Description
The objective of the report is to explore the various factors which influence the green purchasing behaviour of the Indian consumer. Will advertising attitude and ad usage of a person predict his green purchasing behaviour. Will his attitude towards private brands influence his green purchasing behaviour. To give a segmented opinion of the green purchasing behaviour attitude based on their gender, family type, education level etc.
GREEN PURCHASING BEHAVIOUR
Abhishek Vyas (09P124)
Page | 1
Contents
Acknowledgment-----------------------------------------------------------------------------------------------04 1. Introduction a. Green Purchasing---------------------------------------------------------------------------05 b. The current West----------------------------------------------------------------------------05 c. Literature survey----------------------------------------------------------------------------06 d. GPNI: Green Purchasing Network India------------------------------------------------07 e. Reason for choosing this topic------------------------------------------------------------08 f. Differentiation of our project------------------------------------------------------------08
g. Objective and scope of the project------------------------------------------------------08 2. Methodology a. Research questions-------------------------------------------------------------------------10 b. Research Methodology--------------------------------------------------------------------10 c. Survey technique---------------------------------------------------------------------------10
d. Questionnaire -----in
Annexure-------------------------------------------------------------e. Sample-----------------------------------------------------------------------------------------10 3. Results
Page | 2
a. Exploratory Research-----------------------------------------------------------------------11 b. Descriptive Research i) ii) c. Analysis i) ii) iii) Green Purchasing behavior---------------------------------------13 Attitude towards Private label brands-------------------------17 Brand Consciousness----------------------------------------------20 Attitude towards advertisements-------------------------------21 Ad usage--------------------------------------------------------------23 Questionnaire-------------------------------------------------------11 Subjects---------------------------------------------------------------12
iv) v)
d. Results (Variables)
--------------------------------------------------------------------------25 e. Correlation-----------------------------------------------------------------------------------26 f. Regression------------------------------------------------------------------------------------27 g. Independent sample t-test i) ii) Gender----------------------------------------------------------------32 Marital Status-------------------------------------------------------33 Family type-----------------------------------------------------------35
iii)
h. One way ANOVA (education)
------------------------------------------------------------36
Page | 3
4. Conclusion a. Finding based interpretations------------------------------------------------------------37 b. Further Scope--------------------------------------------------------------------------------37 Annexure
Acknowledgement
We thank our colleagues, friends, faculty and other well wishers for their encouraging words and support while doing this project. We also thank
Page | 4
our friends from PGPM, PGPHR and NMP batches, an friends from facebook and orkut who took out their precious time to participate in our survey. We are grateful to Prof. Ajay Kumar Jain, Faculty, Management
Development Institute, Gurgaon for his continuous support and guidance without which this research could not have been fruitful. His help has been of key importance towards the completion of the report. We would also like to thank the creators of PASW software without which the complex analysis wouldn’t have been possible. Finally, we also take this opportunity to appreciate the institute, MDI, for providing this learning and also assisting in infrastructure and administrative work. We are grateful to all the professors for their guidance and support at each step. Their insights and teachings have played a critical role in developing this report.
Abhishek Vyas (09P124) Debasish Jena (09P134) Kalapala Ashwini Prasad(09P146) Narayanan S (09P152) Shweta Bagrecha (09P172) Vishal Gupta(09P179)
INTRODUCTION
Green Purchasing
Page | 5
Environmentally preferable purchasing or green purchasing is the conscious selection and buying of products or services that most effectively minimize their environmental impact over their life cycle from manufacturing to disposal. The products that come under this category are those that conserve energy and water, minimize release of waste and environmentally harmful pollutants, those which can be recycled or reused, etc. Use of biodegradable plastic, bio based fuels, solar and wind power and products using alternative to toxic or hazardous chemicals also constitute green purchasing behaviour. Green purchasing is also about process improvements; for example, consolidating multiple user orders with a given supplier into a single order. This will result in a single delivery, thus reducing shipping costs and carbon emissions. In short green purchasing behaviour is the attitudinal aspect of the consumer to add environmental aspects to price and performance criteria while making a purchase.
The current West
Studies held in Australia (Mobium Group (2008) ‘The LOHAS (Lifestyles of Health and Sustainability) report), Europe and US of A(Lawrence, 1993), have all found out that the market for environmental goods and services has grown significantly in recent years and a number of studies have highlighted increasing consumer interest in the area of more sustainable products and services. Hence providing green products is now the new motto of organizations in order to capture the mind of the consumer. Organizations have already started becoming more conscious and responsible regarding decreasing the carbon footprint of their products as well as their processes. Few organizations like Motorola, IBM, S.C. Johnson, TRW, Nokia, Sony, Ford, Ray-O-Vac, Northern Telecom, Apple Computer, Sun Microsystems, and the Body Shop have shown visibility of strategy in this direction.
Page | 6
Literature survey
The concept of green marketing has evolved over the years. There are basically three stages in which it has evolved.
1. The decade of the late 1980s marked the first stage of green
marketing, when the concept of “green marketing” was newly introduced and discussed in industry (Peattie and Crane, 2005). Owing to the upsurge of this new concept many marketer tried to involve in green marketing in order to generate positive consumer response which would be converted into goodwill, market share and sales. However in spite of reports stating that the environmental problems constituted one of the uppermost public concerns, market growth of these products fell short of expectations.
2. The second stage started off as a consumer backlash. Many
organizations “greenwash”ed the consumers. In order to improve their sales, thus creating cynical attitude of the consumers towards the green concept. Some of the marketing practices which lead to the failure of green marketing during this period are (Peattie and Crane 2005):
a. Green spinning -> Taking a reactive stance of “green”, if
accused of malpractice
b. Green Selling -> taking an opportunistic approach by adding
some green claims to existing products with an intention to boosts profits.
c. Green harvesting -> Becoming enthusiastic about the
environment only when greening would result in cost savings.
d. Entrepreneur marketing -> Developing innovative green
products without actually considering consumer needs
Page | 7
e. Compliance marketing -> Just following the environmental
standards as an opportunity to promote the company’s green credentials rather than actually being involved
3. The evolution of the third stage is just a response to the
anomalies occurring in the second stage. With the implementation of advanced technology, stricter state enforcement on deceptive claims, govt. regulations and incentives and closer scrutiny from various environmental organizations and media many green products have regained confidence in the 2000’s (Gurau and Ranchhod, 2005; Ottoman, 2007). With green and sustainable development as the theme of 21st century development, two trends have been predicted as inevitable in the near future of green marketing. They are:
a) First the concept of an eco friendly approach of doing business
will be pushed into mainstream(Hanas 2007)
b) Second, corporations from developed countries will initiate
international green marketing in order to expand their market, increase their sales and take advantage of the positive image of their green brands established in their domestic markets (Gura?u and Ranchhod, 2005; Johri and Sahasakmontri, 1998; Pugh and Fletcher, 2002).
GPNI: Green Purchasing Network India
GPNI is an evolving network of professionals interested and active in the general area of sustainable consumption and production- more specifically: Green Purchasing and Public Procurement. It is currently a loose informal network of professionals primarily operating as an internet based electronic forum. The objectives of the GPNI are:
Page | 8
1. To create awareness amongst Indian industry and other stakeholders about Green Purchasing and Procurement (GPP) 2. To encourage and facilitate implementation of GPP and Greening Supply Chains (GSC) projects to enhance the competitiveness of the Indian industries.
Reason for choosing this topic
Recent effort by leaders like Al Gore and Dr. R.K. Pachauri, environment has taken a significant portion of our thinking space. We have become more sensitive and responsible for the environment. Hence consumers now look for more sustainable and green products which have low impact on the ecosystem. Thus in order for organizations to survive in this new era of greenism, they have to consider going green as part of their long term strategies mould consumer minds towards the green value of their product and service offerings. India being a developing nation is bound to be the destination of most of the organizations in order to implement their long term strategies. Thus they need to know what are the various factors that affect the green purchasing behaviour of Indian consumers and whether by advertising and branding, can they affect their green purchasing behaviour.
Differentiation of our project
Most of the environment researches have been done in Europe, Australia, America and some parts of Asia. However no much concrete researches have been done for the Indian context. Our project gives insights keeping in mind the Indian consumer.
Objective and scope of the report
Page | 9
Objective:
? Explore the various factors which influence the green purchasing behaviour of the Indian consumer.
? Will advertising attitude and ad usage of a person predict his green
purchasing behaviour ? Will his attitude towards private brands influence his green purchasing behaviour
? To give a segmented opinion of the green purchasing behaviour
attitude based on their gender, family type, education level etc.
Problems faced during the research:
» » Problem of having a larger sample size Lack of environmental research in Indian context
Scope of the project
The scope of the project is to help marketers wanting to boost their sales by introducing green products, by saying whether branding or advertising is going to have any impact on the green purchasing behaviour of the consumer or not. If yes, which segments are more likely to be responsive?
Page | 10
Methodology
Research Questions
1. Does the ad usage of a person predict his green purchasing behaviour? 2. Does the attitude of a person towards private brands influence his green purchasing behaviour?
3. Do gender, family type, education and marital status affect the
green purchasing behaviour?
Research Methodology
We propose to conduct the research as following1. Do an exploratory research by opinions about the topic from people.
2. Conduct a conclusive research(descriptive) by floating survey
among MBA students, undergraduates, working professionals to validate our findings
3. From the collected data try to establish the relationship between
advertising attitude and branding attitude with green purchasing behaviour
Survey Technique
Page | 11
Data was collected in various ways: - Through online filling up of survey - By approaching students at NMP hostel and PGPM hostel of MDI
Sample
The sample constituted mostly of students pursuing MBA at Management Development Institute Gurgaon, in addition to student of other colleges, friends and relatives in order to get a varied sample
RESULTS
Exploratory research
An exploratory was conducted in a hostel of Management Development institute, 30 MBA students were asked to write 5 points each, by which we arrived at around 121 points. Most of the points were overlapping. Hence after adding the cumulative count of each distinct point, we considered 21 variables of green purchasing behaviour.
Descriptive research
Questionnaire
The questionnaire consisted of 6 parts. They were:
1. Control variables – These factors were taken to help us develop
an insightful view of the background of the respondents. Questions asked in this category were age, gender, family type, education and marital status.
2. Green purchasing behaviour – This questionnaire consisted of 21
questions collected from the exploratory research previously done. All the questions in this part of the questionnaire asked the
Page | 12
respondent to rate the variable on a 5-point Likert scale e.g. my education influences my green purchasing behaviour?
3. Attitude towards private brands – This questionnaire is a scale
borrowed from Marketing Scales Handbook. This composed of six 7point Likert-type statements that measure the consumer attitude towards private distributor brands. Not only does the scale capture the consumer’s opinion of the general quality level of private brands but also provides a sense of consumers tendency to buy them or not. E.g. In general private label brands are poor-quality products.
4. Brand consciousness – This questionnaire is a scale borrowed
from Marketing Scales Handbook. A three 5-point Likert-type summated ratings scale measuring the degree to which a person expresses a desire to buy “brand name products”. The implication is that the consultation prefers nationally known brands rather than private distributor or generic goods. E.g. I usually purchase brand name products
5. Attitude towards Advertising – This questionnaire is a scale
borrowed from Marketing Scales Handbook. Five 5-point Likert-type statements are used to measure consumer attitudes about advertising in general. E.g. Most advertising is very annoying.
6. Ad Usage - This questionnaire is a scale borrowed from Marketing
Scales Handbook. This scale is composed of four, 5-point Likert-type statements measuring the extent to which a consumer reports consulting advertisements before making purchase decisions in order to make better decisions.
