implications of confounding variables on rural purchaser’s

Implications of Confounding variables on Rural Purchaser’s Brand

predilection

Prof. Dr. K. Ajay Singh*

School of Management, IMS Unison University, Dehradoon

[email protected]

Akansha Madan⃰

Research Scholar, School of Management, IMS Unison University,

Dehradoon

[email protected]

Abstract

The purpose of this study is to demonstrate the power of the purchaser's intended commodity

attributes along with the lifestyle factors that induce him/ her to buy shampoos and how he / she

correlates a product's utility to its intrinsic value. The contemporaneous research is envisaged to

explore consumer’s brand predilection and uncover the phenomenon of intended commodity

attributes intended by the purchaser regarding emblazoned shampoos in rural regions of

Saharanpur zone. This is an enviable work that aims to analyze data on demographic

characteristics, brand predilection and factors influencing purchaser's intended commodity

attributes to buy emblazoned shampoos in rural regions. It is intended to evaluate the influence

of demographic variables on factors influencing the purchaser's intended commodity attributes of

emblazoned shampoos and inturn its relationship with consumer brand predilection. The dataset

is obtained from 1016 individuals. The research methodology consists of Principal Component

Factor Analysis with Varimax rotation, One-way Manova and Multiple Regression Analysis.

Keywords: Marketing, Rural Marketing, Consumer Purchase behaviour, Principal

Component Factor Analysis, Manova, Multiple Regression Analysis

WAFFEN-UND KOSTUMKUNDE JOURNAL

Volume XI, Issue VIII, August/2020

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Introduction

Rural buyer uses two key differentiators of rationale to justify their purchase decisions; logical

and psychological. Considerations pro and con rendering the acquisition may slide into one

classification or another, or they may drift through both categories. Decision makers in rural

merchandising ought to understand their commodity, and why someone buys it from them.

Psychological motivations mostly overshadow logical motives. For instance, the user is likely to

come back to the retailer they previously used despite this retailer billing more than others. That

is because they perceive the business’s trust and loyalty given previous service delivery and

customer support.

Creating this personal connection between the business and the buyer is essential for

guaranteeing that they stick to the business, as well as promoting the business to relatives and

friends across word of mouth, etc. It’s quite important to consider where the buyers prefer to buy

from to make the right promotional choices.

Organizations who wish to build a place in the rustic domain need to understand what the

suburban consumer wants. With the assistance of data analytics developed by rural research

specialists, their propensity and consumption-related actions should be premeditated in detail.

Organizations have to deliver quality goods and services to people in rural areas by delving

deeply into the product offerings that rustic consumers expect. They will ensure that the goods

achieve the requisite specifications and are designed in compliance with rural constraints. The

essential components that rural consumers want, including good value and reliable product

quality, must be provided. Purchaser awareness is the beginning of a great promotional

campaign. They may not have much to do from selling to a target audience that they don't really

comprehend; surely the best way to access and communicate with a client is to consider their

shopping orientation.

Consequently, industry groups are already focusing on discerning rural buyers' mind frame and

proclivities. They have been exceedingly focusing their resources on expanding approaches of

engagement to attract these buyers. Enterprises that have succeeded in scaling their hinterland

systems are gradually implementing the 4As of rural targeting to establish a brawny presence in

India.



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Literature review

Commodities purchased by consumers over lifecycle can be classified into segments in

conformance with defined parameters. This article reveals that by implementing a clustered

methodology to commodity items, business model can be rendered quite successful. A

framework for identifying buyer durables attribute sets and buyer preference trends relevant to

their procurement is illustrated. There are various facets of the buyer's expectations of the

regularity of the trade and the value of the agreement. Firstly, to explain how buyers build and

use these preconceptions, a theoretical framework is portrayed. Secondly, the findings of a

comprehensive survey are then used to measure the degree of competence of buyers regarding

the current volume of transactions and the value of transactions. Thirdly theories are being

examined on what kind of shoppers has detailed knowledge of offers. Findings show that many

consumers are remarkably accurate with respect to the duration of the offer and the value of the

transaction. Moreover, the return on transaction frequency and selling price is higher for

shoppers with huge family size as well as those who browse regular brochures of stuff on sale,

devote more resources on product impulse purchases of the particular brand, and eventually buy

the package size consistently, . For elderly customers, it's lower. While sellers traditionally relied

on urban areas where rivalry has indeed enhanced, they are spreading their trade in rural regions

as a result of massive appetite for FMCGs among rural communities. Marketing people have

discovered new approaches to reach the rural sector in order to facilitate their continued

existence. The rural business founder in India was HUL. Analytical research found that a typical

rural family usually spends 60% of their monthly income on food. Rural dwellers considered

packaging to be more worthwhile in purchasing commodities. They believed improved wrapping

encompasses a superior product, and they were more swayed by the convenience of storage.

