DETERMINING THE REASONS OF UNIVERSITY STUDENTS 'PARTICIPATION IN ONLINE SHARING PLATFORMS

doi:10.12804/revistas.urosario.edu.co/disertaciones/a.15180

10.12804/revistas.urosario.edu.co/disertaciones/a.15180

AVANCES (Tema Abierto)

DETERMINING THE REASONS OF UNIVERSITY STUDENTS 'PARTICIPATION IN ONLINE SHARING PLATFORMS^*

Determinando las razones de la participación de los estudiantes universitarios en plataformas de intercambio en línea

Determinando os motivos da participação de estudantes universitários em plataformas de compartilhamento on-line

Ayhan Şengöz ¹

Anadolu University (Türkiye)
ayhansengoz@anadolu.edu.tr

^* This article was prepared by the author from his doctoral thesis titled "Determining the Reasons for Participation of University Students in Online Sharing Platforms", completed in the Department of Communication Design and Management at Anadolu University, Institute of Social Sciences. Ethics Committee Approval was received for the study in accordance with the decision numbered 41121 of Anadolu University Social and Human Sciences Scientific Research and Publication Ethics Committee.

Received: January 8,2025
Accepted: April 9,2025
Date of prepublication: June 4,2025

To cite this article: Şengöz, A. (2026). Determining the Reasons of University Students 'Participation in Online Sharing Platforms. Anuario Electrónico de Estudios en Comunicación Social "Disertaciones", 19(1). https://doi.org/10.12804/revistas.urosario.edu.co/disertaciones/a.15180

ABSTRACT

In recent years, consumers, particularly young individuals adept at using information and communication technologies, have shown a growing interest in online sharing platforms. Young people's rapid adoption of these platforms, coupled with increased financial investments and their innovation potential, underscores the importance of studying this phenomenon. However, there is a notable lack of qualitative and quantitative studies exploring the motivations for participation, which are fundamental to understanding user behavior. This study aims to identify why university students participate in online sharing platforms and examine how these motivations influence their intention to participate. The findings are expected to support the development of more user-friendly platforms. A qualitative study with semi-structured interviews was conducted to uncover the factors influencing participation, followed by proposing a conceptual model based on these findings. Structural Equation Modeling (SEM) was employed to test the hypotheses and validate the model. The analysis revealed compatibility between the model and the data, with most hypotheses confirmed. Results indicate that financial benefits, social interaction, trust in comments and ratings, and sustainability significantly enhance participation intentions.

Keywords: online sharing platforms; sharing economy; users attitudes; motivation; participation intention.

RESUMEN

En los últimos años, los consumidores, especialmente los jóvenes con habilidades en el uso de tecnologías de la información y la comunicación, han mostrado un creciente interés por las plataformas de intercambio en línea. La rápida adopción de estas plataformas por parte de los jóvenes, junto con el aumento de las inversiones financieras y su potencial innovador, subraya la importancia de estudiar este fenómeno. Sin embargo, existe una notable escasez de estudios cualitativos y cuantitativos que exploren las motivaciones para participar, las cuales son fundamentales para comprender el comportamiento de los usuarios. Este estudio tiene como objetivo identificar las razones por las cuales los estudiantes universitarios participan en plataformas de intercambio en línea y examinar cómo estas motivaciones influyen en su intención de participar. Se espera que los resultados contribuyan al desarrollo de plataformas más accesibles y centradas en el usuario. Se realizó un estudio cualitativo, con entrevistas semi-estructuradas, para descubrir los factores que influyen en la participación, seguido de la propuesta de un modelo conceptual basado en estos hallazgos. Para poner a prueba las hipótesis y validar el modelo se utilizó el Modelado de Ecuaciones Estructurales. El análisis reveló una compatibilidad entre el modelo y los datos, confirmándose la mayoría de las hipótesis. Los resultados indican que los beneficios económicos, la interacción social, la confianza en los comentarios y valoraciones, y la sostenibilidad incrementan significativamente la intención de participar.

Palabras clave: plataformas de intercambio en línea; economía colaborativa; actitudes de los usuarios; motivación; intención de participación.

RESUMO

Nos últimos anos, consumidores —especialmente jovens, adeptos do uso de tecnologias de informação e comunicação —têm demonstrado crescente interesse por plataformas de compartilhamento on-line. A rápida adoção dessas plataformas por esse público, aliada ao aumento dos investimentos financeiros e ao seu potencial de inovação, reforça a importância do estudo desse fenômeno. No entanto, há uma notável carência de estudos qualitativos e quantitativos que explorem as motivações para a participação, fundamentais para a compreensão do comportamento do usuário. Este estudo tem como objetivo identificar as razões pelas quais estudantes universitários participam de plataformas de compartilhamento on-line e examinar como essas motivações influenciam sua intenção de participação. Espera-se que os resultados apoiem o desenvolvimento de plataformas mais amigáveis ao usuário. Um estudo qualitativo, com entrevistas semiestruturadas, foi conduzido para desvendar os fatores que influenciam a participação, seguido pela proposta de um modelo conceitual com base nesses resultados. A Modelagem de Equações Estruturais (MEE) foi empregada para testar as hipóteses e validar o modelo. A análise revelou compatibilidade entre o modelo e os dados, com a maioria das hipóteses confirmadas. Os resultados indicam que benefícios financeiros, interação social, confiança em comentários e avaliações, e sustentabilidade aumentam significativamente as intenções de participação.

Palavras-chave: plataformas de compartilhamento on-line; economia compartilhada; atitudes dos usuários; motivação; intenção de participação.

Introduction

Advancements in information and communication technologies and the proliferation of personal technological devices have significantly expanded the scope and volume of user interactions. These devices, with capabilities such as global positioning systems and data sharing, have reshaped how individuals engage with one another.

