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Analysing user well-being in ridehailing services

Shaikh, Aijaz A.,Liebana-Cabanillas, Francisco,Alharthi, Majed,Alamoudi, Hawazen,Karjaluoto, Heikki

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This is a self-archived version of an original article. This version may differ from the original in pagination and typographic details. Author(s): Title: Year: Version: Copyright: Rights: Rights url: Please cite the original version: CC BY 4.0 https://creativecommons.org/licenses/by/4.0/ Analysing user well-being in ridehailing services © Aijaz A. Shaikh, Francisco Liebana-Cabanillas, Majed Alharthi, Hawazen Alamoudi and Heikki Karjaluoto. Published in Spanish Journal of Marketing - ESIC. Published by Emerald Publishing Limited Published version Shaikh, Aijaz A.; Liebana-Cabanillas, Francisco; Alharthi, Majed; Alamoudi, Hawazen; Karjaluoto, Heikki Shaikh, A. A., Liebana-Cabanillas, F., Alharthi, M., Alamoudi, H., & Karjaluoto, H. (2024). Analysing user well-being in ridehailing services. Spanish Journal of Marketing, 28(2), 207-227. https://doi.org/10.1108/sjme-12-2022-0253 2024 Analysing user well-being in ridehailing services Aijaz A. Shaikh University of Jyväskylä, Jyväskylä, Finland Francisco Liebana-Cabanillas University of Granada, Granada, Spain Majed Alharthi and Hawazen Alamoudi King Abdulaziz University, Rabigh, Saudi Arabia, and Heikki Karjaluoto University of Jyväskylä, Jyväskylä, Finland Abstract Purpose –Although the sharing economy improves comfort and convenience, it is yet unclear how it affects subjective well-being. This study aims to offer a conceptual model for understanding the linkages between the antecedents and consequences of subjective well-being in ridehailing services. Design/methodology/approach –Using a non-probabilistic sampling method and a pre-tested survey instrument, 450 responses were collected from January to March 2020. The data were analysed using structural equation modelling. Findings –Experience quality and perceived convenience are correlated with subjective well-being. Perceived value and personal innovativeness were not correlated with subjective well-being, as the former does not contribute to the latter’s development. Continuous usage intention significantly correlated with subjective well-being, followed by customer relationship proneness and advocacy. Regarding gender and age differences, men place higher value on customer relationship proneness than women, while women place higher value on subjective well-being than men. Older users value perceived convenience and customer relationship proneness in ridehailing services more than younger users. Practical implications –Understanding key factors contributing to user well-being in ridehailing would promote a more affordable mobility sector globally. This understanding would enable ridehailing businesses to create more effective business and marketing plans while prioritising user well-being, thus enhancing user happiness and reducing turnover rates. Originality/value –This research demonstrates how crucial it is for users’well-being to have a positive experience and find the service convenient. It also highlights the importance of building strong customer relationships and examines how gender and age influence people’s adoption and use of these services. Keywords Ridehailing services, Subjective well-being, Customer relationship proneness, Usage intention Paper type Research paper © Aijaz A. Shaikh, Francisco Liebana-Cabanillas, Majed Alharthi, Hawazen Alamoudi and Heikki Karjaluoto. Published in Spanish Journal of Marketing - ESIC. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http:// creativecommons.org/licences/by/4.0/legalcode Ridehailing services Received 17 December 2022 Accepted 20 September 2023 Spanish Journal of Marketing - ESIC Emerald Publishing Limited e-ISSN: 2444-9709 p-ISSN: 2444-9709 DOI 10.1108/SJME-12-2022-0253 The current issue and full text archive of this journal is available on Emerald Insight at: https://www.emerald.com/insight/2444-9709.htm An alisis del bienestar del usuario en los servicios de transporte compartido Resumen Prop osito –Aunque la economía colaborativa mejora la comodidad y conveniencia, aún no est aclaro c omo afecta al bienestar subjetivo. Ofrecemos un modelo conceptual para comprender las conexiones entre los antecedentes y consecuencias del bienestar subjetivo en los servicios de transporte compartido. Diseño/metodología/enfoque –Utilizando un m etodo de muestreo no probabilístico y un instrumento de encuesta previamente probado, se recopilaron 450 respuestas entre enero y marzo de 2020. Los datos fueron analizados utilizando un modelo de ecuaciones estructurales. Hallazgos –La calidad de la experiencia y la percepci on de conveniencia est an correlacionadas con el bienestar subjetivo. El valor percibido y la innovaci on personal no se correlacionaron con el bienestar subjetivo, ya que el primero no contribuye al desarrollo del último. La intenci on de uso continuo se correlacion o significativamente con el bienestar subjetivo, seguida por la propensi on a las relaciones con los clientes y la defensa de estos servicios. En cuanto a las diferencias de g enero y edad, los hombres valoran m as la propensi on a las relaciones con los clientes que las mujeres, mientras que las mujeres valoran m as el bienestar subjetivo que los hombres. Los usuarios mayores valoran m as la percepci on de conveniencia y la propensi on a las relaciones con los clientes en los servicios de transporte compartido que los usuarios m as j ovenes. Originalidad –Esta investigaci on demuestra lo crucial que es para el bienestar de los usuarios tener una experiencia positiva y encontrar el servicio conveniente. Tambi en resalta la importancia de construir relaciones s olidas con los clientes y examina c omo el g enero y la edad influyen en la adopci on y uso de estos servicios. Implicaciones pr acticas –Comprender los factores clave que contribuyen al bienestar de los usuarios en los servicios de transporte compartido promovería un sector de movilidad m as asequible a nivel global. Esta comprensi on permitiría a las empresas de transporte compartido crear planes de negocios y marketing m as efectivos, priorizando el bienestar de los usuarios y mejorando así su felicidad y reduciendo las tasas de rotaci on. Palabras clave Servicios de transporte compartido, Bienestar subjetivo, Propensi onalarelaci  on con el cliente, Intenci on de uso Tipo de artículo Trabajo de investigaci on 分析乘车服务中的用户福祉 摘要 目的 –尽管共享经济提高了舒适度和便利性,但它如何影响主观幸福感尚不清楚。我们提供了一个 概念模型,用于理解乘车服务中主观幸福感的前因后果之间的联系。 设计/方法/途径–采用非概率抽样方法和预先测试的调查工具,在2020 年1月至3月期间收集了450 份回复。数据采用结构方程模型进行分析。 研究结果–体验质量和感知便利性与主观幸福感相关。感知价值和个人创新性与主观幸福感不相 关,因为前者无助于后者的发展。持续使用意愿与主观幸福感密切相关,其次是客户关系倾向和拥 护。