International Journal of Business and Economy (IJBEC) eISSN: 2682-8359 [Vol. 2 No. 4 December 2020]
Journal website: http://myjms.mohe.gov.my/index.php/ijbec
FACTORS INFLUENCING CONSUMER PURCHASE BEHAVIOR ON FOOD DELIVERY APPS
Flores, Jill Kimberly U.1* and Castaño, Mary Caroline N.2
1 2 The Graduate School, University of Santo Tomas, Manila, PHILIPPINES
*Corresponding author: jillkimberly.flores.gs@ust.edu.ph; mncastano@ust.edu.ph
Article Information:
Article history:
Received date : 5 November 2020 Revised date : 18 November 2020 Accepted date : 25 November 2020 Published date : 4 December 2020
To cite this document:
Flores, J., & Castaño, M. (2020).
FACTORS INFLUENCING
CONSUMER PURCHASE BEHAVIOR ON FOOD DELIVERY APPS.
International Journal Of Business And Economy, 2(4), 25-42.
Abstract: The Filipino's fast-phased lifestyle dramatically influences their purchasing power as a consumer.
According to the Philippine Statistics Authority, 41.9% of every Filipino household's expenditures are on food consumption. With the noticeable increase in consumers' digital activity, food delivery apps have widely contributed to Filipinos' food eating habits. It has given them the right and efficient platform to purchase food whenever and wherever they want. This study identifies the influence of food delivery apps on consumers' purchase behavior in the National Capital Region (NCR), Philippines. The study employed the descriptive-correlation analysis on the gathered purposive survey responses from 462 participants. All participants are currently located in NCR and own a mobile device with at least one installed food delivery app. The results revealed that online tracking (α
= 0.000), experience and habit (α = 0.000), online ratings and review (α = 0.000), PE (α = 0.000), hedonic motivation (α = 0.000), and price value (α = 0.001) have a significant impact on consumer purchase behavior.
However, consumer purchase behavior was not significantly predicted by EE (α = 0.193); SI (α = 0.759);
Facilitating Conditions (α =548). This study aims to provide theoretical contributions and practical implications relevant to the academe, businesses, government, and consumers.
Keywords: food delivery apps, food ordering apps, mobile application, consumer purchase behavior.
1. Introduction
The food we eat is part of complex systems that include production, distribution, transportation and storage, preparation, use, and waste disposal. Food is a local activity linked to local and global food chains (Chakraborty, Sahakian, Rani, & Shenoy, 2016). In the Philippines, food is considered as a culture. (Euromonitor, 2020). On average, Filipino families in 2018 had an average annual income of PHP 313,000; 76.4% of their annual income is allocated for expenditures that amount to PHP 239,000.00. Within the average annual expenditures of Filipino households, 42.6% of the total expenses were spent on food consumption. (Philippine Statistics Authority, 2018). The Philippines' food industry caters to the Filipino population of 100.98M, with a growth rate of 1.72%. (Philippine Statistics Authority, 2016) In tandem with the growing Filipino population, the Philippine food industry grows at a phenomenal rate. (Marasigan, 2019). Filipinos still prefer buying through wet markets and sari-sari stores as it sells goods and commodities in retail, which is preferred by Filipino households with a limited budget. (Euromonitor, 2020). Additionally, Filipinos’ motivation to buy in-stores is to see the item before buying them, and they could purchase them immediately.
Currently, consumers live increasingly hectic lifestyles, requiring more significant levels of convenience in every daily activity. With the rise of third-party delivery platforms, consumers' choices widened and allowed them to purchase food and have it delivered to their doorsteps in a few minutes. (Vitali, 2019). Before the pandemic and implementation of ECQ in the Philippines, 25% of the consumers bought an item or service online at least weekly. (Euromonitor, 2020)
According to the survey done by Euromonitor in 2020, there was an increase in the demand for e- commerce during the implementation of ECQ in the Philippines.46% of the consumers have appreciated the ability to order at any time and from anywhere (Euromonitor, 2020). Across the Regions in the Philippines, households in the National Capital Region (NCR) had the highest average annual income and expenditures at PHP 460,000 and PHP 369,000.00, respectively. Out of the PHP 369,000 annual expense of households living in NCR, 38.1% is spent on food consumption. It is then further classified into two groups: food consumed at home and food regularly consumed outside of the home. Based on families residing in the NCR, food regularly consumed outside of the home is at 31%, while the food consumed at home is 69% of the total household expenditures. (Philippine Statistics Authority, 2018)
With the significant influence of the digital lifestyle on consumers, food delivery methods are increasingly and continuously being developed to expand the choices available to the consumer further. (Vitali, 2019). Additionally, with the increasing rate of smartphones replacing the PC as the primary device of consumers' daily lives, consumers are gradually shifting to ordering through their smartphones. It provides power to consumers to purchase whatever and whenever they want.
