Next Article in Journal
A Combination Approach of the Numerical Simulation and Data-Driven Analysis for the Impacts of Refracturing Layout and Time on Shale Gas Production
Previous Article in Journal
Water Chemical Characteristics and Safety Assessment of Irrigation Water in the Northern Part of Hulunbeier City, Grassland Area in Eastern China
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Sustainability
Volume 14
Issue 23
10.3390/su142316069
sustainability-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Consumers’ Intentions to Buy Cosmetics and Detergents with Ingredients Made from Recycled CO2

by
Antonia Delistavrou
* and
Irene Tilikidou
Department of Organisations Management, Marketing and Tourism, International Hellenic University, 57400 Thessaloniki, Greece
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(23), 16069; https://doi.org/10.3390/su142316069
Submission received: 11 October 2022 / Revised: 16 November 2022 / Accepted: 28 November 2022 / Published: 1 December 2022
Browse Figure
Versions Notes

Abstract

:
This paper aims to examine Greek consumers’ intentions to purchase innovative green cosmetics and detergents. The new products, not yet delivered to the market, will contain green chemicals produced by recycled CO2, sun, and water. A model of the Theory of Planned Behaviour extended by scepticism was conceptualised, and the relevant measures were originally developed for this study. A survey was conducted through electronic interviews with 306 respondents. Stratified sampling was implemented according to the population distributions of gender and age in Greece. The results revealed that perceived behavioural control was the stronger influencer of intentions, followed by subjective norms, while the impact of attitudes was found to be surprisingly weak. Scepticism was found able to moderate the relationship between subjective norms and consumption intentions, indicating that the influence of important persons on intentions towards green buying is stronger in those consumers who obtained a higher level of scepticism.

1. Introduction

Climate change, due to carbon emissions, has been placed at the top of environmental challenges, while neutrality has been declared both necessary and feasible by 2050, as agreed in the UN Glasgow Financial Alliance for Net Zero (GFANZ) in 2021 [1]. Business missions have to be built on genuinely sustainable corporate goals followed by innovative marketing strategies avoiding greenwash [2,3]. Although ecological marketing has never been in the mainstream of the marketing research agenda, the examination of various aspects of pro-environmental consumer behaviour has provided a plethora of publications for more than three decades [4,5]. Nevertheless, besides organic food [6], research on specific products or product categories has so far remained scant [7,8,9]. This study concerns two Consumer Packaged Goods (CPGs), namely cosmetics and detergents. Personal and house care products represent a significant portion of the chemical industry globally, as they are frequently purchased and daily used [10]. The examination of sustainable production in these two CPGs is of notable importance for environmental protection, as the chemical industry is considered one of the most polluting industrial sectors [11,12]. Recent technological evolutions are able to provide innovative processes in the production of green ingredients that can be used in cosmetics and detergents. Contemporary technologies have been developed in carbon capture, utilisation, and storage (CCUS) [13,14]. This study is mainly related to CCU, also referred to as CO2 recycling [15]. Some new, green oxo products can be produced by recycled CO2, sun, and water. Among them, there are three chemicals, glycolic acid, n-valeraldheyde, and LimoxalTM, all of which can be embedded in personal care and household cleaning products.
It is to be noticed that although evolutions in technology have been reflected in numerous academic publications [16], the consumer side has been rather in its shadow, so far. Nonetheless, it is essential to understand consumer response, as this is the key element for any sustainable offering to obtain success in the marketplace [14,17]. There have been some consumer research efforts concerning carbon footprint labelling [18] and some others on natural or organic cosmetics [19], but the topic of chemical green cosmetics—even more detergents—has remained remarkably unexplored [10,20]. However, chemical cosmetics and detergents occupy by far the largest market share in the relevant sectors. Even more, larger voids exist in the literature with regard to consumers’ intentions to choose new cosmetics and detergents that are going to contain green oxo products [10,14,21].
In pro-environmental consumer research, attitudes are considered to be the dominant antecedent of intentions and behaviour. Nevertheless, a significant gap in evaluations between attitudes and behaviour has many times been indicated [22,23,24,25]. A relatively recent Eurobarometer [26] survey of more than 27,000 Europeans (n = 27,498) has shown that protecting the environment is very (53%) and fairly (41%) important for Europeans, that climate change is a very (77%) and a fairly (14%) serious problem in the EU, and that they agree (26% totally, 42% tend to) that their consumption habits adversely affect the environment in Europe and the rest of the world. Just 22% of them had chosen products with an ecological label in the last six months before that survey.
This study concerns intentions, as cosmetics and detergents containing green chemicals are still in the production stage. Significant theoretical models have been suggested and valorised in order to understand the formulation of consumers’ intentions, among which the Theory of Planned Behaviour (TPB) occupies the most prominent position [27]. Nonetheless, as TPB has been criticised for leaving a considerable portion of the variance in intentions unexplained; that the model should be expanded by additional variables or background factors has been suggested many times, as has more focus on potential inter-relationships among them [5,27,28,29,30]. Mediation and moderation techniques are being utilised in order to reveal hidden aspects within the paths that formulate a dependent behavioural variable [31,32]. Indeed, fruitful outcomes have been indicated in some topics of pro-environmental research [33,34,35]. Examination of intentions is indispensable in this study, as research concerning CPGs with green ingredients is still in its early stages [36]. Additional variables that either precede or interfere in the relationships between consumption intentions and the predictors of TPB are expected to reveal hidden aspects in the procedure that drive intentions.
It is also to be noted that the overall sustainable products account just for 17% of total CPGs market sales [37]. There are many parameters that prevent the expansion of the market, among which consumer scepticism about environmental claims has long been suggested to be quite crucial [38]. Nevertheless, although scepticism has been alleged to be the strongest barrier towards a preference for an eco-product versus a conventional one [39,40], it has so far been rather neglected by both academics and practitioners [2]. Zarei and Maleki [39] argued that it is surprising that papers focusing on pro-environmental purchasing behaviour do not include scepticism.
Therefore, this study aimed to examine a model of TPB that was extended by scepticism with regards to the consumers’ preferences for cosmetics and detergents containing ingredients made from recycled CO2.

