--- Page 1 --- ACKNOWLEDGEMENTS First and foremost, I owe my deepest gratitude to my advisor, Dr. Thomas Krikser, for his vigilant guidance, extensive knowledge, valuable suggestions, and, most importantly, his patience throughout this project. His insightful feedback and unwavering support have been crucial in every stage of my research. His encouragement and dedication have inspired me to strive for excellence and have significantly contributed to the success of this project. I would also like to extend my heartfelt thanks to Mrs. Paula Krejbich for her excellent advice and invaluable assistance with the research. Her insights and support have been instrumental in shaping the direction and outcome of this study. Her willingness to help and her keen understanding of the subject matter have been greatly appreciated. Lastly, my sincere gratitude goes to my family for their continuous and unparalleled love, support, and encouragement. I am especially grateful to my parents for always being there for me and providing financial support during my lab work. Without their support, I could not have completed this research. List of Figure Figure 1: Recognition rate of the FDAs in Kassel City (Multiple-answer question) 9 Figure 2: Frequency of using FDA in Kassel City 10 List of Table Table 1: List of Variables after Adjustment 7 Table 2: Experience with the Food Delivery Service in Kassel City 8 Table 3: Experience with the FDA in Kassel City 8 Table 4: Socio demography of observed sample 11 Table 5: Cronbach alpha result 12 Table 6: Summary of Fit Indices 13 Table 7: Standardized Factor Loadings 14 --- Page 2 --- Table 8: Pearson correlation coefficients 15 Table 9: Model Summary 16 Table 10: Coefficients of independent factors in multivariate regression 17 List Of Abbreviations FDA: Food delivery application CFA: Confirmatory Factor Analysis EFA: Exploratory Factor Analysis EOU: Ease of use PR: Price RK: Risk UF: Usefulness TR: Trust SI: Social Influence IU: Intention to use DETERMINANTS SHAPING CONSUMER INTENTIONS FOR UTILIZING FOOD DELIVERY APPLICATIONS WITHIN THE URBAN CONFINES OF KASSEL, GERMANY Tuan M. Nguyena, Thomas Krikserb, Paula Krejbichc --- Page 3 --- a Department of Ökologische Agrarwissenschaften, Kassel University b Corresponding author’s email address: c Corresponding author’s email address: ABSTRACT The purpose of this study was to investigate the factors that affect the customer intention to use the Food Delivery Application (FDA) within the urban confines of Kassel, Germany. The preliminary scales are created based on the Theory of Reasoned Action model (Ajzen & Fishbein, 1975), the Technology Acceptance Model (Davis, 1985), and the E-CAM model (Joongho Ahn, 2001). After that, interviews with experts are conducted to adjust the questionnaire. The survey was conducted using the convenience method and 375 responses were collected from consumers in Kassel City and analyzed using Cronbach’s alpha for reliability, Confirmatory Factor Analysis (CFA) to confirm the fitness of the model, and multiple regression analysis to conclude the relationship between the factors and the usage intention of the FDA. The results indicate that perception of price, perceived usefulness, perception of trust, and social influence all contribute positively to the intentions for utilizing FDA within the urban confines of Kassel City. Conversely, the perception of risk exerts a negative impact on the intention to utilize FDAs in Kassel City. Additionally, this study offers several managerial recommendations for food delivery app providers. These suggestions aim to enhance service quality, guide future development strategies, and support market expansion. Keywords: Food delivery applications, consumer behavior, intention to use, Kassel city, marketing Introduction In today''''s fast-paced world, where people struggle daily with work-life balance, many find buying groceries or cooking a waste of time. This is where food delivery applications step in and change the traditional delivery concept (Hirschberg et al., 2016). With just a smartphone, people can access and filter the restaurants in the area to their liking with detailed information on menus, price points, and reviews from other users… It takes almost no effort to have a meal served at their doorstep in less than an hour. Research shows that speed, accuracy, and ease of use are key reasons people shop online (Dixon et al., 2009; Kimes, 2011), with convenience being a major driver of customer loyalty (Goebel et al., 2012). Despite extensive studies on online shopping behavior, there is limited research specifically on food delivery apps. Thus, it is critical to comprehend both the driving forces behind consumer usage of the apps and the barriers that discourage individuals from ordering their food online. The food delivery system in Germany experienced a surge during the coronavirus (COVID-19) pandemic. With the enforcement of lockdown measures requiring the closure of all restaurants, many businesses had to adapt to food delivery services as a means of survival during this challenging period. Moreover, Germans are also getting used to ordering food or groceries online. In 2020, Germans expended nearly 4 billion euros on delivery services. The major German food delivery apps are Wolt, Lieferando, Yuze, Ubers Eat, and Gorillas. The competition in this industry intensified when many big companies started entering the market. With just Lieferando and Dominos dominating in 2020, in late 2021, Ubers Eats, Wolt, and Gorillas joined the market and quickly gained a share through tons of marketing and promotion. In a survey conducted by Umair Bashir in 2023 on online food delivery bookings, findings revealed that 75 percent of the respondents had utilized Lieferando in the past 12 months. Following closely, Dominos garnered a usage rate of 27 percent, while Uber Eats was utilized by 18 percent of the respondents. According to Statista, n.d., The online food delivery market in Germany is anticipated to achieve a revenue of US$17.60 billion in 2024. This revenue is forecasted to exhibit an annual growth rate of 11.27% (CAGR 2024-2028), leading to a market volume of US$26.98 billion by 