Online food delivery services: cross-sectional study of consumers’ attitude in Malaysia during and after the COVID-19 pandemic

Theoretical background

This study aims to examine the essential factors perceived by consumers as influential in their decision to persist in using OFDS following the COVID-19 outbreak. Previous studies have frequently combined the Theory of Planned Behaviour (TPB) and Technology Acceptance Model (TAM) to explain why people engage in a specific behaviour. For example, a study conducted in China used TPB, TAM and three patient-centered factors to examine the elements affecting patients’ acceptance of mobile medical platforms²³, while another study conducted in Italy combined TPB and TAM to analyse the main drivers of users’ intention to use foods delivery apps¹⁸. Other examples include the examination of continuance intention to utilise mobile banking in Jordan, achieved through the integration of UTAUT, TPB, TAM and service quality with machine learning methods²⁴, and understanding library user behavioral utilisation intention of physical book as compared to e-book format in Malaysia by combining TAM, TPB and Theory of Self-Regulation (TSR)²⁵.

This study proposes a similar approach to form an integrative theoretical research model adapted from the Technology Acceptance Model (TAM) and Theory of Planned Behaviour (TPB). Expanding upon this foundation, the research model incorporates additional factors such as convenience motivation, price-saving orientation and time-saving orientation. TAM, conceptualised by Davis in 1989, put forward that users’ attitudes toward a technology are shaped by their perception of its ease of use and usefulness. These attitudes subsequently influence users’ behavioural intentions to adopt and continue using the technology²⁶. In the context of OFDS, perceived ease of use relates to how easy consumers believe ordering food online is. A user-friendly interface, straightforward navigation, and intuitive app design all contribute to a high level of perceived ease of use. Consumers who find the service easy to use are more likely to form positive attitudes toward the service and their intention to use it.

TPB, developed by Ajzen in 1991 extends the understanding of user behaviour by incorporating attitudes, subjective norms and perceived behavioural control as determinants of behavioural intentions, which in turn impact actual behaviour²⁷. This framework holds significant recognition within psychology and social science disciplines, aiming to elucidate and predict human behaviour. Attitude plays a pivotal role in influencing an individual’s perception and inclination toward a specific behaviour. In the context of OFDS, consumers’ attitudes are primarily shaped by two key factors: their perceptions of the benefits, which encompass aspects such as convenience, cost-effectiveness, and time efficiency; and their perceptions of the ease of using the service²⁸. When consumers hold favourable beliefs regarding these factors, it leads to the development of positive attitudes, which in turn, significantly enhances the likelihood of consumers forming a positive intention to engage in OFDS. In essence, attitude acts as a critical determinant in the decision-making process regarding the adoption and utilisation of OFDS among consumers.

Both TAM and TPB emphasise the importance of behavioural intentions. While TAM believes that perceived ease of use and usefulness lead to behavioural intentions, TPB directly incorporates behavioural intentions as a key component. Behavioural intention represents the user’s intention or willingness to engage in a specific behaviour. If consumers find OFDS easy to use, they are more likely to use them regularly. This intention is driven by the notion that the service provides convenience and efficiency in food ordering. TAM is particularly useful for understanding continuance intentions. It implies that users’ initial attitudes and behavioural intentions influence their continued use of technology or services. Likewise, while TPB is traditionally applied to assess initial intentions, it can be adapted to consider continuance intention by exploring whether user’s attitudes and behavioural intentions formed during the pandemic persist as the situation changes. Consumers with positive attitudes and strong initial intentions may also have strong continuance intentions.

In this study, the research model was expanded to include convenience motivation, time-saving orientation and price-saving orientation. Consumers are motivated by the desire to simplify their lives and save time and effort. Convenience motivation is consistent with this concept as it reflects consumers’ drive to seek convenience in their choices. Convenience motivation also aligns with attitudes and behavioural intentions in TPB. If consumers perceive OFDS as highly convenient and complementary to their lifestyle, it positively influences their attitudes and intentions towards ordering food online. Aside from convenience, consumers frequently seek ways to make simple and expedite daily activities. TPB’s perceived behavioural control accounts for this time-saving approach. If consumers believe that OFDS save them time and effort compared to traditional dining options, this perception positively influences their attitudes and behavioural intentions, making them more inclined to use the service to save time. Furthermore, today’s consumers seek not only time-saving and ease but also economic advantages. Both TAM and TPB indirectly consider cost-related factors. TAM can account for cost-related benefits through perceived usefulness, whereas TPB can account for external factors such as subjective norms related to cost savings. If consumers believe OFDS as cost-effective because of promotions, discounts, or reduced transportation costs, it can positively impact their attitudes and intentions to use the service.

This comprehensive framework combines elements from the TAM and the TPB, augmenting them with additional variables. By doing so, it encompasses not only the technological adoption aspects (TAM) but also the broader socio-psychological factors (TPB) that shape consumer attitudes and behavioural intentions in the context of OFDS. This integrated approach facilitates a holistic examination of the various variables and their intricate interconnections, thereby yielding a more nuanced understanding of consumer behaviour within the realm of OFDS.