2. Theoretical Background and Hypotheses Setting

Fishbein and Ajzen [41] introduced the Theory of Reasoned Actions (TRA), in which intentions are deemed to be determined by attitudes (Att) and subjective norms (SN). Later, Ajzen [42,43] established the Theory of Planned Behaviour (TPB), which is an extension of TRA, as the non-volitional determinant of Perceived behavioural control (PBC) was added to the model. Although TPB has been extensively employed during the last decades in the examination of behavioural intentions, it is still considered to be of profound value [44]. There are ongoing efforts to expand TPB by the addition of several variables in the model, aiming to explain larger portions of variance in intentions and behaviour [44,45]. In TPB, behavioural intentions are determined by consumers’ attitudes (AΤ) towards the behaviour, subjective norms (SN), and perceived behavioural control (PBC) [43]. TPB suggested that intentions to adopt a certain behaviour should increase to the extent that one holds positive attitudes toward the behaviour, thinks that important persons want him/her to perform this behaviour (i.e., injunctive norms) or adopt the behaviour themselves (descriptive norms), and also perceives opportunities but no obstacles to adopting the behaviour [45,46].
With regards to previous findings, it is to be noted that there have been some studies in which TPB was employed for the examination of consumers’ intentions to buy green cosmetics, namely natural or organic personal care products USA [33], Indonesia [47], Malaysia [48], Taiwan [49], Indonesia [50], South Africa [19]. In these studies, attitudes were found to be the strongest impact on intentions, whereas subjective norms and perceived behavioural control were found to influence intentions to a lesser extent in most cases [19,33,47,48,49,50].
With regards to green detergents, Isa et al. [51], in Malaysia, examined buying intentions, which were found to be influenced by the green perceived quality, green perceived value, and green trust towards eco-friendly brands of laundry detergent powder. Arli et al. [52], in Indonesia, employed an extended model of TPB and found that subjective norms were the stronger among the TPB predictors of intentions, while among the additional factors (pro-environmental self-identity, ethical obligation, and consumers’ readiness to be green), the pro-environmental self-identity was found to impact intentions more strongly.
In this study, it is hypothesised that the TPB direct predictors are able to affect consumer preferences for green cosmetics and detergents, which are going to contain green chemical ingredients made from recycled CO2. Therefore, the following hypotheses were set:
H1. 
Attitudes influence Consumers’ Intentions to buy green CPGs.
H2. 
Subjective norms influence Consumers’ Intentions to buy green CPGs.
H3. 
Perceived behavioural control influences Consumers’ Intentions to buy green CPGs.

Scepticism and Consumption Intentions

In terms of theory, Mohr et al. [38] were more probably the first to suggest that when consumers come in contact with eco-labels or advertisements of ecological products, they do not automatically believe them; they may feel sceptical and thus less motivated to buy green. They defined green scepticism as consumers’ doubt about claims that concern the environmental benefits or efficiency of a green product [38]. Obermiller and Spangenberg [53] defined general ad scepticism as disbelief toward advertising claims and argued that sceptics should be less persuaded by green ads. Chang [54] suggested that scepticism might be generated by general attitudes that eco-products are customarily more expensive and less effective than the regular offerings. They argued that ambivalent participants feel higher discomfort with high-effort advertisement claims; this induces lower believability of the green claims in the ad, which results in negative brand attitudes. Leonidou and Skarmeas [2] explained that the root of the term scepticism is found in the Greek word «skeptomai», which means to think, to consider, to ponder, to judge. Whereas a part of this brain function is positive as it induces information seeking, better evaluations and decisions, they suggested that scepticism may generate information seeking, negative word of mouth, and lower willingness to buy green products. They postulated that scepticism can neither increase nor decrease consumers’ attitudes towards attribution and suggested honest business strategies as the antidote to scepticism [2]. Zarei and Maleki [39] argued that purchasing experiences, in which the actual characteristics of a product do not respond to eco-labels on packages, make consumers sceptical the next time they go shopping. Nguyen et al. [3] underlined that consumer scepticism can mostly be derived from “greenwash”. Greenwash means that pro-environmental advertisements or labels deliberately display solely positive information about the product that might be either overly or quite insignificant, in comparison to the overall environmental footprint of the company. For example, a chemical industry might extensively display eco-packaging (packages made from recycled pulp) in order to hide that the factory is responsible for the largest amount of carbon emissions in the specific industrial area. Such cases generate people’s doubts or even suspicions about consumer deception or even larger frauds.
With regards to the employment of mediation and moderation in models that included scepticism, Goh and Balaji [55] in Malaysia found a moderating role for environmental concern and environmental knowledge in a direct causal relationship between scepticism and green purchase intentions. Zarei and Maleki [39] in Iran, on the opposite side, examined the moderating role of scepticism in the relationships between green purchase behaviour and both environmental attitudes and environmental knowledge, but their hypotheses that were not confirmed. Nguyen et al. [3] in China found that scepticism mediated the negative relationship between greenwash and green purchase intentions. Luo et al. [40] in China found a mediating effect of information utility in a direct causal negative relationship between advertising scepticism on social media and green purchase intention.
Overall, scepticism is alleged to induce uncertainty about the advertised ecological features of a product, the actual contribution of such products to environmental protection, or the quality and efficacy of eco-products; it was found capable of leading to lower assessments of eco-products [39]. Therefore, it can be assumed that scepticism is able to negatively affect intentions towards several types of pro-environmental purchasing behaviours. It is noted that, to the best of our knowledge, there has not been any other study to examine the moderating role of scepticism in a TPB model to date. Hence, the following hypothesis was set:
H4. 
Scepticism moderates the relationships between Consumption intentions and each one of (a) Attitudes, (b) Subjective norms, and (c) Perceived behavioural control.

