The importance of consumer motives for green mobility: A multi-modal perspective

Abstract

While most consumers agree that adopting more sustainable mobility behaviors should be a priority, this attitude often fails to translate into actual behavior. We argue that this is because sustainable mobility products do not sufficiently satisfy consumer mobility motives. To investigate this issue from a multi-modal perspective, we first synthesized previous research into a general measure of superordinate consumer motives in the mobility domain. We then conducted a representative survey experiment in which potential mobility consumers (N = 504) reported their mobility motives and their purchase intentions for a diverse set of mobility products including electric vehicles, hybrid-electric vehicles, efficient fuel cars, electric bikes, annual public transport tickets and sport utility vehicles. In line with our expectations, mobility motives substantially contributed to explaining all purchase intentions on top of demographic variables and prior ownership. While environmental motives were the most important predictor, also status, financial, independence, safety and hedonic motives contributed substantially to the prediction of mobility purchase intentions. We discuss the importance of consumer motives as a basis for marketing and policy measures, to effectively promote sustainable mobility alternatives during the rise of multi-modal mobility.

Introduction

The rapidly aggravating effects of climate change call for a massively accelerated reduction of greenhouse gas emissions in all sectors of human life (IPCC, 2018). Changes in individual consumer behavior can play a major role in achieving this objective. However, changing consumer behavior can be difficult, especially in conservative, slow-changing sectors such as the transportation domain. Global transportation continues to heavily rely on the combustion of fossil fuels which results in unacceptably high levels of CO₂, referred to as the carbon lock-in (Seto et al., 2016). To a large extent, the carbon lock-in is due to very low adoption rates of more energy efficient transport technologies, as indicated by the < 1% share of Battery Electric Vehicles on the global automobile market (IEA, 2018b). As a consequence, the private transport sector alone currently contributes to 25% of global CO₂ emissions, with an ascending trend (IEA, 2018a).

It is thus crucial to develop innovative ways to break the carbon lock-in by increasing the uptake of more sustainable ways of transportation. Recent research has begun to address the potential of reducing CO₂ emissions by changing consumer behavior (Anable et al., 2012, van de Ven et al., 2018), especially focusing on one-shot consumer behavior such as purchase decisions. Purchase decisions can be particularly impactful, as in this case a single behavioral choice has a strong impact on long-term environmental consequences (Hensher, 1985, Nolan, 2010). Consistent with this, an increasing amount of consumer research is investigating purchase intentions as a measure for preference for eco-innovations like battery- or hybrid-electric vehicles (Biresselioglu et al., 2018, Fry et al., 2018, Haustein and Jensen, 2018, Li et al., 2017, Schmalfuß et al., 2017).

Existing research has identified that both objective characteristics and psychological factors influence preferences for sustainable mobility technology such as hybrid- and full-electric vehicles (Cherchi, 2017, Soto et al., 2018). While objective characteristics like purchase price, technological advances, or structural changes were found to be important predictors of alternative fuel vehicle preference (Valeri and Danielis, 2015, Wolbertus et al., 2018), psychological factors such as social norms, social signaling or range anxiety have been shown to predict preferences as well (Cherchi, 2017, Heffner et al., 2007, Rezvani et al., 2018). Here we will contribute to a better understanding of the impact of psychological factors by investigating how consumer mobility motives influence consumer’s purchase intentions of a variety of sustainable mobility products.

A large body of literature illustrates the importance of psychological variables as determinants of purchase behavior (Alwitt and Pitts, 1996, Follows and Jobber, 2000, Lange and Dewitte, 2019, McDonagh and Prothero, 2014, Wang, 2017). For example, individual differences concerning altruistic or biospheric values and beliefs were important and reliable predictors of consumer behavior in various markets (Jansson et al., 2011, Mainieri et al., 1997, Pepper et al., 2009, Schultz et al., 1995, Schwartz, 1992). In the transportation literature, broad motivational constructs such as environmental concern and general environmental attitudes significantly predicted preferences for sustainable mobility options, such as electric vehicles and other low emission vehicles (Carley et al., 2013, Daziano and Bolduc, 2013, Dunlap, 2008, Egbue and Long, 2012, Lane and Potter, 2007, Skippon and Garwood, 2011). However, research also recognized an attitude-behavior gap between broad, domain-unspecific attitudinal measures such as environmental concern and environmental behavior (Stern, 2000). It has been suggested that more domain-specific attitudinal measures are better predictors of specific behavior, reducing the prediction gap between attitudes and behavior (Alwitt and Pitts, 1996, Choi and Johnson, 2019, Corraliza and Berenguer, 2000, Karp, 1996, Oliver and Rosen, 2010, Thøgersen and Ölander, 2006). For instance, environmental concern was found to more strongly link to public transport use than to car use (Daziano & Bolduc, 2013). Similarly, a general environmental attitude measure was strongly linked to household actions, but was only weakly linked to behavior in the transportation domain (Bratt et al., 2015, Lavelle et al., 2015). Along the same lines, a measure of environmental value orientation was linked to product reuse and waste-minimization intentions, but not to recycling intentions (Barr, 2007). One possible explanation for these discrepancies is that individuals simultaneously pursue multiple goals that differ in their importance across situations and domains. Thus, the extent to which environmental concern will manifest in actual behavior depends on how important other conflicting goals are in the situation at hand (Rezvani et al., 2015; Stern, 2000).

