Being innovative, fun, and green? Hedonic and environmental motivations in the use of green innovations

ABSTRACT

This paper seeks to determine the decision-making route relating to hedonic and environmental motivation in green innovation adoption and to show how two similar green innovations can motivate consumers differently. It also aims to determine the effect of domain-specific innovativeness (DSI) on emotions and green identity on environmental motivations. The paper focuses on two types of green transport innovations: shared e-bikes and e-scooters. Four models were tested using structural equation modelling based on survey data from 800 shared e-bike and e-scooter users. The results reveal that the decision to use shared e-bikes follows a cognitive route, while shared e-scooter use follows an affective route. Additionally, findings show that DSI significantly affects positive emotions in the use of both shared microvehicles. However, green identity only impacts the environmental motivations in shared e-bike use.

KEYWORDS:

• Cognition
• emotions
• hedonic motivation
• environmental
• consumer innovativeness
• green innovation

Introduction

The recent Intergovernmental Panel on Climate Change (IPCC) report (2021) ominously warns us that it is ‘Code red for humanity.’ This means that humans would experience extreme weather and climate conditions if no actions to cut carbon emissions and dependence on non-renewable energy sources are taken. Indeed, this warning involves a sense of urgency and concern, as human consumption has caused dramatic changes to the Earth’s climate. With this increasing awareness of the environmental problems caused by human consumption, many consumers are looking for ways to achieve a more sustainable lifestyle through the products they use (Leonidou et al., 2010; Paul et al., 2016). Consequently, the role of green innovations to promote sustainability has become important.

In particular, the passenger transport sector, which is responsible for about 45% of greenhouse gas emissions from transport globally (Ritchie, 2020), has seen a boost in green innovations. Examples of green transport innovations that could mitigate passenger emissions coming from cars are electric vehicles and shared micromobility. While a study shows that the uptake of electric vehicles can help the UK meet its CO₂ emission targets (Hill et al., 2019), a report about shared micromobility outlines how this transport innovation has the potential to cover over 50% of passenger trips, including those made with cars, in China, the EU and the US (Heineke et al., 2019).

Overall, green transport innovations aim to help mitigate the adverse impact of the transport industry on the environment. Nevertheless, the consumer decision to adopt these innovations does not necessarily have to be environmentally motivated. The decisions may vary depending on, for example, the purpose of the trip (Jia & Fu, 2019), consumers perception of the values and risks linked to the adoption (Wang et al., 2020), and the way these innovations promote or are aligned with self-identities (Potoglou et al., 2020). In this paper, we add to the understanding of the consumer decision to adopt green innovations by comparing the decision-making process related to hedonic and environmental motivations involved in the adoption of shared micromobility and show how two similar green innovations can motivate consumers differently. This paper also aims to determine the effect of a personal trait, domain-specific innovativeness, and consumer green identity, on the hedonic motivation and the environmental motivation, respectively.

Shared micromobility is a transport mode that uses electric or human-powered smaller scale, lightweight vehicles, such as bikes, e-bikes, and e-scooters, on an instant need basis (Reck et al., 2021; Zarif et al., 2019). Globally, shared micromobility, such as shared e-scooters and e-bikes, can be seen in major urban areas, and forecasts have estimated that it ‘could make up to $800 billion in revenues by mid-2020s and total 1 trillion personal miles, or 4% of global transport’ (Vaish, 2019). In 2010, an estimated 101 bike-sharing programmes were operating in 125 cities worldwide, with more than 139,000 shared bicycles in their fleet (Shaheen et al., 2010). As for shared e-scooters, their adoption has been four times faster than that of shared bikes, with the mode reaching 626 cities in 53 countries since their launch in 2018 (Møller et al., 2020). For instance, Voi, an e-scooter sharing company present in ten countries, has already registered over 16 million trips (Møller et al., 2020), while Lime has hit 34 million rides with its fleet, which includes e-bikes and e-scooters (Zarif et al., 2019).

However, shared micromobility has faced a lot of critiques since they were introduced in cities, especially shared e-scooters. One of the much-debated issues is whether shared micromobility trips are replacing car trips instead of trips made by public transport, private bikes, and by foot. Other issues of shared micromobility are the lack of infrastructure to support shared microvehicle use and the visual pollution and risks of accidents it causes (Møller et al., 2020). Many are also concerned about the safety of using it (Allem & Majmundar, 2019; Fearnley, 2020). Despite these critiques, why do people still use shared micromobility? Which of its attributes account for its adoption?

To contribute to answering these questions, this paper examines two types of shared micromobility: shared e-scooters and shared e-bikes. While both shared e-bikes and e-scooters are part of the shared micromobility phenomenon, there are conflicting opinions regarding their greenness and the emotions related to them (Abduljabbar et al., 2021; Gössling, 2020; Hollingsworth et al., 2019). Indeed, as shared micromobility is an innovation promoted as both fun and environmentally sound (Møller et al., 2020; Zarif et al., 2019), this paper takes these two attributes as starting points. If indeed shared micromobility is perceived as a green innovation, the motivation for its use should be partly related to its environmental benefits. Second, with shared e-scooters especially, studies have shown how they are used for hedonic experiences related to leisure and fun (e.g. Kopplin et al., 2021; Reck et al., 2021). Therefore, this paper aims to determine how decision-making relating to the hedonic and environmental motivations in the adoption of shared micromobility happen.

In particular, this paper investigates whether hedonic motivation is an information processing heuristic, which means that the decision to adopt shared micromobility relies first on positive affective cues or emotions before assessing its environmental impact cognitively, or whether hedonic motivation follows environmental motivation, which implies that consumers evaluate the environmental impact of shared micromobility before its hedonic benefits. Indeed, according to Shiv and Fedorikhin (1999), consumers tend to follow either an affective or a cognitive route in choice-making. The affective route heavily relies on emotions during the decision-making process and uses one’s emotions as a basis for judgement. By contrast, the cognitive route takes greater consideration of logic and reasoning (Schwarz, 2000; White et al., 2019).

Personal traits and consumer identity also play major roles in the decision to adopt green innovations. In this paper, we specifically look at consumer innovativeness and green identity. Whereas previous innovation studies show that consumer innovativeness can be linked to consumers’ decisions to adopt innovations (Flores & Jansson, 2021; Heidenreich et al., 2017; Paparoidamis et al., 2019), environmental psychology literature points to green identity as an important driver for green product adoption (de Groot & Steg, 2010; van der Werff et al., 2013; Whitmarsh & O’Neill, 2010).