(Vitali, 2019). Food Delivery apps have been attracting Filipinos in NCR and other regions in the Philippines. It allows consumers to obtain the freedom to purchase food whenever and wherever they want. (Vitali, 2019). Although there are already studies focusing specifically on the function of the food delivery app itself. However, these apps’ consumer purchase behavior has not yet been thoroughly studied and tested empirically by researchers. Therefore, there is a gap and need to assess the factors that drive consumers' purchasing behavior by utilizing food delivery apps. It is essential to understand such factors to project and address consumer purchase behavior on food
delivery apps. This study aims to identify the characteristics of consumer purchase behavior as key purchasing determinants of food delivery apps and determine the general perceptions of consumers who use food delivery apps.
2. Literature Review
2.1 Consumer Purchase Behavior on Food Delivery Apps
With the expanding choice of brands and the appearance of more international retailers in the Philippines, Filipino consumers have been pushed up to discretionary spending but still price sensitive. (Euromonitor, 2020) Before implementing Enhance Community Quarantine (ECQ) in NCR, Filipino consumers, especially households with a limited budget, still prefer buying through wet markets and sari-sari stores as it sells single portions. (Euromonitor, 2020). Additionally, Filipinos’ motivation to purchase in-stores is to see the item before buying them, and they could buy them immediately.
Upon implementing ECQ, there was a noticeable increase in the demand for e-commerce in the Philippines; 46% of the consumers have appreciated the ability to order at any time and anywhere (Euromonitor, 2020). Online food delivery is the fastest-growing opportunity in the foodservice industry. Consumers have discovered this to be the most convenient way to purchase whenever and wherever they are. (Vitali, 2019). The market for online food delivery is seen to have significant growth potential. With restaurants expanding online, more and more online food delivery platforms, specifically food delivery apps, are emerging. (Vitali, 2019). In a study regarding behavioral intention to use food delivery apps in Korea, consumers search for various information to reduce risk when buying online. (Lee, Lee, & Jeon, 2017)
According to Euromonitor’s Global Consumer Food Service Statistics, Worldwide infiltration of foodservice internet requests reached 8% in 2019. A noteworthy change from telephone requesting to online has been noted in all areas. One of the fundamental reasons, aside from general development in digitalization among the populace, is the dynamic presentation of outsider conveyance players and aggregators: the developing accessibility of cafés, sensible costs because of the budding rivalry, and high assistance quality.
With the noticeable expansion of online food delivery apps, and more and more consumers ordering through their smartphones, apps will become data sources. The market still presents enormous growth potential. (Vitali, 2019). In the Philippines, it was observed in 2019 that businesses would increase their delivery services as busy consumers prefer convenience in their purchases. (Euromonitor International, 2020) The popularity of food delivery apps in the Philippines was mitigated due to the Philippines' worsening traffic situation, specifically in the National Capital Region.
Additionally, with the Pandemic and the implementation of Community Quarantine in NCR, which is also causing a crisis in different parts of the world, it drives drastic consumer purchase behavior changes. With businesses and consumers turning to provide contactless purchases due to the fear of spreading the virus. (Evans, 2020). There is a study on the behavioral intention of food delivery apps in Korea. As the study was limited to Korea, it does not mean that the study results
can be applied globally. Also, as there is a continuous development of food delivery apps, other factors will be explored and considered in future researches.
2.2 Performance Expectancy (PE)
PE is the extent to which a person believes that using the application improves a task or work performance. (Okumus, Ali, Bilgihan, & Ozturk, 2018). PE was integrated from five concepts from previous research models: which are: First, perceived usefulness, which was adapted from the study of Davis in his Technology Acceptance Model (TAM), which is a user’s perception of his understanding that it would enhance their performance. Second, extrinsic motivation is considered as rewards and penalties. Third, job-fit, which is the user’s belief that technology will produce an increase in job performance. Fourth, the relative advantage is when a user perceives the new technology as more useful than the previous one. Lastly, the fifth is outcome expectation, which the sense of accomplishment received from personal and performance-related expectations.