The emergence of early commercial sharing platforms, driven by technological innovation, has led companies and consumers to view sharing as a sustainable and profitable alternative to ownership (Belk, 2007; Botsman & Rogers, 2010). This trend has been further fueled by social media's ability to facilitate the sharing of music, movies, and other content (Galbreth et al., 2012; Gansky, 2010), alongside the rapid expansion of physical product-sharing systems (Benkler, 2004; Gansky, 2010). Sharing platforms represent an economic-technological phenomenon supported by advances in information and communication technology, increased consumer awareness, the proliferation of collaborative web communities, and the growth of social commerce and social sharing (Botsman & Rogers, 2010; Kaplan & Haenlein, 2010; Wang & Zhang, 2012). Consequently, sharing platforms have become globally accessible, extending their reach and scale (Olson & Kemp, 2015). Additionally, advancements in search and matching technologies and payment systems have resolved many challenges associated with buying and selling goods and services online. These platforms now serve as viable alternatives to traditional and online businesses across diverse sectors, including transportation, accommodation, healthcare, education, food delivery, and logistics (Owyang, 2013; OECD, 2016; Chase, 2015).

Unlike traditional sharing, which often occurs within small, localized groups, online sharing platforms operate globally, enabling connections between users worldwide. The study of these platforms intersects with various disciplines, including inequality, security, consumer rights, sustainability, management, and law. Despite their interdisciplinary relevance, research on sharing platforms remains in its infancy. Scholars have defined and conceptualized these platforms using various terms, such as collaborative consumption (Botsman & Rogers, 2010; Keetels, 2013), access-based consumption (Bardhi & Eckhardt, 2012), commercial sharing systems (Lamberton & Rose, 2010), platform and gig economy (Kenney & Zysman, 2016; Friedman, 2014).

For behavior to qualify as participation in a sharing platform, it must meet specific conditions: both the provider and the consumer must retain control over the activity, the exchange must benefit all parties, and the engagement must be deliberate and informed (Belk, 2007; Belk, 2014; Botsman & Rogers, 2010; Giesler, 2006; John, 2013).

The rapid adoption of online sharing platforms, coupled with increasing financial investments and their potential for innovation, underscores the importance of further research (Pagel, 2012). Previous studies have explored dimensions such as workforce dynamics, risk, security, consumer rights, and sustainability. However, there is a notable lack of research on the motivational factors driving consumer attitudes and intentions toward these platforms.

Participation in sharing platforms is often motivated by altruistic values, such as helping others, promoting sustainability, or reducing environmental impact (Prothero et al., 2011). However, these platforms also offer tangible individual benefits, which can strongly influence participation.

With the spread of the Internet and its tools, sharing activities have become possible online. A new production and consumption model has emerged that includes sharing goods and services among users through internet platforms. The goods and services offered on online sharing platforms, the number of users, the income generated, and the investments made in these platforms are increasing. However, the social impact of the platforms is increasing day by day. Although there are significant gaps and deficiencies in the knowledge about online sharing platforms in Turkey, it is important to reveal the potential of this new channel of sharing, the reasons for participation and the factors affecting the intention to participate. In addition, the fact that it is the first time that the factors that motivate the participation intentions of university students, who constitute the group that participates most in online sharing platforms in our country, is investigated and makes the research important. Thus, it is estimated that the information to be collected regarding the participation intentions of the group in question will provide information for platforms, users, and public and private institutions. This study focuses on understanding why university students engage with online sharing platforms and examines the factors influencing their intention to participate. The research process involves three key steps: identifying participation motivations through qualitative research, proposing a model that explains these relationships, and testing the model through empirical analysis.

Theoretical Framework and Research Hypotheses

Studies investigating the motivations behind participation in online sharing platforms often draw from various theoretical foundations. This study adopts Self-Determination Theory (SDT) as its theoretical framework to explain the factors influencing participation intentions.

Originally developed by Edward L. Deci and Richard M. Ryan, SDT has become a pivotal framework for understanding human motivation over the past four decades. At its core, SDT distinguishes between intrinsic and extrinsic motivations. Intrinsic motivation involves engaging in an activity for personal satisfaction, interest, or pleasure, while extrinsic motivation is driven by external rewards, social approval, or the avoidance of negative consequences (Gagné & Deci, 2014; Ryan & Deci, 2017).

What sets SDT apart is its emphasis on the varying degrees of control and autonomy associated with different types of motivation. Intrinsically motivated behaviors are inherently autonomous and voluntary, arising from an individual's self-determined interests and values. In contrast, extrinsically motivated actions may be externally controlled, depending on the extent to which they are imposed or aligned with personal goals (Ryan & Connell, 1989).

The present study applies SDT to understand the underlying themes identified during the qualitative phase and to develop hypotheses exploring how these factors influence participation.

Financial Benefit

Financial benefits relate to earning money, saving time and space, and acquiring goods or services at the lowest cost. These benefits also include avoiding the expenses associated with ownership. Lamberton & Rose (2012) highlight cost savings as a critical determinant of participation in sharing platforms. Frenken & Schor (2017) argue that the direct economic impacts of platform participation are overwhelmingly positive, particularly for younger users, who are often motivated by financial gains (Bócker & Meelen, 2017). Similarly, Bucher, et al. (2016) emphasize that earning or saving money, time, and space serves as a primary driver for participation.

• H1: Financial benefit positively affects perceived benefit.

Social Interaction

Social interactiofn plays a central role in the success of online sharing platforms. These platforms foster a sense of community, enabling users to connect socially and build meaningful relationships. Schor & Fitzmaurice (2015) suggest that, alongside financial benefits, users seek social rewards, such as increased social connections. Albinsson et al. (2018) further underscore the importance of belonging to a community as a key motivation for sharing activities. In this study, social interaction includes engaging with other users, developing relationships, and experiencing a sense of community.

Building on these insights, the following hypotheses were developed:

• H2: social interaction positively affects perceived benefit.

