Gadjah Mada International Journal of Business Vol.
No.
2 (May-August 2.
: 175-197 Attitudinal Factors Influencing Digital Collaborative Consumption Among Internet Users:
A Confirmatory Study in IndonesiaAU Lukni Burhanuddin Ahmada*.
Reza Ashari Nasutionb.
Devi Arnitab Universitas Jenderal Achmad Yani.
Indonesia Institut Teknologi Bandung.
Indonesia Abstract: There has been a substantial surge in people participating in collaborative consumption (CC) over the past few years, particularly on digital platforms.
This phenomenon has encouraged some researchers to explore the motivational factors affecting user intention to use CC.
However, the previous research has predominantly concentrated on identifying these factors in the context of CC service, with limited attention specifying the digital platform where the interaction among users is different.
Hwang and Griffiths's model of intention that predicts the behavioral intention of millennials' participation in CC is unique in a way that it recognizes both attitude and empathy as the main factors affecting intention to use a CC platform.
The model could be relevant for CC, as it covers different values such as utilitarian, hedonic, and symbolic values.
This study has developed a model to make it comprehensive by adding several factors from past research: perceived behavioral control and online initial trust.
We tested the model in the Indonesian context using partial least squares regression.
One of the worldAos most populous countries.
Indonesia provides a thought-provoking digital CC practice opportunity.
The results show that empathy and online initial trust are not significant predictors of intention to participate in CC.
In addition, utilitarian value is not a significant predictor of attitude toward participating in CC.
Thus, attitude is the critical factor affecting intention to participate in CC, and perceived usefulness, perceived ease of use, and hedonic and symbolic values are significant predictors of the effect of attitude on participation in CC.
This study can provide valuable insight for those startup practitioners who create this type of business model, characterized by its rapid change and volatile nature.
The results could play a role in guiding marketers specializing in CC to enhance their apps using effective tactics or strategies, thereby improving the customerAos participation on their platform.
Keywords: collaborative consumption, digital, technology, e-commerce, startup, sharing economy, user intention JEL Classification: M300.
M310 *Corresponding authorAos e-mail: lukni.
burhanuddin@lecture.
ISSN: PRINT 1411-1128 | ONLINE 2338-7238
https://journal.
id/gamaijb Gadjah Mada International Journal of Business - May-August.
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Introduction The development of digital technology has created innovative business models that broaden customer reach, expand market opportunities, and enhance operational efficiency (Astuti & Nasution, 2.
Among those models, the platform-based digital business has emerged as the most popular one, notably the collaborative consumption model (CC) (Barnes & Mattsson, 2.
Digital CC has been applied to various activities from selling and buying .
, olx.
id, bukalapak.
com, and tokopedia.
, to renting .
Ru mah123.
com and Urbanindo.
, and offering services .
Gojek and Gra.
(Noviantoro et al.
, 2020.
Fauzi & Sheng, 2020.
Pratama, 2.
Generally, collaborative consumption aims to maximize the utilization of products and reduce the financial burden of ownership through the collaborative use of the products among the involved parties (Benjaafar et al.
, 2.
The PWC report by Lieberman .
presents data indicating a rising trend of individuals participating in CC as evidenced by increasing numbers year after year.
The report projects substantial growth within the sharing economy sector, an interchangeable concept associated with CC (Minami, et al.
The report forecasts a potential global revenue escalation from USD 15 billion in 2014 to an estimated USD 355 billion by 2025.
The trend of sharing, which enables individuals and groups to generate income from underused assets, is facilitated by digital platforms that foster unique user interactions.
In the realm of digital CC, the motivational factors that drive users to engage in CC are not solely influenced by the service offered but also by the platform itself.
The majority of existing research mostly focuses on identifying the influential factors in the context of CC services, with limited exploration specifically in the digital domain, such as the study conducted by Mayasari & Haryanto .
A study conducted by Hwang and Griffiths .
is considered a notable contribution to the field of CC research.
They proposed a model that predicts the behavioral intention of millennials' participation in CC.
They suggested that users' cognitive perception and affective attitude will be the main drivers of the intention.
The PWC research data suggests that a significant proportion of potential users of CC fall within the millennial age range, which accounts for the majority of the respondents in this study.
The current research could also benefit from incorporating relevant constructs as stated by Goyal.
Maity.
Thamizhvanan, & Xavier .
Chen & Barnes .
Kim & Ahn .
Pavlou & Gefen .
Sun .
Shadkam .
Becerra & Korgaonkar .
Kim .
Schlaegel .
, and Hsu.
Chuang, & Hsu .
, which highlight that online initial trust and perceived behavioral control are significant drivers of intention to use digital platforms.
Moreover, given the current researchAos emphasis on CC users' participation in digital platforms, it is appropriate to consider the applicability of the technology acceptance model (TAM) as a suitable dimension.
The perceived usefulness and perceived ease of use of digital platforms play essential roles in influencing people's intentions to use digital platforms according to the TAM (Cheah.
Phau, & Liang .
Dakduk.
Ter Horst.