Convenience motivation

Convenience is defined as the perceived time, value and effort required to facilitate the use of OFDS. Consumers now have the freedom to choose from a wide range of food providers listed on the internet at any time and from anywhere. As a result of its convenience, consumers will be motivated to use OFDS on a regular basis^29,30.

A total of 47% of e-commerce users in Southeast Asia shopped online to save time and energy, and 87% agreed on the usefulness of internet services during the COVID-19 outbreak³¹. Malaysians also prefer online shopping when they have a hectic schedule³². The ease of comparing prices across different online platforms and a wide variety of items are all motivating factors that drive consumers to shop online. Convenience was also cited as the top reason for shopping online in Q4 2020, and remained the top three reasons in Q1 2021³³.

Perceived ease of use

Perceived ease of use (PEOU) refers to a person's perception of how hassle-free it is to use a system. The quality of a system is defined as the ease with which pages can be navigated, the presence of a clear and uncomplicated layout, and the system's dependability³⁴. It is critical for businesses to ensure that their online platform is simple to use because bad designs or a complicated process will deter consumers from continuing with the online purchase.

The amount of effort required to use a system will serve as a critical predictor of its adoption and subsequent usefulness^17,26. It was discovered that if it is relatively effortless to use a system, consumers are more likely to order food online¹³.

Time-saving orientation

In today's fast-paced world, where consumers’ busy schedules mean time is in short supply, time-saving orientation (TSO) has become a critical factor in easing daily tasks while fully utilising time. Many office workers could not afford the time and trouble of going out to eat, including driving and queuing up to place order. Thus, using OFDS is the quickest way to get food and the time saved can be used to complete other tasks.

Higher-income consumers value time because of the opportunity costs. As such, they find online shopping appealing because it allows them to make better use of their time¹⁹. A study discovered that timesaving is the key determinant of consumers' motivation to use technology-based self-service³⁵. When consumers are able to save time, their perception turns positive and as a result, their attitude towards OFDS also becomes favourable^10,20,29.

Price-saving orientation

Price can be defined as the value (monetary or non-monetary) an individual must put forth in an exchange for a product or service^36,37. One of the key factors influencing customer satisfaction is price-saving orientation (PSO), which includes offers and discounts provided by sellers¹¹. 82.9% of Malaysians purchased a product online in the past month⁵. The internet makes it easier to compare prices among different online sellers, which has proven to be advantageous for consumers to purchase at a lower price, which in turn has a significant effect on their behavioural intention to shop online^17,38.

OFDS provide additional perks such as not having to pay for service charge imposed by the restaurants, as well as getting free delivery and discount coupons. Additionally, consumers do not need to expend energy or effort to visit a physical store or restaurant. Thus, consumers will be more satisfied with their online food ordering experience and will be more likely to use these services in the future^12,20.

Attitude, behavioural intention and continuance intention

Attitude (ATT) can be defined as a consumer's overall reaction when using a specific device or technology²⁷. It refers to a person's reaction, whether positive or negative, to a given object³⁹. When consumers believe that online food ordering is useful and capable of easing their daily lives, they are more likely to develop a positive attitude which will lead to continuance intention (CI) of using it. Thus, attitude is positively related to behavioural intention^10,18,40.

Behavioural intention (BI) is defined as a person's proclivity to act in a certain way⁴¹. The intent to use OFDS denotes a consumer's desire to purchase food and beverages through online delivery platforms¹⁰. Many studies have established that the factors used to measure BI include positive word-of-mouth, willingness to recommend a product or service to others and also repurchase intention⁴². Consumers who are pleased and content with their online purchase experience are expected to continue doing so¹².

The main objective of this study is to identify the factors that may influence consumers’ attitude and behaviour towards continuance intention in using OFDS post pandemic, as illustrated in the proposed research model in Figure 1. The hypotheses are proposed as follows:

Figure 1. Research model.

Ethics

Research ethics approval was obtained from Multimedia University, Malaysia (EA1422021) and the respondents gave their written informed consent when filling out the Google Form.

Questionnaire development

An online survey with close-ended questions was designed using Google Form to examine the research hypotheses. It consisted of two parts: demographic information of respondents and 25 measurement items which indicated seven variables, namely, CM, PEOU, TSO, PSO, ATT, BI and CI towards OFDS, which were adopted from previous studies^{10,12,14,18,22,43–45} and recorded in Table 1. All items were measured based on a five-point Likert-type^46,47.

Data collection

In this study, purposive sampling method was applied^48–50 because the selected samples are more representative of the population. It is commonly used by researchers for similar studies, such as a recent study on the intention to use OFDS among consumers in Malaysia, which gathered 224 samples for data analysis¹⁰. Questionnaire was sent to potential respondents who were close contacts (relatives, friends and students) of the authors of this study, and they were invited through email, Facebook and WhatsApp, between 22 March 2021 and 18 April 2021.

