Consumers' purchasing decisions regarding environmentally friendly products: An empirical analysis of German consumers
Introduction
Environmentally friendly or “green” buying behavior is one of the domains in which consumers are able to transfer their environmental concerns into corresponding actions. Green behavior reflects actions that are carried out with the aim of optimizing the environmental consequences to meet the needs of current and future generations. Green consumers and their buying behavior are well examined fields of research (for a discussion see Peattie (2001)). Buying organic products is the most popular action to reduce an individual's environmental impact (Isenhour, 2010).
Markets for green products such as organic produce are steadily growing (Bund ökologischer Landwirtschaft (BÖLW), 2016, U.S. Department of Agriculture Economic Research Service, 2014). This development not only produces benefits for the environment, but also creates opportunities for businesses which engage in this growing niche market. Research found that companies and retailers which implement green strategies achieve higher profitability and market shares (Menguc and Ozanne, 2005), greater levels of employee commitment (Maignan and Ferrell, 2001), increased customer satisfaction (Lombart and Louis, 2014, Luo and Bhattacharya, 2006) and a more positive image (Lavorata, 2014). However, findings about the relationship between consumers’ attitudes and environmentally friendly behavior are still inconsistent. It is also unclear which factors determine real buying behavior. Most studies that analyze green purchasing behavior either focus on behavioral intention as a proxy for behavior (Auger et al., 2008, Lu et al., 2015, Schuitema and Groot, 2015) or rely on self-reported survey data (Follows and Jobber, 2000). Although some studies analyze real purchasing behavior, they only focus on attitude and its predecessors as a predictor of behavior (Hauser et al., 2013, Tarkiainen and Sundqvist, 2009).
The present study focuses on consumers' purchasing decisions with reference to environmentally-friendly products. In contrast to prior research in this field, the study takes into account more predictors than just attitude. The conceptualized model also integrates personal norms and willingness to pay (WTP) as further promising factors which might explain behavior. Hence, the relative importance and the respective structure of each single factor can be revealed. The model also contrasts measures of stated attitudes and behavior with measures of actual behavior. Thus, the model tests if these factors are able to predict actual green purchasing behavior. In sum, the study contributes to the understanding of green purchasing behavior. Main drivers of green purchasing behavior can be identified while simultaneously modeling the potential gaps between (a) attitude and behavior and (b) self-reported and actual behavior. The results of the study provide a better understanding of self-reported and actual purchasing behavior in seven different product categories. Thus, the present study responds to the call for more research at the product category level (Padel and Foster, 2005) and even expands research to further product categories beyond organic food.
Section snippets
Conceptualization and hypotheses development
The theory of planned behavior (TPB) (Ajzen, 1991) is widely applied and acknowledged to explain environmentally friendly behavior (Bamberg and Möser, 2007, Leonidou and Leonidou, 2011, Paul et al., 2016). It has also been supported with regard to organic products (Honkanen et al., 2006, Kim and Chung, 2011, Pino et al., 2012, Zhou et al., 2013). According to the TPB, behavior is guided by three major factors: attitude, subjective norm and perception of behavioral control (PBC). Individuals are
Operationalizing green products
Generally, green products are defined as products that are less or not at all harmful for the environment in comparison to a substitute of the same product category. This is linked to one or several product-inherent attributes whose environmental impact is low or even non-existent (Haws et al., 2014). For consumers, it is challenging to assess the environmental impact of products correctly (Tobler et al., 2011). Therefore, the definition of green attributes for the respective product categories
Descriptives
In general, the respondents showed a strong and positive attitude towards the environment (mean =3.599; standard deviation (SD)=0.957). They also tended to follow norms when buying daily consumer goods (mean =3.214; SD =1.005), while expressing a marginally positive yet almost neutral WTP for products with green attributes (mean =3.093; SD =0.963). The overall self-reported behavior was not very distinctive either, but slightly positive (mean =3.177; SD =0.912).
Means of the dependent variables
Discussion and implications
The factors integrated into the study were able to explain approximately two-thirds of the variance of SRB which reflects consumers' behavioral tendencies regarding environmentally-friendly behavior. However, SRB was not significantly related to actual green purchasing behavior in any product category. Since WTP for products with green attributes was considered as a direct predictor of behavior, the gap can hardly be explained by higher costs of green products. Whereas WTP had a significant
Limitations
The results showed that the integrated factors are able to predict SRB. However, SRB and actual purchasing behavior diverge. Naturally, the measure of SRB was based on self-assessment, which requires a careful interpretation of the results. Individuals tend to overestimate their self-reported behavior (Armitage and Conner, 2001), as well as their WTP (Kovalsky and Lusk, 2013). The gap between SRB and behavior might result from consumers’ motives besides environmental aspects as well as from
Acknowledgments
The author gratefully acknowledges that this project was funded by the German Federal Ministry of Education and Research within the program “FHprofUnt” (Grant number 17026X11). She would also like to thank the project partner GfK for the fruitful cooperation and the provision of data. An earlier version of this paper was presented at the AMA 2015 Winter Educators’ Conference in San Antonio, TX, in February 2015. The extended abstract was published in the proceedings under the title “The
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