Moreover, we are grateful and appreciate the lecturers and tutors of UTAR who guided us in the process of completing this research. The study would like to generate a significant contribution to the public to better understand the factors that influence customer loyalty to online food delivery services. The objective of this research is to explore the factors that influence customer loyalty to online delivery services.
RESEARCH OVERVIEW
- Introduction
- Research Background
- Problem Statement
- Research Objectives
- General Objective
- Specific Objectives
- Research Questions
- Hypothesis of the Study
- Significance of the Study
- Chapter Layout
- Chapter Summary
To investigate the relationship between price quality and customer loyalty for online food delivery services. To investigate the relationship between food quality and customer loyalty to online food delivery service. There is a significant relationship between price quality and customer loyalty for online food delivery services.
LITERATURE REVIEW
- Introduction
- Underlying theories
- Deming’s theory of profound knowledge
- Review of the Literature
- Customer Loyalty (Dependent Variable)
- Price Quality (1st Independent Variable)
- Service quality (2nd Independent Variable)
- Information quality (3rd Independent Variable)
- Food Quality (4th Independent Variable)
- Theoretical Framework Reference
- Hypothesis Development
- Chapter Summary
In this context, one of the factors that influences the customer loyalty of online food delivery is price quality. The quality of the information plays an important role in mobile applications that influence the customer loyalty of online food delivery services. The privacy and security are an important part of the customer loyalty of online delivery services.
Research Methodology
- Introduction
- Research Design
- Data Collection Methods
- Sampling Design
- Target Population
- Sampling Frame and Sampling Location
- Sampling Elements
- Sampling Technique
- Sampling Size
- Research Instrument
- Questionnaire
- Questionnaires Design
- Constructs Measurement
- Data Processing
- Data Checking
- Data Coding
- Data Entering
- Data Cleaning
- Data Analysis
- Descriptive Analysis
- Reliability Analysis
- Inferential Analysis
- Chapter Summary
Furthermore, this research uses non-probability sampling, and there is no data on the number of individuals using online food delivery services in the target population. Therefore, the consent of the participants is recognized at the beginning of the questionnaire; therefore, individuals who are not interested in participating in the questionnaire are filtered out. To get a better accuracy of the survey, we will collect a total of 500 questionnaires from our target population.
This is used for questions in Sections B, C, D, E, F and G where a five-point scale of 'Strongly agree, agree, neutral, disagree and strongly disagree' is given for the individuals to choose on the level do they agree or disagree with the statement of the questions. After the distribution of the questionnaire dataset, all obtained data is loaded into the analysis program for the outcome of the proposal. Unlike mean, descriptive analysis can calculate other measures of the data, for example the most commonly used descriptive.
In this study, descriptive analysis was used for the data in part A of the questionnaire on the demographics of individuals. To get a better picture of the data, a pie chart is appropriate for all questions in section A except the last one about how often they order food delivery online. For this study, Cronbach's Alpha is used to determine the reliability of the study and whether or not the data collected is positively related to each other.
The Pearson correlation coefficient value ranges from -1 to +1, with positive values indicating positive relationships, while negative values indicating negative relationships.
DATA ANALYSIS
Introduction
The regression can estimate the effect of change on the dependent variables based on the independent variables.
Descriptive Analysis
- Respondent Demographic Profile
- Gender of Respondents
- Age of Respondents
- Education level of Respondents
- Ethnic Group of Respondents
- Marital Status of Respondents
- How often do respondent order food delivery service through online
- Central Tendencies Measurement of Constructs
- Price Quality
- Service Quality
- Information Quality
- Food Quality
- Privacy and Security
- Customer loyalty
Based on table 4.1 and figure 4.1, there are 500 respondents in this study, of which 263 are male respondents and 237 are female respondents. According to table 4.1.3 and figure 4.13, the respondents with an education level of bachelor or degree are the highest with a number of 46 people and a representation of 85.2%. Based on the table and figure above, the majority of the respondents are from the Chinese ethnic group at a rate of 86.4, while Indian has 13.6%.
Based on the table and figure above, majority of the respondents are of single status while only a handful of respondents are married with a percentage of 99.2% and 0.8%. Based on Table 4.6 and Figure 4.16, there are 61 respondents and represented 12.2% who order online food delivery service daily. In addition, 8 respondents who rarely order food online with a percentage of 1.6% and finally 26 respondents who never order food online with a percentage of 5.2%.
Scale Measurement
- Reliability Test
Inferential Analysis
- Correlation between Price Quality and Customer loyalty
- Correlation between Service quality and Customer loyalty
- Correlation between Information quality and Customer loyalty
- Correlation between Food Quality and Customer loyalty
- Correlation between Privacy and Security and Customer loyalty
- Multiple Linear Regression Analysis
Customer loyalty increases when prices and quality are high, according to the correlation value of 0.785. The correlation coefficient value of 0.785 is within the range of 0.70 to 0.90, indicating that the strength of this association is strong and significant. The correlation coefficient value of 0.766 is within the range of 0.70 to 0.90, indicating that the strength of this association is strong and significant.
