Enhancing Consumption of Sustainable Transportation: Determinants and Outcome of Consumer Engagement with Bike-Sharing Service

doi:10.21203/rs.3.rs-1961420/v1

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Enhancing Consumption of Sustainable Transportation: Determinants and Outcome of Consumer Engagement with Bike-Sharing Service

https://doi.org/10.21203/rs.3.rs-1961420/v1

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published 01 Mar, 2023

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Bike-sharing service has become a popular sustainable means of transportation due to its direct impact on traffic congestion, energy consumption, the environment, and people’s quality of life. Existing literature suggests that sustainable consumption can be promoted by engaging consumers with green products. This study examined drivers and the outcome of consumer engagement with bike-sharing services based on the technology acceptance model (TAM). A survey was conducted to collect the data from the users of the bike-sharing service in Kuala Lumpur. Structural equation modelling was used to analyse the data and find the relationship between variables. The empirical analyses showed that perceived ease of use and perceived usefulness of the bike-sharing service positively impact all facets of consumer engagement with bike-sharing service, which subsequently influences the continuance usage intention of bike-sharing service. The findings of this study offer useful insights that could enhance the consumption of bike-sharing service. This study also offers some guidelines to transportation practitioners, policymakers, and urban planners regarding promoting healthy and sustainable travel behaviour among urban commuters through bike-sharing service.

Consumer engagement

Perceived ease of use

Perceived usefulness

Continuance intention

Bike-sharing system

Perceived ease of use affects consumer engagement with BSS.
Perceived usefulness affects consumer engagement with BSS.
Consumer engagement with BSS affects continuance intention of BSS.

People show increasing concerns regarding the impact of the urban transportation system on the environment, energy consumption, and quality of life (Deliana & Rum, 2019; Zhu & Diao, 2020). Driven by these concerns, many planners acknowledge that the continued pursuit of automobility is neither sustainable nor desirable (Kent & Karner, 2019). These issues can be resolved by promoting sustainable non-motorised transport modes, including biking (Kim, Choi, Kim, & Fujii, 2017). More specifically, cycling is valuable to society for its ability to ease traffic congestion and pollution, increasing environmental sustainability, and creating healthier individuals (Cupples & Ridley, 2008). Owing to this, planners and decision-makers are trying to enhance the adoption of cycling through improved infrastructure, enhanced safety (Horton, Rosen, & Cox, 2007), and fiscal incentives (Caulfield & Leahy, 2011).

Recently, researchers have shown an increased interest in the bike-sharing service (hereafter BSS) due to its rise in popularity as an alternative mode of transportation in urban areas. There is little doubt that the popularity of BSS is due, at least in part, to the demands of the increasingly mobile population and the negative environmental impact of motorised transportation systems (Jamšek & Culiberg, 2020; Murphy & Usher, 2015). Consequently, BSS providers are investing heavily in BSS infrastructure. To illustrate, capital costs of BSS can range from $4000 to $5000 per bicycle, which also covers the cost of docking stations and kiosks (Beitsch, 2016). Despite heavy investment in BSS and high public support for BSS, there appears to be lessening personal use of BSS (Kim et al., 2017). Furthermore, users’ reckless attitude towards BSS has shut down numerous BSS providers due to huge financial or operational failures (Nikitas, 2019). Scholars need to revisit what makes BSS a desirable mode of transportation and how consumers’ continuance usage intention of BSS can be enhanced.

The past few years have seen increasingly rapid advances in the field of sustainable urban transportation. This has led to an enhanced discussion on factors influencing the adoption of the sustainable mode of transportation, including BSS. To illustrate, Shen, Zhang, and Zhao (2018) have examined the role of external factors such as bicycle infrastructure, bike fleet size, built environment, and weather conditions on BSS usage. Manzi and Saibene (2018) investigated the factors driving satisfaction with BSS. Similarly, a number of researchers explored psychological factors that may affect consumer attitude towards BSS (Kim et al., 2017; Milakis, 2015). These psychological factors include internal individual elements such as attitudes, personal values, and beliefs (Piligrimienė, Žukauskaitė, Korzilius, Banytė, & Dovalienė, 2020). However, questions have been raised about the role of internal motivational factors such as consumer engagement in BSS consumption. One of the most significant current discussions in marketing philosophy is that consumer engagement enhances consumption of products (Pansari & Kumar, 2017). The research to date has tended to focus on consumer engagement construct in the commercial context. The generalisability of existing research on consumer engagement is problematic. What is not yet clear is the impact of consumer engagement with BSS on the continuance usage intention of BSS. Understanding this relationship will provide guidelines to BSS providers on enhancing the consumption of BSS.