Subjects
A total of 100 respondents participated. Out of them 79 were males and 21 were females. The age bracket of the respondents ranged from 16 from 52. However majority (89%) belonged to the age group of 21 – 27. 15 people among the respondents were married and the rest were unmarried. The education status also varied with 14 people having completed their post graduation, 18 respondents had passed graduation,
Page | 13
2 were still undergraduates and 65 were still pursuing post graduation. Of the respondents 15 were from joint family and the remaining 85 were from nuclear families.
ANALYSIS
i. Identifying the factors underlying the green purchasing behaviour....
The 100 responses to the green purchasing behaviour questionnaire were taken. They were subjected to an initial screening of Descriptive analysis, where a screening criterion of mean value of 3.3 was set. Based upon this criteria 5 variables were rejected. They were GPB6, GPB15, GPB16, GPB17, GPB21.
Page | 14
Descriptive Statistics Std. N Statistic GPB1 GPB2 GPB3 GPB4 GPB5 GPB6 GPB7 GPB8 GPB9 GPB10 GPB11 GPB12 GPB13 GPB14 GPB15 GPB16 GPB17 (r)GPB18 (r)GPB19 GPB20 GPB21 Valid N (listwise) 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 Minimum Maximum Statistic 2.00 2.00 1.00 1.00 1.00 1.00 2.00 1.00 1.00 1.00 2.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 Statistic 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 Mean Statistic 3.8400 4.0500 4.1200 3.4500 3.8400 2.7900 3.9000 3.6500 3.3000 3.5300 3.8000 3.7400 3.8300 3.7600 2.3100 3.2800 3.1000 3.7000 4.0600 3.7200 2.3400 Deviation Statistic .84948 .78335 .87939 1.14040 .86129 1.20851 .92660 1.04809 1.21854 1.00960 .94281 1.07891 1.03529 1.03592 1.26087 1.11988 1.18492 1.21023 1.14433 .87709 1.11210 Skewness Kurtosis
Statistic Std. Error Statistic Std. Error -.291 -.732 -.966 -.375 -.651 .099 -.731 -.596 -.359 -.444 -.472 -.594 -.821 -1.003 .595 -.400 -.123 -.726 -.945 -.792 .458 .241 .241 .241 .241 .241 .241 .241 .241 .241 .241 .241 .241 .241 .241 .241 .241 .241 .241 .241 .241 .241 -.540 .524 .890 -.571 .473 -1.076 -.147 -.047 -.896 -.273 -.594 -.340 .218 .776 -.783 -.541 -.896 -.346 -.288 .851 -.648 .478 .478 .478 .478 .478 .478 .478 .478 .478 .478 .478 .478 .478 .478 .478 .478 .478 .478 .478 .478 .478
(r) Means that question was reverse coded; yellow were removed Then a factor analysis was done on the selected 16 variables to decide upon the factors underlying the Green Purchasing behaviour of the Indian consumer. Below is the output of the factor analysis
Page | 15
KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Bartlett's Test of Sphericity Approx. Chi-Square df Sig. .754 542.643 120 .000
The value of KMO is more than 0.5. Thus the degree of common variance among the eleven variables is "middling" bordering on "meritorious". If a factor analysis is conducted, the factors extracted will account for fairly decent amount of variance. Also the significance level of Bartlett’s test is very less little than 0.01, which is a good sign. After establishing the adequateness of our sample, we proceed to perform the factor analysis. The extraction was done by the principal components method. For rotation in order to determine the factors, we chose the Varimax rotation. In order to assign each variable individually under distinct factor, we suppressed the coefficients below an absolute value of 0.55 which corresponded to the sample size of 100. Below is the rotated component matrix which was generated:
Page | 16
Rotated Component Matrixa Component 1 GPB1 GPB2 GPB3 GPB4 GPB5 GPB7 GPB8 GPB9 GPB10 GPB11 GPB12 GPB13 GPB14 (r)GPB18 (r)GPB19 GPB20 .811 .688 .850 .823 .738 .614 .836 .552 .578 .926 .719 .598 2 3 4 5
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 12 iterations.
Now the 5 factors taken together account for 65.434 % of the total variance. This is a fair representation of the total variance present.
Page | 17
Total Variance Explained Extraction Sums of Squared Initial Eigenvalues Comp onent 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 Total 4.854 1.893 1.314 1.289 1.119 .916 .822 .652 .614 .525 .475 .411 .379 .303 .226 .206 % of Variance 30.336 11.833 8.214 8.056 6.994 5.725 5.137 4.077 3.836 3.282 2.969 2.571 2.370 1.896 1.413 1.290 Cumulative % 30.336 42.169 50.383 58.439 65.434 71.158 76.295 80.372 84.208 87.491 90.459 93.031 95.401 97.297 98.710 100.000 Total 4.854 1.893 1.314 1.289 1.119 Loadings % of Variance 30.336 11.833 8.214 8.056 6.994 Cumulative % 30.336 42.169 50.383 58.439 65.434 Total 2.817 2.323 2.072 2.002 1.256 Rotation Sums of Squared Loadings % of Variance 17.605 14.517 12.949 12.515 7.848 Cumulative % 17.605 32.122 45.071 57.585 65.434
Extraction Method: Principal Component Analysis.
Analysis – Normal observation showed the emergence of 5 factors.
However we chose not to club a single variable to make a factor. Hence GPB8 was dropped and so was factor 5. So we are left with 4 factors. Now in order to form more meaningful inference of the factors we suggest names to these factors. The factors that we came up with are:
1. Factor 1(Responsiblity for the environment) (Cronbach’s Alpha =.702 )-> a. b. c. d. GPB1 (My awareness of the environment affects my green purchasing behavior) GPB4 (Current social trends affects my green purchasing behavior) GPB11 (The recyclable nature of green products propells my green purchasing behavior) GPB12 (Care for future generations affect my green purchasing behavior) Page | 18
2. Factor2 (Reflective boost of participation) (Cronbach’s Alpha =.613 ) -> a. GPB14 (It's the perception of doing a good thing that affects my green purchasing behavior) b. GPB20 (I think its the responsible part of me that involves me in green purchasing behaviour) 3. Factor3(Environmental attitude) (Cronbach’s Alpha =.785 ) -> a. GPB18 (I am not concerned about my green purchasing behavior) b. GPB19 (I think that the whole green concept is a waste of time and resources) 4. Factor 4(Personal influences) (Cronbach’s Alpha = .597) -> a. GPB7 (Concern for my own health affects my green purchasing behavior) b. GPB9 (How does the urge of setting an example for others affect my green purchasing behavior) c. GPB10 (My perception of green products as the most effective and quality products affect my green purchasing behaviour) In order to confirm our findings from the factor analysis, we should calculate the reliability for each factor, and the reliability of the construct. We do this to be confident whether the variable measure the same thing or idea as purported by the factor and whether the factors measure the same thing as the construct. This is called construct reliability. We measure the reliability by calculating the cronbach’s alpha. Individual cronbach’s alpha is mentioned beside the factors above. A good value of cronbach’s alpha is 0.7 -0.8. Very high cronbach’s alpha tells that the items are highly correlated, which might be due to considering the same idea. However a value of 0.6-0.7 is also acceptable. In or case all our factors except factor 4 have values above 0.6, and factors 4 has approximately 0.6. Now in order to check the construct reliability, we calculate the cronbach’s alpha for the factors. Below is the output table:
Reliability Statistics Cronbach's Alpha .572 N of Items 4
An item-total statistics table gives us an idea of what our alpha would be like if an item were deleted. As the cronbach’s alpha, taking 4 items at a time results in a value less than 0.6, we need to resort to the item-total table. From the table Page | 19
we see that if we drop the fourth factor i.e. environmental attitude, we would be more confident that the factors essentially measure the green purchasing behaviour. A high inter-variable cronbach’s alpha for the factors means that the questions asked were relevant and related to the factor environmental attitude, however the factor was not properly defining the construct of green purchasing behaviour. Now since the 4th factor (Personal influences) is not far away from 0.6(0.597), we keep the factor assuming the sample size to be the cause of the slightly less value.
Item-Total Statistics
Scale Mean if Item Deleted Responsiblityfortheenvironment_d pnd Reflectiveboostofparticipation_dp nd Environmentalattitude_dpnd Personalinfluences_dpnd 11.0242 11.3275 11.1642 11.1967
Scale Variance if Item Deleted 3.449
Corrected ItemTotal Correlation .440
Cronbach's Alpha if Item Deleted .446
3.065
.510
.376
3.157 3.660
.233 .302
.636 .539
Hence now we are left with three factors which affect the green purchasing behaviour of the Indian consumer. They are 1. Responsiblity for the environment 2. Reflective boost of participation 3. Personal influences
ii. Attitude towards Private label brands
We perform the same procedures as we did for the Green purchasing behavior.Below is the descriptive analysis
Page | 20
Descriptive Statistics N Att twrd pvt lbl brnd1 Att twrd pvt lbl brnd2 Att twrd pvt lbl brnd3 (r)Att twrd pvt lbl brnd4 Att twrd pvt lbl brnd5 Att twrd pvt lbl brnd6 Valid N (listwise) 100 100 100 100 100 100 100 Minimum 1.00 1.00 1.00 1.00 1.00 1.00 Maximum 7.00 7.00 7.00 7.00 7.00 7.00 Mean 4.0700 4.1700 4.0400 4.6600 4.0400 4.0200 Std. Deviation 1.65300 1.53777 1.59494 1.53886 1.42786 1.40691
As the means are not wide apart, we keep all the variables for the factor analysis.
KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Bartlett's Test of Sphericity Approx. Chi-Square df Sig. .822 257.187 15 .000
A KMO value is 0.822 is a good sign of the adequacy of the sample. Also in the total variance explained table, the 2 factors taken together account for 72.938% of the total variance. This is a fair representation of the total variance present.
Page | 21
Total Variance Explained Extraction Sums of Squared Com pone nt 1 2 3 4 5 6 Total 3.356 1.021 .581 .515 .311 .216 Initial Eigenvalues % of Variance 55.928 17.010 9.691 8.586 5.184 3.602 Cumulative % 55.928 72.938 82.629 91.215 96.398 100.000 Total 3.356 1.021 Loadings % of Variance 55.928 17.010 Cumulative % 55.928 72.938 Total 3.331 1.046 Rotation Sums of Squared Loadings % of Variance 55.509 17.429 Cumulative % 55.509 72.938
Extraction Method: Principal Component Analysis.
Hence we proceed with the rotated component matrix table. Given below is the table.
Rotated Component Matrixa Component 1 Att twrd pvt lbl brnd2 Att twrd pvt lbl brnd1 Att twrd pvt lbl brnd3 Att twrd pvt lbl brnd6 Att twrd pvt lbl brnd5 (r)Att twrd pvt lbl brnd4 .876 .864 .856 .745 .724 .977 2
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 3 iterations.
Analysis - This states that except variable 4, all other variables can be
clubbed into a factor. Variable 4 is thus dropped because of its singularity in the 2nd factor. Hence only one factor emerges out of the factor analysis. This factor is conveniently known as:
Page | 22
1. Factor 1(Attitude towards the private label brand) (Cronbach’s Alpha =.875 ) a) Att twrd pvt lbl brnd1 -> Buying private brands make me feel
good
b) Att twrd pvt lbl brnd2 -> I love it when private label brands are
available for the product categories I purchase
c) Att twrd pvt lbl brnd3 -> For most product categories, the best
buy is usually the private label brand
d) Att twrd pvt lbl brnd5 -> Considering the value of money, I prefer
private label brands to national brands
e) Att twrd pvt lbl brnd6 -> When I buy a private label brand, I
always feel that I a getting a good deal
Reliability Statistics Cronbach's Alpha .875 N of Items 5
iii.