The correlation coefficient value of 0.687 is within the range of 0.50 to 0.70, indicating that the strength of this relationship is moderate and significant. The correlation coefficient of 0.776 shows that when food quality is high, customer loyalty will increase. The correlation coefficient of 0.674 shows that when Privacy and Security are high, customer loyalty will increase.
The strength of this relationship is moderate and significant as the correlation coefficient value of 0.674 falls within ±0.50 to ±0.70. This section presents the results of multiple regression analysis by examining the influence of the independent variables on customer loyalty. The remaining 24.9% of the variation cannot be explained by this model, indicating that additional factors can be used to explain customer loyalty.
Service quality had the greatest variable influence on customer loyalty among the independent variables with a beta value of 0.515.
DISCUSSION, CONCLUSION AND IMPLICATIONS
Introduction and Summary of Statistical Analysis
- Introduction
- Central Tendency
- Inferential Analysis
- Multiple Linear Regression Analysis and Linear Regression Analysis
Customer loyalty has a positive correlation with the five independent variables, with privacy and security having the highest significant value (0.828), followed by price quality (0.818), food quality (0.767), service quality (0.651) and information quality (0.600). Because the correlation coefficient values of these three variables are in the range of ±0.70 to ±0.90, the three associations have a high degree of intensity. The remaining two relationships have a modest degree of intensity, as their correlation coefficients are in the range of ±0.50 to ±0.70.
Discussion of major findings
- Price Quality and Customer Loyalty
- Service Quality and Customer Loyalty
- Information Quality and Customer Loyalty
- Food Quality and Customer Loyalty
- Privacy and Security and Customer Loyalty
The second hypothesis H2 assumes that service quality has a significant impact on customer loyalty of online food delivery service. Therefore, the predictor variable of service quality for the study is a significant factor in predicting the dependent variable of customer loyalty. The third hypothesis H3 states that information quality has a significant influence on customer loyalty of online food delivery service.
Therefore, for the study, the predictor variable of information quality is an important factor in predicting the dependent variable of customer loyalty. The fourth hypothesis, H4, states that food quality has a significant effect on customer loyalty to an online food delivery service. Therefore, for the study, the predictor variable of food quality is an important factor in predicting the dependent variable of customer loyalty.
As a result, there is a significant causal relationship between food quality and online food delivery service. The fifth hypothesis H5 states that privacy and security have significantly influenced customer loyalty of online food delivery service. Therefore, for the study, the predictor variable of privacy and security quality is a significant factor in predicting the dependent variable of customer loyalty.
Privacy and security are a significant part of influencing customer loyalty of online food delivery service.
Implication of the research
- Theory implication
- Managerial Implication
The organization must ensure the security of the customer data while the customer is using the Online Food Delivery Services (OFDS) through the application. The popularity of online meal delivery is growing rapidly due to the many benefits such as direct delivery of meals to customers' doorsteps, various payment methods, attractive discounts, incentives and cashbacks of online food delivery. Delvecchio and Puligadda (2012) believe that compared to alternative food service platforms, the lower the price of a meal, the greater the attractiveness of food delivery platform services.
Due to the prevalence of online meal ordering, users prefer to visit many websites, search platforms, compare prices and give reduced prices on various food delivery platforms. They will believe that the website offers lower cost food delivery services and more useful websites. Since price is the main factor that the consumers are aware of, online food delivery services can plan their future marketing strategies based on their prices to attract more potential customers.
One way to do this is to always check the prices of other online food delivery platforms, to make sure that the prices of food and delivery prices are not so far from competitors, but on the other hand also to keep the prices as low as possible while maintaining a sustainable amount of profit to keep the company going. Apart from focusing on food quality, online food delivery services should make enough efforts to keep their food quality and service quality up to the expectations of the customers. Online food delivery companies can have a routine check of the employees to make sure that their service is up to the company's standard.
Managers of online food delivery companies can allocate less time and funds to these two areas and instead focus more on the areas that have the highest effect on customer loyalty.
Limitation of Study
Recommendation for Future Research
By focusing on a more comprehensive age group, researchers can obtain additional information that will be more applicable to the overall OFD users. Furthermore, having a more comprehensive perspective on the factors influencing customer loyalty to online food delivery services will be useful information and experience for future researchers.
Conclusion
Online Food Delivery Services: How to Make Food Delivery the New Normal. Journal of Marketing Advances and Practices. Retrieved March 4, 2022, from https://www.theedgemarkets.com/article/mco-big-win-online-food-deliveries-and-cloud-kitchens. Factors affecting customer satisfaction and loyalty of an online food delivery service during the COVID-19 pandemic: its relationship to open innovation.
Online food delivery services: cross-sectional study of consumer attitude in Malaysia during and after the COVID-19 pandemic [version 1; peer review: 1 disapproved]. The impact of online food delivery service quality on customer satisfaction and customer loyalty: the role of personal innovativeness. Rezaei, "Consumer Experiences, Attitude and Behavioral Intention toward Online Food Delivery (OFD) Service," Journal of Retailing and Consumer Services, p.
The influence of the quality of online food delivery services on customer satisfaction and customer loyalty: the role of personal innovation. An investigation of the online Food Aggregator (Ofa) service: differentiate the online and offline service quality. I would keep ordering through online food delivery app even if there is a price increase in Grab Food.
