Identifying the Most Effective and Worthwhile PayLater Application for Gen Z in the Digital Era Using the TOPSIS Method ^†

Abstract

The development of digital technology has changed various aspects of life, including in the financial sector. One of the innovations that has received a significant amount of attention is the PayLater service. Generation Z, as a generation born in the digital era, has a unique consumption pattern. Members of Generation Z tend to look for financial solutions that are fast, practical, and accessible through technology. This study aims to provide guidance for Generation Z (age 20–28 years) in choosing the PayLater application that best suits their needs and financial situation. Using the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method, this study evaluates the effectiveness of several popular PayLater applications. Data were collected through an online questionnaire aimed at potential users who already had a monthly income. The criteria used in the assessment include the average transaction value, difficulty in paying installments, data security and privacy, ease of application access, and interest rates. The results of the analysis show that Shopee PayLater has the highest preference score, making it the best choice for Generation Z. This research is expected to contribute to improving financial literacy and helping Generation Z to make better decisions regarding financial services in the digital era.

1. Introduction

The development of digital technology has changed various aspects of life, including in the financial sector. One of the innovations that has received a significant amount of attention is the PayLater service. Buy Now Pay Later (BNPL), commonly known as PayLater, is a service that allows consumers to purchase goods or services and pay for them at a later time without the need for a credit card. This convenience makes PayLater a practical solution, especially for the younger generation who do not yet have access to formal financial products [1]. Based on several surveys, nine out of ten BNPL consumers have changed their shopping habits because they believe BNPL provides quick access and affordable prices. Although simple to use, this service has a number of drawbacks. Since customers often forget the specified payment dates and face financial difficulties, the use of BNPL services can trigger careless spending patterns [2]. Generation Z, born between 1995 and 2012, has a unique consumption pattern: they tend to seek financial solutions that are fast, practical, and accessible through technology [3]. Based on a survey conducted, 60% of Gen Z consumers in Indonesia prefer using digital-based services to meet their needs, including financial services such as PayLater [4].

However, the existence of various PayLater applications in the market poses a challenge for consumers, who must determine the most effective application according to their needs. Improper selection of the PayLater application can have serious impacts, such as increasing financial burdens due to hidden service fees, unprotected personal data security risks, and the potential for uncontrolled use that leads to debt problems that are difficult to resolve. This negative impact not only affects the financial situation of users, but also their mental health and quality of life in the long term. Research shows that the unwise use of PayLater can lead to consumptive behavior and impulse purchases, which can potentially cause financial problems for users [5]. Generation Z, who are 20 to 28 years old in 2025, already have a monthly income that allows them to take advantage of various PayLater applications. To help them choose the PayLater application that best suits their needs and financial situation, we used the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method to determine the most optimal choice. This method provides an objective and structured evaluation, thereby minimizing the risk of inappropriate decision making. By using TOPSIS, Generation Z can choose the PayLater application based on various important criteria, such as features, cost, security, and ease of use. This approach has a number of advantages because it allows for more measured and thorough decision making and helps users to avoid making decisions based on subjective opinions [6].

1.1. Problem Formulation

The field observations carried out by the researcher revealed several questions, including:

• What are the relevant criteria in assessing the effectiveness and efficiency of PayLater applications for Generation Z in the digital era?
• How can the application of the TOPSIS method help in identifying the most effective and worthwhile PayLater application for Generation Z?
• Which PayLater application best meets the TOPSIS criteria for Generation Z in Indonesia?

1.2. Research Objectives

Based on the formulation of the problem above, the purpose of the research is to determine the most effective and feasible PayLater application for Generation Z in the digital era. We use the TOPSIS method as an evaluation framework, with the main purpose of providing objective guidance for Generation Z in choosing a PayLater application that meets their needs, based on payment flexibility, service fees, ease of access, application reputation, and data security and privacy. The results are expected to help Generation Z in choosing services that are practical, efficient, and in agreement with their lifestyle.

2. Research Foundation

2.1. Profile of the Research Institute

Nusa Putra University is a higher education institution located in Sukabumi, West Java. Founded with the aim of providing quality education that blends modern technology and local wisdom, the university continues to grow into a nationally and internationally recognized center for innovation and research. As a dynamic educational institution, Nusa Putra University has various faculties that support the development of science and technology, one of which is the Faculty of Engineering, Computers, and Design. This faculty houses the Information Systems Study Program, which is where this research was carried out. This research involves respondents from the 2021–2022 cohort who were aged between 20 and 28 years in 2025 and already have a monthly income. This study cohort was chosen to ensure that the results of the research are relevant to the user group that actively uses PayLater services to manage their finances.

