Regression Analysis to Identify Relationship between Service Failure, Service Recovery, Customer Satisfaction and Loyalty in Food Delivery Platform †
1
Department of Leisure Services Management, Chaoyang University of Technology, Taichung 413310, Taiwan
2
Department of Living Sciences, National Open University, Nantou 540003, Taiwan
*
Author to whom correspondence should be addressed.
†
Presented at the 2024 IEEE 4th International Conference on Electronic Communications, Internet of Things and Big Data, Taipei, Taiwan, 19–21 April 2024.
Eng. Proc. 2024, 74(1), 28; https://doi.org/10.3390/engproc2024074028
Published: 29 August 2024
(This article belongs to the Proceedings of 2024 IEEE 4th International Conference on Electronic Communications, Internet of Things and Big Data)
Abstract
:We explored the relationship and impact of service failures, acceptance of service recovery strategy, post-recovery satisfaction, and loyalty in the food delivery service industry. We used the convenience sampling method and adopted an online questionnaire survey on food delivery services for consumers aged 19 to above 30. Service failure, service recovery strategy acceptance, post-recovery satisfaction, and loyalty scales were explored. A total of 128 valid responses were analyzed for descriptive statistics, t-test and one-way analysis of variance, Pearson correlation analysis, and regression analysis. Missing food items was the most common and most serious service failure. Providing a refund was the most efficient service recovery strategy. If the service recovery strategy was handled properly, it effectively improved satisfaction and loyalty after service recovery was applied. If the service charge of delivery platforms increased, consumers mostly reduced the usage of the service. Therefore, delivery staff need to check whether the meal was correctly delivered. If service failures occur, active care or apologies must be made with the refund. Delivery platform must avoid increased service change and consumers would use the platform stably.
1. Introduction
The world’s first online ordering system was launched by Pizza Hut in 1994, and today, online ordering has become a billion-dollar industry. In 2021, the revenue of the global online ordering industry reached USD 302.826 billion, and the growth rate is expected to be 9.89% from 2021 to 2025, of which USD 172.243 billion will come from food delivery services [1]. Nowadays, online ordering through delivery services has become common, and the use of delivery services is even more likely to exceed online ordering transactions directly with stores. Driven by the pandemic, international food delivery service companies such as FoodPanda and UberEats have expanded their business to deliver goods based on online food delivery services [2]. The domestic food delivery service industry is booming with the opportunity given by the epidemic, and the main user group in China is 20–30 years old. The advantage of delivery platforms lies in preferential promotional activities, brand image, and service quality of delivery people in the service process [3,4]. Scholars have proposed that the profit of food delivery service platforms depends on the number of orders, and this type of delivery service is not appropriate for other markets, and a minimum city size is required to maintain operating profits [5]. It is difficult for companies to maintain the penetration rate of food delivery services in the market.
According to the statistics of the Consumer Protection Division of the Executive Yuan (2021), there were 1977 consumer complaints on online food delivery platform services in 2020, while there were 566 consumer complaints from January to April 2021, which was not significantly improved compared with 564 in the same period of the previous year. The service failure of food delivery platforms continues to occur, and the situation of post-recovery satisfaction in service recovery has not been researched. Effective service recovery is important for online traders to maintain customer satisfaction and loyalty [6]. Therefore, in this study, under the shrinkage of food delivery platform services, the current situation of service failures of food delivery services was explored for the post-recovery satisfaction of different service recovery strategies by analyzing the relationship between post-recovery satisfaction and loyalty using food delivery service. We also examined the effectiveness of post-recovery satisfaction after the occurrence of food delivery services failing to provide a reference for operators in their management policies.
2. Literature Review
2.1. Food Delivery Service
The F&B industry is moving from traditional brick-and-mortar operations to online transactions, with alternative systems emerging from supplier procurement to customer-facing ordering, home delivery, and delivery services [7]. In the past, F&B providers provided online ordering services on their official websites, but food delivery service platforms have opened up a new era of online ordering, where customers can choose from different F&B providers on the platform. In the early days, most online ordering platforms were serviced for restaurant reservations, where customers replaced telephone ordering online, and the platform was responsible for collecting customers’ orders. After the ordering information was forwarded to the restaurant, customers chose the store or the restaurant to arrange delivery. In contrast, new online delivery platform companies have built their logistics networks to provide delivery services to restaurants that do not have self-delivery [8]. The development of online ordering services is divided into three stages: (1) enterprises operating their online ordering systems, (2) collecting customers’ orders through platforms, and (3) collecting customers’ orders and arranging delivery services through platforms. Food delivery service platforms enhance the efficiency of market matchmaking and allow consumers to share information through a consumer evaluation mechanism to increase restaurant choices through the platform and obtain a better consumer experience [9].