3. Methodology

A survey was conducted according to the stratified sampling method [56,57]. The strata of the sample were designed based on the population distribution of gender and age. Online interviews were undertaken by a research agency on a Greek consumer panel during November–December 2021. Finally, 306 usable questionnaires were collected.
A structured questionnaire included the TPB variables originally developed for the requirements of this study, and a measure of scepticism towards environmental claims adopted from Mohr et al. [38]. The development of the TPB variables was based on the procedure suggested by the founder and the TACT (Target, Action, Context, Time) methodology, which guided the development of the behavioural intentions [42]. According to the principle of compatibility, all other measures of the theoretical model should be developed following the intentions conceptualisation. Thus, Target is “CPGs (cosmetics and detergents) with green, chemical ingredients”, Action is “consumers’ intentions to prefer them”, Context is “any point of sale,” and Time is “when available in the market”. A long development procedure was undertaken to construct original scales for all the TPB variables. In the first step, four different groups of 20 marketing students (from the International Hellenic University) were recruited in deliberately organised elicitation studies in order to gather phrases regarding, separately, their attitudes, subjective norms, perceived behavioural control and purchasing intentions towards CPGs that are going to contain green chemicals. In the second step, all the above-mentioned statements were included in a questionnaire, which served as the instrument of a preliminary student study. The questionnaire was administered to a cluster sample of 231 marketing students. The relevant data were analysed to refine the measures by conducting exploratory factor analysis (principal component analysis with varimax rotation) and internal consistency analysis (Cronbach’s alpha and item-to-total correlations). In the third step, the refined measures were pilot tested with four marketing experts for face validity and a convenient sample of 25 consumers. After minor modifications, the final questionnaire included the following variables: attitudes (Att) with five items, measured on a 6-point semantic differential scale; subjective norms (SN); perceived behavioural control (PBC), and consumption intentions (CI) with four items each, measured on 6-point Likert scales from 1 = Absolutely Disagree to 6 = Absolutely Agree. Mohr et al.’s [38] scepticism (Sc) consists of 6 items, also measured on a 6-point Likert scale. Five demographic characteristics were also included in the questionnaire, namely gender, age, level of formal education, annual income, and occupation. The demographics of the sample are presented in Table 1. The t-tests did not indicate any statistically significant differences between the characteristics of the sample and the population parameters [58].
Statistical analyses were conducted via SPSS v.17 and AMOS v.20. Firstly, the data were examined for missing data and outlier detection. Then, Cronbach’s alpha was calculated in each initial scale to ensure the internal consistency of the measures. Confirmatory factor analysis (CFA) was conducted in the measurement model to ensure adequate measurement for structural equation modelling. After that, the inspection of common method bias and the descriptive analysis of the final measures followed. Finally, the structural model analysis was conducted.

4. Results

4.1. Data Examination and Reliability

Before proceeding to further analyses, the data were screened for missing values and outliers. No missing values were indicated while the Mahalanobis D2 test detected 14 outliers confining the sample to 292 cases for further analysis. Cronbach’s alpha values were above 0.80 except for the Sk scale (Att: 0.898, SN: 0.924, PBC: 0.880, CI: 807, Sk: 0.707). It is to be noted that two out of six items of Mohr et al.’s [38] construct were eliminated in the item analysis process, and Cronbach’s alpha increased to 0.869.

4.2. Measurement Model

Before proceeding to further analyses, the data were screened for cross-loadings and error covariances and tested for bias due to common method variance. The examination of the modification indices resulted in the exclusion of two items of the Att variable (Att1, Att5) due to cross-loadings and two items of the CI variable (CI1, CI2) due to high error covariances. Harman’s single factor test was employed to test the common method variance bias [59]. Exploratory factor analysis with principal components was conducted for all items of all constructs, and the variance extracted in the 1st factor was found to be 28.38% (<50%). Consequently, the data are considered unbiased of common method variance [59].
The measurement model resulted in well-accepted goodness-of-fit (GOF) values (Table 2). The validity of the measurement model was then examined in terms of convergence and discriminant validity [60]. Convergence validity was assessed (see Table 2) with (a) all factor loadings being higher than 0.70, (b) all values of average variance extracted (AVE) being higher than 0.50, which indicate adequate convergence, and (c) all values of construct reliability being higher than 0.80, which indicate that all constructs demonstrate exemplary reliability [60,61]. Discriminant validity was assessed for all constructs (Table 2), with the AVE values of all 2-construct combinations being greater than the respective squared correlation of each combination [60]. Finally, nomological validity was assessed with statistically significant correlations for all pairs of constructs in the hypothesised direction (Table 2). In conclusion, the measurement model was judged to be valid, so the examination of the structural model followed.

4.3. Descriptive Statistics

The measure of Att takes theoretical values from 3 to 18 and, with a mean of 13.226, (see Table 2) indicated rather positive attitudes towards purchasing CPGs with green chemicals. SN takes theoretical values from 4 to 24 and, with a mean of 15.346, indicated a moderate level of perceived social pressure, while PBC, which also takes theoretical values from 4 to 24, with a mean of 17.089 indicated a rather high level of control over purchasing green CPGs. CI takes theoretical values from 2 to 12 and, with a mean of 8.459, indicated a rather high level of intentions to purchase CPGs with green chemicals. Sc takes theoretical values from 4 to 24 and, with a mean of 14.322, indicated a moderate level of scepticism towards environmental claims. Internal consistency was reassessed, and all measures indicated well-accepted Cronbach’s alpha values from 0.847 to 0.924 (Table 2).

4.4. Structural Model

4.4.1. Original TPB

The GOF values obtained (Figure 1) indicated that the structural model fits the data very well. CI obtained statistically significant structural relationships with SN and PBC. The structural relationship between CI and Att was marginally significant (p < 0.10). In sum, the structural model results led to accepting H1, H2, and H3. The squared multiple correlation indicated that 64.5% of the variance in CI is explained by the interacting effects of Att, SN, and PBC.