Santalla.
Molina, & MalaveA .
Therefore.
Hwang and GriffithAos .
model will be more comprehensive if we add those constructs.
Our study aims to enhance the existing model of CC by Hwang and Griffiths .
by incorporating other relevant variables, namely online initial trust (OIT) and perceived behavioral control (PBC), as well as the TAM, to reinforce the digital CC participation theory that provide valuable insight for the startup practitioners who create this Ahmad et al type of business model.
We tested the model in the Indonesian context.
The country is one of the worldAos most populous countries and is considered to provide a thought-provoking opportunity for digital business, particularly in terms of CC practice, as reported by the Indonesian Ministry of Communications and Informatics .
Several startups in Indonesia have emerged within the context of CC realms.
For instance, social crowdfunding (Kitabis.
, peer-to-peer lending (Investree.
Amarth.
, ride-hailing (Gojek.
Gra.
, educational (Ruangguru.
Rumah Belaja.
, and healthcare (Halodoc.
Alodokte.
(Barnes & Mattsson, 2016.
Santoso & Erdaka, 2015.
Sevisari & Reichenberger, 2.
This paper is organized into six sections.
Section 2 discusses the literature review and hypotheses development.
Section 3 outlines the method of study.
Section 4 describes the analysis.
The findings are then discussed in Section 5.
Finally.
Section 6 concludes our studies, discusses the implications, provides directions for future research, and explains the limitations of our work.
Literature Review In line with its aim to enhance and use the research model previously used by Hwang and Griffiths .
, this study draws on other research that is relevant to this investigation.
Their research is based on two theoretical frameworks: the cognitive hierarchy model and the theory of reasoned action, both of which explore the value-attitude-intention relationship, which plays a crucial role in all marketing activities (Holbrook, 1.
Additionally, empathy is included in the model because this variable is highly correlated with prosocial behavior, one of the motivating factors to participate in a sharing economy Furthermore, the model incorporates two relevant theories related to the acceptance of technology by users, the technology acceptance model (TAM) and the unified theory of acceptance and use of technology (UTAUT).
The TAM primarily focuses on the ease of use and usefulness of the technology (Davis, 1.
, while the UTAUT emphasizes the attainability of the technology itself through the construct of perceived behavior control (PBC) (Venkatesh et al.
, 2003.
Additionally, given that digital CC is a social activity facilitated by a digital platform, anonymity becomes crucial as it acts as a barrier for users to use this service.
Consequently, this research includes online initial trust (OIT) as the control variable that potentially influences users' intention of digital CC.
Online Collaborative Consumption The term CC describes a socio-economic model implemented with technology where a group of people shares the use of the products or services to reduce the economic cost of ownership (Piscicelli et al.
, 2015.
Raice, 2.
The practice might refer to renting, sharing, borrowing, bartering, lending, swapping, and gifting (Piscicelli.
Cooper, and Fisher, 2.
In other words.
CC is the share of usage of products or services through a digital platform.
Sharing, in BelkAos .
definition, refers to a public act that ties us to other people and the way we connect with others and the solidarity and connection that Botsman & Rogers .
propose three CC models: product/service system, redistribution markets, and collaborative lifestyles.
The difference between them lies in the company's role .
, profit, non-profit, or publi.
, the ownership transfer level, the type of trading activity .
, lending or rentin.
, and whether economic transactions take place or not (Botsman & Rogers, 2010.
Hamari et al.
, 2.
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Intention to Use Collaborative Consumption Several studies have reported the motivation for participation in CC practices.
Hwang & GriffithsAos .
study assesses the intention to use CC among millennials and points out that cognitive value perceptions and affective attitudes affect users' intention to use CC.
Nelson.
Rademacher, & Paek .
identify four motives for people sharing their economic properties with others: decluttering, financial factors .
, saving money, obtaining bargain.
, environmental concern, and desire for social value.
Another study by Lamberton and Rose (Lamberton and Rose, 2.
suggests that product availability is a key influencing factor affecting CC initiation.
When the participants believe the item they are looking for is unavailable, they will participate in a CC activity.
Then.
Belk .
mentions product affordability as another critical factor.
He states that some relatively unaffordable items, like cars, motivate people to participate in CC to be able to utilize the car without having to own it.
Finally, our study on the motivation behind individual participation in CC results in the conceptual model as presented in Figure 1.
Figure 1.
Conceptual Model Attitude towards Collaborative Consumption Due to the strength of its empirical support and theoretical basis, the technology acceptance model (TAM) (Davis, 1.
has been extensively adopted by several researchers to describe the intentions of a user and his/her actual behaviors on a particular technology (Al-Emran et al.
, 2018.
Keen et al.
, 2.
Behavioral intention refers to the strength of oneAos intention to engage in a particular behavior (Fishbein and Ajzen, 1.
Meaning that identifying the intention to use can help determine actual behavior in users' decision-making process to use a technology or platform (Y.
Wang et al.
, 2020.
Hwang & Griffiths, 2017.
Zhang et al.
, 2.
