Prof. Parul Gupta- Green Attitude of Consumers

Green Shade of Young Customers of Passenger Cars in Delhi & NCR - A Study of Consumer

Attitude Towards Green Cars

Ms. Parul Gupta1

Department of management studies

Army Institute of Management & Technology,

Greater NOIDA-201306(U.P.), India

Email – [email protected]

Phone No. - 919250500956

1 Senior Faculty Marketing Area

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Abstract

The automobile has probably done more to shape the character of 21st-century India than any

other piece of technology. It has liberated the average person from the limitations of time and

place, opening up new opportunities and offering new experiences. More significantly, it is one

of the pivotal elements of our economy. No wonder, then, that Indians have made the car such a

central fixture of their lives. But the automobile also affects the environment in many ways. Cars

and their associated infrastructure use resources, consume energy, and emit pollutants on a

substantial scale. The car presents a special kind of environmental dilemma.

The present empirical study is conducted to record and measure consumer attitude towards green

cars and green practices of passenger car manufacturers. This study defines three aspects of

consumer’s attitude, those are, Effective, Cognitive and Behavioral response of target

consumers. The results of Factor Analysis applied on the primary data collected from 250

sample units brings a new shade of young consumers in light that is GREEN. The younger

consumer segment of passenger cars in Delhi & NCR is found to be greener having highly

positive Effective and Cognitive scores but little weaker scores on Behavioral aspects. Thus

study concludes that young consumers of passenger cars carry a more positive attitude for green

practices and green cars on all three scales those are perceptual and emotional while elder

consumers were found to be aware of environmental problems caused by passenger cars thus

scoring reasonably good on perceptual scale but less promising scores on emotional and

behavioral scales.

Key Words

1. Effective Attitude - Sympathetic nervous system responses, verbal statements

of effect.

2. Cognitive Attitude - Perceptual responses, verbal statements of belief.

3. Behavioral Attitude - Overt actions Verbal Statement occurring behavior.

4. Factor Analysis - An effective tool for Data Summarization.

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Introduction

The automobile has probably done more to shape the character of 21st-century India than any

other piece of technology. It has given us mobility and independence. It has given us the

convenience of going where we want to, when we want to, and of doing so in comfort. It has

liberated the average person from the limitations of time and place, opening up new

opportunities and offering new experiences. More significantly, it is one of the pivotal elements

of our economy. No wonder, then, that Indians have made the car such a central fixture of their

lives.

But the automobile also affects the environment in many ways. Cars and their associated

infrastructure use resources, consume energy, and emit pollutants on a substantial scale. They are

a source of noise and congestion, a leading cause of accidental deaths and adverse effect on

human health. They have also radically reshaped the landscape directly through the building of

expressways, roads, and other infrastructure, and indirectly through effects on settlement

patterns. Because it is so tightly woven into the fabric of modern Indian life, the car presents a

special kind of environmental dilemma. On one hand, there is the need to eliminate or reduce the

environmental stresses associated with it. On the other, there is the desire to preserve the

advantages it has given us. Reconciling these objectives presents a considerable challenge.

Two bodies have role here to play in this context; The Customer and the passenger car

manufacturers. The manufacturer is expected to obey the set of rules framed by Legal bodies and

offering environmental friendly cars to manage the health of the environment so that it remains

viable for human surveillance and the customers are expected to develop a positive attitude to

pay for green efforts of manufacturers and exercise green practices while using a car. The role of

two parties does not end here. There is lot more expected from both in the quickly changed

scenario. Passenger car manufacturers are not only expected to implement what is legally

compulsory for them to do but to go beyond this and implement best available techniques to do

justice with the scarce natural resources and to reduce environmental burden on their shoulders.

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This concept is recognized as Corporate Environmental Responsibility which is a vital and

independent organ of Corporate Social Responsibility throughout the world. Similarly customers

should have positive response not only on cognitive and effective parameters but it should be

reflected in their behavior. Since passenger cars do most of the pollution during usage stage of

it’s life cycle hence the customer’s attitude towards green cars is significantly more important.