Seller consumer dependency is a strange occurrence that is noticeable even nowadays in India's

rural settings. User reliance is a mutual relationship building measure and plugs an obvious void

in client attachment study within the relational customer-seller partnership. The behavioural

parameter of buyer choice-making mechanism cross-sectional analysis indicates that presumed

time pressure had negligible effect while buying opinion stewardship and identity-confidence

browsing had a significant impact. The responsiveness of consumerism and buyers to emotional



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manipulation had a mild effect. Alterations in choice-making modes portray that buyers have

become more cognizant of brand and style whereas in their shopping they are more impetuous

and callous. Price, brand, efficiency, accessibility, positioning, etc. were important factors in

determining the buying decisions of the countryside buyer. The critical factors involving FMCG

items' regarding rural buying inclination are strong communication methods, justifications for

brand flipping, payment habits, and degree of satisfaction among rural buyers. Channels used for

advertisement or brand recognition vary across occupational groups. Grocery transactions are

often on credit contrary to what has been commonly assumed. Consumers are at most prepared to

travel 12 km to buy perishables. The rate of consumption is not poor, but small discretionary

income contributes to small-scale transactions and creative selling activities carried out by

industries in rural regions, while meeting the determinants of visibility and knowledge, are

impacted by issues related to cost effectiveness and accessibility, which function as impediments

for rural buyers. For a multitude of reasons people are resistant for new products, but the primary

is inability to change culturally ingrained ideologies and habits. The greater the experimentation,

the stronger the unrest, and several companies see intense novelty in people with minimal

resources and limited product knowledge. To attract small-income consumers, value systems

might have to be reprogrammed. Consumers may need reduced price ranges than they would

achieve with the business. They need to improve the particular product’s short-term adoption while

reinforcing the corporate image in an up-and-coming millennial consumer market. While base-of -

the-pyramid buyers buy commodity iteration via the same networks as contemporary users, the

business might augment the commodity to satisfy special needs and increase the overall business

model. E-commerce marketing statistics could disclose which customer categories have the

highest preference for a specific company's products. India also has a relatively significant

number of subscribers of digital media. Multinationals may use digital channels such as

Facebook and Whats App to create trustworthy communities. Virtual property, browser tools,

business analytics, and Western-perfected social media management tactics can easily be

customized to the Indian economy. Willingness of BOP consumers to guide and embrace new

products is very restricted. They also discovered that impoverished shoppers are coping with

their lower self-efficacy due to reduced rates of workable reading and writing, exploiting their

social networks to obtain and interpreting numerous substantial metaphorical indications of the

business. Three classes of buyers (loyalists/ rational/ opponents of marketing strategy) were



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analysed and it has been noticed that there is a substantial correlation amongst loyalists/ rational/

opponents in terms of age, sex, profession, and income level, apart from schooling and

proximity. Apart from celeb experience and credibility, the qualities assessed demonstrated a

productive relationship with purchasing purpose. Value coherence directly impacts consumer –

brand identity (CBI), cognitive brand engagement and user – brand engagement (CBE), that in

turn effect the way for evolving consumer-brand connections as assessed by customer loyalty. It

optimized established perspective into the mechanics of customer interaction, with special

emphasis on models of hospitality. The measurements proposed value coherence within

hospitality offerings as an impactful driver of CBI, cognitive engagement, and CBE. CBI serves

as a powerful indicator of emotional engagement, CBE and brand allegiance. Industry is

experiencing a phenomenon in which consumers move from shopping behaviours to organic

formulations from synthetic or chemical-based formulations. The research showed a strong

connection of natural formulations amongst age, family and education with frequency of

purchase. The findings indicated that the overall impact of Marketing, Features, Value of

Acquiring and Repudiation affected aromatic formulations’ purchasing inclination. Lifestyle

factors along with social power, behaviour development, inner experience, emotions and

awareness, and interactivity facilitate a shift in the disposition of viable buyers.

Objectives of the study

1. To analyze dependence of factors effecting purchaser's intended commodity attributes of

branded shampoos on age in rural markets of district Saharanpur.


branded shampoos on gender in rural markets of district Saharanpur.


branded shampoos on education in rural markets of district Saharanpur.


branded shampoos on family income in rural markets of district Saharanpur.

5. To determine the association between factors affecting purchaser's intended commodity

attributes and brand predilection of rural people with reference to branded shampoos.



