Antecedents of Buying Intention towards Green Products – A Structural Equation Modelling Approach
Dr. Debasis Pani
Assistant Professor,
Gandhi Institute of Advanced Computer and Research,
Rayagada, Odisha
Mail Id: debasispani.iacr@gmail.com
Dr. Sunil Kumar Pradhan
Associate Professor,
Department of Business Administration,
Berhampur University,
Bhanja Bihar, Berhampur, Odisha.
Mail Id: sunil.sunita123@gmail.com
Abstract
The consumer in the present era is not only sensitive towards environment but also shows his concern towards environmental problem and health issues related to consumption of the non-green product. Hence the consumer ensures his consumption activity should not have any detrimental affect towards the environment; consequently the consumer shows favourable attitude towards the green product and strongly support for the consumption of eco-friendly product. This development of the green consumption behaviour is strongly preceded by the attitude and behavioural belief system of the consumer. Earlier cross-sectional studies have shown the attitude of the consumer is the important factor towards buying intention but earlier studies have not clearly stated the importance of social and control belief on the buying intention of the consumer. The thrust of the current study is to explore the relationship of attitude of green consumer towards their perceived subjective norms, perceived consumption effectiveness and buying intention. The data was collected from 428 respondents by adopting multistage random sampling procedures from important cities of Odisha. The collected data were analyzed with PLS-SEM technique.
The findings of the study revealed that the attitude towards green product is the most important factor that influences perceived subjective norms, perceived consumption effectiveness and buying intention of the consumer. The current study unveils the basic understanding about the consumption behavior towards green product. Further, the findings of the study can encourage marketers in developing strategies to entice green consumers.
Keywords: Attitude towards Green Product, Perceived Subjective Norms, Perceived Consumption Effectiveness and Buying Intention
Introduction
The consumer in the contemporary era are showing formidable attitude towards the green product, their concern for the green product further significantly influenced by the several environmental issues like global warming, resource depletion, and pandemic caused by COVID-19. (Costa et al., 2020; Dangelico and Pontrandolfo, 2010) Subsequently the consumers are becoming more sensitive towards green product and marketing of green products takes a momentum. The concept of selling environmentally friendly green products is known as "Green Marketing." Green marketing focuses on meeting consumer requirements and wants while causing less detrimental affect towards environment. Consumption behaviour literature states, green products as those that are produced with using less natural resources, have a lower environmental effect, and generate less waste. (Policarpo and Aguiar, 2020). Several studies have shown that the consumer is showing favourable buying intention towards green product, in this juncture understanding the nexus between the buying intention of the consumer and its antecedents is a paramount interest for both the academicians and marketers. Past studies have shown the buying intention of green consumer and it’s antecedents in the form of conceptual framework. However such kind of exploration study is in a nascent state in the context of Indian consumer, as the findings of the earlier cross-sectional studies has revealed that the buying behavior of green products is significantly influenced by several factors and it varies with the demography of the consumers. In the view of above discussion; an empirical understanding of buying intention towards green product is required. Hence, the thrust of the current research is to assess buying intention of the consumer towards green product in relation with three critical constructs as “attitude towards green product”, “perceived subjective norms” and “perceived consumption effectiveness” in the form of a conceptual framework.
Review of Literature
Attitude towards Green Product (AGP): Attitude has long been emphasised as a crucial factor of behavioural intention. Attitudes may impact a customer's evaluation of a product's qualities, increasing or decreasing individual interest and influencing overall feelings about whether or not to acquire a product. To Fishbein and Ajzen (2005), “attitude as a learned predisposition to respond in a consistently favourable or unfavourable manner with respect to a given object” According to Chen and Deng, (2016), “attitude towards green products is perceived as the degree to which performance of green purchase behavior is negatively or positively valued by individuals”. Several studies related to ‘Green Consumption’ stated that consumer holding positive attitude towards green product are showing keen interest on acquiring knowledge about green products (Sharma and Dayal, 2016). Studies conducted by Kim and Chung (2011) revealed that the uses of green product increases for those consumer who have subsequently formed favourable attitude and positive mindset towards green product. Theoretical and empirical evidence supported the proposition that attitude towards the green product is a significant predictor of purchase intention of green product. Therefore the current study proposes a directional relationship between attitude towards the green product and buying intention.