在性别和年龄差异方面,男性比女性更重视客户关系倾向,而女性比男性更重视主观幸福感。老 年用户比年轻用户更重视乘车服务中的便利感和客户关系代言。 独创性–这项研究表明,用户获得积极的体验和便捷的服务对他们的福祉至关重要。研究还强调了 建立牢固的客户关系的重要性,并探讨了性别和年龄如何影响人们采用和使用这些服务。 实际意义–了解有助于提高乘车旅行用户幸福感的关键因素,将在全球范围内推动建立一个更加经 济实惠的移动出行行业。这种理解将使打车企业能够制定更有效的业务和营销计划,同时优先考虑用 户福祉,从而提高用户幸福感并降低流失率。 关键词打车服务,主观幸福感,客户关系倾向,使用意向, 文章类型研究型论文 1. Introduction The sharing economy idea was initially put forth in 1978 (Felson and Spaeth, 1978). Nonetheless, the phenomenon of sharing or collaborative economy started appearing in the mainstream SJME research since early 1980s and several empirical studies were contributed to the area of sharing, collaborative consumption, the mesh, commercial sharing systems, co-production, co-creation, presumption, product-service systems, access-based consumption and consumer participation (Alharthi et al., 2021). The contemporary research (cf. Prieto et al.,2022), has defined ridehailing service as peer-to-peer platforms, which consists of a triangle of actors: a service provider, a service enabler and a customer. In practice, the ridehailing services do not hire any person or staff to provide mobility services. Instead, it allows the registered and qualified drivers (also called captains) to deliver services at their convenience and when they are willing to serve. Unlike the traditional business models where the employer decides work responsibilities, schedule and salary, the “sharing”business models allow the registered drivers to decide when and how much to work independently. Recently, the concept of subjective well-being has received considerable attention in marketing and consumer behaviour research (Shaikh et al., 2023), which seeks to understand how interacting with others either enhances or undermines one’s self-outlook, quality of life and satisfaction (Wang et al., 2023). Except a few studies (Alharthi et al.,2021;Ma et al., 2018) that have examined the relationship between the sharing services and subjective wellbeing, not much has been reported. Nonetheless, synthesising the prior literature on subjective well-being provided a holistic overview of the term “subjective well-being”such as well-being is a subjective evaluation of the degree of someone’s own happiness that also consider meaningfulness, positive emotions, engagement and global judgements of life satisfaction (Alharthi et al., 2021;Davlembayeva et al., 2020). Despite the sharing economy’s significance, popularity and market share growth projections, mainstream research on it is still in its fledglingstageandhasnotyetpeaked( Alharthi et al., 2021;Hamari et al.,2015). The literature examining the connections between sharing economy platforms and subjective well-being (or happiness/satisfaction/quality of life) remains scarce (Shaikh et al., 2019a). Over the past two decades, however, particularly since the advent of online businesses, digital platforms, mobile-based sharing services and social media, the concept of subjective well-being has gradually transformed, and the use of online and mobile-applicationsupported services have become a part of everyday life. While the advent of the sharing economy has made comfort and convenience more accessible (Shaikh et al., 2019a), it is not clear whether it has enhanced users’subjective well-being. Nonetheless, the well-being research could help to better understand the relationship between the ridehailing users and their mental health. These deficiencies and assumptions led us to conclude that understanding user well-being in ridehailing services is an important area of research. This study has two major objectives. Firstly, we contribute to the subjective well-being theory in the context of ridehailing services. Secondly, we examined the key antecedents and consequences of ride-hail user subjective well-being. For that matter, we identify the variables from the contemporary research (cf. Alamoudi et al., 2023;Wang et al., 2023; Shaikh et al., 2019a) and examine their relationships with the predicted variable of subjective well-being. Consequently, our research makes significant contributions to two streams of literature: research related to subjective well-being and research on the sharing economy. We have proposed following three research questions: RQ1. What key variables contribute to the overall well-being of ridehail users? RQ2. How does ridehail users’increased well-being affect intention to use the service, develop better customer relationships and recommend it? RQ3. How do a ridehail user’s demographic traits, specifically gender and age, impact the relationships between the key variables? Ridehailing services Our study would increase the knowledge of the elements that affect the subjective wellbeing of ridehailing users. Moreover, our research would offer crucial industry insights for ridehailing companies. Ridehailing companies should create business and marketing plans to increase user satisfaction and happiness and lower turnover by knowing the variables that affect users’subjective well-being. Although ridehailing services consider three major players –ridehail driver, ridehail user and platforms such as Uber and Lyft (Cha and Lee, 2021)–we have concentrated on the antecedents and consequences of ridehail user well-being. Also, we have used the term “ridehailing”,whichis considered different from “ridesharing services”. Recently, Pigalle and Aguil era (2023) explained that ridesharing refers to shared automobile (such as car or van) journeys between people with comparable origin–destination pairings. Here, the profitisnottheultimatemottointhe ridesharing services and the popular example include BlaBla. On the other side, ridehailing firms use smartphone applications to connect drivers and passengers at a profit such as Uber. The rest of this paper is organised as follows. In Section 2, we provide the theoretical background. Conceptual model and hypothesis development are described in Section 3. The research method is presented and explained in Section 4. The results are presented in Section 5. Lastly, we conclude the paper with a discussion of the implications, limitations and future research directions in Section 6. 