. The second phase was a field survey to gather the data necessary to test the relationships between the construct. The field survey was conducted PAN India however we received major responses from Bangalore, Purnea, Satna, Patna, Ahmedabad, Bilaspur, Ranchi, Bhubaneswar & Cuttackand 320 usable responses (All the responses were 1st checked for missing values by treating missing values in SPSS by categorizing them into quantitative variables and categorical variables and the researcher selected in all cases from the pattern to tabulate each case from the sample and it will also indicate missing & extreme values for each variable with Univariate statistics and estimated list wise and found no missing values) were taken into considered for the data analysis after deleting 1 outlier.

1.6 Sampling design

A sample design is a definite plan for obtaining a sample from a given population. It refers to the technique or the procedure would adopt in selecting items for the sample (Malhotra & Dash, 2007). The population of the study would be the automotive customers PAN India. The purposive sampling technique was adopted for the present study. Non- Probabilistic sampling was used to select the respondents as the population was required to possess the characteristics relevant to the automotive phenomenon being studied (Malhotra & Ds, 2012). For population that are larger, Cochran (1963:75) developed the equation to yield a representative sample for proportions i.e n0 = Z2pq/e2 Where n0 is the sample size, Z2 is the abscissa of the normal curve that cuts off an area α at the tails (1 – α equals the desired confidence level, e.g., 95%), e is the desired level of precision, p is the estimated proportion of an attribute that is present in the population, and q is 1-p. The value for Z is found in statistical tables which contain the area under the normal curve. During 2017-18 and As per SIAM report 2, 49, 72,788 vehicles were sold and passenger vehicles were sold 32, 87,965 which is 13% (32, 87,965 / 2, 49, 72,788 * 100 =13.16) of the total vehicle sales and we assumed the vehicle sales at Odisha too in the same proportion and hence we calculated our n0 based on the aboveformula.

n0 = Z2pq/e2
n0 = (1.96)2 * (.13)(.87) / (0.05)2
n0 = (3.8416) * (.1131) / (0.0025)
n0 = .43448496 / .0025
n0 = 173.793984
n0 = 173 minimum responses

1.7 The choice of scale

The literature in this study was used as a guideline for the development of the statements in the questionnaire. My research questions comprises of 4 Variables for Customer satisfaction constructs which was measured in 7 point Likert scale where 1 represents Strongly Agree and 7 represents Strongly disagree and is considered as interval scale (Malhotra, N. K., & Dash, S. (2007)

1.8 Reliability of constructs post pilot test

The reliability of construct is .861 for our construct Brand Choice. Reliability is considered acceptable when Cronbach’s alpha meets or exceeds 0.700.

1.9 Statistical tools and techniques used for data analysis Frequency distribution, Percentage, Leven’s test, T-Test , Cohen’s D , Welch, 1 way ANOVA, Tucky , Omega Square W2, and Games Howell, Mean Plot 1.10 Descriptive analysis of sample The demographic factors have an effect on the customer or prospects behaviour or demographic variables are used to categorize the population parameter into divergent groups. As the choice of preference of consumer differs on the basis of demographic characteristics like age, gender, income, occupation, education, social class etc. the study of demographic factor is essential in segmenting, targeting ad positioning the automotive products. Keeping this in view, the researcher attempted to make a demographic analysis, as these variables are the most popular tools, used in distinguishing customer groups. The consumer demographics studied in the research are gender, age, marital status, social class, education, employment status, family size, income level. Table 1 depicts a sample profile studied for the current research.