(De Pourcq, Verleye, Trybou, & Lariviere, 2020). Based on previous studies, PE had predicted its significant impact on consumers' intention to use technological advancement or system. (Ali, Nair,
& Hussain, 2016). Food delivery apps provide consumers with access to various food options without exerting much physical effort. These applications collect their information for users to place orders on the restaurants whenever and wherever they want. It is possible that food delivery apps would satisfy consumers based on the applications of practical value to an individual.
2.3 Effort Expectancy (EE)
EE refers to individuals observed to consistently prefer using a new system, which is easy and would require less effort. (Alalwan, 2018). Therefore, EE is essential in most studies on technology acceptance and innovation diffusion. Like PE, EE was constructed from three concepts from previous research models: ease of use, the complexity of use, and ease of use. To further discuss, these three concepts describe the user’s perception to efficiently use the new technology, the user's perception of the difficulty to use the latest technology, and the users' perception of how easily the new technology is used. (De Pourcq, Verleye, Trybou, & Lariviere, 2020). In previous studies, EE had a significant positive impact on behavior. (Alalwan, Dwivedi, & Rana, 2017; Herrero, San Martín, & Garcia-De Los Salmones, 2017; Oliveira, Thomas, Baptista, & Campos, 2016).
Although some studies have found out that EE has no significant influence on behavior. As food delivery apps require consumers to complete the ordering food without any direct assistance from the restaurant they are trying to place an order to, the intent to use the food delivery app could be developed to be perceived by consumers as uncomplex and effortless.
2.4 Social Influence (SI)
SC is the assumption of users to which famous people should use the application. As technology has been increasingly influencing Filipinos' daily lives, they might be primarily influenced by others’ opinions (family, friends, influencers, colleagues) whom they consider relevant to them.
Like PE and EE, SI was from three concepts from previous studies: subjective norms, social factors, and images, which were also adapted in the TAM model. These three concepts perceive the user’s importance on how they should act to others, the culture and social contracts the user shares with others, and the user’s perception that the use of the new technology will affect their or other’s social status. (De Pourcq, Verleye, Trybou, & Lariviere, 2020). Previous studies present
that SI affects behavior (Okumus, Ali, Bilgihan, & Ozturk, 2018; Khalilzadeh, Ozturk, & Bilgihan, 2017; Verkijika, 2018). When deciding on using technology, individuals often consider opinions from their social network. Positive social influence would encourage user adoption, while negative SI would promote the technology’s non-adoption. (Verkijika, 2018)
2.5 Facilitating Conditions (FC)
FC is the consumers' perception of the resources and support available to perform a behavior. This determines the technology use of the consumer. As consumers, the basis of a high-quality application would be based on the application's ability to consistently function with minimal or no technical problems and the availability of support needed by users to ensure the application’s quality. (Alalwan, 2020). Previous studies have shown that Facilitating Conditions has a direct relationship with the customer's intention to use an application. (Verkijika, 2018; Alalwan, Dwivedi, & Rana, 2017).
2.6 Hedonic Motivation (HM)
HM is the fun obtained from using technology. Consumers' feelings regarding the pleasure of using food delivery apps could be based on the application's system's innovativeness and newness. As mobile apps contribute to people's everyday lives, smartphone applications are considered modern and creative, making customers enjoy or feel pleasure when using these applications (Yeo, Goh,
& Rezaei, 2017; Okumus, Ali, Bilgihan, & Ozturk, 2018). According to previous studies, HM positively shapes the customer's perception of online food delivery apps' effectiveness and handiness. (Yeo, Goh, & Rezaei, 2017). HM empowers customers to co-produce value by providing feedback on the services offered by the mobile application.
2.7 Price Value (PV)
PV is the structure of a technology that could have a significant impact on consumers' technology use. PV is the monetary cost of using the perceived benefits of the application. Consumers are expected to compare the costs of ordering food via food delivery apps versus the traditional way of ordering food through the restaurants. From previous studies, price value significantly affects consumer's behavior on continued usage. (Alalwan, Dwivedi, & Rana, 2017). With the evident increase in brand choices and international retailers, consumers are given more options to buy and what brand to support. However, Filipino consumers remain price sensitive. (Euromonitor, 2020).
