FACTORS AFFECTING TRUST AND INTEREST IN TRANSACTIONS BY INDONESIAN MSME SELLERS IN E-COMMERCE

Abstract

Introduction/Main Objective: This study aims to examine the factors that influence the trust and interest in e-commerce transactions among MSME actors in Indonesia. Therefore, a study was conducted on the effect of these variables. Background of the problem: The transition of MSMEs in Indonesia to using e-commerce for carrying out their business transactions. Every year, there is an increase in the number of MSMEs converting from conventional to digital, as well as the government's contribution to assist in the transition. Novelty: The variable of interest in transacting through e-commerce is the basis for conventional businesses to switch to digital, but in other studies, no one has added a variable of trust as an intervening variable, and several other supporting variables for the interest in transacting via e-commerce. This study presents new research that provides a comprehensive view of the technology acceptance model (TAM) and how it relates to trust and interest in ecommerce transactions. Research Methods: This study uses a snowball sampling technique by employing a survey of the MSMEs in Indonesia with certain criteria. This study also uses structural equation modeling (SEM) based on partial least squares (PLS). Findings/Results: This study proves that all the variables of trust and interest in e-commerce transactions are supportive and significant, but there are two hypotheses that do not support them (H3 and H6). This shows that empirically MSMEs are not necessarily interested in using e-commerce for their business transactions. Conclusion: This study provides insight into the trust and interest in e-commerce transactions among MSME business actors. We suggest that the MSMEs should switch to using e-commerce for their transactions, to develop their businesses into digital ones.

Headnote

ABSTRACT

Introduction/Main Objective: This study aims to examine the factors that influence the trust and interest in e-commerce transactions among MSME actors in Indonesia. Therefore, a study was conducted on the effect of these variables. Background of the problem: The transition of MSMEs in Indonesia to using e-commerce for carrying out their business transactions. Every year, there is an increase in the number of MSMEs converting from conventional to digital, as well as the government's contribution to assist in the transition. Novelty: The variable of interest in transacting through e-commerce is the basis for conventional businesses to switch to digital, but in other studies, no one has added a variable of trust as an intervening variable, and several other supporting variables for the interest in transacting via e-commerce. This study presents new research that provides a comprehensive view of the technology acceptance model (TAM) and how it relates to trust and interest in ecommerce transactions. Research Methods: This study uses a snowball sampling technique by employing a survey of the MSMEs in Indonesia with certain criteria. This study also uses structural equation modeling (SEM) based on partial least squares (PLS). Findings/Results: This study proves that all the variables of trust and interest in e-commerce transactions are supportive and significant, but there are two hypotheses that do not support them (H3 and H6). This shows that empirically MSMEs are not necessarily interested in using e-commerce for their business transactions. Conclusion: This study provides insight into the trust and interest in e-commerce transactions among MSME business actors. We suggest that the MSMEs should switch to using e-commerce for their transactions, to develop their businesses into digital ones.

ARTICLE INFO

Article information:

Received 11 April 2022. Received in revised version 24 August 2022. Received in revised version 8 December 2022. Accepted 9 December 2022.

Keywords:

technology acceptance model (TAM), trust, interest in transactions in e-commerce, MSME

JEL Code:

L26, L81, M15, Z13

INTRODUCTION

In the current era of digitalization, the internet has become a necessity and is proliferating. Internet users in Indonesia have increased every year. Research conducted by the Hootsuite and We Are Social platforms released in January 2020 shows the number of internet users in Indonesia has reached 175.4 million people, while the total population of Indonesia is around 272.1 million. Compared to 2019, Indonesia's internet users increased by about 17 percent, or 25 million (Kumparan, 2020). The data show that people have used the internet to facilitate their activities. The growth process of internet users can change media information such as information technology (IT). IT can encourage rapid business development because of the varied information supported by internet network media. One of the emerging IT acceptances is e-commerce. E-commerce can be accessed through devices connected to the internet; they can access e-commerce platforms which provide convenience when conducting transactions without the barriers of time and distance. E-commerce includes the distribution, sale, purchase, marketing, and services of a product that is carried out in an electronic system, such as the internet or other forms of computer networks (Wardhana, 2016). Opportunities for the development of e-commerce are very open in Indonesia. Firstly, this is because of the large population, so it has vast market potential. Secondly, Indonesia's geography, an archipelago that is spread out over large distances, makes e-commerce a system that allows everyone to conduct transactions (Rachadian in Firmansyah, 2017).

E-commerce's growth is increasing rapidly every year. In 2018, the number of transactions from 13,485 e-commerce businesses were 24,821,916, with transaction values reaching 17.21 trillion rupiah (Rozama et al., 2019). Of the 50 e-commerce sites in Indonesia that can be accessed via similarweb.com (2020), it is desirable to transact online based on the number of visitors per month. The 10 e-commerce sites with the highest number of visitors in Indonesia are presented in the image below:

For their development, Micro, Small, and Medium Enterprises (MSMEs) engaged in fashion, electronics, cosmetics, food, and so on require innovations to survive amid competition both at home and abroad. MSMEs are currently switching from conventional sales to digital sales using e-commerce as a form of migration to improve their current competitiveness and existing opportunities. In 2018 the sales model in e-commerce was dominated by sellers at 80.81 percent, followed by resellers at 19.41 percent, and the smallest intermediary seller with a buyer, called a dropshipper, at 4.78 percent (Rozama et al., 2019). Government support is available through the Go Online MSME program, initiated by the Ministry of Cooperatives and Small and Medium Enterprises and the Ministry of Communication and Information, in 2017. The goal is to commit to getting eight million MSMEs online by 2020 (Islami, 2017). Based on the listings results in 3,504 census blocks, 15.08 percent of businesses have sold goods/services via the internet. Of the recorded number, 72.83 percent of the businesses sold goods/services via the internet in 2018, while 2.76 percent did not have sales transactions in 2018. The remaining 25.1 percent of businesses just started selling goods/services via the internet in 2019 (Rozama et al., 2019). The Ministry of Cooperatives and Small and Medium Enterprises has also increased its target to 10 million MSMEs that will migrate to e-commerce by 2020. To achieve an additional two million MSMEs, the Ministry of Cooperatives and Small and Medium Enterprises of the Republic of Indonesia has collaborated with several wellknown e-commerce companies, such as Blibli, Tokopedia, Shopee, Bukalapak, and Lazada (Annur, 2020). This further encourages MSMEs to migrate from conventional trade to digital. Interest in transacting via e-commerce encourages users to conduct their transactions via ecommerce.

MSMEs are shifting to using e-commerce to assist in with the efficiency and effectiveness of their performance, such as fast and secure payment transaction processing, saving time, carrying out promotions easily, prompt service, etc. However, they also face obstacles to using e-commerce, namely 1) not interested in selling online; 2) it is more convenient to sell directly (offline); 3) security concerns; 4) concerns about privacy; 5) concerns about technical issues; 6) concerns about issues of trust; and 7) lack of knowledge or expertise (Rozama et al., 2019). MSMEs that use e-commerce must understand matters relating to the continuity of transactions in the e-commerce system being used. Trust is the key factor for users of e-commerce. There have been several cases that occurred in ecommerce that were affected by hacker attacks, as reported by Pusparisa (2020), such as Bukalapak (March 17, 2020) where approximately 13 million items of users' data were stolen, Tokopedia (April 17, 2020) was hacked and lost over 91 million items of users' data and more than 7 million items of merchants' data, and Bhinneka (May 10, 2020) was hacked and 1.2 million items of users' data were lost. These hackers steal data such as e-mails, names, passwords, and even users' phone numbers. These events can create risks, possibly caused by inadequate security, the users' privacy cannot be protected, and they can damage the reputations of the business actors in e-commerce.

When using e-commerce, the risks that will be faced by business actors trusting consumers using e-commerce can be in the form of fraud, credit card piracy (carding), fake transfer evidence, consumer complaints due to differences in the goods sent, and similar problems. The risks faced by business actors tend to be higher than with conventional transactions. The security of business actors in e-commerce must also be considered because they are directly related to e-commerce service providers and consumers. Several security layers should allow users to trust the e-commerce site they go to for the transactions they want to carry out online. Users get security protection through identity verification, proof of transactions carried out, and the like. Digital track records carried out in e-commerce are considered necessary by business actors because irresponsible parties can misuse the evidence. Personal information about the business actors is also uploaded to commerce in the form of business names, telephone numbers, credit card numbers, business owners' identities, business e-mails, ecommerce site passwords, and so on. Trust regarding the privacy provided by e-commerce can be in the form of users not being asked for too much personal information, direct verification of users when the information will be used on other sites, viewing the data collected during e-commerce's use, etc. E-commerce providers must provide convenience for transactions related to privacy issues with users. Reputation is an intangible asset, and although it is not visible, it has a significant impact on the company or business entity. The assessment given by consumers after completing the transaction can provide an overview of the online store that handled the transaction. Usually, this is supported by testimonies from buyers regarding transactions they have made at the online store. The better the rating given by consumers, the better the reputation obtained by the online stores. Prospective buyers can also view online ratings and reviews given by previous buyers on the e-commerce site being used, which aims to increase the trust in the transactions undertaken on the site.

E-commerce provides many uses or benefits that users feel. Users will choose to use specific e-commerce sites to increase the efficiency and effectiveness of the work done. This shows how e-commerce benefits business actors when conducting online buying and selling. Users can feel the ease of using e-commerce by it being accessible anywhere and anytime. E-commerce makes it easier for business actors to develop their business activities. The site's appearance, navigation, and other features offered by the ecommerce site can be quickly learned and understood by its users. When people use ecommerce sites, they will try and understand the system to find out how happy or comfortable they are with using that site. In addition to making it convenient for users to access, ecommerce must also provide pleasure or comfort after using it. When an individual feels happy and comfortable using his/her chosen ecommerce site, this will increase his/her interest in conducting online transactions. In addition to providing convenience, e-commerce is also driven by the surrounding environment using existing technology. Social factors also encourage individuals to use e-commerce; people may provide recommendations that can encourage other individuals to use the technology. In addition, word-of-month supports individuals in using e-commerce in their environment. Individual experience factors from using e-commerce affect other users' use of e-commerce.

This study refers to the theory of technology acceptance model (TAM) involving risk, privacy, security, reputation, usefulness, ease of use, enjoyment, and social interest in transacting via e-commerce, with trust as an intervention variable. This study reveals the shift by business actors from conventional businesses to digital ones, by considering the dimensions of trust and interest in transacting using e-commerce. The contribution of this research is to provide information to MSME actors that business transitions that are carried out conventionally should be done digitally, by trusting the use of ecommerce for the business transactions that need to be carried out. It also provides knowledge and news of the developments in research updates in the same field, considering trust and interest in the transactions done using e-commerce, and other factors that influence it. In this research, the government can make and evaluate approriate policies to pay more attention to MSMEs in their transition to digitalization, so that the broader business community in Indonesia can develop.

LITERATURE REVIEW AND HYPOTHESES DEVELOPMENT

1.Technology Acceptance Model (TAM)

The theory behind the technology acceptance model (TAM) is the adaptation of the theory of reasoned action (TRA), which is connected to beliefs, attitudes, will, and behavior, and was developed by Ajzen and Fishbein (1975). Davis (1989), in developing TAM to explain the determinants of computer acceptance, describes users' behavior in accepting and using new technology. Ratuolivia (2012), explains that TAM is an information system theory that makes models of how users want to accept and use technology. TAM is the model used to predict and explain how technology users receive and use technology related to their work or entertainment. TAM has critical variables that can be used to study behavior, namely perceived usefulness and perceived ease of use. These affect attitudes toward behavior, behavior intentions, and behavioral.

A study by Kim et al. (2008) developed a theoretical framework that identifies consumer beliefs and purchase intentions, analyzes consumer behavior data found on the internet, collects the data through web surveys, and provides theoretical and managerial implications for this behavior. Pavlou's (2003) research found the effect of trust and perceived risk when combined with other variables, because many factors affect online shopping. Koufaris and Hampton-Sosa (2004), in their research, also developed a theoretical framework for the perception of trust with websites and companies. The research illustrates that trust and transactions using websites (e-commerce) must be developed further.

Based on the previous research, this study modifies the TAM model by adding several variables that can affect trust and the interest in e-commerce transactions. External variables that are added include perceived risk, perceived security, perceived privacy, and perceived reputation that all affect perceived trust. Then using the TAM key variables, namely perceived usefulness and perceived ease of use, and adding the external variables perceived enjoyment, perceived social, and perceived trust, which affect the interest in e-commerce transactions amid the uncertainty about the use of ecommerce for business transactions.

2.Perceived Risk

Kim et al. (2008) explained that perceptions of risk or uncertainty affect public confidence in their decisions. Many people feel uncertain about transactions being carried out using ecommerce. The perception of risk is a factor that has an essential role in shaping an individual's interest in using e-commerce (Suhir et al., 2014). In research undertaken by Jayantri and Seminari (2018), it is explained that risk perception directly affects consumer confidence, if the perception of risk is high, then distrust occurs, which results in doubt and the possibility that the user will quit the online store or transaction, and if the perception of risk is low, there will be trust that then affects the user's commitment and loyalty. Risk is closely related to trust because of the uncertainty or risk that will affect customers when making transactions via e-commerce.

3. Perceived Security

Park and Kim (2006) define security as the ability of online stores to control and maintain security for data transactions. Gefen et al. (2003) reveal that consumers who feel safe with using the internet would tend to trust websites that provide e-commerce services, compared to people who feel that the internet is unsafe because they are not sure that adequate protection exists on e-commerce sites. The security provided by e-commerce can be in the form of the authenticity of the products sold, accuracy in the delivery of goods, protection of consumer rights, etc. If the security provided by e-commerce, or buying and selling service providers is considered good, this can increase consumers' sense of trust in buying and selling online.

4. Perceived Privacy

Ackerman and Davis (2002), define privacy as an individual's ability to manage the completeness of his/her personal information, and where the information will be needed and how it is used by other parties. Privacy relates to a company or consumer's personal information and data that has been provided to carry out transactions via e-commerce. Kinasih and Albari (2012) said that in the context of the internet, privacy is related to aspects of distribution, such as obtaining or using personal information. Therefore, someone's private information is at risk of being misused by certain parties. Franzak et al. (2001) reveal that the more a person feels that the information he/she provided is properly guarded by a web address, the higher the level of trust in that web address will be.

5. Perceived Reputation

Javenpaa et al. (2000), define reputation as the extent to which consumers believe that an organization is honest and cares about its customers. Whetten and Mackey (2002) explain that a company's reputation is defined as a specific type of feedback received by an organization from its stakeholders regarding the credibility and identity claims against the organization. Fombrun (1996) explains a good reputation is important because it increases the company's profits, investors in securities, and employees of its job vacancies. Dharma (2006) argues that sellers try to avoid things that cause them to get a bad reputation. Consumer testimony is one of the things that informs about a company's reputation on the e-commerce sites that may be used by consumers. Customers were satisfied if the result met their expectations (Patma et al., 2021). The reputation of ecommerce itself is usually based on other people's information about specific e-commerce sites, rating provided by consumers, consumer responses after visiting a site or making a transaction, and also discussion forums about ecommerce web services which may generate consumer confidence in buying and selling online.

6.Perceived Usefulness

Davis (1989) defines perceived usefulness as the level of individual confidence that an information technology system can make it easier to carry out activities and improve performance. Davis further explains that by giving users a sense of confidence, their performance will increase by using technology or a web system. Wibowo (2008) explains that perceived usefulness is a perception of usefulness that is defined as a measure in which the use of technology is believed to benefit the people who use it. The effectiveness and efficiency felt by e-commerce users are the benefits of using e-commerce for their transactions (Rinwantin and Pujiastuti, 2022). User confidence in using the website for making transactions online will be increased. The usefulness of e-commerce has a large effect on online shopping and is an essential factor influencing the interest in online transactions.

7. Perceived Ease of Use

Davis (1989) states that the perceived ease of use is the level of confidence an individual has in the belief that when using an information technology system it will not require any effort (free of effort) and it will be easy to understand. This perception is also related to the perception of individuals who find it easy and have no difficulty when making transactions via ecommerce. Ease in the e-commerce system can include the ease of the interaction, the user interface, and payment until the purchase process occurs. If the technology is easy to use, people will be more interested in using this technology.

8. Perceived Enjoyment

Davis et al. (1992) state that users who enjoy using information systems are more likely to form behavioral intentions than other users who do not experience much pleasure. Pikkarainen et al. (in Davis, 2004) state that comfort is a condition where an individual uses technology to carry out his/her activities and considers it to be fun. Puspitasari (2017) argues that perceived enjoyment is how a person can feel satisfied and happy with something he/she gets. The enjoyment felt by users of e-commerce will increase the frequency of these users making online transactions.

9. Perceived Social

Venkatesh et al. (2003) said that social influence relates to how individuals view other people and believe that they must use the new systems. Davis (1989) reports that the social influence felt, and the support that a person using this technology gets, can be stated as an aspect of social influence. This is because social factors will encourage individuals to accept something that their community has used. Wardhana (2016) states that the people around individuals who provide opinions or recommendations are the main driving force for individuals to use technology.

10. Perceived Trust

Mayer et al. (1995) state that trust is a person's willingness to be sensitive to the actions of others, based on the expectation that other people will take specific actions on the recommendation of those who believe in them, without depending on their ability to monitor or control them. Pujastuti et al. (2014) state that there would be no online trading transactions without trust. Susilo et al. (2022) state that consumers will believe that sellers can provide goods and services appropriately and conveniently in the internet world. Trust in the seller lies in the seller's ability to provide the promised services to the buyer, the seller's willingness to provide benefits to both parties, and the seller's behavior in running his/her business (Mayer et al., 1995). The trust placed in e-commerce sellers will lead to consumers making more transactions using ecommerce.

11. Transaction Interest in E-commerce

Badan Pengembangan dan Pembinaan Bahasa (2016), a transaction is a sale and purchase agreement (in trade) between two parties, normally for some form of payment. The acceptance of current technology has changed transactions from conventional to digital. Digital transactions can be attributed to the intention of, or interest in, the user's behavior and his/her acceptance of technology. In TAM, individual belief is a determining factor for influencing individual behavior when using a system. It will continue to develop the intention to use the system; this intention also influences decisions about the use of technology. Kim et al. (2008) explain the relationship between interest and behavior, based on the assumption that humans seek to make rational decisions based on the information they have. As long as the services provided by information technology are considered profitable, individuals will continue to use these IT services. Interest in, or the intention of, using e-commerce can make it easier for users to process transactions carried out online. E-commerce is the information technology that users choose.

12.E-commerce (Electronic Commerce)

Li and Yang (2014), disclose that e-commerce is a business mechanism that works electronically by focusing on online business transactions and it has the opportunity to build a more humane and personalized relationship with its customers without depending on time and space. Nurrohmah and Alfanur (2016) describe ecommerce as the purchase and sale of goods and services on the internet. It can carry out transactions involving goods or services between two or more parties using electronic tools and techniques. For Turban et al. (2015), ecommerce is the process of buying, selling, or trading data, goods, or services via the internet. Laudon and Traver (2017) believe that ecommerce is a commercial transaction involving the exchange of value between individuals, carried out through or using digital technology. Leung et al. (2020) say that the emergence of the e-commerce market has created broad market opportunities for retailers and logistics service providers, increased purchase and sales satisfaction, and facilitated logistics service providers' abilities to manage larger ones. From the results of the explanation above, it can be concluded that e-commerce comprises of transactions involving sales, purchases, marketing, payments, deliveries, and services to customers that are carried out through electronic devices which can be connected to the internet. Rozama et al. (2019) state that there are three definitions of sellers in e-commerce, namely:

1. A seller is a person who sells goods/services produced by himself, or who obtains them from a supplier, so that the seller him/herself determines the price and profits. The seller is more independent and has complete control over the goods, and there is no commission because the goods are sold directly by the vendor, so he/she makes a profit.