Brand Consciousness
Given below are the various tables of output of the same steps undertaken
Descriptive Statistics N Brnd conscious1 (r)Brnd conscious2 (r)Brnd conscious3 Valid N (listwise) 100 100 100 100 Minimum 1.00 1.00 1.00 Maximum 5.00 5.00 5.00 Mean 3.6600 3.3000 3.4000 Std. Deviation 1.02711 .90453 1.11916
KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Bartlett's Test of Sphericity Approx. Chi-Square df Sig. .499 13.398 3 .004
Page | 23
Total Variance Explained Extraction Sums of Squared Com pone nt 1 2 3 Total 1.359 1.000 .641 Initial Eigenvalues % of Variance 45.297 33.333 21.370 Cumulative % 45.297 78.630 100.000 Total 1.359 1.000 Loadings % of Variance 45.297 33.333 Cumulative % 45.297 78.630 Total 1.357 1.002 Rotation Sums of Squared Loadings % of Variance 45.218 33.412 Cumulative % 45.218 78.630
Extraction Method: Principal Component Analysis.
Reliability Statistics Cronbach's Alphaa -.334 a. The value is negative due to a negative average covariance among items. This violates reliability model assumptions. You may want to check item codings. N of Items 3
Analysis - From the above tables we interpret that the KMO value of .
499 is not good. Though the variances explained by the factors explain 78.63% of the total variance, yet the cronbach’s alpha is too low and negative. Therefore due to these issues, we drop this factor and the scale for consideration as the respondents were not able to correlate the construct with the scale.
iv.
Attitude towards advertisement
Given below are the various tables of output of the same steps undertaken
Page | 24
Descriptive Statistics N (r)Atti twrds advert1 Atti twrds advert2 Atti twrds advert3 Atti twrds advert4 (r)Atti twrds advert5 Atti twrds advert6 Atti twrds advert7 Valid N (listwise) 100 100 100 100 100 100 100 100 Minimum 1.00 1.00 1.00 1.00 1.00 1.00 1.00 Maximum 5.00 5.00 5.00 5.00 5.00 5.00 5.00 Mean 3.3700 3.1200 3.5500 2.8100 2.7700 3.7000 3.6000 Std. Deviation 1.02154 1.20839 1.03840 1.26886 1.02351 1.14150 1.07309
KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Bartlett's Test of Sphericity Approx. Chi-Square df Sig. .593 136.992 21 .000
Total Variance Explained Extraction Sums of Squared Com pone nt 1 2 3 4 5 6 7 Total 2.346 1.335 1.207 .761 .554 .488 .308 Initial Eigenvalues % of Variance 33.520 19.078 17.248 10.877 7.915 6.969 4.393 Cumulative % 33.520 52.598 69.846 80.723 88.637 95.607 100.000 Total 2.346 1.335 1.207 Loadings % of Variance 33.520 19.078 17.248 Cumulative % 33.520 52.598 69.846 Total 1.866 1.711 1.313 Rotation Sums of Squared Loadings % of Variance 26.651 24.437 18.758 Cumulative % 26.651 51.088 69.846
Extraction Method: Principal Component Analysis.
Page | 25
Rotated Component Matrixa Component 1 (r)Atti twrds advert5 Atti twrds advert4 Atti twrds advert2 Atti twrds advert6 Atti twrds advert7 (r)Atti twrds advert1 Atti twrds advert3 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 7 iterations. .787 .728 .710 .742 .736 .902 .583 2 3
Factor 1
Reliability Statistics Cronbach's Alpha .625 N of Items 3
Factor 2
Reliability Statistics Cronbach's Alpha .437 N of Items 2
Factor 3
Reliability Statistics Cronbach's Alpha .452 N of Items 2
The construct reliability is:
Page | 26
Reliability Statistics Cronbach's Alpha .466 N of Items 3
Analysis - Owing to the low cronbach’s alpha we reject the construct
and take simply the factor 1 in our experiment. Thus the factor identified was:
1. Factor 1(Attitude towards advertisement)( Cronbach's Alpha =
0.625) a) Most advertising is very annoying b) If most advertising was eliminated, consumers would be better off
c) I enjoy most ads(r)
v. Ad Usage
Given below are the various tables of output of the same steps undertaken
Descriptive Statistics N Ad usage1 Ad usage2 Ad usage3 Ad usage4 Valid N (listwise) 100 100 100 100 100 Minimum 1.00 1.00 1.00 1.00 Maximum 5.00 5.00 5.00 5.00 Mean 2.9400 3.1300 3.0200 3.1300 Std. Deviation 1.08078 1.06983 1.10078 1.06035
Page | 27
KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Bartlett's Test of Sphericity Approx. Chi-Square df Sig. .763 137.301 6 .000
Total Variance Explained Compo nent 1 2 3 4 Total 2.585 .661 .401 .353 Initial Eigenvalues % of Variance 64.614 16.515 10.034 8.837 Cumulative % 64.614 81.129 91.163 100.000 Extraction Sums of Squared Loadings Total 2.585 % of Variance 64.614 Cumulative % 64.614
Extraction Method: Principal Component Analysis.
Component Matrixa Component 1 Ad usage3 Ad usage2 Ad usage1 Ad usage4 .851 .841 .761 .759
Extraction Method: Principal Component Analysis. a. 1 components extracted. Reliability Statistics Cronbach's Alpha .816 N of Items 4
Analysis - Owing to the KMO and Bartlett’s value, we move ahead with
the factor analysis alpha we accept the construct and take simply the
Page | 28
factor 1 calculated in our experiment. The factor is reliable as the variables in the factor give a cronbach’s alpha value of 0.816 Thus the factor identified was: 1. Factor 1(Ad Usage)( Cronbach's Alpha = 0.816)
a) To make sure I buy the right product or brand, I often look at the
advertisements to see what others are buying and using. b) If I have little experience with a product, I often check with advertisements c) I often consult advertisements to help choose the best alternative available from a product class d) I often gather information from advertisements about products before I buy
Results
Dependent variables
1. Responsibility for the environment
2. Reflective boost of participation 3. Personal influences
Independent variables
1. Attitude towards the private label brand 2. Attitude towards Advertisement 3. Ad usage
Correlation
In order to check predictability we do a 6 x 6(3 ind + 3 dep) correlation matrix to check for the amount of correlation between all the variables. Below is the correlation matrix:
Page | 29
Correlations Responsiblit Reflectiveb yfortheenvir oostofpartici Personalinfl onment_dp pation_dpn uences_dpn atttwrdpvtlbl Ad_attitud Ad_usag nd Responsiblityforthee Pearson nvironment_dpnd Correlation Sig. (2-tailed) N Reflectiveboostofpart Pearson icipation_dpnd Correlation Sig. (2-tailed) N Personalinfluences_ Pearson dpnd Correlation Sig. (2-tailed) N atttwrdpvtlblbrnd_ind Pearson Correlation Sig. (2-tailed) N Ad_attitude Pearson Correlation Sig. (2-tailed) N Ad_usage Pearson Correlation Sig. (2-tailed) N .718 100 .192 100 .651 100 .086 100 .034 100 100 .071 100 .037 .811 100 .131 .257 100 .046 .731 100 .172 100 -.212* .034 100 1 .519 100 .181 .748 100 .024 .546 100 .114 100 .035 .731 100 1 .086 100 -.212* .000 100 -.065 .000 100 .032 100 -.061 .546 100 1 .257 100 .035 .651 100 .172 .000 100 .360** 100 .350** .000 100 1 .748 100 -.061 .811 100 .114 .192 100 .046 100 .397** .000 100 1 .000 100 .350** .519 100 .032 .071 100 .024 .718 100 .131 1 d .397** d .360** brnd_ind -.065 e .181 e .037
**. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed).
The correlation matrix shows that:
1. The correlation between the dependent variables is high, thus
establishing the validity of our construct.
Page | 30
2. There is a decent correlation between Attitude towards the
environment and responsibility for the environment at 93% 3. There is not significant co-relation between the independent and dependent variables
Regression
1. Regression between the independent variables and attitude towards private brands
Model Summary Adjusted R Model 1 R .215a R Square .046 Square .017 Std. Error of the Estimate .72735
a. Predictors: (Constant), atttwrdpvtlblbrnd_ind, Ad_attitude, Ad_usage
ANOVAb Model 1 Regression Residual Total Sum of Squares 2.469 50.788 53.257 df 3 96 99 Mean Square .823 .529 F 1.556 Sig. .205a
a. Predictors: (Constant), atttwrdpvtlblbrnd_ind, Ad_attitude, Ad_usage b. Dependent Variable: Responsiblityfortheenvironment_dpnd
Coefficientsa Standardized Unstandardized Coefficients Model 1 (Constant) Ad_attitude Ad_usage atttwrdpvtlblbrnd_ind B 3.182 .169 .081 -.052 Std. Error .439 .085 .088 .060 .205 .095 -.089 Coefficients Beta t 7.242 2.000 .918 -.875 Sig. .000 .048 .361 .384
a. Dependent Variable: Responsiblityfortheenvironment_dpnd
Page | 31
Analysis - We see that the adjusted R square has a low value for the
model. The ANOVA analysis is also not significant. Therefore we reject the model. However a bit more looking will hint us that the relation between attitude towards advertisement and responsibility towards the environment. Regression between these factors shows a slope of .15 and a constant value of 3.272. The significance level of the values is 93%
Coefficientsa Standardized Unstandardized Coefficients Model 1 (Constant) Ad_attitude B 3.272 .150 Std. Error .249 .082 .181 Coefficients Beta t 13.124 1.825 Sig. .000 .071
a. Dependent Variable: Responsiblityfortheenvironment_dpnd
2.
Regression between the independent variables and Reflective boost of participation
Model Summary Adjusted R Model 1 R .142a R Square .020 Square -.010 Std. Error of the Estimate .81914
a. Predictors: (Constant), Ad_usage, atttwrdpvtlblbrnd_ind, Ad_attitude
ANOVAb Model 1 Regression Residual Total Sum of Squares 1.325 64.415 65.740 df 3 96 99 Mean Square .442 .671 F .658 Sig. .580a
a. Predictors: (Constant), Ad_usage, atttwrdpvtlblbrnd_ind, Ad_attitude b. Dependent Variable: Reflectiveboostofparticipation_dpnd
Page | 32
Coefficientsa Standardized Unstandardized Coefficients Model 1 (Constant) Ad_attitude atttwrdpvtlblbrnd_ind Ad_usage B 3.171 .050 .004 .134 Std. Error .495 .095 .067 .099 .054 .006 .142 Coefficients Beta t 6.409 .522 .060 1.349 Sig. .000 .603 .953 .181
a. Dependent Variable: Reflectiveboostofparticipation_dpnd
Analysis - Poor regression coefficients, low significance of them and low
adjusted R square values suggest that this regression is not valid.
3. Regression between the independent variables and Reflective boost of participation
Model Summary Adjusted R Model 1 R .157a R Square .025 Square -.006 Std. Error of the Estimate .78779
a. Predictors: (Constant), Ad_usage, atttwrdpvtlblbrnd_ind, Ad_attitude
ANOVAb Model 1 Regression Residual Total Sum of Squares 1.500 59.579 61.079 df 3 96 99 Mean Square .500 .621 F .806 Sig. .494a
a. Predictors: (Constant), Ad_usage, atttwrdpvtlblbrnd_ind, Ad_attitude b. Dependent Variable: Personalinfluences_dpnd
Page | 33
Coefficientsa Standardized Unstandardized Coefficients Model 1 (Constant) Ad_attitude atttwrdpvtlblbrnd_ind Ad_usage B 3.189 .121 -.051 .080 Std. Error .476 .092 .065 .095 .136 -.081 .089 Coefficients Beta t 6.701 1.315 -.790 .844 Sig. .000 .192 .432 .401
a. Dependent Variable: Personalinfluences_dpnd
Analysis - Here also poor significance values of R square and
ANOVA test leads us to conclude that the regression is invalid.
