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Managing Sustainable Sharing Economy Platforms: A Stimulus–Organism–Response Based Structural Equation Modelling on an Emerging Market

Department of Marketing, Babeș-Bolyai University Cluj-Napoca, 400591 Cluj-Napoca, Romania
Faculty of Economic Sciences, “Aurel Vlaicu” University of Arad, 77 Revoluției Str., 310130 Arad, Romania
Author to whom correspondence should be addressed.
Sustainability 2023, 15(6), 5583;
Received: 21 February 2023 / Revised: 17 March 2023 / Accepted: 21 March 2023 / Published: 22 March 2023
(This article belongs to the Special Issue Enhancing Sustainable Rural Development through Tourism Strategies)


Due to the rising appeal of travel, as well as the appearance of low-cost carriers that fly to both popular and exotic destinations, people nowadays tend to book their accommodation through the more convenient and flexible sharing economy platforms. The success of such platforms among consumers depends on various factors, such as satisfaction and platform credibility, and on sustainable performance among contributors, increasing their relevance and visibility. This research proposes a conceptual model for measuring the success of sharing economy platforms in tourism, based on added value, unique experience, and enhanced social interactions, together with credibility and sustainable performance. In this vein, the authors conduct an empirical investigation in an emerging market—Romania—where the development of such sharing economy platforms is still in its infancy. Data gathered by the authors by means of a self-developed questionnaire distributed to 500 respondents are modelled via structural equations with SmartPLS. The results indicate that the platform credibility and sustainable performance of sharing economy platforms are key elements in generating their success. The research adds value to the stimulus–organism–response approach, highlighting some insights from a relevant emerging market, which in the future could become a turning point for inbound and outbound tourism.

1. Introduction

Nowadays, people tend to buy things that are not really needed, even though there are many economic sectors worldwide that promote sustainable consumption practices. One of these is the collaborative economy sector, or sharing economy, a type of economic activity that is relatively sustainable, which eases using products and services in a more efficient and intensive manner than traditional ways. Sharing consumer goods is part of the circular economy, which could ensure a decreasing trend in the consumption of resources, and implicitly, of raw materials, creating to a more sustainable form of consumption globally [1]. Furthermore, the sharing economy is seen as being a relatively new economic opportunity that has as its main purpose the support and expansion of a more sustainable consumption form [2], allowing the transfer of the socioeconomic power from a few large entities to a huge number of connected authors [3]. The collaborative economy is an application or subset of the circular economy [4] due to its impact on environmental sustainability.
The sharing economy might be considered a new path to sustainability because it is a global phenomenon with notable dynamics [5]. At the opposite pole, the prevailing unsustainable economic paradigms may be reinforced by sharing economy platforms, for example, by creating unregulated markets [6]. That is why it is difficult to analyze the sustainable nature of collaborative platforms in tourism in an independent modality, because their durability must be integrated in the sustainable nature of the entire tourism sharing activity.
The aim of this research is to analyze the sustainable side of collaborative sharing activities in tourism, namely sharing accommodation, from the tourist’s perspective. The sustainability of sharing economy platforms refers to the sustainable (efficient) nature of collaborative platforms, and to the environmental sustainability of the accommodation-sharing activity. These two perspectives of sustainability are interdependent. Relying on collaborative sharing platforms means using ICT; therefore, a sustainable technological infrastructure is necessary to successfully implement sharing economy activities [7,8]. This also led us to reconsider the impact of the digital technology lifecycle (and implicitly of home-sharing platforms) on the socioeconomic and environmental equilibrium [9,10] generated by the global tourism activity.
The paper analyses the extent to which sharing economy platforms and collaborative activities in tourism meet the requirements of sustainable (socioeconomic) development, and the environmental impact of home-sharing, an under-researched topic [11]. We argue that the success of sharing economy platforms influences the sustainability of the entire tourism activity. This approach is implemented by means of a quantitative-based survey among tourists in an emerging market (Romania), where the home-sharing sector, including collaborative platforms, is expanding. Therefore, it is relevant to investigate how successful sustainable collaborative platforms can be in an emerging market.
Past research has often relied on the stimulus–organism–response (SOR) model to predict consumer or tourist behavior [12]. We base our approach on the SOR model to highlight the relationship between specific accommodation-sharing constructs (considered part of either the “stimuli” or the “organism”) and the sustainability and success of home-sharing platforms (“response”). This categorization is based on the three pillars of sustainability; the social dimension is represented by “tourists’ unique experience” of sharing economy platforms, their “social interactions”, “platform credibility”, and “platform satisfaction”; the socio-economic dimension is represented by the “platform added value” and “platform success”; the environmental dimension is represented by the “sustainable platform” itself.
The originality of the research lies both in offering a valid conceptual model for sharing economy platforms, as well as presenting new insights from an emerging market, where the use of sharing economy platforms is in its infancy. Furthermore, the paper adds value to the stimulus–organism–response applied to sharing economy platforms.
The paper is structured as follows: Section 1 consists of the introduction, while Section 2 continues with the literature review, including the development of the conceptual model and hypotheses. Section 3 covers the research methodology and Section 4 outlines the research results. Section 5 depicts the discussion, highlighting the originality of the research. The Section 6 ends with conclusions containing the theoretical and managerial implications, as well limitations and future research perspectives.