Increased Vehicular Pollution in Delhi and NCR

India has experienced a dramatic growth in fossil fuel CO2 emissions and the data compiled by

various agencies shows an increase of nearly 5.9% since 1950. No. of vehicles has touched 5.4

million in October 2007 in Delhi only. At present, India is rated as the 6th largest contributor of

CO2 emissions and China the 2nd. However, our per capita CO2 of 0.93t per annum is well

below the world average of 3.87t per annum2. Fossil fuel emissions in India continue to result

largely from coal burning with India being the largest producer of coal in the world. India is

highly vulnerable to climate change as its economy is heavily reliant on climate sensitive sectors

like agriculture and forestry. The vast low lying and densely populated coastline is susceptible to

rise in sea level.

According to the data from CPCB released by Centre for Science and Environment, the deadly

emission of particulate matter of smaller than 2.5 microns (PM2.5) and nitrogen dioxide in Delhi

have risen to more than 400% in October 2007 over what is proposed as a safe limit by CPCB3.

The daily data, available for Delhi, for the first time ever show that for most part of October the

emission of both these lethal chemicals had remained over the proposed standards.

Worse still, monthly data from CPCB showed that for 7 of the months between January and

October 2007, the PM2.5 levels breached the proposed norms. The monthly averaged data also

hide the peak levels of pollution in these particular months. In January and March 2007, the

PM2.5 level pollutant load went up by more than 100% hitting a high of 754 micrograms per

cubic meter in March (compared with the proposed standards of 60 microgram per cubic meter)4.

2 The Times of India, December 11, 20073 Central Pollution Control Board (2008) Parivesh: Newsletter, 6(1), June, CPCB, Ministry of Environment and Forests, Delhi

4Central Pollution Control Board , ‘Country paper on vehicular pollution control strategies for major cities in India’, New Delhi

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Life Cycle of a Passenger Car and Sustainability

The life cycle of an automobile begins with materials production, with includes resource

extraction and materials processing activities. Activities such as mining of minerals, drilling of

petroleum, refining and smelting, steel making, and polymerization each results in a variety of

environmental burdens.

The manufacturing stage starts with the fabrication (e.g. steel metal forming, casting, molding,

extrusion, forging) of product material into automotive parts (e.g. an engine block). The next

steps are the manufacturing/assembly (e.g., machining, joining/fastening) of parts into

components (e.g., an engine) and the final auto assembly (e.g., powertrain automobile).

The use and service stage dominates overall environmental impacts of the vehicle across its life

cycle. Beside the consumption of gasoline the usage phase and services phase include:

Components for running an automobile such as oil, fuel and oil additives, lubricants and

grease, transmission and brake fluid, power steering fluids, washer fluid,

coolant/antifreeze, refrigerants, etc.

Replacements parts such as tires, hoses, wipers, lights, belts, clutch discs and plates,

spark plugs, air filters, batteries, brake shoes and pads, oil filters, etc.

The need for infrastructure such as highway, service and gas station, etc.

At the end of life stage of an automobile it typically enters the recycling infrastructure, which

consists of dismantlers and auto-scrap shredders. Approximately 94 percent of the cars and

trucks are currently returned to dismantling and shredding facilities. The dismantlers remove

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Figure1, Environmental

Burden on Passenger Car

During Various Stages

of It’s Life Cycle

reusable parts and some recyclable materials from the vehicles for resale or recycling, before

sending what is left – the “hulks” – to the shredders. The shredders rip the hulk into small pieces

and recover much of the metal for recycling. What is left, known as the automotive shredder

residue (ASR), is a low density material consisting of textiles, rubber, wood, plastics and dirt that

is sent to the landfill.

The main pollutants from automobile exhausts, for conventional gasoline and diesel engines, are;

carbon dioxide, carbon monoxide, nitrogen oxides, hydrocarbons an suspended particulates.