This study makes several contributions to marketing theory and sustainable urban transportation practice. First, the literature on psychological determinants of consumption of BSS typically relies on attitudinal factors (Kim et al., 2017) and does not treat consumer engagement with BSS as a driver of consumption of BSS. Thus, this study will extend the psychological determinants of consumption intention of BSS in the form of consumer engagement with BSS. Second, this study will provide insights into factors that may enhance consumer engagement with BSS. No previous study has investigated the drivers of consumer engagement with BSS. Third, little is known about the conceptual meaning of consumer engagement with BSS. Thus, the current study’s focus on exploring the consumer engagement concept in the context of BSS widens the boundaries of consumer engagement and sustainable urban transportation research and contributes to the development of consumer psychology theory. Fourth, the research to date focused on several objects of engagement, including a brand (Hollebeek, Glynn, & Brodie, 2014), cloth swapping activity (Camacho-Otero, Pettersen, & Boks, 2020), brand community (Baldus, Voorhees, & Calantone, 2015), sustainable consumption (Piligrimienė et al., 2020), and social media brand posts (Schivinski, Christodoulides, & Dabrowski, 2016). However, no studies have been found which treated BSS as an object of consumer engagement. Thus, the current study considers BSS as the engagement object. Finally, for practitioners who are interested in understanding ways to enhance consumption of BSS, this work will suggest a mechanism involving consumer engagement with BSS to increase intention to use BSS. By taking consumer engagement with BSS into consideration, our work highlights the need for BSS providers and city governments to adopt engagement-enhancing strategies that will lead to increased adoption of BSS, return on investment, and ultimately to sustainable urban development.

This paper is structured as follows. It begins by explicating the theoretical background of this study by giving a brief overview of relevant theoretical constructs. Next, the hypotheses and the conceptual model are presented. This is followed by an explanation of the methodology and results of hypothesis testing. This study concludes with a discussion of the limitations of this study, future research directions, and implications of the findings for both researchers and practitioners.

2.1. Consumption of bike-sharing service

The concept of BSS was introduced over half a century ago in Amsterdam as a dockless BSS providing access to unlocked and free-of-charge bikes (Shen et al., 2018). However, the bike-sharing program was not considered a sustainable system due to inadequate technology (Tironi, 2015), theft, and vandalism (Shen et al., 2018). Later on, the second generation of BSS was introduced in Denmark, where consumers were required to pay a small deposit to unlock bikes from their docking stations (DeMaio, 2009). This generation of BSS saw many improvements over the previous generation in locking, payment, renting, and return of the bikes; however, bike theft was still an issue (Shen et al., 2018). After a while, the third generation of BSS was launched, which overcame theft and vandalism with the help of electronic bike locks, on-board computers, mobile phone access, and telecommunication systems (DeMaio, 2009; Manzi & Saibene, 2018). The fourth generation of BSS was characterised by adopting smart high-tech systems such as smart locks with unique-code identifier chips, docking stations equipped with WiFi, computerised data processing, and online stores for bike accessories (Manzi & Saibene, 2018). Since then, bike-sharing programs have received rapid adoption in Europe and other continents, including Asia (DeMaio, 2009). In Asia, BSS is operating in South Korea, Malaysia, China, and Singapore (Shaheen, Guzman, & Zhang, 2010).

Recently, investigators have examined the drivers of consumption of BSS and found that a number of factors predict the consumption of BSS. For example, factors such as place of residence, the time required to access a BSS station, age (Molinillo, Ruiz-Montañez, & Liébana-Cabanillas, 2020), car traffic volumes, fuel prices, and environmental pollution affect usage of BSS (Manzi & Saibene, 2018). Similarly, Castillo-Manzano and Sánchez-Braza (2013) suggested that people opt for BSS for the convenience it provides to complete a short-distance journey inside the urban areas and the help it offers in reducing pollution and traffic congestion. On the other hand, Bachand-Marleau, Lee, and El-Geneidy (2012) argued that the desire to avoid the theft of one’s own bike and convenience are the key drivers of BSS usage. In another major study, Shaheen, Zhang, Martin, and Guzman (2011) found that well-maintained bikes, locking mechanism, and more docking stations are key motivators for adopting BSS. Moreover, BSS is prone to influence by the weather. To illustrate, Shen et al. (2018) found that rainfall and hot weather can reduce BSS usage. Similarly, they also found that the density of commercial areas, smaller street blocks, supportive cycling facilities, better transportation infrastructure, and more diverse economic activities influence the usage of dockless bikes.

There is a large volume of published studies describing the role of psychological factors in enhancing BSS consumption. To illustrate, Milakis (2015) assert that perceived behavioural control and attitude towards the behaviour affect the intention to use BSS. Similarly, Kim et al. (2017) found that attitude towards environmental issues affects the perceived value of BSS. Furthermore, Yu, Yi, Feng, and Liu (2018) argued that perceived usefulness and perceived ease of use drive a positive attitude towards BSS, which further amplifies the intention to use BSS. Though previous studies have reported the role of psychological factors in influencing BSS adoption, researchers have not dealt with the role of consumer engagement in predicting the consumption intention of BSS. Little is known about consumer engagement with BSS, and it is not clear what factors foster such engagement and its outcome in the form of consumption intentions of BSS.