Perceived Benefit

Perceived benefits refer to beliefs about the positive outcomes associated with specific behavior. Hamari et al. (2015) state that entertainment and economic rewards are important intrinsic and extrinsic motivations that determine users' intention to participate in sharing platforms. Mólhmann (2015) found that community belonging and material benefit variables positively affect participation motivations. Schiel (2015) states that there are two basic motivations clearly felt in participation in sharing platforms, adding that one of them is income and practical advantages, and the other is a lifestyle within the framework of social change and interaction. In the context of online sharing platforms, perceived usefulness encompasses users' perceptions of the advantages gained from participation. This study identifies two primary perceived benefits types: financial and social interaction.

• H3: perceived benefit positively affects the intention to participate in online sharing platforms.

Physical/ Financial Risk

Physical/ Financial risk pertains to the possibility of physical harm, bullying, or financial loss resulting from activities conducted on sharing platforms. Examples include defective goods, unmet service expectations, or unsafe situations during physical interactions.

• H4: physical risk positively affects perceived risk.

Social Risk

Social risk involves societal pressures or discomfort users may experience while engaging with sharing platforms. These risks may include the perceived stigma of opening one's home to strangers, traveling with unfamiliar individuals, or engaging in activities that others in their social circle might disapprove of.

The study conceptualized perceived risk as an extrinsic motivator and proposed the following hypotheses:

• H5: social risk positively affects perceived risk.

Perceived Risk

This study defines perceived risk as users' concerns about potential material or moral losses they may incur when engaging with online sharing platforms. It also includes their understanding about the extent to which such losses can be mitigated or compensated. Kim et al. (2015) describe perceived risk as the user's perception of uncertain and potentially negative outcomes associated with platform participation. Two primary types of perceived risks were identified: physical/ financial risk and social risk.

• H6: perceived risk negatively affects the intention to participate in online sharing platforms.

Trust

Trust arises as a critical factor in the presence of risk and uncertainty, facilitating user participation in online sharing platforms (Cook et al., 2005). Within this context, trust refers to users' willingness to engage in transactions or interactions with others despite limited knowledge about them. Numerous studies emphasize that trust is a key determinant of participation in sharing platforms (Keymolen, 2013; Slee, 2015).

This study examines trust through three sub-dimensions: trust in the platform, trust in users, and trust in comments and ratings.

• Trust in the Platform Trust in the platform reflects users' confidence that the platform is honest, reliable, and competent. It includes beliefs that the platform values user privacy, restricts access to personal data to authorized parties, stores transaction data securely, and fulfills its obligations without falsification.

• Trust in Users This dimension refers to users' perceptions of other participants as honest, reliable, and genuine. It also includes the belief that the information provided by these users about goods and services is accurate and trustworthy.

• Trust in Comments and Ratings Comments and ratings allow users to evaluate each other's performance following transactions, playing a vital role in fostering trust relationships (Keymolen, 2013). Peer recommendations are particularly influential, with studies indicating that 78% of consumers trust these over advertisements (Qualman, 2012). This sub-dimension encompasses users' confidence in the accuracy and reliability of reviews and ratings shared by others.

• Based on these sub-dimensions, the following hypotheses are proposed:

• H7: trust in the platform positively affects the intention to participate in online sharing platforms.

• H8: trust in users positively affects the intention to participate in online sharing platforms.

• H9: trust in comments and ratings positively affects the intention to participate in online sharing platforms.

Sustainability

Sustainable consumption seeks to address social and environmental imbalances by encouraging individuals to adopt more responsible behaviors. Online sharing platforms contribute to sustainability by keeping goods in circulation, thereby maximizing usage and extending the life span of individual items. These platforms connect individuals who own unused or underutilized goods with those who want to rent or purchase them, reducing waste and promoting a more efficient system. Research suggests that sustainability indirectly influences sharing behaviors. Hamari et al. (2016) highlight that sustainability serves as an intrinsic motivator for users participating in sharing platforms. This motivation encompasses reducing environmental pollution, conserving natural resources, promoting responsible consumption, and achieving energy savings.

Based on these insights, the following hypothesis was developed:

• H10: perception of sustainability positively affects the intention to participate in online sharing platforms.

Method

This study employed a mixed-methods research design using an exploratory sequential approach. In this design, qualitative data was collected and analyzed first to identify key themes and variables. These findings informed of the subsequent quantitative phase, where a data collection tool was developed to test the relationships among the identified variables. In the widely used typology articulated by Creswell & Clark (2010), three basic designs in mixed methods research are identified: convergent, explanatory sequential, and exploratory sequential designs. In an exploratory sequential design, the qualitative phase precedes the quantitative phase. This design is traditionally employed to inform the development of a new survey instrument and to interpret the two sets of results together.

Consequently, the quantitative results can confirm, validate, or generalize the initial exploratory qualitative findings (Clark & Ivankova, 2015). This approach aimed to generalize insights from the qualitative phase to a larger population. The study received approval from the Anadolu University Social and Human Sciences Scientific Research and Publication Ethics Board (Approval Number: 41121). Additionally, permission for data collection was obtained from the Maltepe University Rectorate (Permission Number: 43660838-605.01).

Qualitative Study

The qualitative phase of this study involved 21 university students from various faculties at Anadolu and Maltepe Universities. Semi-structured interviews were conducted to explore participants' motivations for using online sharing platforms, their platform preferences, the benefits and drawbacks they associate with these platforms, their perceptions of user comments and evaluations, and their views on sustainability and the future of sharing platforms. The interview guide consisted of nine questions addressing these topics. The responses were analyzed to identify key themes which formed the foundation for the subsequent quantitative phase of the research. To ensure the reliability of the data, the researcher's role was clearly explained to the participants, and both the participants and the social context in which the data were collected were described in detail. The data were presented using a descriptive approach, and feedback was sought from other researchers during the data collection and analysis phases.

To evaluate the validity of the findings, a comprehensive literature review was conducted, and consistency checks were made against the identified themes. Input and feedback were also solicited from qualitative research experts to ensure the robustness of the analysis. The themes that emerged and representative participant opinions, are summarized in Table 1.

