Email: ijbe.
feubb@gmail.
http://ojs.
ijbe-research.
com/index.
php/IJBE/index Digital Technology and Consumer Purchase Decisions in Basic Necessities Purchases in Ogan Komering Ilir Regency Muji Gunartoa.
Erizia Putrib Universitas Sriwijaya Universitas Bina Darma mgunarto@hotmail.
Abstract This study investigates the impact of digital technology utilization on consumer purchase decisions for necessities through the AISAS (Attention.
Interest.
Search.
Action.
Shar.
model, focusing specifically on users of the Ayo SRC application in Ogan Komering Ilir Regency.
Indonesia.
Despite the significant growth in the number of application users, there remain challenges in converting user Interest and Search activities into actual purchase Actions.
Employing a quantitative associative approach, data were collected from 249 active application users and analyzed using Structural Equation Modeling based on Partial Least Squares (SEM-PLS).
The findings revealed that digital technology significantly enhances consumer Attention.
Interest, and Search behaviors.
However, only the Attention stage significantly influenced actual Purchase Decisions.
These results underline the critical role of creating attention-grabbing digital content to facilitate effective consumer conversion.
The study offers theoretical insights into digital consumer behavior within the AISAS framework and practical recommendations for improving digital marketing strategies, particularly in optimizing consumer Attention to drive purchasing behaviors on digital platforms.
Article Info
A Received A Revised A Published A Pages A DOI
A JEL
A Keywords : 26thJanuary 2025
: 20th May 2025
: 28th August 2025
: 376-394
: http://dx.
org/10.
33019/ijbe.
: M31
: Digital Technology.
Purchase Decision.
AISAS Model.
Consumer Behavior.
Ayo SRC Application This work is licensed under a Creative Commons Attribution 4.
0 International License.
Introduction The development of the internet and social media has shifted the paradigm of economic activities from face-to-face systems to online systems.
This transformation enables the expansion of markets without geographical and temporal limitations, covering both national and international scales (Cotula, 2013.
Luo & Tung, 2.
Data from Google.
Temasek, and Bain & Company show a significant increase in Indonesia's digital economy in 2020 (Anggraini & Gunarto, 2024.
Colditz, 2023.
Ramadhan & Gunarto, 2.
, driven by fundamental changes in social patterns and consumer spending due to digitization (Monteiro et al.
, 2.
Social media has become a catalyst in social interaction and shopping activities, creating intense internet traffic.
This phenomenon represents the evolution of word of mouth into a digital form that is effective in attracting customers.
This transformation is closely linked to the influence of digital marketing strategies implemented by companies to promote and market their products (Sharabati et al.
, 2.
The internet technology revolution has catalyzed significant changes in consumer behavior, especially in shopping preferences.
Ecommerce has emerged as an efficient solution for transactions, offering time and cost The accessibility of e-commerce to reach both local and international markets has further increased its appeal to the public, enabling transactions without physical interaction between buyers and sellers (Azizah & Yuningsih, 2023.
Dewi et al.
, 2.
Purchase decisions are a complex process in determining the optimal choice for product acquisition, involving stages such as problem identification, information search, alternative evaluation, decision-making, and post-purchase evaluation (Karimi et al.
, 2.
In the online context, purchasing decisions are influenced by multiple factors, including personal characteristics, vendor credibility, website quality, and attitudes toward online purchases (Azizah & Yuningsih, 2023.
Dewi et al.
, 2.
Digital marketing has transformed the contemporary marketing landscape, surpassing conventional boundaries in promotional creativity (Ramadhan & Gunarto, 2.
defines it as the exploitation of digital technologies to create communication channels with potential recipients, while emphasizing the use of electronic media for promoting products or services.
The AISAS (Attention.
Interest.
Search.
Action.
Shar.
model has emerged as a comprehensive framework for analyzing the purchasing decision process in the digital age.
This model describes the consumer journey from the attention stage (Attentio.
, the emergence of interest (Interes.
, information search (Searc.
, purchasing decision (Actio.
, to sharing experiences (Shar.