In studies concerning consumer innovativeness, it is widely argued that the more innovative an individual is, the higher the likelihood that the person will adopt innovations during the early market stages (Midgley & Dowling, 1978; Roehrich, 2004). This adoption effect is magnified in domain-specific innovativeness (DSI), in which individuals adopt innovations faster in their areas of interest (Paparoidamis & Tran, 2019; Thøgersen et al., 2010). On the other hand, for green identity, individuals who see themselves as green have a higher intention to adopt and purchase products that they believe have a less adverse impact on the environment (Barbarossa & De Pelsmacker, 2016; Whitmarsh & O’Neill, 2010). Overall, considering innovativeness and identity together provides more detailed implications on how to promote this transport innovation, as it has been argued that considering them together is important in attitude formation and hedonic value appraisal of technology products (Lee et al., 2011).

Importantly, this paper makes several contributions to theory and practice. First, it adds to the understanding of the relationship between hedonic and environmental motivation in the actual adoption of green innovations. Even though many studies have looked at hedonic motivation in pro-environmental decision-making, studies have mostly looked at attitudes and intentions and less on actual behaviour (Schneider et al., 2021). Domain-specifically, although previous research has demonstrated that different types of green innovations elicit different psychological and behavioural reactions (Paparoidamis & Tran, 2019), they have so far not focused on distinguishing the effects of cognitive environmental motivation and hedonic motivation in green transport innovations. Research regarding the adoption of transport innovations has shown that emotions and cognitive deliberation are important for people to adopt new mobility modes (Moons & De Pelsmacker, 2012; Rezvani et al., 2017; Schuitema et al., 2013).

Second, this paper contributes to identifying the effect of personal traits and consumer identity in the evaluation of the attributes of innovations. Specifically, on the one hand, by recognising how a consumer’s green identity impacts the way they perceive the environmental attributes of green innovations, this paper sheds light on the extent to which green innovations can be considered pro-environmental by consumers who identify themselves as green. Indeed, the relationship between green identity and pro-environmental behaviour still needs to be established across various contexts (Confente et al., 2020; Dermody et al., 2015; Whitmarsh & O’Neill, 2010). On the other hand, by identifying the effect of consumer innovativeness on emotions, this paper adds knowledge of how personal traits are related to affect, especially in innovative products that can fulfil both hedonic motivations and perceived utilitarian motivations, in the sense that a particular innovation adoption can benefit the environment.

Overall, this paper argues that marketing strategies have to consider how personal traits, such as consumer innovativeness, and consumer identity, such as green identity, can affect emotions and environmental motivations in the use of new pro-environmental products. Specifically, marketers need to align their promotion of the innovative, hedonic, or green attributes of green innovations and the motivations of innovators and green consumers. Researchers have argued that understanding how emotions and perceptions affect consumers’ decisions to adopt innovations is helpful in order to develop effective campaigns to increase acceptance and encourage broader adoption (Aroean & Michaelidou, 2014; Enrique Bigné et al., 2008; Lee et al., 2011).

Theoretical background

Scholars have debated the roles of cognition and affect in the decision-making process over the years. Some assess these factors separately and argue that they oppose each other or are distinct (Dolan, 2002; Kim et al., 2013; Voss et al., 2003). However, others contend that they are interrelated and can significantly affect the implications that each one has in decision-making (Chiew & Braver, 2011; Frank et al., 2014; Homburg et al., 2006; van der Linden, 2014). Although previous research has shown this interrelation, it remains unclear how they affect each other. Several researchers have reasoned that affect is a driver of cognition (Chaudhuri et al., 2010; Chiew & Braver, 2011; Dolan, 2002; Kwortnik & Ross, 2007), while others have demonstrated that cognition comes first before affect (Choi et al., 2011; Koenig-Lewis et al., 2014; Watson & Spence, 2007). Given the relevant number of studies showing how cognition and affect could influence decision-making, several researchers (e.g. Altarawneh et al., 2018; Marx et al., 2007; van der Linden, 2014) have proposed the dual processing perspective to take into account how decisions can be a continuous interaction between emotions and cognition.

Cognition and environmental motivation

The cognitive route deliberately evaluates product attributes and trade-offs. This route considers various costs and benefits of using a product, and the decision is formed based on whether the benefits of product use outweigh the costs. Therefore, products are evaluated based on their instrumental performance, and their use requires thinking (Arruda Filho et al., 2020). In an organisational study regarding the introduction of innovations to an enterprise, the results showed that cognitive assessment precedes emotions (Choi et al., 2011). Employees tended to evaluate the benefits of the innovation first for their work and its technicalities before appraising the innovation’s emotional values. On a consumer level, Demerath (1993) has proposed that individuals experience increased pleasure when they can explain why an object is good or bad and when they can predict things will happen. Wood and Moreau (2006) have further argued that the emotions in using new products can be caused by learning efforts and recognising the benefits and risks of product use.

In relation to green behaviour, a study about cognitions related to car use and its alternatives has demonstrated that the attitude towards non-car use is influenced by cognitions connected to the environment (Gardner & Abraham, 2010). Another study about environmental appeals has also shown that environmental reasoning was involved in products that were perceived to have had a significant environmental impact compared to products that did not (Kong & Zhang, 2014). This environmental reasoning can serve as an accessible heuristic or cue for consumers in the decision to act sustainably (Dermody et al., 2015; Jaiswal & Kant, 2018). Haws et al. (2014) have illustrated that individuals with high green consumption values, or those who consume green products to express their environmental values, also engage in motivated reasoning. They have pointed out that consumers tend to evaluate non-environmental attributes of green products more favourably and that their consumption is not only for environmental protection but also to preserve personal resources.

Although linked to environmental-related information processing, these findings reveal that environmental motivation can also be based on other forms of cognitive deliberation, such as financial or social gains, apart from considerations for environmental welfare. In line with this, according to Noppers et al. (2015) – given that environmental attributes of electric cars are important – these attributes are still less likely to predict the adoption of electric cars than instrumental and symbolic attributes. This means that the positive assessment of costs and benefits of ownership and perceptions of others towards use are more important than the environmental impact of electric cars in the adoption decision. Nevertheless, the recent experiments concerning the perceived performance of sustainable products conducted by Chernev and Blair (2021) have provided support that environmental attributes can positively influence the product performance beliefs of consumers.

In general, many consumers have favourable attitudes towards the environment and prefer products that have a less negative impact on the environment. Several studies have demonstrated that consumers are more likely to choose green products because they believe they can help the environment through green consumption (Bang et al., 2000; Chernev & Blair, 2021; Kong & Zhang, 2014). Nevertheless, the environmental motivation in cognitive decision-making could be objective and subjective as consumers attribute different importance to distinct product characteristics (Hwang & Griffiths, 2017). This motivation may also be based on expected or anticipated product characteristics rather than actual product characteristics (Hahnel et al., 2014).