Besides, consumersAo use intention is strongly considered to become a market penetration indicator when a startup establishes a new product (Merhi.
Hone, and Tarhini, 2.
Ahmad et al According to the TAM, consumers' intention on particular technology is influenced by the consumers' attitude toward that technology (Khare & Sadachar, 2014.
Wu & Chen, 2.
One's attitude toward any technology can be predicted with a high degree of accuracy from the knowledge of the user's beliefs about the technology and the evaluation aspect of these beliefs (Fishbein and Ajzen, 1.
In other words, consumers are more likely to use new technology, in this case, the digital CC platform, when they believe that the platform will benefit them, i.
, increase work performance.
Hence:
H1: Attitude toward the online CC platform positively correlates with the behavioral intention to use the platform.
Perceived Behavioral Control The unified theory of acceptance and use of technology (UTAUT) puts perceived behavioral control (PBC) as one variable indicating a person's trigger to act on intention to behavior (Venkatesh et al.
, 2003.
UTAUT defines PCB as an individualAos has perceived difficulty or ease to do a specific behavior, according to the theory of planned behavior (TPB) proposed by Ajzen .
It is believed that the total of obtainable control beliefs could determine perceived behavioral control.
PCB describes how easy or difficult the user can do behavioral intentions (Al-Emran et al.
, 2.
Control beliefs are explained as the existence of an element that can facilitate or hinder action in behavioral reason.
When the PBC is higher, the more chance the behavior will arise (Chien et al.
, 2014.
Dakduk et al.
, 2.
According to Mathieson.
Peacock, & Chin .
and Sembada & Koay .
PCB is related to the person who thinks their power can manipulate control.
this research, from the perspective of user control.
PCB variables can complete the model while using a digital-based platform.
The person who is more experienced with the digital platform .
igital native.
will certainly have a higher degree of CC use compared to non-digital natives due to their computer technical skills when using it (Mittendorf, 2.
Another higher PBC level can also be seen from the resources perspective (Roos & Hahn.
Sembada & Koay, 2.
This AoresourceAo can refer to the type of userAos gadget when connected to the network or how capable the connectivity supports them when using the digital platform.
The ability to use the digital platform and the resource to access its CC platform are essential.
H2: Perceived behavioral control positively correlates with the behavioral intention to use the online CC platform.
Empathy Hwang and GriffithsAos .
model regarding CCAos behavioral intention states that empathy is the critical factor influencing a CC userAos intention.
Empathy is a prosocial behavior that arises from a user attaching to another individual's feelings (Eisenberg and Miller, 1.
Other research explores empathy in the individual motivation contexts to help others who need altruistic action based on attaching to others' perspectives (Hwang and Griffiths, 2.
Empathy has multidimensional variables, according to Escalas & Stern .
Another dimension alongside the personAos feeling of attachment, empathy, could refer to an outcome of cognitive or perceptual practices (Eisenberg.
Wentzel, and Harris, 1.
and also feeling sympathy, concern, and compassion (Batson, 2014.
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et al.
, 2.
The various perceptions of empathy's position also serve to divide the item into two: emotional empathy and cognitive empathy (Parra, 2.
Emotional empathy is considered to be allocating the emotion, while cognitive empathy is more considered to be the capability to adapt to the otherAos perspective.
Marimon.
Llach.
Alonso-Almeida, & Mas-MachucaAos .
and Hwang and GriffithsAos .
studies assimilate empathy to understand how consumers intend to use and buy or rent the CC of services/products served by the venture from the emotional aspect.
Meanwhile, in this study, we propose empathy as a construct indicating the userAos emotional feeling to attach with other users through the platform, and it can release feelings of concern toward it according to CC in the digital platform.
An experiment related to ad response conducted by Escalas and Stern .
shows that consumer empathy affects the customer's attitude toward the advertisement.
Therefore, connecting the line with this prosocial behavior of CC, the following statement is hypothesized.
H3: Empathy influences the behavioral intention to use CC through an online platform.
Online Initial Trust Trust in online platforms is categorized into three perspectives: technical-based dimension, the uncertainty of transaction, and competency-based reputation (Yoon.
Doney & Cannon, 1997.
Heijden et al.
, 2003.
Koufaris & Hampton-Sosa, 2.
The technical-based perspective correlates with the technical aspect of an online platform and how the users can obtain it, such as web searching, website or app presentation, and the technology itself.
The uncertainty of transactions is more related to how online apps assure security.
The competency-based perspective will be tightly correlated with the brand reputation of the website or application, interaction, and fulfillment.
Trust is a set of beliefs, including ability, integrity, and benevolence (Svare et al.
, 2020.
Mayer et al.
, 1.
It is an eagerness of an individual to be indefensible to othersAo behavior.
In comparison.
Pappas (Pappas, 2.
and Rempel.
Holmes, & Zanna .
state there is a feeling of confidence and security that responds to other parties.
When trust exists, the organization do not have to invest on expensive and complex infrastructures as security can be attained through simpler means due to mutual trust among individual (Susilo et al, 2.
Therefore, trust in the model will complete the factor influencing the digital userAos intention to use the CC platform.
H10: Online initial trust positively influences the behavioral intention to CC through an online platform.
Factors Influencing Attitude toward Collaborative Consumption Perceived Ease of Use and Perceived Usefulness Perceived ease of use refers to the technology acceptance model proposed by Davis (Davis, 1.
perceived ease of use is correlated with an individualAos belief that the technology usage will offer an effortless experience that will directly or indirectly affect the Another study conducted by Hansen.
Saridakis, & Benson .
Inegbedion .
, and Hsieh.
Rai, & Keil .
finds that perceived ease of use has a significant influence on driving the continuance of technology use.
In this study, the ease of use will be Ahmad et al correlated with the userAos comfortability and effortless usage.
According to Chu & Lu .
, whose research is related to the music platform, perceive usefulness as being how users believe that listening to music will fulfill a particular purpose.
Chiu.
Lin, & Tang .
state that several empirical studies confirm the significance between perceived ease of use and perceived usefulness with intention.
Davis .
also proposes that perceived usefulness is a highly significant predictor construct of attitudes to implement new technology at two distinct periods in the word processing software context.
Other similar studies conducted by Mathieson.
Peacock, & Chin .
Venkatesh.
Morris.
Davis, & Davis .
Szajna .
Agarwal & Karahanna .
, and Adams.
Nelson, & Todd .
also support the idea.
The modification of the TAM used for information technology (IT) is also validated by Yoon .
Therefore, if we correlate those previous studies with this research in the CC context, we might say that using the CC platform will fulfill the user's purpose.
H4: Perceived ease of use positively influences the attitude toward CC through an online platform.
H5: Perceived usefulness positively influences the attitude toward CC through an online platform.
Utilitarian Value.
Hedonic Value, and Symbolic Value According to Blackwell.
Miniard, and Engel (Blackwell et al.
, 2.
, the motivation to purchase is separated into two distinct perspectives: intrinsic and extrinsic motivation.
Intrinsic motivation, similar to utilitarian and hedonic value, is the judgment of the consumers on the benefits from their consumption experience, while extrinsic factors will be identified as security and privacy that correspond to the influence of external resources (Ozturk et al.
, 2016.
Wang et al.
, 2.
In this study, we try to focus on the intrinsic According to Kim & Han .
, the consumer's feelings acquire hedonic It is more personal as a fun feeling than task fulfillment.
Hedonic value is reflected as entertainment and emotion when shopping rather than the purpose of shopping itself, which is a utilitarian value (Bettiga et al.
, 2.
For example, a consumer who is more into hedonic value will search for the pleasure of shopping rather than the utilitarian value related to the essential purpose of buying goods.
It is interesting to bring these two values into this study because they can be identified from the features that are offered from the CC platform (Benoit et al.
, 2017.
Hwang & Griffiths, 2.
For instance, one of the most popular Indonesian ride-hailing services.
Gojek, can offer more practical benefits such as effort saving and utility which are vital determinants of usersAo satisfaction because the users can save energy to travel within the city with competitive pricing (Hwang and Griffiths, 2.
On the other hand, the CC platform focusing on video sharing like youtube will deliver more hedonic value because users can enjoy watching videos from millions of users (T.
Zhang et al.
, 2.
Therefore, this study finds the correlation between two intrinsic factors, like utilitarian and hedonic value, which strengthens the previous research.
The symbolic value is related to altruistic or social value: the sustainability awareness to consume (UinjareviN et al.
, 2.
For example, we can minimize our carbon footprint when we use a product.
In the context of the current study.
Zipcar emphasizes that using certain services can reduce environmental footprints.
this benefit can lead young consumers to perceive the symbolic value of the practice (Catulli et al.
, 2.
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by KRC Research and Zipcar, 45% of consumers between the ages of 18 and 34 years consciously choose to use alternative forms of transportation, and 16% of them acknowledge that they drive less because they want to protect the environment (B.
Davis et al.
, 2.
H6: Utilitarian value positively influences the attitude toward CC through an online platform.
H7: Hedonic value positively influences the attitude toward CC through an online Factors Influencing Empathy toward Collaborative Consumption As mentioned above, empathy in this research is defined as a user's emotional feeling to attach himself or herself to other users through a platform that releases feelings of concern.
Keeble .
, in his study, states that CC would probably induce value perceptions .
tilitarian, hedonic, and symbolic valu.
When the platform offers more benefits of sharing usage than ownership, the utilitarian value exists (S.
Lee & Kim, 2018.
Hwang & Griffiths, 2.
For example.
Gojek provides ride-sharing .
ike or ca.
, bringing more benefits than owning it.
Unlike utilitarian value, hedonic value can appear when the CC platform brings experience to entertain users (Babin & Attaway, 2000.
Benoit et al.
One example that represents this variable can be seen when Gojek offers a helpful food delivery experience through a smartphone and gives an exciting way to select menus featuring many discounts.