(Anggun Sari Sasmita & Nila Sartika Achmadi, 2022.
Sherwin et al.
, 2.
The implementation of digitalization in Ogan Komering Ilir Regency facilitates community access to information.
For example, when accessing the marketplace for community economic empowerment and supporting MSMEs Go Digital.
The impact is reducing poverty rates in Ogan Komering Ilir Regency.
The local government is also digitizing MSMEs, which number approximately 17 thousand in this Regency, by creating a local marketplace, then we encourage MSMEs to go digital, such as product photography This work is licensed under a Creative Commons Attribution 4.
0 International License training, then packaging and others so that MSMEs in Ogan Komering Ilir Regency can enter Overall, digital transformation plays an important role in improving the performance of MSMEs in Ogan Komering Ilir Regency.
However, the adoption of digital technology by MSMEs still faces several challenges, such as limited access to the internet, low levels of digital literacy, and lack of support from the government.
The government and relevant stakeholders need to work together to overcome these challenges and encourage the adoption of digital technology by MSMEs.
Thus.
MSMEs in Ogan Komering Regency can optimally utilize digital technology to improve their performance, competitiveness, and growth in the digital era.
The AYO SRC application is different from other applications in that it has various services such as connecting shop owners with trusted distributors so that shop owners can shop for merchandise online.
However, shop owners are still given the freedom to shop elsewhere if they are considered more profitable.
Not only useful for shop owners.
AYO SRC can also be used by consumers to find SRC grocery stores in various regions.
The application also has a AuPay CornerAy feature that can be used by shop owners and consumers to provide convenience in digital payments.
In addition, the Ayo SRC application also provides an opportunity for local distributors and producers to utilize SRC grocery stores to sell their products through AuLocal CornerAy.
The implementation of digital marketing in Ogan Komering Ilir Regency, particularly through the AYO SRC application launched by Sampoerna on May 10, 2019, has become a catalyst for digital transformation in grocery stores.
This application offers comprehensive features for business development and transaction enhancement, including e-ordering and Cash on Delivery systems (Hanifah & Restianto, 2.
The number of Ayo SRC application users in Ogan Komering Ilir Regency has significantly increased over recent years.
Specifically, the number of users rose from 302 in 2022 to 523 in 2023, representing an annual growth rate of approximately 73.
This growth continued into 2024, albeit at a lower rate of around 25.
81%, bringing the total number of users to 658.
The deceleration in user growth suggests that the application may be entering a maturity phase, indicating the necessity for more targeted marketing strategies to attract new users and retain the existing user base effectively (Hanifah & Restianto, 2.
However, the implementation of digital marketing through the Ayo SRC application still faces various challenges.
From the perspective of accessibility and interactivity, the limitations of the marketing platform and the lack of activity on social media hinder the accessibility of information and interaction with consumers.
The aspects of entertainment and informativeness also require optimization to improve consumer understanding of the transaction process and application features.
Changes in consumer behavior in the digital era also bring challenges for companies.
First, with the abundance of information available online, consumers tend to be more selective in choosing the brands or products they choose.
They trust reviews from other consumers more than traditional marketing claims.
Therefore, companies must pay attention to their brand reputation online and strive to obtain positive This work is licensed under a Creative Commons Attribution 4.
0 International License reviews from consumers.
Second, in the digital era, consumers have higher expectations of the experience provided by companies.
They want fast, responsive, and personalized service.
Companies must be able to face this challenge by strengthening customer service, increasing response speed, and personalizing communication with consumers.
This study aims to analyze the influence of digital technology usage on consumer purchase decisions for basic goods in Ogan Komering Ilir Regency, focusing on indicators such as accessibility, interactivity, entertainment, credibility, irritation, and informativeness.
The study employs a quantitative approach, collecting data through questionnaires and adopting the AISAS model as the analytical framework.
The results of this study are expected to contribute to the theoretical development of understanding purchase decisions through the AISAS model in the context of digital technology, as well as provide practical implications for the development of digital marketing strategies for grocery stores in Ogan Komering Ilir Regency.