2.2. Service Failures
Food delivery services have four characteristics, namely Intangibility, Heterogeneity, Inseparability, and Perishability, collectively known as IHIP [10]. From the perspective of the service process, service failures refer to unexpected negative situations during service delivery [11]. If service failures are defined from the perspective of customers, it refers to companies failing to meet customer expectations and requirements [12]. Service failures are inevitable in the service industry [13]. Service failures must be discussed in terms of frequency, time, and severity. From the perspective of social exchange theory, service failure is divided into outcome failure and process failure, outcome failure is related to the economic benefits obtained by customers from services, and process failure is the fault of customers in the process of obtaining services [14,15]. Any service failure in the service process may leave customers with a negative feeling [16], bring negative service evaluation to the enterprise, and reduce customers’ willingness to repurchase. Thus, the enterprise needs to manage the different types of service failures through different service recovery strategies to reduce the impact on the enterprise.
2.3. Service Recovery Strategy
Mistakes are inevitable in the service process, and customers are often left dissatisfied and disappointed, and the service provider then needs to take compensatory actions and measures to eliminate negative evaluations by the customer and remedy the relationship between the two parties [17]. This process is called the service recovery strategy [18]. The service recovery strategy is classified into psychological remedies and substantive [15]. Psychological remedies are intangible; i.e., the delivery person shows concern in a respectful and empathetic manner, explains the reason for the mistake, admits negligence, and apologizes. Substantive remedies are physical and tangible compensation measures, including giveaways, discount compensation, proposed discount coupons, refunds, and free or additional monetary compensation.
2.4. Post-Recovery Satisfaction
The degree of customer satisfaction in the service process is called the first satisfaction. In the event of a service failure, the enterprise provides corresponding service recovery actions for the service failure situation, and the customer will be satisfied with the suitability of the service recovery strategy, also known as post-recovery satisfaction [19,20]. If the service recovery is not satisfactory, the post-recovery satisfaction may be lower than the first satisfaction, and conversely, the post-recovery satisfaction will be higher than the first satisfaction if the service recovery strategy is appropriate [21,22]. The effectiveness of a service recovery strategy can be measured by post-recovery satisfaction, which can not only reduce the impact of service failures but also lead to a higher level of recognition. Previous studies confirmed that post-recovery satisfaction affects customers’ loyalty to the company, as well as the subsequent trust and commitment relationship with the company [23,24].
2.5. Loyalty
The customer’s continuous preference is defined by the product or service and the willingness to repurchase, that is, customer loyalty [25], via four facets: cross-buying intention, price tolerance, willingness to recommend a brand or company to others, and willingness to repurchase [26]. We researched service failures in the context of online shopping, the types of service failures in online transactions, and the impact of service recovery strategy on remediation satisfaction and loyalty. The customers of process failure are biased towards psychological remedies, and substantive remediation can improve remediation satisfaction and loyalty, and remediation satisfaction and loyalty have a significant positive impact. Online merchants need to focus more on the benefits of the service recovery strategy and post-remediation satisfaction [27]. Loyalty must be considered as the concept of whether the food delivery service is regarded as trustworthy and recommended to others, and whether the food delivery service is used if the service fee is increased. Previous studies confirmed that there is a significant positive relationship between post-recovery satisfaction and customer loyalty [26,28,29].
3. Research Methodology
3.1. Subjects
According to the results of an online survey conducted by Kantar Insight and LifePoints in July 2019, young people aged 20–30 used food delivery services mostly (Wang, 2021). The questionnaire in this study was designed for the consumer groups of 19–30-year-olds. It was distributed from 20 October to 20 November 2021, using online questionnaire sampling, and after the formal questionnaire was established and modified by an information and validity analysis, 300 questionnaires were issued and tested (Figure 1).