4.
Regression b/w independent variables and the dropped factor Environmental attitude
ANOVAb Model 1 Regression Residual Total Sum of Squares 9.503 103.557 113.060 df 3 96 99 Mean Square 3.168 1.079 F 2.936 Sig. .037a
a. Predictors: (Constant), Ad_usage, atttwrdpvtlblbrnd_ind, Ad_attitude b. Dependent Variable: Environmentalattitude_dpnd_dropped
Coefficientsa Standardized Unstandardized Coefficients Model 1 (Constant) Ad_attitude atttwrdpvtlblbrnd_ind Ad_usage B 5.325 -.021 -.145 -.260 Std. Error .627 .121 .085 .126 -.018 -.169 -.210 Coefficients Beta t 8.487 -.177 -1.701 -2.068 Sig. .000 .860 .092 .041
a. Dependent Variable: Environmentalattitude_dpnd_dropped
Page | 34
Analysis - A strong significance level of 96% between Environmental
attitude and ad usage makes us conclude that ad usage has an effect on the environmental attitude. Individually establishing the relationship between the factors, we see that ANOVAb Model 1 Regression Residual Total Sum of Squares 6.282 106.778 113.060 df 1 98 99 Mean Square 6.282 1.090 F 5.766 Sig. .018a
a. Predictors: (Constant), Ad_usage b. Dependent Variable: Environmentalattitude_dpnd_dropped
Coefficientsa Standardized Unstandardized Coefficients Model 1 (Constant) Ad_usage B 4.769 -.291 Std. Error .385 .121 -.236 Coefficients Beta t 12.398 -2.401 Sig. .000 .018
a. Dependent Variable: Environmentalattitude_dpnd_dropped
-a positive increase in the ad usage has a negative relationship on the environmental attitude
Independent sample T-test
1.
Grouping on the basis of gender:
Page | 35
Group Statistics Gender Responsiblityfortheenvironment_ Male dpnd Female N 79 21 79 21 79 21 Mean 3.6867 3.7857 3.6266 4.1667 3.4937 3.8889 Std. Deviation .74083 .71714 .84909 .48305 .81625 .57090 Std. Error Mean .08335 .15649 .09553 .10541 .09184 .12458
Reflectiveboostofparticipation_dp Male nd Personalinfluences_dpnd Female Male Female
Independent Samples Test Levene's Test for Equality of Variances t-test for Equality of Means 95% Confidence Interval of the Difference Mean F Responsiblityfort Equal variances heenvironment_ assumed dpnd Equal variances not assumed Reflectiveboosto Equal variances fparticipation_dp assumed nd Equal variances not assumed Personalinfluenc Equal variances es_dpnd assumed Equal variances not assumed -2.554 44.28 9 .014 -.39522 .15477 -.70708 -.08335 4.373 .039 -2.084 -3.797 56.56 2 98 .040 -.39522 .18967 -.77161 -.01883 .000 -.54008 .14226 -.82500 -.25517 5.029 .027 -2.791 -.558 32.29 0 98 .006 -.54008 .19354 -.92416 -.15601 .580 -.09901 .17730 -.46004 .26203 .072 Sig. t df 98 tailed) .585 e -.09901 Std. Error e .18071 Lower -.45762 Upper .25961
Sig. (2- Differenc Differenc
.789 -.548
Interpretations:
a) There is a significant difference in the Reflective boost of
participation factor among males and females
Page | 36
b) There is a significant difference in the Personal influence factor among male and female. c) There is no significant difference among the responsibilities towards the environment among male and female.
2.
Grouping based on Marital status
Group Statistics Marital Status N 15 85 15 85 15 85 Mean 3.5167 3.7412 3.5333 3.7765 3.9333 3.5137 Std. Deviation .99762 .67859 .81211 .81469 .76842 .77588 Std. Error Mean .25758 .07360 .20969 .08837 .19841 .08416
Responsiblityfortheenvironment_ Married dpnd Unmarried
Reflectiveboostofparticipation_dp Married nd Personalinfluences_dpnd Unmarried Married Unmarried
Page | 37
Independent Samples Test Levene's Test for Equality of Variances t-test for Equality of Means 95% Confidence Interval of the Difference Std. Mean F Responsiblityfo Equal rtheenvironme variances nt_dpnd assumed Equal variances not assumed Reflectiveboos Equal tofparticipation variances _dpnd assumed Equal variances not assumed Personalinflue Equal nces_dpnd variances assumed Equal variances not assumed 1.947 19.38 6 .066 .41961 .21552 -.03087 .87008 .108 .743 1.934 98 .056 .41961 .21699 -.01101 .85022 - 19.31 1.069 3 .298 -.24314 .22755 -.71887 .23260 .046 .830 1.066 98 .289 -.24314 .22806 -.69571 .20943 -.838 16.36 1 .414 -.22451 .26789 -.79140 .34238 2.578 Sig. .112 t 1.094 df 98 tailed) ce Error ce Lower Upper .18271 Sig. (2- Differen Differen
.277 -.22451
.20520 -.63173
Interpretations:
a) There is no significant difference among Married and Unmarried for
all the factors
3.
Grouping based on Family type
Page | 38
Group Statistics Family type Responsiblityfortheenvironment_ Joint dpnd Nuclear N 15 85 15 85 15 85 Mean 3.8167 3.6882 3.7000 3.7471 3.6889 3.5569 Std. Deviation .72866 .73690 .75119 .82960 .58373 .81713 Std. Error Mean .18814 .07993 .19396 .08998 .15072 .08863
Reflectiveboostofparticipation_dp Joint nd Personalinfluences_dpnd Nuclear Joint Nuclear
Page | 39
Independent Samples Test Levene's Test for Equality of Variances t-test for Equality of Means 95% Confidence Interval of the Difference Std. Mean F Responsiblityfo Equal rtheenvironmen variances t_dpnd assumed Equal variances not assumed Reflectiveboost Equal ofparticipation_ variances dpnd assumed Equal variances not assumed Personalinfluen Equal ces_dpnd variances assumed Equal variances not assumed .755 24.86 1 .457 .13203 .17485 -.22818 .49223 1.667 .200 .598 98 .551 .13203 .22069 -.30593 .56998 -.220 20.51 7 .828 -.04706 .21381 -.49235 .39823 .051 .822 -.205 98 .838 -.04706 .22933 -.50215 .40803 .628 19.40 4 .537 .12843 .20441 -.29881 .55567 .005 Sig. .943 t .623 df 98 tailed) .535 e .12843 Error e Lower Upper .53732 Sig. (2- Differenc Differenc
.20604 -.28046
Interpretations:
a) There is no significant difference among Married and Unmarried for
all the factors.
4.
Grouping based on education type(one way ANOVA)
Page | 40
ANOVA Sum of Squares Responsiblityfortheenvironm Between Groups ent_dpnd Within Groups Total Reflectiveboostofparticipation Between Groups _dpnd Within Groups Total Personalinfluences_dpnd Between Groups Within Groups Total 1.671 49.607 51.278 .741 64.290 65.031 8.898 49.522 58.419 df 4 92 96 4 92 96 4 92 96 2.224 .538 4.133 .004 .185 .699 .265 .900 Mean Square .418 .539 F .775 Sig. .544
Interpretation:
a) Regarding the responsibility for the environment and reflective boost of participation, there wasn’t any significant difference owing to education. b) There was significant difference for the personal influences factor owing to the education
Conclusion
Key findings based interpretations
1. There is a positive relation between attitude towards advertisement
and responsibility towards the environment. Thus if my attitude towards advertisements is positive in general, and I am not cynical about them, then showing green ads will have an impact on the green purchasing behaviour and the relation value is 0.15
2. Ad usage has an effect on the environmental attitude, however the
relation is negative. This states that if I am a person who consults ads before making a purchase, seeing a lot of ads might dilute the seriousness of the cause and thus lessen the environmental attitude.
Page | 41
3. The environmental concern hasn’t gathered enough steam to be
registered yet on the Indian minds. So branding a green product might not be a good investment. After long exposure to green flavour in Indian products, they might grow sensitive to individual brand. Then the responses might tilt towards branding as a effective strategy. 4. Owing to the significant difference in the Reflective boost of participation among males and females, showing different ads catering to male and female ego will have an additional impact on the green strategy of organizations. 5. Owing to the significant difference in the Personal influence factor among male and female, creating differentiation of products for males and females is also going to boost additional sales. 6. Married-Unmarried, and people from nuclear or joint family have the same level of green purchasing behaviour.
7. Education affects the personal influence factor of the green
purchasing behaviour. Thus implementing the green strategy or creation of advertisements should be first done to the educated segment of the society, or cities where the educated class is more e.g. metropolitan cities or showing ads in high end magazines.
Further scope
a) Using the inferences of our project, marketers can check for the
actual difference in the sales after incorporating ads tactically. b) More segmentation can be done in working class depending on the income levels and suggestions based on those segments.
c) The respondents can be more varied, so the future researches can
measure the green purchasing behaviour of young, teenagers, adults and aged.
ANNEXURE
Questionnaire floated for the survey is:
1. Choose your gender – Male/Female
Page | 42
2. Share your age 3. Marital status – Married/Unmarried 4. Education – Passed Board exam/ Undergraduate/Passed graduation/ Pursuing Post graduation/Completed Posta graduation 5. Family type – Nuclear/Joint
(1) Least Important
(2) Somewhat Important
(3) Moderately Important
(4) Highly Important
(5) Most Important
Rate the parameters on the magnitude on which it affects your green purchasing behaviour
1 2 3 4 5 6. My awareness of the environment affects my green purchasing behavior 7. My education influences my green purchasing behavior 8. My concern for the nature affects my green purchasing behavior 9. Current social trends affects my green purchasing behavior 10. My personality affects my green purchasing behavior 11. Peer pressure affects my green purchasing behavior 12. Concern for my own health affects my green purchasing behavior 13. How is cost involved in my green purchasing behavior 14. How does the urge of setting an example for others affect my green purchasing behavior 15. My perception of green products as the most effective and quality products affect my green purchasing behavior 16. The recyclable nature of green products propells my green purchasing behavior 17. Care for future generations affect my green purchasing behavior 18. Conscience compells my green purchasing behavior 19. It's the perception of doing a good thing that affects my green purchasing behavior 20. The opportunity to "show off" is what directs my green purchasing behavior 21. Childhood habits direct my green purchasing behavior 22. Parental influences direct my green purchasing behavior 23. I am not concerned about my green purchasing behavior
Page | 43
24. I think that the whole green concept is a waste of time and resources 25. I think its the responsible part of me that involves me in green purchasing behavior 26. Somewhere I believe its the fear of being out-dated that affects me in green purchasing behavior A1. Buying private brands make me feel good(7 point) A2. I love it when private label brands are available for the product categories I purchase(7 point) A3. For most product categories, the best buy is usually the private label brand(7 point) A4. In general private label brands are poor quality products(7 point) A5. Considering the value of money, I prefer private label brands to national brands(7 point) A6. When I buy a private label brand, I always feel that I a getting a good deal(7 point) A11. I usually purchase brand name products A12. Store brands are of poor quality A13. All brands are about the same B1. Most advertising provides consumers with essential information B2. Most advertising is very annoying B3. Most advertising makes false claims B4. If most advertising was eliminated, consumers would be better off B5. I enjoy most ads B6. Advertising should be more closely regulated B7. Most advertising is intended to deceive rather than to inform consumers B11. To make sure I buy the right product or brand, I often look at the advertisements to see what others are buying and using B12. If I have little experience with a product, I often check with advertisements B13. I often consult advertisements to help choose the best alternative available from a product class B14. I often gather information from advertisements about products before I buy
Page | 44
doc_260111177.doc
The objective of the report is to explore the various factors which influence the green purchasing behaviour of the Indian consumer. Will advertising attitude and ad usage of a person predict his green purchasing behaviour. Will his attitude towards private brands influence his green purchasing behaviour. To give a segmented opinion of the green purchasing behaviour attitude based on their gender, family type, education level etc.