Affect and hedonic motivation

The affective route relies on the emotions that individuals feel or anticipate feeling when using a product. Consumers evaluate the hedonic attributes related to the product and assess the product based on these attributes. When a person is motivated to behave hedonically, the objective is to enhance how one feels and realise these improved feelings within a short period (Lindenberg & Steg, 2007).

According to Loewenstein and Lerner (2003), immediate emotions or those that individuals feel during decision-making can have both a direct and indirect effect on the decision. Emotions can also directly influence both reason and beliefs (Dolan, 2002), as well as satisfaction loyalty (Enrique Bigné et al., 2008). When searching for brand information, consumers’ feelings towards products can play a significant part in evaluating the brand (Pickett‐Baker & Ozaki, 2008). Therefore, emotions can lead to bias against the cognitive beliefs that people hold regarding particular objects (Dolan, 2002). Concerning products perceived as high risks, such as innovations, hedonic attributes exert a greater influence on purchase intention (Arruda Filho et al., 2020). Specifically, in radical innovations or new products that meet consumer needs significantly better than existing products, Chaudhuri et al. (2010) have suggested that emotions can determine consumers’ response to radical innovations and directly affect how they evaluate these products in terms of risk perception and willingness to try. Emotions also become more salient in experiential decisions, such as those involved in travelling, than information-processing (Kwortnik & Ross, 2007). In the decision to use cars, affect also is a better predictor than functional benefits (Steg, 2005).

In terms of engaging in ethical consumption, according to Gregory-Smith et al. (2013), affect is linked to the decision to act with concern for the environment. Pooley and O’Connor (2000) have shown that affect is more significant than information provision in the case of green attitude formation. In relation to green transport innovations, it has been demonstrated that intention to use electric cars is significantly affected by emotions and attitudes (Moons & De Pelsmacker, 2012; Rezvani et al., 2017).

To encourage the adoption of new behaviour, such as green innovations, Fitzmaurice (2005) has proposed exemplifying the positive emotions that individuals could feel. Indeed, Venkatesh et al. (2002) have found that the intrinsic motivation to feel positive emotions increases the perceived usefulness and ease of use of new technologies. This hedonic motivation also leads individuals to spend more time using the products, making them more knowledgeable about their benefits.

Green identity and environmental motivation

Apart from affect and cognition, studies have demonstrated that personal traits and consumer identity also affect decision-making. In the case of green innovations, it is interesting to examine green identity and consumer innovativeness, as both characteristics can be linked to the increased likelihood of green innovation adoption (Flores & Jansson, 2021; Heidenreich et al., 2017; Paparoidamis et al., 2019).

Products can be used to achieve identity goals (Grewal et al., 2000). Scholars have long argued that consumers use products consistent with their self-concept (Belk, 1988; Escalas, 2013). The self-concept can be looked at from various perspectives – actual, ideal, and social. While actual and ideal perspectives concern how a person sees and wants to see themselves, respectively, social self relates to the way a person presents the self to others (Sirgy, 1982).

In line with the actual and ideal self-concepts, there is growing interest in studies dealing with the consumption of products to confirm, maintain, and promote self-identity (Berger & Heath, 2007; Dhar & Wertenbroch, 2012). Products help define self-identity and, at times, help acquire missing personal characteristics (Grewal et al., 2000). Moreover, products can be used to acquire tangible materialistic gains through the symbolic benefits they render (Bliege Bird & Smith, 2005). For instance, a person might choose to buy a less tasty but healthier food option to validate the self-identity of living a healthy lifestyle (Dhar & Wertenbroch, 2012). Another example is when consumers utilise aesthetic products to solidify their value for beauty (Townsend & Sood, 2012). Indeed, consumers may be driven away from purchasing or consuming certain products because these do not conform with how they perceive themselves (Whitmarsh & O’Neill, 2010).

In studies regarding sustainable behaviour, green or pro-environmental identity has become one of the most important predictors of intention or actual adoption of sustainable products (Dermody et al., 2015; van der Werff et al., 2013; Whitmarsh & O’Neill, 2010). The alignment of pro-environmental behaviour and self-interest increases the level of pro-environmental actions (Pickett‐Baker & Ozaki, 2008). In the switching intention to use bioplastic products, consumers who identify as pro-environmental have a higher intention to switch than those who do not (Confente et al., 2020; Scarpi et al., 2021). In the case of autonomous alternatively fuelled vehicles, pro-environmental identity positively influences the green perceptions of the vehicles (Potoglou et al., 2020).

According to a study in the United States that examined the environmental and social innovativeness value of electric cars, these cars significantly reflect the environmentalist identities of users (White & Sintov, 2017). This means that consumers who identify themselves as pro-environmental have a higher adoption intention and actual adoption of these cars (Barbarossa & De Pelsmacker, 2016). Therefore, some consumers adopt electric cars because they communicate their pro-environmental values (Griskevicius et al., 2010).

Based on these findings supporting the notion that consumers’ environmental product perception can depend on how they see themselves, we argue that because shared micromobility is presented as green transport, people who identify themselves as green should have a higher likelihood of perceiving these microvehicles as green, thereby increasing the likelihood of shared micromobility adoption among green consumers. Hence, we hypothesise that:

H1a:

Green identity is positively related to environmental motivations in shared e-bike use.

H1b:

Green identity is positively related to environmental motivations in shared e-scooter use.

Domain-specific innovativeness and hedonic motivation

Domain-specific innovativeness (DSI) states that consumers are innovative in domains of interest as opposed to being generally innately innovative. This means that consumers have a tendency to adopt innovations if they fall within specific domains of interest (Roehrich, 2004). Goldsmith et al. (1995) have found that the DSI is more correlated to purchasing new clothes and electronics than innate innovativeness. DSI also directly influences the willingness to pay when studied in the context of smart toys (Zhang et al., 2020). In domain-specific innovation studies, while the focus has been on the attributes of innovations, such as originality, eco-friendliness, functionality, and hedonic benefits (Li et al., 2015), other studies in this area have concentrated on the willingness to pay for innovations (Frank et al., 2015; Zhang et al., 2020). Some have also assessed DSI as a moderating variable and concluded that DSI affects intention and adoption more strongly when it is a moderator (Leicht et al., 2018; Li et al., 2015).

In the context of autonomous cars, DSI moderates the effect of different antecedents of adoption and purchase intentions (Leicht et al., 2018). Paparoidamis et al. (2019) have studied eco-innovative designs in high-tech product categories and found that radical eco-innovative attributes elicit stronger adoption intention than incremental eco-innovative attributes. Designs that allow for substitution of resources increase adoption intention compared to those that achieve resource efficiency and elimination (Paparoidamis et al., 2019).