2. Literature review 2.1 Sharing economy –a non-ownership phenomenon The term “sharing economy”, also referred to as “peer-to-peer economy”,“collaborative consumption/economy”,“platform economy”,“gig economy”and “lateral exchange market” (Rojanakit et al.,2022), was introduced by Lessig (2008). Sharing economy is defined as collaborative consumption made by the activities of sharing, exchanging and rental of resources without owning the goods (Lee et al., 2000, p. 1). Research (cf. Tunçel and Özkan Tektas,2020) has related the sharing economy with collaborative consumption and peer-to-peer markets. Here, sharing economy is considered an economic model that is based on traditional sharing, bartering, lending, trading, renting, gifting and swapping, but redefined through new digital technologies and peer communities. Other recent studies (Wei et al.,2020) stated that the sharing economy relies on the users’willingness to share or use other people’s resources rather than own resources themselves, and that for such an exchange to be carried out, the users have to be trustworthy. Deloitte (2017) has classified carsharing into three major domains: free-floating, stationary and peer-to-peer. Free-floating facilitates microand macro-mobility and is considered the most flexible and convenient mobility concept introduced a few years ago in the global north. Popular free-floating examples include Tier, Bolt Helbiz and Lime. Free-floating allows the users to pickup and return the vehicles or e-scooters at any place within the specified demographic location or area without any fixed stations. Using the mobile application, the free-floating is accessed and used for a short one-way trip, and the user is charged according to the time spend. On the other hand, stationary or station-based car-sharing allows round trips with the start and end point being the same. For example, Flinkster in Germany. The stationary mobility concept is less flexible and can be used for long distances. The peer-to-peer mobility concepts –the context of this study –is on the rise and will soon become mainstream equally in the developed and developing regions of the world. While the service provider arranges the cars and scooters for free-floating and stationary car sharing, peer-to-peer carsharing (or P2P car sharing) is a macromobility concept. Here vehicle belongs to a private individual and is identified and coordinated by a third-party company such as Uber (Barbour et al., 2020). SJME 2.2 Subjective well-being theory, antecedents and consequences According to Davlembayeva et al. (2020,p.5),theterm“well-being”is conceptualised as subjective well-being as it mirrors the subjective definition of the standard of living and subjective evaluation of the degree of someone’s own happiness and satisfaction. Loureiro et al. (2019) have defined consumer or subjective well-being as consumers’perception of the extent to which a brand positively contributes to a quality-of-life enhancement. Positive impressions of a service such as ridehailing or brand may lead to an increase in consumers’well-being, which refers to an evaluation of one’s own life experiences consisting of happiness and life satisfaction (Loureiro et al.,2019). From the contemporary literature, various antecedents and consequences of subjective well-being were identified and examined from the users’perspective. As subjective well-being represents the “quality of life”and has various philosophical and theoretical sources based on theories of hedonism and authentic happiness (Liang et al.,2020), we selected and included the antecedents into the theoretical model (Figure 1) that promote the end user wellbeing in a developed country context such as perceived value, personal innovativeness and perceived convenience. Furthermore, considering the significanceofuserwelfareandqualityof life in promoting subjective well-being, the variable “experience quality”(and not the service quality) was added to our model examining its relationship with the subjective well-being. Research (Molinillo et al., 2020) has described experiences in terms of the thoughts and feelings that consumers have about what is happening when they are doing something. Experience quality or quality of experience is defined as the collection of subjective and objective human needs and experiences arising from the interaction of a person or customer with a specific technology, brand, service, system or business entity in a particular context (Laghari et al., 2020;Laghari and Connelly, 2012). The evaluation of experience quality tends to be holistic and affective rather than attribute based or cognitive, as in the case of service quality (Laghari et al., 2020). The consumers’concern for receiving more value for less and the service providers’ concern for providing greater value for less have always been the core of product and service development and deployment, increased consumer acceptance and sustained customer usage of the technology or service. Research (Zeithaml, 1988) has considered Figure 1. Illustration of hypotheses Experience Quality Perceived Value Personal Innovativeness Utilitarian Perceived Convenience Subjective Well-being Customer Advocacy Customer Relationship Proneness Continuous Usage Intention Hedonic Social H1 (+) H2 (+) H3 (+) H4 (+) H5 (+) H6 (+) H7 (+) H8 (+) H9 (+) Moderator: Gender (H10); Age (H11) Ridehailing services customer perceived value as customer benefit derived from his/her monetary and nonmonetary payments, or sacrifice of risk, to the products and services offered by a company. Rogers (1995) has defined personal innovativeness as the degree to which a person tends to adopt new technologies, products or services earlier than others. The quality of being innovative usually asks for the desire to take a risk and look for ways of experimenting on new technologies or services when available. This means that an individual with personal innovativeness is deemed more confident when using new and innovative services such as ridehailing. Perceived convenience means how helpful a system, technology or application is in completing a certain task from the point of view of its users. Nonetheless, research (cf. Chang et al.,2012) has defined perceived convenience as a “level of convenience toward time, place, and execution that one feels during the participation in mobile learning”(p. 812). Motivating consumers to use a technology or service for a prolonged period is one of the core elements of companies’marketing and service innovation strategies. Bhattacherjee (2001), who introduced the information system continuance model, first identified the difference between the initial acceptance/adoption and post-adoption or continuous usage intention/behaviour and defined continuance usage intention as “an individual’s intention to continue using an information system”(p. 359). Customer relationship proneness represents a customer’s relatively stable, conscious tendency and increased likelihood of developing relationships with service providers, including retailers or brands (De Wulf et al., 2001). Relationship proneness is considered an evolution of relational constructs such as commitment (Olavarría-Jaraba et al.,2018) and a personality trait (Bloemer et al., 2003) that motivates the consumer to develop a personal relationship with a specific product or service (e.g. ridehailing). Customer advocacy has long been considered analogous to word of mouth and one of the important topics in the attitude literature (Bechler et al.,2020). Moreover, a number of studies (i.e. Wu and Chang, 2019) have defined advocacy as a willingness of a person to recommend a product, service or piece of information to others. 