In order to allow for more reliable and specific predictions of behavior, models of sustainable consumer behavior have started to focus on more domain-specific variables and motives (Honkanen et al., 2006, Noppers et al., 2014, Schuitema et al., 2013, Steg, 2005). Comprehensive theoretical models have proposed that the effect of general constructs like values, beliefs and attitudes on behavior is mediated by consumer motives and goals that are more proximal to the target behavior (Alwitt and Pitts, 1996, Choi and Johnson, 2019, Homer and Kahle, 1988, Paulssen et al., 2014). Domain-specific consumer motives are thus of considerable importance when trying to reliably predict a specific behavior. In the present study, we tested the assumption that consumers have a set of specific mobility motives which determine their purchase intentions for a range of different mobility products. We will describe these motives in more detail in the following section.

A range of different motives have been found to impact consumer behavior in the mobility domain (Steg, 2005, Steg et al., 2001, Whitmarsh et al., 2009). Initial work focused on instrumental motives such as financial motives (Hensher, 1985, Rouwendal, 1997) and safety motives (Steg, 2003, Steg, 2005), consistent with classic economic thinking which postulates that consumers are mainly motivated to reduce the cost of their mobility and to maximize their personal safety.

It has moreover been shown that consumers derive utility from aspects of their mobility behavior that cannot be accounted for by purely rational economic reasoning (Carrus et al., 2008). For instance, the possession and purchase of sustainable mobility products can have symbolic meaning for consumers (Heffner et al., 2007, Rezvani et al., 2018, Schuitema et al., 2013, Steg, 2005). Thus, a car can be a symbol of personal convictions that can serve to underline one’s self-identity (Sirgy, 1986, Skippon and Garwood, 2011). As a result, the extent to which a given mobility product is perceived as reflecting one’s own self-identity can have strong influences on purchase intentions, independent of classic economic or instrumental factors (Steg, 2005). Thereby, purchase decisions can satisfy inherent status motives. The satisfaction of status motives has been shown to manifest in consumers paying premium prices for luxury products (Kim, Park, & Dubois, 2018), as well as in costly signaling through the purchase of sustainable products that serve an altruistic purpose (Griskevicius et al., 2010; Miller, 2009, Noppers et al., 2014). Mobility can moreover serve to fulfill motivations of enjoyment and pleasure, pointing to hedonic motives as another more affective driver of consumer mobility (Choi & Johnson, 2019). This motive can lead consumers to commit to traveling as a leisure activity (Anable and Gatersleben, 2005, Mokhtarian and Salomon, 2001, Mokhtarian et al., 2001). Mobility consumers moreover value how much their travel mode allows them to avoid restrictions due to external factors (Haustein & Jensen, 2018), pointing to independence as another important mobility motive. For instance, traveling by car allows for a more flexible departure time than traveling by public transport (Steg, 2003). Traveling with an electric car may lead to constraints due to underdeveloped charging infrastructure, potentially inducing range anxiety (Fry et al., 2018). Finally, environmental motives have been shown to play a significant role in consumer mobility behavior, as over the past decades more and more consumers have started to integrate environmental considerations into their product choices (Anable, 2005, Noppers et al., 2015, Noppers et al., 2014, Steg, 2016). Environmental motives were in particular identified as important drivers of the adoption of energy-efficient innovations in the mobility sector, such as for instance Battery Electric Vehicles (Biresselioglu et al., 2018, Li et al., 2017, Rezvani et al., 2018).

Overall, there is strong evidence for the importance of individual consumer motives as determinants of consumer mobility behavior. In the present study, we synthesized and integrated these findings into a measurement of superordinate consumer mobility motives which are relevant across the entire mobility domain. These superordinate motives were then used to predict purchase intentions for a diverse set of mobility products.