Attitude with Subjective Norms and Consumption Effectiveness
The attitude and buying experience determine the consumer's perceived social norms and consumption effectiveness, and the buying experience shapes the consumer's desire to buy ecological products. Vermeir and Verbeke, (2006) found in his study that the environmental and social values encourages the consumer to use green product. Further; several studies reviled that goods with social and natural purposes could encourage consumers to make environmentally friendly purchases (Joshi & Rahman; 2015). A similar study conducted by Sharaf et al., (2015) emphasized the importance of social influence on the attitude of the consumer towards green product. Above empirical findings connotes a positive relationship between the attitude of the consumer and perceived subjective norms. But this study aims to understand whether the perceived social beliefs of the consumer are shaped by the attitude of the consumer or not.
Another important factor that influences that attitude of the consumer is the perceived consumption effectiveness. As consumers can effectively ensure that his or her consumption activity is not damaging the environment. Several studies suggest that perceived consumption effectiveness strongly influences consumers cognitive thought process and emotional responses (Bandura, 1977). Study conducted by Durndell and Haag (2002) found existence of strong positive correlation between the perceived consumption effectiveness and attitude of the consumer. In contrary, Ng and Law (2015) in his study found that the perceived consumption effectiveness influences the attitude of the consumer. Hence from the above study it is evident that Attitude influences the perceived subjective norms and consumption effectiveness, which is supported by both theoretical and empirical research. As a result, it suggests that attitude positively influences the subjective norms and consumption effectiveness of the consumer.
Perceived Subjective Norms (PSN): Normative beliefs are the main predictors of subjective norms (Ajzen, 2015) In most cases, the acts or responses of family, friends, advisors, or other experts play a significant role in determining consumers buying decision (Davies et al., 2002). The acceptance, advice, or recommendations of referents, on the other hand, might interfere with or modify an individual's behavioural cognitions (Arvola et al., 2008). According to Hee, (2000), “Subjective norm is the opinions of others that are influential on an individual's decision making. If he or she believes that people who are significant to him or her approve the behavior, they are likely to perform the behavior, and vice versa”. Furthermore, it is anticipated that subjective norms will have an impact on consumers' intentions to buy green products. This means that consumers' intentions to buy green products may be affected by the strong judgement made by the reference group. Sharaf et al., (2015) in his study found, for consumption of green product the influence of social forces are indispensable. In contrast, Paul et al. (2016) found that consumers' intentions to make decisions to buy green product were unaffected by subjective norm. Therefore it is an implication before the researcher to explore the nexus between perceived subjective norm and buying intention.
Perceived Consumption Effectiveness (PCE): The purchasing of green products has been connected to consumers' belief in their potential to successfully tackle environmental concerns (Samdahl and Robertson, 1989). Several academics research has identified perceived consumption effectiveness as a significant predictor of green purchase behaviour (Dagher, G.K., Itani, O., 2014). The term "perceived consumer effectiveness" refers to people's perceptions of how much their activities can help solve environmental problems (Ellen et al. 1991). According to Jaiswal, D., & Kant, R. (2018) “the phenomenon of perceived consumption effectiveness was also interpreted in terms of behavioural control and internal locus of control, and self-efficacy in the ecological consumer research” Perceived consumption effectiveness is a measure that assesses an individual's subjective evaluation of his or her ability to contribute to the solution of societal environmental problems, and it is closely linked to self-evaluation in the context of environmental issues (Kim and Choi,2005). Given the preceding discussion, this study is sincere attempt to see the effect of perceived consumption effectiveness on buying intention.