3. Conceptual model and hypotheses development We used a theoretical model (see Figure 1) to examine the antecedents and consequences of subjective well-being in an emerging sharing-economy field. 3.1 Experience quality on subjective well-being Prior research has examined the relationship between experience quality and ridehail user well-being as well as ridehail user happiness and satisfaction, which are considered very close to well-being. For example, Haji et al. (2021) discovered that the quality of the ridehailing experience significantly improved ridehail users’pleasure and well-being. Wu et al. (2017) found that experience quality has a significant effect on happiness. In the tourist industry context, Laghari and Connelly (2012) found that the skydiving experience has a lasting influence on a tourist’s well-being, happiness and life. Thus: H1. Experience quality is positively related to subjective well-being. 3.2 Perceived value on subjective well-being We intend to determine the extent to which the perceived value of sharing services influences ridehail user well-being. Silva et al. (2019) have found a positive relationship between these two variables. Specifically, in the context of bike-sharing services, Ma et al. (2018) found that perceived value (i.e. hedonic, utilitarian and social) has the greatest impact on subjective wellSJME being. Of the three perceived-value dimensions, hedonic value has the strongest effect on subjective well-being, followed by social and utilitarian value. Similarly, in a recently published article, Liu et al. (2023), found that three perceived-value dimensions (functional value, emotional value and social value) significantly affect hedonic and eudaimonic well-being. In the sharing economy context, according to Hamari et al. (2015), enjoyment and economic reward are important intrinsic and extrinsic motivators that determine users’intention to participate in the sharing economy. Thus, the hypothesis below was formulated. H2. Perceived value is positively related to subjective well-being. 3.3 Personal innovativeness on subjective well-being Individuals that are innovative are more likely to be early users of technology (Marikyan et al., 2023). The relationship between personal or individual innovativeness and user well-being or happiness is established. Here, Honkaniemi et al. (2015) found that the higher the innovativeness, the higher the well-being, and vice versa. Marikyan et al. (2023) reported a positive relationship between individual innovativeness and well-being. In view of this relationship between personal innovativeness and well-being, the hypothesis below was formulated: H3. Personal innovativeness is positively related to subjective well-being. 3.4 Perceived convenience on subjective well-being Perceived convenience or ease of use (Chang et al.,2012;Yoon and Kim, 2007) has been examined from various technology perspectives, and its role in increasing consumer wellbeing or quality of life has been established. El Hedhli et al. (2013) found that shopping mall convenience significantly and positively predicts shopping well-being. Xiao et al. (2023) found direct relationship between ease of use and well-being. The hypothesis below was thus formulated: H4. Perceived convenience is positively related to subjective well-being. 3.5 Subjective well-being on continuous usage intention Continuous usage intention differs from the technology or service acceptance, entails the actual behaviour of the consumer since the initial adoption of a technology, system, application or service does not guarantee its continuous usage (Shaikh et al., 2019b). The relationship between subjective well-being and continuous use of a product or service has gradually become more prominent in the literature of various technology-related areas. For example, Azzahro et al. (2018) found that subjective well-being has a significant positive influence on users’intention to continue using online dating applications. Thus, we hypothesised: H5. Subjective well-being is positively related to continuous usage intention. 3.6 Subjective well-being on customer relationship proneness and customer advocacy Relationship proneness is considered an evolution of relational constructs such as commitment (Olavarría-Jaraba et al., 2018) and a personality trait (Bloemer et al., 2003) that motivates the consumer to develop a personal relationship with a specific product or service (e.g. ridehailing) that does not change for a long time. Olavarría-Jaraba et al. (2018) argue Ridehailing services that customer relationship proneness is influenced by the quality of the relationship between afirm and a consumer, and that there is a relationship between relationship proneness and customer satisfaction and trust (Menidjel et al.,2019). As consumer satisfaction is considered the cognitive component of subjective well-being (Spruyt et al., 2020), the hypothesis below was formulated: H6. Subjective well-being is positively related to customer relationship proneness. Rai and Nayak (2018) have found that customer well-being or happiness is one of the key indicators of advocacy and word of mouth. Customer satisfaction, which is strongly related to user well-being, is a primary driver of positive word of mouth communication (Hennig-Thurau et al.,2004). The study discovered that satisfied and happy customers are more inclined to advocate the company, product or service. Thus, the hypothesis below was formulated: H7. Subjective well-being is positively related to customer advocacy. V azquez-Carrasco and Foxall (2006) found a positive association between consumer relationship proneness and intention to remain in a business relationship, which develops a favourable usage behaviour. Kim et al. (2012) showed that consumer relationship proneness significantly affects resistance to change. Collectively, these findings led to our prediction that increased customer relationship proneness will lead to the continuous usage of a specific service or product and will improve customer advocacy for such service or product. Thus, the hypotheses below were formulated: H8. Customer relationship proneness is positively related to continuous usage intention. H9. Customer relationship proneness is positively related to customer advocacy. 