Impact of PEU And PEOU On IEBT And Social Media Marketing for MSME Sustainability
Syifa Alsatira Fadhillah1*, AMA Suyanto1*, Gina Goniah1*
1 Faculty of Economics and Business, Telkom University, Bandung, Indonesia
*Corresponding Author: [email protected], [email protected], [email protected]
Accepted: 15 December 2022 | Published: 31 December 2022 DOI:https://doi.org/10.55057/ajrbm.2022.4.4.9
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Abstract: Empirical studies in various countries show the negative impact of Covid-19 on the domestic economy, such as decreased purchasing power and consumption, deteriorating company performance, and threats to the financial and banking sectors as well as the existence of MSMEs. Based on data from the Bandung City Micro, Small and Medium Enterprises Cooperatives Service (KUMKM) as reported by the Jabar Ekspres digital news platform (2021), 90% of MSMEs in Bandung City have been affected by the pandemic. Social media marketing can help MSMEs to continue to survive as a sustainable business. The urgency or reason for choosing this research is because researchers want to know the extent of the impact of Perceived Usefulness and Perceived Ease of Use on Internet/e-Business Technology and Social Media Marketing used by MSMEs in Bandung City, how it affects the Sustainability of MSMEs in Bandung City, and to assess how effective the adoption of Internet/e-Business Technology and Social Media Marketing activities by MSMEs in Bandung City. This study uses quantitative methods with SEM analysis techniques with SmartPLS software. Based on the purpose of this research is a causal research. Collecting data in this study is by distributing questionnaires to get 400 respondents. The result of the analysis in this study indicate that Perceived Usefulness had a positive and significant effect on Internet/e-Business Technology, Perceived Usefulness had a positive and significant effect on Social Media Marketing, Perceived Ease of Use had a positive and significant effect on Internet/e-Business Technology, Perceived Ease of Use had no positive effect. and significant to Social Media Marketing, Internet/e-Business Technology has positive and significant effect on Social Media Marketing, Internet/e-Business Technology has positive and significant effect on Sustainability of MSMEs and Social Media Marketing has positive and significant effect on Sustainability of MSMEs.
Suggestions that can be put forward are, for the sustainability of MSMEs in the city of Bandung, it can be done using Social Media Marketing or the use of social media as a marketing strategy for MSME actors. Aspects of Social Media Marketing. In addition, the government can hold seminars or training on the use of social media and technology as a tool for MSMEs in the city of Bandung.
Keywords: Internet/e-Business, Social Media Marketing, Perceived Usefulness, Perceived Ease of Use, Sustainable MSMEs
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1. Introduction
Empirical studies in various countries show the negative impact of Covid-19 on the domestic economy, such as decreased purchasing power and consumption, deteriorating company performance, and threats to the financial and banking sector and the existence of MSMEs (Pakpahan, 2020). One of the affected sectors is MSME. MSMEs in Indonesia experienced a decline in sales in 2020. Meanwhile Thaha (2020) states that MSMEs are a sector that makes a very large contribution to the Indonesian economy. So that if the growth of MSMEs decreases, it will affect the economic rate. Evidenced by the supporting data reported by the Minister of Finance, namely Sri Mulyani, who stated that economic growth in Indonesia in the second quarter of 2020 was minus 5.32%. The city of Bandung is one of those affected, based on data from the Economic Growth Rate (LPE) the economic growth of the city of Bandung has decreased by 6.75%, starting from 4.47% in 2019 to minus 2.28% in 2020. One of the factors the cause is the decline in MSME growth (Firmansyah, 2021). Based on data from the Bandung City Micro, Small and Medium Enterprises Cooperative Service (KUMKM) which was reported from the Jabar Express digital news platform (2021) 90% of MSMEs in Bandung City have been affected by the pandemic. Atet Dedi as the Head of the KUMKM Service said that 90% of MSMEs as a whole were affected by Covid-19 because there was no preparation when social restrictions (PSBB) were first implemented and they had not adapted to the current pandemic conditions (Jabar Ekspres, 2021). It is feared that the continuous decline in MSME sales will have a sustainable impact on economic growth. Therefore there must be factors that encourage the sustainability of MSMEs. Atet Dedi as the Head of the KUMKM Office encourages MSME actors to utilize internet technology to market their products (Jabar Ekspres, 2021).