4.4.2. Expanded TPB

As mentioned in the theoretical background, moderation occurs when the strength of a relationship depends on the level of another variable, i.e., a moderator [31]. In this study, the moderating role of scepticism was tested via multi-group analysis [60] with AMOS v.20. The goal of this analysis was to test the magnitude and the strength of the relationships between CI and each one of Att, SN, and PBC across the respondents’ level of Sc towards environmental claims. The sample was divided into two groups, i.e., those who obtained scores in Sc below the mean and those who obtained scores above the mean (51.4% and 48.6%, respectively).
Firstly, the measurement invariance across groups was assessed by means of configural and metric invariance. Configural invariance was assessed with acceptable GOF values (χ2 = 196.197, df = 116, TLI = 0.963, CFI = 0.973, RMSEA = 0.049) in the unconstrained model (all factor loadings were free to vary across groups, i.e., the measurement model). Then, a constrained model (all factor loadings were constrained to be invariant across groups) was run, and the GOF values (χ2 = 210.321, df = 125, TLI = 0.964, CFI = 0.971, RMSEA = 0.049) indicated a good fit to the data. Metric invariance was assessed as the Δχ2 test (Δχ2/df = 1.569) between the unconstrained and the constrained model was within the interval (±1.96), indicating that the two models are not statistically different.
In order to test the impact of the moderator (Sc) on the structural relationships of the TPB model, the differences in the relevant paths between the two groups (below and above the Mean in Sc) were tested by the examination of the structural invariance. The procedure incorporated the examination of the critical ratios of the differences between the paths across the two groups and the Δχ2 test between the unconstrained (all structural relationships were freely estimated) and the constrained models (structural relationships were constrained to be invariant across groups). The unconstrained model obtained acceptable GOF values (χ2 = 196.197, df = 116, TLI = 0.963, CFI = 0.973, RMSEA = 0.049). The examination of the critical ratios indicated that there is a statistically significant difference between the groups only in the structural relationship between SN and CI (critical ratio:1.993). The differences in the other paths (Att on CI and PBC on CI) were found to be non-significant (critical ratios: 0.407 and -0.056, respectively). After that, a structural model was run in which the path from SN to CI was constrained to be invariant across groups. The GOF values obtained (χ2 = 200.178, df = 117, TLI = 0.962, CFI = 0.972, RMSEA = 0.050) indicated that the model fits the data well. The Δχ2 test estimation (Δχ2/df = 3.981) was out of the interval ±1.96, indicating that the constrained model obtained a statistically significant worse fit than the unconstrained one. The results in Figure 1 indicate that there is a statistically significant (p < 0.05) difference between the two groups in the effect of SN on CI, which is altered as a function of Sc (moderator). The standardised weights obtained in the two groups indicate that the effect of SN on CI is stronger in the group of consumers with a higher level of Sc (above the mean) than in those with a lower level of Sc (below the mean) toward environmental claims. These results led to the acceptance of H4b and to the rejection of H4a and H4c.
Overall, with regards to the effect of SN on CI, the squared multiple correlation coefficients indicated that the variance explained, in the expanded by Sc TPB model (Figure 1), is higher (71.5%) in the group of consumers who obtained scores in Sc above the mean than in the group who obtained scores in Sc below the mean (61%).

5. Discussion and Conclusions

This study indicated that TPB is powerful to explain consumption intentions (CI) towards cosmetics and detergents that will contain innovative, green ingredients made from recycled CO2. It was indicated that the stronger determinant of CI is PBC, followed by SN, while Att were found to impact on CI weakly. According to the previous research findings, most of which were presented in the theoretical framework section (e.g., [33]), attitudes have been portrayed as the strongest predictor of intentions across time, for a number of products. In contrast, this study—which concerns cosmetics and detergents with green chemicals—indicated that the stronger predictor of Greek consumers’ intentions is their perceptions about control, followed by subjective norms, while the impact of attitudes was found to be surprisingly very weak. These findings verify Ajzen’s [43] notice that the ability of each determinant to explain people’s intentions might differ across behaviours or contexts. It seems that personal confidence, easiness, and absence of obstacles are the most important indicators of willingness to prefer fast-moving consumer goods in Greece during this particular period, i.e., post-recession but still during COVID-19 restrictions. The importance of subjective norms was found to follow control in terms of influence strength. The respondents of this study expressed rather strong perceptions regarding family members and important persons who would like them to choose green cosmetics and detergents.
Secondly, it is to be commented that there is a noticeable impact in the portion of variance explained when scepticism was entered into the model as a moderator. The relationship between SN and CI was strengthened when scepticism (Sc) entered the model as moderator. The expanded by Sc TPB model was found to be more powerful than the original one. The percentage of variance explained in CI for those who obtained Sc scores below the mean, was found to be 61.0%, raising to 71.5% in the group of those who obtained Sc scores above the mean.
It is to be commented that scepticism was found to moderate (increase) only the relationship between subjective norms and intentions, whereas the hypothesised moderating effects of scepticism in the relationships between attitudes and intentions, as well as those between perceived control and intentions, were not verified. These findings are in line, to an extent, with Zarei and Maleki’s [39] study, in which the moderating effects of scepticism between environmental attitudes or environmental knowledge and green purchasing behaviour were not confirmed. In fact, it seems that Zarei and Maleki [39] were right to claim that scepticism is able neither to increase nor decrease attitudes. Nonetheless, this study confirms that scepticism might be able to interfere in the relationship between subjective norms and intentions. In any case, the finding that scepticism strengthens the relationship between subjective norms and intentions should be further discussed and analysed. Evidence was provided by this study that, in Greece, the influence of other important persons on consumer preferences for green cosmetics and detergents is stronger in sceptics than in their counterparts. In other words, it might be implied that the more sceptical someone is, the more influenced by important people he/she is. Further comparisons with other previous research results are not feasible due to the extensive differences in the relevant theoretical frameworks.
Overall, it is concluded that consumer preferences for the new green chemical cosmetics and detergents are mostly influenced by their sense of control while higher levels of consumer scepticism increase the capacity of other important authorities to influence these intentions.