2.2. Consumer engagement with bike-sharing service

The notion of consumer engagement has recently received significant attention in the marketing literature (Brodie, Hollebeek, Jurić, & Ilić, 2011; Meire, Hewett, Ballings, Kumar, & Van den Poel, 2019). A number of studies in the domain of marketing posit that engagement is a promising concept which involves a set of activities to influence consumer behaviour (Bowden, Conduit, Hollebeek, Luoma-aho, & Solem, 2018; Vivek, Beatty, & Morgan, 2012). In the domain of marketing, consumer engagement has been defined as “a psychological state that occurs through interactive, co-creative consumer experiences with a focal agent/object” (Brodie et al., 2011). Recent evidence suggests that consumer engagement positively contributes to new customer acquisition and existing customer retention (Ho, Chung, Kingshott, & Chiu, 2020). Similarly, much of the previous research also found that psychological factors drive consumer behaviour towards sustainable products (Liu, Qu, Lei, & Jia, 2017).

Consumer engagement has been seen as a multidimensional construct with properties that vary with the context and the engagement object (Hollebeek et al., 2014). Advocating BSS goes beyond purchasing it and may include interacting with BSS without necessarily owning it (Vivek et al., 2012). This is one of the important assumptions of the consumer engagement concept. Based on this premise, consumer engagement with BSS can be defined as the intensity of an individual’s participation in and connection with BSS initiated by the consumer (Vivek, Beatty, Dalela, & Morgan, 2014). Such consumer engagement may exhibit consumer thinking, feelings, actions, and social interactions involving the BSS (Vivek et al., 2012). Some scholars maintain that consumer engagement often involves three main dimensions: conscious attention, enthused participation, and social connection (Vivek et al., 2014). The current study follows the same approach for the conceptualisation of the construct of consumer engagement with BSS. Conscious attention refers to the degree of interest consumers have in interacting with BSS. Similarly, consumers enthused participation in green transportation in the form of their willingness to shift to more eco-friendly transportation and their motivations for driving green transportation will affect their engagement with green transportation (Fischer, 2008; Froehlich et al., 2009). Enthused participation in BSS refers to the zealous feeling consumers have related to using or interacting with the BSS (Vivek et al., 2014). Finally, social connection refers to enhancing the interaction based on the inclusion of others with the BSS. Consumers like talking about and sharing their experience of green transportation with others, and sometimes their green behaviours act as conversation starters (Froehlich et al., 2009).

Most of the existing studies on consumer engagement focus on commercial entities as an object of engagement (Hollebeek et al., 2014), and there are very few studies that explore the concept of consumer engagement with green transportation alternatives such as BSS (Piligrimienė et al., 2020). The potential of consumer engagement in affecting consumers’ actions suggests investigating the role this construct plays in the continuance of consumption of BSS. Consumer engagement with green transportation alternatives such as BSS may result in behaviours such as reliance on green transportation, which have positive implications for sustainable consumption and the natural environment (Mainieri, Barnett, Valdero, Unipan, & Oskamp, 1997; Syrdal & Briggs, 2018).

2.3. Determinants of Consumer Engagement with bike-sharing service

Researchers look for opportunities to advance the understanding of attitudes, motives, and values that drive consumer behaviour. Recent trends in consumer engagement have led to a proliferation of studies investigating why some consumers tend to engage with objects more than others. Factors found to be influencing consumer engagement vary with the engagement objects and contexts. Identification of determinants of consumer engagement in sustainable consumption is challenging due to this concept's novelty in the context of sustainable consumption (Piligrimienė et al., 2020). Several attempts have been made to examine the factors influencing consumer engagement (Meire et al., 2019; Waqas, Hamzah, & Salleh, 2020) and sustainable consumption activity itself (Manzi & Saibene, 2018). However, a systematic analysis of existing literature revealed that far too little attention was paid to investigating consumer engagement drivers with BSS.

The technology acceptance model (TAM) is one of the most widely applied theoretical models in understanding, explaining, and predicting the usage of new technologies (Venkatesh & Davis, 2000). As smart high-tech tools characterise the fourth generation of BSS (Manzi & Saibene, 2018), the TAM can guide towards factors that can influence consumer engagement with BSS. The TAM model, introduced by (Davis, 1989), explains how “perceived usefulness” and “perceived ease of use” of technology drive the consumption of a technology-based object. Though the TAM model has been mostly restricted to understand the consumers’ intention to use a variety of information systems, including social media (Rauniar, Rawski, Yang, & Johnson, 2014), online learning (Abdullah & Ward, 2016), and online games (Hsu & Lu, 2004), recently it has been adopted to investigate the consumption of BSS (see Jamšek & Culiberg, 2020; Wang, Wang, Wang, Wei, & Wang, 2020). To illustrate, Hazen, Overstreet, and Wang (2015) adopted the TAM and found that perceived quality and perceived convenience influence the adoption of BSS. Similarly, Yu et al. (2018) discovered that perceived usefulness and perceived ease of use affect consumer attitude towards BSS.