Table 1: Sample Profile

Characteristics	Category	Frequency	percentage
Gender	Male	239	74.7
	Female	81	25.3
Age	18-25	24	7.5
	26-35	173	54.1
	36-45	70	21.9
	46 & above	53	16.6
Occupation	Government	161	50.3
	Private	85	26.6
	Self-Employed	47	14.7
	Professional	27	8.4
	Others	0	0
Marital Status	Married	224	70
	Un-Married	96	30
Family Size	1-5	278	86.9
	6-10	35	10.9
	11 & More	7	2.2
Income Level	< 5 Lakhs	71	22.2
	6-10 Lakhs	115	35.9
	11-15  Lakhs	95	29.7
	>16 lakhs	39	12.2
Academic Background	School Education	5	1.6
	Graduate	97	30.3
	PG	160	50
	Professional Degree	58	18.1
Social Class	Middle Class	186	58.1
	Upper Middle Class	119	37.2
	Rich / Affluent	15	4.7

.11 Perceptual difference & Brand Choice

This study will talk about Brand Choice and its perceptual difference with our 8 demographic variables named Gender, Age group, Occupation, Marital Status, Family Size, Income level, Academic Background, and Social class.

Table 2: Perceptual difference of identified construct across Gender (Demographic)

Independent samples T-Test
		Levene's Test for Equality of Variances		t-test for Equality of Means			Cohen’s d	Result
		F	Sig.	t	df	Sig. (2-tailed)
BC	Equal variances assumed	2.213	.138	-.268	318	.789	-0.034304 Negative	Non-Significant
	Equal variances not assumed			-.249	122.732	.804
	Equal variances not assumed			.082	123.631	.935

The Male group (N=239) was associated with Brand Choice M = 2.8249 (SD = .95099). By comparison the Female group (N=81) was associated with a numerically smaller difference in Brand Choice M= 2.8591 (SD = 1.10345). To find out the Mean perceptual difference across gendertoward Brand choice, an independent sample T Test was performed. As can be seen on Table 1.11.1, the male and female distributions were sufficiently normal for the purpose of conducting T-test (i.e., Skew < 2.0 and Kurtosis < 9.0; Schmider, Ziegler, Danya, Beyer, & Buhner, 2010). Additionally, the assumption of homogeneity of variance was tested and satisfied via Leven’s F test (The Levene's test uses an F-test to test the null hypothesis that the variance is equal across groups. A p value less than .05 indicates a violation of the assumption, Levene 1960) F (318) = 2.213, p =.138 the independent sample T-test was associated with a statistically non-significant effect, t (318) = -.268, p= .789. Thus the perception of male and female were not statistically significant towardsBrand choice hence the null hypothesis “H1a: There is no perceptual difference towards Brand Choice across Gender” was accepted. Cohen’s d (d = t ) was estimated at -0.034304 , which is negative in its effect which means the effect is actually working against our independent variable by decreasing the mean value (based on Cohen’s ,1992 guideline small = .20, medium =.50 & large = .80)

Table 3: Perceptual difference of identified construct across Age (Demographic)

Construct	Levene’s Test		Result	Welch	Result	Games Howell
	F	Sig
BC	9.906	.000	Variance not assumed	.276	Not Significant	No diff

A one-Way ANOVA between groups ANOVA was performed to compare the impact of age on Brand Choice. Respondents are divided into four age groups based upon their age (Group 1: 18-25 years, Group 2: 26-35 Years, Group 3- 36-45 Years and Group 4- 46 years & above). The outcome variable was found to be normally distributed but equal variance not assumed based upon the results of Leven’s test (The Levene's test uses an F-test to test the null hypothesis that the variance is equal across groups. A p value less than .05 indicates a violation of the assumption, Levene 1960) F (3, 316) = 9.906, p = .000003. As we can see from table 1.11.2 this test says that Age and Brand choice are violating the assumption hence instead of 1 way ANOVA we need to conduct Welch test which confirm that there is no statistical difference between Age &Brand choice F (3, 88.808) = .1.311, P = .276. Thus the null hypothesis is accepted “H1b: There is no difference between age and Brand Choice.