2. Literature Review

The sharing economy might contribute to the achievement of sustainable development goals and pillars—in terms of the social, economic, and environmental aspects [10]. However, the sharing economy does not pay enough attention to environmental issues such as clean water, clean energy, and climate equilibrium [13]. It is unknown whether sharing economy platforms that support collaborative practices might be considered possible links toward sustainability [14]. The literature generally considers the sharing economy to have positive effects on all dimensions of sustainability [15,16,17,18].
The consumer’s feelings, attitudes, and behavior are determined by the external environment, sustained by the stimulus–response theory proposed by Thorndike [19], who believed that learning is dependent on how strong the relationship between the stimulus and the response is. This means that people might react to any kind of stimulus, even if most of them refuse to believe that their decisions are the result of any sort of conditioning [19]. The SOR model was further developed, the literature [20] pinpointing that the emotional state induced by an external stimulus can determine both approach behaviors and avoidance behaviors. Approach behaviors are positive behavioral responses to external stimuli (i.e., the desire to revisit a tourist destination or positive verbal evaluation), while avoidance behaviors are negative behavioral responses (e.g., negative verbal evaluation of hotel services) [21]. Consumer emotions are influenced by environmental stimuli, which may not be fully conscious, but may affect individual approaches and avoidance behaviors [22]. Psychological research finds that it is not only external determinants that influence consumer behavior, but also the internal feelings and emotions of each person. Many previous behavioral models were criticized as being constructions with a lack of coherence and flexibility [23]. Consequently, the stimulus–response theory could be regarded as incomplete, with the need for a framework to develop a more complex theory, i.e., the stimulus–organism–response (SOR) model [24]. This was a reconsideration of the stimulus–response theory and an evolutionary step in modeling consumer behavior [23]. The SOR model was a critique of the stimulus–response theory, developed in past decades, and one of the most used frameworks to examine the stimulus–response association, and how people mediate this relationship [25]. From a psychological perspective, the SOR model allows us to reveal the reasons behind a person’s behavior, which means understanding which stimuli influence the mental state of an individual. This model is the most suitable to understand consumer behavior [26].
The SOR model was, and still is, often used in contemporary research. It has been used to explore how sustainable behavior was demonstrated in bicycle-sharing in China [27], while other studies [28] attempted to discover the motivation of Chinese consumers to avoid seeking information about the COVID-19 pandemic. The model was also used in tourism research to elucidate tourists’ behavior in different contexts. Visitor behavior has been analyzed by tourism studies [29,30,31], with consumer behavior predicted by using factors such as quality of cognition and perceived services [30]. Emir et al. [32] tried to identify the influencing factors of online hotel bookings in Malaysia through the SOR perspective. The findings were that quality of information, perceived interactivity, privacy, safety, price, promotion, and finally, word of mouth were the proposed catalysts expected to influence the organism (perceived value) and intention of online hotel bookings (response). Other authors [33] tried to understand the behavior of the active sports tourist in sport events on a small scale. Their study aimed to investigate the structural relationships between perceived value, tourist satisfaction, emotional experiences, and destination loyalty, given the context of sporting events that occur on a small scale, by adopting the SOR model. This model was also implemented to predict tourists’ intentions.
The literature has also examined the link between processes (O-organism), such as customer engagement, inputs (S-stimulus), customer trust towards platforms, and outputs (R-response), customer loyalty [34,35]. The SOR framework helps us to understand customer relationships, i.e., customer engagement and loyalty, resulting from customers’ trust in home-sharing hosts and platforms [31]. In a study conducted on 303 users of the Airbnb platform in five cities in Malaysia [36], the authors highlighted the relationship between social and information overload (S), satisfaction, and trust/credibility in platforms (O), as well as intention to continue (R). Others [37] proposed a model that analyzed the relationships between authenticity, the benefits of staying at Airbnb locations (home benefits), social interactions (S—all as stimuli), perceived enjoyment (O), and repurchase intention (R). Approach behavior can be measured both by actual behavior (attachment to a tourist experience and visiting tourist attractions), as well as by behavioral intentions (intention to revisit and recommendations) [34,38,39]. Authentic experiences might also be a relevant stimulus, especially if displaying the intention to visit a touristic destination [34].
A simpler definition of sharing platforms, in our opinion, could be an electronic platform that connects buyers and sellers, built to create new digital systems by using new technologies and the Internet [40,41] to allow the rapid connection of customers to goods/services, saving money and time. The most researched sharing sector is accommodation, through the Airbnb platform, while the most researched topics are price, trust, experience, consumption, and value [42,43].
The products/services offered by smart peer-to-peer (P2P) tourism platforms are rapidly adapting to better satisfy consumer needs, as opposed to more traditional services [16,44]. Reliance on these services is based on high interest and confidence in such platforms [45], although the literature shows that repetition of such behavior is scarce [46]. High frequency of use has been one of the factors contributing to the behavioral success of platform sharing [47,48], such services being consolidated with trust and security [49]. Socio-demographic variables (age, gender, and education) are determinants that influence the repetitive use of collaborative platforms [46,50]. When a consumer wants to repeat the sharing experience, he/she does so because of a specific destination [51], or because the motivation of using the platform is leisure or enjoyment [16,44,52]. Enjoyment positively affects the consumer’s attitude to accommodation-sharing platforms because the use of them can result in fun and different positive experiences [37]. Having fun when accessing these platforms predisposes an affinity for technology, a socializing mentality, or both [53].
Although certain companies, such as Uber or Airbnb, have had significant success in making the connection between providers and users [54], building a successful model in the sharing economy involves a series of challenges. The success of a sharing platform might also reside in its ability to provide better services, attract new tourists, or increase the loyalty of existing ones, without experiencing financial or other negative losses in reputation, image, quality of services, etc. [55]. Trust is the key factor in establishing a long-term relationship between customers and hosts, having a substantial effect on intention [56].
Fun and enjoyment in using sharing platforms reflects the success of this activity and the changes in the accommodation-sharing behavior of consumers. One of the key factors influencing the sustainable development of the sharing economy is credibility, and, implicitly, the success of this activity. Because the platform, provider, consumers, and the shared products/services [57] are the main components of this collaborative economy, there exist a lot of “trust relationships”; for example, trust towards the platform, trust towards peers, and trust towards the offered products/services [53]. From the home-sharing point of view, trust is oriented towards two directions: customers’ trust in the platform and the trust in guests to behave in a respectful manner [57]. Trust is not only a direct path to success, but also a belief that business risk will be reduced [58,59] by the sharing partner who will act in a fair and reasonable way [16]. Managers of accommodation platforms are assured of the knowledge needed to encourage younger generations to participate in the collaborative economy. Attitude, social norms, and trust are important variables influencing the younger generation’s behavior towards sharing economy platforms [60].
Stimuli are the determinants encountered by a consumer when he/she experiences different products or services [61]. We consider the stimuli that influence sharing platform credibility as the added value, the unique and authentic experience provided by accessing the offered services through the platform [62,63], and the social interactions between all parties involved in the process.
Consumers are strongly driven by value and convenience when deciding to participate in the P2P economy [64]. The first model bringing the concept of “perceived value” into a technology acceptance model was the value-based adoption model (VAM), considered as a possible prerequisite for the adopting intention of the technology [65]. Consumer perception of emotional value, quality value, and price value are all factors that influence customer value and loyalty [66]. A study of 476 respondents indicated that perceived value is affected by transaction costs and perceived benefits, which in turn affect the intention to use the platform [55]. Customer loyalty is the consequence of perceived value, and extra-role brand building behavior is the consequence of perceived value, both influencing brand performance [67]. Perceived value also has a positive impact on m-commerce [68]. Perceived value adoption is determined by the ratio between the sacrifices required when using some technology or innovation and the perceived benefits [69].