Recent evidence suggests that TAM can predict consumer engagement (Bianchi & Andrews, 2018; Moriuchi, 2019). Nevertheless, in the context of BSS, the existing accounts fail to use the TAM to examine the drivers of consumer engagement with BSS. Hence, this study aims to fill this gap by integrating TAM and consumer engagement with BSS into a holistic research framework to predict the continuance consumption intention of BSS.

Consumers’ behavioural responses are driven by their psychological states (Buxbaum, 2016). In other words, consumer’s cognitive and emotional states lead to certain behavioural outcomes (Donovan & Rossiter, 1982). Similarly, Jacoby (2002) asserts that internal psychological processes can influence consumer actions. The current study follows Piligrimienė et al.’s (2020) approach in adopting consumer engagement as a psychological, motivational state which can influence consumers to buy green products.

Vivek et al. (2012) argue that internal consumer states such as involvement can influence consumer engagement facets of conscious attention, enthused participation, and social connection. Following the ideas of the TAM, the current study adopts perceived usefulness and perceived ease of use as internal states that may influence consumer engagement with BSS. Perceived usefulness refers to the degree to which a consumer believes that using a specific system or technology will enhance the performance of a particular activity (Davis, 1989). Attitude towards objects can be fostered through the perceived usefulness of objects (Lee, Cheung, & Chen, 2005). This notion is also supported by Yu et al. (2018), who found that perceived usefulness influences consumers’ evaluations of BSS. Similarly, Park, Kim, and Kim (2014) showed that perceived usefulness leads to consumer engagement by enhancing the acceptance of the smart grid system. McLean (2018) used TAM and outlined the continued importance of the perceived usefulness of the technology in enhancing consumer engagement with a retailer’s mobile application. Piligrimienė et al. (2020) also discovered that internal factors such as consumer perceptions impact consumer engagement in sustainable consumption. Thus, it can be hypothesised that:

H1: Perceived usefulness of BSS will have a positive impact on the conscious attention facet of consumer engagement.

H2: Perceived usefulness of BSS will have a positive impact on the enthused participation facet of consumer engagement.

H3: Perceived usefulness of BSS will have a positive impact on the social connection facet of consumer engagement.

Perceived ease of use is another psychological state that influences consumers’ behaviours in accepting BSS (Yu et al., 2018). Perceived ease of use is the extent to which consumers believe that utilising the technology could be effortless (Davis, 1989). Extant literature on technology adoption indicates that perceived ease of use positively affects consumer attitude towards technology (Hsu & Lin, 2008; Jin, Chai, & Tan, 2012). The current generation of BSS requires less mental efforts to unlock and pay for BSS usage, thus more likely to generate a positive attitude towards BSS (Yu et al., 2018). The ease of use of a product relies on its ability to perform tasks smoothly, increased productivity, efficiency, and performance, which profoundly influence consumer’s reaction towards the product (Rose, Clark, Samouel, & Hair, 2012). Previous research suggests that the perceived ease of use of a mobile application influences customer’s experience (McLean & Wilson, 2016), which is an important element of consumer engagement (Calder, Malthouse, & Schaedel, 2009). In a similar vein, McLean (2018) showed a significant effect of perceived ease of use on consumer engagement with a retailer’s m-commerce app. Thus, it can be postulated that:

H4: Perceived ease of use of BSS will have a positive impact on the conscious attention facet of consumer engagement.

H5: Perceived ease of use of BSS will have a positive impact on the enthused participation facet of consumer engagement.

H6: Perceived ease of use of BSS will have a positive impact on the social connection facet of consumer engagement.

Consumer engagement with BSS represents the internal state of mind which is motivational in nature (Brodie et al., 2011). According to Vivek et al. (2012), consumer engagement facets such as conscious attention, enthused participation, and social connection lead to value, trust, affective commitment, word of mouth, loyalty, and brand community involvement. Similarly, Hollebeek (2011) asserts that consumer engagement enhances consumer loyalty, trust, commitment, satisfaction, connection, empowerment, emotional bonding, etc. This notion is also supported by Piligrimienė et al. (2020), who showed that consumer engagement in sustainable consumption results in the acquisition of green products. In the same vein, Joshi and Rahman (2017) suggested that engagement in sustainable behaviour results in responsible actions and the desire to be part of the change process. Consequently, it can be hypothesised that:

H7: The conscious attention facet of consumer engagement with BSS has a positive impact on the continuance intention of BSS.

H8: The enthused participation facet of consumer engagement with BSS has a positive impact on the continuance intention of BSS.

H9: The social connection facet of consumer engagement with BSS has a positive impact on the continuance intention of BSS.