3.2. Research Method
Based on the literature review, the following hypotheses were proposed.
H1:
There is a significant relationship between different service failures and the acceptance of different service recovery strategies.
H2:
Service recovery has a significant positive impact on post-recovery satisfaction.
H3:
Post-recovery satisfaction has a significant positive impact on loyalty.
4. Results and Discussion
This study was conducted from 20 October to 20 November 2021, using a snowballing online questionnaire to explore the relationship between food delivery service failures, service recovery, post-recovery satisfaction, and loyalty. Food delivery service consumers who had experienced service failures were used as the research subjects. A total of 246 questionnaires were collected in this survey, and 221 were validated with a rate of 89.8%. Among them, 128 encountered service failures of the delivery platform.
4.1. Demographics of Subjects
Gender, marital status, age, occupation, average monthly income, weekly food delivery service costs, and service failure experience were analyzed. Overall, 73.4% of the respondents were females and 26.5% were males; 83.6% were unmarried, while 16.4% were married; 31.5% were students, and 1.6% were employed; and 43.8% had an average monthly income of CNY 20,001–40,000, while 2.3% earned CNY 60,001–80,000. For the weekly food delivery service, 35.9% spent CNY 201–500, and 2.3% spent CNY 1101–1400. FoodPanda (76.6%) was the most favored platform.
4.1.1. Service Failure
Service failures included four process failures and seven outcome failures. The largest number of “outcome failures” was three. Missing food and beverage products garnered 86 responses, followed by “process failure” with 2 “improper delivery speeds”. A total of 69 respondents experienced “10. No refunds will be given for cancellations” for “process failure”. The largest number of the respondents experienced “3. Missing food and beverage products” as the outcome failure of the merchant not preparing the product and the delivery staff not confirming the item, and “2. Improper delivery speed” refers to the process failure of the delivery personnel on the platform who did not deliver on time.
4.1.2. Severity Analysis of Service Failures
The severity of service failures was scored from 1 to 5. The more serious the failure, the higher the score. The more serious ones were “3. Missing food and beverage products”, and “10. No refunds will be given for cancellations”. The average score was 3.36 for “6. Lack of food hygiene”. The item “4. Cutlery problem” under “process failure” scored 3.4. The most serious failure item was “3. Missing food and beverage products”, indicating that the respondents could not accept it. The least serious failure item was “4. Cutlery problem”, indicating that the respondents did not particularly care about the cutlery problem.
4.2. Number and Severity of Service Errors
Service recovery strategy acceptance refers to which service recovery strategy satisfies customers after encountering service failures. It includes four items for substantive remedies and four items for psychological remedies. The average score was 3.69. From the perspective of “psychological remedies”, the average score was 3.79. The failure item “3. The platform gives this consumption free of charge” scored 4.01, and “The platform provides a coupon for the next consumption” scored the lowest. The respondent’s favorite service recovery strategy was to be provided free consumption in such an event.
4.3. Acceptance of Service Remediation Strategies
Post-recovery satisfaction included three items. The average score was 3.49. The item “3. Overall, I am satisfied with the remediation of the error” scored 3.51, “1. Overall, I gave a positive rating to the response to the food delivery service’s handling error” scored 3.49, and “2. Overall, I am satisfied with the way the service handled the error” scored 3.47 on average. The respondents supported post-recovery satisfaction.
4.4. Loyalty
Loyalty refers to the respondent’s use and trust of food delivery service. The average score for loyalty was 3.06. The item “1. I still consider the food delivery service to be trusted” scored 3.33. “3. Assuming the food delivery service charges go up, I will still use the food delivery service” scored 2.55, indicating that if the platform raised charges, the respondents reduced the number of the uses of the platform.
4.5. Service Failures and Service Recovery Strategy Acceptance
Service failures included seven items and outcome failure included three items. The items were multiple-choice questions. The number of choices was the score for the service failures and outcome failure. Pearson correlation analysis was conducted for the service recovery of substantive remedies and psychological remedies. Process failure had a negative correlation with psychological remedies, which means that the respondents wanted to obtain psychological remedies for service failures (Table 1).