The findings can serve as a reference for business practitioners in optimizing digital services to enhance consumer engagement with the Ayo SRC application.
Literature Review The development of digital technology has changed the way companies market their products and services.
Digital marketing has become an essential instrument in modern marketing strategies, especially in the context of grocery sales.
This section will discuss the key concepts related to digital marketing, purchase decisions, and the AISAS model in the context of digital marketing.
Digital Marketing and Components Digital marketing has become a key element in contemporary marketing strategies.
Digital marketing is a promotional activity conducted for a brand or product using electronic media (Christina et al.
, 2019.
Swami, 2.
The real-time nature and limitless reach of digital marketing make it an effective tool for promoting products (Ramadhan & Gunarto, 2.
There are several factors that influence the effectiveness of digital marketing (BermeoGiraldo et al.
, 2022.
Castayeda et al.
, 2020.
Nuseir & Aljumah, 2.
First, accessibility plays a fundamental role, as users must be able to easily access information and services Providing clear and transparent information is essential to encourage application usage and positively affect purchasing decisions (Zhou et al.
, 2.
Second, interactivity refers to two-way communication between the application and the consumer, and it is important for companies to better understand consumer needs (Endacott, 2.
Third, entertainment involves the application's ability to offer an enjoyable experience while conveying information.
engaging design and content are vital to enhance consumer engagement (Kim et al.
, 2.
Fourth, credibility reflects the level of trust consumers place in the application and its information, finding that credibility significantly impacts consumer satisfaction and trust (Liu et al.
, 2023.
Metzger & Flanagin, 2.
Fifth, irritation encompasses factors that reduce digital marketing effectiveness, such as manipulative tactics or negative user experiences, and underscores the need to minimize irritation to preserve consumer trust (Liu et al.
, 2023.
Metzger & Flanagin, 2.
Finally, informativeness is the This work is licensed under a Creative Commons Attribution 4.
0 International License applicationAos capacity to deliver accurate and useful information.
it is identified as a key determinant of successful digital marketing (Dewi et al.
, 2023.
Iqbal, 2.
Digital marketing strategies enhance consumer interactions by increasing accessibility, interactivity, and informativeness, thus effectively capturing consumer attention, generating interest, and stimulating further information search activities (Anggraini & Gunarto, 2024.
Santosa & Vanel, 2.
Therefore, the following hypotheses are proposed:
H1: The use of digital technology positively and significantly influences consumer Attention.
H2: The use of digital technology positively and significantly influences consumer Interest.
H3: The use of digital technology positively and significantly influences consumer Search The AISAS Model in Digital Marketing The AISAS model (Attention.
Interest.
Search.
Action.
Shar.
is an evolution of the traditional AIDMA model, reflecting changes in consumer behavior in the digital era (Adlan & Indahingwati, 2020.
Anggun Sari Sasmita & Nila Sartika Achmadi, 2022.
Cahyaningsih.
Jaelani et al.
, 2023.
Saadah et al.
, 2023.
Sherwin et al.
, 2.
This model can be visualized as follows:
Source : (GMO Research & AI, 2.
Figure 1.
The AISAS Model This work is licensed under a Creative Commons Attribution 4.
0 International License The table below illustrates the application of the AISAS concept in the context of digital Table 1.
Example of AISAS Model Concept Application AISAS Variable Attention Interest Search Action Share Example of Application Consumers see a product advertisement on social media.
Consumers become interested in learning more about the product, prompting them to browse the product's social media accounts.
Consumers search for more specific information about the product via Google, such as ingredients, reviews from other users, and the benefits and advantages of the product.
Consumers decide to purchase the product after being convinced of its quality based on the information obtained from Google or social media.
Consumers share their experience after purchasing or using the product on their own social media accounts.
Source: (GMO Research & AI, 2.
The AISAS model consumers will pay attention to product promotion activities that can arouse interest, then consumers will collect more complete product information by searching, and then will make a purchase (Sherwin et al.
, 2.
After that, it is continued by sharing the experience of consuming the purchased product with others.
The AISAS model asserts that consumer attention, interest, and active information search are sequential steps leading to purchase decisions.