GREEN PURCHASING BEHAVIOUR
Abhishek Vyas (09P124)
Page | 1
Contents
Acknowledgment-----------------------------------------------------------------------------------------------04 1. Introduction a. Green Purchasing---------------------------------------------------------------------------05 b. The current West----------------------------------------------------------------------------05 c. Literature survey----------------------------------------------------------------------------06 d. GPNI: Green Purchasing Network India------------------------------------------------07 e. Reason for choosing this topic------------------------------------------------------------08 f. Differentiation of our project------------------------------------------------------------08
g. Objective and scope of the project------------------------------------------------------08 2. Methodology a. Research questions-------------------------------------------------------------------------10 b. Research Methodology--------------------------------------------------------------------10 c. Survey technique---------------------------------------------------------------------------10
d. Questionnaire -----in
Annexure-------------------------------------------------------------e. Sample-----------------------------------------------------------------------------------------10 3. Results
Page | 2
a. Exploratory Research-----------------------------------------------------------------------11 b. Descriptive Research i) ii) c. Analysis i) ii) iii) Green Purchasing behavior---------------------------------------13 Attitude towards Private label brands-------------------------17 Brand Consciousness----------------------------------------------20 Attitude towards advertisements-------------------------------21 Ad usage--------------------------------------------------------------23 Questionnaire-------------------------------------------------------11 Subjects---------------------------------------------------------------12
iv) v)
d. Results (Variables)
--------------------------------------------------------------------------25 e. Correlation-----------------------------------------------------------------------------------26 f. Regression------------------------------------------------------------------------------------27 g. Independent sample t-test i) ii) Gender----------------------------------------------------------------32 Marital Status-------------------------------------------------------33 Family type-----------------------------------------------------------35
iii)
h. One way ANOVA (education)
------------------------------------------------------------36
Page | 3
4. Conclusion a. Finding based interpretations------------------------------------------------------------37 b. Further Scope--------------------------------------------------------------------------------37 Annexure
Acknowledgement
We thank our colleagues, friends, faculty and other well wishers for their encouraging words and support while doing this project. We also thank
Page | 4
our friends from PGPM, PGPHR and NMP batches, an friends from facebook and orkut who took out their precious time to participate in our survey. We are grateful to Prof. Ajay Kumar Jain, Faculty, Management
Development Institute, Gurgaon for his continuous support and guidance without which this research could not have been fruitful. His help has been of key importance towards the completion of the report. We would also like to thank the creators of PASW software without which the complex analysis wouldn’t have been possible. Finally, we also take this opportunity to appreciate the institute, MDI, for providing this learning and also assisting in infrastructure and administrative work. We are grateful to all the professors for their guidance and support at each step. Their insights and teachings have played a critical role in developing this report.
Abhishek Vyas (09P124) Debasish Jena (09P134) Kalapala Ashwini Prasad(09P146) Narayanan S (09P152) Shweta Bagrecha (09P172) Vishal Gupta(09P179)
INTRODUCTION
Green Purchasing
Page | 5
Environmentally preferable purchasing or green purchasing is the conscious selection and buying of products or services that most effectively minimize their environmental impact over their life cycle from manufacturing to disposal. The products that come under this category are those that conserve energy and water, minimize release of waste and environmentally harmful pollutants, those which can be recycled or reused, etc. Use of biodegradable plastic, bio based fuels, solar and wind power and products using alternative to toxic or hazardous chemicals also constitute green purchasing behaviour. Green purchasing is also about process improvements; for example, consolidating multiple user orders with a given supplier into a single order. This will result in a single delivery, thus reducing shipping costs and carbon emissions. In short green purchasing behaviour is the attitudinal aspect of the consumer to add environmental aspects to price and performance criteria while making a purchase.
The current West
Studies held in Australia (Mobium Group (2008) ‘The LOHAS (Lifestyles of Health and Sustainability) report), Europe and US of A(Lawrence, 1993), have all found out that the market for environmental goods and services has grown significantly in recent years and a number of studies have highlighted increasing consumer interest in the area of more sustainable products and services. Hence providing green products is now the new motto of organizations in order to capture the mind of the consumer. Organizations have already started becoming more conscious and responsible regarding decreasing the carbon footprint of their products as well as their processes. Few organizations like Motorola, IBM, S.C. Johnson, TRW, Nokia, Sony, Ford, Ray-O-Vac, Northern Telecom, Apple Computer, Sun Microsystems, and the Body Shop have shown visibility of strategy in this direction.
Page | 6
Literature survey
The concept of green marketing has evolved over the years. There are basically three stages in which it has evolved.
1. The decade of the late 1980s marked the first stage of green
marketing, when the concept of “green marketing” was newly introduced and discussed in industry (Peattie and Crane, 2005). Owing to the upsurge of this new concept many marketer tried to involve in green marketing in order to generate positive consumer response which would be converted into goodwill, market share and sales. However in spite of reports stating that the environmental problems constituted one of the uppermost public concerns, market growth of these products fell short of expectations.
2. The second stage started off as a consumer backlash. Many
organizations “greenwash”ed the consumers. In order to improve their sales, thus creating cynical attitude of the consumers towards the green concept. Some of the marketing practices which lead to the failure of green marketing during this period are (Peattie and Crane 2005):
a. Green spinning -> Taking a reactive stance of “green”, if
accused of malpractice
b. Green Selling -> taking an opportunistic approach by adding
some green claims to existing products with an intention to boosts profits.
c. Green harvesting -> Becoming enthusiastic about the
environment only when greening would result in cost savings.
d. Entrepreneur marketing -> Developing innovative green
products without actually considering consumer needs
Page | 7
e. Compliance marketing -> Just following the environmental
standards as an opportunity to promote the company’s green credentials rather than actually being involved
3. The evolution of the third stage is just a response to the
anomalies occurring in the second stage. With the implementation of advanced technology, stricter state enforcement on deceptive claims, govt. regulations and incentives and closer scrutiny from various environmental organizations and media many green products have regained confidence in the 2000’s (Gurau and Ranchhod, 2005; Ottoman, 2007). With green and sustainable development as the theme of 21st century development, two trends have been predicted as inevitable in the near future of green marketing. They are:
a) First the concept of an eco friendly approach of doing business
will be pushed into mainstream(Hanas 2007)
b) Second, corporations from developed countries will initiate
international green marketing in order to expand their market, increase their sales and take advantage of the positive image of their green brands established in their domestic markets (Gura?u and Ranchhod, 2005; Johri and Sahasakmontri, 1998; Pugh and Fletcher, 2002).
GPNI: Green Purchasing Network India
GPNI is an evolving network of professionals interested and active in the general area of sustainable consumption and production- more specifically: Green Purchasing and Public Procurement. It is currently a loose informal network of professionals primarily operating as an internet based electronic forum. The objectives of the GPNI are:
Page | 8
1. To create awareness amongst Indian industry and other stakeholders about Green Purchasing and Procurement (GPP) 2. To encourage and facilitate implementation of GPP and Greening Supply Chains (GSC) projects to enhance the competitiveness of the Indian industries.
Reason for choosing this topic
Recent effort by leaders like Al Gore and Dr. R.K. Pachauri, environment has taken a significant portion of our thinking space. We have become more sensitive and responsible for the environment. Hence consumers now look for more sustainable and green products which have low impact on the ecosystem. Thus in order for organizations to survive in this new era of greenism, they have to consider going green as part of their long term strategies mould consumer minds towards the green value of their product and service offerings. India being a developing nation is bound to be the destination of most of the organizations in order to implement their long term strategies. Thus they need to know what are the various factors that affect the green purchasing behaviour of Indian consumers and whether by advertising and branding, can they affect their green purchasing behaviour.
Differentiation of our project
Most of the environment researches have been done in Europe, Australia, America and some parts of Asia. However no much concrete researches have been done for the Indian context. Our project gives insights keeping in mind the Indian consumer.
Objective and scope of the report
Page | 9
Objective:
? Explore the various factors which influence the green purchasing behaviour of the Indian consumer.
? Will advertising attitude and ad usage of a person predict his green
purchasing behaviour ? Will his attitude towards private brands influence his green purchasing behaviour
? To give a segmented opinion of the green purchasing behaviour
attitude based on their gender, family type, education level etc.
Problems faced during the research:
» » Problem of having a larger sample size Lack of environmental research in Indian context
Scope of the project
The scope of the project is to help marketers wanting to boost their sales by introducing green products, by saying whether branding or advertising is going to have any impact on the green purchasing behaviour of the consumer or not. If yes, which segments are more likely to be responsive?
Page | 10
Methodology
Research Questions
1. Does the ad usage of a person predict his green purchasing behaviour? 2. Does the attitude of a person towards private brands influence his green purchasing behaviour?
3. Do gender, family type, education and marital status affect the
green purchasing behaviour?
Research Methodology
We propose to conduct the research as following1. Do an exploratory research by opinions about the topic from people.
2. Conduct a conclusive research(descriptive) by floating survey
among MBA students, undergraduates, working professionals to validate our findings
3. From the collected data try to establish the relationship between
advertising attitude and branding attitude with green purchasing behaviour
Survey Technique
Page | 11
Data was collected in various ways: - Through online filling up of survey - By approaching students at NMP hostel and PGPM hostel of MDI
Sample
The sample constituted mostly of students pursuing MBA at Management Development Institute Gurgaon, in addition to student of other colleges, friends and relatives in order to get a varied sample
RESULTS
Exploratory research
An exploratory was conducted in a hostel of Management Development institute, 30 MBA students were asked to write 5 points each, by which we arrived at around 121 points. Most of the points were overlapping. Hence after adding the cumulative count of each distinct point, we considered 21 variables of green purchasing behaviour.
Descriptive research
Questionnaire
The questionnaire consisted of 6 parts. They were:
1. Control variables – These factors were taken to help us develop
an insightful view of the background of the respondents. Questions asked in this category were age, gender, family type, education and marital status.
2. Green purchasing behaviour – This questionnaire consisted of 21
questions collected from the exploratory research previously done. All the questions in this part of the questionnaire asked the
Page | 12
respondent to rate the variable on a 5-point Likert scale e.g. my education influences my green purchasing behaviour?
3. Attitude towards private brands – This questionnaire is a scale
borrowed from Marketing Scales Handbook. This composed of six 7point Likert-type statements that measure the consumer attitude towards private distributor brands. Not only does the scale capture the consumer’s opinion of the general quality level of private brands but also provides a sense of consumers tendency to buy them or not. E.g. In general private label brands are poor-quality products.
4. Brand consciousness – This questionnaire is a scale borrowed
from Marketing Scales Handbook. A three 5-point Likert-type summated ratings scale measuring the degree to which a person expresses a desire to buy “brand name products”. The implication is that the consultation prefers nationally known brands rather than private distributor or generic goods. E.g. I usually purchase brand name products
5. Attitude towards Advertising – This questionnaire is a scale
borrowed from Marketing Scales Handbook. Five 5-point Likert-type statements are used to measure consumer attitudes about advertising in general. E.g. Most advertising is very annoying.
6. Ad Usage - This questionnaire is a scale borrowed from Marketing
Scales Handbook. This scale is composed of four, 5-point Likert-type statements measuring the extent to which a consumer reports consulting advertisements before making purchase decisions in order to make better decisions.
