Research Question
Today, technology plays the key role in almost all aspects of human beings from the homes to the public spaces (Masihuddin et al., 2017). Many businesses are moving from the traditional cash payment systems to the card and online payments (Goczek & Witkowski, 2015). Automated payments are becoming common in the world today as corporations seek an efficient and less costly system. The electronic payment systems have succeeded and grown because of they make transactions safe, easy, fast, and efficient. By using a card or phone, one is able to pay for different goods and services that they have acquired (Goczek & Witkowski, 2015). Cards are easy to carry around and they can be used to make payments to different people or businesses as well. The technological revolutions have seen the increased use of Automated Teller Machine (ATM) cards, Visas, and online application payment systems where no hard cash is handled (Goczek & Witkowski, 2015). In many countries around the world, cash and paper-based payments are slowly being replaced by electronic payments.
Although businesses are implementing electronic payments systems, technological changes come with various challenges that may make it difficult to use (Masihuddin, Khan, Mattoo, & Olanrewaju, 2017). One of the challenges is the acceptability and use of new technologies by people (Masihuddin et al., 2017). Some people tend to be rigid and conservative about new technologies and they take a long time to start using them. In the cases where there is no surety, people tend to use the systems that they know and are familiar with. This conservatism and fear of exploration may lead to slow technological revolutions compared to other places. The Singaporean corporations and people have lagged behind in adopting electronic payments systems. Many of them still use cash and paper-based systems to pay for goods and services despite the other sectors of economy improving (Arora, Ujakpa, Jonathan, Appiah-Annin, & Mwanza, 2016). This shows that there is a significantly slower progress regarding the use of electronic payment system. As a result, there is a need to establish the number of people that use electronic payments systems in Singapore. The research question is, therefore, what is the number of Singaporeans using electronic payment for transactions.
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Hypothesis
A hypothesis is defined as the envisioned position of a situation made with little evidence before further investigation. The hypothesis for this study is, many people in Singapore use electronic payment systems for the goods and services received . From the hypothesis, there will be dependent and independent variables to be analyzed. The dependent variable is the number of electronic payment cards that a respondent has. This variable enables the determination of the popularity and use of electronic payment systems in retail businesses. The independent variables are age, gender, education level, marital status, employment status, and accessibility of the internet. The independent variables are the characteristics of the study population that may determine their use of electronic payment systems (Peck, Olsen, & Devore, 2015). The accessibility of internet services is a variable of interest because it may play a significant role in the use of electronic payment systems. It is presumed that the people that can access a stable internet can also use electronic payment systems. Each variable will be presented as a question in a questionnaire and consumers are required to answer all of them. The age variable will be categorized into four for the purposes of analysis.
Sampling
The study is a survey study where the participants are given questionnaires to fill. The questionnaires are self-administered and one has to fill for themselves then submit them at designated times and place. The sampling frame is made up of people aged between 19 and 50 because the study targets frequent and active shoppers. The ages are categorized into 19 – 24, 25 – 30, 31 – 36, 37 – 42, and 43 – 50. It will include people of all genders, social classes, and educational levels as long as they fall within the age bracket. The sample frame provides a basis for the accuracy of the data and conclusions to be drawn from it (Peck et al., 2015). However, the researcher needs to ensure that all potential respondents are residents of the respective areas within which the questionnaire is administered. Furthermore, it is important to avoid areas where a given group is likely to be overrepresented. For example, a market near a college would not be ideal for data collection as the unmarried and younger people will be more than in a typical market.
The research will use a random sampling method for the consumers from different parts of the country. The respondents will be selected on the basis of those who are willing as long as they fall within the eligible age categories (Peck et al., 2015). To get a representative sample of all the people in Singapore, the study population will come from the major cities and towns from the five regions in the country in the country. Random sampling ensures that there is no bias because all the eligible persons have a chance of being selected.
There are many people that are eligible for the study given the size the target population. This makes it necessary to use a sampling strategy for to determine the sample and sample size for the study. First, the sampling will be done at the markets where targeted consumers are likely to get goods and services. Also, different groups of research assistants will be dispatched to different regions and towns to ensure that the data collected is purely random. The data will also be collected at different times of the day. All these strategies are meant to ensure that there is no development of bias and that people of both genders and eligible ages are represented significantly.
Issues of Reliability and Validity
Reliability
Reliability is the consistency with which the tools used produce similar results from similar settings (Peck et al., 2015). The study’s reliability can be compromised by getting data from non-residents who may give different information about the use of electronic payments. This data may lead to drawing inaccurate conclusions from the study. During the study, one of the requirements for the respondents will be their long-term residence. A respondent should have lived in a given area for at least a year to be an eligible respondent. Furthermore, the respondents must be people who shop in places where the use of cards is not compulsory. Ensuring that the respondents are from the localities indicated ensures that the information obtained is characteristic of the given place. This enables the reproducibility of the same data with other researchers in the same area.
Validity
Validity refers to the accuracy of the study’s conclusions based on the intentions of the study (Peck et al., 2015). There is a possibility of researchers developing biases while selecting the sample population. This may come about when researchers collect data from the same area for a long time and understand the residents’ payment behaviors. The development of a biased sample selection and data collection may lead to skewed outcomes and wrong conclusions. The potential development of bias can be reduced or prevented by ensuring that the people collecting data do not go to places that they are familiar with. The data collectors will be sent to areas different from their homes towns and cities. Furthermore, they are required to collect data in the morning, during the day and in the evening to ensure a representative sample. Furthermore, the data collectors are required to ensure that they give the questionnaires to the people of both genders in almost equal measures. That way, there is a minimal development of an affinity to a specific gender that may arise from their use of electronic payments systems or not.
Analysis and Interpretation of Data
The data will be analyzed using the Statistical Package for the Social Sciences (SPSS) software (Norris, Qureshi, Howitt, & Cramer, 2014). The analysis will measure the frequencies of all the variables in descriptive statistics and the measure the dependent variable against the independent variables. The descriptive statistics provide the general characteristics of the study population, its gender and age composition and their use of electronic payments systems (Peck et al., 2015). Apart from the descriptive analyses, there will also be relationship analyses that determine the behavior ownership of cards with respect to the independent variables.
The data can be interpreted to show that many Singaporeans do not use electronic payments systems regardless of their gender, education, age, and employment status. Additionally, the conclusion will depend on the numbers of people that own electronic cards and use them. It will also compare the card usage between the genders, age, employment, and educational levels. The findings can be used to show that Singapore’s adoption and use of electronic payment systems are still in dire states. It also opens a door to a qualitative research that determines the reasons as to why the Singaporeans prefer cash and paper-based based payments over the safe, convenient, and efficient electronic payments.
References
Arora, R., Ujakpa, M. M., Jonathan, F., Appiah-Annin, K., & Mwanza, P. T. (2016). Challenges inhibiting E-Zwich electronic payment system . Journal of Information Engineering and Applications, 6 (10), 18-31.
Goczek, L., & Witkowski, B. (2015). Determinants of non-cash payments . Retrieved March 21, 2018, from https://www.nbp.pl/publikacje/materialy_i_studia/196_en.pdf
Masihuddin, M., Khan, B. U. I., Mattoo, M. M. U. I., & Olanrewaju, R. F. (2017). A Survey on e-payment systems: elements, adoption, architecture, challenges and security concepts. Indian Journal of Science and Technology, 10 (20).
Norris, G., Qureshi, F., Howitt, D., & Cramer, D. (2014). Introduction to statistics with SPSS for social science . Oxford, UK: Routledge. Print
Peck, R., Olsen, C., & Devore, J. L. (2015). Introduction to statistics and data analysis. Boston, MA: Cengage Learning. Print