6. Implications

This study enriched, to an extent, our knowledge with relevance to consumers’ response to new green CPGs containing innovative chemicals, made from recycled CO2. TPB was for the first time applied to examine consumers’ intentions to purchase new, green cosmetics and detergents, while the model was expanded by the employment of scepticism as a factor constraining intentions. Both theoretical and practical implications can be drawn by the outcomes of this study.
In terms of theory, the results of this study imply the dominant role of behavioural control in the formulation of intentions towards buying green, daily use products. The usual acceptance of attitudes as the stronger predictor of intentions is challenged in this paper. Of course, the findings concern solely cosmetics and detergents, with regards to a particular time and place. Nonetheless, it might be implied that the above overall direction seems promising with regards to other fast-moving products and/or services.
Findings regarding subjective norms are of equal, if not superior importance, as the impact of significant persons on intentions was indicated to be higher among sceptics. It can be argued that there is much more to be understood with regard to the role of subjective norms, particularly in connection with some psychographic cohorts of consumers. It seems that the role of SN might be crucial in terms of its effect on some groups of consumers, particular those who are doubtful or reluctant to formulate positive intentions towards a distinctly significant pro-environmental change of habits with regard to their daily choices. Above all, the results that concern scepticism imply that there is a whole separate theoretical direction that has been noticeably neglected in pro-environmental consumer research. This direction involves examining not only the factors that can motivate consumers to act pro-environmentally, but also, if not primarily, those factors that prevent them from acting in favour of the natural environment. This perspective might be found to be of extraordinary value, as it promises mitigation of the social desirability effect in measurement, as well as the disclosure of hidden insights in the formulation of pro-environmental intentions and actual behaviour.
Further, numerous practical implications are derived by the results of this study. Businesses interested in the development of innovative, sustainable CPGs formulas, as well as commercial enterprises interested in penetrating the market of cosmetics and detergents, could make productive use of the results of this study when designing their marketing strategies. First of all, they should explain via all possible communication media that chemical cosmetics and detergents can be truly environmentally friendly. In fact, green chemical products can offer much more to sustainability goals, as they can preserve carbon emissions to a considerably larger extent than can the production of natural or organics. It is to be noted that organics concern just the agricultural sector whereas chemical products concern the much more polluting industrial sector. Secondly, the results imply that chemical industries have to avoid greenwash by all means. Marketing managers shall have to realise—and accordingly persuade the headquarters—that the only way to proceed is via adoption and implementation of a holistic, environmentally friendly strategy, even if this initially requires temporary costly investments in carbon capture and utilisation. Including in the composition of either cosmetics or detergents the new, green oxo products, made by recycled CO2, will be proven greatly beneficial in the long run. Further, the packaging labels on the new cosmetics and detergents, as well as any kind of advertisement, should include genuine, honest, pro-environmental claims, possibly explaining—in an easy-to-understand way—the contribution of recycled CO2 in the reduction of carbon emissions and hence in climate change mitigation. The relevant marketing communication efforts should valorise consumers’ sense of confidence to choose new, innovative, green offerings. When these products reach the market, the overall advertisement effort shall have to creatively present the absence of any obstacles to their preference. In addition, distinctly loud messages should specifically target doubts about environmental claims in ads by placing emphasis on close referents, as well important public persons who are already convinced to buy the new green CPGs and would enthusiastically recommend consumers to act similarly.

7. Limitations and Further Research Suggestions

There are, of course, evident limitations in this paper, most of which lead to suggestions for future research. First of all, although the estimation of common method variance was found to be satisfactory, there is always an effect of social desirability in pro-environmental research. This is indicated in the rather high scores obtained in both attitudes and intentions. This issue should be taken care of in future research, most likely with the help of a separate measure able to remove the effect of social desirability. Further, the attitudinal measure was found to be rather weak in terms of both measurement quality (just three items remained after refining the measurement model) and its impact on intentions (significant at p < 0.10 and weak). This evaluation calls for an additional measure for attitudes, possibly more closely related to the reduction of carbon emissions. The emergence of behavioural control, as the strongest influencer, indicates the great importance of convenience and self-confidence in shaping consumers’ intentions. This direction should not be underestimated in future research designs. With relevance to the inclusion of scepticism in the expanded TPB model of this study, the results are judged to be rather limited as only the moderating role of scepticism in the relationship between subjective norms and intentions was revealed. It is apparent that there is much more to be understood with reference to the role of scepticism and its position and function in a TPB model, either as a mediator/moderator or perhaps as a background or even a direct to intentions factor. The fact that Sc provided limited effects in this study, coupled with its limited use in previous research, could perhaps be attributed to Mohr et al.’s [38] measure itself. There is most likely a requirement for a new, more contemporary, and valid measurement of scepticism to serve future research. Furthermore, there are essentially endless options in approaching the grid of variables that might interfere in a TPB model and formulate behavioural intentions. Moreover, this study clearly highlighted the necessity of investigating the actual behaviour when the new green cosmetics and detergents find their place in the market. As the United Nations Framework for Climate Change [61] postulated the urgent goal of decompressing the climate emergency in favour of both humanity and the physical environment, the connection between technology and consumer research is necessary, and pressingly required.

Author Contributions

Conceptualisation, A.D. and I.T.; methodology, A.D. and I.T.; software, A.D.; validation, A.D. and I.T.; formal analysis, A.D. and I.T.; investigation, A.D. and I.T.; resources, A.D. and I.T.; data curation, A.D. and I.T.; writing—original draft preparation, A.D. and I.T.; writing—review and editing, A.D. and I.T.; visualisation, A.D.; supervision, A.D. and I.T.; project administration, A.D. and I.T.; funding acquisition, A.D. and I.T. All authors have read and agreed to the published version of the manuscript.