On the other hand, symbolic value appears when the CC platform elicits positive feedback as part of a prosocial movement (UinjareviN.
Koo, and BerberoviN, 2.
For example, using environmentally friendly products or services such as sharing transportation can indicate the existence of individual prosociality or, in this case, a signaling effect of the benevolence of symbolic value (Bird and Smith, 2.
Holbrook .
, in his research, states that empathy is influenced by the consumer's value perception, which is studied because it has a significant effect on marketing activities.
On the other hand, the study by Hwang and GriffithsAos .
shows that symbolic value increases empathy, but not attitude, and utilitarian value increases attitude but not empathy.
the influence of empathy's value alongside attitude suggests that increasing awareness of prosocial issues converts into empathetic feelings about CC (Benoit et al.
, 2017.
Botsman & Rogers, 2010.
Prothero et al.
, 2.
H8: Hedonic value has a positive influence on the empathy toward CC through an online platform.
H9: Symbolic value positively influences the empathy toward CC through an online platform.
Methods Data Collection The sample population for this study is internet users from various cities in Indonesia.
This country was selected because its collaborative economy has been proliferating (Paundra et al.
, 2.
According to the World Economic Forum, 87% of Indonesians are inclined to utilize products or services within a shared community, surpassing the global average of 66% (Liem, 2.
Moreover, the rise of the economy is also indicated by Ahmad et al the widespread use of Gojek which has become the first Indonesian unicorn company in the ride-hailing business (Pratama, 2.
Kuncoro, 2.
The population was limited to digital users who have experience using digital CC platforms such as ride-hailing services (Gojek.
Gra.
, peer-to-peer accommodation (Airbn.
, crowdfunding platforms (KitaBis.
, sharing economy-based e-commerce (Bukalapa.
, and so forth.
The selected population for this study is Indonesian internet users who have prior experience with digital CC.
An online questionnaire was distributed to this population taken from the researcherAos database and relatives, primarily residing in several big cities across Indonesia.
The online survey was conducted using Google Forms where participants were provided with clear instructions beforehand.
The study period commenced in April 2018 and ran for approximately two and a half years until its completion.
Measures The questionnaire used for data collection contained scales to measure the ten constructs of the current studyAos research model.
They are Attitude Toward CC .
Intention to Use CC .
Empathy .
Hedonic Value .
Online Initial Trust .
Perceived Behavioral Control .
Perceived Ease of Use .
Perceived Usefulness .
Symbolic Value .
, and Utilitarian Value .
A 6-point Likert scale was administered, in which 1 = strongly disagree, 2 = moderately disagree, 3 = slightly disagree, 4 = slightly agree, 5 = moderately agree, and 6 = strongly Table 1.
Measurement Item Construct Questionnaire Item References Using a digital CC platform would be a good idea (A.
Using a digital CC platform would be more interesting than traditional CC (A.
Using a digital CC platform would be fun (A.
(Hwang and Griffiths.
I intend to continue using a digital CC platform in the future (IU.
I will always try to use a digital CC platform in my daily life (IU.
I plan to continue to use a digital CC platform frequently (IU.
(Hwang and Griffiths.
Empathy I felt as if I needed to participate in a digital CC platform when there was crucial or intense discussion over a digital CC platform (E.
(Hwang and Griffiths.
Hedonic Value While using a digital CC platform.
I felt a sense of fun (HV.
I enjoyed the exposure to new information during a digital CC platform discovery (HV.
I had a good time because I was able to act on the spur of the moment (HV.
(Hwang and Griffiths.
I use web site/apps if it is trustworthy and honest (OIT.
I use web site/apps if it is the website wants to keep promises and obligations (OIT.
I use web site/apps if the information on this website is plentiful and of sufficient quality (OIT.
(Doney & Cannon, 1.
, .
an der Heijden, 2.
and (Koufaris and Hampton-Sosa, 2.
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Perceived Behavioral 1.
Control Perceived Ease of Use Perceived Usefulness 1.
Symbolic Value Utilitarian Value Result I use web site/apps if the website offers secure personal privacy (OIT.
I use web site/apps if It is thought that this website keeps my best interests in mind (OIT.
Whether or not I use a digital CC platform is entirely (Ajzen, 1.
up to me (PBC.
There are likely to be plenty of opportunities for me to use a digital CC platform (PBC.
I have total control over the use of a digital CC platform (PBC.
Interaction with a digital CC platform would be clear (Davis, 1.
to understand (PEU.
Navigating a digital CC platform would be easy (PEU.
A digital CC platform will be easy to learn to use (PEU.
A digital CC platform will make it easy to perform a task (PEU.
Using a digital CC platform would make it easier to do my job (PU.
A digital CC platform would be helpful for my job (PU.
Using a digital CC platform would increase productivity (PU.
(Davis, 1.
Using a digital CC platform would make me feel (UinjareviN.
Koo and more responsible (SV.
BerberoviN, 2.
Using a digital CC platform would make me feel like a part of a more significant cultural movement (SV.
I found the information I was looking for in a digital CC platform (UV.
I accomplished what I wanted to do in a digital CC platform (UV.
(Hwang and Griffiths.
The study sample follows non-probability sampling with a convenience sampling approach because of its affordability, easy accessibility, and time flexibility.
Besides, the respondents were considered to have an equal opportunity to use any application or website they were interested in.
A pilot questionnaire was distributed to the first 30 respondents to check validity and reliability.
Three hundred twenty questionnaires were gathered and retained for further analysis for the final survey.
To analyze the data collected, we examined the proposed conceptual development model, and tested the studyAos formulated hypotheses.
the partial least squares structural equation modeling (PLS-SEM) technique was used.
PLS-SEM is a powerful tool to measure a model because it can measure with a robust result without a lot of assumptions and requirements such as multicollinearity (Wold et al.
, 2.
This study employed the PLSSEM method using SmartPLS version 3.
0 to validate the proposed model and assess the hypotheses (H.
Hwang et al.
, 2.
Ahmad et al Validity and Reliability Analysis The result shows all indicators are valid and reliable, with each of the Cronbach alpha values being more than 0.
6 and each of the average variance extracted (AVE) values being higher than the acceptable score of 0.
5 (Larcker, 1981.
Hair et al.
, 2.
Moreover, the factor loadings of all measures are more significant than their construct on any other Thus, the validity and reliability of the proposed model have been achieved to a satisfactory level.
The validity, reliability, and factor loading summary is presented in Figure 2 and Table 1.
Figure 2.
Result of Reliability and Factor Loading Table 2.
Result of Validity and Reliability Test Composite Alpha Variance Cronbach's rho_A Reliability Extracted (AVE) Attitude Towards CC Intention to Use CC Empathy Hedonic Value Online Initial Trust Perceived Behavioral Control Perceived Ease of Use Perceived Usefulness Symbolic Value Utilitarian Value The result of the structural model equation could be obtained by evaluating the Gadjah Mada International Journal of Business - May-August.
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R-squared .
eterminant coefficien.
and the path coefficient .
ffect siz.
The R-squared indicates that the variance of the exogenous construct can explain the endogenous construct.
The results of R-squared can be classified into a good model (R2: 67%), a moderate model (R2: 33%), and a poor model (R2: 19%).
The path coefficient/effect size indicates how the exogenous construct influences the endogenous construct.
The level of influence usually has three classifications: poor .
, average .
, and a strong level of influence .
Based on the structural modelAos data analysis as presented in Table 3, the R-squared value for variables affecting attitude is 70.
6%, and for variables affecting intention to use 2%, indicating that these variables effectively account for a significant proportion of endogenous variables.
In addition, hedonic and symbolic variables demonstrate a moderate level to explain the empathy construct, as the R-squared value is 48.
The bootstrap test in SmartPLS 3 was used to calculate the result of the study with 5000 iterations with a one-tailed test type.
The result of the structural model equation could be obtained by evaluating the R-squared .
eterminant coefficien.
and the path coefficient .
ffect siz.
The R-squared indicates that the variance of the exogenous construct can explain the endogenous construct.
The results of R-squared can be classified into a good model (R2: 67%), a moderate model (R2: 33%), and a poor model (R2: 19%).
The path coefficient/effect size indicates how the exogenous construct influences the endogenous construct.
The level of influence usually has three classifications: poor .
, average .
, and a strong level of influence .
Based on the structural modelAos data analysis as presented in Table 3, the R-squared value for variables affecting attitude is 70.
6%, and for variables affecting intention to use 2%, indicating that these variables effectively account for a significant proportion of endogenous variables.
In addition, hedonic and symbolic variables demonstrate a moderate level to explain the empathy construct, as the R-squared value is 48.
The bootstrap test in SmartPLS 3 was used to calculate the result of the study with 5000 iterations with a one-tailed test type.
Table 3.
Result of R-Squared and Effect Size Relationship between Variables H4 : Perceived Usefulness Ie Attitude towards CC H5: Perceived Usefulness Ie Attitude towards CC H6: Utilitarian Value Ie Attitude towards CC H7: Hedonic Value Ie Attitude towards CC H1: Attitude towards CC Ie Intention to Use CC H3: Empathy Ie Intention to Use H2: Perceived Behavioral Control Ie Intention to Use CC H10: Online Initial Trust Ie Intention to Use CC H8: Hedonic Value Ie Empathy H9: Symbolic Value Ie Empathy Hypothesis Testing Effect Size T-Value The analysis suggests strong support for our seven posited hypotheses.
H1.
H2.
H4.
H5.
H7.
H8, and H9.
For five of those hypotheses (H1.
H5.
H7.
H8, and H.
, the relationship is significant, with p-values below 0.
By contrast, the research results show Ahmad et al that for three hypotheses the relationship is not significant.
The three rejected hypotheses are empathyAos effect on intention to use CC (H3, p-value 0.
, online initial trustAos effect on intention to use CC (H10, p-value 0.
, and utilitarian valueAos effect on attitude toward CC (H6, p-value: 0.