Prior studies suggest that consumer decisions in the digital era are heavily influenced by how effectively a product or service captures attention, sustains interest, and meets informational needs (Cahyaningsih, 2020.
Jaelani et al.
, 2.
Thus, the following hypotheses are formulated:
H4: Consumer Attention positively and significantly influences Purchase Decisions.
H5: Consumer Interest positively and significantly influences Purchase Decisions.
H6: Consumer Search behaviors positively and significantly influence Purchase Decisions.
Purchase Decision in the Digital Context The purchase decision is a complex and dynamic process influenced by a variety of psychological, social, and contextual factors that shape consumer behavior (Kotler & Armstrong, 2.
It involves sequential stages beginning with problem recognition, followed by information search, alternative evaluation, purchase decision, post-purchase evaluation, purchase timing, and payment method (Ayreni & Gunarto, 2.
In the digital marketing context, these stages are significantly affected by online environments where consumers have instant access to vast amounts of information, peer reviews, and personalized content, which facilitate more informed and confident decision-making (Cummins et al.
Hyubl & Trifts, 2.
Moreover, factors such as website usability, trustworthiness, social influence through digital communities, and seamless transactional processes play critical roles in guiding consumers through the decision journey (Bhaskaran, 2024.
Rajib & Roy, 2.
Post-purchase experiences, including after-sales service and digital feedback mechanisms, further impact consumer satisfaction and brand loyalty, emphasizing the This work is licensed under a Creative Commons Attribution 4.
0 International License importance of continuous engagement beyond the point of sale (Ferraz et al.
, 2.
Therefore, a comprehensive understanding of the digital purchase decision process enables marketers to develop integrated strategies that optimize consumer experience at every touchpoint, ultimately driving competitive advantage in the digital marketplace.
Integration of Digital Marketing and Purchase Decision Research has demonstrated that digital marketing significantly influences consumer purchase A positive relationship between digital marketing and purchase decisions has been confirmed in empirical studies (Onsardi et al.
, 2.
Furthermore, digital marketing facilitates more effective promotional activities by enabling two-way communication between marketers and consumers (Adam & Gunarto, 2021.
Anggraini & Gunarto, 2024.
Ramadhan & Gunarto, 2.
The AISAS model provides an effective framework for understanding how digital marketing influences purchase decisions.
Each stage in this modelAifrom Attention to ShareAiplays a crucial role in shaping consumer purchase decisions and creating a sustainable marketing cycle.
This literature review indicates that digital marketing, purchase decisions, and the AISAS model form an interconnected system in the context of modern marketing.
A deep understanding of the components of digital marketing and the stages of consumer purchase decisions is essential for optimizing digital marketing strategies.
The AISAS model offers an effective framework for analyzing and enhancing the effectiveness of digital marketing in influencing consumer purchase decisions.
The AISAS model emphasizes that consumer decisions to purchase directly influence subsequent actions, such as actual buying behavior, and the tendency to share experiences post-purchase.
Research indicates that satisfied consumers are likely to engage in repeat purchases and recommend products to others through various digital channels (Batu, 2019.
Daruhadi, 2.
Hence, the following hypotheses are proposed:
H7: Purchase Decisions positively and significantly influence consumer Action.
H8: Consumer Action positively and significantly influences consumer Share behavior.
Research Methods This study uses a quantitative approach with a survey method to analyze the impact of digital technology usage on consumer purchase decisions in the purchase of basic commodities through the Ayo SRC application in Ogan Komering Ilir Regency.
Quantitative research is a systematic scientific study that analyzes phenomena and causal relationships through the collection of measurable data using statistical, mathematical, or computational techniques (Fadilla et al.
, 2023.
Gunarto, 2.
This study is associative in nature, which, according to (Sugiyono et al.
, 2.
aims to identify the relationship between two or more variables, examine their roles, effects, and the cause-and-effect relationship between the independent and dependent variables.
The variables under study include the use of digital technology (PTD) as the independent variable, purchase decision (PD) as the dependent variable, and the AISAS model (AISAS) as the mediating variable, consisting of Attention.
Interest.
Search.
Action, and Share.
This work is licensed under a Creative Commons Attribution 4.
0 International License The population of this study consists of all users of the Ayo SRC application in Ogan Komering Ilir Regency, totaling 658 individuals in 2024.
The sampling technique used is non-probability sampling with a purposive sampling method, with the criterion that respondents are active users of the Ayo SRC application.
ycu= 1 658.
,052 ) ycu= 2,645 ycu = 248,77 The sample size was rounded to 249, resulting in a total of 249 respondents.
Table 2 presents the operationalization of the research variables, which includes the definitions and indicators for each variable:
Table 2.
Operationalization of Research Variables Variable Definition Indicators Use of Digital Technology (PTD) Promotional activities carried out by a brand or.
Accessibility product using electronic media .
Interactivity .
Entertainment .
Credibility .
Irritation .
Informativeness Attention (ATT) A reaction from awareness that leads to increased .
Consumers discover new activity in concentration and narrowing of .
Consumers can recall attention towards an object.
The application attracts consumer attention, .
Consumers pay attention to the product.
Scale Likert Likert Interest (INT) The stage where an individual becomes interested .
The product is unknown to the Likert in learning more about a product, its advantages, consumer and the benefits it offers, and whether it meets.
Consumers are interested in making a purchase their needs.
The application entertains the .
The application alleviates consumer boredom, .
Products within the app are appealing to consumers Search (SEA) At this stage, consumers search for knowledge.
Consumers search for product Likert about products that have caught their interest.
Consumers obtain the information they need.
This work is licensed under a Creative Commons Attribution 4.
0 International License Variable Definition Indicators Scale .
Consumers see additional information from various available sources.
Action (ACT) Efforts to persuade potential buyers to make a.
Consumers trust the Likert purchase which is expected to result in actual .
Consumers are inclined to purchase behavior.
make a purchase, .
Consumers are confident in making a purchase, .
Consumers make the purchase Share (SHA) At this stage, consumers begin recommending the .
Consumers share the Likert application they use, products they have purchased to others.
Consumers share personal experiences after using the purchased product, .
Consumers recommend the product they bought to others.
Purchase Decision (PD) A process of consumer behavior that represents .
Product choice, .
Brand choice, what consumers believe when making a purchase .
Distributor choice, .
Purchase timing, .
Purchase quantity.
Likert Source: Author, 2025 Data analysis was conducted using Structural Equation Modeling (SEM) based on Partial Least Squares (PLS).
According to (Furadantin, 2.
SEM-PLS is effective for analyzing complex models with small samples and does not require the assumption of normal Mediation Testing uses the bootstrapping procedure to test the significance of indirect effects.
Model evaluation is performed using SmartPLS software, with evaluation criteria as shown in Table 3.
Table 3.
Model Evaluation Criteria Criterion Rule of Thumb R-Square 75, 0.
50, and 0.
25 indicate strong, moderate, and weak models, respectively.
Effect Size f2 02, 0.
15, and 0.
35 (Small.
Medium, and Larg.
QA Predictive Relevance A QA > 0 indicates that the model has predictive relevance.
A QA < 0 indicates that the model has poor predictive relevance.
qA Predictive Relevance 02, 0.
15, and 0.
35 (Weak.
Moderate, and Stron.
Significance (TwoTaile.
t-value 1.
65 (Significance Level = 10%), 1.
96 (Significance Level = 5%), and 2.
(Significance Level = 1%) Source: Author, 2025 This work is licensed under a Creative Commons Attribution 4.
0 International License This study adopts a systematic sampling approach to ensure adequate representation of various characteristics of Ayo SRC application users.
Data analysis was conducted in stages to ensure the validity and reliability of the research findings.
Result This study analyzes data from 249 users of the Ayo SRC application in Ogan Komering Ilir (OKI) Regency.
The demographic characteristics examined include gender, age, education level, source of information about the application, duration of use, and monthly income.
Table 4.