Innovativeness can be linked to consumer hedonic motivation. Indeed, some innovators are hedonically motivated. Instead of attaching high significance to the instrumental benefits of the innovation, they place more importance on the emotional benefits they experience in product use (Li et al., 2021). As innovators are consumers who have a high need for emotions from products they consume (Aroean & Michaelidou, 2014), their innovativeness could help to explain their higher likelihood of feeling more positive emotions during the use of innovations. Several researchers have also found that hedonic attributes of innovations can be significantly linked to innovative behaviour (Hahnel et al., 2014; Heidenreich et al., 2017). With these findings, for shared e-bikes and e-scooters, we hypothesise that:

H2a:

Domain-specific innovativeness is positively related to positive emotions in shared e-bike use.

H2b:

Domain-specific innovativeness is positively related to positive emotions in shared e-scooter use.

Model 1: Cognitive–environmental motivation route

After presenting the theoretical underpinnings of the variables included in this paper, we proceed by examining the decision-making process involved in the use of shared e-bikes and e-scooters.

In the cognitive route, we hypothesise that consumers first consider the environmental impact of shared e-bikes and e-scooters before considering the positive emotions of using these shared micromobility modes. In particular, in Model 1 – as presented in the previous sections – we hypothesise that environmental motivations and consumer innovativeness influence the effect of positive emotions on the use of shared e-bikes and e-scooters.

Aside from the impact of consumer innovativeness on positive emotions, green identity positively affects the positive emotions from the use of shared e-bikes and e-scooters, albeit indirectly through environmental motivation, as illustrated in Figure 1. This proposition is in line with previous studies showing that people who consume sustainable products feel a positive affect due to the awareness of the environmental benefits of the products and the products’ alignment with personal values (van der Linden, 2018; Venhoeven et al., 2020). We, therefore, propose that

Figure 1. Cognitive route.

H3a:

Environmental motivations are positively related to positive emotions in shared e-bike use.

H3b:

Environmental motivations are positively related to positive emotions in shared e-scooter use.

Model 2: Affective–hedonic motivation route

In the affective route, as depicted in Figure 2, we hypothesise that consumers consider their emotions first before considering the environmental impact of shared e-bikes and e-scooters. According to Bagozzi (1997, p. 312), ‘Emotions serve to motivate action, qualify information processing and in general regulate the pursuit of consumption goals.’ In accordance with this, consumers would consider the hedonic benefits of using shared e-bikes and e-scooters before thinking about how these shared vehicles could help to reduce the adverse environmental impact of transport or their travel behaviour. Indeed, a study of e-scooter owners has demonstrated that hedonic motivation significantly influences intention to use, whereas environmental concern does not (Kopplin et al., 2021). In addition, whereas several issues regarding shared e-bikes’ and e-scooters’ environmental impact may increase scepticism regarding their environmental benefits, because current product users tend to assess non-green attributes of green products more favourably (Haws et al., 2014), we propose that

Figure 2. Affective route.

H4a:

Positive emotions are positively related to environmental motivations in shared e-bike use.

H4b:

Positive emotions are positively related to environmental motivations in shared e-scooter use.

Methodology

Sample

To test the models, we surveyed users of shared e-bikes and e-scooters in Copenhagen and Stockholm. In total, 800 respondents participated − 400 from Copenhagen (shared e-bikes users = 200 and shared e-scooter users = 200) and 400 from Stockholm (shared e-bikes users = 200 and shared e-scooter users = 200). The participants were recruited using a panel research company between February and March 2020 and identified using the question ‘In the past year, have you used a shared electric bicycle or electric scooter?’ The two cities were chosen as they are relatively similar in many aspects, such as geographical location, economic status, and cultural background. Furthermore, these cities were chosen as shared micromobility has been introduced there first in the Nordic region (Wachunas, 2019).

The survey had several parts. The first part identified the users of shared e-scooters and e-bikes. The second part was about the degree of domain-specific innovativeness and green identity of the participants, and the environmental motivations and positive emotions linked to the use of shared e-bikes and e-scooters. Finally, the third part inquired about sociodemographic characteristics. A breakdown of the sociodemographic variables is found in Table 1.

Table 1. Socio-economic characteristics of participants.

		Shared e-bike users (n = 400) – percentage	Shared e-scooter users (n = 400) – percentage
Gender	Male	53.75	48.75
	Female	46.25	51.25
Age	16–29	32.00	48.75
	30–39	22.25	24.50
	40–49	21.50	13.75
	50–65	24.25	13.00
Education	Elementary school	6.00	5.50
	High school	24.50	32.00
	A few years of college studies	14.00	13.25
	College studies completed	44.75	40.50
	Other	10.75	8.75
Income	Less than 20,000 per month before tax	19.25	34.25
(in local currency)	20,000–35,000 per month before tax	28.00	20.50
	35,000–50,000 per month before tax	25.50	18.75
	50,000–65,000 per month before tax	6.50	7.50
	Over 65,000 per month before tax	5.75	6.00
	Prefer not to answer	15.00	13.00

Table 1 shows that the distribution between male and female shared e-bike and e-scooter users was similar, with males comprising 53.75% of shared e-bike users and 48.75% of shared e-scooter users. About 64% of the participants were also under 40 years old. Notably, the distribution of age among participants who use shared e-bikes is more even compared to that of shared e-scooters, especially for those aged 30 and older. Over 42% of the users asked had completed their college education and approximately 23% had a household income of between 20,000 and 50,000 (in Swedish kronor or Danish kroner) per month. Interestingly, 34% of shared e-scooter users earned less than 20,000 in their local currency per month, which could be attributed to the high number of participants being between 16 and 29 years old.

Measures

This paper is interested in four constructs: domain-specific innovativeness (DSI), green identity, environmental motivations, and positive emotions. The DSI question was adapted from the study by Noppers et al. (2015) regarding the role of product attributes in the adoption of sustainable technology. The participants were asked which of the statements in Table 2. Describes them best. In Table 2. The DSI segmentation of the participants is summarised. The segmentation is originally based on Rogers’ (2003) established adopter categories.

Table 2. Domain-specific innovativeness categories.