In the case of using the Airbnb platform among South Korean guests, a significant positive effect was found between monetary savings, novelty, unique experience, fun, excitement, and perceived value. However, there was no connection between social interactions and perceived value [70]. There is a debate in the literature [68] on the perceived value of sharing platforms as opposed to traditional tourist operations. Potential clients of a platform are likely to be interested in the benefits it brings, i.e., added value mirrored by service trust, flexibility, ease of access, platform reputation, timely responses from the platform, and the degree to which such platforms might offer unique experiences. Therefore, a platform must display attractive benefits [71].
The intention of the consumer is to buy products and services in which the exchange process is perceived to have added value. Consumers concerned with environmental problems play an essential role, especially when they use second-hand P2P platforms (such as eBay and Facebook Marketplace) that shape the behavior and habits of sustainable consumption among young consumers [71]. We consider that a sharing platform which gives consumers power to increase their preference for environmentally friendly products/services adds value to purchase intention, while facilitating the supply and demand for green online services, increasing the sustainability of consumption choices through online platforms [71]. In this way the green consumption values of consumers are emphasized [72], which can be considered a surplus value compared to the perceived value, or a benefit that constitutes a platform’s added value. Based on the above-mentioned considerations, we state the first hypothesis:
Hypothesis 1 (H1).
The added value of sharing economy platforms exerts a positive influence on their credibility.
Tourist expectations of a unique experience are dynamic and influenced by a variety of factors. The unique experience involves the personal feelings of tourists derived from the use of customized, authentic, and tailored tourism products and services [73]. For tourists, P2P transactions offer (compared to traditional tourism services) cost-effective options and superior value for money, which gives them greater convenience [16]. Furthermore, due to the novelty and meaningful interactions between tourists and locals, the sharing economy platforms offer more authentic tourism experiences [74,75].
An authentic and unique experience has a significant impact on cognitive and affective responses, being an important determinant of virtual tourism [34]. One of the main features of the experience of a shared economy is authenticity; travelers expect unique experiences in authentic settings, as well as social interactions with local inhabitants of the visited destinations. Furthermore, the idea that sharing allows the accessibility of products/services unavailable elsewhere can represent a unique (or authentic) experience for numerous customers [7]. To create a unique experience for Airbnb tourists, it was found that interaction with hosts and local culture, together with home interiors and an atmosphere of unique accommodation was important [76].
Authenticity plays an important role in shaping a unique experience, being an important part of consumer satisfaction with Airbnb accommodation [77]. Local authenticity is valued as a motivating factor for staying in a location through Airbnb [44]; guests perceive the platform as superior to hotels in providing an authentic experience [78]. The expectations of a unique experience exert a positive influence on both attitudes and repurchase intention [73].
In our context, the experience created by a sharing platform must also be considered because the success of a sharing economy business rests on the individual’s access to the platform through their personal devices. A positive online experience will increase consumer satisfaction and repurchasing intention [79]. This means that consumer satisfaction is created by experiential value, reflecting consumers’ emotions, feelings, joy, and fun [80]. A positive experience of the sharing economy will improve attitudes towards the platform itself, confirming the credibility of consumers in such platforms [81,82], while inducing loyalty [83]. In this context, we postulate a new hypothesis.
Hypothesis 2 (H2).
The unique experience generates credibility for sharing economy platforms.
By enabling tourists to connect with local communities and to share their personal experiences, sharing economy platforms foster direct host–customer interactions [50]. The frequency of travel is significantly increased by the social attraction of collaborative consumption [16]. Social practices draw attention to the situations of host–guest interactions [84].
The social experience generated through sharing was discussed by Hawlitschek et al. [53], while social influence, more precisely the idea of sharing one’s social environment, was analyzed by Venkatesh et al. [85]. A significant predictor of the intention of the user to rent in P2P sharing was social interaction [86]. Compared to hotel services, home-sharing travelers expect more local host social interaction [74]. However, not all home-sharing guests can establish social contact with the local host [87]. While some people value receiving an invitation from the host and appreciate the tips offered about the accommodation, for others, lack of interaction with the host is not well received, because many of these apartments are rented in the absence of their hosts [88].
Unexpectedly, social interaction did not play a role in determining intention and perceived enjoyment but was of great importance in producing satisfaction and loyalty [50]. Staying in a stranger’s apartment, or taking in strangers can entail great risks, so credibility is essential in this choice. The sense of community is promoted by sharing platforms, and this can improve trust between users [89]. Recently, social interaction and social influence have become motivations for consumers to use sharing platforms [90]; people receive pressure from other members of the community, which impacts strongly on their attitude and behavior [91].
Of primary importance to Airbnb accommodation is social interaction, which influences tourists’ experiences and level of satisfaction. A statistically significant predictor of satisfaction with accommodation through this platform is the host–guest relationship [37]. Social interaction (and the benefits derived therein) contributes significantly to the host’s sharing attitude, the intention to participate by both parties, and the customer’s accommodation experience [92]. Social orientation acts as a motivator of trust [93]. Therefore, we postulate the following hypothesis.
Hypothesis 3 (H3).
Social interactions impact sharing economy platforms’ credibility.
The organism is ‘a stimuli by-product, and stimuli are environmentally influenced’ [94]. Platform credibility and satisfaction are the components of the organism (as part of the SOR model). A sustainable platform must have a direct influence on the success of the platform. Credibility is fundamental in the growth and sustainability of collaborative platforms, being a key element to supporting the success and development of the sharing economy. When individuals share their resources, interactions between strangers can involve high risk, causing financial and other losses [95]. When analyzing the antecedents of trust in the sharing economy, the literature [89] highlighted three antecedents: institution-based credibility, trust-related behaviors, and trusting beliefs towards relevant stakeholders. Trust exists not only at the individual level (for instance the client and/or host), but also on the level of sharing platforms [88]. Platform credibility suggests that tourists believe in protection against perceived risks through the sharing platform, while host trust means host reliability and trustworthiness [31]. Li and Wang [57] analyzed the effects on the sharing economy trust of the online trust mechanism, establishing the link between trust in platforms and trust in the whole collaborative activity, while at the same time dividing trust into two types from the perspective of accommodation sharing: trust in consumers and trust in sharing platforms. Users and service providers are encouraged to connect with hosts by trusting the platform information; trust in the platform being only one part of the shared economic trust mechanism.
Understanding and measuring trust can be very beneficial to such platforms, enabling them to identify both the online and offline trust attitude [96]. Trust is fundamental to the existence of sharing economy platforms, playing a major role in decision-making to buy P2P accommodation [97]. The infrastructure is provided by these platforms to make home-sharing possible, but they ultimately depend on people’s willingness to trust strangers [96]. Trust was a main deterrent of collaborative consumption on the Airbnb platform [16]. The positive motivational factors for using the platforms of the shared hosting economy were trust, reviews, utility, and search for learning and knowledge [98]. To act in good faith, customers and hosts must trust each other [31], since platform trust positively influences host trust [99]. Customer engagement and loyalty were significantly related to customer trust [100]. Trust perception is determined by salient themes (such as location, room descriptions, room aesthetics, repurchase intention, host attributes, overall evaluation, etc.) [101]. Trust and success on the platform are influenced by presentation [96]. To identify a platform’s mission of establishing and maintaining trust, participants are encouraged to participate in trust-based commercial exchange platforms [102]. Platform trust has a direct connection with the consumer’s intention in the collaborative economy [34]. Perceived trust of hosts is crucial in attracting tourists [90].