As food delivery apps give consumers the option of ordering food through restaurants without exerting too much physical effort to visit the restaurant, food delivery apps could save both financial and non-financial costs included in ordering food from restaurants using food delivery apps. (Alalwan, 2020)
2.8 Experience and Habit (EH)
Experience is the opportunity to use technology as is typically operationalized as the passage of time from technology's initial use. Habit is deemed to directly affect technology as it weakens or limits the relationship strength between intention and technology usage. The accumulated experience from learning and its formation of habitual behavior can impact customers' attitudes and beliefs that could predict consumers' continued intention to use. (Alalwan, 2020). Based on
previous studies, it might be possible that the experience and habitual behavior of consumers who are using food delivery apps could continuously use the app.
2.9 Online Reviews and Ratings (ORR)
ORR is word-of-mouth, which is published via online platforms. Nowadays, these reviews have been considered as valuable resources for consumers on their decision making of purchasing a product or a service. Online reviews contain feedback from consumers, which other customers use as relevant information in their decision making. Online reviews are considered an integral part of the customer's engagement with online communities. (Mathwick & Mosteller, 2016). Online Ratings are associated with online reviews, considered another type of crowd review that evaluates a product or a service's features. Online ratings help capture the product's overall evaluation or service by customers who have already tried such products or services. Online Reviews and ratings can motivate consumers to continue using food delivery apps, contributing to consumers’
satisfaction using the mobile application. Online reviews and ratings are considered vital in customer's purchase intentions and customer's trust.
2.10 Online Tracking (OT)
OT is an innovative feature of food delivery apps. It provides the ordered food’s actual location and the estimated time when the ordered food from the food delivery app would arrive at the designated area. This feature could lead consumers to be more motivated to use food delivery apps that encourage them to save on physical effort and time when ordering food through traditional ways. Online Tracking presents all the stages of customer orders through constant updates on the state of their order until delivery of the order. (Gutierrez, O'Leary, Rana, Dwivedi, & Calle, 2019;
Kapoor & Vij, 2018). Additionally, online tracking could be enhancing the customer's shopping experience by improving the productivity, pleasure, and satisfaction of customers. (Alalwan, 2020).
2.11 Problem Statement
This study aims to determine the factors influencing consumer purchase behavior to food delivery apps. Currently, similar studies were conducted by Lee, Lee, & Jeon (2017). They examined the relationships between the determinants that affect customers' use of food delivery apps in Korea by using an extended technology acceptance model. Another study was conducted by (Chakraborty D., 2019) that focuses on the determinants of indicated site quality and administration quality in Indiaby using SERVQUAL. Additionally, a study that examined customer e-satisfaction and continued intention to reuse was conducted by (Alalwan, 2020), which focuses on the mobile food ordering app and its effect on Jordanian consumers. This study examines the factors that determine consumer purchase behavior on utilizing food delivery apps, which will be reviewed by adopting the Extended Unified Theory of Acceptance and Use of Technology (UTAUT2). This study pursues examining the aspects that influence consumer purchase behavior towards using food delivery apps. In particular, this study would focus on consumers' behavior in using food delivery apps. Even though food delivery apps have been extensively used in the Philippines, related issues regarding consumer behavior on the utilization of the food delivery apps have not yet been thoroughly studied and tested by researchers. Several studies relating to food delivery apps from other countries were used to further the research focused on the Philippines. The study's locale will
be in the National Capital Region only, and the sampling procedure will only be limited to purposive sampling. Therefore, the question which is generally addressed by this study are as follows:
(1) To determine the demographic profiles of the respondents of the research (2) To determine the significant factors that influence consumer purchase behavior.
This study will focus on and limitedly gather from individuals currently residing, either permanently or presently, in the National Capital Region. As this study will focus on food delivery apps, it is understood that only those individuals who currently own a mobile device are subjected to this study. However, the study will not dwell on consumer purchase behavior on other food delivery segments besides food delivery applications, which can be downloaded and installed on smartphones. The purpose of this limitation is for the researcher to get the opinion of specific individuals who are currently using food delivery apps. There are studies on consumer purchase behavior to use food delivery apps, but these studies are only limited to other countries that might not be applicable in the Philippines. Furthermore, as the survey for the analysis was during the COVID-19 Pandemic, the researcher's movement has been limited to contactless or no person-to- person means of distribution of survey-questionnaires. Lastly, the sampling procedure will only be limited to purposive sampling.