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Hypothesis of the study

1. There is significant difference between factors affecting purchaser's intended commodity

attributes across age with reference to branded shampoos.


attributes between people belonging to different genders with reference to branded

shampoos.


attributes between people belonging to different education levels with reference to

branded shampoos.


attributes between people belonging to different family income categories with reference

to branded shampoos.

5. There is significant relationship between factors affecting purchaser's intended

commodity attributes and brand predilection of rural people with reference to branded

shampoos.

Research Methodology

This analysis is an attempt to explore the nature of the product attributes intended for branded

shampoos by rural buyers. To elicit responses from rural participants, a well-defined and

organized questionnaire was designed. The measurement tool used in this research used Likert

scale to extract.

The fieldwork is carried out in the surveyed communities of Saharanpur district (as per the

concept of rural dwelling census) as Saharanpur's rural community is a robust sector with nearly

2400,000 massive population and rural people's earnings is also requisite to allow them to sustain

a decent life and they have considerable appetite for FMCG branded items. Stratified Random

Sampling technique is utilized.

The analysis of the research used includes:



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1. Principal Component Factor Analysis (PCA),

2. One-way Manova to examine the variance in demographic variables such as age, gender,

family income, and education in these factors.

3. Multiple regression analysis to determine the association between factors affecting

purchaser's intended commodity attributes and buyer's brand predilection.

Data Analysis

The primary data was analyzed through SPSS package version 21.0 by IBM.

(See Table-1) The total explained variance of phenomenon in case of shampoo is 64.811 (.50),

wherein explained variance of component 1 – Influence factor is 32.785 , explained variance of

component 2 – Psychological factor is 20.621 and explained variance of component 3 – Value

factor is 11.405.

(See Table-2) The reliability of factors affecting purchaser's intended commodity attributes is

tested using cronbach’s alpha whose number of items was 13 and values were found to be .827

for shampoo which were found to be higher than the minimum criteria of .70. The factors that

are best able to explain the selected constructs are identified with the help of Principal

Component Analysis (PCA), wherein the reliability of each measurement scale resulting after

realizing PCA has been verified. The checking of the scales validity and reliability was

performed by means of an iterative process, which provided all values higher than the minimum

threshold viz. KMO test (>.5), Barlett’s test of sphercity (<.005). Eigenvalue is taken to be

greater than 1. The approx. chi-square value of factors affecting purchaser’s intended commodity

attributes of shampoo was found to be 3608.932 with 78 degrees of freedom and significance (<

.005).

(See Figure-1) The first three principal components have eigenvalues greater than 1. These

components explain 64.811% of the variation in the data. It reveals that the eigenvalues start to

form a straight line after the third principal component. Therefore the remaining principal



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components account for a very small proportion of the variability (close to zero) and are

probably unimportant.

Multivariate Analysis on factors affecting purchaser's intended commodity attributes

Statistical Power of MANOVA Tests

H1: There is significant difference between factors affecting purchaser's intended

commodity attributes across age with reference to shampoos.

Fixed Factor – Age

Dependent variable- Factors affecting purchaser's intended commodity attributes

(See Table-4) Out of 679 respondents, who use shampoo 335 respondents are less than 20 years

old, 209 respondents are between 20 and 40 years old, 115 respondents are more than 40 years

old. .

(See Table-5) Box’s Test of Equality of Covariance Matrices tests the assumption that the

dependant variable covariance matrices are equal across the levels of the independent variable

(age). The above table shows that the Box’s M is statistically significant (<.001) in case of

shampoo and the assumption that observed covariance matrices of the dependant variables are

equal across the groups, has apparently not been met. In this case outcome based on Pillai’s trace

is the most conservative thing to do but the value of factors affecting purchaser's intended

commodity attributes is statistically significant (p < .001) based on all four indexes.

(See Table-6) Bartlett’s Test of Sphercity determines if the correlations between the dependent

variables are sufficiently strong to support the MANOVA. A statistically significant outcome

indicates that the correlations are sufficient. The above table shows that the approximate chi-

square = 222.657 in case of shampoo and. The value of Bartlett’s Test of Sphercity is statistically

significant (p < .001) in case of shampoo.

(See Table-7) The analysis of one way multivariate analysis of variance showed that the age of

rural purchasers had an effect on the combined factors affecting purchaser's intended commodity

attributes for shampoos in rural markets of district Saharanpur.



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The Wilks’ lambda of shampoo (.336) measures the percent of variance in the age that is not

explained by the difference in factors influencing purchase orientation towards shampoo and

subtracting that value from 1.00 gives a sense of the strength of the age effect ( a multivariate

analog of Eta square). In this analysis, 1 - .336 = .664, and so it appears that age explained

approximately 66.4% of the variance of the discriminant score variable factors affecting

purchaser’s intended commodity attributes i.e. influence factors, psychological factors and value

factors. The effect size (.420) was found to be medium. The results showed that there was a very

strong power (1.000) which had predicted the strength of the relationship between the age and

factors influencing purchase orientation. The results have further shown that F-value was

158.097 and the P-value was significant at .05 percent level.