2028. Within the Meal Delivery market, the user base is expected to reach 37.0 million by 2028. The heightened demand in Germany''''s online food delivery market is attributed to the nation''''s emphasis on efficiency and convenience. Kassel is a city on the Fulda River in northern Hesse in central Germany. It is the third largest city in Hesse state, with a population of 200,406 in 2021. With more than 40 percent of the population belonging to the millennials and genZ generation (Kassel Stadt, Hesse, Germany, n.d.), the city is expected to have a high usage of food delivery. The COVID-19 pandemic accelerated the adoption of these services, leading to the entry of several food delivery apps into the Kassel market, including Lieferando, Dominos, Uber Eats, and Flink, and the city even has its local food delivery application called Yuze. Therefore, it is sensible to conduct a study about the determinants shaping customer intentions for using food delivery applications within Kassel City. Objective This research has two main objectives: firstly, to identify the key factors affecting the usage intention of FDA within Kassel city, Germany, and secondly to suggest possible marketing strategies to food delivery companies to improve the functions and services to meet the consumer’s requirements. Methodology Development of hypotheses By means of a comprehensive review of the scholarly literature encompassing the topics of intention to use and the acceptance of technology, in conjunction with relevant theoretical frameworks. This study posits a set of six key determinants to identify the factors that impact consumer intention to employ food delivery applications such as Lieferando, Wolt, Uber Eat, and Yuze… within Kassel City, Germany. The study inherits factors from three models and one study: the social influences factor from the TRA model (Ajzen & Fishbein, 1975), perceived ease of use and perceived usefulness from the TAM (Davis, 1985), Perception of risk from the E-CAM model (Joongho Ahn, 2001) and Perception of price, Perception of trust, and perceived usefulness from the study of Hasslinger et al (2007). Hypothesis H1: Perceived ease of use has positive (+) effects on the usage intention of food delivery applications within the urban confines of Kassel, Germany
Introduction
Objective
This research has two main objectives: firstly, to identify the key factors affecting the usage intention of FDA within Kassel city, Germany, and secondly to suggest possible marketing strategies to food delivery companies to improve the functions and services to meet the consumer’s requirements.
Methodology
Development of hypotheses
By means of a comprehensive review of the scholarly literature encompassing the topics of intention to use and the acceptance of technology, in conjunction with relevant theoretical frameworks This study posits a set of six key determinants to identify the factors that impact consumer intention to employ food delivery applications such as Lieferando, Wolt, Uber Eat, and Yuze… within Kassel City, Germany The study inherits factors from three models and one study: the social influences factor from the TRA model (Ajzen & Fishbein, 1975), perceived ease of use and perceived usefulness from the TAM (Davis, 1985), Perception of risk from the E-CAM model (Joongho Ahn, 2001) and Perception of price, Perception of trust, and perceived usefulness from the study of Hasslinger et al (2007).
Hypothesis H 1 : Perceived ease of use has positive (+) effects on the usage intention of food delivery applications within the urban confines of Kassel, Germany
Hypothesis H 2 : Perception of price has positive (+) effects on the usage intention of food delivery applications within the urban confines of Kassel, Germany
Hypothesis H 3 : Perception of trust has positive (+) effects on the usage intention of food delivery applications within the urban confines of Kassel, Germany
Hypothesis H 4 : Perceived usefulness has positive (+) effects on the usage intention of food delivery applications within the urban confines of Kassel, Germany
Hypothesis H 5 : Perception of risk has negative (-) effects on the usage intention of food delivery applications within the urban confines of Kassel, Germany
Hypothesis H 6 : Social influences have positive (+) effects on the usage intention of food delivery applications within the urban confines of Kassel, Germany
Qualitative research
Our seven determinants (1) Perceived ease of use, (2) Perception of price, (3) Perception of trust, (4) Perceived usefulness, (5) Perception of risk, (6) Social influences, and (7) Usage intention will be measured by Likert 5-point scale with 1 strongly disagree to 5 strongly agree Based on the literature review a preliminary scale is created.
Qualitative research is focused on investigating, enhancing, and refining the observed variables utilized for measuring the concepts within the model To adjust the scale, we interviewed experts and individuals, ensuring that the chosen approach still encapsulates the traits of the observed sample set These interviews are guided by a structured framework aimed at standardizing the preliminary scale for the seven listed determinants The discussion focused on the elements that constitute the determinants influencing the intention to use the food delivery application, along with the preliminary scale for the mentioned seven determinants.
Each participant engaged in an initial discussion with the researcher to gather pertinent data Subsequently, the questionnaire is refined based on the collected information The adjusted data then is deliberated upon with the participants once more.The qualitative research process concludes when the discussion questions yield consistent results that align with the previous findings or reveal novel insights Le Nam &Mai (2021).
Quantitative research
Quantitative research is implemented using survey questionnaires Data collection is carried out after the qualitative research phase, where the questionnaire is refined into an official version The gathered information is utilized to assess the reliability and validity of the scale, the appropriateness of the model, and the relationship between the factors.