Respondent Characteristics Characteristic Gender
Age
Last Education Information Source Duration of Use Monthly Income
Category Male
Female < 20 years 21-30 years 31-40 years 41-50 years > 50 years JHS
SHS
Diploma BachelorAos Degree Postgraduate Social Media Google Family or Friends Other Sources < 1 years 1-2 years 2-3 years >3 years < Rp 2.
Rp 2.
000 - Rp 5.
> Rp 5.
Total Percentage (%) Source: Research Data, 2025 Table 4 shows that the majority of respondents are male .
%) with an age range of 31-40 years .
%), indicating strong adoption among working-age adults.
In terms of educational background, most respondents have completed high school .
%), which shows accessibility across various education levels.
The main source of information about the Ayo SRC application is word-of-mouth marketing, which seems to be very effective, particularly through Family or Friends .
%).
User retention appears to be strong, with 41% of respondents reporting a usage duration of more than 3 years, indicating a sustainable value proposition for users.
Lastly, the income analysis reveals that the majority of users earn between IDR 2-5 million per month .
%), showing strong penetration among middleincome consumers.
This work is licensed under a Creative Commons Attribution 4.
0 International License The analysis results indicate a high level of digital technology adoption among Ayo SRC application users.
The majority of respondents .
8%) agreed or strongly agreed that the application can be accessed quickly online, with 54.
2% agreeing and 40.
6% strongly Only a small proportion .
2%) expressed doubts or disagreed.
Regarding communication features, 95.
5% of respondents gave positive feedback on the availability of contact features .
hone and WhatsAp.
, which facilitate interaction with the applicationAos This data suggests that the implementation of digital technology has successfully enabled two-way communication between users and service providers.
The user experience aspect also received positive feedback, with 93.
1% of respondents agreeing that the application provides an enjoyable and entertaining experience.
This is in line with the findings of (Fauzi et al.
, 2.
which states that a positive user experience is strongly correlated with the level of digital technology adoption.
The analysis of the attention dimension reveals that the Ayo SRC application has successfully captured and maintained users' attention.
The data shows that 92.
7% of respondents obtained new information through the application, with 59.
4% agreeing and 33.
3% strongly agreeing.
This finding confirms the theory (Nori Dwi Apriandi, 2.
about the importance of novelty in capturing users' attention in the digital space.
The ability to remember the applicationAos content is also high, with 93.
2% of respondents stating that they can recall the information they received.
The distribution of answers shows strong consistency, with the majority of respondents .
%) paying attention to the products displayed in the application.
The interest dimension shows interesting results, with 92.
3% of respondents expressing interest in new products that they had not previously known.
This indicates the effectiveness of the application in introducing new products to consumers.
The data also reveals that 93.
of respondents are interested in purchasing products, reflecting a high potential for conversion from interest to action.
This finding is consistent with the research of (Cahyaningsih, 2.
on the relationship between interest and purchase intention in the context of e-commerce.
The analysis of information-seeking behavior shows a systematic pattern, with 96.
4% of respondents actively searching for additional information about products that caught their This data reflects high user engagement with the applicationAos content.
The effectiveness of the information presentation in the app is also shown to be high, with 94.
of respondents stating that they obtained the information they needed.
This suggests that the application has successfully met the information needs of its users.
The analysis of the action dimension reveals a high level of trust in the application, with 2% of respondents stating that they trust the information provided.
This finding aligns with the research of (Daruhadi, 2.
on the importance of trust in driving digital purchase The data shows that 92.
7% of respondents have a tendency to make a purchase, 7% have confidence in their purchase decisions.
Most significantly, 95.
2% of respondents reported having made an actual purchase through the application.
This work is licensed under a Creative Commons Attribution 4.
0 International License Based on the analysis of data from 249 respondents who are users of the Ayo SRC application in Ogan Komering Ilir (OKI) Regency, it was found that the majority of respondents showed a positive tendency to share their experiences using the application.
In the first indicator regarding sharing the application with others, 58.
6% of respondents agreed and 32.
strongly agreed.
This indicates a high level of organic viral marketing among users.
Regarding the sharing of personal experiences after using the product, 55.
8% of respondents agreed, and 34.