Funding

The research leading to these results has received funding from the European Union’s Horizon 2020 innovation action programme under grant agreement No. 862192—SunCoChem project.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki. The interviews were undertaken by a research agency, which is a member of The Market Research and Public Opinion Companies Association (SEDEA) of Greece and the European Society for Opinion and Market Research (ESOMAR). The interviews with consumers were carried out in accordance with the relevant codes of ethics (http://www.hrh.gr/en/about-us/accreditations-code-of-ethics), accessed on 10 October 2022.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Data available on request due to restrictions. The data presented in this study are available on request from the corresponding author. The data are not publicly available due to a privacy agreement introduced with the informed consent.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. United Nations. GFANZ Glasgow Financial Alliance for Net Zero. Available online: https://www.gfanzero.com/ (accessed on 7 March 2022).
  2. Leonidou, C.N.; Skarmeas, D. Gray shades of green: Causes and consequences of green skepticism. J. Bus. Ethics 2017, 144, 401–415. [Google Scholar] [CrossRef] [Green Version]
  3. Nguyen, T.T.H.; Yang, Z.; Nguyen, N.; Johnson, L.W.; Cao, T.K. Greenwash and green purchase intention: The mediating role of green scepticism. Sustainability 2019, 11, 2653. [Google Scholar] [CrossRef] [Green Version]
  4. Chen, H.; Long, R.; Niu, W.; Feng, Q.; Yang, R. How does individual low-carbon consumption behavior occur? An analysis based on attitude process. Appl. Energy 2014, 116, 376–386. [Google Scholar] [CrossRef]
  5. Joshi, Y.; Uniyal, D.P.; Sangroya, D. Investigating consumers’ green purchase intention: Examining the role of economic value, emotional value and perceived marketplace influence. J. Clean. Prod. 2021, 328, 129638. [Google Scholar] [CrossRef]
  6. Chen, M.F. Selecting environmental psychology theories to predict people’s consumption intention of locally produced organic foods. Int. J. Consum. Stud. 2020, 44, 455–468. [Google Scholar] [CrossRef]
  7. Bertrandias, L.; Elgaaied-Gambier, L. Others’ environmental concern as a social determinant of green buying. J. Consum. Mark. 2014, 31, 417–429. [Google Scholar] [CrossRef]
  8. Schuitema, G.; De Groot, J.I.M. Green consumerism: The influence of product attributes and values on purchasing intentions. J. Consum. Behav. 2015, 14, 57–69. [Google Scholar] [CrossRef] [Green Version]
  9. Barbarossa, C.; De Pelsmacker, P. Positive and negative antecedents of purchasing eco-friendly products: A comparison between green and non-green consumers. J. Bus. Ethics 2016, 134, 229–247. [Google Scholar] [CrossRef]
  10. Kronthal-Sacco, R.; Van Holt, T.; Atz, U.; Whelan, T. Sustainable purchasing patterns and consumer responsiveness to sustainability marketing messages. J. Sustain. Res. 2020, 2, 200016. [Google Scholar] [CrossRef]
  11. DECHEMA. Low Carbon Energy and Feedstock for the European Chemical Industry. Available online: https://dechema.de/dechema_media/Downloads/Positionspapiere/Technology_study_Low_carbon_energy_and_feedstock_for_the_European_chemical_industry.pdf (accessed on 18 January 2022).
  12. Jones, C.R.; Olfe-Kräutlein, B.; Naims, H.; Armstrong, K. The social acceptance of carbon dioxide utilisation: A review and research agenda. Front. Energy Resour. 2017, 5, 11. [Google Scholar] [CrossRef]
  13. Van Heek, J.; Arning, K.; Ziefle, M. Reduce, reuse, recycle: Acceptance of CO2 utilisation for plastic products. Energy Policy 2017, 105, 53–66. [Google Scholar] [CrossRef]
  14. Linzenich, A.; Arning, K.; Offermann-van Heek, J.; Ziefle, M. Uncovering attitudes towards carbon capture storage and utilisation technologies in Germany: Insights into affective-cognitive evaluations of benefits and risks. Energy Res. Soc. Sci. 2019, 48, 205–218. [Google Scholar] [CrossRef]
  15. Perathoner, S.; Centi, G. CO2 recycling: A key strategy to introduce green energy in the chemical production chain. ChemSusChem 2014, 7, 1274–1282. [Google Scholar] [CrossRef] [PubMed]
  16. Arning, K.; Offermann-van Heek, J.V.; Ziefle, M. Acceptance profiles for a carbon-derived foam mattress. Exploring and segmenting consumer perceptions of a carbon capture and utilisation product. J. Clean. Prod. 2018, 188, 171–184. [Google Scholar] [CrossRef]
  17. Jones, C.R.; Kaklamanou, D.; Stuttard, W.M.; Radford, R.L.; Burley, J. Investigating public perceptions of carbon dioxide utilisation (CDU) technology: A mixed methods study. Faraday Discuss. 2015, 183, 327–347. [Google Scholar] [CrossRef] [Green Version]
  18. Canavari, M.; Coderoni, S. Consumer stated preferences for dairy products with carbon footprint labels in Italy. Agric. Food Econ. 2020, 8, 4. [Google Scholar] [CrossRef] [Green Version]
  19. Shimul, A.S.; Cheah, I.; Khan, B.B. Investigating female shoppers’ attitude and purchase intention toward green cosmetics in South Africa. J. Glob. Mark. 2022, 35, 37–56. [Google Scholar] [CrossRef]
  20. Patak, M.; Branska, L.; Pecinova, Z. Consumer intention to purchase green consumer chemicals. Sustainability 2021, 13, 7992. [Google Scholar] [CrossRef]
  21. Bom, S.; Jorge, J.; Ribeiro, H.M.; Marto, J. A step forward on sustainability in the cosmetics industry: A review. J. Clean. Prod. 2019, 225, 270–290. [Google Scholar] [CrossRef]
  22. Chekima, B.; Chekima, S.; Wafa, S.A.W.S.K.; Igau, O.A.; Sondoh, S.L., Jr. Sustainable consumption: The effects of knowledge, cultural values, environmental advertising, and demographics. Int. J. Sustain. Dev. World Ecol. 2016, 23, 210–220. [Google Scholar] [CrossRef]