Table 4.
Result of T-Value and P-Value Original Sample (O) Sample Mean (M) Standard Deviation Attitude Toward CC Ie Intention to Use CC Supported Empathy Ie Intention to Use CC Rejected Hedonic Value Ie Attitude Toward CC Supported Hedonic Value Ie Empathy Supported Online Initial Trust Ie Intention to Use CC Rejected Perceived Behavioral Control Ie Intention to Use CC Supported Perceived Ease of Use Ie Attitude Toward CC Supported Perceived Usefulness Ie Attitude Toward CC Supported Symbolic Value Ie Empathy Supported Utilitarian Value Ie Attitude Toward CC Rejected T Value P Values Result Discussion The variables that come from the TAM are perceived usefulness and perceived ease of use, and they positively influence attitude toward CC.
This means that the users evaluate whether the platform can fulfill their purpose (S.
Lee et al.
, 2018.
Chiu et al.
or whether it can bring ease when the users use it so they will engage in an effortless process (Hansen et al.
, 2018.
Davis, 1.
According to the statistical result, both are highly significant, as seen from their p-values (PEU: 0.
025 and PU: 0.
As mentioned above, many researchers agree regarding the significance of the relationship between perceived ease of use and perceived usefulness on intention in various implementations such as word processing software, music applications, and other digital platforms for which the result are the same (Bendary & Al-Sahouly, 2018.
Lu et al.
, 2019.
Waddell & Williamon.
The variables linked to the attitude are utilitarian value and hedonic value.
These two constructs refer to how the users can get the purposive .
or pleasure .
Completing the whole construct, besides the two previous variables, utilitarian and hedonic values will enrich attitude's antecedents since attitude is highly related Gadjah Mada International Journal of Business - May-August.
Vol.
No.
2, 2025
to the motivational behavior, especially in terms of product purchase, in this case, is to use the platform (Dhar & Wertenbroch, 2000.
Moon et al.
, 2.
Conversely, this research reveals that utilitarian and hedonic values do not positively influence attitude.
This difference is still questioned and leads to some assumptions as to whether it is correlated with the different sample taken for this research or the context being digital platforms.
These findings also suggest the need for further research to shed light on this area.
Online initial trust (OIT) is related to a secure feeling of the users when using the platform.
It is a userAos feeling of confidence and security that responds to other parties in the digital CC platform (Fondevila-Gascyn et al.
, 2019.
Rempel et al.
, 1.
The result rejects the hypothesis that OIT positively influences the intention to use CC.
Trust is a variable mentioned in previous studies regarding purchase intention, especially in the digital market.
In this research, we considered trust as a variable that can influence people's intention to use the platform, yet the result does not support the idea .
-value = Despite trust being recognized as a crucial factor influencing purchase intention, its significance diminishes when its relationship regarding digital CC using intention is tested in this context.
This observation leads to the assumption that users who participate in using CC may not consider the associated risks before making financial transactions through this platform.
In addition, it is assumed that escalating OIT, such as building a companyAos reputation can convert users to paying customers, which has not been covered in this research context.
As mentioned above, empathy is a userAos emotional feeling to attach himself or herself to other users through a platform, which releases feelings of concern toward them.
According to Cano Murillo.
Kang and Yoon .
and Eisenberg and Miller .
, empathy is strongly related to prosocial behavior that utilizes feelings between individuals.
In the context of CC platforms, empathy can be correlated with the user's capacity to feel in accordance with another user's sense and feeling, which is translated into information served like a comment, narration, service offered, or discussion on a CC platform.
Since the digital collaborative platform serves as a place where internet users gather to utilize the service, empathy will emerge.
Empathy also makes symbolic values emerge because they correlate with social impact.
The result shows that empathy does not influence the intention to use the CC platform .
-value: 0.
The researchers considered that this might happen because our survey focuses on a particular CC context and general types.
As previously mentioned, the inclusion of empathy in this research is justified due to its potential to be a determining factor affecting usersAo engagement in digital CC within the context of prosocial behavior in the sharing economy domain.
Addressing this result in light of the study by Hwang and Griffiths .
, which demonstrates a positive influence between empathy and purchase intention, one might assume that empathy plays a role in people's buying behavior in the context of altruistic behavior.
However, the current result shows that empathy doesnAot emerge in the same way in the context of how users intend to use the apps as it does in the purchasing behavior.
This result can contribute to the body of research, like the study by Hwang and Griffiths .
, which finds that empathy does have a robust relational effect on purchase intention.
One hypothesis that is rejected is that utilitarian value significantly influences attitude, although it has not been rejected in previous research.
The two variables from the TAMAiperceived usefulness and perceived ease of useAithat are the point of this research have been demonstrated to be significant.
The high significance level in this research is further evidence to prove the model.
Furthermore, the result shows that perceived behav188 Ahmad et al ioral control (PBC) significantly affects the intention to use CC.
However, the result also indicates that the online initial trust (OIT) variable that influences the intention in the model is rejected.