According to Patma et al. (2021) using the internet will involve The Adoption of Internet/e- Business Technology (IEBT Adoption) and social media marketing technology. Patma et al.
(2021) stated that the sustainability of MSMEs can be influenced by the adoption of internet/e- business technology. The adoption of innovation by SMEs is associated with various factors, especially organization, environment and technology. SMEs realize that innovation takes an important role and increases the benefits of current practices and systems. As a result, it is predicted that the involvement of internet/e-business technology will drive greater performance. The direct and indirect benefits of implementing IEBT can be seen in maximizing existing resources, which can have an impact on profits. According to Patma et al. (2021) social media marketing can also affect the sustainability of MSMEs. Described by Achmad et al.
(2020) that social media may be an increasingly popular choice for businesses because it allows communication to go beyond one to one personal conversations to many to many. The number of active social media users in Indonesia is 160 million or equivalent to 59% of the population in Indonesia and as many as 99% of users use social media via cellular. This indicates that the market potential in social media is very high and this platform has become an easy instrument for communicating online between consumers and companies, or between consumers and consumers around the world at any time. The use of social media marketing can increase the trust and loyalty of a company's brand, besides that social media marketing makes it easier for consumers to obtain information about company products. The use of social media by a company makes it easy for companies to build brands and increase their business activities (Chatterjee & Kumar Kar, 2020). In the involvement of marketing technology using the adoption of IEBT and social media, it will involve the technology acceptance model (TAM) proposed by Patma et al. (2021) the model resulted from several aspects, namely perceived usefulness (PEU) and perceived ease of use (PEOU).
Perceived Usefulness (PEU) can be realized when MSMEs believe that the involvement of a quality management system will help them improve performance (Patma et al., 2021).
Furthermore, when MSMEs see the benefits of using Social Media Marketing to produce better productivity, there is no doubt that MSMEs will adopt this method in their business (Patma et al., 2021). Likewise with the Perceived Ease of Use (PEOU) developed by Patma et al. (2021) has been widely used to understand the adoption of new technologies in business and other relevant fields. In a business context, entrepreneurs are more likely to adopt new technologies for company development and are easy to implement. Effective use of technology in terms of social media can lead to better achievements and income. This makes MSMEs involve and try social media to run their business. Under these conditions, innovation is easier for users to implement, so that users are motivated to adopt the technology (Patma et al., 2021).
The urgency or reason for choosing this research topic is because the researcher wants to know how far the impact of perceived usefulness and perceived ease of use on internet/e-business technology and social media marketing is used by MSMEs in Bandung City, what is the impact on the sustainability of MSMEs in Bandung City, and to assess how effective the adoption of internet/e-business technology and social media marketing activities by MSMEs in the city of Bandung. According to this researcher it is necessary and important to study to compare the results of how the city's economic growth is performing Bandung from the MSME sector after the pandemic and the current pandemic which took almost 2 years, what changes were made, felt and impacted on the economic activities of MSMEs in the city of Bandung. With the results of existing research, this research can scientifically conclude the impact of perceived usefulness and perceived ease of use on internet/e-business technology and social media marketing on the growth progress of UMKM in Bandung City.
2. Literature Review
2.1. Social Media Marketing
Social media are independent and commercial online social networks where people come together to socialize and share messages, opinions, images, videos and other content (Kotler &
Armstrong, 2018). Kapoor et al. (2018) defined that social media consists of communication websites that facilitate the formation of relationships between users from various backgrounds, resulting in a rich social structure. According to Samuel et al. (2018) Social media is any digital tool that allows users to quickly create and share content with the public. Social media includes various websites and applications. Some, like Twitter, specialize in sharing links and short text messages. Others, like Instagram and TikTok, are made to optimize photo and video sharing.