Table 4: Perceptual difference of identified construct across Income Level (economics)

Construct	Levene’s Test		Result	1 way ANOVA		Result	Tucky	Effect size (w2)
	F	Sig		F Test	Sig
BC	.362	.781	Equal variance assumed	.762	.516	Not Significant	No difference across group	.002

A one-Way ANOVA between groups ANOVA was performed to compare the impact of Income level on Brand Choice. Respondents are divided in Four Income level groups based upon their age (Group 1: < 5 Lakh, Group 2: 6-10 Lakh Group 11-15 Lakh and Group 4- > 16 Lakh). The outcome variable was found to be normally distributed and the assumption of homogeneity of variance was tested and satisfied via Leven’s F test (The Levene's test uses an F-test to test the null hypothesis that the variance is equal across groups. A p value less than .05 indicates a violation of the assumption, Levene 1960) F (3, 316) = .362p = .781As we can see from table 1.11.3 this test says that Income level on Brand Choice are not violating the assumption After meeting the assumption of ANOVA we run the ANOVA test report says that there is no statistical difference between Income level on Brand Choice F (2, 317) = .762, P = .516. Thus the null hypothesis accepted “H20: There is no difference between income level and Brand choice To test the effect size we conducted Omega squared (ω2) is a descriptive statistic used to quantify the strength of the relationship between a qualitative explanatory (independent or grouping) variable and a quantitative response (dependent or outcome) variable. The relationship is interpreted in terms of the proportion of variation in the response variable that is associated with the explanatory variable. As a proportion, it can have values between 0 and 1, with 0 indicating no relationship and 1 indicating that all of the variation in the response variable is attributed to the explanatory variable. Omega squared is used as an effect-size index to judge the meaningfulness of the observed relationship identified using the analysis of variance F test. It can supplement the results of hypothesis tests comparing two or more population means. We calculated W2 = SSB- (dfB)* MSW / SST + MSWand we found the effect is -.002 which says that practically on ground there are no effect at all of Income level on Brand choice and after conducting Tucky test to found is there no difference across group.

Table 5: Perceptual difference of identified constructs across Marital Status (Societal)

		Levene's Test for Equality of Variances		t-test for Equality of Means			Cohen’s d		Result
		F	Sig.	t	df	Sig. (2-tailed)
BC	Equal variances assumed	3.763	.053	.759	318	.448		3.45345 small	Non-Significant
	Equal variances not assumed			.839	229.024	.402

The Married group (N=224) was associated with Brand Choice M = 2.8611(SD = 1.05555). By comparison the Un-Married group (N=96) was associated with a numerically smaller difference in Brand Choice M= 2.7693 (SD = .81880). To find out the mean perceptual difference that Married & Unmarried were associated significantly towards Brand Choice, an independent sample T Test was performed. As can be seen on Table 1.11.4, the Married & un-Married distributions were sufficiently normal for the purpose of conducting T-test (i.e., Skew < 2.0 and Kurtosis < 9.0; Schmider, Ziegler, Danya, Beyer, & Buhner, 2010). Additionally, the assumption of homogeneity of variance was tested and satisfied via Leven’s F test (The Levene's test uses an F-test to test the null hypothesis that the variance is equal across groups. A p value less than .05 indicates a violation of the assumption, Levene 1960) F (318) = 3.763, p = .053. The independent sample T-test was associated with a statistically non-significant effect, t (318) = .759, p= .448. Thus the perception of Married and Unmarried were not statistically significant towards Brand Choice hence the null hypothesis “H3a: There is no perceptual difference towards Brand choice across married & unmarried” was accepted. Cohen’s d (d = t ) was estimated at 3.45345, which means the effect size is small (based on Cohen’s, 1992 guideline small = .20, medium =.50 & large = .80)

Table 6: Perceptual difference of identified constructs across Occupation (Societal)

Construct	Levene’s Test		Result	Welch	Result	Games Howell
	F	Sig
BC	1.497	.215	Variance Not assumed	.001	Significant	Difference exist across group

A one-Way ANOVA between groups ANOVA was performed to compare the impact of occupation on Brand Choice. Respondents are divided into four occupation groups based upon their age (Group 1: Government, Group 2: Private, Group 3- Self-Employed and Group 4- Professional). The outcome variable was found to be normally distributed but equal variance not assumed based upon the results of Leven’s test (The Levene's test uses an F-test to test the null hypothesis that the variance is equal across groups. A p value less than .05 indicates a violation of the assumption, Levene 1960) F (3, 316) = 1.497, p = .215. As we can see from table 1.11.5 this test says that occupation and Brand Choice are violating the assumption hence instead of 1 way ANOVA we need to conduct Welch test which confirm that there is statistical difference between occupation and Brand Choice F (3, 99.971) = 5.786, P = .001 . Thus the null hypothesis is not accepted “H3b: There is no difference between occupation and Brand Choiceand Games Howell test also concluded that there are difference across government and professional.

