Online-to-offline food delivery (OFD) services integrate online ordering systems and human resources to optimize food supply in a more cost-effective resolution. In urban areas such as China, the United Kingdom, the United States, and South Korea, business opportunities for OFD have been consistently expanded (Roh & Park, 2019). Abundant studies have explored the motivations behind OFD usage, primarily focusing on practical aspects such as cost savings and convenience. Some studies perceive OFD as a novel platform, suggesting that variables like perceived usability, perceived usefulness, and perceived enjoyment significantly and positively explain the adoption of the new platforms, OFD.

Nevertheless, it is revealed that the percentage of individuals using online food delivery services at least once (15%) is lower than those who shop directly from stores (63%) (Keeble et al., 2020). This indicates that, while most people may have used OFD, it is not their primary dining option compared to alternatives. Therefore, exclusively examining the intention to use delivery platforms may disregard people's real-life choices in dining options, posing challenges in fully comprehending the psychological motivations and situational factors influencing peoples’ decisions to use online food delivery.

This study aims to examine unexplored user experience of online food delivery, including the psychological and behavioral motivations involved in various contexts. Additionally, we implement the experience sampling method to address gaps in retrospective questionnaires. Finally, this study experiments with two questionnaire formats to seek more effective methods for collecting experience sampling data.

Approach and avoidance theory on dietary behavior

The approach and avoidance theory provides a framework for understanding eating motivations concerning moods. Approach and avoidance reactions are innate responses to external stimuli deeply rooted in biology, designed to propel progress and evolution. These reactions guide organisms toward potentially favorable stimuli or, conversely,  away from harmful stimuli (Elliot, 2006; Elliot & Covington, 2001). The theory suggests that human behaviors are triggered by positive (desirable) events to maintain or enhance positive situations and also by negative (undesirable) events to escape oneself from negative situations physically. According to Elliot and Covington (2001), avoidance motivation is fundamental to motivation theories, asserting that all motivation theories should be grounded in avoidance mechanisms. Therefore, in the context of eating and drinking behaviors, an individual in a negative or unsatisfactory emotional state may use drinking to enhance positive emotions, such as optimism and resistance to depression (Cox & Klinger, 1988).

Apart from positive and negative emotions, the situation also plays a significant role in influencing eating motives. In their study on drinking motives, Cox and Klinger (1988) proposed that positive and negative incentives and situational factors influence human decisions to drink. Situational factors pertain to the environment a person finds themselves in, such as whether they are alone or with others and the extent of encouragement or discouragement from others. Therefore, the presence or absence of a situation reflects internal rewards, such as controlling or managing an individual's inner emotional state, or external rewards, such as the influence of social acceptance or social recognition (Cooper, 1994). Jackson et al. (2003), based on the four-factor model of drinking motivation, developed the Motivations to Eat Scale (MES), categorizing eating motivations into four dimensions: pleasure motivation, coping motivation, social motivation, and conformity motivation. These dimensions explain the psychological motives behind human eating behaviors. As one form of dining, online food delivery should theoretically align with the purposes of these four eating motivations to explain how individuals choose different dining options to meet their needs aroused by mental activity, as illustrated in the image below.

Interpersonal differences in dietary motivation

Dietary motivation, influenced by situational factors and individual variances, has been explored through demographic characteristics such as age, gender, education level, and income. For instance, Keeble et al. (2020) found that customers of online food delivery services in Western countries tend to be younger, have higher education, and have children. In contrast, studies in China indicate that individuals in single-person households are more frequent users of online food delivery services. This suggests that such services help single-person households obtain appropriately portioned individual meals (Cho et al., 2019). Roh and Park (2019) further pointed out that family situations can influence the experience of online food delivery services. Group households with multiple members, characterized by higher responsibilities, may engage in more complex information processing. This study investigates interpersonal differences in the influence of gender, age, habits, and personality traits related to behavioral inhibition/approach systems on online food delivery services' usage behavior and motivation.

Experience Sampling Method

The Experience Sampling Method (ESM) involves collecting data through multiple reports from participants in their daily situations, providing a closer reflection of events as they occur. In this research, the experience sampling survey instructs participants to respond whenever they dined during the 10-day study period. The questionnaire covers dining preferences, meal initiation times, dining expenses, number of diners, dining methods, motivation for chosen dining methods, satisfaction, and, if applicable, inquiries about the perceived aesthetics and usability of online food delivery platforms. A total of 70 participants contribute to 1403 responses. After excluding incomplete responses (29), surveys with completion times less than 5 seconds (4), and instances where recall time exceeded 30 minutes (805), the valid responses amount to 565.