  23. ElHaffar, G.; Durif, F.; Dubé, L. Towards closing the attitude-intention-behavior gap in green consumption: A narrative review of the literature and an overview of future research directions. J. Clean. Prod. 2020, 275, 122556. [Google Scholar] [CrossRef]
  24. Bangsa, A.B.; Schlegelmilch, B.B. Linking sustainable product attributes and consumer decision-making: Insights from a systematic review. J. Clean. Prod. 2020, 245, 118902. [Google Scholar] [CrossRef]
  25. Coffin, J.; Egan–Wyer, C. The ethical consumption cap and mean market morality. Mark. Theory 2022, 22, 105–123. [Google Scholar] [CrossRef]
  26. European Union. Attitudes of European Citizens Towards the Environment, Special Eurobarometer 501. Available online: https://data.europa.eu/data/datasets/s2257_92_4_501_eng?locale=en (accessed on 12 September 2022).
  27. Sun, W. Toward a theory of ethical consumer intention formation: Re-extending the theory of planned behaviour. AMS Rev. 2020, 10, 260–278. [Google Scholar] [CrossRef] [Green Version]
  28. Yadav, R.; Pathak, G.S. Young consumers’ intention towards buying green products in a developing nation: Extending the theory of planned behaviour. J. Clean. Prod. 2016, 135, 732–739. [Google Scholar] [CrossRef]
  29. Li, A.; Wang, Z.; Li, Y.; Liao, A. Impacts of consumer innovativeness on the intention to purchase sustainable products. Sustain. Prod. Consum. 2021, 27, 774–786. [Google Scholar] [CrossRef]
  30. Delistavrou, A. Theory of planned behaviour and boycotting: The moderating role of socio-political control and demographics. EuroMed J. Bus. 2022, 17, 270–287. [Google Scholar] [CrossRef]
  31. Preacher, K.J.; Rucker, D.D.; Hayes, A. Addressing moderated mediation hypotheses: Theory, methods, and prescriptions. Multivar. Behav. Res. 2007, 42, 185–227. [Google Scholar] [CrossRef]
  32. Demming, C.L.; Jahn, S.; Boztûg, Y. Conducting mediation analysis in marketing research. J. Res. Manag. 2017, 39, 76–93. [Google Scholar] [CrossRef]
  33. Kim, H.Y.; Chung, J.E. Consumer purchase intention for organic personal care products. J. Consum. Mark. 2011, 28, 40–47. [Google Scholar] [CrossRef]
  34. Polonsky, M.J.; Vocino, A.; Grimmer, M.; Miles, M.P. Temporal and environmental orientation and PECB. Int. J. Consum. Stud. 2014, 38, 612–619. [Google Scholar] [CrossRef]
  35. Qu, Y.; Xu, F.; Lyu, X. Motivational place attachment dimensions and the pro-environmental behaviour intention of mass tourists: A moderated mediation model. Curr. Issues Tour. 2019, 22, 197–217. [Google Scholar] [CrossRef]
  36. Pop, R.-A.; Săplăcan, Z.; Alt, M.-A. Social media goes green—The impact of social media on green cosmetics purchase motivation and intention. Information 2020, 11, 447. [Google Scholar] [CrossRef]
  37. NYU STERN Center for Sustainable Business. Sustainable Market Share Index, 2021 Report. Available online: https://www.stern.nyu.edu/experience-stern/about/departments-centers-initiatives/centers-of-research/center-sustainable-business/research/csb-sustainable-market-share-index (accessed on 12 September 2022).
  38. Mohr, L.A.; Eroğlu, D.; Ellen, P.S. The development and testing of a measure of skepticism toward environmental claims in marketers’ communications. J. Consum. Aff. 1998, 32, 30–55. [Google Scholar] [CrossRef]
  39. Zarei, A.; Maleki, F. From decision to run: The moderating role of green skepticism. J. Food Prod. Mark. 2018, 24, 96–116. [Google Scholar] [CrossRef]
  40. Luo, B.; Sun, Y.; Shen, J.; Xia, L. How does green advertising skepticism on social media affect consumer intention to purchase green products? J. Consum. Behav. 2020, 19, 371–381. [Google Scholar] [CrossRef]
  41. Fishbein, M.; Ajzen, I. Belief, Attitude, Intention, and Behaviour: An Introduction to Theory and Research; Addison-Wesley: Reading, MA, USA, 1975. [Google Scholar]
  42. Ajzen, I. From Intentions to Actions: A Theory of Planned Behaviour. In Action Control: From Cognition to Behavior; Kuhl, J., Beckmann, J., Eds.; Springer: Berlin, Germany, 1985; pp. 11–39. [Google Scholar]
  43. Ajzen, I. The theory of planned behaviour. Organ. Behav. Hum. Decis. Process. 1991, 50, 179–211. [Google Scholar] [CrossRef]
  44. Bosnjak, M.; Ajzen, I.; Schmidt, P. The theory of planned behavior: Selected recent advances and applications. Eur. J. Psychol. 2020, 16, 352–356. [Google Scholar] [CrossRef]
  45. Fishbein, M.; Ajzen, I. Predicting and Changing Behavior: The Reasoned Action Approach; Taylor and Francis Inc.: New York, NY, USA, 2010. [Google Scholar]
  46. De Leeuw, A.; Valois, P.; Ajzen, I.; Schmidt, P. Using the theory of planned behavior to identify key beliefs underlying pro-environmental behavior in high-school students: Implications for educational interventions. J. Environ. Psychol. 2015, 42, 128–138. [Google Scholar] [CrossRef]
  47. Askadilla, W.L.; Krisjanti, M.N. Understanding Indonesian green consumer behavior on cosmetic products: Theory of Planned Behavior model. Pol. J. Manag. Stud. 2017, 15, 7–15. [Google Scholar] [CrossRef]
  48. Ghazali, E.; Soon, P.C.; Mutum, D.S.; Nguyen, B. Health and cosmetics: Investigating consumers’ values for buying organic personal care products. J. Retail. Consum. Serv. 2017, 39, 154–163. [Google Scholar] [CrossRef]
  49. Hsu, C.L.; Chang, C.Y.; Yansritakul, C. Exploring purchase intention of green skincare products using the theory of planned behavior: Testing the moderating effects of country of origin and price sensitivity. J. Retail. Consum. Serv. 2017, 34, 145–152. [Google Scholar] [CrossRef]
  50. Chin, J.; Jiang, B.C.; Mufidah, I.; Persada, S.F.; Noer, B.A. The investigation of consumers’ behavior intention in using green skincare products: A pro-environmental behavior model approach. Sustainability 2018, 10, 3922. [Google Scholar] [CrossRef] [Green Version]