Table 7: Perceptual difference of identified construct across Family Size (Societal)

Construct	Levene’s Test		Result	1 way ANOVA		Result	Tucky	Effect size (w2)
	F	Sig		F Test	Sig
BC	2.476	.086	Equal variance assumed	3.735	.025	Significant	Difference across group	.016

A one-Way ANOVA between groups ANOVA was performed to compare the impact of Family Size on Brand Choice. Respondents are divided into threeFamily Size groups based upon their age (Group 1: 1-5, Group 2: 6-10, and Group 3- 11 & more). The outcome variable was found to be normally distributed and the assumption of homogeneity of variance was tested and satisfied via Leven’s F test (The Levene's test uses an F-test to test the null hypothesis that the variance is equal across groups. A p value less than .05 indicates a violation of the assumption, Levene 1960)F (2, 317) =2.476p = .086As we can see from table 1.11.6 this test says that Family Size on Brand Choice are not violating the assumption After meeting the assumption of ANOVA we run the ANOVA test report says that there is no statistical difference between Family Size on Brand ChoiceF (2, 317) = 3.735, P =.025. Thus the null hypothesis is not accepted the hypothesis “H3c: There is no difference between Family size and Brand choice. To test the effect size we conducted Omega squared (ω2) is a descriptive statistic used to quantify the strength of the relationship between a qualitative explanatory (independent or grouping) variable and a quantitative response (dependent or outcome) variable. The relationship is interpreted in terms of the proportion of variation in the response variable that is associated with the explanatory variable. As a proportion, it can have values between 0 and 1, with 0 indicating no relationship and 1 indicating that all of the variation in the response variable is attributed to the explanatory variable. Omega squared is used as an effect-size index to judge the meaningfulness of the observed relationship identified using the analysis of variance F test. It can supplement the results of hypothesis tests comparing two or more population means. We calculated W2 = SSB- (dfB)* MSW / SST + MSWand we found the effect is .016which says that practically on ground there are no effect at all of Family Size on Brand choiceand after conducting Tucky test to found is there any difference across group we found that there are difference across group mostly between Nuclear Family and joint family, however there are no such huge difference between family size of 6-10 and 11 & more.

Table 8: Perceptual difference of identified construct across Education (Societal)

Construct	Levene’s Test		Result	Welch	Result	Games Howell
	F	Sig
BC	3.065	.028	Equal variance not assumed	.334	Not Significant	No difference across group

A one-Way ANOVA between groups ANOVA was performed to compare the impact of Education on Brand Choice. Respondents are divided in Four Income level groups based upon their age (Group 1: School Education, Group 2: Graduate, Group3: Post Graduate and Group 4: Professional Degree). The outcome variable was found to be normally distributed and the assumption of homogeneity of variance was tested and satisfied via Leven’s F test (The Levene's test uses an F-test to test the null hypothesis that the variance is equal across groups. A p value less than .05 indicates a violation of the assumption, Levene 1960)F (3,316) = 3.065 p =.028. As we can see from table 1.11.7 this test says that Education on Brand Choice are violating the assumption hence instead of 1 way ANOVA we need to conduct Welch test which confirm that there is no statistical difference between Education Level on Brand ChoiceF (3, 18.916) = 1.209, P = .334 .Thus the null hypothesis is accepted “H3d: There is no difference between Education and Brand choice and Games Howell test concluded that there are no difference across group.