Carbon dioxide is the most significant greenhouse gas and as such is the main cause of global

warming. Carbon dioxide emissions are directly related to fuel consumption, and for each

kilometer travelled, can only be reduced by increasing vehicle efficiency, or switching to

alternate fuels such as natural gas. Every 60 litre fill up at the gas station results in about 135 kg

of carbon dioxide being released into the atmosphere. Globally, automobiles emissions are

directly responsible for close to 10% of man made carbon dioxide emissions. If gasoline refining

and processing, as well as automobile manufacturing are considered, automobiles are responsible

for 15 - 20% of global carbon dioxide emissions5.5 OECD (1997): The Automobile and Autoparts Industry, Workshop on Market Access Issues in the Automobile Sector, Paris, 10-11 July 1997

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USEConsideration

Repair & MaintenanceAir emissionDesire for fossil fuelsEnergy consumption

MANUFACTUREConsideration

Material SelectionResource utilization

MATERIAL PRODUCTIONConsideration

Environmental management at suppliers levelEco friendly auto parts

RETIREMENTConsideration

Non disposable -hazardous wasteResource recycling & conservation

FACTORS INFLUENCING SUSTAINABILITY

ENVIRONMENT

HUMAN HEALTH

VOC emission during the use of the automobile (e.g., exhaust and evaporative) are greater than

those generated by any other life-cycle stage. The second largest contributor to VOC emission is

automobile painting. Beside the resource consumption through running a vehicle and the needed

infrastructure (e.g., highways, service and gas station), the maintenance and service operations

contribute significantly to the environmental impact of automobile use. Vehicle repair and

maintenance processes also generate waste such as organic solvents, paint sludge, and alkalis.

Hazardous organic solvents used for the part cleaning, such as naphtha, chlorinated solvents, and

mineral sprits, can evaporate or contaminate groundwater if land filled or dumped. Used tires are

another significant solid waste burden. In Table 6, some major hazardous components of the

automobile life cycle are summarized.

Attitude

Attitude is “a relatively enduring organisation of beliefs, feelings, and behavioural tendencies

towards socially significant objects, groups, events or symbols” (Hogg & Vaughan 2005)

Attitude may comprise characteristics of strength, magnitude or intensity, importance, salience or

centrality, complexity, flexibility, etc. Commonly, however, attitude measurements are

concerned with the magnitude dimension and its direction; that is, the degree of favorableness or

unfavorableness of a person with regard to a psychological object. A psychological object may

be a person, a group, an idea, a symbol, or anything with regard to which people could harbor

positive or negative feelings.

Structure of Attitude

Attitudes structure can be described in terms of three components: Affective component,

Behavioral Component and Cognitive component. Affective component involves a person’s

feelings / emotions about the attitude object. Behavioral (or conative) component is the way the

attitude influences how individual acts or behaves. Cognitive component involves a person’s

belief / knowledge about an attitude object.

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The multicomponent theory of attitudes views attitudes as having multiple independent

components. These include an affective component (which refers to the feelings, emotions, or

drives associated with an attitude object), a cognitive component( which refers to the beliefs,

judgments, or thoughts associated with an attitude object), and a conative component (which

refers to the primary motivational or behavioral consequences of attitudes). The theory suggests

that the simultaneous consideration of these distinct attitudinal components rather than

concentration on a single component provides better predictions of persuasion outcomes.

A series of beliefs which can be cognitive or evaluative can combine to create an attitude

(Heberlein, 1981). Beliefs are important in the formation of value which is an enduring belief

that a specific mode of conduct or end-state of existence is personally or socially preferable

(Rokeach, 1973). The link between attitudes, intentions and behavior has been explained

primarily by Ajzen (1985, 1988), Ajzen and Fishbein (1980). This theory is based on the

assumption that human beings usually behave in a sensible manners where they will take into

account information available to them and consider the consequences of their actions. Thus

people are expected to act in accordance with their intentions. The three components are usually

linked. However, there is evidence that the cognitive and affective components of behavior do

not always match with behavior. This is shown in a study by LaPiere (1934).