Table 1. Participants' opinions

Theme		Participant opinion	Participant code
Benefit	Financial benefit	... Sometimes when I go to my family or to my friends out of town, I rent the whole house. Even though it's not much, the money is good...	5
Benefit	Social interaction	... I use both Couchsurfing and Airbnb. I have met very interesting people. I especially like hosting people from abroad...	17
Risk	Physical risk	... staying at someone's house that you don't know. It's okay to be in the city but getting into someone's car that you don't know on an intercity trip takes some courage. Besides, my family doesn't like such things. It becomes a problem later...	10
Risk	Social risk	. ..The lady living in the apartment across the street asks. My son, how many of you are staying? I said I am staying alone. She says that when you are not home, someone comes in and out. She wouldn't understand if I explained. I say they are my friends...	5
Trust	Trust in users	... Everything I buy second-hand, there is always a fault. I bought a table lamp. The part where the cable connects is broken. It lights up and then it doesn't. I bought an iPod. The headphone jack is broken. Of course, I returned it. It's very annoying. The guy wrote that it is in good working order...	1
Trust	Trust in comments and ratings	... I think that comments and ratings are very important. So it definitely affects my decision-making. Anyway, if there is a ranking based on points and comments, I look at everything according to that first...	12
Sustainability		... Yes, of course, I think it contributes. You are not buying something new. It has already been produced, the person who buys it does not need it anymore, you have it. You buy it and use it. Nothing new is produced. You use what already exists. I think this is important...	15

Quantitative Study

The quantitative phase of the research focused on university students enrolled at Anadolu University and Maltepe University. Data were collected from a total of 1,073 students. To ensure the quality of the data, potential distortions were examined using Mahalanobis distance, a statistical method for identifying outliers and data inconsistencies. As a result, 151 responses that did not meet the assumptions of normal distribution were excluded, leaving a final sample size of 922 participants. Of the 922 participants, 506 (54.9%) were female, and 416 (45.1%) were male. Regarding the distribution between universities, 541 participants (58.7%) were from Anadolu University, while 381 participants (41.3%) were from Maltepe University.

Instrument

The scale developed for this study was based on the themes identified during the qualitative research phase. Items were adapted from previous research on the topic to ensure its relevance to the study's theoretical framework and objectives. The scale measures explicitly participants' intention to engage with online sharing platforms, using Self-Determination Theory as its conceptual foundation.

The scale consists of 11 factors, each representing a key aspect of the participants' motivations and attitudes towards online sharing platforms. These factors include:

• Financial Benefit.

• Social Interaction.

• Perceived Benefit.

• Physical Risk.

• Social Risk.

• Perceived Risk.

• Trust in the Platform.

• Trust in Users.

• Trust in Comments and Ratings.

• Sustainability.

• Intention.

To evaluate the validity of the scale, both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were conducted. Before conducting the EFA, Kaiser-Meyer-Olkin (KMO) and Bartlett's Test of Sphericity were applied to assess the suitability of the data for factor analysis. The KMO value was 0.843, indicating that the data were appropriate for factor analysis. Following this, the Varimax rotation method was used to maximize the variance explained by each factor. During this process, eight items were removed due to overlapping distributions and factor loadings lower than 0.30. After eliminating these items, the EFA was rerun, and the KMO value was recalculated at 0.817, further confirming the data's appropriateness for factor analysis. The resulting factor distributions were satisfactory, with the final 11 factors explaining 68% of the total variance. The factor loadings and item distributions can be seen in Table 2.

Table 2. Item distributions and Cronbach's alpha values according to Explanatory Factors

Factors	Factor loadings	Cronbach's alpha values	Factors	Factor loadings	Cronbach's alpha values
Social Int1	.780	.807	Financial Benefit1	.770	.648
Social Int2	.840		Financial Benefit2	.673
Social Int3	.753		Financial Benefit3	.658
Social Int4	.702		Financial Benefit4	.576
Sustainability1	.707	.804	Perceived Benefit!	.576	.728
Sustainability2	.816		Perceived Benefit2	.720
Sustainability4	.828		Perceived Benefit3	.765
Sustainability5	.720		Trust in Comments and Ratings1	.862	.820
Trust in the Plat1	.720	.805	Trust in Comments and Ratings2	.872	.820
Trust in the Plat2	.767		Physical Risk2	.861	.758
Trust in the Plat3	.787		Physical Risk3	.812	.758
Trust in the Plat4	.799		Social Risk1	.885	.732
Trust in Users1	.793	.800	Social Risk2	.874	.732
Trust in Users2	.842		Perceived Risk1	.885	.654
Trust in Users3	.722		Perceived Risk2	.771	.654
Intention1	.838	.795
Intention2	.828
Intention3	.675

Following the Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA) was performed to assess the validity of the scale further. CFA is an essential step before applying Structural Equation Modeling (SEM), as it allows for the confirmation of the factor structure identified in the EFA. In this analysis, Composite Reliability (CR) and Average Variance Extracted (AVE) were used to evaluate the scale's convergent validity and discriminant validity. CR assesses the internal consistency of the factors, while AVE measures the amount of variance in the items that is captured by the underlying factor. The results showed that both CR and AVE values were acceptable, confirming the scale's robustness. The detailed results of the CFA analysis, including the factor loadings and fit indices, can be found in Table 3.

Table 3. Table of values for confirmatory factor analysis

Factors	Factor means	Item Numbers	Item means	Std. Dev	Loadings	Critical ratio	Std. errors
Social Interaction	3.39	SInt1	3.44	1.06	0.70
CR*= ,812		SInt2	3.33	1.07	0.80	19.80	.059
AVE**= ,520		SInt3	3.27	1.08	0.71	18.30	.057
		SInt4	3.49	0.98	0.67	17.33	.051

Sustainability	3.26	Sus1	3.33	0.96	0.62
CR= ,813		Sus2	3.33	0.88	0.77	17.61	.064
AVE= ,525		Sus4	3.28	0.86	0.83	18.15	.066
		Sus5	3.11	0.91	0.66	15.95	.064

Trust in the Platform	2.83	TrustP1	2.67	1.08	0.70
CR= ,804		TrustP2	2.89	1.04	0.69	18.39	.052
AVE= ,509		TrustP3	2.98	1.06	0.62	16.70	.052
		TrustP4	2.77	1.04	0.83	20.73	.056

Trust in Users	2.71	TrustU1	2.59	1.01	0.84
CR= ,820		TrustU2	2.60	0.98	0.89	25.83	.039
AVE= ,611		TrustU3	2.94	0.96	0.58	17.60	.038

Intention	3.44	Int1	3.50	0.84	0.84
CR= ,817		Int2	3.58	0.84	0.88	25.42	.041
AVE= ,605		Int3	3.24	0.93	0.58	17.64	.043

Financial Benefit	3.47	FBen1	3.28	0.97	0.50
CR= ,629		FBen3	3.72	0.91	0.77	10.42	.138
AVE= ,371		FBen4	3.41	1.07	0.52	10.10	.113

Perceived Benefit	3.72	PBen1	3.81	0.77	0.68
CR= , 732		PBen2	3.73	0.83	0.76	17.53	.069
AVE= ,478		PBen3	3.62	0.85	0.63	15.54	.066

Trust in Comments and Ratings	3.96	TrustC1	4.00	0.96	0.87
CR= ,826		TrustC2	3.91	0.96	0.80	17.40	.053
AVE= ,465

Physical Risk	3.94	PRisk2	3.84	0.92	0.75
CR= ,756		PRisk3	4.05	0.87	0.81	15.96	.064
AVE= ,406

Social Risk	2.96	SRisk1	3.07	1.10	0.88
CR= ,750		SRisk2	2.85	1.06	0.66	8.86	.082
AVE= ,403

Perceived Risk	3.11	PRisk1	2.82	0.99	0.50
CR= ,735		PRisk2	3.40	0.91	0.98	7.25	.248
AVE= ,403
GFI: 0.921, AGFI: 0.902, NFI: 0.889, CFI: 0.924, TLI: 0.912, IFI: 0.925, RMR: 0.046, RMSEA: 0.045

Following the Confirmatory Factor Analysis (CFA), Structural Equation Modeling (SEM) was employed to test the relationships among the variables identified in the study's conceptual model. SEM is a powerful statistical technique that allows researchers to examine complex relationships between multiple variables simultaneously. It combines factor analysis and multiple regression analysis elements to evaluate the structure of interrelationships expressed in a set of equations. In SEM, path analysis assesses direct and indirect relationships between variables, testing the strength and direction of these effects. This approach is particularly useful for testing the research hypotheses, as it enables the researcher to evaluate how well the theoretical model fits the observed data. The fit indices for the SEM model, which assess how well the model represents the data, are presented in the previous tables. These indices help determine whether the data support the hypothesized relationships in the model.

Findings

Qualitative Research Findings

All interviewees were familiar with online sharing platforms, having first learned about them through friends or social media. Every participant reported using at least one sharing platform, citing benefits as the primary reason for their engagement. The participants emphasized two main benefits of using sharing platforms: financial gain and social interaction. Many participants mentioned that using these platforms saves them money and access goods or services at a lower cost. Social interaction, particularly through platforms related to accommodation and car sharing, was also a key motivator. Several participants expressed concerns about the risks associated with sharing platforms, especially those related to accommodation and transportation. The main challenges cited were trust in users and social risks. Trust was identified as a significant concern when interacting with strangers, and social risk was often linked to the potential judgment from others in their social circles. Most participants highlighted the importance of comments and ratings when choosing to engage with a platform or a specific user. They considered ratings to be a reliable indicator of user trustworthiness and quality of service. Nearly all participants believed that online sharing platforms contribute positively to sustainability by promoting the reuse of items and reducing waste. Many expressed the view that these platforms would continue to expand in both scale and scope in the future, especially as technological advancements further enhance the capabilities of the platforms and their users.

Quantitative Research Findings

A multivariate analysis of variance (MANOVA) was conducted to examine the relationships between research factors and demographic variables. First, the relationship between gender and participation in sharing platforms was analyzed. The results from Pillai's Trace indicated significant gender differences. The partial eta squared value was 0.079 (p = 0.000), suggesting a meaningful effect. A Bonferroni adjustment was applied to control for Type I errors, tightening the significance level to 0.004.

Significant gender differences were observed in the following factors:

• Perceived Benefit (p = 0.000; ƞp² = 0.013)

• Social Risk (p = 0.000; ƞp² = 0.016)

• Perceived Risk (p = 0.000; ƞp² = 0.009)

• Trust in Platforms (p = 0.001; ƞp² = 0.011)

• Trust in Comments and Ratings (p = 0.000; ƞp²= 0.018)

The findings revealed that women generally perceive more benefits from participating in online sharing platforms than men. They also report higher levels of social and perceived risk, but they have more trust in the platform and the ratings/comments made by other users.

The MANOVA results were also analyzed according to internet usage. The Wilks' Lambda test indicated one significant difference (p = 0.005) with a partial eta squared value of 0.023. The factor with the significant difference was intention to participate in sharing platforms (p = 0.000; ƞp²= 0.010). As internet usage increased, so did the intention to participate in online sharing platforms.

Finally, MANOVA results were examined for differences based on social media usage. Significant differences were observed in two dimensions:

• Social Interaction (p = 0.000; ƞp² = 0.022)

• Intention (p = 0.003; ƞp² = 0.013)

These findings suggest that as social media usage increases, so does the social interaction factor in participation, further contributing to an increased intention to engage with online sharing platforms.

Structural Equation Modeling (SEM) Path Analysis

After conducting the hypothesis tests, seven of the proposed hypotheses were confirmed, while three were rejected. The effect sizes, which indicate the strength of the relationships between the factors in the model, are shown in Table 5.