Based on the theoretical background, a conceptual model is developed, indicating the expected relationships among different constructs in Fig. 1.

The present study adopted a quantitative research design in which a survey was undertaken to collect data from the potential respondents through a questionnaire, which further helped examine the outcome of proposed hypotheses by employing statistical procedures. Data were collected in Kuala Lumpur, Malaysia, from current users of oBike. oBike is a public BSS run by a private firm headquartered in Singapore since 2017, the purpose of which is to assist urban commuters in short distance travel through bicycles. To obtain valid responses, the researchers ensured the recruitment of only those respondents who had experienced the BSS. To determine the minimum sample size required, an a priori type of power analysis using G*Power 3.1 software (Faul, Erdfelder, Buchner, & Lang, 2009) was undertaken with the following parameters: effect size f² =0.15 (medium), α = 0.05, power value = 95%, and predictors = 2, and the sample size rendered was 107. Consequently, data were collected from 207 individuals. However, 17 responses were discarded due to straight lining and incompleteness, rendering the final sample of 190 valid responses, which exceeded the requirements of power.

The survey questionnaire was designed by adapting the measuring scales from the existing sources, whereas content validity was ensured by the experts, whose suggestions were accordingly incorporated and helped in removing the ambiguity for the respondents (Waqas, Ali, & Khan, 2014). The questions were measured on a 5-point Likert scale and were addressed to the users of oBike. The details of the sources of the measuring items are summarised in Table 1.

Table 1 Sources of the measuring items

Constructs	No. of Items	Source
Perceived Ease of Use (PEOU)	3	Davis (1989); Davis, Bagozzi, and Warshaw (1989); Venkatesh and Davis (1996, 2000)
Perceived Usefulness (PU)	3	Davis (1989); Davis et al. (1989); Venkatesh and Davis (1996, 2000)
Conscious Attention (CA)	3	Vivek et al. (2014)
Enthused Participation (EP)	4	Vivek et al. (2014)
Social Connection (SC)	3	Vivek et al. (2014)
Continuance Intention (CI)	4	Davis (1989); Davis et al. (1989); Venkatesh and Davis (1996, 2000)

Prior to ample data collection, it is important to reduce the Common Method Variance (CMV), which leads to biased results if not properly addressed. Podsakoff, MacKenzie, and Podsakoff (2012) proposed certain procedural and statistical remedies for controlling the CMV. Based on the suggestions, procedural remedies were used at the time of developing and designing the questionnaire. These include 1) improving the language of the statements of the measuring items so that they are easy to comprehend, which decreases the ambiguity that a respondent feels while answering survey questions, 2) incorporating a temporal gap among the questions so that it helps the respondents to have a little break which will decrease the level of stress. For the statistical remedy, Harman (1976) single factor test was applied in which the total variation explanation of the construct while applying factor analysis was found to be 68.072% based on the Eigenvalue greater than 1, whereas the first factor explains only 27.282%, which eliminates the evidence of the presence of CMV. In addition to this, Najmi and Ahmed (2018) assert that the values of the inter-construct correlation exceeding 0.9 also indicate the presence of CMV, which is also not found in the present study (See inter-construct correlation values in Table 4). Thus, after confirming the absence of CMV, further statistical analyses were applied to the data of 190 respondents, the demographic profile of whom are summarised in Table 2.

Table 2 Demographic profile of the respondents (N = 190)

		Frequency	Percent
Gender	Male	87	45.8
Gender	Female	103	54.2
Age (In Years)	18–24	125	65.8
	25–34	49	25.8
	35–44	14	7.4
	More than 45	2	1.1
Education	Bachelors	126	66.3
	Masters	38	20.0
	Doctorate	26	13.7
Ethnic Group	Malay	93	48.9
	Chinese	49	25.8
	Indian	12	6.3
	Others	36	18.9
Main Travel Mode	Walking	53	27.9
	Private Bicycle	3	1.6
	Motorcycle	15	7.9
	Car	47	24.7
	Bus	44	23.2
	Metro Rail Transit	20	10.5
	Others	8	4.2

The present study employs the Partial Least Square-Structural Equation Modelling (PLS-SEM) technique, a variance-based technique capable of predicting the hypothesised relationships from the data more robustly than the conventional SEM (Hair, Hult, Ringle, & Sarstedt, 2016). In addition, PLS-SEM works well with small sample sizes by computing measurement and structural model relationships separately instead of simultaneously (Hair, Risher, Sarstedt, & Ringle, 2019). Based on the recommendations by Hair et al. (2016), the PLS-SEM is applied in a two-stepped approach, including assessing measurement model and structural model.

5.1 Measurement model

In the measurement model, the outer model is assessed, including the evaluation of convergent validity and discriminant validity.