Measuring Consumer Attitude

Researchers arrive at measures of attitudes by inference. But we need data on which to base our

inference. Such data are collected by various methods. To observe the ongoing behavior of

people in the natural setting; respondents may directly be asked to state their feelings with

regard to the issue under study; a well-defined task may be assigned to respondents and record

their performance; data can be generated by giving the respondents partially structured stimuli to

interpret or react to. Physiological reactions of respondents when exposed to the attitudinal

object can also provide us with relevant data. Westie and DeFleur (1959) studied the attitudes of

subjects by taking the latter's galvanic skin responses, heartbeat, etc, when presented with

pictures of Negroes and Whites in various social situations. Hess and Polt (1960) found that

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pleasant stimuli gave rise to pupillary dilation, whereas unpleasant ones led to pupillary

constriction on the part of subjects.

But when a researcher wants to know how people feel about a certain thing, it seems most

natural to ask them straight away as to what their feelings are. Direct questioning has, therefore,

had an appeal as a method of studying attitudes. But, however logical and smooth this technique

may seem to be, it serves only a limited purpose of roughly classifying respondents as favorable,

unfavorable, and indifferent with regard to a psychological object. Here the same problem

emerges as the one often encountered in direct observation; normally, neither direct observation

nor direct questioning assesses the degree of attitudes an individual possesses. In the absence of

such an index, we cannot discriminate among individuals within the favorable and the

unfavorable groups; nor can we know the distance between the two groups. There may, of

course, be times when we require only to know as to how many are "for" and how many

"against" a particular issue. Direct questioning may adequately serve the purpose here.

Green Consumer Attitude and its Effect on Buying Behavior

Concerns related to the environment are evident in the increasingly environmentally conscious

market place. Over the years majority consumers have realized that their purchasing behavior has

a direct impact on many ecological problems (Laroche, 1996). Consumers do not always buy

sustainable products as consequences of environmental concern or to benefit the community or

due to personal beliefs but mainly to give priority to health, to be part of the social group, to

distinguish from others and to accomplish the need to tryout new technologies (Vermeir and

Verbeke, 2004). Environmental concern is a strong attitude towards preserving the environment

(Crosby, Gill and Taylor 1981). Based on the pioneering research of Dunlap and Van Liere

(1978), environmental concern is also defined as a global attitude with indirect effects on

behaviour through behavioural intention (Gill, Crosby and Taylor 1981). People’s psychological

responses towards the environment as individuals and consumers are also referred to as

environmental concern attitude. Some writers have referred to “ecological concern”, which refers

to the degree of emotionality, the amount of specific factual knowledge, and the level of

willingness as well as the extent of the outcomes of these (behavioural intention, recycling

behavior and purchase intention on green products) on pollution issues (Maloney and Ward,

1973).

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Consumer attitude and Green cars

Cars have two opposite personalities. One is friendly and attractive the other is destructive and

can be lethal. The desire to own a car is linked to pleasure, sexuality, convenience and freedom.

Men lust for attractive, prestigious cars they way they lust for women and women desire men

with attractive, prestigious cars. Car manufacturers have long used attractive, lightly clad

women to advertise their latest auto designs. As it has already been discussed that vehicular

pollution is increasing day by day in Delhi & NCR and passenger cars are one of the major

sources of vehicular pollution. There is a requirement of synergized efforts of car manufacturers

and car consumers to control this problem. What is most for a marketer is to understand

consumer attitude and its effect on consumer behavior. It is not always seen that attitudes have to

be changed first in order that intended behavior may follow; nor is the reverse being implied that

behavior must be changed so that corresponding attitudes will emerge. In fact, attitude may

influence behavior and in turn be influenced by it. Whatever the theoretical position on this

what-comes-first issue, it is a fact that attempts to introduce a change, more often than not, faces

some degree of resistance. Such resistance is dependant on how favorably or unfavorably the

population in question is inclined toward the proposed course of action and related issues. It is

here that knowledge of the target population's attitudes can guide any effort for planning and

implementing developmental change.