Buying Intention (BI) : the intention of the consumer plays an important role in shaping the buying behavior, as consumers having a strong intention will more likely to perform desired buying behavior than compared with a consumer without intention. (Devonish et al., 2010) A consumer's willingness to buy green products for the benefit of the environment is referred to as buying intention towards green products, and such a consumer's willingness includes a motive to buy green products (Dagher and Itani, 2014). When confronted with a consumption circumstance, a person's intentions dictate behaviour, which is a very particular action that he or she will choose. There is evidence from a several research that the intention to buy green product and behavior related to buying green products are positively correlated. (Nguyen et al., 2016; Kumar et al., 2017) Insights gained from the earlier empirical studies stated that consumers are more likely to behave in a particular way if they have a higher intention to do so (Ajzen, 1991).
Conceptual Framework Hypothesis Development
In the view of above discussion, findings of empirical studies and under the premises of theory the below conceptual framework is proposed. The exogenous variables in this model are "Attitude toward green products”, “Perceived subjective norms”, “Perceived consumption effectiveness". The endogenous variable is "Buying intention".
Figure No:-1. The Proposed Research Model
Source: Authors own analysis
Hypothesis 1. (H1) Consumer’s attitude towards green product positively influences their buying intention
Hypothesis 2. (H2) Consumer’s attitude towards green product positively associated with their perceived consumption effectiveness
Hypothesis 3. (H3) Consumer’s attitude towards green product positively associated with their perceived subjective norms
Hypothesis 4. (H4) Perceived subjective norms have positive effect on buying intention for green product
Hypothesis 5. (H5) Perceived consumption effectiveness have positive impact on buying intention for green product
Methodology
The objective of the study is to understand the buying intention of the consumer relating to eco-friendly green products, in the form of a conceptual framework. The various constructs undertaken in the study are Attitude toward green products (AGP), perceived subjective norms (PSN), perceived consumption effectiveness (PCE) and buying intention (BI). Before development of the questionnaire 30 respondents were selected for pilot study from the city of Berhampur. During the interviewing process enough care was taken by the researcher to understand their buying motives and attitude towards green product. A questionnaire was devised to examine customers' attitudes regarding use of green product after taking into consideration essential recommendations and suggestions from the respondents. To validate the proposed conceptual model a five point likert scale based and self-administered questionnaire was used. The data collection was carried out both online and offline surveys in important cities of Odisha to measure the response of the customer relating to four constructs (AGP,PSN, PCE and BI). To measure the construct AGP, PSN the scales were adopted from earlier studies (Maichum et al.;2016, Wu & Chen, 2014; Al Mamun, et al. 2018). For the scales representing the construct PCE is devised from the earlier study conducted by (Maichum et al. 2017). Finally to measure the BI, the scales were adapted from earlier studies (Ha & Janda, 2012; Al Mamun, et al., 2018;Chen, C. C., et.al., 2018). All of the scale items included in the questionnaire of current study is based on the adopted scale. The response of 428 valid sample were collected through both online and offline survey methods from five important cities of odisha by adopting multistage random sampling method. The questionnaire was to collect the demographic information of the respondents relating 7 attributes and his response relating to 33 scale based items. The scale based items were measured with 5-point Likert scale where the lowest point 1 represents “strongly disagree” to highest point 5 represents “strongly agree”. According to Norman (2010), if the sample size is large then parametric test can give extreme robust result even if some of the assumption of normality is not fulfilled. The current study has incorporated large sample size of 428. However, to validate the conceptual framework the researcher used Smart-PLS, a non-parametric test to access the measurement model and bootstrapping method to test the hypothesised relationship among the construct.
Data Analysis and Results
Respondents Profile
A total of 428 respondents were surveyed during the study from five important cities of odisha. The respondents were categorised based on their demographic variable like place (Districts), gender, age, qualification, occupation, marital status and income.