  51. Isa, S.M.; Lim, C.K.; Chin, P.N. Green purchase intention of laundry detergent powder in presence of eco-friendly brand. Glob. Bus. Manag. Res. Int. J. 2017, 9, 128–143. [Google Scholar]
  52. Arli, D.; Tan, L.P.; Tjiptono, F.; Yang, L. Exploring consumers’ purchase intention towards green products in an emerging market: The role of consumers’ perceived readiness. Int. J. Consum. Stud. 2018, 42, 389–401. [Google Scholar] [CrossRef]
  53. Obermiller, C.; Spangenberg, E.R. On the origin and distinctness of skepticism toward advertising. Mark. Lett. 2000, 11, 311–322. [Google Scholar] [CrossRef]
  54. Chang, C. Feeling ambivalent about going green. J. Advert. 2011, 40, 19–32. [Google Scholar] [CrossRef]
  55. Goh, S.K.; Balaji, M.S. Linking green skepticism to green purchase behaviour. J. Clean. Prod. 2016, 131, 629–638. [Google Scholar] [CrossRef]
  56. Zikmund, W.G. Exploring Marketing Research, 8th ed.; Thomson/South-Western: Cincinnati, OH, USA, 2003. [Google Scholar]
  57. Churchill, G.A., Jr.; Iacobucci, D. Marketing Research: Methodological Foundations, 9th ed.; Thomson South-Western Publishers: Orlando, FL, USA, 2005. [Google Scholar]
  58. Podsakoff, P.M.; MacKenzie, S.B.; Lee, J.-Y.; Podsakoff, N.P. Common method biases in behavioral research: A critical review of the literature and recommended remedies. J. Appl. Psychol. 2003, 88, 879–903. [Google Scholar] [CrossRef]
  59. Hair, J.F.; Black, W.C.; Balin, B.J.; Anderson, R.E. Multivariate Data Analysis. In Maxwell Macmillan International Editions; Macmillan International: Stuttgart, Germany, 2010. [Google Scholar]
  60. Bagozzi, R.P.; Yi, Y. On the evaluation of structural equation models. J. Acad. Mark. Sci. 1988, 16, 74–94. [Google Scholar] [CrossRef]
  61. UNCC/United Nations Framework Convention on Climate Change Annual Report 2020. Available online: https://unfccc.int/sites/default/files/resource/UNFCCC_Annual_Report_2020.pdf (accessed on 7 April 2022).
Sustainability 14 16069 g001 550
Figure 1. Expanded TPB, hypotheses and results.
Figure 1. Expanded TPB, hypotheses and results.
Sustainability 14 16069 g001
Table
Table 1. Sample demographics.
Table 1. Sample demographics.
n% n%
Total306100Total306100
Gender Annual Income
Men14748.0up to 5.000€4916.0
Women15952.0between 5.001–15.000€8427.5
between 15.001–25.000€8126.5
Age between 25.001–35.000€3611.8
18–24 years old3611.8between 35.001–45.000€ 92.9
25–34 years old5819.0between 45.001–55.001€62.0
35–44 years old6220.355.001€ and more20.7
45–54 years old7323.9No answer3912.7
55–64 years old5618.3Occupation
65 years or older216.9Professional/Entrepreneur/Farmer3310.8
Private employee9832.0
Education Public employee4514.7
Primary school144.6Unemployed4815.7
Secondary school11437.3Houseperson 134.2
Vocational training6119.9Retired309.8
University8026.1Student268.5
Masters’3110.1Other 72.3
Ph.D.62.0No answer 62.0
Table
Table 2. Measurement Model and Descriptives.
Table 2. Measurement Model and Descriptives.
GOFχ2dfSig.χ2/dfCFITLIRMSEA
Results120.81258p < 0.0012.0830.9780.9710.061
Cut-off ≤3.0≥0.90≥0.90≤0.80
MeansFactor LoadingsCR
Attitudes(Range: 3–18,Cronbach’s alpha: 0.921)13.226 0.926
Att2: Undesirable-Desirable 4.5030.801
Att3: Unwise (Foolish)/Wise4.3150.954
Att4: Negative/Positive4.4070.933
Subjective Norms(Range: 4–24, Cronbach’s alpha: 0.924)15.346 0.915
SN1: My family members think I should not/should buy CPGs containing green chemical ingredients 3.8730.903
SN2: My friends think I should not/should buy CPGs containing green chemical ingredients 3.8180.917
SN3: Important people who influence my behaviour think I should not/should buy CPGs containing green chemical ingredients 3.8320.797
SN4: Persons who are significant to me do buy CPGs containing green chemical ingredients for themselves3.8220.795
Perceived behavioural control(Range: 4–24, alpha: 0.880)17.089 0.884
PBC1: Selecting a CPG containing green chemical ingredients is completely up to me. 4.2880.768
PBC2: I am confident that if I want to buy a CPG containing green chemical ingredients, I can buy it. 4.4180.896
PBC3: There are no obstacles for me if I want to select a CPG with green, chemical ingredients 4.2120.794
PBC4: I am confident that I can easily find a CPG containing green chemical ingredients if I want to buy it4.1710.778
Consumption Intentions(Range: 2–12, Cronbach’s alpha: 0.847)8.459 0.849
CI3: I am seriously thinking to buy CPGs containing environmentally friendlier ingredients as soon as I run out of the products I am currently using4.2500.821
CI4: I will definitely switch to a brand of a CPG that contains green chemical ingredients4.2090.896
AttSNPBCCI
Average Variance Extracted0.8070.7310.6570.738
Correlations (squared correlations)
Attitudes 0.423 (0.179)0.318 (0.101)0.411 (0.169)
Subjective Norms 0.517 (0.267)0.669 (0.448)
Perceived Beh. Control 0.719 (0.517)
GOF: Goodness of Fit, CR: Construct Reliability, AVE: Average Variance Extracted.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Delistavrou, A.; Tilikidou, I. Consumers’ Intentions to Buy Cosmetics and Detergents with Ingredients Made from Recycled CO2. Sustainability 2022, 14, 16069. https://doi.org/10.3390/su142316069

AMA Style

Delistavrou A, Tilikidou I. Consumers’ Intentions to Buy Cosmetics and Detergents with Ingredients Made from Recycled CO2. Sustainability. 2022; 14(23):16069. https://doi.org/10.3390/su142316069

Chicago/Turabian Style

Delistavrou, Antonia, and Irene Tilikidou. 2022. "Consumers’ Intentions to Buy Cosmetics and Detergents with Ingredients Made from Recycled CO2" Sustainability 14, no. 23: 16069. https://doi.org/10.3390/su142316069

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop