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factors that affecting adoption of cashless

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Nguyễn Gia Hào

Academic year: 2023

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The research aimed to investigate the factors influencing the adoption of cashless payment in Malaysia's night market. The targeted respondents for this research were the cashless payment users in Malaysia's night market.

Introduction

Overview of Cashless Payment

Europe and North America were the leaders of cashless payment as they contributed 243.6 billion in 2019. The impact of the adoption of cashless payment on a country is different because it depends on the acceptable level of the society.

Figure 1.1: Transaction Value of Digital Payments by Segments in Malaysia from 2017 to  2025
Figure 1.1: Transaction Value of Digital Payments by Segments in Malaysia from 2017 to 2025

Research Background

Data from Bank Negara Malaysia showed that e-wallet transactions reached RM23.5 billion in the first ten months of 2020. Then, due to the rise of the digital economy, economic modeling predicts that Malaysia will receive net positive benefits of US$4 billion by 2032, including a 2.6% contribution to GDP, 0.16.

Malaysia Night Market

Problem Statement

Research Question

Thus, this study has focused on the factor that affects the introduction of cashless payment in the night market. H20: There is no significant correlation between perceived ease of use and adoption of cashless payment. There is a significant correlation between perceived ease of use and the adoption of cashless payment.

In other words, perceived usefulness has a significant relationship with the acceptance of cashless payments in the Malaysian night market. Subsequently, perceived ease of use was also found to have a significant relationship between the acceptance of cashless payments. The result revealed that perceived security has no significant relationship with acceptance of cashless payments.

Perceived usefulness, perceived ease of use and relative advantage are the factors that determine the adoption of cashless payment in the Malaysian night market.

Figure 2.1: The Unified Theory of Acceptance and Use of Technology  Performance
Figure 2.1: The Unified Theory of Acceptance and Use of Technology Performance

Significant of Study

Research Objective

Specific Objective

Chapter Layout

  • Perceived Ease of Use
  • Perceived Security
  • Relative Advantage
  • Social Influence

On the other hand, the dependent variable for this research was the intention to use mobile payment services. The independent variables in this research were technology anxiety, social influence and benefits of mobile payment services. On the other hand, the dependent variables were attitude towards mobile payment services and intention to use mobile payment services.

On the other hand, the dependent variable was the intention to use mobile payment systems. On the other hand, the dependent variable was the behavioral intention to use mobile payment services.

Theoretical Background

Expectations Confirmation Theory

Proposed Theoretical Framework

Hypothesis Development

Perceived Ease of Use

Perceived Security

Relative Advantage

Social Influence

Conclusion

This research group has investigated the elements that influence the acceptance of cashless payments in the Malaysian night market. In other words, there are no problems using cashless payments in Malaysia. Perceived security No significant relationship Supported by Ahmad, 2021 Does not affect acceptance of cashless payments.

METHODOLOGY

Research Design

When choosing a research design for a project, consider these three factors: the purpose of the study, the personal experiences of the researcher, and the reader. We decided to use a descriptive research methodology to investigate consumers' knowledge of cashless payment options at the night market. Respondents may be required to provide additional demographic information provided in the first part of the questionnaire.

However, the most important demographic information is that respondents must say whether they use cashless payments or are non-cashless payment users. The objective is to investigate the consumer's perspective on cashless payment and the elements that influence their willingness to embrace cashless payment in the night market.

Data Collection Method

  • Primary Data

Because primary data is obtained expressly for research purposes, it is more reliable, accurate and impartial. Primary data is more appropriate to get information from consumers to measure their level of satisfaction with the use of contactless payment in Malaysia, as this research examines the consumer's perspective on the use of contactless payment in Malaysia. Apart from that, it also helps us to keep track of the data collection procedure.

As a result, there is no missing information, as online respondents are required to answer all the mandatory questions, and only those. However, around 131 sets of questionnaires were discarded because they did not identify themselves as customers with cashless payment.

Figure 3.1: Data Collection Flow Chart
Figure 3.1: Data Collection Flow Chart

Sampling Design

  • Target Population
  • Sampling Frame and Sampling Location
  • Sampling Element
  • Sampling Technique
  • Sample Size

The researcher selects the questionnaire respondents depending on their availability and proximity to the researcher. Besides that, convenience sampling is used as it can benefit and give the researcher a more accessible approach to recruiting the respondents. Convenience sampling is collecting samples by obtaining conveniently available samples on a website or online service (Edgar & Manz, 2017).

The researcher chooses only those respondents that match their criteria and convenience. The sample size table below shows that the total number of responders has been reduced to 177.

Research Instrument

  • Pilot Test

For Part B and Part C, the Five Point Likert scale is adapted to examine the factors influencing the adoption of cashless payment in the Malaysian night market. I am willing to use cashless payment in my daily life. to save time and costs. SI4 I will use contactless payment if the service is widely used by people in my community.

Cronbach's Alpha value for perceived security is 0.893, followed by perceived usefulness, acceptance of cashless payments, and relative advantage. However, the other two variables, perceived ease of use and social influence, had Cronbach's Alpha values ​​less than 0.8.

Table 2: Origin of questionnaire
Table 2: Origin of questionnaire

Construct Measurement

  • Nominal Scale
  • Interval Scale
  • Ratio Scale

All variables are reliable based on the table above since their Cronbach's Alpha value is greater than 0.7. Social influence has the lowest Cronbach's Alpha score of 0.762, while perceived ease of use has the second lowest at 0.780. The numbers given to respondents to choose in the variable on a nominal scale do not indicate any order and are used solely for data classification.

The number of respondents' answers is not specified in the questions, but it has its connotations. A ratio scale is an ordered scale with true zeros in the difference between measurements.

Table 4:  Measurement Scale for Section B of the Questionnaire  Section B:
Table 4: Measurement Scale for Section B of the Questionnaire Section B:

Data Processing

  • Data Checking
  • Data Editing
  • Data Coding
  • Data Cleaning

In other words, an interval scale has order and the difference between two values ​​is essential (Stevens, 2021). Data editing is analyzing the data for consistency, discovering errors and outliers, and correcting inaccuracies. The purpose of data processing is to improve the quality, correctness and suitability of the data and to make it suitable for the purpose for which it was obtained.

Data editing can help the researcher improve the usability of the data and ensure that the data is connected and consistent (Guides, n.d.). It is a technique of summarizing and describing facts to produce a systematic description of recorded or observed phenomena (SAGE Research Methods, 2017).

Data Analysis

  • Descriptive Analysis
  • Reliability Test
  • Spearman’s Correlation Analysis
  • Multiple Linear Regression Analysis

Data cleaning will be performed by removing questionnaires that do not meet the requirements of this study, such as respondents who did not offer a scale while answering the survey. In the latest study, the dependent variable will be an intention to use contactless payment in the Malaysian night market, and the independent variables will be grouped into five categories: perceived ease of use, perceived ease of use, perceived usefulness, and relative advantage and social influence. The significance limits of 1 percent, 5 percent, and 10 percent will be examined to provide depth to this study.

If the p-value is less than 0.05, there is no significant relationship between the independent and dependent variables at the 5 percent significance level. The larger the value of beta, the more the independent variable tends to the dependent variable.

Table 6 : Rule of Thumb for Cronbach’s Alpha
Table 6 : Rule of Thumb for Cronbach’s Alpha

Residual Diagnostic Test

  • Normality Test
  • Heteroscedasticity Test
  • Multicollinearity Test

Heteroskedasticity occurs when the variance of the residuals is unequal across a range of measured values. When the p-value of the Breusch-Pagan test is higher than 0.05, it means that the residuals have the same variance, commonly known as homoscedasticity (Gujarati & Porter, 2013). Multicollinearity is a term used in data analysis that indicates the existence of two exploratory variables in a linear regression model that are shown to be related by proper examination and a predefined degree of accuracy (Corporate Finance Institute, 2022).

The variance inflation factors (VIF) were calculated to determine how much multicollinearity existed in the equation to identify it (Gujarati & Porter, 2013).

Conclusion

DATA ANALYSIS

Descriptive Analysis

  • Demographic Profile of Respondents
  • Central Tendencies of Frequency Analysis

Further, from a gender perspective, the majority of respondents in this survey were female. On the other hand, most of the respondents in this research are Chinese because they showed 92% out of 100%. The result showed that 80.90% of respondents preferred mobile payments and only 19.10% preferred contactless payments such as debit cards or credit cards.

The result showed that 69.3% of respondents used cashless payments more than five times a month. On the other hand, only 1% of respondents visited the night market more than seven times in a month.

Table 4.1.1 shows the respondents’ demographic profile regarding age, gender,  ethnicity, average income level, marital status, education level, occupation, type of  cashless payment, frequency of using cashless payment, and frequency of visiting  Malaysia
Table 4.1.1 shows the respondents’ demographic profile regarding age, gender, ethnicity, average income level, marital status, education level, occupation, type of cashless payment, frequency of using cashless payment, and frequency of visiting Malaysia

Reliability Test

On the other hand, the independent variable with the highest standard deviation was social influence, 0.714, and a mean of 4.247. The threshold of significance for this research will be 5% and the objective will be to determine whether or not there is a statistically significant relationship between the independent and dependent variables. In other words, there is a significant relationship between the independent variable and the dependent variable.

Therefore, these three independent factors have an important link with the adoption of cashless payments. The Variance Inflation Factors (VIF) values ​​are less than ten, indicating that there is no statistical evidence to support the existence of a linear relationship between the independent variables.

Table 11: Result for Spearman’s Analysis Correlation
Table 11: Result for Spearman’s Analysis Correlation

Introduction

Summary of Statistical Analysis

The research result was supported by Yang et al. 2021) because the findings also showed that the perceived ease of use has a positive and significant relationship with the adoption of giro payments. Moreover, a study by Sharinah Puasa et al. 2017) showed that social influence has no significant relationship with acceptance of cashless payments. The result is not supported by Patil et al. 2020) showed that social influence has a weak and significant relationship with acceptance of cashless payments.

In addition, a study by Abrahao et al. 2018) showed that social influence could affect the adoption of cashless payments in Malaysia. In brief, the study aims to investigate the factors influencing the use of cashless payment in the Malaysian night market.

Table 20: Summary of the discussion for major findings
Table 20: Summary of the discussion for major findings

Discussion of Major Findings

Implication of the Study

  • Policy Implication

Limitation of Study

Recommendation for Future Research

Conclusion

Gambar

Figure 1.1: Transaction Value of Digital Payments by Segments in Malaysia from 2017 to  2025
Figure 1.2: Average Transaction Value Per User in Malaysia from 2017 to 2025
Figure 2.1: The Unified Theory of Acceptance and Use of Technology  Performance
Figure 2.2: Technology Acceptance Model (TAM)
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