Subjects
A total of 100 respondents participated. Out of them 79 were males and 21 were females. The age bracket of the respondents ranged from 16 from 52. However majority (89%) belonged to the age group of 21 – 27. 15 people among the respondents were married and the rest were unmarried. The education status also varied with 14 people having completed their post graduation, 18 respondents had passed graduation,
Page | 13
2 were still undergraduates and 65 were still pursuing post graduation. Of the respondents 15 were from joint family and the remaining 85 were from nuclear families.
ANALYSIS
i. Identifying the factors underlying the green purchasing behaviour....
The 100 responses to the green purchasing behaviour questionnaire were taken. They were subjected to an initial screening of Descriptive analysis, where a screening criterion of mean value of 3.3 was set. Based upon this criteria 5 variables were rejected. They were GPB6, GPB15, GPB16, GPB17, GPB21.
Page | 14
Descriptive Statistics Std. N Statistic GPB1 GPB2 GPB3 GPB4 GPB5 GPB6 GPB7 GPB8 GPB9 GPB10 GPB11 GPB12 GPB13 GPB14 GPB15 GPB16 GPB17 (r)GPB18 (r)GPB19 GPB20 GPB21 Valid N (listwise) 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 Minimum Maximum Statistic 2.00 2.00 1.00 1.00 1.00 1.00 2.00 1.00 1.00 1.00 2.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 Statistic 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 Mean Statistic 3.8400 4.0500 4.1200 3.4500 3.8400 2.7900 3.9000 3.6500 3.3000 3.5300 3.8000 3.7400 3.8300 3.7600 2.3100 3.2800 3.1000 3.7000 4.0600 3.7200 2.3400 Deviation Statistic .84948 .78335 .87939 1.14040 .86129 1.20851 .92660 1.04809 1.21854 1.00960 .94281 1.07891 1.03529 1.03592 1.26087 1.11988 1.18492 1.21023 1.14433 .87709 1.11210 Skewness Kurtosis
Statistic Std. Error Statistic Std. Error -.291 -.732 -.966 -.375 -.651 .099 -.731 -.596 -.359 -.444 -.472 -.594 -.821 -1.003 .595 -.400 -.123 -.726 -.945 -.792 .458 .241 .241 .241 .241 .241 .241 .241 .241 .241 .241 .241 .241 .241 .241 .241 .241 .241 .241 .241 .241 .241 -.540 .524 .890 -.571 .473 -1.076 -.147 -.047 -.896 -.273 -.594 -.340 .218 .776 -.783 -.541 -.896 -.346 -.288 .851 -.648 .478 .478 .478 .478 .478 .478 .478 .478 .478 .478 .478 .478 .478 .478 .478 .478 .478 .478 .478 .478 .478
(r) Means that question was reverse coded; yellow were removed Then a factor analysis was done on the selected 16 variables to decide upon the factors underlying the Green Purchasing behaviour of the Indian consumer. Below is the output of the factor analysis
Page | 15
KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Bartlett's Test of Sphericity Approx. Chi-Square df Sig. .754 542.643 120 .000
The value of KMO is more than 0.5. Thus the degree of common variance among the eleven variables is "middling" bordering on "meritorious". If a factor analysis is conducted, the factors extracted will account for fairly decent amount of variance. Also the significance level of Bartlett’s test is very less little than 0.01, which is a good sign. After establishing the adequateness of our sample, we proceed to perform the factor analysis. The extraction was done by the principal components method. For rotation in order to determine the factors, we chose the Varimax rotation. In order to assign each variable individually under distinct factor, we suppressed the coefficients below an absolute value of 0.55 which corresponded to the sample size of 100. Below is the rotated component matrix which was generated:
Page | 16
Rotated Component Matrixa Component 1 GPB1 GPB2 GPB3 GPB4 GPB5 GPB7 GPB8 GPB9 GPB10 GPB11 GPB12 GPB13 GPB14 (r)GPB18 (r)GPB19 GPB20 .811 .688 .850 .823 .738 .614 .836 .552 .578 .926 .719 .598 2 3 4 5
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 12 iterations.
Now the 5 factors taken together account for 65.434 % of the total variance. This is a fair representation of the total variance present.
Page | 17
Total Variance Explained Extraction Sums of Squared Initial Eigenvalues Comp onent 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 Total 4.854 1.893 1.314 1.289 1.119 .916 .822 .652 .614 .525 .475 .411 .379 .303 .226 .206 % of Variance 30.336 11.833 8.214 8.056 6.994 5.725 5.137 4.077 3.836 3.282 2.969 2.571 2.370 1.896 1.413 1.290 Cumulative % 30.336 42.169 50.383 58.439 65.434 71.158 76.295 80.372 84.208 87.491 90.459 93.031 95.401 97.297 98.710 100.000 Total 4.854 1.893 1.314 1.289 1.119 Loadings % of Variance 30.336 11.833 8.214 8.056 6.994 Cumulative % 30.336 42.169 50.383 58.439 65.434 Total 2.817 2.323 2.072 2.002 1.256 Rotation Sums of Squared Loadings % of Variance 17.605 14.517 12.949 12.515 7.848 Cumulative % 17.605 32.122 45.071 57.585 65.434
Extraction Method: Principal Component Analysis.
Analysis – Normal observation showed the emergence of 5 factors.
However we chose not to club a single variable to make a factor. Hence GPB8 was dropped and so was factor 5. So we are left with 4 factors. Now in order to form more meaningful inference of the factors we suggest names to these factors. The factors that we came up with are:
1. Factor 1(Responsiblity for the environment) (Cronbach’s Alpha =.702 )-> a. b. c. d. GPB1 (My awareness of the environment affects my green purchasing behavior) GPB4 (Current social trends affects my green purchasing behavior) GPB11 (The recyclable nature of green products propells my green purchasing behavior) GPB12 (Care for future generations affect my green purchasing behavior) Page | 18
2. Factor2 (Reflective boost of participation) (Cronbach’s Alpha =.613 ) -> a. GPB14 (It's the perception of doing a good thing that affects my green purchasing behavior) b. GPB20 (I think its the responsible part of me that involves me in green purchasing behaviour) 3. Factor3(Environmental attitude) (Cronbach’s Alpha =.785 ) -> a. GPB18 (I am not concerned about my green purchasing behavior) b. GPB19 (I think that the whole green concept is a waste of time and resources) 4. Factor 4(Personal influences) (Cronbach’s Alpha = .597) -> a. GPB7 (Concern for my own health affects my green purchasing behavior) b. GPB9 (How does the urge of setting an example for others affect my green purchasing behavior) c. GPB10 (My perception of green products as the most effective and quality products affect my green purchasing behaviour) In order to confirm our findings from the factor analysis, we should calculate the reliability for each factor, and the reliability of the construct. We do this to be confident whether the variable measure the same thing or idea as purported by the factor and whether the factors measure the same thing as the construct. This is called construct reliability. We measure the reliability by calculating the cronbach’s alpha. Individual cronbach’s alpha is mentioned beside the factors above. A good value of cronbach’s alpha is 0.7 -0.8. Very high cronbach’s alpha tells that the items are highly correlated, which might be due to considering the same idea. However a value of 0.6-0.7 is also acceptable. In or case all our factors except factor 4 have values above 0.6, and factors 4 has approximately 0.6. Now in order to check the construct reliability, we calculate the cronbach’s alpha for the factors. Below is the output table:
Reliability Statistics Cronbach's Alpha .572 N of Items 4
An item-total statistics table gives us an idea of what our alpha would be like if an item were deleted. As the cronbach’s alpha, taking 4 items at a time results in a value less than 0.6, we need to resort to the item-total table. From the table Page | 19
we see that if we drop the fourth factor i.e. environmental attitude, we would be more confident that the factors essentially measure the green purchasing behaviour. A high inter-variable cronbach’s alpha for the factors means that the questions asked were relevant and related to the factor environmental attitude, however the factor was not properly defining the construct of green purchasing behaviour. Now since the 4th factor (Personal influences) is not far away from 0.6(0.597), we keep the factor assuming the sample size to be the cause of the slightly less value.
Item-Total Statistics
Scale Mean if Item Deleted Responsiblityfortheenvironment_d pnd Reflectiveboostofparticipation_dp nd Environmentalattitude_dpnd Personalinfluences_dpnd 11.0242 11.3275 11.1642 11.1967
Scale Variance if Item Deleted 3.449
Corrected ItemTotal Correlation .440
Cronbach's Alpha if Item Deleted .446
3.065
.510
.376
3.157 3.660
.233 .302
.636 .539
Hence now we are left with three factors which affect the green purchasing behaviour of the Indian consumer. They are 1. Responsiblity for the environment 2. Reflective boost of participation 3. Personal influences
ii. Attitude towards Private label brands
We perform the same procedures as we did for the Green purchasing behavior.Below is the descriptive analysis
Page | 20
Descriptive Statistics N Att twrd pvt lbl brnd1 Att twrd pvt lbl brnd2 Att twrd pvt lbl brnd3 (r)Att twrd pvt lbl brnd4 Att twrd pvt lbl brnd5 Att twrd pvt lbl brnd6 Valid N (listwise) 100 100 100 100 100 100 100 Minimum 1.00 1.00 1.00 1.00 1.00 1.00 Maximum 7.00 7.00 7.00 7.00 7.00 7.00 Mean 4.0700 4.1700 4.0400 4.6600 4.0400 4.0200 Std. Deviation 1.65300 1.53777 1.59494 1.53886 1.42786 1.40691
As the means are not wide apart, we keep all the variables for the factor analysis.
KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Bartlett's Test of Sphericity Approx. Chi-Square df Sig. .822 257.187 15 .000
A KMO value is 0.822 is a good sign of the adequacy of the sample. Also in the total variance explained table, the 2 factors taken together account for 72.938% of the total variance. This is a fair representation of the total variance present.
Page | 21
Total Variance Explained Extraction Sums of Squared Com pone nt 1 2 3 4 5 6 Total 3.356 1.021 .581 .515 .311 .216 Initial Eigenvalues % of Variance 55.928 17.010 9.691 8.586 5.184 3.602 Cumulative % 55.928 72.938 82.629 91.215 96.398 100.000 Total 3.356 1.021 Loadings % of Variance 55.928 17.010 Cumulative % 55.928 72.938 Total 3.331 1.046 Rotation Sums of Squared Loadings % of Variance 55.509 17.429 Cumulative % 55.509 72.938
Extraction Method: Principal Component Analysis.
Hence we proceed with the rotated component matrix table. Given below is the table.
Rotated Component Matrixa Component 1 Att twrd pvt lbl brnd2 Att twrd pvt lbl brnd1 Att twrd pvt lbl brnd3 Att twrd pvt lbl brnd6 Att twrd pvt lbl brnd5 (r)Att twrd pvt lbl brnd4 .876 .864 .856 .745 .724 .977 2
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 3 iterations.
Analysis - This states that except variable 4, all other variables can be
clubbed into a factor. Variable 4 is thus dropped because of its singularity in the 2nd factor. Hence only one factor emerges out of the factor analysis. This factor is conveniently known as:
Page | 22
1. Factor 1(Attitude towards the private label brand) (Cronbach’s Alpha =.875 ) a) Att twrd pvt lbl brnd1 -> Buying private brands make me feel
good
b) Att twrd pvt lbl brnd2 -> I love it when private label brands are
available for the product categories I purchase
c) Att twrd pvt lbl brnd3 -> For most product categories, the best
buy is usually the private label brand
d) Att twrd pvt lbl brnd5 -> Considering the value of money, I prefer
private label brands to national brands
e) Att twrd pvt lbl brnd6 -> When I buy a private label brand, I
always feel that I a getting a good deal
Reliability Statistics Cronbach's Alpha .875 N of Items 5
iii.