3.7 Moderating effects of gender and age Previous studies (cf. Herzallah et al., 2022) have examined the moderating effects of gender and age on digital services. Consequently, previous studies on the adoption and use of digital services have shown that men exhibit more traits related to productivity or task orientation compared to women (Venkatesh and Morris, 2000). Kalini cet al. (2019) showed that men are more likely to use peer-to-peer payments than women and are therefore less exposed to the potential risks involved. Glavee-Geo et al. (2017) examined the moderating effect of gender on the linkage between subjective norms and behavioural intention and found that the effect of subjective norms on mobile banking adoption is stronger for women than for men. In summary, the aforementioned researchers argue that gender plays a significant role and moderates the relationships between various variables. Thus, we conclude and suggest that gender may moderate some of the variables in the sharing economy: H10. The gender of ridehailing services users moderates all paths in the theoretical lens. Many studies have also analysed the effect of age on consumer behaviour, particularly on mobile payments (Li ebana-Cabanillas et al., 2014), online shopping (Tan and Ooi, 2018), review sites (Anaya-S anchez et al.,2019) and the sharing economy (Hsiao et al.,2018), among others. Liebana-Cabanillas and Alonso-Dos-Santos (2017) discovered that age has a moderating effect on the intention to use e-commerce platforms; in their study, the younger subjects were more interested in the real value obtained from their purchases and in their immediate benefit and productivity. Hsiao et al. (2018) found a negative correlation between age and adoption of the sharing economy. Considering the significance of user age groups in SJME technologies and innovations) and are thus very enthusiastic about technology, devices and innovative services. As such, the fact that perceived value and personal innovativeness did not show a connection with subjective well-being in such countries seems logical. The relationship between the outcome variables and subjective well-being was also examined and found significant. Theoretically, this study identified customer relationship proneness as one of the key variables navigating the success and failure of ridehailing services via the predicted variable of subjective well-being. Earlier, Wei et al. (2015), while examining the effects of relationship benefits and relationship proneness on relationship outcomes, found that customer relationship proneness develops a sense of well-being among the customers, which leads to relationship commitment with the company. Nonetheless, subjective well-being was found to be directly correlated with continuous usage intention, as was found in the study by Azzahro et al. (2018). This indicates that increased subjective well-being will further stabilise the customer relationship with the service providers, including that with ridehailing service providers. The effects of customer relationship proneness on continuous usage intention and customer advocacy were also examined, and the results suggest that relationship proneness, which refers to a user’s relatively stable and conscious tendency to engage in a relationship (De Wulf et al.,2001), increases the advocacy of ridehailing services. We contributed to the literature on the role of gender and age differences in ridehailing service adoption and usage in developed countries. The key findings of our study enable us to draw the conclusion that women value subjective well-being more highly than men do, demonstrating that women have a hedonistic orientation while men have a utilitarian orientation. Men place a higher value on customer relationship propensity than women do. With regard to age, our study findings show that older users value perceived convenience and customer relationship proneness in ridehailing services more than younger users do. 6.2 Managerial implications Our study findings provide several practical implications. Firstly, subjective well-being was shown in this study to be one of the core constructs that play a decisive role in consumer choices for any specific service or product. The study findings suggest that companies should focus their attention on increasing the well-being of the consumers. In addition, two important elements that affect consumers’subjective well-being are the experience quality and perceived convenience. To improve ridehail user happiness and loyalty, service providers should put a higher priority on these factors in their business operations and marketing plans. The study findings also suggest that the industry leaders and marketing executives should devise policies and marketing and business strategies that support and promote consumer well-being for the consumers’continuous usage of their service and for developing relationship proneness in the consumers, and for greater customer advocacy for the company and for ridehailing services on the whole. Although consumers have not placed a greater emphasis on the perceived value of ridehailing services, from a global perspective, the sharing-economy industry should not ignore or undermine the perception of value. Price is widely considered a factor inevitably influencing perceived value or that ridehail user takes into account when ordering a ride. Other factors also play a decisive role, such as the usefulness, ease of use and quality of the mobile application, including its clear layout, transparent pricing policy, the cleanness and age of the cars and the attitudes of the captains or drivers. These will provide a superior value to the consumers and will increase their subjective well-being, which will in return promote their prolonged usage of the ridehailing service. In Spain and other western Ridehailing services countries, where the high quality of the public transport or mass transit system can pose a serious challenge to and competition for ridehailing services, the high value, low price and service reliability of ridehailing services can play a decisive role in beating such competition. The findings of this study also suggest that increasing the consumers/users’subjective well-being will increase their advocacy of the services on the whole and of a service provider in particular. This advocacy by the happy and satisfied customers will gradually reduce the marketing and promotion overhead and increase the customer base of the company and should thus be considered an asset. The sharing-economy industry should also ensure the convenience of ordering as well as finding a ride close to consumers’offices, homes or shopping centres. The “pick and drop”places should be clearly identified for consumer convenience, especially near public places such as shopping centres. This study was among the very few studies so far that have identified the significance of micro-mobility and its growth due to social distancing and the pandemic. The macrosharing industry should give greater emphasis to developing micro-mobility services to retain its market share, customer satisfaction and loyalty. 