2.2. Study Book

2.2.1. Concept of Paylater

PayLater is a financial service that allows users to purchase goods or services with a deferred payment system, usually in installments, without a credit card. PayLater services are increasingly popular in Indonesia, especially among Generation Z, who prioritize convenience and flexibility in financial transactions. PayLater is also considered a form of consumptive credit that can increase people’s purchasing power, but it has risks such as late payments and high interest rates [7].

2.2.2. Generation Z and Digital Consumption Behavior

Generation Z is a group born between 1997 and 2012; they are known as digital natives, which means that they are very familiar with digital technology and services in their daily lives. Generation Z tends to prefer digital transactions over conventional payment methods. They are also more interested in services that offer convenience, efficiency, and flexibility, such as PayLater [8].

2.2.3. TOPSIS Method in PayLater Evaluations

The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is one of the multi-criteria decision-making methods that is often used in comparative analyses of financial services. TOPSIS can provide more objective evaluation results by considering various assessment factors, such as interest rates, data security, ease of use, and payment flexibility [9].

2.2.4. Security and Privacy in the Use of PayLater

Data security and user privacy are important aspects of PayLater services. A study conducted shows that personal data protection and privacy policy transparency are some of the main factors that users are concerned about in choosing PayLater service. Users tend to choose services that have strong data encryption and protection against leaks of personal information [10]. By referring to the various studies cited above, this study uses the TOPSIS method to identify the most effective PayLater application in accordance with the needs of Generation Z in Indonesia.

2.3. Research Methods

This research uses a quantitative method by collecting data through conducting a survey of PayLater service users, application developers, and related regulators. Primary data were obtained through a Likert-scale-based questionnaire, which was used to measure users’ preferences, experiences, and risk perceptions. The TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) approach is used to determine user preferences for PayLater service features based on predetermined criteria, such as:

• Interest
• Data security and privacy
• Number of limits
• Ease of application access

We used a Likert-scale-based questionnaire to measure users’ preferences, experiences, and risk perceptions.

2.4. Research Model

This research model uses the TOPSIS approach, which involves the following steps:

• Collection of data: survey about PayLater features.
• Data normalization: adjusting the data to be equivalent.
• Calculation of weights: provides importance values for each criterion.
• Determining the ideal solution: compares data with best and worst results.
• Calculation of the final result: ranking features based on distance to the ideal solution.

3. Results and Discussion

3.1. Data Collection Methods

The research was carried out using quantitative methods through the distribution of questionnaires online via the Google Forms application in the first two weeks in December. The questions in the questionnaire were prepared based on the results of the analysis of three PayLater applications: namely, Kredivo, Akulaku, and Shopee PayLater. As such, the measured aspects reflect the user experience of these three services.

The target respondents are 100 people from the Information Systems Study Program Class of 2021–2022 aged 20 to 28 years old in 2025 and who already have a monthly income. After the data collection stage is completed, the quality of the data is checked for the last two weeks in December to ensure validity and reliability, in accordance with the predetermined research schedule.

Once the number of respondents met the target and the quality of the data was verified, the next step was to identify the best PayLater application based on the results of the questionnaire using the TOPSIS method. This method was chosen because it provides an accurate quantitative approach for assessing the level of user satisfaction with the available PayLater services, taking into account various previously analyzed criteria from Kredivo, Akulaku, and Shopee PayLater [11].

3.2. Calculating Results Using the TOPSIS Method

In this study, the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method is used to determine the best alternative based on several predetermined criteria. The criteria used in this calculation are provided below.

3.2.1. Data Criteria

Table 1. Criteria and weights of assessment.

ID	Criterion	Weight (%)
C1	Interest	35
C3	Data Security and Privacy	30
C4	Number of Limits	25
C5	Ease of Application Access	15

shows the evaluation criteria used in the study along with their respective weights. The weights were assigned based on the priority level of each criterion obtained from the respondents’ questionnaire results. In this case, Interest (C1) has the highest weight of 35%, followed by Security and Data Privacy (C3) with 30%, Credit Limit (C4) with 25%, and Application Accessibility (C5) with the lowest weight of 15%.

3.2.2. Criteria Weighting Data

After calculating the average of the questionnaire results, the following weights are obtained in

Table 2. Criteria weighting data.