5% strongly agreed to share their experiences.
This finding is in line with previous research, which indicates that positive consumer experiences are more likely to be shared with others (Batu, 2.
The product recommendation aspect shows very positive results, with 53.
8% of respondents agreeing and 42.
2% strongly agreeing to recommend the products they purchased to others.
This data indicates a high level of user satisfaction with the products purchased through the Ayo SRC application.
The analysis of the purchase decision variable reveals a consistent pattern in consumer decision-making.
Regarding product selection, 59.
8% of respondents agreed, and 32.
strongly agreed that they made decisions based on their own preferences.
This indicates a high level of consumer autonomy in the purchasing process.
In terms of brand selection, 59% of respondents agreed, and 36.
1% strongly agreed that they chose a brand according to their This data indicates that consumers have a high brand awareness and consider brand factors in their purchase decisions.
Figure 2.
Final Outer Model The results of the convergent validity analysis indicate that the measurement model required several iterations to meet the expected criteria.
This work is licensed under a Creative Commons Attribution 4.
0 International License Table 5.
Outer Loading Final
INDICATORS
ACT-2
ACT-3
ACT
ACT-4
ATT-1
ATT-2
ATT-3
ATT-4
INT-2
ATT
INT
PTD
SEA
SHA
INT-3
INT-4
INT-5
KP-1
KP-5
PTD-1
PTD-2
PTD-3
PTD-6
SEA-1
SEA-2
SEA-3
SHA-1
SHA-2
SHA-3
Source: Author Data, 2025 The analysis of the Average Variance Extracted (AVE) shows that all variables have AVE values greater than 0.
50, confirming good convergent validity.
Table 6.
Average Variance Extracted (AVE) INDICATORS
Average Variance Extracted (AVE) ACT
ATT
INT
PTD
SEA
SHA
Source: Author Data, 2025 This work is licensed under a Creative Commons Attribution 4.
0 International License These findings indicate that the measurement instruments used in the study have good validity and can be relied upon to measure the intended constructs.
This result aligns with previous research, which highlights the importance of convergent validity in digital consumer behavior research (Purohit et al.
, 2.
The analysis of discriminant validity in the contemplative model was carried out by evaluating the cross-loading scores of the constructs.
A latent construct is considered to meet the discriminant validity criteria if the correlation between the indicator and its construct is higher than the correlation with other constructs.
The results of the discriminant validity test were conducted using SmartPLS 4.
Table 7.
Based on the results of the discriminant validity test, it was found that the square root of the AVE for each construct was greater than the correlations with the latent constructs it represents.
The cross-loading values overall have scores > 0.
5, indicating that the discriminant validity in this study can be considered good.
Table 7.
Cross-Loading for Discriminant Validity INDICATORS
ACT-2
ACT-3
ACT-4
ATT-1
ATT-2
ATT-3
ATT-4
INT-2
INT-3
INT-4
INT-5
KP-1
KP-5
PTD-1
PTD-2
PTD-3
PTD-6
SEA-1
SEA-2
SEA-3
SHA-1
SHA-2
SHA-3
ACT
ATT
INT
PTD
SEA
SHA
Source: Author Data, 2025 The reliability test using the PLS method was conducted through the composite reliability score, which must be > 0.
70, and Cronbach's Alpha to measure the lower bound of a construct's reliability.
The results of the reliability test are presented in Table 8.
This work is licensed under a Creative Commons Attribution 4.
0 International License Table 8.
Cronbach's Alpha and Composite Reliability VARIABLE
Cronbach's Alpha
Composite Reliability ACT
ATT
INT
PTD
SEA
SHA
Source: Author Data, 2025 The results of the construct reliability measurement in Table 8 show that all research data are valid and reliable, as the Composite Reliability values obtained are > 0.
7 and the Cronbach Alpha values are lower than the Composite Reliability.
This indicates that the instruments used have a high level of consistency and can be relied upon to measure the constructs being Table 9.
R-Square VARIABLE
ATT
INT
SEA
ACT
SHA
R-Square Adjusted R Square Source: Author Data, 2025 The analysis results show that the R-Square value for ATT is 0.