Trust in hosts [103,104], trust in providers, trust in consumers, and trust in products [53] is also analyzed in the literature. Regardless of the form of trust we are referring to, trust plays an enormous role in accommodation sharing, as there are fewer available direct remedies against trust violation [105]. In the case of trust violation, consumer protection laws cannot be applicable [102].
To generate future purchase intention, it is necessary to deeply understand the role of trust in the hospitality sharing economy [103] and to ensure a high level of satisfaction amongst customers. Although the literature has indicated that both trust and satisfaction are decisive in understanding customers’ behavioral intentions, the research is limited to exploring the relationships between the two concepts [104]. Building trust between the client and the host (in the sharing economy context) is a necessary condition for the emergence of a feeling of satisfaction regarding the use of collaborative platforms. In this vein, we state the following hypothesis.
Hypothesis 4 (H4).
Credibility towards a sharing economy platform positively influences the satisfaction in such platforms.
Consumers will be satisfied if their current experience of home-sharing platforms is more pleasant than their expectations. As an essential element for service providers, consumer satisfaction leads to positive post-purchase behavior, such as positive word-of-mouth and repeated visits, and supports customer retention, that is, increased sales and profit [16]. The literature [15,82,106] pinpoints the positive effect of consumer satisfaction on future intentions to choose sharing economy platforms.
The importance of credibility in a sharing economy is huge because it directly impacts repurchase intention. The relationship between satisfaction and the intention is mediated by trust [104]. The attributes of Airbnb businesses that ensure satisfaction vary among the studies found in the literature. Consumers’ desire and recommendations for reusing Airbnb are higher due to greater customer satisfaction and trust in Airbnb. Initial credibility [107] will be fostered by hedonic value [83], interaction with Airbnb hosts (positive behavior of hosts: assistance and timely responses) and maintaining positive communication with guests [108]. This will have a positive impact on user satisfaction [104]. The key antecedents of consumer loyalty are consumer satisfaction and trust in Airbnb.
The reciprocity achieved by the exchange of value in social and material resources is the main determinant of satisfaction and intention to access the sharing platform [64]. The theory of self-determination pinpoints that the intention to participate in the sharing economy is dependent on intrinsic and extrinsic motivations. The desire to reduce waste and environmental impacts on consumption can be an intrinsic motivation [109]. The main factors influencing customer satisfaction regarding the P2P economy are monetary benefits, accommodation attributes (location, host reception, and accommodation comfort), and fun [16]. Satisfaction and avoidance of dissatisfaction must be created by a successful business [106]. The sources of dissatisfaction of consumers are more diverse compared to the sources of satisfaction [110]. The experience of each customer of home-sharing platforms can influence the future behavior of consumers, especially if they post their experiences on the forums of these platforms or discuss their opinions in online reviews. According to Liu et al. [18], customer platforms are reliable sources of information for a better understanding of what drives customer satisfaction. The company’s offer will be improved to meet consumers’ future demands. The importance of customer reviews is even greater in P2P hosting than in conventional hotels [111], the online platform being the only communication channel with customers [112]. User satisfaction with sharing platforms positively influences the intention to reuse those platforms [113,114], as well as the intention to recommend them [114]. Thus, it is of research interest to study the factors that generate the behavioral success of sharing platforms, especially in the little-explored context of emerging economies.
Because customer loyalty is a way to ensure the success of sharing activities [115], we can conclude that an entrepreneur who pays enough attention to this could ensure a high satisfaction level of the consumer using the platform. Perceived usefulness and satisfaction significantly influence the continued use intention of the platforms. Consumers will continue to use sharing platforms as their satisfaction level reaches a higher level [116]. We propose the following hypothesis.
Hypothesis 5 (H5).
Satisfaction with sharing economy platforms generates the customer-oriented success of these platforms.
A strong influence factor that encourages the adoption of circular economy practices in emerging economies is consumer behavior in relation to sustainability [117]. From the environmental sustainability point of view, opinions analyzing home-sharing are contradictory. Some conclude that the sharing of accommodation is a sustainable activity [18,114,118,119,120], while others think that it is harmful to the environment [11,121,122]. Some authors concluded that the sustainability impacts of sharing economy platforms will remain unclear for a long time to come [123].
Developing since the 2000s, the sharing economy has provided important societal benefits, especially in terms of sustainable development (reducing pollution, facilitating access to resources, and reducing poverty) [120]. The contribution made by the sharing economy to social well-being, economic growth, environmental protection, saving of natural resources, reduction in energy consumption, and emissions is uncontroversial [124]. Sustainability has a positive influence on people’s attitude towards the sharing economy [125], the sharing economy being a solution for sustainability promotion. Trust among users, between users, and in the platform is at the core of the sharing economy that influences sustainability [95]. Sustainability positively influences the supplier’s attitude towards providing Airbnb accommodation services [37], thus being a main driver of collaborative consumption [16]. Sharing, moreover, is environmentally friendly [15]. Due to less energy and resource consumption, and less waste production, this type of accommodation is a more sustainable alternative to traditional travel accommodation [118]. To encourage consumers to adopt services, the benefits of house-sharing services in terms of environmental sustainability can be used as a communication strategy [18]. Shared economies could be used to stimulate potential incentives to reduce the consumption’s ecological footprint and to implement effective sustainable development approaches [8]. Moreover, the green tourism sharing activity may increase consumers’ trust in tourism sharing platforms. In this way, environmentally sustainable travel is promoted, using the existing resources in an efficient modality. We formulate the following hypothesis.
Hypothesis 6 (H6).
Sustainability of sharing platforms has a positive influence on the credibility towards them.
There is available information regarding accommodation-sharing centers on the activity of Airbnb, Couchsurfing, HomeExchange, etc. In 2014, a relevant environmental study concluded that Airbnb brought significant gains compared to hotel accommodation—up to 89% in greenhouse gas emissions, 48% in water, 32% in waste and 78% in energy savings [126]. Private property accommodation through home-sharing platforms may lead to lower CO2 e-emissions due to the lack of energy-intensive facilities, and comparatively low water use and waste generation [17]. However, these assumptions were no longer valid when a study on the Sydney Airbnb market found that tourism sharing generated equivalent direct and indirect carbon emissions of carbon dioxide. Sizeable greenhouse emissions are also brought about by tourist accommodation (Airbnb or traditional hotel accommodation), which collectively accounts for 20% of worldwide tourism emissions [121].
Sustainable tourism might be encouraged through the existence of an alternative rental platform: Fairbnb [127]. Fairbnb, a platform set up in response to the disruptive Airbnb model, first appeared in Amsterdam and Venice [128], and since emerged in many European destinations, such as Venice, Barcelona, Bologna, and Valencia. Fairbnb encourages a more sustainable type of tourism, providing travelers with a more authentic experience. If future sharing platforms were based on offering green products/services, reducing resource and energy consumption and greenhouse gas emissions, the effect on sharing environmental sustainability could be greater satisfaction when using these platforms, which could be translated into changing consumers’ attitude towards digital platforms [129]. This could, in the long term, assure a high success of these kinds of businesses. In this context, we postulate the following hypothesis.
Hypothesis 7 (H7).
The sustainability of sharing economy platforms has a positive impact on the satisfaction generated when using such platforms.
Key factors in influencing attitudes and behavioral attitudes towards collaborative consumption, such as sustainability, pleasure, reputation, and economic benefits allows the success of the business, by changing consumers’ attitudes towards the collaborative economy [15]. We propose the following hypothesis.
Hypothesis 8 (H8).
The sustainability of sharing economy platforms triggers the behavioral success of such platforms.
Based on the literature, the authors propose a conceptual model (see Figure 1), depicting the success of sharing platforms based on different prerequisites. The model depicts the attitude and expectations of consumers about the experience and benefits offered by sharing platforms, which ultimately influences trust in collaborative platforms [57], platform success [114] and user satisfaction [113,114]. At the same time, the model shows a close correlation between the sustainable character of the sharing platform [120,124], consumer credibility, and platform satisfaction and success.