Table 9: Perceptual difference of identified constructs across Social class (Societal)

Construct	Levene’s Test		Result	Welch	Result	Games Howell
	F	Sig
BC	6.394	.002	Equal variance not assumed	.945	Not Significant	No difference across group

A one-Way ANOVA between groups ANOVA was performed to compare the impact of Social class on Brand Choice. Respondents are divided in three groups based upon their class (Group 1: Middle class, Group 2: Upper-Middle class, and Group3: Rich/Affluent). The outcome variable was found to be normally distributed and the assumption of homogeneity of variance was tested and satisfied via Leven’s F test (The Levene's test uses an F-test to test the null hypothesis that the variance is equal across groups. A p value less than .05 indicates a violation of the assumption, Levene 1960)F (2,317) = 6.394 p =.002. As we can see from table 1.11.8 this test says Social class on Brand Choice are violating the assumption hence instead of 1 way ANOVA we need to conduct Welch test which confirm that there is no statistical difference between Social class on Brand Choice F (2, 44.207) = .057, P = .945 Thus the null hypothesis is accepted “H3e: There is no difference between Social class & Brand Choice” and Games Howell test concluded that there is no difference across group.

Table 10: Results and Discussions

SLNO	Hypotheses	Result
H1	There is an association between demographic characteristics of consumers and Brand Choice on purchased cars.	Not supported
H1a	There is no perceptual difference towards Brand Choice across Gender.	Null Hypothesis accepted
H1b	There is no difference between age and Brand Choice.	Null Hypothesis accepted
H2	There is an association between economic characteristics of consumers and Brand Choice on purchased cars.	Not supported
H20	There is no difference between income level and Brand Choice.	Null Hypothesis accepted
H3	There is an association between Societal characteristics of consumers and customer satisfaction on purchased cars.	Partially Supported
H3a	There is no perceptual difference towards Brand Choice across married & unmarried.	Null Hypothesis accepted
H3b	There is no difference between occupation and Brand Choice.	Null Hypothesis not  accepted
H3c	There is no difference between Family size and Brand Choice.	Null Hypothesis not accepted
H3d	There is no difference between Education and Brand Choice.	Null Hypothesis accepted
H3e	There is no difference between Social class &Brand Choice.	Null Hypothesis accepted

Buttle 1992; Otnes and McGrath 2001; and Hernández et al. 2011 beforehand suggested thatGender and Brand choice are related however my sample study is not supporting their findings and it says Gender and Brand choice is not related to each other. Kotler et al. 2001; Anderson, S. T., Harrison and Rainer Jr 1992; Anderson, S. T., Kellogg, R., Langer, A., &Sallee, J. M.,2013 explored and found that there is a solid relationship amongst age and brand decision however our study couldn’t able to find out any statistical significance of Age and brand choice. Occupation is one of the extensive components (Ahuja 2011; Onyeagwara, C. An., Agu, G. An., and Aja, E. E. ,2019) and it is also supported in our study too and we found that Occupation and Brand choice is statistically significant.Studies like LeClerc, Schmitt, and Dube, 1994; Mohamad, Ahmed, Honeycutt Jr., and Tyebkhan, 2000 says that Family size and brand choice are related and our research is also supporting the above findings & we can say in our study that family size and Brand choice are statistically significant. Level of education affect customer to buy distinctive brands of decision (Kotler et al. 2001) but our study is showing that there is no statistical significance between education & Brand Choice. Studies like (Yalcin, 2005 ; Onyeagwara, C. An., Agu, G. An., and Aja, E. E. ,2019 ) mentioned Salary influences the significance of inclinations for various sustenance characteristics however our study is not supporting the above authors study and we conclude by saying this in our research income & brand choice are not statistically significant.Onyeagwara, C. An., Agu, G. An., and Aja, E. E. (2019) in his examinations found that Marital status is critical in selection of brands and spot of purchasing but in our study we didn’t find any statistical significance between Marital status & Brand choice. Cuneo, Our study is also not supporting current study of A., Milberg, S. J., del Carmen Alarcon-del-Amo, M., and Lopez-Belbeze, P. ,2019 who bolsters that social class influences selection of brands.

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