Since a passenger car does most of the pollution during usage stage of its life cycle hence it is all

the more important to measure consumer attitude towards Green cars so that the problem of

increasing vehicular pollution can be effectively controlled. Without the appreciation of

consumers, car manufacturers green efforts will go in vein hence it is very important to

understand consumer attitude towards Green cars. It is observed in the previous studies that

young consumers carry positive attitude towards green products and their response for green

advertising and marketing has been more promising. . Not much work is done to measure

consumer attitude towards Green cars and Green driving practice. A pilot study was conducted to

explore the attitude of car consumers and it was observed that younger consumers were found to

be more environmental friendly in comparison to elder consumers.

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In the light of previous studies and the observations of pilot study, we propose,

H1: Younger consumers will have overall positive Green attitude in comparison to elder

consumer with moderately positive or negative Green attitude.

H2a: Younger consumers will have overall positive Green cognitive attitude in comparison to

elder consumer with moderately positive or negative Green cognitive attitude.

H2b: Younger consumers will have overall positive Green cognitive attitude in comparison to

elder consumer with moderately positive or negative Green affective attitude.

H2c: Younger consumers will have overall positive Green cognitive attitude in comparison to

elder consumer with moderately positive or negative Green behavioral attitude.

Survey Instrument

An attitude is an enduring disposition to consistently behave in a given manner and it is a

hypothetical construct that is not directly observable, but is measurable by an indirect means

such as verbal expression or overt behavior. To meet this condition a Likert scale of five points

was used as a survey instrument to record consumer attitude towards Green driving. Based on the

results of pilot study conducted total eleven items were prepared in the instrument to throw light

on Cognitive, Affective and Behavioral Green Attitude of participants. All eleven items in the

instrument were positive statements referring three components of attitude (mentioned above).

Participants

A total of 250 passenger car consumers participated in this study. Participants were divided into

two categories; Elder consumer and Younger Consumer. The age of elder consumer ranged from

25- 35 years and 36-45 years for younger consumer.

Data Analysis & Results

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Total 240 records out of 250 were analyzed to measure the Green attitude of passenger car

customers using SPSS Windows Version 16.0. A Factor analysis on eleven items reveled three

underlying dimensions in the instrument. Primary component method was used to extract factors

and Varimax rotation was used to rotate factors. These three dimensions were labeled as

Cognitive Attitude Category, Affective Attitude Category and Behavioral Attitude Category.

Bartley test was used to make sure that correlation matrix is not an identity matrix. The value of

Kaiser-Meyer-Olkin Measure of sampling adequacy was found to be 0.746. Thus clearing KMO

test with 95% confidence .All the three factors explained 54.23% cumulative variance with

eigenvalue more than 1.0.at individual level.

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Insert Table 1a, 1b & 1c here

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Based on the standardized scores of factors, records were further divided into three categories;

extremely positive attitude, Positive attitude and Negative attitude for all three extracted factors.

Standardized scores for first factor – Behavioral attitude category ranged from (-3.24) to (1.62),

for second factor – Cognitive attitude category ranged from (-0.4.97) to (2.18) and for third

factor – Affective attitude category ranged from (-3.12 to 1.83).

Results of Chi Square support the hypothesized response pattern that younger consumers were

found to have Greener Attitude in comparison to elder consumers. On the basis of totalscore

secured by participants, the whole sample was divided into three categories; Green Consumers

(totalscore <=22 & >11), Yellow Consumers (totalscore <=11 & >0) and Red consumer

(totalscore <=0 & >-22). 92.5% of the total younger consumers participated, have fallen into

Green consumer category in comparison to 10.5% of elder consumers who were identified as

Green consumers. Thus the difference between the green attitude of younger consumer and elder

consumer was found to be significant at 0.05 significance level. We find that majority of

Younger consumers had overall extremely positive Green attitude on the other hand majority of

elder consumers had either moderately positive or negative Green attitude.