Hypothesis 1

Consumers have superordinate mobility motives relevant to a variety of mobility products. These motives can be reliably measured and their structure confirmed by means of confirmatory factor analysis.

Demographic characteristics have been of great value for consumer segmentation (e.g., Salomon & Ben-Akiva, 1983) and in predicting consumer preferences for mobility products (e.g., electric vehicles; Cherchi, 2017). In the case of sustainable mobility, age, level of education, gender and income have been found to account for a considerable amount of variance in behavior (e.g., Li et al., 2017, Steg et al., 2001). Moreover, demographic characteristics have been useful in describing early adopters of alternative fuel vehicles. Early adopters of sustainable mobility have been identified as primarily middle-aged men from rural or suburban cities with higher levels of socio-economic status (Ensslen et al., 2016, Haustein and Jensen, 2018, Plötz et al., 2014). However, attitudinal variables have been discussed to significantly add to the predictive value of demographics when comprehensively investigating consumer purchase intentions (Diamantopoulos et al., 2003, Haustein and Hunecke, 2013, Haustein and Møller, 2016, Hunecke et al., 2010). Taken together, given the importance of demographic characteristics in predicting consumer preferences for sustainable mobility products (Cherchi, 2017, Oliveira and Dias, 2019, Spurlock et al., 2019) these factors serve as a useful baseline when investigating the impact of mobility motives on mobility purchase intentions (Peattie, 2010).

Another previously identified determinant of mobility purchase behavior is prior ownership, reflecting habits and inertia in modal choice (Belgiawan et al., 2014, Cherchi and Manca, 2011, Chng et al., 2018, Klöckner and Blöbaum, 2010). This is well grounded in behavioral theories that include past behavior as an integrative part of their predictions (Bentler and Speckart, 1979, Chng et al., 2018, Smith et al., 2008), and in the context of consumer behavior manifests as an inertia to switch from a habitual brand or technology to another (Biel et al., 2005, Cherchi and Manca, 2011, Valeri and Cherchi, 2016, Wood and Neal, 2009). Including habitual behavior as predictor of car purchase significantly improved predictions, in addition to financial, technical, and attitudinal characteristics of different mobility technologies (Valeri & Cherchi, 2016). When considering the uptake of innovative mobility products for which prior purchase behavior does not yet exist on a large scale, habitual purchase behavior is of crucial importance because it favors the purchase of more established mobility technologies (Tao et al., 2019). Ownership allows consumers to reduce uncertainty due to first-hand experiences and to get accustomed to a mobility product, creating new habits and overcoming existing doubts. In fact, facilitating direct experience has been among the most frequent and effective strategies of industry and policy to promote the adoption and use of new mobility technologies, such as electric vehicles or electric bikes (Haustein and Møller, 2016, Labeye et al., 2016, Schmalfuß et al., 2017).

In the present study, we aimed to examine the predictive value of mobility motives over and above other relevant consumer variables such as demographic and prior possession variables. Furthermore, we aimed to use the predictive value of these traditional variables as a benchmark to compare and evaluate the impact of mobility motives on purchase intentions.

Hypothesis 2

Consumer mobility motives significantly predict mobility purchase intentions on top of demographic and prior ownership variables.

Although extensive research has been conducted on the psychological drivers of car use (Chng et al., 2018, Jansson et al., 2011, Schuitema et al., 2013, Steg et al., 2001), it is important to point out that purchase decisions in the mobility domain are not limited to car purchases. In urban areas, the purchase of an annual public transport ticket can considerably determine consumer mobility behavior and related CO₂ emissions (Miller et al., 2016). Similarly, an increasing number of consumers decide to purchase electric bikes or motor cycles to cover distances that would have otherwise required the use of a car (Plazier et al., 2018, Wu et al., 2015). Thus, a considerable share of the consumer population considers alternative mobility options which should not be neglected in relevant research. Additionally, the combination of multiple modes of transportation has become an important part of consumer mobility (Meyer & Shaheen, 2017). These developments require an integrative approach to better understand consumers mobility purchase intentions.

In contrast to past research that has mostly focused on a single mobility product at a time, the present research simultaneously investigates purchase intentions for a variety of mobility products, including an electric vehicle, a hybrid-electric vehicle, an efficient fuel car, an electric bike, an annual public transport ticket and a sport utility vehicle (SUV). This approach allows us to evaluate how the influence of mobility motives varies between different purchase intentions for mobility options and how the predictive power of motives varies in comparison to demographic variables and prior ownership for the different mobility options.

Hypothesis 3 (exploratory)

The explanatory contributions of mobility motives, as well as demographic and prior ownership variables, differ across purchase intentions for different mobility products.