The item “10. No refunds will be given for cancellations” under “process failure” was significantly different from psychological remedies. The number of the respondents who experienced “10. No refunds will be given for cancellations” was larger than that of those experiencing “10. No refunds will be given for cancellations”. When consumers encountered “10. No refunds will be given for cancellations”, they were not willing to obtain substantive remedies. Thus, H1 was supported (Table 2).
4.6. Impact of Service Recovery Strategy Acceptance on Post-Recovery Satisfaction
Service recovery (Beta: 0.571) positively impacted post-recovery satisfaction, and the amount of inspection variation was 32.0%, indicating that if the platform improves service recovery, it improves post-recovery satisfaction. This supported H2 (Table 3).
Substantive remedies and psychological remedies positively impacted post-recovery satisfaction. Substantive remedies (Beta: 0.398) had a greater impact than psychological remedies (Beta: 0.271) on post-recovery satisfaction. The inspection variation was 32.4%. The service recovery strategy provided by the platform for substantive remedies improved post-recovery satisfaction (Table 4).
4.7. Impact of Post-Recovery Satisfaction on Loyalty
Post-recovery satisfaction (Beta: 0.6392) significantly impacted loyalty, and the variation was 47.4%, indicating that the improvement of post-recovery satisfaction improved platform loyalty. Thus, H3 was supported (Table 5).
5. Conclusions
Service failures in online delivery and food and beverage services were explored in this study. The most serious failures include “3. Missing food and beverage products” and “10. No refunds will be given for cancellations”. When food and beverage products were missed from orders, the service provider lost customers. In terms of service recovery strategy acceptance, psychological remedies were more important than substantive remedies. “3. The platform gives this consumption for free” was the item with the greatest level of acceptance, and consumers were less likely to obtain psychological remedies when they encountered a process failure, especially for “10. No refunds will be given for cancellations”. Post-recovery satisfaction was low, and consumers were negative about the service recovery when they encountered service failures. Consumers thought it was inappropriate and were not satisfied with the way they were handled. Loyalty scores were not high, especially if the delivery service increased its fee. Consumers were found to use food delivery services less often. Service recovery strategies must be considered in food delivery services to improve the post-recovery satisfaction of customers and loyalty.
The most frequent and most severe service failure was “missing food and beverage products”. Thus, it is recommended that food delivery service staff need to confirm that the store delivers precisely. If the store is busy and cannot confirm delivery, they need to confirm that the food delivery address is correct. Service recovery highly impacted customer satisfaction, and customers scored highly for “3. The platform gives this consumption for free”. Thus, in food delivery services, service failures must be avoided and service recovery must be offered. Consumers were not satisfied with the service recovery of the current food delivery service platforms in general. Therefore, food delivery service platforms must provide service recovery after each service failure to improve customers’ evaluations of the platform. Consumers are less likely to have their loyalty affected by fees. Therefore, it is recommended that the adjustment of service fees be minimized so that consumers can use the platform consistently.
Author Contributions
Conceptualization, Y.-J.H. and S.-C.C.; methodology, Y.-J.H. and S.-C.C.; validation, S.-C.C., Y.-S.L., H.-Y.C. and W.-T.C.; formal analysis, Y.-J.H.; investigation, S.-C.C., Y.-S.L., H.-Y.C. and W.-T.C.; resources, Y.-J.H.; data curation, S.-C.C., Y.-S.L., H.-Y.C. and W.-T.C.; writing—original draft preparation, Y.-S.L., H.-Y.C. and W.-T.C.; writing—review and editing, W.-T.C.; supervision, Y.-J.H.; project administration, Y.-J.H.; funding acquisition, Y.-J.H. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
Data are contained within the article.
Conflicts of Interest
The authors declare no conflict of interest.
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Figure 1.
Research framework.
Table 1.
Correlation between service failures and service recovery strategy acceptance.
| Substantive | Psychological Remedies | ||
|---|---|---|---|
| Process failure | Pearson correlation | −0.008 | −0.257 ** |
| significance (two-tail) | 0.925 | 0.003 | |
| amount | 128 | 128 | |
| Outcome Failure | Pearson correlation | 0.026 | −0.115 |
| significance (two-tail) | 0.775 | 0.194 | |
| amount | 128 | 128 | |
** p < 0.01.
Table 2.