Brand Consciousness
Given below are the various tables of output of the same steps undertaken
Descriptive Statistics N Brnd conscious1 (r)Brnd conscious2 (r)Brnd conscious3 Valid N (listwise) 100 100 100 100 Minimum 1.00 1.00 1.00 Maximum 5.00 5.00 5.00 Mean 3.6600 3.3000 3.4000 Std. Deviation 1.02711 .90453 1.11916
KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Bartlett's Test of Sphericity Approx. Chi-Square df Sig. .499 13.398 3 .004
Page | 23
Total Variance Explained Extraction Sums of Squared Com pone nt 1 2 3 Total 1.359 1.000 .641 Initial Eigenvalues % of Variance 45.297 33.333 21.370 Cumulative % 45.297 78.630 100.000 Total 1.359 1.000 Loadings % of Variance 45.297 33.333 Cumulative % 45.297 78.630 Total 1.357 1.002 Rotation Sums of Squared Loadings % of Variance 45.218 33.412 Cumulative % 45.218 78.630
Extraction Method: Principal Component Analysis.
Reliability Statistics Cronbach's Alphaa -.334 a. The value is negative due to a negative average covariance among items. This violates reliability model assumptions. You may want to check item codings. N of Items 3
Analysis - From the above tables we interpret that the KMO value of .
499 is not good. Though the variances explained by the factors explain 78.63% of the total variance, yet the cronbach’s alpha is too low and negative. Therefore due to these issues, we drop this factor and the scale for consideration as the respondents were not able to correlate the construct with the scale.
iv.
Attitude towards advertisement
Given below are the various tables of output of the same steps undertaken
Page | 24
Descriptive Statistics N (r)Atti twrds advert1 Atti twrds advert2 Atti twrds advert3 Atti twrds advert4 (r)Atti twrds advert5 Atti twrds advert6 Atti twrds advert7 Valid N (listwise) 100 100 100 100 100 100 100 100 Minimum 1.00 1.00 1.00 1.00 1.00 1.00 1.00 Maximum 5.00 5.00 5.00 5.00 5.00 5.00 5.00 Mean 3.3700 3.1200 3.5500 2.8100 2.7700 3.7000 3.6000 Std. Deviation 1.02154 1.20839 1.03840 1.26886 1.02351 1.14150 1.07309
KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Bartlett's Test of Sphericity Approx. Chi-Square df Sig. .593 136.992 21 .000
Total Variance Explained Extraction Sums of Squared Com pone nt 1 2 3 4 5 6 7 Total 2.346 1.335 1.207 .761 .554 .488 .308 Initial Eigenvalues % of Variance 33.520 19.078 17.248 10.877 7.915 6.969 4.393 Cumulative % 33.520 52.598 69.846 80.723 88.637 95.607 100.000 Total 2.346 1.335 1.207 Loadings % of Variance 33.520 19.078 17.248 Cumulative % 33.520 52.598 69.846 Total 1.866 1.711 1.313 Rotation Sums of Squared Loadings % of Variance 26.651 24.437 18.758 Cumulative % 26.651 51.088 69.846
Extraction Method: Principal Component Analysis.
Page | 25
Rotated Component Matrixa Component 1 (r)Atti twrds advert5 Atti twrds advert4 Atti twrds advert2 Atti twrds advert6 Atti twrds advert7 (r)Atti twrds advert1 Atti twrds advert3 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 7 iterations. .787 .728 .710 .742 .736 .902 .583 2 3
Factor 1
Reliability Statistics Cronbach's Alpha .625 N of Items 3
Factor 2
Reliability Statistics Cronbach's Alpha .437 N of Items 2
Factor 3
Reliability Statistics Cronbach's Alpha .452 N of Items 2
The construct reliability is:
Page | 26
Reliability Statistics Cronbach's Alpha .466 N of Items 3
Analysis - Owing to the low cronbach’s alpha we reject the construct
and take simply the factor 1 in our experiment. Thus the factor identified was:
1. Factor 1(Attitude towards advertisement)( Cronbach's Alpha =
0.625) a) Most advertising is very annoying b) If most advertising was eliminated, consumers would be better off
c) I enjoy most ads(r)
v. Ad Usage
Given below are the various tables of output of the same steps undertaken
Descriptive Statistics N Ad usage1 Ad usage2 Ad usage3 Ad usage4 Valid N (listwise) 100 100 100 100 100 Minimum 1.00 1.00 1.00 1.00 Maximum 5.00 5.00 5.00 5.00 Mean 2.9400 3.1300 3.0200 3.1300 Std. Deviation 1.08078 1.06983 1.10078 1.06035
Page | 27
KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Bartlett's Test of Sphericity Approx. Chi-Square df Sig. .763 137.301 6 .000
Total Variance Explained Compo nent 1 2 3 4 Total 2.585 .661 .401 .353 Initial Eigenvalues % of Variance 64.614 16.515 10.034 8.837 Cumulative % 64.614 81.129 91.163 100.000 Extraction Sums of Squared Loadings Total 2.585 % of Variance 64.614 Cumulative % 64.614
Extraction Method: Principal Component Analysis.
Component Matrixa Component 1 Ad usage3 Ad usage2 Ad usage1 Ad usage4 .851 .841 .761 .759
Extraction Method: Principal Component Analysis. a. 1 components extracted. Reliability Statistics Cronbach's Alpha .816 N of Items 4
Analysis - Owing to the KMO and Bartlett’s value, we move ahead with
the factor analysis alpha we accept the construct and take simply the
Page | 28
factor 1 calculated in our experiment. The factor is reliable as the variables in the factor give a cronbach’s alpha value of 0.816 Thus the factor identified was: 1. Factor 1(Ad Usage)( Cronbach's Alpha = 0.816)
a) To make sure I buy the right product or brand, I often look at the
advertisements to see what others are buying and using. b) If I have little experience with a product, I often check with advertisements c) I often consult advertisements to help choose the best alternative available from a product class d) I often gather information from advertisements about products before I buy
Results
Dependent variables
1. Responsibility for the environment
2. Reflective boost of participation 3. Personal influences
Independent variables
1. Attitude towards the private label brand 2. Attitude towards Advertisement 3. Ad usage
Correlation
In order to check predictability we do a 6 x 6(3 ind + 3 dep) correlation matrix to check for the amount of correlation between all the variables. Below is the correlation matrix:
Page | 29
Correlations Responsiblit Reflectiveb yfortheenvir oostofpartici Personalinfl onment_dp pation_dpn uences_dpn atttwrdpvtlbl Ad_attitud Ad_usag nd Responsiblityforthee Pearson nvironment_dpnd Correlation Sig. (2-tailed) N Reflectiveboostofpart Pearson icipation_dpnd Correlation Sig. (2-tailed) N Personalinfluences_ Pearson dpnd Correlation Sig. (2-tailed) N atttwrdpvtlblbrnd_ind Pearson Correlation Sig. (2-tailed) N Ad_attitude Pearson Correlation Sig. (2-tailed) N Ad_usage Pearson Correlation Sig. (2-tailed) N .718 100 .192 100 .651 100 .086 100 .034 100 100 .071 100 .037 .811 100 .131 .257 100 .046 .731 100 .172 100 -.212* .034 100 1 .519 100 .181 .748 100 .024 .546 100 .114 100 .035 .731 100 1 .086 100 -.212* .000 100 -.065 .000 100 .032 100 -.061 .546 100 1 .257 100 .035 .651 100 .172 .000 100 .360** 100 .350** .000 100 1 .748 100 -.061 .811 100 .114 .192 100 .046 100 .397** .000 100 1 .000 100 .350** .519 100 .032 .071 100 .024 .718 100 .131 1 d .397** d .360** brnd_ind -.065 e .181 e .037
**. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed).
The correlation matrix shows that:
1. The correlation between the dependent variables is high, thus
establishing the validity of our construct.
Page | 30
2. There is a decent correlation between Attitude towards the
environment and responsibility for the environment at 93% 3. There is not significant co-relation between the independent and dependent variables
Regression
1. Regression between the independent variables and attitude towards private brands
Model Summary Adjusted R Model 1 R .215a R Square .046 Square .017 Std. Error of the Estimate .72735
a. Predictors: (Constant), atttwrdpvtlblbrnd_ind, Ad_attitude, Ad_usage
ANOVAb Model 1 Regression Residual Total Sum of Squares 2.469 50.788 53.257 df 3 96 99 Mean Square .823 .529 F 1.556 Sig. .205a
a. Predictors: (Constant), atttwrdpvtlblbrnd_ind, Ad_attitude, Ad_usage b. Dependent Variable: Responsiblityfortheenvironment_dpnd
Coefficientsa Standardized Unstandardized Coefficients Model 1 (Constant) Ad_attitude Ad_usage atttwrdpvtlblbrnd_ind B 3.182 .169 .081 -.052 Std. Error .439 .085 .088 .060 .205 .095 -.089 Coefficients Beta t 7.242 2.000 .918 -.875 Sig. .000 .048 .361 .384
a. Dependent Variable: Responsiblityfortheenvironment_dpnd
Page | 31
Analysis - We see that the adjusted R square has a low value for the
model. The ANOVA analysis is also not significant. Therefore we reject the model. However a bit more looking will hint us that the relation between attitude towards advertisement and responsibility towards the environment. Regression between these factors shows a slope of .15 and a constant value of 3.272. The significance level of the values is 93%
Coefficientsa Standardized Unstandardized Coefficients Model 1 (Constant) Ad_attitude B 3.272 .150 Std. Error .249 .082 .181 Coefficients Beta t 13.124 1.825 Sig. .000 .071
a. Dependent Variable: Responsiblityfortheenvironment_dpnd
2.
Regression between the independent variables and Reflective boost of participation
Model Summary Adjusted R Model 1 R .142a R Square .020 Square -.010 Std. Error of the Estimate .81914
a. Predictors: (Constant), Ad_usage, atttwrdpvtlblbrnd_ind, Ad_attitude
ANOVAb Model 1 Regression Residual Total Sum of Squares 1.325 64.415 65.740 df 3 96 99 Mean Square .442 .671 F .658 Sig. .580a
a. Predictors: (Constant), Ad_usage, atttwrdpvtlblbrnd_ind, Ad_attitude b. Dependent Variable: Reflectiveboostofparticipation_dpnd
Page | 32
Coefficientsa Standardized Unstandardized Coefficients Model 1 (Constant) Ad_attitude atttwrdpvtlblbrnd_ind Ad_usage B 3.171 .050 .004 .134 Std. Error .495 .095 .067 .099 .054 .006 .142 Coefficients Beta t 6.409 .522 .060 1.349 Sig. .000 .603 .953 .181
a. Dependent Variable: Reflectiveboostofparticipation_dpnd
Analysis - Poor regression coefficients, low significance of them and low
adjusted R square values suggest that this regression is not valid.
3. Regression between the independent variables and Reflective boost of participation
Model Summary Adjusted R Model 1 R .157a R Square .025 Square -.006 Std. Error of the Estimate .78779
a. Predictors: (Constant), Ad_usage, atttwrdpvtlblbrnd_ind, Ad_attitude
ANOVAb Model 1 Regression Residual Total Sum of Squares 1.500 59.579 61.079 df 3 96 99 Mean Square .500 .621 F .806 Sig. .494a
a. Predictors: (Constant), Ad_usage, atttwrdpvtlblbrnd_ind, Ad_attitude b. Dependent Variable: Personalinfluences_dpnd
Page | 33
Coefficientsa Standardized Unstandardized Coefficients Model 1 (Constant) Ad_attitude atttwrdpvtlblbrnd_ind Ad_usage B 3.189 .121 -.051 .080 Std. Error .476 .092 .065 .095 .136 -.081 .089 Coefficients Beta t 6.701 1.315 -.790 .844 Sig. .000 .192 .432 .401
a. Dependent Variable: Personalinfluences_dpnd
Analysis - Here also poor significance values of R square and
ANOVA test leads us to conclude that the regression is invalid.