Table 5. SEM path analysis results

Hyp.	Path	Std. Est.	Unstd. Est.	Cr	S.E	p	S/NS
H1	Financial Benefit — Perceived Benefit	.428	.399	7.902	.051	***	S
H2	Social Interaction — Perceived Benefit	.470	.371	10.008	.037	***	S
H3	Perceived Benefit — Intention	.298	.404	7.480	.054	***	S
H4	Physical Risk — Perceived Risk	.383	.260	5.292	.049	***	S
H5	Sosyal risk — Perceived Risk	.105	.073	2.713	.027	.007	S
H6	Perceived Risk — Intention	.005	.008	.181	.045	.856	NS
H7	Trust in the Platform — Intention	.064	.051	1.430	.036	.153	NS
H8	Trust in Users — Intention	.012	.015	.264	.055	.792	NS
H9	Trust in Comments and Ratings — Intention	.250	.226	6.650	.034	***	S
H10	Sustainability — Intention	.290	.342	7.168	.048	***	S
GFI: 0.921, AGFI: 0.902, NFI: 0.889, CFI: 0.924, TLI: 0.912, IFI: 0.925, RMR: 0.046, RMSEA: 0.045

^*** p<0,001

Both financial benefit and social interaction were found to affect perceived benefit positively. As material benefit and social interaction increase, so does the perceived benefit of participating in online sharing platforms. This increase in perceived benefit, in turn, positively influences the intention to participate. Increased physical and social risks led to a higher perception of perceived risk. However, contrary to expectations, perceived risk did not negatively affect participation intention. The hypothesis regarding the negative impact of perceived risk on participation intention was not confirmed. The hypotheses predicting that trust in the platform and trust in users would positively affect participation intention were not supported. In other words, participants' trust in the platform and other users did not significantly influence their intention to engage with online sharing platforms. On the other hand, trust in comments and ratings was positively associated with participation intention. This suggests that as participants' trust in comments and ratings increases, so does their intention to participate in sharing platforms. This finding highlights the importance of user feedback in shaping participation behaviors. Finally, the hypothesis suggesting that an increased perception of sustainability would positively influence participation intention was confirmed. Participants who believed that online sharing platforms contribute to sustainability were more likely to intend to participate in these platforms.

Discussion and Conclusion

Results Regarding Demographic Findings

The frequency of sharing among participants does not significantly differ by gender, university, age, or income. Van de Glind (2013) highlights that women share more and are more willing to join sharing platforms, while willingness declines with increasing age and income. OECD (2016) reports that individuals aged 18-29 use sharing platforms two to three times more than older groups, both as providers and consumers. In Turkey, 47% of 18-29-year-olds use such platforms compared to 34% of the overall population. Owyang et al. (2014) note that collaborative consumption services are mainly used by young people from their teens to mid-thirties across various socioeconomic backgrounds.

The lack of significant variation in sharing frequency in this study may be attributed to the homogeneous demographic structure of the sample. In a study involving participants with a broader range of ages, income levels, and education, sharing frequency might differ according to these variables. Multivariate analysis of variance was applied to evaluate the relationship between demographic variables and the eleven dimensions of the sharing platform participation model. Regarding gender, significant differences were observed in perceived benefit, social risk, perceived risk, and trust in platforms and comments and ratings. Women perceive greater benefits from participating in online sharing platforms. However, although they trust platforms, comments, and ratings more than men, their risk perception is also higher than men's. Regarding age groups, significant differences were found in perceived benefit, social risk, perceived risk, and trust in platforms and comments and ratings. Older students perceive greater benefits from using platforms and exhibit higher trust in platforms, comments/ratings, and increased risk perception. This may be attributed to their more excellent experience with using such platforms. Conversely, younger users with less experience have lower perceptions of benefit, trust, and risk. These patterns could be reversed in a broader age-based study. Bócker (2017, p.36) notes that younger groups are more economically motivated to use shared assets. Among university students, social interaction increases with academic progression, showing a significant correlation. Higher internet and social media usage are linked to greater participation in online sharing platforms, with social media particularly enhancing social interaction. All interviewed students were aware of online sharing platforms, mainly through friends, the internet, or social media, and actively used at least one. The most popular platforms involve buying and selling assets (e.g., eBay, Sahibinden, Letgo, Dolap), while rental and service-matching platforms are less commonly used. This behavior aligns with Botsman & Rogers' (2010) concepts of critical mass and social proof key to sustaining sharing platforms and competing with traditional shopping. Early adopters create social proof, encouraging wider adoption and reducing psychological resistance. University students' tech-savvy nature fosters both critical mass and social proof, vital for sharing platform growth.

Results Regarding Structural Equation Modeling

The results reveal a positive and highly significant relationship between material and perceived benefit (p = 0.428, t = 7.902, p < 0.001). Sharing platforms offer substantial material benefits for users, both as providers and consumers. For consumers, prices are lower due to reduced transaction costs, minimized labor expenses, avoidance of regulatory fees, and the absence of branding costs. Additionally, platforms often provide lower-quality but more affordable options. For providers, these platforms offer opportunities to earn or save money.

The qualitative findings corroborate these results, showing that students frequently purchase low-quality second-hand products, rent items they do not need permanently, sell unused possessions, or find cost-effective transportation options. Some even rent out parts or the entirety of their homes to gain financial benefits or reduce costs.

Material benefits significantly influence users' perceived benefits, affecting their participation intentions. In the research model, factors not only influence each other directly but also interact indirectly, as shown through path analysis. Financial benefit exerts a significant indirect effect on intention through perceived benefit (p = 0.127, p = 0.001). Increasing perceived financial benefit enhances users' intentions to use sharing platforms.

Previous studies on participation motivations in online sharing platforms consistently highlight financial benefit as a strong motivator (Lamberton & Rose, 2012; Hamari et al., 2016; Bellotti, 2015; Móhlmann, 2015; Schor, 2015; Bocker & Meelen, 2016; Bucher, 2017). The findings of this study align closely with these earlier results.