INT is 0.
SEA is 255.
KP is 0.
ACT is 0.
027, and SHA is 0.
This indicates that the influence of exogenous variables on ATT.
INT, and SEA can be considered weak, as the R-squared value is >0.
Meanwhile, the influence on KP and ACT is very weak, as the R-squared value is <0.
The influence on SHA is moderate, with an R-squared value >0.
Table 10.
Results of Direct Effect Testing CONNECTION
PTD -> ATT
PTD -> INT
PTD -> SEA
ATT -> KP
INT -> KP
SEA -> KP
KP -> ACT
ACT -> SHA
Original Sample Sample Mean Standard Deviation T Statistics P-Values Source: Author Data, 2025 This work is licensed under a Creative Commons Attribution 4.
0 International License Based on the test results in Table 10, it was found that: Digital Technology Use has a positive and significant effect on Attention .
-statistic = 18.
214, p < 0.
Digital Technology Use has a positive and significant effect on Interest .
-statistic = 10.
602, p < 0.
Digital Technology Use has a positive and significant effect on Search .
-statistic = 7.
806, p < 0.
Attention has a positive and significant effect on Purchase Decision .
-statistic = 2.
006, p < Interest does not have a significant effect on Purchase Decision .
-statistic = 0.
545, p > 0.
Search does not have a significant effect on Purchase Decision .
-statistic = 0.
194, p > 0.
Purchase Decision has a positive and significant effect on Action .
-statistic = 2.
p < 0.
Action has a positive and significant effect on Share .
-statistic = 22.
064, p < 0.
The model fit evaluation using the NFI value shows a result of 0.
553, indicating that the modelAos quality is not yet optimal.
The model is able to explain approximately 55.
3% of the observed data variation, but it has not yet reached the strong minimum standard .
This suggests that the modelAos fit with the data is not yet optimal.
This finding has important implications for the development of digital marketing strategies in the context of purchasing staple goods.
The use of digital technology has proven to be effective in influencing the early stages of the purchasing decision process .
ttention, interest, searc.
, but its impact on actual purchase decisions still requires strengthening.
This aligns with previous research that emphasizes the importance of integrating digital technology into retail marketing strategies.
The results of this study contribute theoretically to the understanding of digital consumer behavior, particularly in the context of purchasing staple goods through an application.
The high levels of sharing and autonomous purchase decisions indicate a shift in consumer behavior from traditional to digital, in line with technology adoption theory.
Practically, these findings can serve as a reference for e-commerce application developers in enhancing sharing features and product recommendation systems.
The high level of user experience sharing can also be leveraged for more effective viral marketing strategies.
Conclution and Suggestion This study demonstrates that the use of digital technology through the Ayo SRC application has a significant impact on the decision-making process for purchasing basic necessities in Ogan Komering Ilir Regency.
Based on data analysis from 249 respondents, it was found that the use of digital technology positively and significantly influences the Attention.
Interest, and Search stages in the AISAS model.
However, only the Attention stage had a significant effect on the Purchase Decision.
The results also reveal that the majority of Ayo SRC users are male .
%) with an age range of 31-40 years .
%) and a high school education level .
%).
The high adoption of digital technology is reflected in 94.
8% of respondents who appreciate the ease of access to the application, as well as 95.
5% who value the available communication features.
The research model shows a fairly good quality with an NFI value 553, though it has not yet reached the optimal standard.
This work is licensed under a Creative Commons Attribution 4.
0 International License Based on the research findings, several recommendations for improvement are as follows:
There is a need to develop application features that focus more on improving the conversion from the Interest and Search stages to Purchase Decision, as these stages have not shown significant influence.
It is important to optimize marketing strategies to increase penetration among female users and age groups outside of the 31-40 years range.
Strengthening the user experience and interactivity aspects of the application to increase user .
Developing digital education programs to improve technology literacy among users with varied education levels.
Implementing more attractive reward systems to encourage the sharing of user experiences, given the high effectiveness of wordof-mouth marketing in driving application adoption.
References