2. A reseller (reseller) is a person who buys a product from a distributor or supplier at a lower price than the market, and resells it to get some profit from the sale of the item.

3. A dropshipper (an intermediary for sellers and buyers) is almost the same as a reseller, but he/she does not have the goods being sold, so his/her job is only to find consumers and then report their orders to the supplier. After that, the supplier will send the desired items to the customer, and the dropshipper will get a commission.

HYPOTHESIS DEVELOPMENT

1.Perceived Risk to Trust

Mayer et al. (1995) state that the perception of risk leads to beliefs about the possibility of gain or loss beyond consideration, including the relationship with trust. Trust in the use of technology is related to risk. The higher the risk from the technology, the less trust users have in it. Vice versa, the lower the risk from the technology, the greater trust its users have. Based on the description above, the proposed hypothesis is:

H1: Risk positively influences trust.

2. Perceived Security to Trust

Park and Kim (2006) define security as the ability of online stores to control and maintain the security of their transactions' data. Gefen et al. (2003) said that consumers who feel safe with the internet environment would trust websites that provide e-commerce services, compared to people who feel that the internet is unsafe because they do not believe there are adequately protected e-commerce sites. Based on the description above, the proposed hypothesis is: H2: Security positively influences trust.

3. Perceived Privacy to Trust

Hu et al. (1999) define privacy as the right of individuals to be themselves by considering several dimensions of privacy, such as behavior, communication, and personal data. The growing capacity of new technologies to process usersupplied information and the added complexity makes privacy an important issue. E-commerce will ask for personal data from users for identity purposes, and to avoid bad behavior in transactions using e-commerce. This makes users doubt the data they upload to e-commerce because it involves users' personal information. Ecommerce must be able to give confidence to the user in the given personal identity. Based on the description above, the proposed hypothesis is:

H3 : Privacy has a positive effect on trust.

4. Perceived Reputation to Trust

Dharma (2006) says that a perceived reputation or the perception of one's reputation provides confidence to other parties regarding one's ability, integrity, and goodwill. Fombrun (1996), states that reputation is a manifestation of a person's experiences with the product or service they get, a good reputation will increase the supplier's credibility, making consumers more confident that they will get what has been promised to them. A good reputation will lead to trust from the consumers. Based on the description above, the proposed hypothesis is:

H4 : Reputation has a positive effect on trust.

5. Perceived Usefulness on Interest in Ecommerce Transactions

Davis (1989) found that perceived usefulness gives users the belief that their performance will increase by using the technology or system. Thompson et al. (1991) suggest that the usefulness of information technology systems is comes from the benefits users experience when carrying out their duties. The more useful an information system is means it can provide benefits to its users so that they have more confidence in it. Based on the description above, the proposed hypothesis is:

H5: Usefulness has a positive effect on the interest in e-commerce transactions.

6. Perceived Ease of Use on Interest in Ecommerce Transactions

Davis (1989) found that perceived ease to use is the level at which a person believes using information technology is easy and does not require much effort from the wearer. An information system that is often used shows that the system is better known, easier to operate, easier to understand, and easier for users to use. Based on the description above, the proposed hypothesis is:

H6: Ease to use has a positive effect on the interest in e-commerce transactions.

7. Perceived Enjoyment on Interest in Ecommerce Transactions

Davis et al. (1992) also found that perceived pleasure or perceived enjoyment is the extent to which an activity using a computer system is perceived to be something that is personally enjoyable outside of the instrumental value of the technology. Davis et al. (1992) also state that users who get comfort from using an information system are more likely to form behavioral intentions than users who do not experience much comfort. The enjoyment provided by ecommerce when carrying out the user's activities can increase the trust of e-commerce users. Based on the description above, the proposed hypothesis is:

H7: Enjoyment has a positive effect on the interest in e-commerce transactions.

8.Perceived Social on Interest in Ecommerce Transactions

Hsu and Lin (2007) explain that when people participate in a social system, they identify with and assume a role in it. Factors from this social environment influence individuals to do something wih the new things that appear. The social environment is also a driving force in technological progress. The surrounding environment can also influence sellers and buyers to use the e-commerce system that the surrounding environment has provedid. Based on the description above, the proposed hypothesis is:

H8: Social system have a positive effect on the interest in e-commerce transactions.

9.The Effect of Trust on Interest in Ecommerce Transactions

Travis (2003) states that electronic commerce is the latest development that tries to influence customers to use a technology that makes customers' lives easier in their buying and selling transactions. Kim et al. (2008) state that the decision to use e-commerce is influenced by trust, which is one of the factors that increase the use of e-commerce, because trust is an understanding in the minds of consumers about online shopping. In other words, if consumers are not sure about e-commerce sites then they will not request the products or services from them. Users will use e-commerce for transactions between the sellers and themselves, this strongly influenced by their trust. Features that make it easier for sellers to use e-commerce make the sellers switch to using e-commerce to process their buying and selling transactions. Based on the description above, the proposed hypothesis is:

H9: Trust has a positive effect on the interest in e-commerce transactions.

METHOD, DATA, AND ANALYSIS

This research method used primary data obtained through the distribution of questionnaires. The object of this research was Micro, Small, and Medium Enterprises (MSMEs) throughout Indonesia that used ecommerce in their business transactions. The data collection method used snowball sampling and Google Forms as a medium for distributing the questionnaires so they could reach all the different regions in Indonesia. This study collected questionnaires filled out by 368 respondents, but 51 respondents did not meet the specified criteria, so 317 questionnaires were used; these would be processed and analyzed further. The type of questionnaire used was a closing questionnaire, which is a questionnaire where the answers had been provided, in this case by using a Likert scale, from 1 = strongly disagree to 5 = strongly agree. The data filling method used a non-probability sampling technique with a snowball sampling approach. The business criteria sampled in this study were as follows:

1. MSMEs in Indonesia.

2. MSMEs following Law Number 20 of 2008 concerning Micro, Small, and Medium Enterprises of The Republic of Indonesia (Ministry of Cooperatives and Small and Medium Enterprises of the Republic of Indonesia, 2008).