Data Analysis

The experience sampling data exhibits a nested structure, wherein each response is not independent but is concurrently influenced by participant characteristics and situational factors at the time of the event. Therefore, this study applies a two-level nested model to examine the variability at the interpersonal and event levels. Given the data structure of experience sampling surveys, we run Hierarchical Linear Models (HLM) and Hierarchical Generalized Linear Models (HGLMs) (Finch et al., 2014) for analysis.

OFD Usage

This study proposes that approach and avoidance motives are associated with online-to-offline (O2O) food delivery service behaviors. The pleasure motive exhibits a negative correlation with the usage of online food delivery platforms. The findings demonstrate that the pleasure motive significantly influences the likelihood of online food delivery usage (β = -2.77, SE = 1.38, p < .05), indicating that a higher pleasure motive is associated with a lower likelihood of using online food delivery. Similarly, the compliance motive is correlated with the use of online food delivery platforms. The results reveal that the compliance motive significantly influences the likelihood of online food delivery (β = -3.70, SE = 1.19, p < .01), suggesting that a higher compliance motive is associated with a lower likelihood of using online food delivery.

Regarding the hypothesis concerning avoidance personality traits, the results indicate that the Behavioral Activation System (BAS) personality trait moderates the pleasure motive (β = 0.86, SE = 0.41, p < .05) for using online food delivery platforms. Moreover, the Behavioral Inhibition System (BIS) personality trait moderates the compliance motive (β = 1.18, SE = 0.37, p < .01). Therefore, this experience sampling study of OFD suggests that individuals with higher BAS personality are more likely to use online food delivery due to the pleasure motive. This result aligns with the theory that expected positives drive pleasure motives, and individuals with high BAS traits are more sensitive to rewards. Regarding pleasure motives for OFD, factors like price and the appeal of food are involved. Lau et al. (2013) assume that individuals expecting a self-rewarding situation would choose higher-rate dining options on OFD to fulfill their pleasure motives. Although OFD lacks smell and taste, it provides visual stimuli such as advertisements and high-quality food images to stimulate users’ pleasure motives.

On the other hand, individuals with higher BIS traits are more inclined to use online food delivery due to the compliance motive. Compliance motives are related to social influence, social norms, and expectations from other people. Therefore, individuals with higher BIS traits, more sensitive to punishments in a social environment, would use O2O services due to social influence and expectations.

Effect of Experience Sampling Questionnaire Formats

In this study, participants were randomly allocated to two groups and tasked with completing experience sampling questionnaires using different interface designs, specifically, general online and conversational questionnaires. The difference between the two questionnaire interface designs on response outcomes was examined by one-way ANOVA.

Firstly, the analysis of objective data aimed to evaluate response conditions. It was observed that the response frequency in the conversational questionnaire (M = 17.29, SD = 5.57) was significantly lower than that in the general questionnaire (M = 21.97, SD = 5.77) (F(1,68) = 11.95, p < .001). This indicates that the conversational questionnaire might impose a more significant burden on participants, resulting in a lower overall response rate than the general questionnaire. Concerning retention rates on the final day of the study, no significant differences were found between the two questionnaire interfaces (F(1,68) = 1.47, p = 0.231), suggesting that the questionnaire design did not influence whether participants continued responding until the last day. When comparing the recall time from the occurrence of eating events to completing the questionnaire, no significant differences were found between the two questionnaire interfaces (F(1,68) = 0.032, p = .86), indicating that the two questionnaire designs did not shorten or prolong participants' recall biases.

However, in terms of the duration of completing the questionnaire, participants using the conversational questionnaire spent significantly more time (M = 272.1, SD = 272.17) than those using the general questionnaire (M = 113.57, SD = 113.57) (F(1,68) = 8.47, p < .01). This implies that the conversational questionnaire demands more time to complete. In the context of the experience sampling questionnaire method may increase participant burden, which is not conducive to long-term participation. The completion rate of the conversational questionnaire (M = 0.954, SD = 0.052) was also significantly lower than that of the general questionnaire (M = 1, SD = 0) (F(1,68) = 26.44, p < .001), indicating that participants using the conversational questionnaire were more likely to interrupt exit or submit incomplete questionnaire data, leading to a loss of valid samples.

Regarding participants' subjective evaluations of the questionnaire design, there was no significant difference in usability scores between the conversational questionnaire and the general questionnaire (F(1,51) = 0.002, p = .96). The average usability score for the conversational questionnaire was 70.38 (SD = 15.45), and for the general questionnaire was 70.19 (SD = 14.46), indicating that both questionnaires achieved a usability rating above 70, with no discernible superiority or inferiority.