The emergence of sharing platforms makes sharing more attractive for users, expanding its application to a broader social scale. On some sharing platforms, a new form of social interaction arises as users come together and meet face-to-face during or after the transaction process. According to Schor et al. (2016), there is a widespread claim of "common benefit" in sharing platforms. This refers to the advantages of meeting new people, making friends, and getting to know others. Platforms that facilitate accommodation, car sharing, and service matching are observed to be more successful in fostering new social interactions.

Parigi et al. (2013), Schor (2015), highlight that such platforms help users engage in social interaction, meet new people, make friends, and feel a sense of belonging to a community. Students interviewed as part of this research emphasized that social interaction is significant for them when using accommodation platforms. However, they noted that they carefully choose the users with whom they interact, with user profiles being a decisive factor. Some students even reported that in certain cases, they are willing to forgo some or all of the financial gains to establish the desired social connection.

The relationship between social interaction and perceived benefit reveals a positive and highly significant correlation (p = 0.470, t = 10.008, p < 0.001). This finding aligns with the observations of Bocker & Meelen (2016), who stated that individuals willing to share their homes often have social motivations in addition to economic ones, and Schor and Fitzmaurice (2014), who noted that users of sharing platforms expect both social and economic benefits to satisfy their desire for increased social connections. Social interaction has a significant (p = .001) indirect effect (p = .140) on usage intention through perceived benefit. Thus, increasing users' perceptions of social interaction indirectly enhances their intention to use these platforms.

On the other hand, Hamari et al. (2016) argue that extrinsic motivations, such as financial benefits, tend to overshadow initial intrinsic motivations over time. Even if users initially join platforms for intrinsic reasons, their motivations may later shift toward extrinsic ones. Frenken & Schor (2017) predict that early adopters of sharing platforms are more open to social interaction but that this tendency may diminish as participation increases for financial and economic reasons.

Perceived benefits refer to users' perceptions of the potential positive values associated with participation in the sharing economy. Material benefits and social interaction were identified as the two most significant positive values, and, as expected, they were found to affect perceived benefits positively and indirectly influence participation intention. The perceived benefits dimension, which was significantly influenced by these two sub-dimensions, also positively and significantly affected participation intention (p = 0.298, t = 7.480, p < 0.001). As the perceived benefits of the platforms increase, users' participation intentions also increase.

Another group of factors examined in the study includes risk factors. Perceived risk represents users' concerns about material or moral loss or damage that may result from actions taken on online sharing platforms and the compensation for such losses or damages. Three types of perceived risk were identified in relation to user participation in sharing platforms: physical/material risk, social risk, and legal risk. However, since the factor loadings for the statements related to legal risk were below 0.30, this dimension was excluded from the analysis.

Physical/material risk refers to physical harm, harassment, or material losses that users may experience due to activities conducted on the platforms. The analyses revealed that both physical risk (p = 0.298, t = 7.480, p < 0.001) and social risk (p = 0.298, t = 7.480, p = 0.007) positively and significantly affect perceived risk. Increased physical or social risks contribute to a heightened perception of risk.

Sharing platforms, particularly those involving vehicle/travel sharing and participation in accommodation services, often involve physical interactions. These scenarios inherently carry physical and social risks, which are believed to influence users' participation intentions. For instance, some students who participated in semi-structured interviews expressed concerns about the risks of staying in a stranger's house or engaging in intercity travel. They also noted that such activities might not be socially acceptable within their immediate environment.

However, the test results indicated no significant relationship between perceived risk and participation intention (p = 0.005, t = 0.181, p > 0.05). In other words, while students acknowledge the presence of physical or social risks in using sharing platforms, these risks do not appear to influence their participation intentions.

Trust is the willingness of one party to be vulnerable to the actions of another party, based on the expectation that the other party will perform an important action to the trustor, irrespective of the ability to monitor or control the other party (Mayer et al., 1995). In online sharing platforms, trust involves sharing and interacting with other users without sufficient knowledge about them or their behavior. As noted in numerous studies, trust is one of the most influential factors driving participation (Botsman & Rogers, 2010; Keymolen, 2013; Slee, 2013). According to Hamari et al. (2016), trust can be a fundamental antecedent to sharing intention. Similarly, Botsman & Rogers (2010) emphasize that trust is a key success factor in sharing.

With user participation in online sharing platforms, trust is analyzed in three sub-dimensions: trust in the platform, trust in other users, and trust in comments and ratings.

An important actor in online sharing platforms is the platform itself. These platforms, which can be defined as an online intermediary, vary significantly in their user relationships and the degree of user participation they facilitate. Sharing platforms represent two-sided or multi-sided markets that serve both providers of goods and services and consumers who demand them. The primary role of many sharing platforms is to facilitate, organize, and mediate user activities. Specifically, key functions of peer platforms include providing search capabilities, matching providers with consumers, establishing reputation and trust-building mechanisms, and exercising varying degrees of control over sharing and user interactions. These platforms aim to reduce users' anxiety and uncertainty about transactions.

Based on this information, it is hypothesized in this study that users' trust in platforms affects their participation intentions. However, analysis results show no significant relationship between trust in the platform and participation intention (p = 0.064, t = 1.430, p > 0.05). Research by Hawlitschek (2016) indicates that the trust relationship between providers and the platform is much stronger than between consumers and the platform. This highlights the platform's ability to create events and direct users to list items, as well as the fact that providers often share a range of personal data and must trust the platform in cases of unexpected returns or damages.

Thus, platforms should appear trustworthy to generate business and manage the mutual perceptions of their users and the resources exchanged on the platform. According to OECD (2016), young consumers trust sharing platforms more than older groups, with this trust increasing among participants who use the platforms more intensively. Many researchers have stated that trust reduces uncertainty and risk while increasing participation and transaction intentions. For example, Keetels (2013) argues that participants are significantly more willing to engage when strong verification mechanisms, insurance guarantees, comprehensive information about other participants, and robust cooperation norms are in place. Lampinen (2015) goes further, noting that even in cases where participation does not require direct financial investment and the associated social and material benefits are desirable, a lack of trust can hinder the adoption of peer-to-peer exchanges.