6.3 Limitations and future research directions The present study has certain limitations. Firstly, this study was conducted from a crosssectional perspective, which hindered any kind of further assessment of the evolution of user behaviour over time. In this sense, a longitudinal approach should enable such analysis to check the robustness of the relationships and constructs in the research mode while examining the evolution of the effects of the variables over time. Secondly, the scope of this study included macro-mobility services such as Uber. Future studies can expand the scope of this study and include other types of macro-mobility services, such as flying taxis, and micro-mobility devices such as e-scooters. Thirdly, previous studies have largely examined the consumer segmentation between users and non-users of sharing services (Lutz and Newlands (2018). However, segregating the consumers into different segments considering the nature of the services offered by Uber is worthy of examination and is thus recommended. Fourthly, several studies have considered the ridehailing service or a matching agency (e.g. Uber) and end user perspectives (e.g. Rider). Captain or driver who own assets plays a critical role and can navigate the success and failure of the sharing economy and its development or decline. The driver’sstake is thus paramount and should be examined. Fifthly, replicating the study with a bigger and more geographically diversified population is another important future research direction. This would enable a more thorough investigation of the phenomenon being studied and improve the generalisability of the results. The future study may shed light on potential differences or similarities in the interactions between the dimensions across various cultural and contextual settings by involving people from different areas or nations. Sixthly, majority of the studies on the sharing economy have been conducted in the context of developed countries (cf. Forno and Garibaldi, 2015); only a few have examined it in the context of developing countries (cf. Alharthi et al.,2021). Multi-country assessments –for example, comparing developed and developing countries –are rare and therefore recommended. Seventhly, in relation to the moderating effect of age analysed, we propose an extension of this effect by balancing the sample in a more exhaustive approach. Moreover, and as argued by Rojanakit et al. (2022), research conducted in sharing economy filed is dominated by the quantitative or survey methods, thereby overlooking the informative knowledge, which could be otherwise captured using qualitative approaches. Future research thus should conduct more thorough investigation of the filed using exploratory and explanatory approaches and therefore recommended and included in the analysis of new moderating effects such as experience (Azimi and Jin, 2022). SJME Last but not the least, the mobile applications facilitating ridehailing services are gradually evolved by way of adding new features, services and ideas, and have become popularly known as “super applications”. Future studies may consider all the features and services offered by super applications and may examine the consumers’perspective on the usage of these applications for meeting their everyday needs. 7. Conclusion This study examined the factors that contribute to and are affected by subjective well-being in the context of ridehailing services in Spain. We used a marketing firm in Spain to gather primary data using a non-probabilistic sampling technique and a survey instrument that had already been tested. The study constructs were measured using a seven-point Likert scale, and a 450-person survey sample was subjected to a structural equation model for data analysis. According to the findings, experience quality and perceived convenience were highly connected with users’subjective well-being. There was no discernible correlation between perceived value and personal innovativeness and subjective well-being. The tendency to form customer relationships was discovered to be a crucial factor that affected subjective well-being, encouraging continuous usage intention, customer relationship proneness and customer advocacy. Women valued subjective well-being more than men did, whereas men valued customer relationship proneness more than women did. Users over the age of 50 placed a higher emphasis on perceived convenience. The practical ramifications of this study suggested that businesses should prioritise experience quality and perceived convenience while simultaneously providing greater value to improve consumers’subjective well-being. To guarantee ongoing use of their services, foster relationships with customers and strengthen customer advocacy, businesses should also work to improve consumer well-being. Overall, this study offers insightful information that will help professionals in the field, legislators, new businesses and entrepreneurs create successful marketing plans and workable business ideas for the ride-hailing services sector. References Alamoudi, H., Shaikh, A.A., Alharthi, M. and Dash, G. (2023), “With great power comes great responsibilities–examining platform-based mechanisms and institutional trust in rideshare services”,Journal of Retailing and Consumer Services, Vol. 73, p. 103341. Alharthi, M., Alamoudi, H., Shaikh, A.A. and Bhutto, M.H. (2021), “Your ride has arrived”exploring the nexus between subjective well-being, socio-cultural beliefs, COVID-19, and the sharing economy”,Telematics and Informatics, Vol. 63, pp. 1-14. Anaya-S anchez, R., Molinillo, S., Aguilar-Illescas, R. and Li ebana-Cabanillas, F. (2019), “Improving travellers’trust in restaurant review sites”,Tourism Review, Vol. 74 No. 4, pp. 830-840. Anderson, J.C. and Gerbing, D.W. (1992), “Assumptions and comparative strengths of the two-step approach: comment on Fornell and Yi”,Sociological Methods and Research, Vol. 20 No. 3, pp. 321-333. Azimi, G. and Jin, X. (2022), “Propensity toward ridesourcing: the impacts of previous experience and mode dependency”,Journal of Transportation Engineering, Part A: Systems, Vol. 148 No. 4, p. 04022010. Azzahro, F., Hidayanto, A.N., Maulida, R.M., Zhu, Y.Q. and Sandhyaduhita, P.I. (2018), “Exploring the influential factors in continuance usage of online dating apps: gratification, subjective well-being and self-disclosure”,PACIS, p. 322. Barbour, N., Zhang, Y. and Mannering, F. (2020), “Individuals’willingness to rent their personal vehicle to others: an exploratory assessment of peer-to-peer carsharing”,Transportation Research Interdisciplinary Perspectives, Vol. 5, pp. 1-7. Ridehailing services Bechler,C.J.,Tormala,Z.L.andRucker,D.D.