5.1.1 Convergent validity

Convergent validity is ensured when the measuring items of a construct show a level of relatedness, forcing them to make a construct (Waqas, 2021). For that, Hair et al. (2016) suggested the threshold value of greater than 0.7 for factor loadings and composite reliability, whereas, for average variance extracted (AVE), the threshold value is greater than 0.5. The results reported to meet all of the aforementioned criteria and summarised in Table 3.

Table 3 Convergent validity

Factors	Items	Loadings	Composite Reliability	Average Variance Extracted (AVE)
Conscious Attention (CA)	CA1	0.829	0.896	0.741
	CA2	0.892
	CA3	0.862
Continuance Intention (CI)	CI1	0.901	0.941	0.801
	CI2	0.873
	CI3	0.873
	CI4	0.931
Enthused Participation (EP)	EP1	0.814	0.927	0.761
	EP2	0.893
	EP3	0.915
	EP4	0.864
Perceived Ease of Use (PEOU)	PEOU1	0.896	0.855	0.664
	PEOU2	0.773
	PEOU3	0.768
Perceived Usefulness (PU)	PU1	0.832	0.839	0.637
	PU2	0.677
	PU3	0.871
Social Connection (SC)	SC1	0.886	0.913	0.778
	SC2	0.903
	SC3	0.856

5.1.2 Discriminant validity

Discriminant validity is ensured when the measuring items of a construct show a level of distinguishability with the measuring items of another construct and force them to make a respective construct (Waqas, 2021). In this study, it has been assessed by two measures. Firstly, the Fornell and Larcker (1981) according to which the square root of AVE should be exceeding from the values of inter-construct correlations. The results reported to meet the Fornell-Larcker Criterion and summarised in Table 4.

Table 4 Fornell-Larcker criterion

	CA	CI	EP	PEOU	PU	SC
CA	*0.861*
CI	0.668	*0.895*
EP	0.709	0.687	*0.872*
PEOU	0.265	0.449	0.352	*0.815*
PU	0.499	0.575	0.477	0.287	*0.798*
SC	0.535	0.593	0.556	0.380	0.365	*0.882*

Note: the diagonal bold and italic values represent square root of AVE and off-diagonal values represents inter-construct correlations; CA: Conscious attention; CI: Continuance intention; EP: Enthused participation; PEOU: Perceived Ease of Use; PU: Perceived usefulness; SC: Social connection

The second measure to assess the discriminant validity is the Heterotrait-Monotrait Ratio (HTMT) which is comparatively a newly proposed criterion by Henseler, Ringle, and Sarstedt (2015). The threshold value of HTMT is less than 0.85, which in the present study is met, thus confirming the discriminant validity. The results are summarised in Table 5.

Table 5 Heterotrait-Monotrait Ratio (HTMT)

	CA	CI	EP	PEOU	PU	SC
CA
CI	0.763
EP	0.830	0.752
PEOU	0.328	0.532	0.424
PU	0.623	0.686	0.560	0.366
SC	0.627	0.658	0.622	0.448	0.459

Note: CA: Conscious attention; CI: Continuance intention; EP: Enthused participation; PEOU: Perceived Ease of Use; PU: Perceived usefulness; SC: Social connection

5.2 Structural model

This includes assessing the inner model in which the predictive relevancy of the model and hypothesis testing are assessed.

5.2.1 Predictive relevancy

This shows the overall ability of the model to predict and estimate the dependent variable. The higher level of prediction relevancy indicates a higher level of quality that a model possesses. The predictive relevancy and accuracy are assessed by the coefficient of determination R² and cross-validated redundancy Q². For R² the value close to 0.26 is considered strong (Cohen, 1988), whereas, for Q², the value should be above 0 (Hair et al., 2016). The results summarised in Table 6 show the quality, predictive accuracy and relevancy of the structural model.

Table 6 Predictive power of the construct

	R-Square	Q-Square
CA	0.265	0.180
CI	0.577	0.427
EP	0.278	0.196
SC	0.216	0.148

Note: CA: Conscious attention; CI: Continuance intention; EP: Enthused participation; SC: Social connection

5.2.2 Hypothesis testing

Based on the hypothesised relationships, perceived usefulness was found to be the highest predictor of conscious attention (β=0.460, p < 0.01) followed by the enthused participation (β=0.410, p < 0.01), and the social connection (β=0.282, p < 0.01). Considering perceived ease of use, it was found to be the highest predictor of the social connection (β=0.304, p < 0.01), followed by the enthused participation (β=0.237, p < 0.01) and the conscious attention (β=0.136, p < 0.05). On the other hand, while predicting the conscious attention, the enthused participation was found to be the highest predictor (β=0.345, p < 0.01) followed by the conscious attention (β=0.293, p < 0.01) and lastly, the social connection (β=0.244, p < 0.01). All of the hypotheses were found statistically significant and positive in nature. The results are summarised in Table 7.