According to Kotler & Armstrong (2018) using social media will certainly have advantages and challenges. On the bright side, social media is targeted and personal which allows marketers to create and share brand content tailored to individual consumers and customer communities. Social media is interactive, which makes it ideal for initiating and participating in customer conversations and listening to customer feedback. Social media marketing indicators according to Patma et al. (2021) namely promotion, competitor encouragement and usage techniques. According to Zuhdi et al. (2019) The functions of social media marketing are as follows:
1) Set social media marketing goals 2) Audience research
3) Formation of the most necessary metrics 4) Analysis of competition
5) Curate and create engaging content
6) Punctuality should be a top priority 7) Optimize and access the results
2.2. Adoption of Internet/e-Business Technology
The ease of accessing the internet has changed the pattern of relationships that determine the norms of behavior and interaction (Zhong et al., 2020). Kleins et al. (2017) defines the internet as referring to an emerging paradigm consisting of uniquely addressable sets of things that communicate with each other to form dynamic networks around the world. According to Rustam (2017) the internet is called supermedium communicating as a product of a combination of information and communication technology, all contexts are possible. This supports community communication media carried out digitally. While Sumarto et al. (2020) defines the internet as a global network that can connect various computer networks that have uses as a source of information for their users.
e-Business is the use of electronics, computing, and internet-based technologies to change traditional revenue models and business designs for the mutual benefit of customers and vendors (Hamed, 2019). Meanwhile, according to Dianda & Pandin (2021) e-Business is a dynamic combination of technology, business processes and applications that will connect consumers, certain community groups and companies through electronic transactions and the sale of goods, information and services through electronic media. The introduction of internet/e-business technology is necessary for companies to carry out product marketing and social media marketing. The introduction of the IEBT plays a very strategic role in companies and can increase the usability of current practices and systems. As a result, higher performance is expected to be obtained by combining Internet technology / e-business technology. The indirect and direct benefits of implementing IEBT are to maximize existing resources which can have an impact on profits (Patma et al., 2021).
2.3. Perceived Usefulness (PEU)
According to Kabir et al. (2017) perceived usefulness is the extent to which users of technology or information systems can be trusted to improve their performance at work. In other words, the extent to which users of information systems and technology are optimistic that productivity and effectiveness at work can be increased through the use of the system. Therefore, user intentions are determined by the perceived usefulness they have on the system. Patma et al.
(2021) suggested that perceived usefulness has played an important role in predicting user attitudes toward technology. Perceived usefulness is a sensation that is useful for consumers to feel related to the productivity and effectiveness of the system as a whole to improve user performance.
The use of technology and information systems by individuals is mediated by acceptance of the technology in realizing the benefits felt by the individual, which in turn is determined by two cognitive factors, perceived usefulness (PEU) and perceived ease of use (PEOU). In other words, the extent to which a person believes that using technology will improve job performance. Therefore, the more useful a technology is, the higher the user's desire to use it (Tahar et al., 2020). Based on some of the meanings that have been stated above, it can be concluded that perceived usefulness or usefulness felt by consumers is the sensation felt by consumers related to the productivity and effectiveness of the system and its overall benefits to increase user performance. In other words, the extent to which system users are optimistic that their productivity and effectiveness in their work can be increased through the use of the system. The perceived usefulness (PEU) indicators used are business benefits, marketing
benefits, productivity benefits, query management benefits, and service benefits (Patma et al., 2021).
2.4. Perceived Ease of Use (PEOU)
According to Tahar et al. (2020) perceived ease of use explains the extent to which users can believe that in using technology, they can do anything without distractions that become an obstacle for them. Isma et al. (2021) stated that perceived ease of use is a belief about the decision-making process in using information technology. A person's perception of the ease of using information technology is the level at which a person believes that using a technology can make it easier to complete his work. Meanwhile, according to Samuel et al. (2018) perceived ease of use or perceived ease of use as two cognitive beliefs that postulate the theory of system use by individual behavioral intentions to use the system. Perceived ease of use in the Technology Acceptance Model is defined as the extent to which a person believes that certain technologies are easy to use and lead to perceived benefits (Patma et al., 2021).
According to Patma et al. (2021) Indicators of perceived ease of use are easy to learn, easy to identify customers, easy to identify requests, easy to find information, and easy to promote.