(2020),“Choosing persuasion targets: how expectations of qualitative change increase advocacy intentions”,Journal of Experimental Social Psychology,Vol.86, pp. 1-12. Bhattacherjee, A. (2001), “Understanding information systems continuance: an expectationconfirmation model”,MIS Quarterly, Vol. 25 No. 3, pp. 351-370. Bloemer, J., Odekerken-Schröder, G. and Kestens, L. (2003), “The impact of need for social affiliation and consumer relationship proneness on behavioural intentions: an empirical study in a hairdresser’s context”,Journal of Retailing and Consumer Services, Vol. 10 No. 4, pp. 231-240. Bollen, K.A. (1989), “A new incremental fit index for general structural equation models”,Sociological Methods and Research, Vol. 17 No. 3, pp. 303-316. Cha, M.K. and Lee, H.J. (2021), “Does social trust always explain the active use of sharingbased programs? A cross-national comparison of Indian and US rideshare consumers”,Journal of Retailing and Consumer Services, Vol. 65, pp. 1-9. Chang, C.C., Yan, C.F. and Tseng, J.S. (2012), “Perceived convenience in an extended technology acceptance model: mobile technology and English learning for college students”,Australasian Journal of Educational Technology, Vol. 28 No. 5, pp. 809-826. Chelminski, P. and Coulter, R.A. (2011), “An examination of consumer advocacy and complaining behavior in the context of service failure”,Journal of Services Marketing, Vol. 25 No. 5, pp. 361-370. Davlembayeva, D., Papagiannidis, S. and Alamanos, E. (2020), “Sharing economy: studying the social and psychological factors and the outcomes of social exchange”,Technological Forecasting and Social Change, Vol. 158, pp. 1-14. Deloitte (2017), “Car sharing in Europe business models, national variations and coming disruptions”, available at: https://www2.deloitte.com/de/de/pages/consumer-industrial-products/articles/carsharing-in-europe.html De Wulf, K., Odekerken-Schroder, G. and Iacobucci, D. (2001), “Investments in consumer relationships: a cross-country and cross-industry exploration”,Journal of Marketing, Vol. 65 No. 4, pp. 33-50. El Hedhli, K., Chebat, J.C. and Sirgy, M.J. (2013), “Shopping well-being at the mall: construct, antecedents, and consequences”,Journal of Business Research, Vol. 66 No. 7, pp. 856-863. Felson, M. and Spaeth, J.L. (1978), “Community structure and collaborative consumption: a routine activity approach”,American Behavioral Scientist, Vol. 21 No. 4, pp. 614-624. Fornell, C. and Larcker, D.F. (1981), “Evaluating structural equation models with unobservable variables and measurement error”,Journal of Marketing Research, Vol. 18 No. 1, pp. 39-50. Forno, F. and Garibaldi, R. (2015), “Sharing economy in travel and tourism: the case of home-swapping in Italy”,Journal of Quality Assurance in Hospitality & Tourism, Vol. 16 No. 2, pp. 202-220. Glavee-Geo, R., Shaikh, A.A. and Karjaluoto, H. (2017), “Mobile banking services adoption in Pakistan: are there gender differences? ”,International Journal of Bank Marketing, Vol. 35 No. 7, pp. 1090-1114. Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E. and Tatham, R.L. (2006), Multivariate Data Analysis (Vol. 6), Pearson Prentice Hall, Upper Saddle River, NJ. Haji, S., Surachman, S., Ratnawati, K. and MintartiRahayu, M. (2021), “The effect of experience quality, perceived value, happiness and tourist satisfaction on behavioral intention”,Management Science Letters, Vol. 11 No. 3, pp. 1023-1032. Hamari, J., Sjöklint, M. and Ukkonen, A. (2015), “The sharing economy: why people participate in collaborative consumption”,Journal of the Association for Information Science and Technology, Vol. 67 No. 9, pp. 2047-2059. Hennig-Thurau, T., Gwinner, K.P., Walsh, G. and Gremler, D.D. (2004), “Electronic word-of-mouth via consumer-opinion platforms: what motivates consumers to articulate themselves on the internet?”,Journal of Interactive Marketing, Vol. 18 No. 1, pp. 38-52. SJME Herzallah, D., Muñoz-Leiva, F. and Liebana-Cabanillas, F. (2022), “Drivers of purchase intention in Instagram commerce”,Spanish Journal of Marketing - ESIC, Vol. 26 No. 2, pp. 168-218. Honkaniemi, L., Lehtonen, M.H. and Hasu, M. (2015), “Well-being and innovativeness: motivational trigger points for mutual enhancement”,European Journal of Training and Development, Vol. 39 No. 5, pp. 393-408. Hsiao, J.C.Y., Moser, C., Schoenebeck, S. and Dillahunt, T.R. (2018), “The role of demographics, trust, computer self-efficacy, and ease of use in the sharing economy”,Proceedings of the 1st ACM SIGCAS Conference on Computing and Sustainable Societies, pp. 1-11. Iii, J.E.M., Seo, W.J., Jordan, J.S. and Funk, D. (2015), “Exploring the impact of social networking sites on running involvement, running behavior, and social life satisfaction”,Sport Management Review, Vol. 18 No. 2, pp. 182-192. Kalini c, Z., Li ebana-Cabanillas, F.J., Muñoz-Leiva, F. and Marinkovi c, V. (2019), “The moderating impact of gender on the acceptance of peer-to-peer mobile payment systems”,International Journal of Bank Marketing, Vol. 38 No. 1, pp. 138-158. Kim, H.Y., Kang, J.Y.M. and Johnson, K.K. (2012), “Effect of consumer relationship proneness on perceived loyalty program attributes and resistance to change”,International Journal of Retail and Distribution Management, Vol. 40 No. 5, pp. 376-387. Laghari, K.U.R. and Connelly, K. (2012), “Toward total quality of experience: a QoE model in a communication ecosystem”,IEEE Communications Magazine, Vol. 50 No. 4, pp. 58-65. Laghari, A.A., Memon, K.A., Soomro, M.B., Laghari, R.A. and Kumar, V. (2020), “Quality of experience (QoE) assessment of games on workstations and mobile”,Entertainment Computing,Vol.34,pp.1-10. Lee, H., Lee, Y. and Yoo, D. (2000), “The determinants of perceived service quality and its relationship with satisfaction”,Journal of Services Marketing, Vol. 14 No. 3, pp. 217-231. Lessig, L. (2008), Remix: Making Art and Commerce Thrive in the Hybrid Economy, Bloomsbury Academic, p. 352. Liang, Z., Luo, H. and Liu, C. (2020), “The concept of subjective well-being: its origins an application in tourism research: a critical review with reference to China”,Tourism Critiques: Practice and Theory, Vol. 2 No. 1, pp. 2-19. Liebana-Cabanillas, F. and Alonso-Dos-Santos, M. (2017), “Factors that determine the adoption of Facebook commerce: the moderating effect of age”,Journal of Engineering and Technology Management, Vol. 44, pp. 1-18. Li ebana-Cabanillas, F., S anchez-Fern andez, J. and Muñoz-Leiva, F. (2014), “Antecedents of the adoption of the new mobile payment systems: the moderating effect of age”,Computers in Human Behavior, Vol. 35, pp. 464-478. Liu, S., Li, S., Chen, Y. and Zheng, T. (2023), “Examining relationships among food’s perceived value, well-being, and tourists’loyalty”,Journal of Vacation Marketing, Vol. 29 No. 2, pp. 