Hence, null hypothesis is rejected and alternate hypothesis is accepted that there is

significant difference between factors affecting purchaser's intended commodity attributes

with reference to age. It was postulated that stage of lifecycle of the respondents

significantly impact their intended attributes towards shampoos.

(See Table-8) Levene’s test of homogeneity of variance presents statistical significance results

for influence factors, psychological factors and value factors in case of shampoo (< .05). It

indicates that influence factors, psychological factors and value factors demonstrate hetrogeneity

of variances. Hence, Tamane’s T2 post hoc tests are examined for these variables. Thus, we will

increase the stringency of our revised alpha level beyond the Bonferroni level when evaluating

the univariate effects (.05/3 = .017).

(See Table-9) The ANOVA on the “influence factors” was significant, F (2,656) = 96.584 > (F-

table), p <.01 while the ANOVA on the “Psychological factors” was significant, F (2,656) =

108.818 > (F-table), p <.01 and the ANOVA on the “Value factors” was also significant, F

(2,656) =75.687 > (F-table), p < .01. Hence, age had a major effect on all three factors affecting

purchaser’s intended commodity attributes of shampoo namely, influence, psychological factors

and value factor at 10% level of significance.

Post-hoc tests



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Since the Levene’s test has revealed a statistically significant result for influence, psychological

and value factors, the post-hoc analysis has been made with respect to Tamhane’s T2 test. It was

found that all the three groups <20, 20-40 and >40 differ from each other on each of these

measures.

H2: There is significant difference between factors affecting purchaser's intended

commodity attributes between people belonging to different genders with reference to

shampoos

Fixed Factor - Gender

Dependent variable - Factors affecting purchaser's intended commodity attributes

(See Table-10) Out of 659 respondents who use shampoo, there are 19 transgender respondents,

289 male respondents and 351 female respondents.

(See Table-11) Box’s M is statistically significant (<.001).

(See Table-12) The above table shows that in case of shampoo approximate chi-square = 36.371.

The value of Bartlett’s Test of Sphercity is statistically significant (p < .001).

(See Table-13) The analysis of one way multivariate analysis of variance showed that the gender

of rural purchasers had an effect on the combined factors affecting purchaser's intended

commodity attributes for shampoos in rural markets of district Saharanpur.

The Wilks’ lambda of shampoo (.657) measures the percent of variance in the gender that is not

explained by the difference in factors affecting purchaser's intended commodity attributes

towards shampoo and subtracting that value from 1.00 gives a sense of the strength of the gender

effect ( a multivariate analog of Eta square). In this analysis, 1 - .657 = .343, and so it appears

that gender explained approximately 34.3% of the variance of the discriminant score variable

factors affecting purchaser's intended commodity attributes on i.e. influence factors,

psychological factors and value factors. The effect size (.189) was found to be medium. The

results showed that there was a very strong power (1.000) which had predicted the strength of the



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relationship between the gender and factors affecting purchaser's intended commodity attributes.

The results have further shown that F-value was 50.918 and the P-value was significant at .05

percent level.


significant difference between with reference to gender. It was postulated that gender of the

respondents significantly impact their intended attributes towards shampoos.


for influence factors and value factors but not for psychological factors in case of shampoo (<

.05). It indicates that influence factors and value factors demonstrate hetrogeneity of variances.

Hence, Tamane’s T2 post hoc tests are examined for these variables. But psychological factors

demonstrate homogeneity of variances. Hence, R-E-G-W-Q test or Ryan-Enoit-Gabriel-Welsch

Studentized Range test which assumes equal variances was used in respect of psychological

factors. Thus, we will increase the stringency of our revised alpha level beyond the Bonferroni

level when evaluating the univariate effects (.05/3 = .017).

(See Table-15) The ANOVA on the “influence factors” was significant, F (2,656) = > 52.046 (F-

table), p <.01 while the ANOVA on the “Psychological factors” was significant, F (2,656) =

54.926 > (F-table), p <.01 and the ANOVA on the “Value factors” was also significant, F (2,656)

= 21.920 > (F-table), p < .01. Hence, gender had a major effect on all three factors affecting


and value factor at 10% level of significance

Post-hoc tests

Since the Levene’s test has revealed a statistically significant result for influence factors and

psychological factors, hence, the post-hoc analysis has been made with respect to Tamhane’s T2

test. It was found that transgender and male group did not differ significantly on influence and

value factors, while female group is more open than either the transgender or male group. R-E-



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G-W-Q post-hoc tests are used for psychological factor, which revealed that all the three groups-

transgender, male and female differ from each other on psychological factor.