Adopter segment	Description	Shared e-bike users, percentage	Shared e-scooter users, percentage
1. Innovators	I am a type of person who closely follows new technological developments in the field of transport and who dares to take risks by being the first to purchase an innovative transport mode.	16.50	15.50
2. Early adopters	I am a type of person who envisions potential advantages in innovative products in the field of transport and who is one of the first to make use of these advantages and to profit from them.	26.75	29.00
3. Early majority	I am a type of person who is interested in innovative products in the transport field, but I am also pragmatic. First, I would like to take my time and be persuaded by the advantages of innovative transport. My decisions are (mainly) based on the recommendations of existing users.	42.75	47.75
4. Late majority	I am a type of person who is not thrilled by innovative products in the transport field, but who rather appreciates security. It is safe to purchase an innovative transport when it has been on the market for some while and offers obvious advantages.	9.25	6.00
5.Traditionalists	am atype of person who is traditional and has little affinity with innovative products in the transport field. Ido not like changes in life and Ipurchase an innovative transport only when the existing model Iuse is not produced anymore.	4.75	1.75

In our study, almost 90% of the participants considered themselves innovators, early adopters, or part of the early majority. However, while 76.75% of shared e-scooter user participants tended to see themselves as an early adopter or early majority, only 69.5% of users of shared e-bikes thought the same. On the other hand, more shared e-bike user participants (14%) believed that they were traditionalists or part of the late majority as opposed to the fewer number of shared e-scooter user participants who believed likewise (7.75%). According to Rogers (2003), only 2.5%, 13.5%, and 34% of consumers should be part of the innovators, early adopters, and early majority groups, respectively. Based on this descriptive argument, there is a clear indication that self-classified adopters of shared e-bikes and e-scooters indeed are early users of innovations in the transport sector, i.e. they belong to the first half of the general adoption curve in the transport domain. Indeed, this is reasonable as shared e-bikes and e-scooters are still considered new products. Nevertheless, this paper applied quota sampling, in which a certain number of participants for each transport mode was selected. Thus, the research does not look at the market in aggregate but instead focuses on individual consumers.

The questions that measured green identity were adapted from the study of Bouman et al. (2018), which tested measures related to environmental behaviours and beliefs. The measures reflect a person’s environmental concern. The higher the values of these measures, the more likely an individual is to perform pro-environmental actions (de Groot & Steg, 2010). In this paper, green identity measures how important it is for the respondent to prevent pollution, protect the environment, respect nature, and live in harmony with nature.

Positive emotion measures have also been adapted from the research of Bouman et al. (2018). The hedonic measures in this paper evaluated the positive emotions of enjoyment of life, doing pleasurable things, and entertainment in connection with the use of shared micromobility. Finally, the measures for environmental motivations come from Noppers et al. (2015). These measures reflect how green the participants perceive shared e-bikes and e-scooters to be in terms of how they help reduce air pollution caused by car traffic in general and in residential areas, dependence on fossil fuel, and environmental problems caused by traffic.

Results

Confirmatory factor analysis

A confirmatory factor analysis (CFA) with AMOS 25.0 applying maximum likelihood estimation was used to test the measurement model. The results revealed significant factor loadings (p < 0.001), with estimates all above 0.65. The construct reliability was measured using Rho, and was above 0.85 for all constructs, which is above the recommended 0.60 (Bagozzi & Yi, 1988). The average variance extracted for both factors was above 0.60, confirming construct validity. Table 3. summarises these results.

Table 3. Factor loadings, construct reliability, and construct validity.

Measures	Factor loading	Composite reliability, CR	AVE
Green identity		0.864	0.617
It is important for me to protect the environment	0.888
It is important for me to prevent environmental pollution	0.833
It is important for me to respect nature	0.743
It is important for me to live in harmony with nature	0.657
Environmental motivations		0.918	0.739
Renting and using electric bicycles/scooters, in general, would help to reduce the environmental problems caused by car traffic	0.915
Renting and using electric bicycles/scooters, in general, would reduce the climate problems caused by car traffic	0.901
Renting and using electric bicycles/scooters, in general, would help reduce air pollution caused by car traffic in residential areas	0.829
Renting and using electric bicycles/scooters, in general, would reduce society’s dependence on fossil fuel	0.786
Positive emotions
Renting and using electric bicycles/scooters is entertaining	0.852	0.875	0.700
Renting and using electric bicycles/scooters is fun	0.850
Renting and using electric bicycles/scooters makes me enjoy life	0.808

The chi-square goodness-of-fit index is statistically significant (χ2 (41) = 189.674; χ2/df = 4.626), which does not validate the measurement model. However, this issue is common in studies with large samples (Bagozzi & Yi, 1988). Thus, other fit indices should also be examined. Other indices were higher than 0.95, which meets the criteria for good model fit (NFI = .966, CFI = .973, IFI = .973, GFI = .960). The rooted mean square error (RMSEA) was 0.067 (lo 90 = .058, hi 90 = .077).

Comparing measures between users

Both users of shared e-bikes (mean = 3.358, SD = .999) and users of e-scooters (mean = 3.558, SD = .904) consider themselves innovative. The distribution of the adopter segment shows that 86% of shared e-bike users think that they are either innovators, early adopters, or part of the early majority when it comes to the use of innovations in transport. On the other hand, over 92% of shared e-bike users share the same beliefs. By using a t-test to compare group means, we determined that there was a significant difference between the level of domain-specific innovativeness of shared e-bike and e-scooter users (t-stat = 2.968, df = 790, p < .05). This result indicates that shared e-scooter users considered themselves more innovative in the field of transport than shared e-bike users.

As for green identity, based on the mean of the measures (shared e-bike users = 4.068, SD = 1.007; shared e-scooter users = 4.092, SD = .931), we can infer that shared e-bike and e-scooter users identify themselves as green. However, these means are not weighted based on the factor analysis loadings; therefore, it is not enough to compare these means to determine mean differences. To test whether users perceive their degree of green identity differently, a multiple-indicator-multiple cause (MIMIC) structural equation model using AMOS was used. Instead of using a t-test, MIMIC allows for the examination of the effect of variables on latent constructs that are measured using several indicators (Ríos-Bedoya et al., 2009). No significant difference between the effect of the two groups on green identity could be established (p = .168, NFI = .970, CFI = .976, IFI = .976, GFI = .970, RMSEA = .076). Therefore, in this study, the green identities of shared e-bike and e-scooter users were not significantly different from each other.

When it comes to the environmental motivations, based on the mean scores, both shared e-bike users (mean = 3.743, SD = 1.174) and e-scooter users (mean = 3.414, SD = 1.160) perceived that the use of these vehicles could help to reduce the adverse environment-related impact of cars. Both groups perceived the positive emotions that can be attributed to the use of shared e-bikes (mean = 3.268, SD = 1.196) and shared e-scooters (mean = 3.295, SD = 1.279). Applying MIMIC (NFI = .967, CFI = .972, IFI = .972, GFI = .962, RMSEA = .087), there is a significant difference between the two groups when it comes to the environmental motivations for using shared e-bikes or e-scooters (p < .001). However, no significant difference between positive emotions can be ascertained (p = .391). These results demonstrate that shared e-bike users have stronger beliefs that shared e-bikes can help mitigate environmental problems caused by car use than e-scooter users. However, both shared e-bike and e-scooter users feel the same degree of positive emotions when using shared e-bikes and e-scooters.