3. MSMEs that used e-commerce.

4. MSMEs engaged in electronics.

5. MSMEs engaged in fashion.

6. MSMEs engaged in cosmetics.

7. MSMEs engaged in food and beverages.

8. MSMEs engaged in household equipment.

RESULT AND DISCUSSION

1.Respondent Characteristics

In general, the initial information obtained from the respondents' responses is as follows:

1. Most of the respondents were women, with most of the sellers using e-commerce being between the ages of 26 to 32 years old (40.7 percent) and 18 to 25 years old (39.7 percent). These ages are the target market the sellers hope to attract to use e-commerce. The respondents were widely spread throughout Java, namely in DKI Jakarta, West Java, Central Java, and East Java, as this is where a lot of the big cities are. They provide easy access, have the facilities, distribution networks, and services required by the sellers to carry out their business activities properly.

2. From Table 2 above, it can be seen that the respondents were fairly evenly distributed among the online shopping systems they used, as 29 percent used Shopee, followed by Tokopedia (20.5 percent), Lazada (18.3 percent), Bukalapak (18 percent), and Blibli (14.2 percent). Judging from the e-commerce systems used, the respondents mostly sold products in the fashion sector (30.3 percent). By using e-commerce, buyers can see the inventory held by the online stores, which also provide information visually with photos or videos that include descriptions of the products being sold, provide proof of purchases by other people, and make transactions using third parties (e-commerce) easily and safely.

3.The growth in the respondents' incomes before and after using e-commerce for buying and selling transactions was very significant. Table 2 above shows that some respondents' incomes were less than IDR 1,000,000 per month (39.4 percent), but after switching to using e-commerce they increased their income to be in the range of IDR 2,500,000 to IDR 5,000,000 per month. E-commerce provided ease of delivery for managing product inventories, product marketing, products, and services for the business activities run by MSMEs. Thus, conventionally run businesses that operated online via ecommerce media had an impact on the activities of business people.

2.Measurement Model Evaluation (Outer Model)

From the table above, it can be seen that all the research variables had an AVE value that was greater than 0.5. Therefore, from the above results, it can be concluded that all the constructs had good construct validity values.

The discriminant validity test could be measured by looking at the value of the FornellLarcker constructs. The results of the discriminant validity test would be said to be good if the value of the construct was higher than that of the other constructs.

3.Structural Model Evaluation (Inner Model)

The inner model test was carried out by measuring the coefficient of determination (R2) and the path coefficient (ß), which were then assessed for significance based on the t-count of each path and the goodness of fit (GoF). The results of the structural measurements of the model were as follows Figure 3.

3.1 Coefficient of Determination (R2)

The value of R2 is said to be good if it has a value greater than 0.1. Based on the table above, it can be seen that the R2 value of the confidence variable was 0.527. This meant that the level of variation in trust's risk, security, privacy, and reputation variables was 52.1 percent, while variables outside the research explain the other 47.9 percent. In contrast, the R2 value of the variable interest in e-commerce transactions was 0.455. This meant that the level of variation in the usefulness, ease of use, enjoyment, social, and trust variables toward the interest in ecommerce transactions was 45.5 percent while other variables outside the research explain the remaining 54.5 percent.

3.2 Path Coefficient (ß)

This study's path coefficient testing was carried out using a bootstrapping procedure with 500 replacements. To see the significance of the influence between variables, it could be done by looking at the path coefficient value and the significant value tcount in the table 6 below.

In the above equation, AVE was a weighted average value with weights obtained from the number of indicators for each latent variable. Calculations using this formula showed the GoF value from the model was 0.74 > 0.38, which meant that a measure that exceeded the GoF threshold value was significant (Tenenhaus and Esposito, 2004). This value meant that the model could be accepted, and the interpretation of the analysis would be continued.

4.Hypothesis Test

1. The Effect of Perceived Risk on Trust (H1)

The test results with SmartPLS analysis showed that the effect of risk on trust had a t-value of 3.854 > 1.96 and a p-value of 0.000 < 0.05, which indicated that the influence was significant and the path coefficient value of 0.326 > 0.1 indicated that the variable risk had a positive effect on trust so that the first hypothesis was supported.

2. The Effect of Perceived Security on Trust (H2)

The test results with SmartPLS analysis showed that the effect of security on trust had a t-value of 3.885 > 1.96 and a p-value of 0.000 < 0.05, which indicated that the effect was significant and the path coefficient value of 0.349 > 0.1 indicated that the security variable had a positive effect on trust so that the second hypothesis was supported.

3. The Effect of Perceived Privacy on Trust (H3)

The test results with the SmartPLS analysis showed that the effect of privacy on trust had a tvalue of 1.233 < 1.96 and a p-value of 0.218 > 0.05, which indicated that the effect was not significant and the path coefficient value was 0.097 <0.1, which indicated that the variable privacy did not have a positive effect on trust so that the third hypothesis was not supported.

4. The Effect of Perceived Reputation on Trust (H4)

The test results with SmartPLS analysis showed that the effect of reputation on trust had a t-value of 3.516 > 1.96 and a p-value of 0.000 < 0.05, which indicated that the effect was significant and the path coefficient value of 0.234 > 0.1 indicated that the variable reputation had a positive effect on trust so that the fourth hypothesis is supported.

5. The Effect of Perceived Usefulness on Transaction Interests in E-commerce (H5)

From the test results with SmartPLS analysis it could be seen that the effect of usefulness on the interest in transactions in e-commerce had a tvalue of 3.146 > 1.96 and a p-value of 0.002 < 0.05, which indicated that the effect was significant and the path coefficient value was 0.253 > 0.1, which showed that the utility variable had a positive effect on transaction interest in e-commerce, so that the fifth hypothesis was supported.

6. The Effect of Perceived Ease of Use on Transaction Interests in E-commerce (H6)

From the test results with SmartPLS analysis it could be seen that the effect of ease of use on interest in transactions in e-commerce had a tvalue of 0.041 < 1.96 and a p-value of 0.967 > 0.05, which indicated that the effect was not significant and the path coefficient value was 0.002 < 0.1, which indicated that the ease of use variable did not have a positive effect on the interest in transactions in e-commerce, so that the sixth hypothesis was not supported.

7. The Influence of Perceived Enjoyment on Interests in Translation in E-commerce (H7)

From the test results with SmartPLS analysis it could be seen that the effect of enjoyment on the interest in transacting in e-commerce had a tvalue of 2.076 > 1.96 and a p-value of 0.038 < 0.05, which indicated that the effect was significant and the path coefficient value was 0.177 > 0.1, which showed that the comfort variable had a positive effect on transaction interest in e-commerce, so that the seventh hypothesis was supported.

8. The Influence of Perceived Social on Transaction Interest in E-commerce (H8)

From the test results with SmartPLS analysis it could be seen that the social influence on interest in transactions in e-commerce had a t-value of 2.411 > 1.96 and a p-value of 0.016 < 0.05, which indicated that the influence was significant, and the path coefficient value was 0.247 > 0.1, which showed that social variables had a positive effect on transaction interest in e-commerce, so that the eighth hypothesis was supported.