H3: There is significant difference between factors affecting purchaser’s intended

commodity attributes between people belonging to different education level with reference

to hair care products.

Fixed Factor-Education

Dependent variable- Factors affecting purchaser’s intended commodity attributes

(See Table-16) Out of 659 respondents who use shampoo, there are 143 illiterate respondents,

326 respondents who are educated less than high school level and 190 respondents who are

educated more than high school level.

(See Table-17) Box’s M is statistically significant (<.001).

(See Table-18) The approximate chi-square is in case of shampoo 300.934 respectively. The

value of Bartlett’s Test of Sphercity is statistically significant (p < .001).

(See Table-19) The analysis of one way multivariate analysis of variance showed that the

education of rural purchasers had an effect on the combined factors influencing purchasers’

purchase orientation for hair care products in rural markets of district Saharanpur.

The Wilks’ lambda of shampoo (.276) measures the percent of variance in the education that is

not explained by the difference in factors influencing purchase orientation towards shampoo and

subtracting that value from 1.00 gives a sense of the strength of the education effect ( a

multivariate analog of Eta square). In this analysis, 1 - .276 = .724, and so it appears that

education explained approximately 72.4% of the variance of the discriminant score variable

factors affecting purchaser’s intended commodity attributes i.e. influence factors, psychological

factors and value factors. The effect size (.475) was found to be medium. The results showed that

there was a very strong power (1.000) which had predicted the strength of the relationship

between the education and factors influencing purchase orientation. The results have further

shown that F-value was 197.240 and the P-value was significant at .05 percent level.



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significant difference between factors affecting purchaser’s intended commodity attributes

with reference to education. It was postulated that level of education of the respondents

significantly impact their intended attributes towards shampoos.


for influence factors and value factors in case of shampoo (< .05) but not for psychological

factors. It indicates that influence factors and value factors demonstrate hetrogeneity of

variances, while psychological variables demonstrate homogeneity of variances. Hence,

Tamane’s T2 post hoc tests are examined for influence and value variables and R-E-G-W-Q

post-hoc tests for psychological variables. Thus, we will increase the stringency of our revised

alpha level beyond the Bonferroni level when evaluating the univariate effects (.05/3 = .017).


table), p <.01 while the ANOVA on the “Psychological factors” was significant, F (2,656) = >

137.538 (F-table), p <.01 and the ANOVA on the “Value factors” was also significant, F (2,656)

= 91.703 > (F-table), p < .01. Hence, education had a major effect on all three factors affecting


and value factor at 10% level of significance.

Post-hoc Tests

Since the Levene’s test has revealed a statistically significant result for influence and value

factors, the post-hoc analysis has been made with respect to Tamhane’s T2 test. It was found

that all the three groups- illiterate, less than highschool pass and more than highschool pass

differed from each other on each of these measures. Psychological factor did not reveal a

statistically significant result and demonstrated homogeneity of variance. R-E-G-W-Q post-hoc

tests revealed that all the three groups- illiterate, less than highschool pass and more than

highschool pass differed from each other on psychological factor.



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H4: There is significant difference between factors affecting purchaser’s intended

commodity attributes between people belonging to different family income with reference

to hair care products.

Fixed Factor – Family income

Dependant variable – Factors affecting purchaser’s intended commodity attributes

(See Table-22) Out of 679 respondents, who use shampoo, family income of 107 respondents is

less than ₹10000, family income of 312 respondents is between ₹10000 and ₹20000 and family

income of 240 respondents is more than ₹20000.

(See Table-23) Box’s M is statistically significant (< .001).

(See Table-24) The approximate chi-square in case of shampoo is 236.378. The value of

Bartlett’s Test of Sphercity is statistically significant (p < .001).

(See Table-25) The analysis of one way multivariate analysis of variance showed that the family

income of rural purchasers had an effect on the combined factors influencing purchasers’

purchase orientation for hair care products in rural markets of district Saharanpur.