Model testing

Shared e-bikes

To assess which of the two models provided a better fit for the data, several indices were compared. Model 1 – the cognitive route, where environmental motivations are antecedents of positive emotions – had the following indices: χ2 (51) = 140.335, p < .001; χ2/df = 2.752; NFI = .951, CFI = .968, IFI = .968, GFI = .944; RMSEA = .066 (lo 90 = .053, hi 90 = .079). For Model 2 – the affective route, where affect is a precursor of environmental motivations – the results provide a significant chi-square (χ2 (51) = 152.507, p < .001; χ2/df = 2.990). Nevertheless, other baseline indices were greater than 0.090 (NFI = .946, CFI = .963, IFI = .964, GFI = .941) and RMSEA = .071 (lo 90 = .058, hi 90 = .084). Based on these indices, the cognitive model fits the data better than the affective model. Nevertheless, because the models are non-nested, parsimony fit indices were also compared. These indices are the Akaike information criterion (AIC) and the Bayesian information criterion (BIC). The model with the lower indices is preferred (Model 1 – Cognitive: AIC = 197.119, BIC = 304.889; Model 2 – Affective: AIC = 206.507, BIC = 314.277). With this comparison, it is reasonable to conclude that Model 1, the cognitive route shown in Figure 3, provides a better fit for modelling shared e-bike use.

Figure 3. Shared e-bike cognitive–environmental motivation model.

Table 4 summarises the SEM results of the shared e-bike cognitive model.

Table 4. Shared e-bike model SEM results.

Construct			β	Hypothesis
Green identity	→	Environmental motivations	0.116**	H1a
DSI	→	Positive emotions	0.249*	H2a
Environmental motivations	→	Positive emotions	0.453*	H3a

Significance level: *p < .001, **p < 0.05.

Shared e-scooters

Model 1, the cognitive route, has the following indices: χ2 (50) = 143.119, p < .001; χ2/df = 2.806; NFI = .951, CFI = .968, IFI = .968, GFI = .945; RMSEA = .067 (lo 90 = .054, hi 90 = .080). For Model 2, the affective route, the results provide a significant chi-square (χ2 (51) = 139.159, p < .001; χ2/df = 2.729). Nevertheless, other baseline indices were greater than 0.090 (NFI = .952, CFI = .969, IFI = .969, GFI = .947) and RMSEA = .066 (lo 90 = .053, hi 90 = .079). The models are non-nested; therefore, parsimony fit indices were also compared. The model with the lower indices is preferred (Model 1 – Cognitive: AIC = 197.119, BIC = 304.889; Model 2 – Affective: AIC = 193.159, BIC = 300.929). With this assessment, it is reasonable to conclude that Model 2, the affective route depicted in Figure 4, provides a better fit for modelling shared e-scooter use.

Figure 4. Shared e-scooter affective–hedonic model.

Table 5 summarises the SEM results of the shared e-scooter affective model.

Table 5. Shared e-scooter model SEM results.

Construct			β	Hypothesis
Green identity	→	Environmental motivations	0.086^a	H1b
DSI	→	Positive emotions	0.296*	H2b
Positive emotions	→	Environmental motivations	0.472*	H4b

Significance level: *p < 0.001^{, a}non-significant.

Table 6 summarises the results of the eight hypotheses of this research. Because the cognitive model fits the use of shared e-bikes better, examining the effect of positive emotions on the environmental motivation in shared e-bike use is excluded. This result does not mean, however, that there is no influence of emotions on motivation. Nevertheless, the environmental motivation route has a stronger predictive capacity than positive emotions on the adoption of shared e-bikes. This capacity is inversely the case for shared e-scooters, in which the affective model provides a better fit.

Table 6. Summary of hypothesis results.

Hypothesis	Supported/rejected/excluded	Significance level
H1a: Green identity is positively related to environmental motivations in shared e-bike use.	Supported	p < .05
H1b: Green identity is positively related to environmental motivations in shared e-scooter use.	Rejected	n/a
H2a: DSI is positively related to positive emotions in shared e-bike use.	Supported	p < .001
H2b: DSI is positively related to positive emotions in shared e-scooter use.	Supported	p < .001
H3a: Environmental motivations are positively related to positive emotions in shared e-bike use.	Supported	p < .001
H3b: Environmental motivations are positively related to positive emotions in shared e-scooter use.	Excluded	-
H4a: Positive emotions are positively related to environmental motivations in shared e-bike use.	Excluded	-
H4b: Positive emotions are positively related to environmental motivations in shared e-scooter use.	Supported	p < .001

Discussion

The novelty of this research lies in its examination of decision-making in green transport innovations and how two similar green innovations can motivate consumers differently. Consequently, this paper aimed to determine the decision-making route related to the hedonic and environmental motivations that shared micromobility users apply in their decision to adopt a green innovation. Based on the findings, the decision to use shared e-bikes follows a cognitive route, in which environmental motivations affect the positive emotions that consumers feel about the use of shared e-bikes. Users of shared e-scooters, on the other hand, are more driven by their emotions before considering the green attributes of these microvehicles.

From these results, it can be inferred that the use of shared e-bikes supports previous studies suggesting that consumers may benefit from the hedonic value of green consumption through their environmental motivation (Valour et al., 2018; Venhoeven et al., 2020). In particular, this finding is congruent with a study conducted in the area of organic food that shows how the perceived ecological welfare attribute of organic food positively affects the hedonic valuation of the product (Lee & Yun, 2015). Furthermore, this finding also corresponds to the recent results on experiments regarding microalgae-based foods and nanophotonic lightbulbs, demonstrating how the degree of environmentally friendly perception of innovations strengthens the positive emotions experienced during innovation use (Contzen et al., 2021).

By contrast, the enjoyment in the use of shared e-bikes comes partly from the perception of the environmental benefits. The environmental motivations of shared e-scooter users are relatively driven by the positive emotions from use, which supports how hedonic motivation can influence the adoption of green innovations (Gurtner & Soyez, 2016; Schuitema et al., 2013). The influence of positive emotions on environmental value perception of products has also been demonstrated in a study of green cosmetic products (Jaini et al., 2019). The environmental motivations can also be considered a secondary motive, as shown in a study of organic food, in which participants only mentioned such motives when prompted (Vega-Zamora et al., 2014).

Additionally, the findings of this paper suggest that shared e-scooter users tend to be hedonic innovators, while shared e-bike users are more utilitarian innovators in the sense that their consumption benefits the environment. These results are in line with previous studies revealing that one of the main reasons for the use of e-bikes is their environmental benefits (Handy & Fitch, 2022; Simsekoglu & Klöckner, 2019), whereas e-scooters are used more for hedonic experience (Kopplin et al., 2021; Reck et al., 2021). Studies in other green product domains have also shown the existence of consumers who purchase green products for hedonic experience (Choi & Johnson, 2019; Moshood et al., 2022), while others for environmental reasons (Hahnel et al., 2014; Saari et al., 2021).