9. The Effect of Perceived Trust on Transaction Interest in E-commerce (H9)

The test results with the SmartPLS analysis showed that the effect of trust on the interest in transactions in e-commerce had a t-value of 2.573 > 1.96 and a p-value of 0.010 < 0.05, which indicated that this effect was significant. The path coefficient value was 0.228 > 0.1, showing that the trust variable had a positive effect on transaction interest in e-commerce, so the ninth hypothesis was supported.

RESULT AND DISCUSSION

Risk has a positive effect on trust. The smaller the risk that occurs during the e-commerce transaction process, the greater the trust of the users in the e-commerce system they use. This is based on the idea that the risks in online transactions are minimized with third parties, namely by using e-commerce. Distrust between sellers and buyers can be reduced because of the involvement of e-commerce in the transaction. Sellers will also be more accessible and trustworthy in any transactions made with the buyers.

Security has a positive effect on trust. The higher the level of security provided by ecommerce systems for their users, the better will be the level of trust given to the system by the users. This is based on the idea that security for shopping via e-commerce sites can make it safe for sellers and buyers to make transactions on the sites. The security provided by e-commerce helps sellers attract buyers and to be able to transact via e-commerce sites, due to the security promised by e-commerce sites. This is also in line with previous research conducted by Marlien and Probo (2011), Firmansyah (2017), and Nurhatinah (2018), who all show that security has a positive effect on trust.

Privacy has no positive effect on trust. The lower the level of privacy provided by ecommerce sites, the lower is the level of trust the users give to the e-commerce sites they use. This is not in line with research conducted by Marlien and Probo (2011), Fimansyah (2017), and Nurhatinah (2018), who all show that privacy has a positive effect on trust. This is based on the premise that the privacy of sellers and buyers is considered insufficient for the level of user trust. Personal information and data provided for ecommerce purposes can be hacked and used by other parties without the user's permission. Ecommerce needs to increase the privacy of its users, both sellers and buyers, so that unwanted things do not occur, such as limiting excessive requests for information from users, not sending the latest news on accounts connected to ecommerce, providing stricter policies on how user information will be used by both the seller and the buyer, and so on.

Reputation has a positive effect on trust. The better that the reputation of an e-commerce system is, the better the trust of the users of that system is. This is in line with research conducted by Marlien (2011), Fimansyah (2017), and Nurhatinah (2018), who found that reputation has a positive effect on trust. This is based on the idea that the more users who use e-commerce for their shopping transactions, the more trust there will be in the e-commerce sites used. Ecommerce is known and used by many people, and has good ratings that will give other users confidence to use it. The reputation level also affects sellers when using e-commerce because potential buyers already understand the ecommerce they are using to speed up the shopping transactions they want.

Usefulness has a positive effect on the interest in e-commerce transactions. This is in line with the research that Wardhana (2016), Monica and Tama (2017), and Pratiwi (2018) undertook, which showed that usability has a positive effect on the interest in using ecommerce. The more the shopping or ecommerce site benefits its users, the more effective and efficient it is for the businesses of the sellers. This is based on the idea that the transactions carried out on e-commerce sites benefit both sellers and buyers. The more the shopping site benefits its users, the more new users become interested in making e-commerce transactions.

Ease of use has no positive effect on the interest in e-commerce transactions. This is not in line with Wardhana (2016), who showed that ease of use positively affects the interest in ecommerce transactions. Meanwhile, in this study, ease of use does not positively affect the interest in transactions using e-commerce. The more difficult e-commerce is to use, the lower the use of e-commerce becomes for the business transactions carried out by sellers. This is based on the idea that the use of e-commerce for sellers in e-commerce transactions is considered difficult to learn and the features on shopping or e-commerce site pages are confusing for the sellers, especially for those who have just joined e-commerce. In receiving orders to get funds from e-commerce, it takes a long time for the seller to switch to a direct order system for his/her business transactions. E-commerce needs to make it easier for new users to understand how to shop on e-commerce sites. It should provide clear directions, provide easy stages, have features that are easier to understand, and so on; especially for sellers who may be interested in switching to using e-commerce for their business transactions.

Enjoyment has a positive effect on the interest in e-commerce transactions. This is in line with the research of Monica (2017), which showed that enjoyment positively affects the interest in e-commerce transactions. The more happy and comfortable the user is shopping via an e-commerce site, the better it is for the users to make transactions through such shopping or ecommerce sites. This is based on the idea that comfort or pleasure is not only felt by the seller, but also by other users of e-commerce. The users feel happy and comfortable, and this will encourage them to make transactions on shopping or e-commerce sites more frequently.

Social influences has a positive effect on the interest in e-commerce transactions. This is in line with Wardhana's research (2016) that showed the social influences of the interest in ecommerce transactions. The more social influence that is exerted by e-commerce users, the more new users will start making transactions using e-commerce. This is based on the idea that society influences users into making transactions on shopping or e-commerce sites. It also supports the idea that environmental or social factors influence users or sellers to make transactions using shopping or e-commerce sites. Other sellers will also recommend or influence other sellers to use the same e-commerce sites.

Trust has a positive effect on the interest in e-commerce transactions. This is in line with research conducted by Wardhana (2016) and Monica (2017), who found that trust positively affects the interest in e-commerce transactions. The greater the trust a shopping or e-commerce site has, the more users will make transactions using that shopping or e-commerce site. This is based on the idea that sellers will have more confidence in transactions carried out via ecommerce sites because they minimize unwanted events compared to transactions made directly with the seller. E-commerce also provides trust to the buyers regarding the sellers who are in e-commerce, meaning that sellers are trusted in the business transactions they carry out.

Research Limitation

The limitations in this study include the fact that the variables used were limited and did not represent all the effects of trust and interest in ecommerce transactions, the research subject was only sellers who make transactions using ecommerce, and some of the variables used only a few indicators in asking questions of the respondents.

CONCLUSION AND SUGGESTION

Shopping or e-commerce sites have an essential role in the continuity of businesses carried out online. Third parties support the trust given to users to conduct e-commerce transactions. The factors that affect the transactions carried out include risk, security, privacy, reputation, usefulness, ease of use, enjoyment, social, trust, and interest in e-commerce transactions.

In this study, to answer the formulation of the research problem, a survey was conducted on sellers on the subject of the MSME actors who have used shopping or e-commerce sites for conducting their business transactions. The questionnaires that were collected and could be processed and analyzed came from 317 respondents, and were considered valid for testing using SmartPLS 3.3. Based on the results obtained by the researcher, it is stated that the variables of risk, security, and reputation have a positive effect on trust. Meanwhile, the privacy variable does not affect trust. Then, the variables of usefulness, enjoyment, social, and trust positively affect the interest in performing transactions using e-commerce. Meanwhile, the ease of use variable does not positively affect the interest in using e-commerce transactions.