The Wilks’ lambda of shampoo (.323) measures the percent of variance in the family income that

is not explained by the difference in factors influencing purchase orientation towards shampoo

and subtracting that value from 1.00 gives a sense of the strength of the family income effect ( a

multivariate analog of Eta square). In this analysis, 1 - .323 = .677, and so it appears that family

income explained approximately 67.7% of the variance of the discriminant score variable factors

affecting purchaser’s intended commodity attributes i.e. influence factors, psychological factors

and value factors. The effect size (.431) was found to be medium. The results showed that there

was a very strong power (1.000) which had predicted the strength of the relationship between the

family income and factors influencing purchase orientation. The results have further shown that

F value was 165.342 and the P-value was significant at .05 percent level.


significant difference between factors affecting purchaser’s intended commodity attributes



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with reference to family income. It was postulated that level of family income of the

respondents significantly impact their intended attributes towards shampoos.


for influence factors, psychological factors and value factors in case of shampoo (< .05). It

indicates that influence factors, psychological factors and value factors demonstrate hetrogeneity

of variances. Hence, Tamane’s T2 post hoc tests are examined for these variables. Thus, we will

increase the stringency of our revised alpha level beyond the Bonferroni level when evaluating

the univariate effects (.05/3 = .017).


table), p<.01 while the ANOVA on the “Psychological factors” was significant, F (2,656) =

127.773 > (F-table), p<.01 and the ANOVA on the “Value factors” was also significant, F(2,656)

=69.274 > (F-table), p<.01. Hence, family income had a major effect on all three factors

affecting purchaser’s intended commodity attributes of shampoo namely, influence,

psychological factors and value factor at 10% level of significance.

Post-hoc tests

Since the levene’s test indicates statistically significant results for influence factors and

psychological factors and value factors. This indicates hetrogenicity of variances. Thus

Tamhane’s T2 results show that all the three groups- <20000, 20000-40000 and >40000 differed

significantly on each of these measures.

Multiple Regression Analysis



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H5: There is significant relationship between factors affecting purchaser’s intended

commodity attributes and brand predilection of rural people with reference to hair care

products.

Dependent variable – Shampoo Brand predilection

Independent variable – Factors affecting purchaser’s intended commodity attributes

(See Table-28) The independent variable influence factor, psychological factor and value factor

has R value of 0.923 which describe the criteria for the correlation between independent

variables and the dependent variable brand predilection for shampoo. Here independent

variables have a strong correlation with brand predilection for 92.3% and from the coefficient of

determination which is square of the correlation coefficient (R2) is equal to 0.852 that showed

85.2% of the variance in the shampoo brand predilection is described by the independent

variables i.e. influence factors, attribute factors, psychological factors and value factors together,

while the remaining (100-85.2) = 14.8% is explained by other variables which are not described

in this research. The adjusted R Square value is .852 and represents some R Square shrinkage as

a result of including three predictors in the model.

(See Table-29) The regression model has four degrees of freedom because that is the number of

predictors in the model. The total degrees of freedom are equal to N-1 or 658, leaving 655

degrees of freedom for the error term. The model accounts for a significant amount of dependent

variable variance, F (3,655) = 1258.860, p < .001. The eta square value is equal to regression

variance divided by total variance, which yields 520.001/610.188 or 85.2%. Hence, all the

independent variables, influence factors, psychological factors and value factors have significant

effect on the dependant variable brand predilection for shampoo.

(See Table-30) Regression equation y on x,

where Ysp = brand predilection for shampoo, α = Intercept, β1, β2, and β3 are slopes associated

with x1, x2, and x3 and x1, x2 and x3 are regression factor scores for shampoo, namely Influence,

Psychological and price respectively.

Hence, Ysp = α + β1x1 + β2x2 + β3x3



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= (.516)x1 + (.566)x2 + (.516)x3

Hence, null hypothesis is rejected and alternate hypothesis is accepted there is significant

relationship between factors affecting purchaser’s intended commodity attributes and

brand predilection with reference to branded shampoo.

Applicability and Generalization

In five diverse geographical regions of rural India, comprising Northern India, Southern India,

Eastern India, Western India and Central India, descriptive research was carried out. These

groups illustrate regions of distinct backwardness, improvement, and growth. For the research,

320 participants were chosen from each geographical region, using stratified random sampling

approach that maintains equal representation of all participants ' socioeconomic, income groups

and other population characteristics. Indeed the target population analyzed (n=1016) is

reasonably large to assure that findings are universally applicable. Hence, the research findings

can be applied to underdeveloped, emerging, and developed world markets.

Whilst concentrating emphasis on using the model, there is indication that marketing companies

and distributors must recognize the subject's validity while producing marketing output that

addresses their intended segment of society. The work can be extended to virtually any type of

FMCG goods currently marketed in rural locations with realistic perspectives for

contextual implementations. The research provides new strategic avenues for strategy and

choice-making consequences for rural branding practitioners, rural policy leaders, rural

administrators and rural vendors that can provide greatest experiences to consumers in rural

India.