Table No: 1 Demographic profile of the green consumer.
|
Variable |
Categories |
Frequency |
Percentage |
|
Districts |
Cuttack |
96 |
22.4 |
|
Baleshwar |
93 |
21.7 |
|
|
Berhampur |
101 |
23.6 |
|
|
Sambalpur |
43 |
10.0 |
|
|
Bhubaneswar |
95 |
22.2 |
|
|
Gender |
Male |
306 |
71.5 |
|
Female |
122 |
28.5 |
|
|
Age |
Below 30 |
133 |
31.1 |
|
30 to 45 |
232 |
54.2 |
|
|
Above 45 |
63 |
14.7 |
|
|
Qualification |
Matriculation |
83 |
19.4 |
|
Intermediate |
179 |
41.8 |
|
|
Postgraduate |
53 |
12.4 |
|
|
Graduate |
113 |
26.4 |
|
|
Occupation |
Service |
104 |
24.3 |
|
Business |
94 |
22.0 |
|
|
Student |
112 |
26.2 |
|
|
Homemaker |
85 |
19.9 |
|
|
Others |
33 |
7.7 |
|
|
Marital Status |
Single |
251 |
58.6 |
|
Married |
177 |
41.4 |
|
|
Income |
Below 25,000 |
136 |
31.8 |
|
25,001 to 50,000 |
115 |
26.9 |
|
|
50,001 to 75,000 |
120 |
28.0 |
|
|
Above 75,001 |
57 |
13.3 |
Source: Authors’ own interpretation.
The above table describing the demographic profile of the green consumers indicates that there are 71.5% of male and 28.5% of female respondent were surveyed. Maximum respondents were belongs to the age category of 30 to 45 years. However the 41.8% of the customers were educated upto intermediate. Maximum green consumers are students and their percentage is 26.2%. Further, the 58.6% of the green consumers are single. Finally maximum green consumers in this study falls in the income category of below 25000 and their percentage is 31.8%.
4.2 Structural Equation Modelling (SEM)
SEM analysis based on Partial Least square (PLS) algorithm is widely used by the researcher to across the world to validate both formative and reflective constructs. PLS-SEM is extremely useful is extremely useful when we have to predict a group of dependent variable with the help of a wide number of independent variable. (Abdi, 2007). According to Hair et al.,(2019) “The PLS-SEM method is very appealing to many researchers as it enables them to estimate complex models with many constructs, indicator variables and structural paths without imposing distributional assumptions on the data.” The PLS-SEM is a very handy in comparison with CB-SEM as it does not require complex calculation and programming. (Ringle et al., 2015).
Common Method Bias test
The problem of common method biasness is inevitable because the primary data has been collected from a similar group of respondents. Therefore the correlation matrix method was used to address the problem of ‘common method bias’ (Guide & Ketokivi, 2015; Yüksel, 2017). According to Bagozzi, Yi & Phillips, (1991) higher correlation among the constructs (r>0.90) indicates existence of problem of ‘common method bias’. It can be shown in the below table that the coefficient of correlation among the constructs are less than 0.90. hence the data collected during the research process were not having the problem of biasness and it is appropriate for further analysis.
Table No: 2 Construct correlation matrix
|
|
AGP |
PSN |
PCE |
BI |
|
AGP |
1 |
|
|
|
|
PSN |
0.763 |
1 |
|
|
|
PCE |
0.728 |
0.687 |
1 |
|
|
BI |
0.773 |
0.771 |
0.700 |
1 |
Source: Authors’ own interpretation.
Analysis of Measurement Model
Measurement models is the preliminary stage of evaluation of a model that indicates the relationship between the constructs and the various items representing the constructs. In PLS-SEM, the evaluation of the measurement model depends upon the scale of the construct whether it is formative or reflective. The ultimate objective of the model assessment is to increase the robustness of the research for that the construct must have to satisfy the validity and reliability criteria. The current study includes 21 items representing four constructs after the purification process of the constructs.