3. Method
This study used a descriptive research design focusing on describing the data and the characteristics of the population and situations under stud that identify the factors that will affect consumer purchase behavior in the Philippines. Further, statistical differences in terms of age, civil status, monthly income, and owning a mobile food delivery app years of work experience were determined to the perception of consumers towards food delivery apps, using correlational analysis, the relationship of Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Condition, Hedonic Motivation, Price Value, Experience, and Habit, Online Reviews and Ratings, and Online Tracking towards consumer purchase behavior were likewise determined.
3.1 Materials
A structured survey questionnaire-survey, which was adapted from previous studies with the researcher's changes to suit the study, will be used as a data-gathering instrument since the researcher will need the collection of primary data. The data gathering would be done online, as the research was done during the implemented Enhanced Community Quarantine in the Philippines.
3.1.1 Samples
This study used purposive sampling where population size (N), the fraction of responses that you are interested in I, and Z(c/100) is the critical value for the confidence level I., The margin of error is at 5%, with a confidence level of 95% with a population size of 12,877,253 residents in NCR (Philippine Statistics Authority, 2018). As explained by the Philippine Statistics Authority, the population and housing census are conducted every five to ten years. The recommended sample
size is 385. The selection of appropriate subjects for this study is the most critical measure of the fundamental research, affecting the quality of the produced results.
3.1.2 Site
The National Capital Region, Philippines, was the study’s locale, as food delivery apps are widely used within the chosen locale. NCR consists of Caloocan City, Las Piñas City, Makati City, Malabon City, Mandaluyong City, Manila City, Marikina City, Muntinlupa City, Navotas City, Parañaque City, Pasay City, Pasig City, Pateros, Quezon City, San Juan City, Taguig City, Valenzuela City (Philippine Statistics Authority, 2016)
3.1.3 Procedures
Design: This study used a descriptive research design focusing on describing the data and the characteristics of the population and situations understudy that identified the factors that affected consumer purchase behavior in the Philippines. Further, statistical differences in terms of age, civil status, monthly income, and owning a mobile food delivery app years of work experience were determined to the perception of consumers towards food delivery apps, using correlational analysis, the relationship of PE, EE, SI, Facilitating Condition, Hedonic Motivation, Price Value, Experience, and Habit Online Reviews and Ratings, Online Tracking towards consumer purchase behavior were likewise determined.
Variables: This study adopted UTAUT2 as a theoretical foundation for the proposed conceptual framework. Albeit the UTAUT2 has been a widely validated model, its structure has shown different findings across different research perspectives. (Verkijika, 2018) (Alalwan, 2020). With this, the researchers have observed that it is essential to modify and validate the UTAUT2 to heighten the overview of its findings.
Guided by previously stated theories and hypotheses, the above illustrates the possible relationship between independent variables and the study's dependent variable. The conceptual framework (Figure 2) shows the suggested seven factors from UTAUT2 used in this study. Furthermore, two additional other factors, online review and ratings, and online tracking, were also included in the model; these were based on the study conducted by (Alalwan, 2020) to further associate the study with food delivery apps.
Figure 1: Conceptual Framework
Based on previous studies, it was also noted that some features included in food delivery apps were included to study research gaps that might be important to the perspective of Filipino consumers who were using food delivery apps. The process was evaluated through analysis, interpretation, and presentation of data from the input. Lastly, the output presented the assessment of the gathered demographic profile, consumer purchase behavior on food delivery apps that helped analyze the findings, conclusion, and further recommendation for the research.
Power and sample size: Subjects who participated in this study were individuals who are residing in NCR, with age ranging from 18 years and above and have at least know how to operate a mobile device and have at least one food delivery app installed on their mobile device since the understanding and knowledge in this specific study is focused on the usage of food delivery applications.
3.2 Measurement
The questionnaire consisted of four parts. The first part included the Informed Consent of the participant. The second part consisted of the Screening Statements that filter participants based on their residency and ownership of the mobile device. The third part of the questionnaire consisted of the participants' demographics and profile. Lastly, the fourth, the primary survey questionnaire and adapted from previous studies with necessary changes, was only made to fit the study's context.
The measurement of PE, EE, FC, SI, PV, HM, ORR, and OT was adapted (Alalwan, 2020). The researcher found the said research instrument suitable for the study that determined the factors influencing consumer purchase behavior on NCR's food delivery apps. This enabled potential underlying relationships to be tested, permitting cross-sectionals designs with samples and multiple factors to be measured concurrently. The questionnaires were prepared in English to ensure that respondents will fully understand and interpret the questions intended by the researcher. The questionnaire consisted of two types: the multiple-choice questions were used as they helped the researcher to get a straight answer from the respondents instantly: items answerable by "yes or no" which were mainly for the screening of respondents; and a five-point Likert scale
was used to get an individual's opinion on the factors influencing consumer purchase behavior. In this study, the scale measured the respondent's level of agreement in which 1, 2, 3, 4, and 5 connotes "Strongly Agree," "Agree," "Neither," "Disagree," and "Strongly Disagree" respectively.