Conclusion

The findings provide valuable information into the dimensions related to considerations that

activate the tendency of the consumer to acquire. The psychological importance and monetary

value of the commodity attributes sought by the buyer in the current study play a critical role in



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deciding the brand predilection of a buyer for shampoo. The study has extracted impact of factor

influencing purchaser purchase orientation such as T.V. Regional and national advertising, brand

ambassador, loved ones, salon reviews and folk activities, psychological factors such as feeling

freshness, feeling enhanced self-esteem, look and feel trendy, feel beautiful / stunning using

shampoo and lead to your lifestyle; and value factors such as prize, complementary offers and

available discounts. The study indicated a significant difference in factors affecting purchaser’s

intended commodity attributes with respect to age, class, education and family income. It also

showed that there is a significant association between purchasers' brand predilection and factors

affecting purchaser’s intended commodity attributes.

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List of Tables

Table – 1

Variance of factors affecting purchaser’s intended commodity attributes

Category

Component 1

Influence factor

(%)

Component 2

Psychological

factor (%)

Component 3

Value factor

(%)

Total

Explained

Variance (%)

Shampoo 32.785 20.621 11.405 64.811

(Source: Compiled by the researcher)

Table – 2

Reliability & Validity of factors

Category

Scales Reliability Kaiser-Meyer-Olkin

Measure of Sampling

Adequacy

Approx.

Chi- Square

Bartlett's Test

of Sphericity

No. of

items

Cronbach's

Alpha df Sig.

Shampoo 13 .827 .828 3608.932 78 .000


Table- 3

Principal Component Factor Analysis – Shampoo

S.no Variables Factor

Loadings

Cronbach’s

Alpha

Component - 1 Influence factors

1.

Do T.V. advertisements in regional and

national channels influence your purchase

decision for shampoo?

.821

.844

2. Does brand ambassador influence your

purchase decision for shampoo? .807

3. Do loved ones influence your purchase

decision for shampoo? .793

4. Do salon reviews influence your purchase


5. Do folk activities influence your purchase


Component - 2 Psychological factors

6. Do you feel freshness with the use of

shampoo? .808

.829

7. Do you feel enhanced self esteem with the

use of shampoo? .805



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8. Do you look and feel trendy with the use of

shampoo? .753

9. Do you feel beautiful/ stunning with the

use of shampoo? .742

10. Does using shampoo contribute to your

lifestyle? .670

Component - 3 Value factors

11. Does the price of the shampoo influence

your purchase decision for it? .866

.856 12.

Do the complementary offers on the

shampoo influence your purchase decision

for it?

.846

13. Does the discount available on the

shampoo influence your purchase decision

for it?

.835


Table – 4

Between Subjects Factors

Value Label Shampoo (f)

< 20 335

20- 40 209

> 40 115


Table – 5

Box's Test of Equality of Covariance Matrices

Box's M 164.893

F 13.629

df1 12

df2 623116.321

Sig. S

S = Significant; NS = Not significant Computed using alpha = .001

(Compiled by the researcher)

Tests the null hypothesis that the observed covariance matrices of the dependent variables are

equal across groups.

Design: Intercept + age

Table – 6

Bartlett’s Tests of Sphericity

Likelihood Ratio S

Approx. Chi-Square 222.657

Degrees of freedom 5



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Tests the null hypothesis that the residual covariance matrix is proportional to an identity matrix.

a. Design: Intercept + age

Table – 7

Multivariate tests

Effect Value F Hypothesis

df Error df Sig.

Partial

Eta

Squared

Observed

Power

Wilks'

Lambda .336 158.097 6.000 1308.000 S .420 1.000



Table – 8

Levene's Test of Equality of Error Variances

F df1 df2 Sig.

Influence factors for shampoo 8.405 2 656 S

Psychological factors for shampoo 6.819 2 656 S

Value factors for shampoo 3.188 2 656 S



Tests the null hypothesis that the error variance of the dependent variable is equal across groups.

Design: Intercept + age

Table – 9

Tests of Between Subjects Effects

Dependent

Variable

Type

III Sum

of

Squares

df Mean

Square F Sig.

Partial

Eta

Squared

Observed

Power

influence

factors for

shampoo

149.681 2 74.841 96.584 S .227 1.000

psychological

factors for

shampoo

163.917 2 81.959 108.818 S .249 1.000

monetary value

factors for

shampoo

123.368 2 61.684 75.687 S .187 1.000





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Table – 10


Shampoo (f)

Transgender 19

Male 289

Female 351


Table – 11

Box’s Test of Equality of Covariance Matrices

Shampoo (f)

Box's M 41.214

F 3.318

df1 12

df2 9222.978

Sig. S





Design: Intercept + gender

Table – 12


Shampoo (f)

Sig. S


Df 5




a. Design: Intercept + Gender

Table – 13

Multivariate tests


df Error df Sig.