3. Research Methodology

As a result of the pandemic crisis, millions of individuals in the tourism and hospitality industry have experienced extraordinarily high levels of job instability worldwide [130]. One of the industries strongly affected by this crisis is collaborative tourism, more precisely, home-sharing. Two of the sharing sectors profoundly affected by lockdown restrictions in Romania are transportation and accommodation, millions of workers having lost their jobs. Tourism has currently started to grow again, so there is hope that online platforms will contribute to relaunch the industry in time [7]. Gradual changes are expected to take place in the future dynamics of online platforms in Romania due to the popularity of P2P activities promoted by the collaborative economy in developed countries [131]. More than that, there are multiple facets to sustainability and digital transformation [132] in Romanian businesses, which will generate, in time, multiple challenges and opportunities for the accommodation-sharing companies too [133].
The purpose of this research is to investigate the behavioral success of sharing economy platforms among tourists due to the impact of sustainability on the credibility of the platforms and tourist satisfaction. In the COVID-19 pandemic, participants were invited to value the platform and experience in relation to Airbnb, Couchsurfing, House Trip, etc. In Figure 1, the conceptual model was calculated according to SmartPLS [134] with structural equation modelling (SEM). The quantitative research was based on the survey technique, using an online questionnaire as the research tool. It was implemented in Romania, in January–April 2022, among Generation Z users of the different sharing platforms (CouchSurfing, House Trip, Airbnb, etc.). As trustworthy information on the exact number of sharing economy platform users is not available in Romania, it was impossible to estimate the total population, and thus, draw a relevant sample size. Therefore, we employed a convenience sampling technique.
The aim was to obtain the most accurate distribution of respondents according to age, gender, and domicile, according to the specifications of the Statistical Yearbook [135]. The questionnaire was also distributed on social networks promoting sharing economy platforms, seeking to obtain answers from people who knew and used them with a certain frequency. The aim was to obtain the best possible representativeness among respondents, given that the COVID-19 pandemic had strongly affected the use of such sharing platforms.
Of the 548 respondents, 69.7% were women (382) and 30.3% were men (166). Most were domiciled predominantly in urban areas (407). A total of 360 people (55.7%) were up to 30 years old. When asked about the average length of stay that could be purchased through sharing economy platforms, 286 people (53.9%) indicated that it varied between one to five nights, 224 people indicated that it varied between six to ten nights, and the rest answered that their average length of stay was over 10 nights. A total of 495 respondents resorted to tourist bookings through such sharing economy platforms; the rest used them for medical or business purposes, alone or with friends and relatives.