Then for future research, researchers can add variables related to trust and interest in using ecommerce transactions, adding further research subjects, namely the buyers. Then a comparison can be made between the two for their interest in e-commerce transactions and add question indicators on several variables to further deepen the research.

Footnote

Corresponding Author at Department of Accounting, Faculty of Economics and Business, University of Lampung, Lampung, 35141, Indonesia.

E-mail address: [email protected] (author#1) , [email protected] (author#2), [email protected] (author#3), [email protected] (author#4).

References

REFERENCE

Ackerman, M. S., & Davis Jr, D. T. (2003). Privacy and security issues in e-commerce. New economy handbook, pp. 911-930.

Annur, Cindy Mutia. (2020). Gandeng ECommerce, Kemenkop Target 10 Juta UMKM Gunakan Marketplace. Retrieved from: https://katadata.co .id/agungj atmiko/digital/5 ee7166a7a248/gandeng-e-commercekemenkop-target10-juta-umkm-gunakanmarketplace.

Ba, S., & Pavlou, P. A. (2002). Evidence of the effect of trust building technology in electronic markets: Price premiums and buyer behavior. MIS quarterly, pp. 243-268.

Badan Pengembangan & Pembinaan Bahasa, Kementerian Pendidikan, Kebudayaan, Riset, dan Teknologi Republik Indonesia. (2018). Kamus Besar Bahasa Indonesia Edisi V Tahun 2016 word Transaksi. Retrieved from: https: //kbbi .web. id/transaksi.

Cheung, C.M.K. & Lee, M.K.O. (2001). Trust in internet shopping: instrument development and validation through classical and modern approaches, Journal of Global Information Management, Vol. 9 No. 3, pp. 23-35.

Cheskin Research & Studio Archetype/Sapient. (1999). eCommerce Trust Study. Retrieved from: https: //file s .transtutors. com/cdn/uploadassig nments/80515_2_cheskinresearchtrust 1999. pdf.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, Vol. 13 No. 5, pp. 319-340.

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace 1. Journal of applied social psychology, 22(14), pp. 1111-1132.

Dharma, F. (2006). Pengaruh Structural Assurance dan Perceived Reputation terhadap Trust Pengguna Internet Di Sistem ECommerce. Simposium Nasional Akuntansi, 9, pp. 23-26.

Firmansyah, Diyan. (2017). Pengaruh Pengalaman, Reputasi, Privasi, dan Keamanan Terhadap Kepercayaan (Trust) Pengguna Internet Dalam Melakukan Transaksi Jual Beli Online (studi empiris pada masyarakat di Surakarta) (Doctoral dissertation, Universitas Muhammadiyah Surakarta). Retrieved from: http: //eprints .um s.ac.id/54874/.

Flavian, C., & Guinalíu, M. (2006). Consumer trust, perceived security and privacy policy. Industrial Management & Data Systems, 106(5), pp. 601-620.

Fombrun, C. J. (1996). Realizing value from the corporate image. Harvard Business School Press, Boston, MA.

Franzak, F., Pitta, D. & Fritsche, S. (2001). Online relationships and the consumer's right to privacy. Journal of Consumer Marketing. Vol. 18 No. 7, pp. 631-642.

Gefen, D. (2000). E-commerce: the role of familiarity and trust. Omega, 28(6), 725737.

Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS quarterly, 27(1), pp. 51-90.

Hsu, C., & Lin, J. C. (2007). Acceptance of blog usage: The roles of technology acceptance, social influence and knowledge sharing motivation. Information & Management. Volume 45 (2008), pp. 65-74.

Hu, P. J., Chau, P. Y., Sheng, O. R. L., & Tam, K. Y. (1999). Examining the technology acceptance model using physician acceptance of telemedicine technology. Journal of management information systems, 16(2), pp. 91-112.

Islami, Nur. (2020). UMKM Online Indonesia Masuk Sarang Raksasa!. Retrieved from http s://kominfo.go.id/content/detail/ 10686/u mkm-online-indonesia-masuk-sarangraksasa/0/sorotan media.

Janda, S., Trocchia, P. & Gwinner, K. (2002). Consumer perceptions of internet retail service quality, International Journal of Service Industry Management, Vol. 13 No. 5, pp. 412-31.

Jarvenpaa, S. L., Tractinsky, N., & Vitale, M. (2000). Consumer trust in an Internet store. Information technology and management, 1(1-2), pp. 45-71.

Jayantari, I. A. A. U., & Seminari, N. K. (2018). Peran Kepercayaan Memediasi Persepsi Risiko terhadap Niat Menggunakan Mandiri Mobile Banking di Kota Denpasar (Doctoral dissertation, Udayana University, Indonesia). Retrieved from: https: //oj s .unud.ac. id/index .php/Manaj emen/ article/view/3 7836.

Kim, D. J., Ferrin, D. L., & Rao, H. G. (2008). A trust-based consumer decision model in electronic commerce: The role of trust, risk, and their antecedents. Decision Support Systems. Volume 44 (2) , pp. 544.

Kinasih, B. S., & Albari, A. (2012). Pengaruh Persepsi Keamanan dan Privasi terhadap Kepuasan dan Kepercayaan Konsumen Online. Jurnal Siasat Bisnis, 16(1).

Koufaris, M., & Hampton-Sosa, W. (2004). The development of initial trust in an online company by new customers. Information & management, 41(3), pp. 377-397.

Kumparan. (2020). Riset: 64% Penduduk Indonesia Sudah Pakai Internet. Retrieved from:<https://kumparan.com/kumparantech/riset64-penduduk-indonesia-sudah-pakaiinternet-1 ssUCDbKILp/full.

Laudon, K. C., & Traver, C. G. (2017). ECommerce 2016 business, tecnology, sociey (12th ed.). England: Britis Library Cataloguint-in.

Lee, M. K., & Turban, E. (2001). A trust model for consumer internet shopping. International Journal of Electronic Commerce, 6(1), 75-91.

Lee, S. H., & Ngoc, H. T. B. (2010). Investigating the on-line shopping intentions of Vietnamese students: an extension of the theory of planned behaviour. World Transactions on Engineering and Technology Education, 8(4), pp. 471-476.

Leung, K. H., Lee, C. K., & Choy, K. L. (2020). An integrated online pick-to-sort order batching approach for managing frequent arrivals of B2B e-commerce orders under both fixed and variable time-window batching. Advanced Engineering Informatics,45,101125.