3.3 Data Analysis
For the primary data analysis, the researcher used the standard deviation to determine if respondents agree with the questionnaire's questions. Additionally, the researcher also used linear correlation to understand the perception of food delivery apps. Lastly, a stepwise regression analysis was used to determine the relationship between the dependent and independent variables.
Stepwise regression analysis was used to determine which predictor variables contributed most to consumer purchase behavior on food delivery apps. Computation and generation were performed using the Statistical Package for the Social Sciences (SPSS). Tables and graphs were used to analyze and draw a conclusion from the gathered data. Likewise, as descriptive statistics were used, percentages, weighted mean, and standard deviation will be part of the data analysis measures.
3.3.1 Validity and Reliability
Pre-testing of the questionnaire to a sample of 20 respondents who were included in the final testing done. This ensured that the participants of the survey did not have difficulty answering the survey questions. The study employed the Cronbach alpha coefficient, which was used to measure and determine the combined scale’s reliability, which depended on the variables' average correlation. Based on the given feedback by the participants, the questionnaire was further enhanced in terms of clarity. Cronbach’s alpha coefficient was tested for all items, as shown in Table 1, and has resulted that all items were reliable for every variable.
Table 1: Cronbach’s Alpha
Possible participants were approached to check if they were within the set criteria. In this study, the survey respondents' characteristics fell in the following criteria: presently living in National Capital Region, whose age ranges from 18 years old and above currently owned and knew how to operate a smartphone, and have at least installed a food delivery app in their smartphone. The primary tool that was used for data gathering was a structured survey. The survey was carried out in the form of a structured online questionnaire, as person to person contact was limited due to the current situation brought about by the COVID-19 Pandemic. To arrive at a better number of samples, the researcher distributed the questionnaire online; this was done to lessen the risk of conducting the survey through face-to-face contact. Due to the current situation with COVID-19,
the researcher deemed this type of distribution as the best method to distribute the questionnaire.
This was given to individuals who fit the criteria and were willing to take part in the study.
Along with the approved consent, screening questions were included at the start of the survey questionnaire to ensure that the right set of people answered the survey questionnaire. The researcher secured formal consent from possible participants before conducting any research to observe appropriate ethical and professional procedures in this study. This was done through an informed consent form, which states the researcher’s name, setting expectations regarding the detail, providing the purpose of the survey, the participant's possible rights, and the researcher's responsibility regarding participation and confidentiality of the participant.
This procedure ensured that the survey participants were well -informed and participated voluntarily. Records of each participant were protected by giving the respondents the option to omit their names. Likewise, to promote anonymity, the signed consent was kept separately from their answers, and each participant was assigned a code number. Additionally, the researcher collected the participants' necessary personal data to achieve this study's purpose, like the location of residence, age, gender, and income bracket. All information from the survey was disclosed to the participant to ensure fairness and transparency.
All the respondents were given a chance to present their concerns before the beginning of the study. On the other hand, the survey questionnaire did not include questions that can cause discomfort to the respondent.
Furthermore, participants were informed that they have the right to withdraw from the study at any time and to request to withhold any information already submitted if they wished to do so. All parties that would be given access to individual survey responses would be subjected to strict confidentiality obligations concerning access and data use. The researcher reported the results of the collected data accurately. No tampering of results was done when the data was presented.
Lastly, the researcher maintains the exclusive rights in all published content of the study.
4. Results and Discussion
Data were collected through an online questionnaire developed in Survey Monkey. The distribution of the survey was done through all possible forms of social media. The researcher opted to choose social media to use as a platform to distribute the survey questionnaire to further reach more participants for the study. To ensure that all participants have a sound understanding of the survey, a screening statement was included in the questionnaire. Five hundred thirty-two participated in the survey. Out of the total number of participants, 462 (86.84%) out of 532 participants who answered the questionnaires were valid for more advanced analysis.