2.5. Micro, Small, and Medium Enterprises
Micro, Small and Medium Enterprises (MSMEs) are one of the business sectors that can develop and sustain the economy. Micro, Small and Medium Enterprises (MSMEs) are an excellent platform for job creation planned by the government, the private sector, and individual business actors (Halim, 2020). Meanwhile, according to Hamdani (2020) MSMEs are a form of economic activity carried out by small business owners who meet statutory standards for net worth or annual sales and ownership.
2.6. Framework
Figure 1: Research Framework
The framework in this study was adopted from Patma et al. (2021) with research indicators for each of the variables. First, for the variable perceived usefulness (PEU), which is used in this study, it is intended to how far it can influence SME's sustainability through the adoption of the internet and social media marketing. Besides perceived usefulness, there is a variable perceived ease of use which also means how far it can influence MSME's sustainability through the adoption of the internet and social media marketing.
This thinking is based on research conducted by (Patma et al., 2021). This research is different from the research conducted by Patma et al. (2021), the difference lies in the number of causal variables, namely "COS", where this variable was not used in this study because in the study
of Patma et al. (2021) "COS" only affects the internet adoption variable. Whereas in this study the "COS" variable is not needed because the object of this research already considers that the value of costs is not part of the burden.
2.7. Research Hypothesis
The hypothesis in this study are as follows:
H1: Perceived Usefulness (PEU) has a positive and significant impact on MSME Internet/e- Business Technology Adoption (IEBT) in Bandung City
H2: Perceived Usefulness (PEU) has a positive and significant impact on MSME Social Media Marketing (SMM) in Bandung City
H3: Perceived Ease of Use (PEOU) has a positive and significant impact on MSME Internet/e- Business Technology (IEBT) Adoption in Bandung City H4: Perceived Ease of Use (PEOU) has a positive and significant impact on Social Media Marketing (SMM) MSMEs in Bandung City
H5: Adoption of Internet/e-Business Technology (IEBT) has a positive and significant impact on MSME Social Media Marketing (SMM) in Bandung City
H6: Adoption of Internet/e-Business Technology (IEBT) has a positive and significant impact on MSME sustainability in Bandung City
H7: Social Media Marketing (SMM) has a positive and significant impact on the sustainability of MSMEs in the city of Bandung
3. Methodology
3.1. Population and Sample
In this study the population is all MSME Owners / Actors in the city of Bandung. The sample to be used in this study is owners/Perpetrators of UMKM in Bandung City who utilize social media as promotional media such as Facebook, Instagram, Youtube, TikTok, WhatsApp.
Bandung City MSME Owners / Actors who have 1-19 employees. The owner/perpetrator of UMKM in Bandung City who has sales of ≤ 200,000,000 per month.
3.2. Data Collection
Data collection by giving written statements to MSME respondents in the city of Bandung. The questionnaire given is a choice questionnaire in which each statement item is provided with five alternative answers so that data can be calculated. Sources of data come from respondents through questionnaires that have been distributed. The respondents used were MSME owners/actors in the city of Bandung.
3.3. Validity and Reliability Test
In testing the validity, this study uses the SmartPLS software which is divided into two models, the first is convergent validity and the second is discriminant validity. In convergent validity, two tests were carried out, namely the loading factor test and the average variance extracted (AVE) test. Meanwhile, the discriminant validity is divided into two tests, namely the cross loading test and the Fornell-Larcker criterion (Ghozali, 2021). To see whether a measuring tool is reliable or not, a statistical approach is used using the SmartPLS data processing program.
In conducting reliability testing it can be said to be reliable when the Cronbach Alpha value of each construct has a value of > 0.70 and when the Composite Reliability value for each construct has a value of > 0.70 (Ghozali, 2021).
3.4. Data Analysis Technique
Data analysis used in this study is to use structural equation modeling (SEM). SEM is a regression-based estimation technique that determines statistical properties. The purpose of the approach SEM is to generate latent variable scores that together minimize the ordinary least squares (OLS) residuals in the model (that is, maximize explanation). The resulting latent variable score is unique and determines the case value of each observation. They also make it possible to predict indicators from endogenous or dependent latent variables in structural models. In short, SEM is a variance-based method that estimates composites that represent latent variables in path analysis models (Richter et al., 2016).
3.5. Hypothesis Test
The data analysis used in this study is to use structural equation modeling (SEM). SEM is a regression-based estimation technique that determines statistical properties. The purpose of the approach SEM is to generate latent variable scores that together minimize the ordinary least squares (OLS) residuals in the model (that is, maximize explanation). The resulting latent variable score is unique and determines the case value of each observation. They also make it possible to predict indicators from endogenous or dependent latent variables in structural models. In short, SEM is a variance-based method that estimates composites that represent latent variables in path analysis models (Richter et al., 2016).
4. Discussion and Conclusion
4.1. Data Characteristic
Respondents in this study were SMEs in the city of Bandung, West Java. In obtaining responses from respondents, the research questionnaire was distributed online. This questionnaire uses the Google Form and then the URL link from the Google Form is distributed directly while it is distributed via several social media, including: Whatsapp, Instagram, Telegram.
Respondents in this study were dominated by respondents with characteristics, namely male gender aged 31-40 years, last education from high school or equivalent, with the type of food/beverage MSME, with 1-4 employees, average income per month MSME 26 -200 million and the age of MSMEs is 4-6 years.
4.2. Research Result
Testing the measurement model or outer model is the initial stage of data analysis from PLS.
Testing the measurement model is done by testing the validity and reliability of each indicator in the study. Indicators on latent variables are tested with a view to measuring the extent to which these items can explain their latent variables. Testing the structural model or outer model consists of several measurement indicators including convergent validity, discriminant validity, and reliability (Ghozali, 2021). The outer model in this study is shown in Figure 2.
Figure 2: Outer Model
The convergent validity value is measured using the Outer Loading value (Ghozali, 2021). The rule of thumb for the Outer Loading value, the minimum Outer Loading value of an indicator is 0.7 (Ghozali, 2021). The following is the Outer Loading value of each item in the assessment presented in Table 1 below.
Table 1: Convergent Validity Results
Laten Variable Indicator Outer Loading Description
Perceived Usefulness PEU1 0,870 Valid
PEU2 0,788 Valid
PEU3 0,878 Valid
PEU4 0,798 Valid
PEU5 0,883 Valid
Perceived Ease of Use
PEOU1 0,986 Valid
PEOU2 0,993 Valid
PEOU3 0,984 Valid
PEOU4 0,982 Valid
PEOU5 0,981 Valid
Internet/ E-Business Technology
IEBT1 0,960 Valid
IEBT2 0,955 Valid
IEBT3 0,970 Valid
IEBT4 0,973 Valid
IEBT5 0,961 Valid
IEBT6 0,999 Valid
IEBT7 0,953 Valid
IEBT8 0,966 Valid
Social Media Marketing
SMM1 0,974 Valid
SMM2 0,994 Valid
SMM3 0,981 Valid
Sustainability MSME’s
SM1 0,993 Valid
SM2 0,930 Valid
SM3 0,988 Valid
SM4 0,966 Valid
SM5 0,968 Valid
SM6 0,980 Valid
SM7 0,995 Valid
Based on the data shown in Table 1, it can be seen that all indicators in the study are valid. In this study, all indicators met the convergent validity criteria because they had Outer Loading values above 0.7. Outer Loading values on indicators that have been declared valid are then placed in each variable table separately. The Outer Loading value of the Perceived Usefulness variable is shown in Table 2.
Table 2: Outer Loading Value of Perceived Usefulness Variables
Laten Variable Indicator Outer Loading Description
Perceived Usefulness PEU1 0,870 Valid
PEU2 0,788 Valid
PEU3 0,878 Valid
PEU4 0,798 Valid
PEU5 0,883 Valid
Based on Table 2, it can be concluded that the 5 indicators on the Perceived Usefulness variable are stated to be valid because they have an Outer value Loading ≥ 0.7. Meanwhile, the Outer Loading results from the Perceived Ease of Use variable are shown in Table 3.