Li, Y., & Yang, R. (2014). New Business Model for Company to Win the Competition. American Journal of Industrial and Business Management, 2014. Vol 4, pp. 190-198.

Mayer, R. C., Davis, J. H., & Schoorman, F. D. (1995). An integrative model of organizational trust. Academy of management review, 20(3), pp. 709-734.

Nurrohmah, A., & Alfanur, F. (2016). Adopsi Ecommerce Pada Usaha Mikro Dan Kecil Di Bandung (studi Kasus Subsektor Fesyen). In e-Proceeding of Management (Vol. 3, pp. 1120-1127).

O'cass, A., & Fenech, T. (2003). Web retailing adoption: exploring the nature of internet users Web retailing behaviour. Journal of Retailing and Consumer services. Vol. 10(2), pp. 81-94.

Park, Chung-Hoon., & Young-Gul Kim. (2006). The Effect of Information Satisfactionand Relational Benefit on Consumers Online Site Commitmennts, Journal of Electronic Commerce in Organizations, 4 (1), pp. 7090.

Patma, T. S., Fienaningsih, N., Rahayu, K. S., & Artatanaya, I. G. L. S. (2021). Impact of Information Quality on Customer Perceived Value, Experience Quality, and Customer Satisfaction from Using GoFood Aplication. Journal of Indonesian Economy and Business: JIEB., 36(1), pp. 51-61.

Pavlou, P. A., & Fygenson, M. (2006). Understanding and predicting electronic commerce adoption: An extension of the theory of planned behavior. MIS quarterly, pp.115-143.

Pavlou, P. A. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International journal of electronic commerce, 7(3), pp. 101-134.

Pikkarainen, T., Pikkarainen, K., Karjaluoto, H., & Pahnila, S. (2004). Consumer acceptance of online banking: an extension of the technology acceptance model. Internet research. 14 (3) pp. 224-235.

Pujastuti, E., Winarno, W. W., & Sudarmawan, S.(2014). Pengaruh E-Commerce Toko Online Fashion Terhadap Kepercayaan Konsumen. Creative Information Technology Journal, 1(2), pp. 139-153.

Pusparisa, Yosepha. (2020). Pencurian Data Pengguna E-Commerce Kian Marak. Retrieved from:<https://katadata.co.id/ariayudhistira/infografi k/5ebb96f067890/pencurian-data-penggunae-commerce-kian-marak/.

Puspitasari, I., & Briliana, V. (2017). Pengaruh perceived ease-of-use, perceived usefulness, trust dan perceived enjoyment terhadap repurchase intention (studi kasus pada website zalora Indonesia). Jurnal Bisnis dan Akuntansi, 19(2), pp. 171-182.

Ratuolivia, C. C., & Siswanto, T. (2012). Evaluasi Penerimaan E-Commerce Dengan Menggunakan Technology Acceptance Model (Studi Kasus gramediaonline.com). In Prosiding Seminar Nasional Teknologi Informasi dan Multimedia 2012 (SNASTIA 2012) (Vol. 3, pp. A37-A42). Teknik Informatika Universitas Surabaya.

Rinwantin & Pujiastuti, Y. (2022). TAM (Technology Acceptance Model) Approach to Analyze Community's Interest in Using E-money. Journal of Applied Sciences in Accounting, Finance, and Tax, 5(1), 1-10.

Rozama, N. A., Kusumatrisna, A. L., Ilmiyah, Z., Sutarsih, T., Siswayu, G., & Syakilah, A. (2019). Statistik E-Commerce 2019. Katalog. Jakarta: Badan Pusat Statistik.

Siahaan, N. H., Martini, A. N., & Halim, M. (2022). The Effect of Cognitive and Affective Involvement on Intention to Use and Word of Mouth: The Case of Zoom Users In Indonesia. Journal of Indonesian Economy and Business, 37(2), pp. 136-161.

Similarweb. (2020). Top sites ranking for Ecommerce And Shopping in Indonesia. Retrieved from: https://www.similarweb.com/topwebsites/indonesia/category/e-commerceand-shopping/.

Smith, M., Bailey, J., & Brynjolfsson, E. (2000). Understanding digital markets: review and assessment. In: Brynjolfsson, E., Kahin, B. (Eds.), Understanding the Digital Economy. MIT Press, Cambridge, MA.

Sugiyono, P.D. (2017). Metode Penelitian Bisnis: Pendekatan Kuantitatif, Kualitatif, Kombinasi, dan R&D. Penerbit CV. Alfabeta: Bandung.

Suhir, M. (2014). Pengaruh Persepsi Risiko, Kemudahan Dan Manfaat Terhadap Keputusan Pembelian Secara Online (Survei Terhadap Pengguna Situs Website ww. kaskus. co. id). Jurnal Administrasi Bisnis, 8(1), pp. 9-10.

Sun, H., & Zhang, P. (2006). The role of moderating factors in user technology acceptance. International journal of human-computer studies, 64(2), pp. 53-78.

Susilo, G. F. A., Rani, U., & Khotijah, S. A. (2022). The Trusting Beliefs of Users and the Intention To Continue Making Purchases Via Social Commerce. Journal of Indonesian Economy and Business, 37(1), pp. 1-14.

Tenenhaus, M., Amato, S., & Esposito Vinzi, V. (2004). A global goodness-of-fit index for PLS structural equation modelling. In Proceedings of the XLII SIS scientific meeting (Vol. 1, pp. 739-742).

Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: toward a conceptual model of utilization. MIS quarterly, pp. 125-143.

Travis, D. (2003). E-commerce Usability, Tools and Techniques to Perfect the On-line Experience. CRS Press.

Turban, E., King, D., Lee, J. K., Liang, T. P., & Turban, D. C. (2015). Overview of electronic commerce. In Electronic commerce (pp. 3-49). Springer, Cham.

Kementerian Koperasi dan Usaha Kecil Menengah Republik Indonesia. (2008). Undang-Undang Nomor 20 Tahun 2008 Tentang Usaha Mikro, Kecil dan Menengah (UMKM). Jakarta.

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, pp. 425-478.

Wardhana, O. H. P. (2016). Pengaruh Persepsi Kemudahan, Persepsi Kegunaan, Persepsi Nilai, Pengaruh Sosial, Persepsi Risiko, dan Kepercayaan Terhadap Minat Menggunakan E-commerce. Jurnal Ilmiah Mahasiswa FEB, 4(2).

Whetten D., & Mackey Mackey. (2002). A social actor conception of organizational identity and its implications for study of organizational reputation. Business & Society. Vol. 41(4), pp. 393-414.

Wibowo, A. (2008). Kajian tentang perilaku pengguna sistem informasi dengan pendekatan technology acceptance model (TAM). Konferensi Nasional Sistem Informasi.