4.
Regression b/w independent variables and the dropped factor Environmental attitude
ANOVAb Model 1 Regression Residual Total Sum of Squares 9.503 103.557 113.060 df 3 96 99 Mean Square 3.168 1.079 F 2.936 Sig. .037a
a. Predictors: (Constant), Ad_usage, atttwrdpvtlblbrnd_ind, Ad_attitude b. Dependent Variable: Environmentalattitude_dpnd_dropped
Coefficientsa Standardized Unstandardized Coefficients Model 1 (Constant) Ad_attitude atttwrdpvtlblbrnd_ind Ad_usage B 5.325 -.021 -.145 -.260 Std. Error .627 .121 .085 .126 -.018 -.169 -.210 Coefficients Beta t 8.487 -.177 -1.701 -2.068 Sig. .000 .860 .092 .041
a. Dependent Variable: Environmentalattitude_dpnd_dropped
Page | 34
Analysis - A strong significance level of 96% between Environmental
attitude and ad usage makes us conclude that ad usage has an effect on the environmental attitude. Individually establishing the relationship between the factors, we see that ANOVAb Model 1 Regression Residual Total Sum of Squares 6.282 106.778 113.060 df 1 98 99 Mean Square 6.282 1.090 F 5.766 Sig. .018a
a. Predictors: (Constant), Ad_usage b. Dependent Variable: Environmentalattitude_dpnd_dropped
Coefficientsa Standardized Unstandardized Coefficients Model 1 (Constant) Ad_usage B 4.769 -.291 Std. Error .385 .121 -.236 Coefficients Beta t 12.398 -2.401 Sig. .000 .018
a. Dependent Variable: Environmentalattitude_dpnd_dropped
-a positive increase in the ad usage has a negative relationship on the environmental attitude
Independent sample T-test
1.
Grouping on the basis of gender:
Page | 35
Group Statistics Gender Responsiblityfortheenvironment_ Male dpnd Female N 79 21 79 21 79 21 Mean 3.6867 3.7857 3.6266 4.1667 3.4937 3.8889 Std. Deviation .74083 .71714 .84909 .48305 .81625 .57090 Std. Error Mean .08335 .15649 .09553 .10541 .09184 .12458
Reflectiveboostofparticipation_dp Male nd Personalinfluences_dpnd Female Male Female
Independent Samples Test Levene's Test for Equality of Variances t-test for Equality of Means 95% Confidence Interval of the Difference Mean F Responsiblityfort Equal variances heenvironment_ assumed dpnd Equal variances not assumed Reflectiveboosto Equal variances fparticipation_dp assumed nd Equal variances not assumed Personalinfluenc Equal variances es_dpnd assumed Equal variances not assumed -2.554 44.28 9 .014 -.39522 .15477 -.70708 -.08335 4.373 .039 -2.084 -3.797 56.56 2 98 .040 -.39522 .18967 -.77161 -.01883 .000 -.54008 .14226 -.82500 -.25517 5.029 .027 -2.791 -.558 32.29 0 98 .006 -.54008 .19354 -.92416 -.15601 .580 -.09901 .17730 -.46004 .26203 .072 Sig. t df 98 tailed) .585 e -.09901 Std. Error e .18071 Lower -.45762 Upper .25961
Sig. (2- Differenc Differenc
.789 -.548
Interpretations:
a) There is a significant difference in the Reflective boost of
participation factor among males and females
Page | 36
b) There is a significant difference in the Personal influence factor among male and female. c) There is no significant difference among the responsibilities towards the environment among male and female.
2.
Grouping based on Marital status
Group Statistics Marital Status N 15 85 15 85 15 85 Mean 3.5167 3.7412 3.5333 3.7765 3.9333 3.5137 Std. Deviation .99762 .67859 .81211 .81469 .76842 .77588 Std. Error Mean .25758 .07360 .20969 .08837 .19841 .08416
Responsiblityfortheenvironment_ Married dpnd Unmarried
Reflectiveboostofparticipation_dp Married nd Personalinfluences_dpnd Unmarried Married Unmarried
Page | 37
Independent Samples Test Levene's Test for Equality of Variances t-test for Equality of Means 95% Confidence Interval of the Difference Std. Mean F Responsiblityfo Equal rtheenvironme variances nt_dpnd assumed Equal variances not assumed Reflectiveboos Equal tofparticipation variances _dpnd assumed Equal variances not assumed Personalinflue Equal nces_dpnd variances assumed Equal variances not assumed 1.947 19.38 6 .066 .41961 .21552 -.03087 .87008 .108 .743 1.934 98 .056 .41961 .21699 -.01101 .85022 - 19.31 1.069 3 .298 -.24314 .22755 -.71887 .23260 .046 .830 1.066 98 .289 -.24314 .22806 -.69571 .20943 -.838 16.36 1 .414 -.22451 .26789 -.79140 .34238 2.578 Sig. .112 t 1.094 df 98 tailed) ce Error ce Lower Upper .18271 Sig. (2- Differen Differen
.277 -.22451
.20520 -.63173
Interpretations:
a) There is no significant difference among Married and Unmarried for
all the factors
3.
Grouping based on Family type
Page | 38
Group Statistics Family type Responsiblityfortheenvironment_ Joint dpnd Nuclear N 15 85 15 85 15 85 Mean 3.8167 3.6882 3.7000 3.7471 3.6889 3.5569 Std. Deviation .72866 .73690 .75119 .82960 .58373 .81713 Std. Error Mean .18814 .07993 .19396 .08998 .15072 .08863
Reflectiveboostofparticipation_dp Joint nd Personalinfluences_dpnd Nuclear Joint Nuclear
Page | 39
Independent Samples Test Levene's Test for Equality of Variances t-test for Equality of Means 95% Confidence Interval of the Difference Std. Mean F Responsiblityfo Equal rtheenvironmen variances t_dpnd assumed Equal variances not assumed Reflectiveboost Equal ofparticipation_ variances dpnd assumed Equal variances not assumed Personalinfluen Equal ces_dpnd variances assumed Equal variances not assumed .755 24.86 1 .457 .13203 .17485 -.22818 .49223 1.667 .200 .598 98 .551 .13203 .22069 -.30593 .56998 -.220 20.51 7 .828 -.04706 .21381 -.49235 .39823 .051 .822 -.205 98 .838 -.04706 .22933 -.50215 .40803 .628 19.40 4 .537 .12843 .20441 -.29881 .55567 .005 Sig. .943 t .623 df 98 tailed) .535 e .12843 Error e Lower Upper .53732 Sig. (2- Differenc Differenc
.20604 -.28046
Interpretations:
a) There is no significant difference among Married and Unmarried for
all the factors.
4.
Grouping based on education type(one way ANOVA)
Page | 40
ANOVA Sum of Squares Responsiblityfortheenvironm Between Groups ent_dpnd Within Groups Total Reflectiveboostofparticipation Between Groups _dpnd Within Groups Total Personalinfluences_dpnd Between Groups Within Groups Total 1.671 49.607 51.278 .741 64.290 65.031 8.898 49.522 58.419 df 4 92 96 4 92 96 4 92 96 2.224 .538 4.133 .004 .185 .699 .265 .900 Mean Square .418 .539 F .775 Sig. .544
Interpretation:
a) Regarding the responsibility for the environment and reflective boost of participation, there wasn’t any significant difference owing to education. b) There was significant difference for the personal influences factor owing to the education
Conclusion
Key findings based interpretations
1. There is a positive relation between attitude towards advertisement
and responsibility towards the environment. Thus if my attitude towards advertisements is positive in general, and I am not cynical about them, then showing green ads will have an impact on the green purchasing behaviour and the relation value is 0.15
2. Ad usage has an effect on the environmental attitude, however the
relation is negative. This states that if I am a person who consults ads before making a purchase, seeing a lot of ads might dilute the seriousness of the cause and thus lessen the environmental attitude.
Page | 41
3. The environmental concern hasn’t gathered enough steam to be
registered yet on the Indian minds. So branding a green product might not be a good investment. After long exposure to green flavour in Indian products, they might grow sensitive to individual brand. Then the responses might tilt towards branding as a effective strategy. 4. Owing to the significant difference in the Reflective boost of participation among males and females, showing different ads catering to male and female ego will have an additional impact on the green strategy of organizations. 5. Owing to the significant difference in the Personal influence factor among male and female, creating differentiation of products for males and females is also going to boost additional sales. 6. Married-Unmarried, and people from nuclear or joint family have the same level of green purchasing behaviour.
7. Education affects the personal influence factor of the green
purchasing behaviour. Thus implementing the green strategy or creation of advertisements should be first done to the educated segment of the society, or cities where the educated class is more e.g. metropolitan cities or showing ads in high end magazines.
Further scope
a) Using the inferences of our project, marketers can check for the
actual difference in the sales after incorporating ads tactically. b) More segmentation can be done in working class depending on the income levels and suggestions based on those segments.
c) The respondents can be more varied, so the future researches can
measure the green purchasing behaviour of young, teenagers, adults and aged.
ANNEXURE
Questionnaire floated for the survey is:
1. Choose your gender – Male/Female
Page | 42
2. Share your age 3. Marital status – Married/Unmarried 4. Education – Passed Board exam/ Undergraduate/Passed graduation/ Pursuing Post graduation/Completed Posta graduation 5. Family type – Nuclear/Joint
(1) Least Important
(2) Somewhat Important
(3) Moderately Important
(4) Highly Important
(5) Most Important
Rate the parameters on the magnitude on which it affects your green purchasing behaviour
1 2 3 4 5 6. My awareness of the environment affects my green purchasing behavior 7. My education influences my green purchasing behavior 8. My concern for the nature affects my green purchasing behavior 9. Current social trends affects my green purchasing behavior 10. My personality affects my green purchasing behavior 11. Peer pressure affects my green purchasing behavior 12. Concern for my own health affects my green purchasing behavior 13. How is cost involved in my green purchasing behavior 14. How does the urge of setting an example for others affect my green purchasing behavior 15. My perception of green products as the most effective and quality products affect my green purchasing behavior 16. The recyclable nature of green products propells my green purchasing behavior 17. Care for future generations affect my green purchasing behavior 18. Conscience compells my green purchasing behavior 19. It's the perception of doing a good thing that affects my green purchasing behavior 20. The opportunity to "show off" is what directs my green purchasing behavior 21. Childhood habits direct my green purchasing behavior 22. Parental influences direct my green purchasing behavior 23. I am not concerned about my green purchasing behavior
Page | 43
24. I think that the whole green concept is a waste of time and resources 25. I think its the responsible part of me that involves me in green purchasing behavior 26. Somewhere I believe its the fear of being out-dated that affects me in green purchasing behavior A1. Buying private brands make me feel good(7 point) A2. I love it when private label brands are available for the product categories I purchase(7 point) A3. For most product categories, the best buy is usually the private label brand(7 point) A4. In general private label brands are poor quality products(7 point) A5. Considering the value of money, I prefer private label brands to national brands(7 point) A6. When I buy a private label brand, I always feel that I a getting a good deal(7 point) A11. I usually purchase brand name products A12. Store brands are of poor quality A13. All brands are about the same B1. Most advertising provides consumers with essential information B2. Most advertising is very annoying B3. Most advertising makes false claims B4. If most advertising was eliminated, consumers would be better off B5. I enjoy most ads B6. Advertising should be more closely regulated B7. Most advertising is intended to deceive rather than to inform consumers B11. To make sure I buy the right product or brand, I often look at the advertisements to see what others are buying and using B12. If I have little experience with a product, I often check with advertisements B13. I often consult advertisements to help choose the best alternative available from a product class B14. I often gather information from advertisements about products before I buy
Page | 44
doc_260111177.doc