Table 3: Outer Loading Value of Perceived Ease of Use Variables Laten Variable Indicator Outer Loading Description Perceived Ease of
Use
PEOU1 0,986 Valid
PEOU2 0,993 Valid
PEOU3 0,984 Valid
PEOU4 0,982 Valid
PEOU5 0,981 Valid
Based on Table 3, it can be concluded that 5 indicators on the Perceived Ease of Use variable are declared valid because they have an Outer Loading value ≥ 0.7. Meanwhile, Outer Loading results from the Internet/e-Business Technology variable are shown in Table 4.
Table 4: Outer Loading Value of Internet/e-Business Technology Variables Laten Variable Indicator Outer Loading Description Internet/ e-Business
Technology
IEBT1 0,960 Valid
IEBT2 0,955 Valid
IEBT3 0,970 Valid
IEBT4 0,973 Valid
IEBT5 0,961 Valid
IEBT6 0,999 Valid
IEBT7 0,953 Valid
IEBT8 0,966 Valid
Based on Table 4, it can be concluded that the 8 indicators on the Internet/e-Business Technology variable are valid because they have an Outer Loading value of ≥ 0.7. Meanwhile, the Outer Loading results from the Social Media Marketing variables are shown in Table 5.
Table 5: Outer Loading Value of Social Media Marketing Variables Laten Variable Indicator Outer Loading Description
Social Media Marketing
SMM1 0,974 Valid
SMM2 0,994 Valid
SMM3 0,981 Valid
Based on Table 5, it can be concluded that 3 indicators on the Social Media Marketing variable are stated to be valid because they have an Outer value Loading ≥ 0.7. Meanwhile, the Outer Loading results from the MSME's Sustainability variable are shown in Table 6.
Table 6: Outer Loading Value of Sustainability MSME’s Variables
Laten Variable Indicator Outer Loading Description Sustainability
MSME’s
SM1 0,993 Valid
SM2 0,930 Valid
SM3 0,988 Valid
SM4 0,966 Valid
SM5 0,968 Valid
SM6 0,980 Valid
SM7 0,995 Valid
Based on Table 6, it can be concluded that the 7 indicators in the MSME's Sustainability variable are declared valid because they have an Outer Loading value ≥ 0.7. Apart from the Outer Loading value, the Average Variance Extracted (AVE) value can be used in convergent validity (Ghozali, 2021). The rule of thumb for the Average Variance Extracted (AVE) value is 0.5 (Ghozali, 2021). In this study, the AVE (Average Variance Extracted) value for each variable is shown in Table 7.
Table 7: Average Variance Extracted (AVE) Laten
Variabel
AVE Value
PEU 0,713
PEOU 0,971
IEBT 0,936
SMM 0,966
SM 0,949
Based on the Average Variance Extracted (AVE) value in Table 7, it is stated that the Average Variance Extracted (AVE) value for each variable is greater than 0.5. Thus, it can be concluded that this study has met sufficient Convergent Validity criteria. The rule of thumb for the Cross Loading value is that the Cross Loading value of an indicator for a construct must be greater than the Cross Loading value for that indicator for another construct (Ghozali, 2021). In this study the value of Cross Loading is shown in Table 8.
Table 8: Cross Loading Value Variabel
Laten
Perceived Usefulness
Perceived Ease of Use
Internet/ E- Business Technology
Social Media Marketing
Sustainability MSME’s
PEU1 0,870 0,343 0,325 0,387 0,537
PEU2 0,788 0,387 0,370 0,464 0,429
PEU3 0,878 0,343 0,327 0,403 0,549
PEU4 0,798 0,388 0,371 0,470 0,439
PEU5 0,883 0,359 0,328 0,405 0,569
PEOU1 0,428 0,986 0,953 0,330 0,389
PEOU2 0,458 0,993 0,971 0,359 0,424
PEOU3 0,404 0,998 0,996 0,332 0,362
PEOU4 0,475 0,982 0,966 0,374 0,437
PEOU5 0,376 0,981 0,981 0,309 0,333
IEBT1 0,472 0,971 0,980 0,376 0,444
IEBT2 0,302 0,917 0,955 0,273 0,267
IEBT3 0,409 0,943 0,970 0,344 0,361
IEBT4 0,451 0,992 0,993 0,353 0,417
IEBT5 0,363 0,919 0,961 0,325 0,319
IEBT6 0,407 0,988 0,999 0,339 0,370
IEBT7 0,428 0,986 0,993 0,330 0,389
IEBT8 0,329 0,921 0,966 0,296 0,290
SMM1 0,446 0,312 0,325 0,974 0,437
SMM2 0,508 0,340 0,340 0,994 0,492
SMM3 0,541 0,364 0,342 0,981 0,529
SM1 0,592 0,395 0,372 0,490 0,993
SM2 0,509 0,351 0,355 0,453 0,930
SM3 0,606 0,394 0,367 0,505 0,988
SM4 0,568 0,367 0,338 0,458 0,966
SM5 0,602 0,412 0,388 0,509 0,968
SM6 0,576 0,370 0,342 0,471 0,980
SM7 0,602 0,398 0,371 0,499 0,995
Based on the Cross Loading values in Table 8, it can be concluded that the indicators in a construct in this study have met the discriminant validity criteria because they have a Cross Loading value that is greater than the Cross Loading value of that indicator to another construct.
In addition, the value of discriminant validity is measured using the root value of the AVE value. The rule of thumb for the root AVE value is to compare the root AVE value of a construct with the correlation of that construct with other constructs (Ghozali, 2021). In this study, the roots of the AVE values are shown in Table 9.
Table 9: Fornell and Larcker’s AVE Root Value Variabel
Laten
Perceived Usefulness
Perceived Ease of Use
Internet/ E- Business Technology
Social Media Marketing
Sustainability MSME’s Perceived
Usefulness 0,844 Perceived Ease
of Use 0,435 0,985
Internet/ E- Business Technology
0,411 0,950 0,967
Social Media
Marketing 0,509 0,346 0,342 0,983
Sustainability
MSME’s 0,596 0,395 0,372 0,497 0,974
Based on the AVE root value in Table 9, it is stated that the AVE root value in a construct is greater in value than the correlation of the construct with other constructs. Thus, it can be concluded that this study met sufficient discriminant validity criteria. Reliability is measured using Cronbach's Alpa (CA) and Composite Reliability (CR) values with CA and CR benchmarks having to be greater than 0.7 (Abdillah, 2018). In this study, CA and CR values are shown in Table 10.
Table 10: Reliability Test Result
Variabel Laten Cronbach
Alpha (CA)
Composite Reliability (CR)
Keterangan
Perceived Usefulness 0,899 0,925 Reliable
Perceived Ease of Use 0,992 0,994 Reliable
Internet/e-Business Technology
0,990 0,991 Reliable
Social Media Marketing 0,982 0, 988 Reliable
Sustainability MSME’s 0,991 0,992 Reliable
Based on the Cronbach's Alpha (CA) and Composite Reliability (CR) values in Table 10, it is stated that the Cronbach's Alpha value and Composite Reliability value for each variable is greater than 0.7. Thus, it can be concluded that this research has fulfilled sufficient reliability criteria. The results of testing the structural model consisting of Beta Standardized values and the T-Value in this study is shown in Table 11.
Table 11: T-Values Result
Path T-
Values
Path Coefficient
P Values
Keterangan
Perceived Usefulness > Internet/e- Business Technology
2,030 -0,023 0,043 H1 Proven Perceived Usefulness >
Social Media Marketing
9,559 0,451 0,000 H2 Proven
Perceived Ease of Use > Internet/e- Business Technology
223,167 0,998 0,000 H3 Proven Perceived Ease of Use > Social Media
Marketing
1,231 -0,203 0,219 H4 Not
Proven Internet/e-Business > Social Media
Marketing
2,231 0,357 0,026 H5 Proven
Internet/e-Business Technology >
Sustainability MSME’s
5,173 0,299 0,000 H6 Proven
Social Media Marketing >
Sustainability MSME’s
9,139 0,419 0,000 H7 Proven
Based on the results of data processing, the results of the coefficient of determination are obtained as follows.