In non-probability sampling, the convenience method is commonly employed to select participants The sample size is dictated by data analysis techniques, financial constraints, and accessibility In Confirmatory Factor Analysis (CFA), the N:q ratio, representing the ratio of cases to free parameters, is a suggested guideline Minimum recommendations range from 10:1 to 20:1 (Schumacker & Lomax, 2015; Kline, 2016; Jackson, 2003) Our sample size of 375 is appropriate for 21 observed variables based on this ratio.
The data is collected through a questionnaire The survey is administered using a combination of methods, including online distribution via the EFS survey portal and printed surveys The process should take place for roughly one month.
The data will be analyzed using IBM SPSS Statistics 29.0 for Pearson correlation and multivariate regression R studios are used to analyze Cronbach’s alpha and CFA.
The scale's reliability was assessed by calculating the Cronbach Alpha coefficient A higher Cronbach Alpha coefficient indicates increased internal consistency reliability It is applied before CFA to exclude variables that have a bad influence on the data (Tavakol et al., 2011)
The Cronbach Alpha coefficient solely reveals the association among measurement variables without specifying which variables should be retained or eliminated Hence, the incorporation of Corrected Item-Total Correlation is recommended to identify and exclude variables that contribute minimally to the intended concept being measured (Hoang, n.d.).
CFA differs from Exploratory Factor Analysis (EFA) as it aims to verify a specific theoretical model rather than exploring underlying factors without predefined notions Unlike EFA, CFA requires researchers to predetermine the number of factors and variables within each factor, assessing how well the existing model fits with research data This process entails examining if the theoretical model aligns with the study's findings, confirming or challenging the validity of the model.
2.3.5 Multiple linear regeneration a) Pearson correlation coefficient
Scales deemed satisfactory were incorporated into Pearson correlation and multiple regression analyses to examine the hypotheses Pearson correlation analysis establishes a linear relationship between the dependent and independent variables, thus validating the appropriateness of subsequent linear regression analysis A Pearson correlation coefficient approaching 1 indicates a stronger linear correlation between two variables Simultaneously, it is essential to scrutinize the correlation among independent variables to identify significant correlations Strong correlations between independent variables need attention as they can impact regression analysis results, potentially leading to issues like multicollinearity (Hoàng Trọng & Chu Nguyễn Mộng Ngọc, 2005). b) Multiple linear regression
The cause-and-effect relationship of the factors is modeled through multiple linear regression The study employed multivariate regression using the Enter method,where all variables were analyzed simultaneously, and the pertinent statistical results were taken into account (Hoàng Trọng & Chu Nguyễn Mộng Ngọc, 2005).
Result
Qualitative research
Table 1: List of Variables after adjustment
EOU1 Learning how to use Food Delivery Applications is effortless for me.
EOU2 The functions of the Food Delivery Applications are clear and easy to understand.
EOU3 The registration, purchasing, and payment procedures of the Food Delivery
Applications are quite simple for me.
EOU4 I can easily find the products I need when using the Food Delivery Application.
PR1 I believe the food delivery application cost is reasonable for the convenience provided.
PR2 I can easily compare the prices of the products.
PR3 I can save money through the application’s special promotions, discounts, or loyalty programs.
PR4 Any additional charges or fees are clearly communicated before placing the order.
TR1 The orders I received are mostly accurate and undamaged.
TR2 The positive reviews and high ratings from other users are accurate.
TR3 Customer support is easily accessible and responsive.
UF1 Food delivery applications help me save time.
UF2 I can buy food anywhere I need with the food delivery application.
UF3 I can buy food any time I need with the food delivery application.
RK1 I am concerned that my personal information might be revealed to a third party without my consent.
RK2 I am concerned about the security of the payment process, which may lead to the loss of my card details and money.
RK3 I am concerned about the restaurant’s food safety.
SI1 My family and relatives believe I should use the food delivery application.
SI2 I was encouraged to use the food delivery application by friends and colleagues who had already tried and recommended it.
SI3 I decided to try food delivery applications after hearing about them from both people in my social circle and the media.
IU1 I plan to use (or continue to use) the food delivery application in the next few months.
IU2 I will invite other people to use the food delivery application.
The preliminary scales are adjusted based on the interviews with 5 experts in the field of FDA Table 1 shows the list of statements for the preliminary scale after adjustment In summary, we have 7 preliminary scales with 22 variables.
Characteristics of the sample
The sample is chosen using the convenience method in the form of survey questionnaires The quantitative analysis was conducted on 375 valid surveys from both the online and offline forms after invalid questionnaires were removed (due to missing responses or disagreement with the data consent).
3.2.1 Usage of the Food Delivery Application a) Experience with the Food Delivery Service
Table 2: Experience with the Food Delivery Service in Kassel City
Years of experience Number of responses
Our survey reveals that residents of Kassel City possess substantial experience with Food Delivery Services Notably, 18% have less than a year of experience, while the majority (62%) have used these services for extended periods Specifically, 33% have 1-3 years of experience, 24% have 3-5 years, and an impressive 25% have over 5 years of experience These findings indicate a high level of familiarity and comfort with food delivery services among the city's residents.