A primary dataset of 256 respondents was gathered, in order to examine consumers’ perception and attitude towards OFDS during the pandemic, which is critical to the future growth of the OFDS industry. The minimum sample size of 191 is determined according to the guideline of Hair et al.⁵¹, with a maximum of 4 arrows pointing at a latent variable and minimum R² of 0.10.

Hypotheses approach

Demographic background of respondents is presented descriptively and graphically. Consistent Partial Least Square (PLSc) approach^51–53 was applied to study the reflective and formative factors in this study and SmartPLS.v3 software was the main tool used (a free version is available for 30 days). Reliability and validity were tested in factor analysis and bootstrapping of 5,000 subsamples was used to estimate PLSc path model⁵⁴.

Profile of survey respondents

Table 2 shows the demographic profile of 256 respondents⁵⁵. All of them has experienced using OFDS and mostly are young adults between the age of 18 to 25 years old (40.63%). 68.75% preferred to eat at home, compared to at a restaurant. Figure 2 depicts the distribution of respondents who ordered food via third-party mobile apps, social media, or the company’s own website or mobile apps. Foodpanda (76.56%) and GrabFood (70.70%) are the most popular in Malaysia because consumers deemed that the platforms are user-friendly¹⁵. However, social media platforms such as Instagram are more suitable for promoting food rather than ordering⁵⁶.

Figure 2. Distribution of online food delivery services platform.

Table 3 recorded the feedback of the respondents whereby the mode for all measurement items is “Agree”, which contributes to the left-skewed distribution except PSO4. The average and standard deviation of variables are recorded in Table 4 and each average is close to “4” (Agree) except PSO.

Table 5 shows the ratio comparison of the dining preference among the OFDS users based on age, gender, marital status and personal income level. As expected, the majority of OFDS users preferred to enjoy their food at home during pandemic especially the elderly or married adults prefer to enjoy their food at home (>80% for age group above 41 years old; married 73%). Although 71.88% of the users were earning a low income, they still preferred to use OFDS and dine at home (71%) compared to higher income respondents. This indicates COVID-19 pandemic has significantly changed people’s lifestyles and has became a new norm.

Reliability and validity

Table 6 shows Cronbach’s alpha^57,58 and composite reliability (CR)^51,59,60 for each variable as above 0.8, which indicates good internal consistency of the questionnaire’s questions scale in measuring a similar variable. * indicates CR>0.95 but there are no significant changes after its removal⁵¹. The average variance extracted (AVE) indices⁶¹ are greater than 0.5 for each variable, indicating no convergent validity problems.

In Table 7 Fornell-Larcker criterion^61,62, the diagonals represent the square root of AVE and off diagonals represent the coefficient of correlation. One tail t-test is conducted on the coefficient of correlation at 5% level of significance. The results revealed that there is a positive correlation between the variables with p-value of 0. There are no discriminant validity issues with the support of HTMT values, recorded in Table 8 based on HTMT_0.90 criterions⁶³.

Consistent partial least square (PLSc) path modelling approach

Six hypotheses were tested using PLSc⁵³, a variance-based structural equation modelling technique, with no concerns about distribution or multicollinearity. In the past decade, the use of PLS modelling has gradually increased in order to handle more complex models.

Table 9 summarises the result of the hypotheses presented in Figure 3, which indicates the path coefficient and outer loading of the variable. PEOU is found to be insignificant in influencing consumers’ attitude towards OFDS (p-value > 0.05). Consumers’ attitude towards using OFDS during and post the COVID-19 pandemic is, however, positively influenced by CM (p-value < 0.05), TSO (p-value < 0.05) and PSO (p-value < 0.05). Furthermore, hypotheses of ATT positively influencing consumers’ BI (p-value < 0.05) and also BI positively influencing consumers’ CI (p-value < 0.05) towards OFDS are supported in this study. Thus, H1, H3, H4, H5 and H6 are validated while H2 is rejected.

Figure 3. Part coefficient and outer loading.

To test the model quality, effect size, f² and predictive relevance, Q² is measured. All the f² values are greater than 0.02 except the path of PEOU→ATT, which indicates no effect toward ATT^64,65. The predictive relevance, Q² is used to determine the predictive power of dependent variables. All the Q² values are greater than 0.35⁶⁶. This means there is substantial predictive relevance in this model.

Limitations

This study did not take into account all of the possible factors that might influence the continuance intention of using OFDS after the pandemic. The model could be improved in the future by including more variables, such as, customer satisfaction and social influences. Furthermore, the findings cannot be generalised as a whole due to convenience sampling biasness. In the future, the study could be narrowed down to a specific group; perhaps looking at some larger cities with higher demand and supply for OFDS.