However, our research did not find evidence to support the claim that increased trust in the platform enhances participation intention.

Keymolen (2013) argues that person-to-person trust plays a central role in highly interactive societies and sharing platforms. The more central a sharing partner is to a user's extended self, the more likely they are to share with that person. Lamberton and Rose (2012) state that communication about the identity of potential sharing partners and their mutual trust can reduce the perceived risk of participating in sharing platforms, thereby influencing participation intention. The study predicts that when users exhibit high trust in each other's abilities, goodwill, and honesty, their participation intention will similarly increase.

However, the analysis results indicate no significant relationship between trust in users and participation intention (p = 0.064, t = 1.430, p > 0.05). Regarding why trust in both the platform and its users does not significantly affect participation intention, Lamberton & Rose (2012) highlight the limitations in the goods and services demanded by users. In other words, the desire to access specific goods and services may overshadow trust considerations. Research conducted by the OECD (2016) further demonstrates that while trust in the seller or provider offering a product or service is important, consumers don't have to proceed with a transaction. Even when users lack trust in the seller or provider, they often continue transactions if the anticipated financial benefits outweigh potential risks.

This finding suggests that the cost-benefit dynamics of the transaction influence consumers' trust calculations. Sharing platforms play a significant role in mitigating users' doubts about each other. When examining the research results, it becomes evident that while trust in users is desirable, it is not indispensable. This underscores that user trust is multifaceted and shaped by various factors rather than a singular determinant.

Comment and rating systems actively create and shape trust relationships (Keymolen, 2013). According to Frenken & Schor (2017), comments and ratings constitute a significant part of the platform's value. Although platform users generate comments and ratings, the value produced is allocated by the platform itself. Analyzing the research results reveals a positive and significant relationship between trust in comments and ratings and participation intention (p = 0.250, t = 6.650, p < 0.001). As trust in comments and ratings increases, participation intention also rises.

In the qualitative dimension of the research, interviewed students stated that comments and ratings are important to them and that they consider these factors in the transactions they conduct on platforms. Additionally, the students highlighted their sensitivity to the presence of fake or dishonest ratings and reviews, emphasizing that such inauthentic feedback poses a significant problem. Frenken & Schor (2017) note that the quality of ratings may diminish the importance of social connections on sharing platforms. As participants accumulate more ratings over time, their self-confidence increases, reducing the need for face-to-face interaction on some platforms.

It provides many benefits, such as saving resources, increasing efficiency, and reducing energy dependency, pollution, and waste. Society is growing awareness about the environmental impact of consumption habits. Second-hand sales, rentals, and shared use maximize the use of goods and reduce the impact of physical products that were once purchased and discarded after limited use. Many sharing platforms describe themselves as environmentally friendly and their operations as reducing their carbon footprint. Chase (2015) states that the ideas embodied in sharing platforms are "the only way to meet the speed, scale, and local adaptation requirements to address climate change over time". Botsman & Rogers (2010) state that people have evolved from a sense of self-interest to a sense of the common good. In addition, it is unexpected that sustainability is the primary and driving motivation for a platform or consumer. It is assumed that sharing is environmentally friendly and will reduce the demand for new products. However, there is no scientific research proving these claims. Sustainability is the last factor in the model that is thought to affect participation intention. As a result of the test, it was found that students' perception of sustainability has a significant effect on participation intention (p = 0.290, t = 7.168, p < 0.001). As the belief among students that sharing platforms contribute to sustainability increases, their intention to participate also increases. Hamari et al. (2015) findings support the idea that viewing transactions on sharing platforms as sustainable activities can increase participation. In the interviews, some students emphasized that the contribution provided by the platforms may be minimal and that official, private, and international institutions should take various steps toward creating a sustainable world. Schor (2015) states that platforms create new markets that expand trade volume and increase purchasing power, increasing consumption. In this case, their environmental impacts are negative rather than positive.

Limitations and Suggestions for Future Research

This study, like any other, has several limitations. First, it is confined to university students, known to be the primary users of online sharing platforms. Future research could expand the sample to include a broader demographic, such as individuals from different age groups, education levels, and professional backgrounds, to provide a more comprehensive understanding of participation motives across populations.

Second, this study focused on 10 variables identified through semi-structured interviews with university students. Other important factors influencing participation intention may have been overlooked. Future qualitative studies could explore additional variables that might affect participation, helping to enrich the findings of this research.

Additionally, this study treated online sharing platforms as a general category. However, sharing platforms vary in focus, such as asset sales, service provision, vehicle sharing, and accommodation. Future research could examine participation motives specific to different platforms, as factors influencing participation are likely to differ depending on the platform's purpose.

Another limitation is the lack of distinction between consumers and providers of sharing services. It is expected that the motivations of consumers and providers will differ, and future studies could separately analyze these groups to identify distinct patterns of behavior and intention.

The theoretical framework of this study was based on Self-Determination Theory, which focuses on intrinsic and extrinsic motivations. Future studies could explore alternative theoretical frameworks to compare the results and provide a more nuanced understanding of the factors influencing participation in sharing platforms.

Furthermore, this study did not consider the influence of cultural differences on participation behavior. As cultural contexts can significantly shape individual behaviors and attitudes, future research should investigate how cultural factors impact participation in online sharing platforms. Such studies could provide valuable insights into the global adoption of sharing platforms and their adaptation to diverse cultural environments.

DETERMINING THE REASONS OF UNIVERSITY STUDENTS 'PARTICIPATION IN ONLINE SHARING PLATFORMS*

Determinando las razones de la participación de los estudiantes universitarios en plataformas de intercambio en línea

Determinando os motivos da participação de estudantes universitários em plataformas de compartilhamento on-line

DETERMINING THE REASONS OF UNIVERSITY STUDENTS 'PARTICIPATION IN ONLINE SHARING PLATFORMS^*