Table 3: Experience with the FDA in Kassel City
Years of experience Number of responses
Table 3 reveals the levels of experience with FDAs among our sample It indicates that over a quarter have little to no experience: 12% have never used FDAs, and 17% have less than a year of experience A significant portion, 36%, have been using FDAs for 1 to 3 years Meanwhile, 23% have between 3 to 5 years of experience, and 12% have more than 5 years of experience with FDAs This data suggests that while Kassel City's residents are generally familiar with Food Delivery Services, the concept of FDAs is relatively new to them, with most users having limited experience. c) Recognition rate of FDA in Kassel City
Lieferando Wolt Yuze Uber Eats Other 0
Figure 1: Recognition rate of the FDAs in Kassel City (Multiple-answer question)
Figure 1 presents the ranking of five FDA options in Kassel City based on recognition Lieferando and Uber Eats are the most recognized with more than 200 responses out of 375 participants Lieferando, being the first FDA to establish itself in Kassel City, has gained significant recognition Uber Eats enjoys strong brand recognition and trust, largely due to its affiliation with the globally recognized Uber brand.
Wolt, another prominent FDA in Germany, is known to around 20% of participants This relatively lower recognition in Kassel is attributed to its more recent market entry into the city In contrast, Yuze, a local FDA, despite being one of the early entrants and having a local focus, suffers from low brand awareness with only 27 responses out of 375 This is likely due to insufficient marketing efforts which is indicated by their low reach on their social media account such as Instagram
Other food delivery services like KFC, Domino's Pizza, and Flink do not have significant popularity in Kassel, as indicated by their minimal recognition of only 15.2% among survey participants. d) Frequency of using FDA
Figure 2: Frequency of using FDA in Kassel City
Among the 375 survey participants, the frequency of using FDAs varies considerably A large portion of the participants use FDAs Occasionally, 83 respondents use them less than once a month, while 137 respondents use them 1 to 2 times a month Additionally, 63 people reported using FDAs once a week, and 53 respondents used these services 2 to 3 times per week Only a small group uses FDAs more frequently, with 25 respondents utilizing them 3 to 6 times per week and 15 respondents using FDAs daily This indicates that in Kassel City while FDAs are regularly used by some, the majority seldom use it, typically on a monthly or weekly basis.
Table 4: Socio demography of observed sample
Characteristics Number of response Percentage
Table 4 illustrates the gender distribution of FDA users, revealing that males constitute the largest group Specifically, males represent 58% of FDA users, while females make up 40%, and others account for 2%.
Table 4 provides a breakdown of the age distribution within our sample The majority of users fall into the 23-35 age group, which comprises 61.3% of the sample.The 18-23 age group is the next largest, making up 33.3% of participants Those in the35-60 age group account for 3.7%, while the least represented groups are individuals under 18 at 1.2% and those over 60 at 0.5% According to the literature, we will remove the response of the under-18 group since they are not economically independent.
Reliability test of the scale
Observed variables M SD Reliability if an item is dropped Corrected Item-
Total Correlation Perceived Ease of Use
Cronbach’s Alpha: 0.85 Perception of Price
Cronbach’s Alpha: 0.73 Perception of Trust
Cronbach’s Alpha: 0.78 Perception of Risk
Cronbach’s Alpha: 0.65 Intention to use
In our research, we assessed the reliability of our scales using Cronbach’s Alpha and Corrected Item-Total Correlations and the results are shown in Table 5 The Cronbach’s Alpha values for all factors exceeded the 0.6 threshold, indicating acceptable internal consistency The lowest Cronbach’s Alpha was observed for the
"perception of trust" factor at 0.64, while the highest was for the "perceived ease of use" factor at 0.85.
Moreover, the Corrected Item-Total Correlations for all variables surpassed the0.3 threshold This meets the criteria set by Cristobal et al (2007), which deem these values acceptable for scales with fewer than seven items These results confirm that our measurement scales have adequate reliability Thus, can be used for the CFA to test the structural model.
Confirmatory factor analysis
Table 6: Summary of Fit Indices
Root Mean Square Error of Approximation (RMSEA) 0.064
Standardized Root Mean Square Residual (SRMR) 0.057
Table 6 gives us the summary of the fit indices of our CFA First, The CFI value is 0.906 According to Hu and Bentler (1999), a CFI value of 0.90 or higher indicates a good fit between the hypothesized model and the observed data The TLI is reported as 0.885 While slightly below the conventional threshold of 0.90 for a good fit, it is still within the range considered acceptable
The Root Mean Square Error of Approximation (RMSEA) value of 0.064, within a 90% confidence interval of 0.057 to 0.071, indicates an acceptable fit to the data as per Browne and Cudeck (1993) Moreover, the Standardized Root Mean Residual (SRMR) of 0.057 falls below the 0.08 threshold established by Hu and Bentler (1999), further supporting a good fit.
Strong relationships were evident between observed variables and their factors, with standardized factor loadings ranging mostly from 0.6 to 0.91 (p < 001) Slight deviations below the 0.6 threshold were observed for TR1 (0.56) and SI3 (0.53), but these values remained acceptable and contributed valuable information to their respective constructs.
Pearson correlation test
Facto r Mean SD EOU PR TR UF RK SI IU
The Pearson correlation coefficients for the seven factors in our study are presented in Table 8 Our primary focus is on examining the correlation coefficients between the dependent variable, intention of use (IU), and the six independent variables: Perceived Ease of Use (EOU), Perception of Price (PR), Perception of Trust (TR), Perception of Risk (RK), Perceived Usefulness (UF), and Social Influence (SI). According to Table 6, the Pearson correlation coefficients between IU and EOU (r 0.33), PR (r = 0.48), TR (r = 0.42), UF (r = 0.42), SI (r = 0.53) are high and are significant at the 0.01 level (p < 0.01) This indicates a strong linear relationship between these variables and makes it reasonable for multi-linear regression analysis
Furthermore, we also notice the coefficient between some independent variables is also high This strong correlation among independent variables may lead to the multicollinearity phenomenon when doing multi-linear regression, which can distort the statistical analysis by inflating the variances of the estimated regression coefficients. Thus, we also need to check for the value inflation factors to avoid multicollianary
The Pearson correlation coefficient between IU and RK is low, indicating a weak or negligible linear relationship between perception of risk and intention of use Despite this low correlation, RK might still be significant in a multiple linear regression model due to its potential interactions or indirect effects through other variables (Hair, 2010) It is essential to include RK in the regression model because variables with low bivariate correlations can still have unique contributions to explaining the dependent variable when considered within the context of other predictors This is particularly true in complex multivariate models where the interplay among variables can reveal significant effects not captured by simple pairwise correlations.
Multiple linear regression
To evaluate our hypotheses, we performed a multiple linear regression analysis with a 95% confidence level The dependent variable in this analysis is IU, while the independent variables include EOU, PR, TR, RK, UF, and SI The multivariate linear regression equation has the following form:
IU = β0 + β1*EOU + β2*PR + β3*TR + β4*UF+ β5* RK + β6* SI + ε
Std Error of the Estimate
R Square Change F Change df1 df2 Sig F
The linear regression model exhibited a strong fit with the data, as indicated by the F-statistic (F (6,368) = 42.325, p < 0.001) The model explained 40.8% of the variance in the dependent variable, with Adjusted R2 and R2 values of 0.408 Furthermore, the absence of multicollinearity was confirmed by VIF values ranging from 1.12 to 1.74, well below the acceptable threshold of 10 (O'Brien, 2007).
Table 10: Coefficients of independent factors in multivariate regression
Hypothesis H 1 : Perceived ease of use has positive (+) effects on the usage intention of FDAs within the urban confines of Kassel, Germany
The Standardized regression coefficient β1 = -0.043, sig(β1) = 0.395 > 5%: reject hypothesis H1
Hypothesis H 2 : Perception of price has positive (+) effects on the usage intention of FDAs within the urban confines of Kassel, Germany
The Standardized regression coefficient β2 = 0.214, sig(β2) = 0.000 < 5%: accept hypothesis H2
Hypothesis H 3 : Perception of trust has positive (+) effects on the usage intention of FDAs within the urban confines of Kassel, Germany
The Standardized regression coefficient β3 = 0.179, sig(β3) = 0.000 < 5%: accept hypothesis H3
Hypothesis H 4 : Perceived usefulness has positive (+) effects on the usage intention of FDAs within the urban confines of Kassel, Germany
The Standardized regression coefficient β4 = 0.124, sig(β4) = 0.013 < 5%: accept hypothesis H4
Hypothesis H 5 : Perception of risk has negative (-) effects on the usage intention of FDAs within the urban confines of Kassel, Germany
The Standardized regression coefficient β5 = -0.098, sig(β5) = 0.022 < 5%: accept hypothesis H5
Hypothesis H 6 : Social Influence has positive (+) effects on the usage intention of
FDAs within the urban confines of Kassel, Germany
The Standardized regression coefficient β5 = 0.358, sig(β6) = 0.000 < 5%: accept hypothesis H6
Discussion
Perceived Ease of Use
The results of the survey in the Kassel area indicate the lack of evidence that the factor “Perceived ease of use” has a positive effect on the usage intention of FDAs This goes against prior studies of Muangmee’s 2021 in Bangkok, Thailand, and Le Nam & Mai’s (2021) study conducted in Da Nang City, Vietnam, which revealed a similar positive relationship between perceived ease of use and usage intention of the FDA user.
The rejection of the hypothesis can be explained as Germany is highly engaged in digital transformation, positioning itself as a leader in various aspects of digital innovation and infrastructure Germany has set ambitious goals through its "Digital Strategy 2025," focusing on integrating digital technologies into every facet of life and business This strategy includes enhancing digital skills, modernizing education with digital tools, and fostering innovation across industries (Germany - Digital Strategy 2025, 2022)
Given Germany's strong emphasis on digital integration, it is plausible that the perceived ease of use of digital applications, including FDAs, is less of a determinant for user intention in Kassel City People in regions with advanced digital landscapes might find ease of use to be a standard expectation rather than a differentiating factor This could explain why the influence of perceived ease of use on the intention to use FDAs is different in Kassel City compared to other cities in the Southeast Area region with different levels of digital engagement.