Table 12: Determination Coefficient Test Results
Variable R-Square Description
Internet/e-Business Technology 0,977 Strong
Social Media Marketing 0,281 Moderate
Sustainability MSME’s 0,293 Moderate
Based on table 12 above, the results of the coefficient of determination from the results of the calculation of 𝑅2 x 100% are obtained, the results are as follows. (0.977x100%) = 97.7%, these results show that 97.7% contributes to the effect of exogenous variables (PEU and PEUO) on the endogenous variable (IEBT), while the remaining 2.3% is a contribution to the influence of IEBT outside this research. (0.281x100%) = 28.1%, the results show that 28.1% contributes to the influence of exogenous variables (PEU, PEUO and IEBT) on endogenous variables (SMM), while the remaining 71.9% is a contribution to the influence of QMS outside of this research. (0.293x100%) = 29.3%, these results show that 29.3% contributes the influence of
exogenous variables (PEU, PEUO, IEBT and SMM) to endogenous variables (SM), while the remaining 70.7% is a contribution influence on SM outside of this study.
Table 13: Effect Size Score Result
Path F-square Description
Perceived Usefulness > Internet/e-Business Technology 0,018 Small Perceived Usefulness > Social Media Marketing 0,225 Medium Perceived Ease of Use > Internet/e-Business Technology 34,918 Big Perceived Ease of Use > Social Media Marketing 0,001 Small Internet/e-Business Technology > Social Media Marketing 0,004 Small Internet/e-Business Technology > Sustainability MSME’s 0,065 Small Social Media Marketing > Sustainability MSME’s 0,219 Medium
Based on Table 13 above, it can be seen that small relationships are found in four relationships, namely Perceived Usefulness towards Internet/e-Business Technology, then Perceived Ease of Use towards Social Media Marketing, then Internet/e-Business Technology towards Social Media Marketing, and Internet/ e-Business Technology towards MSME's Sustainability.
Intermediate relationships are found in two relationships, namely Perceived Usefulness to Social Media Marketing and Social Media Marketing to MSME's Sustainability. The biggest relationship is in one relationship, namely Perceived Ease of Use towards Internet/e-Business Technology.
The results of this GOF test are obtained from the square root of the multiplication between the average variance extracted and the average R-square. GOF itself has a value limit between 0 and 1, with a classification of values of 0.1 (small GOF), 0.25 (medium GOF), and 0.36 (large GOF) (Haryono, 2017).
Table 13: GOF Score Result
Laten Variable AVE
Value
R square
PEU 0,713 -
PEOU 0,971 -
IEBT 0,936 0,977
SMM 0,966 0,281
SM 0,949 0,293
Avarage 0, 907 0,517
The following is the result of calculating the Goodness of Fit that has been obtained by researchers with the formula:
GOF = √̅𝐶̅𝑜̅̅𝑚̅̅̅ × 𝑅2 GOF = √0.907 × 0.517
GOF = √0.468 GOF = 0.684
Based on the results of the goodness of fit test calculations above, it can be concluded that in this study a fit value of 0.684 was obtained. Where according to the category that has been submitted by Haryono (2017) that the value that has been obtained is in the large category.
4.3. Conclusion
This research was conducted on 400 respondents who met the criteria, namely UMKM Bandung City and two filter questions at the beginning of the questionnaire. This study aims to find out how the Impact of Perceived Usefulness and Perceived Ease of Use on Internet/e-
Business Technology and Social Media Marketing for the Sustainability of MSMEs. (Case Study of MSMEs in the City of Bandung During the Pandemic). Data collection and data management have been carried out to obtain the following conclusions:
1) The variable Perceived Usefulness has a negative and significant impact on the Internet/e- Business Technology variable for MSMEs in the city of Bandung.
2) The variable Perceived Usefulness has a positive and significant impact on the Social Media Marketing variable for MSMEs in the city of Bandung.
3) The variable Perceived Ease of Use has a positive and significant impact on the Internet/e- Business Technology variable for MSMEs in the city of Bandung.
4) The Perceived Ease of Use variable does not have a positive and significant impact on the MSME Social Media Marketing variable in the city of Bandung.
5) The Internet/e-Business Technology variable has a positive and significant impact on the MSME Social Media Marketing variable in the city of Bandung.
6) The Internet/e-Business Technology variable has a positive and significant impact on the MSME Sustainability variable in Bandung City.
7) The Social Media Marketing variable has a positive and significant impact on the MSME Sustainability variable in the City of Bandung.
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