Theoretically, these results indicate that familiarity with or experience of e-bikes may have contributed to how consumers assessed the environmental impact of their shared form. Indeed, experience has been demonstrated to influence the formation of cognition and affect-based customer satisfaction (Homburg et al., 2006) and the evaluation of product performance (Pickett‐Baker & Ozaki, 2008). On the other hand, the lack of knowledge regarding how e-scooters could help address the adverse environmental impact of transport made users’ decisions more inclined towards automatic hedonic attributions (Kopplin et al., 2021). Another reason could be that information processing in high-technology products in new contexts, such as in shared e-scooters, is complex (Lee et al., 2011). Because of this complexity, consumers are hesitant to deliberate on the environmental aspects of the transport option.

This research also demonstrates that green identity is related to users’ environmental motivations for the use of green innovations, as shown in other areas, such as the adoption of bio-plastics (Confente et al., 2020) and alternative fuel vehicles (Potoglou et al., 2020). This supports the strategy of promoting shared e-bikes as a green transport mode. This result also confirms previous research showing that the higher a person’s level of environmental concern, the greater the likelihood that they will perceive the environmental benefits of the products they use (Gardner & Abraham, 2010; van der Werff et al., 2013).

Surprisingly, there is a lack of a significant relationship between green identity and environmental motivations among shared e-scooters users. This finding may be ascribed to the issues related to the environmental impact of these microvehicles (Gössling, 2020; Hollingsworth et al., 2019). Because of the scepticism regarding the green attributes of shared e-scooters, users may find it difficult to justify their use through their green identity. This may also be a reason why they take the hedonic route in the decision to use the microvehicle to avoid cognitive dissonance. This conclusion is similar to studies showing that concern for the environment does not directly or significantly affect the assessment of the environmental impact of green products (Bang et al., 2000; Newton et al., 2015). This is also in line with a study regarding how green consumers rationalise flying. By looking at other important aspects of their journey, consumers justify their actions as acceptable. Nevertheless, because the dissonance is strong for some, they reach a point where they cannot justify flying any longer but still continue to fly (McDonald et al., 2015).

Finally, in the use of both shared e-bikes and e-scooters, domain-specific innovativeness strengthens the positive emotions experienced in the use of these shared microvehicles. An explanation for this relationship is that being innovative makes consumers more perceptive regarding the emotional benefits of products (Moons & De Pelsmacker, 2012). Another reason for this is that innovative consumers seek products that are stimulating and elicit positive emotions (Aroean & Michaelidou, 2014), suggesting that shared microvehicles are perceived as enjoyable modes of transport. Thus, as expected, shared e-bikes and e-scooters attract innovators in transport, as demonstrated in other studies regarding e-bikes and e-scooters (Flores & Jansson, 2021; Seebauer, 2015; Simsekoglu & Klöckner, 2019), and these innovators experience positive emotions when they use these shared microvehicles (Kopplin et al., 2021). Interestingly, shared e-scooter users perceive themselves as more innovative than shared e-bike users. Since shared e-scooters are newer than shared e-bikes, as innovation literature has argued, their users are thus more receptive to adopting novel products (Hwang et al., 2021; Truong, 2013). An alternative explanation may be that since e-scooter users are younger than e-bike users, they tend to be more innovative than those belonging to the older age groups (Lambert-Pandraud & Laurent, 2010).

Overall, these findings address the important questions about the roles of innovativeness, greenness, and emotions in the adoption of green innovations. This paper also reveals that different types of green innovations, irrespective of how similar their attributes and promotions are, will motivate consumer adoption differently. Therefore, marketers of green innovations should determine what kind of green innovation they provide, i.e. utilitarian or hedonic, to create better targeted marketing strategies and campaigns to reach potential consumers who are not convinced by the environmental or enjoyable aspects of these products.

Theoretical contributions

This paper responds to the call to examine the factors and reasons involved in how motivations in the adoption of different green innovations can vary (Flores & Jansson, 2021; Paparoidamis & Tran, 2019). The paper started by evaluating the decision-making route taken in the adoption of shared e-bikes and e-scooters, and then assessed how DSI and green identity could affect this process.

In marketing and psychology, many empirical studies have demonstrated the interrelationship between cognition and affect in decision-making (Chiew & Braver, 2011; Choi et al., 2011; van der Linden, 2014). Nevertheless, in order to formulate effective marketing and communication strategies, it is logical to focus on one consistent strategy that targets either affect or cognition (Mayer & Tormala, 2010). Therefore, the marketing of green innovations should target either the emotions or the environmental motivations of the target group, considering the group’s knowledge and experience regarding these products.

A significant theoretical contribution of this paper lies in decision-making in green innovations. Particularly, this paper adds to the literature that underlines the significance of emotions in pro-environmental decision-making and the role of cognition and emotions on the adoption of pro-environmental behaviour (Contzen et al., 2021; Rezvani et al., 2018; Schneider et al., 2021). The study presented here shows that green innovation adoption is an interplay between cognition and affect. Nevertheless, we also show that their impact is dependent on the type of green innovation in question. Specifically, we show how the decision to use shared e-bikes, which can be considered an extension of existing shared conventional bikes, is more influenced by cognition – in this case, the environmental motivation. On the contrary, the use of shared e-scooters is motivated by hedonic reasons to a greater extent, which could be due to its more recent introduction and limited consumer experience. Therefore, in theory, we add to the ongoing discussion regarding what kind of green innovations can drive green behaviour (Jansson et al., 2011; Paparoidamis & Tran, 2019) and have the potential to contribute to lowering the environmental impact of the transport sector.

In line with these contributions, another important theoretical contribution of this study is that it adds to the understanding of how the diffusion of green innovations works. The results demonstrate that even though green innovations are promoted in the same manner and share similar attributes, consumer perceptions and the decision to adopt can still vary (Flores & Jansson, 2021). Some innovators in relation to green products seek the hedonic attributes of the innovations before considering the environmental benefits of the product, while others are highly influenced by their green identity and environmental motivation. Also related to the diffusion of innovations, this paper shows that although the majority of the innovators in the transport domain classify themselves as part of at least the early majority group or the first half of the diffusion curve, not everyone considers themselves innovative. This is not in line with the proposal of Rogers (2003), which argues that those who are first to adopt innovations should be innovative and are, therefore, faster than the late majority and laggards to adopt innovations. This supports previous findings suggesting that consumer innovativeness alone cannot solely predict the adoption of innovations (Li et al., 2015; Roehrich, 2004) and that there is still a need to understand how consumer innovativeness works in the context of green innovations (Paparoidamis & Tran, 2019) and transport innovations (Noppers et al., 2015).