Perception of Price
From the results, we can conclude that the better the price from the FDAs the higher the engagement intention of the user This fits with the outcome of the study by
Le Nam & Mai (2021) According to Table 10, the coefficients of the factors (0.214) indicated that price is the second most significant factor influencing the intention to use. Specific price-related aspects such as reasonable costs for convenience, ease of price comparison, savings through discounts, and transparent additional fees, significantly impact the customer’s behavior, giving them a stronger intention to use the FDAs. Especially the transparent additional fees with 3.94 points from the survey
In Kassel City, 5 FDAs are currently competing for their market share This intense competition atmosphere among FDAs has sparked a price war, leading to substantial promotions, discounts, and loyalty programs As a result, FDAs often provide cheaper rates than those in conventional restaurants, which makes their service very appealing to customers who want value for money For example, Wolt and Uber Eat discounts of 30% on first orders, or Lieferando offers free deliveries Consequently, these competitive pricing strategies attract new clients while enhancing loyalty among old ones who keep enjoying ongoing cost savings and incentives However, unlike traditional restaurants where elements such as decor or location significantly influence customer decisions, in the context of FDAs, these factors are less relevant Thus, price has far more impact on consumer behavior within FDAs than in traditional restaurants.
For our suggestion, the FDAs should continue to prioritize competitive pricing strategies, in order to sustain and expand their customer base in competitive markets like Kassel City This may involve leveraging operational efficiencies, optimizing delivery logistics, and enhancing customer value through innovative promotional offers and loyalty programs To succeed in a competitive market, FDAs need to understand and make the most of how sensitive customers are to prices.
Perception of Trust
Similar to previous studies by Le Nam & Mai (2021) and Muangmee (2021), this research found that higher levels of trust in the application positively influence users' intention to use it The perception of trust, as measured by user ratings, exhibited high values (ranging from 3.37 to 3.93), indicating participants' strong trust in the application, particularly in the accuracy of their orders.
To foster trust among consumers, the FDA should enhance transparency and reliability throughout the entire process, from placing an order to receiving the food. According to Cha et al (2020), the reliability attribute of the FDA has the greatest influence on loyalty and satisfaction Therefore, accurate and detailed reviews and ratings provide users with insights into the quality and reliability of both the service and the individual restaurants This peer feedback system helps to establish a sense of security and reliability, encouraging more users to try and continue using the service.
Secondly, increasing the accuracy of live-tracking of delivery status, so that the users can access to real-time progress of their orders, reducing uncertainty and enhancing the perception of trust in the service, Accurate live-tracking is especially helpful when the wait time is long such as in busy hours or difficult weather, as it allows customers to better plan their orders This transparency in the delivery process reassures users and builds their confidence in the timely and accurate fulfillment of their orders
Thirdly, increases the effectiveness of customer support since according to our survey customer support has the lowest point The service should be able to address all the user’s concerns promptly and efficiently, resolving issues that may arise during the ordering and delivery process Moreover, this level of service ensures that users feel valued and supported, which is essential for fostering long-term loyalty and engagement.
Perceived Usefulness
The study’s outcomes align with the findings of Lee's 2017 research conducted in South Korea and Muangmee’s 2021 study in Bangkok, Thailand Both studies highlighted that perceived usefulness significantly enhances the intention to use FDAs. However, in our study, perceived usefulness has the lowest impact on the customer’s intention to use FDAs with a coefficient of only 0.124.
Perceived usefulness plays a pivotal role in determining the customer's intention to use FDAs In our study, perceived usefulness refers to how effectively these applications meet users' needs by simplifying the food ordering process, saving time, and enhancing overall convenience This sense of usefulness motivates the user to try and keep coming back to these services
FDAs offer a high degree of convenience, particularly in urban settings like Kassel City, where busy lifestyles prevail With just a smartphone, people can access and filter the restaurants in the area to their liking with detailed information on menus, price points, and reviews from other users… It takes almost no effort to have a meal served at their doorstep in less than an hour at any time This convenience is a critical aspect of perceived usefulness, as it aligns with users' needs for efficient and time- saving solutions.
Our suggestion to improve the perceived usefulness of FDAs in Kassel City is first to offer various payment methods In addition to traditional options like credit and debit cards or bank transfers, integrating modern payment methods such as digital wallets like PayPal and Apple Pay or online financial services like Klarna, Skrill… allows users to choose the most convenient and secure options Second, provide 24/7 customer service through live chat, phone support, email, social media, and comprehensive FAQs, so that the problem can be solved at any time the customers want and maintain high satisfaction levels This continuous support fosters trust and reliability, further enriching the user experience Third, the FDAs can apply AI to improve the personalized recommendations functions With AI, FDAs can analyze customers based on their order history, personal preferences, and search history and tailor the restaurant options for each customer Last, it is crucial to ensure there are enough delivery drivers, especially during busy hours such as lunchtime The lack of drivers during such hours can lengthen the expected wait time and affect the customer’s satisfaction Having sufficient staff helps to guarantee timely deliveries and maintain customer convenience This approach ensures that the service remains reliable and efficient, enhancing the overall customer experience.