Platform		Criterion
	Interest	Data Security and Privacy	Number of Limits	Ease of Application Access
	C1	C2	C3	C4
Kredivo	3.78	4.7	3.74	3.97
Akulaku	3.82	3.65	3.23	4.55
Shopee Paylater	3.52	4.5	4.91	4

:

This Table 2 illustrates the average evaluation results provided by respondents for each criterion across the selected PayLater platforms. The assessment is based on four primary criteria: Interest (C1), Data Security and Privacy (C2), Number of Limits (C3), and Ease of Application Access (C4). These criteria were established through an extensive literature review and subsequently validated by means of questionnaires administered to respondents. The findings reveal that each platform demonstrates distinct strengths and weaknesses, which subsequently form the basis for the vector normalization process applied in the following stage of analysis.

3.2.3. Vektor Normalization

The calculations use normalized matrices with vector normalization, for example: (Normalized matrix = root of the power of values on each criterion (x = √C^2)).

In

Table 3. Vektor Normalization matrix.

X1	X2	X3	X4
6.424266495	7.460730527	5.734858324	7.243162293

, the denominator can be seen as the square root of the sum of squares for each column (criterion), Thus:

• X1 = 6.4243 → obtained from √(Σ value² for criterion 1).
• X2 = 7.4607 → normalization result for criterion 2.
• X3 = 5.7349 → normalization result for criterion 3.
• X4 = 7.2432 → normalization result for criterion 4.

3.2.4. Normalization Matrix

The next step is to add the weight value to each normalization value by multiplying the normalization value by the weight (example: CI weight value × normalized weight Y1 = −20.59379076), so that the following results are obtained.

In

Table 4. Calculation with Normalization Matrix.

Alternative	Name	Interest Rate	Data Security and Privacy	Amount of Limit	Ease of Access Applications
Weighted criteria		Y1	Y2	Y3	Y4
A1	Kredivo	−20.59379	18.898954	16.3038029	8.2215471
A2	Akulaku	−20.81171	14.676847	14.0805571	9.4226799
A3	Shopee Paylater	−19.17729	18.094743	12.6855793	8.2836747

, we can see that if we focus on security and limits, Kredivo is superior, then if we focus on ease of access, Akulaku is superior, and finally if we focus on lower interest, Shopee PayLater is superior.

The calculations used in this method are:

• Vi = ∑(wj × xij)
• Vi = total score for the third alternative
• Wj = weight of the j criterion
• xij = value of the third alternative in the j criterion

3.2.5. The Ideal Solution Matrix

Once the ideal solution value is known, the next step is to find the total distance and ranking, which represent the distance between the value of each alternative and the matrix of positive ideal solutions and the negative ideal solution matrix.

3.2.6. Calculating Total Distance

The distance of an alternative to the positive (A+) and negative (A+) ideal solutions is calculated using the Euclidean distance formula:

Di⁺ = √ Σ (Yij − Aj⁺)², j = 1 … n

Di⁻ = √ Σ (Yij − Aj⁻)², j = 1 … n

In the

Table 5. Distance calculation.

Alternative Distances	Positive (+)	Negative (−)	D+ + D−
A1	1.857203276	5.564639943	7.421843219
A2	5.04384388	1.84083761	6.88468149
A3	3.877580477	3.789093073	7.66667355

, it can be concluded that: D⁺ (Positive Distance), the distance of an alternative to the positive ideal solution (the best value for each criterion), the smaller the D⁺, the closer the alternative is to the ideal condition.

3.2.7. Reference Value and Ranking Results

The last step involves finding the preferences value to determine the ranking of each PayLater application with the preferences formula: Negative/(Positive Value + Negative Value). The results are given below.

Based on

Table 6. Preferred values and alternative rankings.

Name	Alternative	V	Ranking
Kredivo	A1	0.750	1
Akulaku	A2	0.267	3
Shopee Paylater	A3	0.494	2

the calculation of preferences in the selection of the best PayLater platform analyzed using the TOPSIS Method shows that the one that exhibits the three highest reference values is Kredivo, with the highest value of 0.750. Thus, Kredivo is the best solution when choosing a PayLater platform for Generation Z.

4. Discussion

This study concludes that, based on calculations made using the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method, the Kredivo application ranks first as the most superior PayLater service among the options available. These results show that Kredivo exhibits the best performance in meeting the various criteria evaluated, such as ease of use, interest rates, payment flexibility, and customer service.

This finding is in line with previous research that highlighted the advantages of Kredivo as a PayLater service. For example, in a study conducted by Maharani and Darna (2024), it was found that ease of transactions and lifestyle have a significant influence on Kredivo’s PayLater usage decisions, showing that Kredivo has successfully met user expectations in these regards [12].

Thus, the results of this study are expected to help Generation Z in choosing the PayLater application that best suits their needs, as well as encouraging improved of financial literacy and the selection of safe financial solutions among Indonesian people.