Table No: 3 Reliability and validity
|
Constructs |
Items |
Factor Loadings |
Cronbach’s Alpha |
rho_A |
Composite Reliability (CR) |
Average Variance Extracted (AVE) |
|
Attitude towards Green Product (AGP) |
B1 B3 B4 B5 B7 B8 |
0.799 0.844 0.853 0.806 0.845 0.834 |
0.915 |
0.917 |
0.934 |
0.701 |
|
Perceived Subjective Norms (PSN) |
C1 C2 C4 C6 C9 |
0.871 0.753 0.833 0.907 0.840 |
0.882 |
0.911 |
0.914 |
0.681 |
|
Perceived Consumption Effectiveness (PCE) |
D2 D4 D6 D8 |
0.861 0.924 0.926 0.805 |
0.902 |
0.908 |
0.932 |
0.775 |
|
Buying Intention (BI) |
E2 E3 E4 E5 E7 E8 |
0.802 0.844 0.783 0.863 0.817 0.827 |
0.905 |
0.909 |
0.926 |
0.677 |
Source: Authors’ own interpretation.
The reliability of the constructs are measured by roh_A and Cornbach’s Alpha and it is clearly evident from the above table that reliability estimates are greater than 0.8. Therefore the construct reliability condition is satisfied. The construct validity can be measured in two stage as “convergent validity” and “discriminant validity”. Fornell and Larcker (1981) have given three criteria for measuring the convergent validity “they are as follows (1) All measurement factor loadings must be significant and exceed 0.70, (2) Construct reliabilities must exceed 0.80, and (3) Average Variance Extracted (AVE) by each construct must exceed the variance due to measurement error for that construct (that is, AVE should exceed 0.50).” in the present study the indicator loading of all the items are greater than 0.702. The composite reliability otherwise known as construct reliability estimated values are greater than 0.8 and finally the AVE estimated values are greater than 0.5, hence the conditions laid by Fornell and Larcker (1981) to fulfil the convergent validity is satisfied.
Table No- 4: Fornell-Larcker Estimates
|
Constructs |
AGP |
BI |
PCE |
PSN |
|
AGP |
0.837 |
|
|
|
|
BI |
0.777 |
0.823 |
|
|
|
PCE |
0.721 |
0.693 |
0.881 |
|
|
PSN |
0.769 |
0.792 |
0.676 |
0.825 |
Source: Authors’ own interpretation.
The Discriminant validity shows the extent to which the scale do not correlate with those constructs, which are conceptually different. According to Gefen and Straub (2005), “discriminant validity is shown when each measurement item correlates weakly with another construct excepts for the ones to which it is theoretically associated” In the present study the Discriminant validity is satisfied with three criteria as suggested by Fornell and Larcker. In the above table the diagonal values represents the square root of AVE for each construct. The diagonal values are greater than the corresponding column values and row values. In the above table, both the conditions laid for discriminant validity are satisfied. Therefore the discriminant validity of all the constructs in our conceptual model is accepted.
Analysis of Structured Model
At structured model the researcher evaluates relationship between the latent constructs. This stage of assessment is to be done when all the conditions for measurement model are satisfied. Initially the VIF statistics of formative constructs were measured to check existence of problem of multi collinearity.
Table No- 5: VIF Estimates
|
Formative constructs |
VIF Values |
|
Attitude towards Green Product (AGP) |
2.944 |
|
Perceived Subjective Norms (PSN) |
2.621 |
|
Perceived Consumption Effectiveness (PCE) |
2.334 |
Source: Authors’ own interpretation.