Perception of Risk
Our analysis reveals that the higher the customer's awareness of the risk, the lower the customer’s intention to use the application However, Le Nam & Mai (2021) had different suggestions They contend that the idea that the risk factor is connected to the intention of usage is unsupported by the available data in Da Nang City, Vietnam
The contradiction between our results and other literature such as Le Nam & Mai(2021), can be explained by the higher awareness of data protection in Germany, which scored 3.78 on the questionnaire Germany is known for its strict and comprehensive data protection laws, which are designed to safeguard individuals' privacy and ensure the secure handling of personal data According to numerous surveys conducted after the General Data Privacy Regulation (EU GDPR) went into effect six years ago For instance, a 2023 survey by the Association of the Internet Industry found that over78.4% of Germans are worried about their data being misused online (eco-Verband derInternetwirtschaft e.V., 2023) Another survey conducted by Eco indicates that a significant portion of users are cautious about their online privacy: 49.7% of users limit app permissions, 40.2% adjust their internet browser settings, and 35.2% are mindful of their social media usage (eco-Verband der Internetwirtschaft e.V., 2023) This suggests that concerns about data protection and privacy may make some individuals wary of using FDAs, potentially leading to hesitation in trying these services.
Food safety concerns negatively impact the adoption of food delivery apps (FDAs) Participants expressed concerns over food safety, with a score of 3.71 Unlike traditional dine-in experiences, FDA users have limited visibility into restaurant hygiene, relying on food images Moreover, the delivery process poses contamination risks due to insufficient hygiene training for delivery drivers, potentially compromising food safety during transit.
To lower the perception of risk, the FDAs must prioritize food safety to protect their customers and maintain trust By implementing strict hygiene practices, ensuring proper handling and packaging, and adhering to regulatory standards, drivers can significantly minimize the potential for food hazards Moreover, restaurants can pose images of their kitchens, staff, and food safety certifications to enhance the trust of the customers Furthermore, FDAs should have clear and transparent privacy policies that explain how customer data is collected, used, and safeguarded These policies must ensure adherence to relevant data protection regulations, including the GDPR.
Social Influence
Table 10 shows that Social Influence positively affects a customer's intention to use the FDAs Le Nam & Mai (2021) and Muangmee (2021) both recognized the importance of Social Influence in their studies on FDAs However, our research in Kassel highlights an even stronger impact of Social Influence, suggesting that in this city, the opinions and behaviors of others play a more critical role in driving the intention to use FDAs.
According to the data presented in Table 10, social influence has been identified as the most influential factor in shaping customers' intentions to use FDAs with a coefficient of 0.358 Among the variables, the influence from social media has the highest mean of 3.69 points, highlighting the effectiveness of robust marketing campaigns on social media by FDAs in Kassel City
In recent years, FDAs have extensively utilized social media to broaden their visibility and attract diverse customer segments They used advanced targeting technology on these platforms to effectively reach their desired audiences By focusing on specific criteria like location, interests, and online behaviors, FDAs can tailor their outreach efforts to connect with users who are interested in their service (Rachmad, Y. E.,2022) Combining these social media strategies with other digital marketing tactics, such as search engine optimization (SEO) and paid search ads, can create a comprehensive approach for acquiring customers This multi-channel strategy not only increases brand awareness but also drives user engagement and loyalty by offering a seamless and personalized customer experience across various touchpoints (Cordova et al., 2022).
Additionally, FDAs harness the power of peer recommendations on social media.
By leveraging the community-oriented nature of these platforms, FDAs initiate campaigns that encourage users to share their experiences or specific orders on their social accounts in exchange for promotional benefits (Cordova et al., 2022) FDAs also encourage users to invite friends and family to use their apps, often through referral bonuses This strategy not only amplifies their media presence but also enhances their brand image and credibility.
To enhance social influence, Fashion Design Agencies (FDAs) should leverage social media platforms like Instagram, Facebook, Twitter, and TikTok by engaging with followers through comments, polls, and live sessions Additionally, sponsoring Kassel University student events, such as parties and competitions, can provide valuable marketing opportunities that foster brand involvement and establish a connection with the target audience.
Conclusion and recommendations
This study aimed to identify the key determinants shaping consumer intentions for utilizing FDAs in the urban confines of Kassel, Germany The research findings have identified that Social Influences, Perceived usefulness, Perception of Trust, andPerception of Price are the factors that positively affect the usage intention of FDAs inKassel Cit, while Perception of Risk has a negative impact These results align with existing literature, demonstrating the significant role of these factors in shaping consumer behavior in the context of FDAs in Kassel City One interesting finding is thatPerceived Ease of use, a traditional factor in various consumer behavior models, has little effect on the intention to use FDAs in the region The implications of these findings are substantial for FDA providers By understanding the critical factors that drive user intention, companies can develop targeted marketing strategies, improve their service offerings, and enhance user experience to increase adoption rates
From the findings, we suggest that the FDAs should prioritize competitive pricing, enhance transparency and reliability, offer diverse payment methods and round-the- clock customer service, implement stringent hygiene and data protection policies, and strengthen social media presence These strategies ensure that the FDAs can effectively attract and retain customers in Kassel City while building a strong, trustworthy brand.
Despite its contributions, this study has several limitations The sample was limited to Kassel City and the participants were recruited through convenience method, which may affect the generalizability of the findings Additionally, the cross-sectional design of the study does not allow for examining changes over time Future research should consider longitudinal studies to assess how consumer intentions evolve with market changes and technological advancements Expanding the study to other regions in Germany or different countries in the EU could provide a more comprehensive understanding of consumer behavior in diverse contexts
In conclusion, this study provides valuable insights into the factors influencing the intention to use FDAs in Kassel City By addressing these determinants, FDA providers can better meet consumer needs and enhance their market presence in an increasingly competitive landscape.