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Insert Table 2a & 2b here

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Based on the standardized score of three derived factors as a result of factor analysis conducted

at the first stage of data analysis, difference in Cognitive attitude, affective attitude and

behavioral attitude of younger and elder consumers was tested with Chi square at 95%

confidence level. Results of three separate Chi square tests conducted to test H1b, H2b and H3b

confirmed that the Younger consumers have more positive Cognitive, Affective and Behavioral,

Green attitude in comparison to elder consumers , thus rejecting null hypothesis in all the above

mentioned cases and accepting H1b, H2b and H3b.

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Insert table 4a & 4b here

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Discussion

Results of study confirm that younger consumers of passenger cars possess more positive

attitude towards Green cars and green driving practices. Study reveals that there is not much

difference in the Green cognitive attitude of younger and elder consumers of passenger cars.

Thus both the categories have sufficient knowledge of adverse effects of vehicular pollution.

Both agree that vehicular pollution is increasing in Delhi & NCR day by day and passenger cars

are responsible for increasing vehicular pollution to a larger extend. Despite of having sufficient

awareness about adverse effects of vehicular pollution it is observed that elder category of

passenger car customers have less score on affective and behavioral attitude scale. On the other

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hand younger consumers have promising scores on affective and behavioral attitude scale. Thus

it is clear that younger generation of Delhi & NCR is not only aware of increasing vehicular

pollution in the region (Cognitive attitude) but they also believe that certain environmental

friendly practices can reduce the environmental harm caused by passenger cars (Affective

attitude). Their positive Green attitude is further reflected in their Green driving practices

(Behavioral attitude). Thus a Younger consumer of passenger cars has an overall consistent

positive Green attitude and offers an opportunity for passenger car manufacturers in India to

capture an upcoming Green segment for environmental friendly cars. While an elder consumer is

found to be comparatively less bothered for environmental harm done by his car and his driving

practices also were less environmental friendly in comparison to younger consumer.

This paper is of interest both for managers and researchers. Managers should focus on new shade

of consumer attitude that is GREEN. Since maximum environmental burden on a passenger car

is during the usage stage of its life cycle, manufacturers alone can not reduce this burden to a

significant extent. The contribution of passenger car consumers is more important in this regard.

Mangers must notice the positive change in the consumer attitude towards Green practices. This

change is creating a separate segment in the passenger car market where consumers are not only

environmental friendly but also appreciate the green initiative of car manufacturers. Thus

passenger car manufacturers and consumers together can eliminate environmental stress

associated with passenger car and simultaneously preserving the benefits it offers.

For researchers, this study suggests that younger consumer’s attitude towards Green practices is

quite promising. Researchers should explore the factors responsible for strengthening this Green

attitude to get more comprehensive view of Green attitude of passenger car consumers. This

research adds on to the growing literature on environmentally sustainable products and Green

marketing. The findings of the study present strong evidences that younger consumers of

passenger cars have a positive Green attitude that can be explored by further investigation.

AnnexureTable 1a Result of Factor rotation using varimax rotation

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Rotated Component Matrixa

Component

1 2 3

pollution level .794

unleaded fuel

increasing pollution in environment .779

use of AC .860

using ecofriendly material .600

PUC(Pollution under control)

turn off car at the red light .733

paper bags are preferable .795

regular service done .540

preference to pool car on some other place .625

ecofriendly diesel or petrol car .625

Extraction Method: Principal Component Analysis.

Rotation Method: Varimax with Kaiser Normalization.

a. Rotation converged in 5 iterations.