Table 7 Hypothesis testing

No.	Hypotheses	Path Coefficients	Standard Deviation	T Statistics	P Values	Remarks
H1	PU → CA	0.460	0.057	8.133	0.000	Supported
H2	PU → EP	0.410	0.060	6.789	0.000	Supported
H3	PU → SC	0.282	0.068	4.111	0.000	Supported
H4	PEOU → CA	0.136	0.064	2.088	0.037	Supported
H5	PEOU → EP	0.237	0.065	3.601	0.000	Supported
H6	PEOU → SC	0.304	0.066	4.535	0.000	Supported
H7	CA → CI	0.293	0.077	3.838	0.000	Supported
H8	EP → CI	0.345	0.078	4.371	0.000	Supported
H9	SC → CI	0.244	0.069	3.524	0.000	Supported

Note: CA: Conscious attention; CI: Continuance intention; EP: Enthused participation; PEOU: Perceived ease of use; PU: Perceived usefulness; SC: Social connection

This study sets out to assess the drivers of consumer engagement with BSS and outcome in the form of the continuance intention of consuming BSS. While there is a large volume of published studies describing the role of consumer engagement in the consumption of commercial products, engagement with BSS lacks empirical and conceptual background. On the other hand, finding drivers of consumer engagement with BSS also represents the research direction in the area of sustainable transportation. Thus, this study contributes both to the development of theory in consumer engagement and consumption of sustainable transportation.

The initial objective of this study was to identify the drivers of consumer engagement with BSS. Very little was found in the literature on factors that can enhance consumer engagement with BSS. With the help of TAM, it is proposed that perceived usefulness of BSS and perceived ease of use of BSS predict consumer engagement with BSS. This study indicates that perceived usefulness and perceived ease of use enhance all facets of consumer engagement with BSS. It is encouraging to compare this result with that found by Park et al. (2014), who showed that perceived usefulness and perceived ease of use of high-tech products increase consumer engagement with such products. This finding also corroborates the ideas of Cheng, OuYang, and Liu (2019), who suggested that perceived usefulness and perceived ease of use of BSS are positively correlated with the attitude towards BSS. More specifically, the perceived usefulness of BSS showed a larger impact on conscious attention, enthused participation, and social connection than perceived ease of use of BSS. This implies that perceived usefulness of BSS plays a more important role in enhancing engagement with BSS by increasing the consumers’ interest in interacting with BSS, evoking strong feelings related to interacting with BSS, and increasing social interaction with other BSS users (Vivek et al., 2014). It is important to bear in mind that the finding does not suggest that perceived ease of use of BSS does not influence conscious attention, enthused participation, and social connection. The difference between perceived usefulness and perceived ease of use of BSS lies in the strength of the relationship of these constructs with facets of consumer engagement.

There are several possible explanations for this result. To illustrate, people are more inclined to consume green products as long as they are trustworthy regarding their environmental usefulness (Wells, Valacich, & Hess, 2011). Specifically, this consumption behaviour is due to consumers’ belief that using BSS would improve environmental performance and life (Passafaro et al., 2014). Similarly, Chen (2016) asserts that the perceived usefulness of BSS related to health and the environment can enhance consumer loyalty with BSS. Furthermore, Chen and Lu (2016) also argue that users and non-users of BSS care about and more conscious about the usefulness of the BSS compared to ease of use of BSS due to their concerns for the environmental usefulness. Thus, it can be concluded that both perceived usefulness and perceived ease of use of BSS can enhance engagement with BSS; however, reinforcing the usefulness of BSS for the environment and personal commute can play a more significant role in augmenting consumer engagement with BSS.

On the question of the effect of consumer engagement on the continuance intention, this study found that all facets of consumer engagement with BSS affect the continuance intention of BSS. This finding is consistent with that of Fang (2017), who showed that consumer engagement is an important factor affecting consumers’ continuance intentions. This result also agrees with the findings of Vivek et al. (2012), which suggest that consumer engagement leads to long term commitment to the brand. The current findings suggest that consumers’ interest in interacting with BSS, strong feelings towards interaction with BSS, and social interaction with other BSS users predict consumers’ continuance usage intention of BSS. The observed effect of consumer engagement facets on the continuance intention could be attributed to higher benefits resulting from engagement with BSS (Bendapudi & Berry, 1997). Another possible explanation for this is that the experience of engagement encourages consumers to persist and return to the usage of the product due to the experiential rewards it provides (Monahan, McArdle, & Bertolotto, 2008). Therefore, it seems that consumer engagement with BSS will lead to intention to keep using BSS.

6.1. Implications and limitations

6.1.1. Theoretical implications

The theoretical contribution of this study is on the enhancement of understanding of drivers and the outcome of consumer engagement with BSS. So far, no study has examined BSS engagement as a psychological state resting on facets, including conscious attention, enthused participation, and social connection. Specifically, this study provides a framework for better understanding and analysing the effect of perceived usefulness and perceived ease of use of BSS in enhancing consumer engagement with BSS, which further leads to continuance usage intention of BSS. This framework integrates both external stimuli (usefulness and ease of use) and internal stimulus (consumer engagement) in predicting the usage intention of BSS. As such, this study adds to the application of the TAM by suggesting that perceived usefulness and ease of use could be promising exogenous variables for the internal state of the consumer, i.e., consumer engagement as an outcome.