Partial

Eta

Observed

Power



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Squared

Wilks'

Lambda .657 50.918 6.000 1308.000 S .189 1.000



Table – 14

Levene’s Test of Equality of Error Variances

F df1 df2 Sig.


Psychological factors for shampoo .186 2 656 NS





Design = Intercept + Gender

Table – 15

Tests of Between-Subjects Effects

Dependent

Variable

Type III

Sum of

Squares

Df Mean

Square F Sig.

Partial

Eta

Squared

Observed

Power

influence factors

for shampoo 90.110 2 45.055 52.046 S .137 1.000

psychological

factors for

shampoo

94.382 2 47.191 54.926 S .143 1.000

monetary value

factors for

shampoo

41.219 2 20.610 21.920 S .063 1.000



Table – 16


Shampoo (f)

Illiterate 143

< Highschool pass 326

>Highschool pass 190


Table – 17



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Box’s test of Equality of Covariance Matrices

Box's M 119.666

F 9.897

df1 12

df2 997343.982

Sig. S





Design: Intercept + education

Table – 18

Barlett’s Test of Sphericity

Sig. S


Df 5




a. Design: Intercept + age

Table – 19

Multivatriate tests


df Error df Sig.

Partial

Eta

Squared

Observed

Power

Wilks’

lambda .276 197.240 6.000 1308.000 S .475 1.000



Table – 20

Levene’s Test of Equality of Error Vaiances

F df1 df2 df3


Psychological factors for shampoo 2.258 2 656 NS

Monetary value factors for shampoo 7.794 2 656 S




Design = Intercept + education



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Table – 21

Tests of Between Subject Effects

Dependent

Variable

Type

III Sum

of

Squares

Df Mean

Square F Sig.

Partial

Eta

Squared

Observed

Power

influence

factors for

shampoo

138.477 2 69.239 87.427 S .210 1.000

psychological

factors for

shampoo

194.398 2 97.199 137.538 S .295 1.000

monetary

value factors

for shampoo

143.770 2 71.885 91.703 S .218 1.000



Table – 22


Shampoo (f)

<10000 107

10000 – 20000 312

> 20000 240


Table – 23

Box’s Test of Equality of Covariance Matricesa

Box's M 118.023

F 9.753

df1 12

df2 524930.070

Sig. S





a. Design: Intercept + Family income

Table – 24




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Sig. S

Approx. Chi-

Square 236.378

Df 5




a. Design: Intercept + Family income

Table – 25

Multivariate tests

Effect Value F

Hypothesis

degrees of

freedom

Error

degrees of

freedom

Sig.

Partial

Eta

Squared

Observed

Power

Family

income .323 165.342 6.000 1308.000 S .431 1.000



Table – 26

Levene’s Test of Equality of Error Variances

F df1 df2 Sig.


Psychological factors for shampoo 5.713 2 656 S




Tests the null hypothesis that the error variance of the dependent variable is equal across

groups.

Design: Intercept + family incomea

Table- 27

Tests of between subjects effects

Dependent

Variable

Type III

Sum of

Squares

Df Mean

Square F Sig.

Partial

Eta

Squared

Observed

Power

influence

factors for

shampoo

146.552 2 73.276 93.987 S .223 1.000

psychological

factors for

shampoo

184.466 2 92.233 127.773 S .280 1.000

monetary value

factors for

shampoo

114.738 2 57.369 69.274 S .174 1.000




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Table - 28

Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

Shampoo .923 .852 .852 .371


Dependent Variable: Shampoo brand predilection

Predictors: (Constant), monetary value factors for shampoo, psychological factors for shampoo,

influence factors for shampoo

Table – 29

ANOVA

Model Sum of Squares Degrees of freedom Mean Square F Sig.

Regression 520.001 3 173.334 1258.860 S

Residual 90.188 655 .138

Total 610.188 658



Dependent Variable: Shampoo brand predilection

Predictors: (Constant), monetary value factors for shampoo, psychological factors for shampoo,

influence factors for shampoo

Table – 30

Coefficients

Model

Unstandardized

Coefficients

Standardized

Coefficients t Sig.

B Std. Error Beta

(Constant) 3.102 .012 214.578 S

Influence factors for

shampoo .497 .014 .516 34.341 S

Psychological factors for

shampoo .545 .017 .566 37.653 S

Monetary value factors for

shampoo .497 .015 .526 34.344 S





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List of Figures

Figure-1 Scree plot - Shampoo



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implications of confounding variables on rural purchaser’s

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