161-174. Loureiro, S.M.C., Japutra, A. and Kwun, D. (2019), “Signalling effects on symbolic status and travellers’ well-being in the luxury cruise industry”,International Journal of Tourism Research, Vol. 21 No. 5, pp. 639-654. Lutz, C. and Newlands, G. (2018), “Consumer segmentation within the sharing economy: the case of Airbnb”,Journal of Business Research, Vol. 88, pp. 187-196. Ma, L., Zhang, X., Ding, X. and Wang, G. (2018), “Bike sharing and users’subjective well-being: an empirical study in China”,Transportation Research Part A: Policy and Practice, Vol. 118, pp. 14-24. Marikyan, D., Papagiannidis, S., F. Rana, O. and Ranjan, R. (2023), “Working in a smart home environment: examining the impact on productivity, well-being and future use intention”, Internet Research, doi: 10.1108/INTR-12-2021-0931. Menidjel, C., Benhabib, A., Bilgihan, A. and Madanoglu, M. (2019), “Assessing the role of product category involvement and relationship proneness in the satisfaction–loyalty link in retailing”, International Journal of Retail and Distribution Management, Vol. 48 No. 2, pp. 207-226. Ridehailing services Molinillo, S., Navarro-García, A., Anaya-S anchez, R. and Japutra, A. (2020), “The impact of affective and cognitive app experiences on loyalty towards retailers”,Journal of Retailing and Consumer Services, Vol. 54, p. 101948. Olavarría-Jaraba, A., Cambra-Fierro, J.J., Centeno, E. and V azquez-Carrasco, R. (2018), “Relationship quality as an antecedent of customer relationship proneness: a cross-cultural study between Spain and Mexico”,Journal of Retailing and Consumer Services, Vol. 42, pp. 78-87. Pigalle, E. and Aguil era, A. (2023), “Ridesharing in all its forms–comparing the characteristics of three ridesharing practices in France”,Journal of Urban Mobility, Vol. 3, p. 100045. Prieto, M., Stan, V. and Baltas, G. (2022), “New insights in peer-to-peer carsharing and ridesharing participation intentions: evidence from the “provider-user”perspective”,Journal of Retailing and Consumer Services, Vol. 64, pp. 1-8. Rai, S. and Nayak, J.K. (2018), “Role of event personality and exhibitors’eudaimonic and hedonic happiness in predicting event advocacy intentions: an empirical study”,International Journal of Event and Festival Management, Vol. 9 No. 1, pp. 86-103. Rogers, E.M. (1995), Diffusion of Innovations, (4th ed). TheFree Press, New York, NY. Rojanakit, P., de Oliveira, R.T. and Dulleck, U. (2022), “The sharing economy: a critical review and research agenda”,Journal of Business Research, Vol. 139, pp. 1317-1334. Shaikh, A., Karjaluoto, H. and Li ebana-Cabanillas, F. (2019a), “What drives customer satisfaction and well-being in ridesharing? a developing country perspective”,Proceedings of the International Conference on Electronic Business. International Consortium for Electronic Business. Shaikh, A.A., Glavee-Geo, R., Karjaluoto, H. and Hinson, R.E. (2019b), “How is the use of mobile money services transforming lives in Ghana?”, in Shaikh, A.A. and Karjaluoto, H. (Eds), Marketing and Mobile Financial Services: A Global Perspective on Digital Banking Consumer Behaviour, Routledge, Abingdon, pp. 256-280, doi: 10.4324/9781351174466-12. Shaikh, A.A., Alamoudi, H., Alharthi, M. and Glavee-Geo, R. (2023), “Advances in mobile financial services: a review of the literature and future research directions”,International Journal of Bank Marketing, Vol. 41 No. 1, pp. 1-33. Silva, A., Monteiro, D. and Sobreiro, P. (2019), “Effects of sports participation and the perceived value of elite sport on subjective well-being”,Sport in Society, Vol. 23 No. 7, pp. 1-22. Spruyt, B., Van Droogenbroeck, F., Siongers, J. and Bradt, L. (2020), “When individual differences meet society: on the complex relationships between boredom proneness, material deprivation, and aspects of subjective Well-Being Among young adolescents”,Youth and Society,Vol.53No.7,pp.1-21. Tan, G.W.H. and Ooi, K.B. (2018), “Gender and age: do they really moderate mobile tourism shopping behavior? ”,Telematics and Informatics, Vol. 35 No. 6, pp. 1617-1642. Tunçel, N. and Özkan Tektaş, Ö. (2020), “Intrinsic motivators of collaborative consumption: a study of accommodation rental services”,International Journal of Consumer Studies, Vol. 44 No. 6, pp. 616-628. V azquez-Carrasco, R. and Foxall, G.R. (2006), “Influence of personality traits on satisfaction, perception of relational benefits, and loyalty in a personal service context”,Journal of Retailing and Consumer Services, Vol. 13 No. 3, pp. 205-219. Venkatesh, V. and Morris, M.G. (2000), “Why don’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior”,MIS Quarterly, Vol. 24 No. 1, pp. 115-139. Wang, X., Lai, I.K.W. and Wang, X. (2023), “The influence of girlfriend getaway luxury travel experiences on women’s subjective well-being through travel satisfaction: a case study in Macau”,Journal of Hospitality and Tourism Management, Vol. 55, pp. 91-100. Wei, X., He, W., Zhang, X., Zhao, C. and Zhao, H. (2020), “A machine learning method for measuring information disclosure in sharing economy platforms”,ICIS 2020: Proceedings the Forty Second International Conference on Information Systems. Digital Innovation at the Crossroads, ISBN 978-0-9966831-3-5. Association for Information Systems (AIS). SJME Wei, Y., McIntyre, F.S. and Soparnot, R. (2015), “Effects of relationship benefits and relationship proneness on relationship outcomes: a three-country comparison”,Journal of Strategic Marketing, Vol. 23 No. 5, pp. 436-456. Wu, H.C. and Chang, Y.Y. (2019), “What drives advocacy intentions? A case study of mainland Chinese tourists to Taiwan”,Journal of China Tourism Research, Vol. 15 No. 2, pp. 213-239. Wu, H.C., Cheng, C.C. and Ai, C.H. (2017), “A study of experiential quality, equity, happiness, rural image, experiential satisfaction, and behavioral intentions for the rural tourism industry in China”, International Journal of Hospitality and Tourism Administration, Vol. 18 No. 4, pp. 393-428. Xiao, M., Tian, Z. and Xu, W. (2023), “Impact of teacher-student interaction on students’classroom wellbeing under online education environment”,Education and Information Technologies, pp. 1-23. Yoon, C. and Kim, S. (2007), “Convenience and TAM in a ubiquitous computing environment: the case of wireless LAN”,Electronic Commerce Research and Applications, Vol. 6 No. 1, pp. 102-112. Zeithaml, V.A. (1988), “Consumer perceptions of price, quality and value: a means-end model and synthesis of evidence”,Journal of Marketing, Vol. 52 No. 3, pp. 2-22. Corresponding author Francisco Liebana-Cabanillas can be contacted at: [email protected] For instructions on how to order reprints of this article, please visit our website: www.emeraldgrouppublishing.com/licensing/reprints.htm Or contact us for further details: [email protected] Ridehailing services