This study also answers the call for boundary-breaking marketing-relevant research (MacInnis et al., 2020) in several ways. First, this study is motivated by real-world issue rather than theories, constructs, or conceptual frameworks in marketing. This study’s finding that persistent usage intention of BSS depends on consumer engagement with BSS not only engages academics in the discipline of marketing but also offers implications to the extant literature in other disciplines such as transportation research. Second, BSS is an understudied product category in the context of consumer engagement. To the best of researchers’ knowledge, no existing study investigated drivers and outcomes of consumer engagement with BSS. Third, this research enriches the technology acceptance and adoption literature by providing empirical support for the better explanatory power of integrating the TAM with consumer engagement theory in the context of BSS.

6.1.2. Managerial implications

This study has important implications for BSS providers by offering guidelines for improving consumer engagement and continuance usage intention of BSS. The findings suggest that respondents show high engagement with BSS if they perceive BSS as useful and easy to use. BSS providers can benefit from these results by highlighting the usefulness of BSS to the environment and consumers. Specifically, the benefits of BSS as a green mode of transportation, flawless functionality and a healthy alternative to automobiles can be communicated. Similarly, perceived ease of use of BSS can be amplified by highlighting the user-friendly features of BSS such as online payment of bills, improved distribution, pedal-assistance, tracking, and comfortable riding experience. Moreover, BSS providers could provide more types of bikes and payment options to enhance the perceived ease of use of BSS. This will eventually enhance consumer engagement with BSS.

The findings imply that BSS provider should enhance consumer engagement with BSS regarding consumers’ interest in interacting with BSS, feelings related to interacting with BSS, and social interaction with other BSS users. In this way, the BSS service provider can enhance the continuance usage intention of BSS. The results suggest that BSS provider should promote conscious attention where consumers yearn for using BSS. Similarly, they should drive enthused participation where consumers’ feelings towards BSS are evoked. Finally, BSS providers should provide platforms for consumers to interact with other BSS users. This can be done by building a consumption community around BSS usage.

6.2. Limitations and future research directions

As this research is one of the initial attempts to use consumer engagement as a driver of the continuance intention of BSS, it can be considered exploratory in nature. Thus, this research has some limitations, which show the possible avenues for future research. Data were collected from the population of one Asian country, i.e., Malaysia; the results might differ for other countries due to variation in the cultural context. Additionally, the sample was driven from younger people only, limiting the generalisability of the findings to other age groups. Future research can further explore the current framework using respondents from different geographic areas and demographic groups.

This study used two factors from the TAM that influence consumer engagement with BSS. Future research might use other factors to predict consumer engagement with BSS. Factors such as customer experience with BSS, customer personality factors, and customer involvement in BSS can be potential drivers of consumer engagement with BSS. Finally, the current study took the continuance intention of BSS as a result of consumer engagement with BSS. Consumer engagement can result in a variety of possible outcomes which present possible avenues for future research.

Finally, there is some scepticism among scholars regarding theoretical accuracy and application of the TAM (Jamšek & Culiberg, 2020). Additionally, the model has been criticised for its application due to the issue of constant and rapid changes in technology (Venkatesh, Morris, Davis, & Davis, 2003). Future research may use the Theory of Reasoned Action (TRA) or the Unified Theory of Acceptance and Use of Technology (UTAUT) to identify the most important determinants of behavioural intention and actual use of BSS.

Ethical Approval:

Researchers have adhered to ethical standards while doing this research study.

Consent to Participate:

Consent was obtained from the participants prior to data collection.

Consent to Publish:

Consent was obtained from the participants prior to data collection, whereas no respondent was individually identified in this study.

Authors Contributions:

MW: Conceptualization, Literature review, Data collection, write-up, editing, reviewing. AN: Conceptualization, Data collection, data analysis, write-up, editing, reviewing. All the authors read and approved the final manuscript.

Funding:

This research study did not receive any funding.

Competing Interests:

The authors declare that they have no conflict of interest.

Availability of data and materials:

All the data analysis results and tools/models used in this study are included in this article.

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Enhancing Consumption of Sustainable Transportation: Determinants and Outcome of Consumer Engagement with Bike-Sharing Service

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Highlights

1. Introduction

2. Theoretical Background

2.1. Consumption of bike-sharing service

2.2. Consumer engagement with bike-sharing service

2.3. Determinants of Consumer Engagement with bike-sharing service

3. Hypotheses Development And Conceptual Framework

4. Methodology

5. Statistical Analysis And Results

6. Discussion

6.1. Implications and limitations

6.1.1. Theoretical implications

6.1.2. Managerial implications

6.2. Limitations and future research directions

Declarations

References

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