Service failures and service compensation.
| Classification | Question | Remedies | T |
|---|---|---|---|
| Process failure |
| Substantive | 0.300 |
| Psychological | 1.701 | ||
| Process failure |
| Substantive | −0.811 |
| Psychological | 0.595 | ||
| Outcome failure |
| Substantive | −0.898 |
| Psychological | −0.367 | ||
| Process failure |
| Substantive | 0.068 |
| Psychological | 0.724 | ||
| Outcome failure |
| Substantive | 0.456 |
| Psychological | 1.115 | ||
| Outcome failure |
| Substantive | 0.237 |
| Psychological | 0.331 | ||
| Outcome failure |
| Substantive | −0.337 |
| Psychological | 1.709 | ||
| Process failure |
| Substantive | −0.502 |
| Psychological | 0.515 | ||
| Process failure |
| Substantive | 0.010 |
| Psychological | 1.785 | ||
| Process failure |
| Substantive | 0.110 |
| Psychological | 2.091 * | ||
| Process failure |
| Substantive | 1.176 |
| Psychological | 1.117 |
* p < 0.05.
Table 3.
Analysis of the impact of service recovery strategy acceptance on post-recovery satisfaction.
Table 3.
Analysis of the impact of service recovery strategy acceptance on post-recovery satisfaction.
| Model | Standardized Coefficient | t | Significance |
|---|---|---|---|
| Beta Allocation | |||
| (Constant) Service recovery | 3.786 | 0.000 | |
| 0.571 | 7.799 | 0.000 | |
| F | 60.817 | ||
| Significance | 0.000 | ||
| 0.320 | |||
| Dependent variable: Post-recovery satisfaction | |||
Table 4.
Impact of substantive remedies and psychological remedies on post-recovery satisfaction.
| Model | Standardized Coefficient | t | Significance |
|---|---|---|---|
| Beta Allocation | |||
| (Constant) substantive remedies psychological remedies | 3.584 | 0.000 | |
| 0.398 | 4.804 | 0.000 | |
| 0.271 | 3.274 | 0.001 | |
| F | 31.377 | ||
| significance | 0.000 | ||
| 0.324 | |||
| Dependent variable: Post-recovery satisfaction | |||
Table 5.
Post-recovery satisfaction on loyalty.
| Model | Standardized Coefficient | t | Significance |
|---|---|---|---|
| Beta Allocation | |||
| (Constant) Post-Recovery Satisfaction | 1.837 | 0.069 | |
| 0.692 | 10.748 | 0.000 | |
| F | 115.516 | ||
| significance | 0.000 | ||
| 0.474 | |||
| Dependent variable: loyalty | |||
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MDPI and ACS Style
Huang, Y.-J.; Chang, S.-C.; Lin, Y.-S.; Chan, H.-Y.; Chang, W.-T. Regression Analysis to Identify Relationship between Service Failure, Service Recovery, Customer Satisfaction and Loyalty in Food Delivery Platform. Eng. Proc. 2024, 74, 28. https://doi.org/10.3390/engproc2024074028
AMA Style
Huang Y-J, Chang S-C, Lin Y-S, Chan H-Y, Chang W-T. Regression Analysis to Identify Relationship between Service Failure, Service Recovery, Customer Satisfaction and Loyalty in Food Delivery Platform. Engineering Proceedings. 2024; 74(1):28. https://doi.org/10.3390/engproc2024074028
Chicago/Turabian StyleHuang, You-Jie, Shu-Chia Chang, Yi-Shin Lin, Ho-Yi Chan, and Wei-Ting Chang. 2024. "Regression Analysis to Identify Relationship between Service Failure, Service Recovery, Customer Satisfaction and Loyalty in Food Delivery Platform" Engineering Proceedings 74, no. 1: 28. https://doi.org/10.3390/engproc2024074028
APA StyleHuang, Y.-J., Chang, S.-C., Lin, Y.-S., Chan, H.-Y., & Chang, W.-T. (2024). Regression Analysis to Identify Relationship between Service Failure, Service Recovery, Customer Satisfaction and Loyalty in Food Delivery Platform. Engineering Proceedings, 74(1), 28. https://doi.org/10.3390/engproc2024074028