We also found that the importance of cognition and emotions may depend on the strength of consumers’ green identity and innovativeness, as well as on the perceived greenness of the product. Many empirical studies have already illustrated the significance of green identity and innovativeness in green decision-making, but it has not yet been clearly demonstrated how these characteristics are mediated once individuals face the decision to use different green innovations.

Managerial implications

In practical terms, this paper helps companies that offer green transport innovations to better formulate marketing and communication strategies. For example, organisations that introduce a green innovation, where the knowledge and experience of consumers are limited, should focus on the hedonic benefits of the product and its usage. On the other hand, those that introduce green innovations that are comparable or extensions to known products would likely be more successful if they focus on green attributes that can be informatively and consciously compared. They can also emphasise how green these innovations are compared to the products they substitute to help consumers justify their behaviour.

In the case of shared micromobility, in order to increase shared e-bike adoption, providers can tap into the hedonic benefits of the innovation and focus on consumers who are mainly motivated to try using innovations due to the positive emotions linked to use. For instance, they can promote shared e-bikes by engaging social media influencers, especially those who promote fun innovations (Borowski et al., 2020). As many are aware of the functional and environmental benefits of bikes in general, in order to promote their shared e-forms, people should also feel the pleasure they can get from travelling with the transport mode compared to cars, for example.

Shared e-scooter providers can attract green consumers by emphasising the environmental benefits of using shared e-scooters and addressing issues related to the short life span of the transport mode. Marketers can also invest more in informing the public about the environmental benefits of using e-scooters, and not only focus on the technical improvements of the innovation. This can be done by collaborating with public transport authorities and asking them to include shared e-scooters in their agenda for greener transport (Ziedan et al., 2021). Additionally, providers can engage people known to fight climate change to ride their vehicles and display the advantages of these compared to cars, for example, in terms of flexibility, ease of access, and traffic congestion. E-scooter providers can also incorporate features into their services that make users aware of the carbon footprint produced by riding an e-scooter, compared to other transport forms. The important thing is to be clear and truthful about how e-scooters are less harmful to the environment if they replace cars and what their disadvantages are when they replace walking or cycling to avoid scepticism from the public.

Nevertheless, as shared e-scooter use can be viewed as hedonic behaviour, promoting shared e-scooters as green may drive away interest from current users. Indeed, people who are motivated by hedonic goals may not behave sustainably (Lindenberg & Steg, 2007). Therefore, providers should find a way to balance the green and fun aspects in their marketing, and should use targeting and positioning strategies to reach different user groups in effective ways.

Limitations and further studies

Although there are several novel contributions of this study as accounted for above, there are also some limitations. In both models, we did not test the direct effect of consumer innovativeness on environmental motivations and green identity on positive emotions since this would have deviated from the focus of this study. Furthermore, we assessed consumer innovativeness as domain-specific innovativeness in transport, in which we look at a consumer’s tendency to adopt new technologies in the sector, including those innovations that are not considered green. Further studies could explore these areas.

As this study is based on environmental perceptions and positive emotions, it would be beneficial to examine other cognitive-based factors in decision-making, such as instrumental and symbolic benefits, and to evaluate how negative affect influences the adoption of shared e-bikes and e-scooters. Further research can also apply the theoretical models of this research to other green innovations and examine whether they support or contradict the findings of this study. In particular, they can assess whether increased experience and knowledge of green product attributes are related to environmental motivation and positive emotions.

Future research could also compare shared micromobility to other forms of transport and to other forms of green innovations in other domains. For instance, although shared e-cars, shared e-bikes, and e-scooters are powered by electricity, they serve different purposes and markets. Unlike shared e-cars, shared micromobility is designed for short-term and short-distance access (Abduljabbar et al., 2021; Reck et al., 2021). When it comes to their similarities with public transport, shared micromobility is not like other forms of public transport as public transport systems are designed to carry many passengers at the same time, with specified routes and destinations. Shared e-bikes and e-scooters, by contrast, are designed for single-person use and offer more flexibility to users (Guidon et al., 2019; Ziedan et al., 2021).

Although the research was conducted in two cities, Copenhagen and Stockholm, this current paper does not compare results between the two cities and the various sociodemographic variables included in the study. Such a comparison could have provided more insights into the similarities and differences between the cities. Nonetheless, these issues were not the main areas of interest as the two cities are similar in many aspects, such as sociodemographic variables, weather conditions, and cultural background. The paper also does not present and compare the frequency of use of the participants, perceptions of differing policies in the two cities, different marketing strategies, and the general debate concerning these vehicles, which could perhaps also account for the differences in use motivations. As the debate is rather fast-paced and new policies are being discussed and implemented based on currently perceived problems, it is challenging to get a full picture of how these factors influence use, perceptions and motivations at any given time. Focusing on green identify, domain-specific innovativeness, and hedonic and environmental motivations as more stable constructs over time was decided rather than making a detailed snapshot picture of other motivations. Further research can explore these dimensions and their interrelatedness to develop more specific local policies also in relation to the critiques raised from a social perspective against the hurried rollout of e-scooters and the problems created. Other researchers could also conduct interviews and longitudinal studies to gain deeper insights into the use of shared e-bikes and e-scooters, especially since the transport innovation industry is fast-paced but also due to changes in the wake of the Covid-19 pandemic.

Finally, the application of the results of this paper should consider that it was conducted in two developed cities, where current infrastructure supports the use of shared microvehicles. Nevertheless, this paper can serve as a guide for practitioners in other cities, particularly those in developing countries, as the introduction of shared micromobility does not require significant public investment or substantial changes to the built environment, compared to building more roads and parking for cars and increasing public transport routes and hubs.

Acknowledgements

The authors would like to thank the editor and the three anonymous reviewers for their comments and suggestions. We would also like to thank K2 for funding the data collection for this project.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The work was supported by the K2.

Notes on contributors

Phil Justice Flores

Phil Justice Flores is a Ph.D. student at the Department of Business Administration at Lund University School of Economics and Management. He is also part of K2 - Sweden’s national centre for research and education on public transport and Lund University Agenda 2030 Graduate School. His research interests are sustainability, consumer behaviour, and innovation adoption. His article has been recently published in the Journal of Consumer Behaviour.

Johan Jansson

Johan Jansson is a professor of Business Administration with specialization in Marketing at Umeå University, Sweden. He is also affiliated with K2 – Sweden’s national centre for research and education on public transport. His research interests include sustainability, green consumption, communication and passenger transport. He articles have been published in journals such as Journal of Consumer Marketing, Energy Policy, and Business Strategy and the Environment.