4. Results

4.1. Evaluation of Measurement Model

In Figure 1, the conceptual model was calculated in SmartPLS 3.0 with structural equation modeling (SEM). All dimensions deduced from the specialized literature were measured in reflective form, the items being subsequently checked, regarding item loadings (Table 1), for average variance extracted (AVE), validity and internal consistency, reliability of the considered indicators (Table 2), and discriminant validity (Table 3). The dimensions of the research have been correctly measured and all the elements have convergent properties because all item loadings are above the minimum recommended value of 0.70 [136]. The values of these item loadings (Table 2) have variations from 0.881 to 0.950, and are well over the minimum requirement of 0.7 [136].
By resorting to Cronbach’s alpha, reliability was tested and had to be minimum 0.7 so that all dimensions could be correctly measured [138]. As can be seen in Table 3, the Cronbach alpha values far exceed this minimum threshold, which denotes the internal consistency of the considered variables. All obtained average variations exceed the minimum threshold required by 0.5, which means that the measurement model is appropriate [139] and convergent validity exists in all the constructs. The minimum values, in the case of composite reliability (CR), are higher than 0.7, according to the minimum threshold suggested by the literature [136], which confirms the reliability of all model constructs in Figure 2.
The Fornell–Larcker criteria were used to test the discriminatory value of each dimension (Table 3). Therefore, for each latent variable, the value of the AVE coefficient of correlation between competent variables and all unique variables had to be higher [140]. All in bold on the diagonal stand is the square root of the explained average variance. The partial correlations between constructs are represented by diagonal values.
A collinearity level was analyzed for elements in the measurement model. As a result, the difference in the value of the average inflation factor (VIF) of all indicators is lower than the maximum level (5) [140]. In this sample, the highest value of item SP2 (4.708) confirms that there are no multicollinearity issues. Afterwards, we proposed to highlight the multicollinearity between the constructs. Thus, a value below the recommended threshold of 5 is the inflation factor of the inner model [140]. It means that there is no multicollinearity between constructs. To test the eight hypotheses, the bootstrap procedure was used (Figure 1). These eight hypotheses show strong positive influences on T statistics and can, therefore, be accepted.

4.2. The Evaluation of Structural Model

The square root median residual (SRMR) shows a SRMR = 0.034 value lower than the recommended threshold < 0.08, so the fit goodness of the saturated model is more than acceptable [140].
Platform satisfaction and sustainable platform explain 70.2% of the variance of platform success (R2 = 0.702), while platform credibility and sustainable platform explain 79.6% of the variance in platform satisfaction (R2 = 0.796). A total of 64.9% of the variance in platform credibility (R2 = 0.649) is explained by platform added value, unique experience, social interactions, and sustainable platforms, which define the strong prediction power of the structural model (see Figure 2).
Figure 2. Structural model.
Figure 2. Structural model.
Sustainability 15 05583 g002
Table 4 indicates a positive significant and strong influence between the added value of the platform and the sharing platform itself (β = 0.449; T-value = 9.493 and p < 0.001), confirming our assumption that the benefits brought by the added value positively impact people’s trust in these platforms. This hypothesis has not been validated so far in the specialized literature, but thanks to the data mentioned above, it is statistically supported, which is why hypothesis H1 is accepted. H2 assumed that unique experience generates credibility for sharing economy platforms. The results show a strong and significant relationship between the two structures (β = 0.263; T-value = 6.099 and p < 0.001); a tendency also pinpointed by previous research revealed in the literature [56,81,82]. Because the hypothesis has been validated in the specialized literature and is confirmed in our research, H2 is supported.
H3 assumed that the social interactions of respondents’ impact the credibility of sharing economy platforms. The results (β = 0.074; T-value = 2.088 and p < 0.005) pinpoint a low and moderate significant connection between the two constructs, which validates the assumption of Tussyadiah and Pesonen [16] in the case of Airbnb, where social behavior did not significantly influence trust in Airbnb. However, the fact that in the specialized literature, this relationship has already been validated [89,93] will allow us to accept the H3 hypothesis as well. The reason why this hypothesis is marginally accepted could be the sample structure, where the largest sector of respondents was up to 30 years old. The age of the participants could be a possible explanation. H4 inferred that the credibility of a sharing economy platform positively influences platform satisfaction. As highlighted by the obtained results (β = 0.825; T-value = 27.849 and p < 0.001), respondents’ trust towards sharing economy platforms manifests a very strong positive and significant influence on platform satisfaction. Similar results were obtained in the literature [83,104,106,137]. Thus, empirical data support H4.
H5 hypothesized that Satisfaction with Sharing Economy Platforms generates customer-oriented success for these platforms. The results demonstrated that satisfaction with a sharing platform has a very strong positive impact on the success of these platforms in terms of customer-oriented success, as evidenced by the results (β = 0.753; T-value = 19.956 and p < 0.000). Similar results have been previously highlighted in the literature [15,16,82,104,106,115]. The customer-oriented success of a platform means that consumers will continue to use it because they feel a high degree of satisfaction [116]. Therefore, H5 is accepted. H6 assumed that the sustainability of the sharing economy platforms positively influences their credibility. As the results (β = 0.137; T-value = 3.140 and p < 0.001) also showed a strong and positive influence between the constructs, we validate this hypothesis. Similar results were previously confirmed by the literature [95,141]. Because the sharing economy is greener than traditional businesses, fueling the idea of trust in green digital businesses [6], hypothesis H6 is accepted.
H7 assumed that the sustainability of the sharing economy platforms has a positive impact on platform satisfaction. The positive influence of moderate impact between the two constructs has been proven by the results (β = 0.097; T-value = 3.153 and p < 0.001), which allows us to accept H7, validating this hypothesis. Likewise, the literature [15,125] emphasizes the idea that a sustainable sharing business will positively influence attitude towards sharing platforms due to the satisfaction felt. Therefore, hypothesis H7 is accepted. H8 inferred that the sustainability of sharing economy platforms triggers the behavioral success of such platforms. The obtained results (β = 0.124; T-value = 3.349 and p < 0.001) show a moderate positive influence of strong significance between the investigated constructs; thus, the empirical data support H8. In fact, the success of this business lies in the loyalty consumers must have to sharing platforms, as Kim [106] emphasized. Additionally, trust in platforms triggers consumer satisfaction [88,95] and implicitly, behavioral success, being the essential element supporting the success of the sharing economy [105].