Table 1b Result of KMO & Bartlett’s test

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .746

Bartlett's Test of Sphericity Approx. Chi-Square 551.735

df 55

Sig. .000

Table 1c Result of Primary component method of Factor extraction

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Total Variance Explained

Component

Initial Eigenvalues

Extraction Sums of Squared

Loadings

Rotation Sums of Squared

Loadings

Total

% of

Variance

Cumulative

% Total

% of

Variance

Cumulative

% Total

% of

Variance

Cumulative

%

1 3.348 30.441 30.441 3.348 30.441 30.441 2.442 22.199 22.199

2 1.499 13.632 44.072 1.499 13.632 44.072 1.849 16.808 39.006

3 1.117 10.157 54.230 1.117 10.157 54.230 1.675 15.223 54.230

4 .937 8.515 62.745

5 .824 7.489 70.234

6 .772 7.022 77.256

7 .662 6.021 83.277

8 .537 4.886 88.163

9 .497 4.521 92.684

10 .438 3.979 96.663

11 .367 3.337 100.000

Extraction Method: Principal Component Analysis.

Table 2a Result of Chi Square test – H1

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 83.802a 2 .000

Likelihood Ratio 92.665 2 .000

Linear-by-Linear

Association80.088 1 .000

N of Valid Cases 240

a. 2 cells (33.3%) have expected count less than 5. The minimum

expected count is 1.08.

Table 2b Crosstable -Age of respondent * Customer category

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Customer category

Total

Red

consumer

Yellow

Consumer

Green

consumer

Age of respondent Age 25 – 35 Years Count 1 42 111 154

% within age of

respondent.6% 27.3% 72.1% 100.0%

% within Customer

category33.3% 35.9% 92.5% 64.2%

Age 36 – 45 Years Count 2 75 9 86

% within age of

respondent2.3% 87.2% 10.5% 100.0%

% within Customer

category66.7% 64.1% 7.5% 35.8%

Total Count 3 117 120 240

% within age of

respondent1.2% 48.8% 50.0% 100.0%

% within Customer

category100.0% 100.0% 100.0% 100.0%

Table 3a Result of Chi square test – H2a

Value df

Asymp. Sig. (2-

sided)



Linear-by-Linear



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Table 3b Crosstable – Age of respondent * Cognitive attitude category

Cognitive Attitude category

Negative Positive

Extremely

Positive Total

Age of respondent Age

25-35 Years

Count 34 74 46 154

% within age of respondent 22.1% 48.1% 29.9% 100.0%

% within Cognitive Attitude

category54.8% 61.7% 80.7% 64.2%

Age

36-45 Years

Count 28 46 11 86



category45.2% 38.3% 19.3% 35.8%




category100.0% 100.0% 100.0% 100.0%

Table 4a Result of Chi Square test – H2b

Chi-Square Tests




Linear-by-Linear



a. 0 cells (.0%) have expected count less than 5. The minimum expected count is

18.28.

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Table 4b Crosstable – Age of respondent * Affective attitude category

Affective Attitude Category

TotalNegative Positive

Extremely

Positive

Age of respondent Age 25-35

Years

Count 41 71 42 154


% within Affective Attitude

Category44.6% 73.2% 82.4% 64.2%

Age36-45

Years

Count 51 26 9 86



Category55.4% 26.8% 17.6% 35.8%




Category100.0% 100.0% 100.0% 100.0%

Table 5a Result of Chi Square test – H2c

Chi-Square Tests




Linear-by-Linear



a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 16.84.

Table 5b Crosstable – Age of respondent * Behavioral attitude category

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Behavioral Attitude category

TotalNegative Positive

Extremely

Positive

Age of respondent Age 25-35

Years

Count 17 78 59 154

% within Behavioral

Attitude category36.2% 60.0% 93.7% 64.2%

Age 36 –

45 Years

Count 30 52 4 86

% within Behavioral



% within Behavioral


Table 6 Major Hazardous Components of The Automobile Life Cycle

Source: CPCB (2002) Parivesh

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Documents

Prof. Parul Gupta- Green Attitude of Consumers