It can be noticed from the above table that the VIF estimates of all the formative constructs of Buying intention are less than 3.33 (Diamantopoulos et al., 2008). Hence there is no problem multicollinearity among the formative constructs of the conceptual model. The structured model is further analysed based on goodness of fit. (Hair, Anderson, Tatham, & Black, 1998;Bagozzi et al., 1991). Henseler et al. (2014) proposed SRMR as goodness-of-fit estimates for PLS-SEM analysis, the significance of this estimation is to avoid misspecification. The estimated SRMR value is 0.068 that is less than the ideal criteria of 0.08 (Hair et al.,2019). The NFI estimates is 0.815 is greater than 0.8, then the model is acceptable fit (Bollen,1989; Forza & Filippini,1998; Greenspoon & Saklofske 1998).
Figure No:2 PLS-SEM Output showing P-Value of Conceptual Model
The above figure shows the conceptual model obtained through PLS-SEM output by applying the consistent bootstrapping option (Hair et al.,2019). The conceptual model together represents the inner model and the outer model. The inner model of the conceptual model shows the path coefficients and P-value where as the outer model shows the outer loading of the observed variable and P-value. It is clearly evident in the inner model the relationship between the perceived consumption effectiveness and the buying intention is not significant. Except this all the relationship in the inner model and outer model are significantly related. The path coefficients provided by the PLS algorithm are equivalent to the standardized beta values provided by multiple regression. The value of these path coefficients indicates the magnitude of impact between constructs.
Table No – 6 : Structural Relationship Testing
|
Hypothesis Path |
Path Coefficients |
T-Value |
P-Value |
Null Hypothesis |
|||
|
H1 |
AGP |
à |
BI |
0.372 |
3.925 |
0.000*** |
Rejected |
|
H2 |
AGP |
à |
PCE |
0.721 |
14.842 |
0.000*** |
Rejected |
|
H3 |
AGP |
à |
PSN |
0.769 |
22.887 |
0.000*** |
Rejected |
|
H4 |
PSN |
à |
BI |
0.426 |
5.404 |
0.000*** |
Rejected |
|
H5 |
PCE |
à |
BI |
0.170 |
1.777 |
0.076 |
Fail to Reject |
*** is significant at the 0.001 level (2-tailed)
Findings and Discussion
The thrust of the study was to explore the various underlying factors and their influence on the buying intention of the consumer towards eco-friendly products. After reviewing the available literature extensively and reviewing the relevant theories the present study proposed four important constructs that is “attitude towards green product”, “perceived subjective norms”, “perceived consumption effectiveness” and “buying intention”. The relationships among these constructs were shown in the form of a conceptual framework.
Conclusion and implication
A conceptual framework was proposed in this research paper pertaining to unveil the nexus between the buying intention and its antecedents. The current study successfully explained the important constructs such as Attitude toward green products, perceived subjective norms, and perceived consumption effectiveness and their hypothesised relationship with buying intention. It is concluded from the study that consumer's attitude toward green products is the crucial component that not only favourably influences buying intention, but also positively impacts the consumer's social beliefs and control beliefs. Hence it is an implication before the marketers to design and develop appropriate communication that focuses upon developing favourable attitude of the consumer. Social norms also have a significant impact on consumer purchasing intentions. Consumer control beliefs that determine consumption effectiveness, on the other hand, do not have a favourable impact on their purchasing intentions. The outcome of the study will help the various stake holders directly and indirectly dealing with the marketing of eco-friendly products.
Limitation and scope for future research
The current study is not free from limitation that can be minimized by the future researchers. Earlier studies suggest that the control belief is an important predictor of buying intention, but we found a non significant relationship between these. Hence more research is required in future to explore the non significant relationship between the consumer’s consumption effectiveness and with its buying intention.
The second limitation is the current study did not explore the mediation effect of perceived subjective norms and perceived consumption effectiveness in relation between the attitude towards green product and buying intention.
Finally the present study considered the respondents from five important cities of Odisha and neglected rural areas, hence future researchers are encouraged to do research in larger demography and compare the buying behaviour of urban and rural consumers relating to green product.
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