An overview of respondent demographics showed that in the age group, most of the respondents were within the age group of 27-32 (26.22%), and the smallest percentage in the age group was those aged 39-44. Females accounted for more than half of the participants (62.58%), while male participants accounted for 37.82% of the participants. In terms of civil status, single participants represented the largest group in the current sample size (47.57%), followed by participants who are married (34.88%); Majority of the participants (64.69%) has a monthly income that ranges from PHP 10,000 to PHP 30,000, while 3.81% of the total number of participants has an income of PHP 91,000 and above. In terms of residency, Quezon City residents constituted the largest group in the current sample size, accounting for 25.79%, followed by Pasig City residents (8.88%).
Most Participants used mobile applications for their food delivery services (64.27%), while the least used platform by the participants was accessing the establishment's website for food delivery services (6.55%). The vast majority (75.05%) of the respondents used food delivery services one to five times a month, followed by those who used food delivery services six to ten times per month. Lastly, most of the study participants (94.50%) perceived that availing of food delivery services was more convenient than going physically to the establishment. The mean and deviation for all items showed that participants seemed to have a positive perception of consumer purchase behavior for all items considered in the study. The average mean of four items for PE was 1.752, four items for EE was 1.731, three items for social influence was 1.997, four items for facilitating conditions was 1.783, three items for hedonic motivation was 2.296, three items for price value was 2.112, four items for experience and habit was 2.499, ten items for online reviews and ratings was 1.887. Five items for online tracking was 1.621. Consequently, The standard deviation value for PE was 0.662, EE was 0.571, social influence was 0.720, facilitating conditions was 0.581, hedonic motivation was 0.706, price value was 0.643, experience and habit was 0.737, online reviews and ratings was 0.608, and online tracking was 0.580. As shown on the graph in Figure 5, All items were almost all aligned, which reflected that all items have a positive value.
The conceptual framework’s research hypotheses were all tested, and it resulted that consumer purchase behavior was significantly predicted by the role of PE (γ = .177, ρ = < 0.001); PV (γ = - .161, ρ = < 0.001); HM (γ = .114 , ρ = < 0.001); EB (γ = .241, ρ = < 0.001); ORR (γ = .235, ρ = <
0.001); OT (γ = .389, ρ = < 0.001). However, consumer purchase behavior was not significantly predicted by EE (γ = .052, ρ = < 0.001); SI (γ = -.012, ρ = < 0.001); FC (γ = -.026, ρ = < 0.001).
These will be further discussed on the Conclusion.
Table 2. Stepwise Regression Weights
Stepwise Regression, as shown in Table 2, was used by the researcher. According to the results reflected, online tracking, experience and habit, online reviews and ratings, PE, hedonic motivation, and price value were significant predictors of consumer purchase behavior on food delivery apps. Simultaneously, other factors like EE, social influence, and facilitation conditions are considered not significant predictors of consumer purchase behavior. Consumers will have a positive intention to purchase through food delivery apps if perceived to improve their daily tasks or performance. PE has a significant effect on Consumer Purchase Behavior, consistent with previous studies (Alalwan, 2020; Okumus, Ali, Bilgihan, & Ozturk, 2018; Ali, Nair, & Hussain, 2016). The researcher's findings reveal that the ease of using food delivery apps or the EE is not significant in consumer purchase behavior. This might be because Filipino consumer purchase behavior significantly impacts the convenience provided by the food delivery app rather than the technicality on how food delivery apps could be easily used. Another important finding is that social influence is not significant in consumer purchase behavior. This might be because consumers rely more on online ratings and reviews provided by previous consumers who have tried using food delivery apps rather than recommendations from essential or influential people.