5. Discussion

Airbnb is the most widely used sharing platform in Romania but has been negatively influenced by the COVID-19 pandemic. However, the sharing economy has started to grow again, increasing its activity [142]. To relaunch this field, an advanced digital technology is needed to ensure the sustainability of collaborative platforms. Even if the numerous lockdowns have seriously affected transportation and accommodation, the high level of the Romanian digital infrastructure has created the necessary framework to increase consumer confidence in the collaborative economy. Younger generations are more receptive to the new digital offers of companies compared to older generations, attitude, credibility, and social relations being the main factors influencing the behavior of sharing platforms consumers [60].
We have analyzed the factors that generate the behavioral success of sharing platforms in an emerging economy. Using the SOR model, we highlighted the most important determinants that can make collaborative platforms more sustainable from the economic, social, and environmental point of view. The main scope of the research was to determine if stimuli such as added value, unique experience, and the social interactions offered by sharing accommodation influence consumers’ trust and behavior towards collaborative platforms, generating satisfaction, the success of the platforms, and a higher level of sustainability. Of the eight proposed hypotheses, all were accepted with a positive influence, even if one of them was marginally acceptable. In this way, many of the hypotheses tested and confirmed in the international specialized literature were accepted as valid for an emerging country such as Romania.
Credibility in a sharing platform is positively influenced by the platform added value, the newly proposed construct in the present research. If we consider that one of the added values is the advanced technology or digitalization, we must emphasize that perceived value and trust are positively influenced by technology seeking [7]. A flexible digitalized sharing platform can stimulate users’ perceptions [143].
Authenticity and unique experience have a significant impact on trust in the accommodation platform. The consumer’s behavior will change if they have a positive accommodation experience, thus ensuring credibility in the services offered by the platform, as identified in the literature [81,82]. Trust induces loyalty [83], which will generate satisfaction in using the platform, and the success of the platform. If the platform also respects environmental principles, we can consider it as being a sustainable platform. Trust and social interaction have the power to increase the credibility of a platform, making it more successful [144]. The influence of social interaction on platform trust is moderate in our research, but the influence of trust on platform satisfaction is major, as previously revealed [104,106].
Customers who are satisfied with the services offered by the platform will return with the intention of receiving a new offer. In this way, the success of the platform is obtained [106,107,108,145] through consumers’ loyalty [83,106,115]. Consumers have greater trust in a sustainable platform. A platform that fulfils the three dimensions of sustainability will have increased success among clients, persuading them to have a favorable attitude towards the platform, tendencies also confirmed by previous research [117,120,124,146].
A sustainable platform will positively influence trust and satisfaction. Taking into account the proposed SOR model, we confirm that the results of our research stated that between the chosen stimuli, added value, unique experience, social interactions and organism, platform trust, platform satisfaction, there is a strong relationship that influences Romanian consumers’ behavior in opting for the use of sharing platforms; the behavior of the respondents is positive, which means that accommodation-sharing through collaborative platforms could be a successful and sustainable business (from the social, economic and environmental points of view). Romania, an emerging country, implemented sharing services on its market comparatively late, compared to advanced economies. Because the home-sharing market is a new field, it is not sufficiently known by Romanians, often being confused with booking services. Furthermore, a large part of the population is not sufficiently informed about the characteristics of accommodation-sharing. Our research brings additional added value to studies that use the SOR model in tourism, more precisely in the home-sharing sector.
The pandemic and the economic crisis that it generated determined a total reformulation of government policies in most of the world. These policies aim, first, to support aggregate demand so that it does not collapse under the weight of severe recession, and, secondly, to support production to regenerate and transform it in relation to the challenges of sustainability, proposed by the new business models. From the environmental sustainability point of view, the authors have different opinions on how environmentally friendly a sharing platform is, or how sustainable the entire collaborative activity is, compared to traditional businesses. The impact of the shared tourism economy on environmental sustainability is both positive and negative. The more frequent use of tourism sharing platforms might even be negative to the environment. Collaborative consumption (such as Airbnb) generates higher energy consumption than traditional tourism, as maintained by some researchers, due to the carelessness of tourists. An increasing number of tourists in the same region may increase pollution emissions, waste production, water, and energy consumption, even if an environmentally sustainable sharing economy helps to allocate resources, decreasing the emission of greenhouse gases. The contradictory discussions between specialists regarding how environmentally friendly (or not) home-sharing platform might be, will continue in the future, because a consensus has not yet been reached.

6. Conclusions

The theoretical contribution of this paper lies both in further developing the stimulus–organism–response approach for collaborative platforms, such as Airbnb, and in implementing the research in an emerging market (Romania), where this subject is still under-researched. The paper proposes a unique and novel research model; the way in which the constructs are placed in the context of the research is original. The grouping of these constructs into the three components of the SOR model is also a personal contribution of the authors, aimed at analyzing the behavior of consumers of home-sharing platforms. The first construct used as a stimulus (platform added value) did not exist in the literature, being defined here as the sum between perceived value and the benefits a home-sharing platform can ensure, a definition that contributes considerably to the advancement of the literature.
The viable business models successfully implemented in different developed countries cannot be easily adopted in emerging ones. Structural problems in emerging or under-developed economies are not like those in developed economies. Romania needs policies that pay attention to all strategic fields and industries, including tourism, but the implementation of all these measures must also be conducted considering climate change, acknowledging the fact that humanity has been living in debt (on borrowed time) for a long time. These aspects must also be considered in the field of the digital home-sharing economy.
From the managerial perspective, we must mention that a successful strategy for home-sharing would be based on innovation, and on building special collaborative platforms in the current climate context (such as, a platform that offers environmentally friendly services to tourists), to meet the requirements of the clients concerned with sustainability issues. The future of sharing platforms requires finding new opportunities to expand and improve them (creating a new design, interesting content, and a high speed of accessing the provided information), in the context of greater competition. For managers or entrepreneurs, it will be of great interest to design more attractive platforms that are easier to access and offer high quality services with maximum promptness, generating increased consumer confidence in these types of businesses. The benefits of such platforms, such as speed of accessing information, attractiveness, flexibility, etc., are necessary to gain customer trust, which will ultimately lead to increased loyalty, and implicitly, the success of these kinds of business. In this way, digital home-sharing could be better organized than traditional businesses.
Among the limitations of this investigation, we emphasize the impossibility of expanding it to the entire Romanian population. Another limitation lies in the fact that respondents were not asked about their travel purpose, so future research could, for instance, emphasize the degree to which tourists rely on sharing economy platforms when traveling for private or business purposes. Future research could also consider how different consumer generations, i.e., Millennials and Generation Z versus Baby Boomers, relate to such sharing economy platforms. Future research could also consider the impact of the geo-political crisis generated by the Russian–Ukrainian war on the use of sharing economy platforms by tourists versus refugees.
Due to the negative impact of mass tourism on the environment (so much discussed and so contradictory), to maximize the positive economic and ecological effects on the resident population by considering the principles of a circular economy, a viable solution could be to design green or environmentally friendly tourist platforms. A green platform is a collaborative platform capable of satisfying the demands of customers in terms of environmental sustainability by offering them more ecological products or services. This means vacations in harmony with the environment, ecological accommodation, ecological cleaning products, bio-food, ecological cosmetics, renewable energy, etc. An example in this regard is the Ecobnb platform built in 2014, which offers a digital platform promoting environmentally friendly tourism offers and putting climate change and sustainability first.