A more comprehensive understanding of how CC is adopted across diverse populations would be enriched by research conducted in distinct demographic contexts.
For instance, intrinsic motivations like enjoyment significantly influence positive attitudes in Finland, while extrinsic motivations like financial benefits are more crucial for continued participation (Hamari.
Sjyklint, and Ukkonen, 2.
In Korea, shared goals serve as the strongest drivers, affecting enjoyment, sustainability, and economic benefits, with social interaction ties and reciprocity norms playing indirect roles (Kim and Yoon, 2.
Latin America, both intrinsic factors .
, enjoyment, sustainabilit.
and extrinsic factors .
, reputation, financial benefit.
drive participation, with personal satisfaction being the strongest motivator (Alzamora-Ruiz et al.
, 2.
Among Generation Z in Vietnam and Spain, attitudes, social norms, and trust are key, with interpersonal influence and electronic word-of-mouth (WOM) shaping intentions in Vietnam, while trust links internal and external variables in Spain's tourism-sharing economy (Pham et al.
, 2021.
Martynez et , 2.
In Tyrkiye, environmental factors such as economic crises, urban mobility, and WOM influence psychological barriers and financial gains, which ultimately shape intentions to engage in CC (Gyngyrdy Belba, 2.
By exploring these diverse demographic and regional variations, the study could yield insights that are more broadly applicable, providing a clearer picture of the drivers of CC adoption across different populations.
addition, the various demographic studies have identified several external factor themes, such as regional economic conditions, cultural values, and technological advancements that shape CC behaviors.
In the future development of CC, these factors could shed light on creating a sustainable business in this domain, such as increasing attractiveness by using financial incentives, improving cultural values to enhance willingness to adapt to the technology, and improving user engagement through technological advancement.
Conclusion This study on CC on a digital platform explored how the cognitive value perceptions and practical attitudes of millennial users are related to the intention to use CC.
Since this research focuses on the type of digital platform which offers a CC process in general, we propose two variables from the TAM and two other variables that influence the context of intention to use a digital CC platform.
Even though only three additional variables are significant .
erceived ease of use, perceived usefulness, and perceived behavioral contro.
, this research has five highly significant variables .
compared to the prior research, which only has three highly significant variables.
The result also shows utilitarian value is not significant, and empathy does not directly influence the intention to use digital CC platforms.
As for its theoretical implication, this research can carry out the empirical testing of intention to use in the digital CC context.
The researchers attempted to find out the antecedents of how the user can gain the intention to use the digital CC platform.
Besides, the researchers inserted some variables, including attitude as the consumer's beliefs or feelings toward an object and empathy as the user's emotional feeling to attach themselves to another user through a platform that releases a feeling of concern about it.
Perceived Gadjah Mada International Journal of Business - May-August.
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No.
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behavioral control means how easy or difficult users can develop the intention to use CC, which directly impacts the intention to use CC on a digital CC platform.
Therefore, the present research can contribute to a further theoretical foundation for a quantitative study and a conceptual model that can depict the intention to use digital CC with the proposed sample in Indonesia.
E-businesses that offer a CC platform have the economic potential for innovation that implements the rapid development of information technology through the internet (Hamari.
Sjyklint, & Ukkonen, 2.
Referring to this research, practitioners can improve their platform to attract more users and gain profit or understand how digital users intend to use the service/feature in the platform they create.
Our proposed conceptual model can help project managers develop new features in their digital CC platform in order to enhance the userAos participation.
Achieving the best result from CC can be accomplished by strengthening the customer perception through attitude as well as building perceived behavioral control through the apps.
First, managers can create advertisements which deliver hedonic value-oriented messages, such as highlighting how CC can bring joy and happiness while using it.
Such an approach is likely to create positive consumer perception regarding the platform.
In addition, managers can develop a lean user experience (UX) and user interface (UI) in order to affect a customerAos preference and thereby boost the userAos intention.
Second, marketers should also convince the consumers that the application can be easily accessed by everybody.
By making the apps light in memory, low cost, and accessible even for the elderly, managers can increase the perceived behavioral control, further escalating a userAos intention to use the platform.
Limitations As mentioned above, the researchers inserted some variables, including empathy.
However, empathy has only one indicator to calculate the result, and this is a limitation of this study.
As observed in other indicators of empathy in the study by Hwang and Griffiths .
, it is primarily assessed based on environmental motivation.
However, this current study considered that the users in digital CC are not always prioritizing the environmental issue, but rather the service offered .
or example, financial technology, digital product marketplace, etc.
Nonetheless, from a business point of view .
nstead of a user point of vie.
, those other indicators might have a relational impact.
Further research regarding empathy in CC needs to be conducted more as complementary research.
The sample of this study is also limited to Indonesian users only.
Therefore, more global samples are necessary to understand how the global market responds to CC.
Furthermore, to provide a more robust and well-rounded analysis, further research could be enhanced by using a qualitative method such as behavioral observation or longitudinal studies which involve tracking data over time, and interviews or focus group discussions to gain deeper understanding in terms of emotional or cognitive aspects.
References