This is consistent with the previous study (Okumus, Ali, Bilgihan, & Ozturk, 2018). Facilitating Conditions resulted as not significant to consumer purchase behavior. It might be because there is a seen increase in consumers using smartphones (Vitali, 2019). That facilitating conditions include the consumer's effort to install and understand how to use the food delivery app; consumers might not consider it necessary. This contradicts previous studies supporting the significant influence of facilitating conditions (Ali, Nair, & Hussain, 2016). Hedonic Motivation is the fun, pleasure, and enjoyment, which could also be translated to intrinsic motivation, obtained from using new products and services. This study has shown that hedonic motivation significantly impacts consumer behavior as food delivery apps are seen by consumers as a new product (Okumus, Ali, Bilgihan, & Ozturk, 2018; Yeo, Goh, & Rezaei, 2017). This result is supported by other studies (Amoroso & Lim, 2017; Alalwan, 2020). The price value of purchasing through food delivery apps also has a positive impact on consumer behavior. This could be because Filipinos are seen to follow brands that offer discounts and promotions, which was based on the study by Waggener Edstrom Communications Ltd. Based on the results, Filipinos still value price when it comes to
ordering food through the use of food delivery apps. This is also supported by studies by (Oyedele, Saldivar, Hernandez, & Goenner, 2018) about mobile smart wristbands. This result was also demonstrated by (Alalwan, Dwivedi, & Rana, 2017), which is in relation to mobile banking (Shaw
& Sergueeva, 2019), which is with regard to the impact of price value on Canadian customers’
intention to use mobile commerce. The study has resulted that Experience and Habit had a significant effect on consumer purchase behavior. As individuals who are happy about the outcomes of their prior experience on the usage of food delivery apps are most likely to repeat the same action, this is in line with the study’s result that experience and habit positively impact consumer purchase behavior. This is consistent with the studies (Amoroso & Lim, 2017; Alalwan, 2020). Also, online ratings and reviews create an experience for consumers to compare experiences and alternatives, as it presents overall feedback from consumers who have tried the food delivery app. (Alalwan, 2020). This agrees with the study done by Waggener Edstrom Communications that Filipino consumers use social media as a common information source to purchase. Lastly, Online tracking also has a significant impact on consumer behavior, as consumers feel that purchasing through food delivery apps is seen to be more efficient on cost and time.
Results showed that Online Tracking, Experience and Habit, Online Reviews and Ratings, PE, Hedonic Motivation, and Price Value are significant predictors of consumer purchase behavior on food delivery apps. On the other hand, Effort Expectancy, Social Influence, and Facilitating Conditions do not significantly affect consumer purchase behavior. As discussed in the related literature, although there are many studies for food delivery apps, only a limited number of studies tested issues related to consumer purchase behavior. (Alalwan, 2020) (Cho, Bonn, & Li, 2019) (Okumus, Ali, Bilgihan, & Ozturk, 2018). A deeper understanding of Filipinos' consumer purchase behavior on food delivery apps is required, especially that there is a lack of studies within the Philippines. This study will contribute to the expansion of understanding consumer purchase behavior on food delivery apps.
Additionally, this study also contributes to the validation of the roles of online reviews and ratings and online tracking. Which are the areas of food delivery apps that are not yet widely studied.
Moreover, this study also provides further understanding of the factors that businesses should consider to give food delivery apps and companies that would use food delivery apps to reach customers. In this regard, companies should focus on promotions that would increase their customers. Furthermore, as for the businesses using food delivery apps, it is necessary that the consumers would see the charges included in their services as value for their money.
5. Conclusion
This research has attempted to present a deeper understanding of the factors that would affect Filipino consumer purchase behavior. It started by reviewing previous studies, which suggested that food delivery apps have only a few existing studies. Based on previous studies, it is found that the UTAUT2 model is the most appropriate theoretical framework for the researcher's proposed conceptual framework. The conceptual framework proposed by the researcher, consumer purchase behavior, was supposed to be predicted by PE, EE, SI, Facilitating Conditions, Price Value, Hedonic Motivation, Experience, and Habit, Online Review and Ratings, Online tracking.
The data was collected from the National Capital Region residents currently using at least one food delivery app on their mobile device. It was then analyzed using Stepwise Regression, which confirmed the significance of the proposed factors on Consumer Purchase Behavior. Considering consumer purchase behavior and the effect of technology in their daily life, this study aims to determine the factors influencing purchase consumer behavior on food delivery apps. Based on the presented theoretical frameworks, the researcher has hypothesized that PE, EE, social influences, facilitation conditions, hedonic motivation, price value, experience and habit, online reviews and ratings, and online tracking affects consumer purchase behavior on food delivery apps.
Although this study aims to understand further the factors that affect consumer purchase behavior on food delivery apps in the National Capital Region, several limitations should be noted.
Although a few factors have been covered in the current study's model, other potential constructs could be considered in future research (e.g., family size, lifestyle, customization, health impact), which were not considered in this research. Additionally, this study was done during the COVID- 19 Pandemic, which might have affected Filipino Consumer Purchase Behavior. Future research may also focus on measuring consumers’ purchase behavior for a defined period to deliver more detailed findings for business owners. Lastly, it is assumed that all participants in this study have at least used a food delivery app and answered the survey questionnaire truthfully.
6. Acknowledgement
The researcher would like to thank God and the family who has supported the conduction of this research.
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