Author Contributions

Conceptualization, D.-C.D., F.-L.I. and S.R.; methodology, D.-C.D. and F.-L.I.; validation, D.-C.D.; formal analysis, D.-C.D.; investigation, L.M.C., F.-L.I. and S.R.; data curation, D.-C.D., L.M.C., F.-L.I. and S.R.; writing—original draft preparation, D.-C.D., L.M.C. and F.-L.I.; writing—review and editing, D.-C.D. and L.M.C.; visualization, D.-C.D. and L.M.C.; supervision, D.-C.D.; funding acquisition, D.-C.D. All authors have read and agreed to the published version of the manuscript.


This research was funded by the Romanian Ministry of Education and Research (CNCS-UEFISCDI, project number PN-III-P1-1.1-TE-2021-0795, within PNCDI III).

Institutional Review Board Statement

This article does not contain any studies with human or animal subjects.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data is available upon request.

Conflicts of Interest

The authors declare no conflict of interest.


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Figure 1. The conceptual model. Source: author’s own development.
Figure 1. The conceptual model. Source: author’s own development.
Sustainability 15 05583 g001
Table 1. Constructs and items.
Table 1. Constructs and items.
ItemMeasureItem Loading
Platform Added Value (PAV) authors own contribution
PAV1I think the platform offers a good price-quality ratio.0.924
PAV2The platform can help fulfil special requests, such as pet-friendly locations or setting up a baby bed.0.907
PAV3It is worth checking in through the platform.0.929
Unique experience (UEX) adapted after [34,44,73,77].
UEX1Staying in a location through the collaborative platform is fun.0.902
UEX2I would enjoy using the platform.0.913
UEX3I always enjoy using this collaborative platform for accommodation.0.909
Social interactions (SIA) were adapted after [37,53,74,86,89,90,91,92].
SIA1The platform offers tourists the opportunity to interact more directly with locals.0.888
SIA2The platform offers visitors opportunities to interact more with other tourists.0.889
SIA3The platform offers guests good social opportunities to interact with hosts.0.881
Platform credibility (PC) adapted after [57,89,95,96,100,137].
PC1I find the platform to be trustworthy.0.931
PC2The platform will honor the promises it made to me.0.920
PC3The promises and assumed commitments are always kept by the platform.0.896
Sustainable Platform (SP) adapted after [8,18,119,120,121,124,125].
SP1Accommodation through the collaborative platform helps to save natural resources.0.945
SP2Accommodation through the collaborative platform is more efficient from the perspective of energy consumption.0.950
SP3Accommodation through the collaborative platform is environmentally friendly.0.930
Platform satisfaction (PSA) adapted after [82,106,107,108,116].
PSA1I am satisfied with the accommodation experience in the location booked through the platform.0.920
PSA2The choice to stay on the platform was a wise one.0.925
PSA3I am satisfied with my interaction with the accommodation provider through the collaborative platform.0.921
PSA4I am satisfied with the information provided by the collaborative platform.0.931
Platform Success (PSS) was adapted after [15,82,113,114,115].
PSS1The platform will be used soon. 0.919
PSS2I will plan my next vacation with the help of this collaborative platform.0.925
PSS3The platform is recommended for making accommodation reservations with others. 0.895
Note: Item loading > 0.7.
Table 2. Creditworthiness indicators of the constructs within the model.
Table 2. Creditworthiness indicators of the constructs within the model.
ConstructCronbach AlphaAverage Variance Extracted (AVE)Composite Reliability (CR)
Platform added value (PAV)0.9090.8460.943
Unique experience (UEX)0.8930.8240.934
Social interactions (SIA)0.8630.7850.916
Platform credibility (PC)0.9030.8380.939
Sustainable platform (SP)0.9360.8870.959
Platform satisfaction (PSA)0.9450.8590.961
Platform success (PSS)0.9000.8330.937
Note: Cronbach’s alpha > 0.7; average variance extracted (AVE) > 0.5; composite reliability > 0.7.
Table 3. Discriminant validity analysis (Fornell–Larcker).
Table 3. Discriminant validity analysis (Fornell–Larcker).
Note: PAV: platform added value; PSA: platform satisfaction; PSS: platform success; PC: platform credibility; SIA: social interactions; SP: sustainable platform; UEX: unique experience.
Table 4. The path coefficients of the structural equation model.
Table 4. The path coefficients of the structural equation model.
PathsPath CoefficientsStandard DeviationT-ValueCI 1p-ValueHypotheses
PAV → PC0.4490.0479.4930.361–0.5390.000 ***H1-Confirmed
UEX → PC0.2630.0436.0990.178–0.3500.000 ***H2-Confirmed
SIA → PC0.0740.0352.0880.007–0.1410.037 *H3-Confirmed
PC → PSA0.8250.03027.8490.761–0.8760.000 ***H4-Confirmed
PSA → PSS0.7530.03819.9560.666–0.8180.000 ***H5-Confirmed
SP → PC0.1370.0443.1400.055–0.2210.001 **H6-Confirmed
SP → PSA0.0970.0313.1530.034–0.1590.001 **H7-Confirmed
SP → PSS0.1240.0373.3490.060–0.2060.001 **H8-Confirmed
Note: * p < 0.05; ** p < 0.01; *** p < 0.001; PAV: platform added value; PSA: platform satisfaction; PSS: platform success; PC: platform credibility; SIA: social interactions; SP: sustainable platform; UEX: unique experience. 1 CI = confidence interval (2.5–97.5%).
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Dabija, D.-C.; Csorba, L.M.; Isac, F.-L.; Rusu, S. Managing Sustainable Sharing Economy Platforms: A Stimulus–Organism–Response Based Structural Equation Modelling on an Emerging Market. Sustainability 2023, 15, 5583.

AMA Style

Dabija D-C, Csorba LM, Isac F-L, Rusu S. Managing Sustainable Sharing Economy Platforms: A Stimulus–Organism–Response Based Structural Equation Modelling on an Emerging Market. Sustainability. 2023; 15(6):5583.

Chicago/Turabian Style

Dabija, Dan-Cristian, Luiela Magdalena Csorba, Florin-Lucian Isac, and Sergiu Rusu. 2023. "Managing Sustainable Sharing Economy Platforms: A Stimulus–Organism–Response Based Structural Equation Modelling on an Emerging Market" Sustainability 15, no. 6: 5583.

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