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As part of a research project at Kassel University, participant consent is sought for an interview lasting approximately 60 minutes The project aims to explore factors influencing consumer utilization of food delivery applications in Kassel, Germany Participation is voluntary, and participants have the right to withdraw at any time A data protection consent form will be provided for review and signature prior to the interview.
The information provided below serves as a criterion to assess the suitability of the participants for the preliminary research objectives When a participant under discussion has an answer that falls into the discontinue section, this participant will not be used to conduct preliminary research.
Questions used for information filtering encompass:
(1) Have you ever used food delivery services?
(2) Have you ever heard of food delivery applications before?
(3) Do you know any food delivery applications?
If yes, please list some Continue.
1 General content related to food delivery services
(1) Which food delivery applications do you know? And according to you how popular are these applications in our city?
(2) Which food delivery applications have you used in the past? How do you rate the effectiveness, advantages, and disadvantages of those applications?
(3) Have you ever recommended any food delivery applications to your friends, families, or colleagues? If yes, how is the response from your friends/families? (4) Do you think that price is something that consumers will be aware of when using food delivery applications?
(5) Do you think that usefulness is something that consumers will be aware of when using food delivery applications?
(6) Do you think that the ease of use of the applications is something that consumers will be aware of when using food delivery services?
(7) Do you think that consumers will be aware of the risk when using food delivery services?
(8) Do you think that the people around you will affect your intention to use the food delivery applications?
(9) Do you think that the trustfulness of the food delivery applications affects the customer’s intention to use?
Determinants for the usage intention
1 Perceived ease of use: This means that food delivery app users will find it easy to get the hang of using the app and feel comfortable using it to get what they want.
Learning how to use Food Delivery Applications is effortless for me.
The way I interact with the Food Delivery Application is clear and easy to understand.
I can easily find the products I need using the Food Delivery
2 Perception of price: this is reflected that certain app promotions allow the customers to purchase products at a lower price than if they were to buy them directly at the store.
I believe the food delivery application cost is reasonable for the convenience provided.
I can easily compare the prices of the products.
I can save money through the application’s special promotions, discounts, or loyalty programs.
Any additional charges or fees are clearly communicated before placing the order.
3 Perception of trust: This is expressed through their desire that the product they receive must look and function exactly as described.
The orders I received are mostly accurate and undamaged.
The positive reviews and high ratings from other users are accurate.
Customer support is easily accessible and responsive.
4 Perceived usefulness: This is recognized by giving the customer all the information needed and helping them order food in a less time-consuming way than the direct buying method.
Food delivery applications help me save time.
I can buy food anywhere I need with the food delivery application.
I can buy food any time I need with the food delivery application
5 Perception of risk: The relationship between perceived risk and customers' concerns about product quality and data protection during online shopping.
I am concerned that my personal information might be revealed to a third party without my consent.
I am afraid that my payment details might be compromised through the transaction process.
I am concerned about the restaurant’s food safety.
6 Social influences: Social influences are how people feel pressure from their friends, family, coworkers, and social media to do or not do something.
My family and relatives believe I should use the food delivery application.
I was encouraged to use the food delivery application by friends and colleagues who had already tried and recommended it.
I decided to try food delivery applications after hearing about them from both people in my social circle and the media.
7 Usage intention: is characterized as the customer's inclination to either continue using or start using the food delivery application.
I plan to use (or continue to use) the food delivery application in the next few months.
I will invite other people to use the food delivery application.
With the statement above, please let me know:
Do you understand the content of each statement? If you don't understand, please tell me why If understood, what does that statement say?
Do you think these statements are good? If not, how should I change?
For each category, are there any statements that need to be added or removed?
Welcome to our online survey on "Factors Leading to the Intention to Use Food Delivery Applications"!
Thank you for joining us in this important research endeavor Your insights will play a crucial role in understanding the factors that influence individuals' decisions to use food delivery applications.
Your participation in this study is entirely voluntary, ensuring the confidentiality of your responses Thoughtful and honest answers to each question are greatly appreciated, as your feedback holds immense value Your time and effort in contributing to the study are deeply valued and will help shape its outcomes.
Let's begin the survey and thank you once again for your participation!
One ore two times a month
Learning how to use Food
Delivery Applications is effortless for me
I can easily find the products I need when using the Food
Learning how to use Food
Delivery Applications is effortless for me
I can easily find the products I need when using the Food
The registration, purchasing, and payment procedures of the Food Delivery Applications are quite simple for me
The functions of the Food
Delivery Applications are clear and easy to understand.
I believe the food delivery application cost is reasonable for the convenience provided
I can save money through the application’s special promotions, discounts, or loyalty programs
The orders I received are mostly accurate and undamaged
I can easily compare the prices of the products
Any additional charges or fees are clearly stated before placing the order
The positive reviews and high ratings from other users are accurate
Customer support is easily accessible and responsive
I can buy food any time I need with the food delivery application
I am concerned that my personal information might be revealed to a third party without my consent
I can buy food anywhere I need with the food delivery application
I am concerned about the security of the payment process, which may lead to the loss of my card details and money
I am concerned about the restaurant’s food safety
My family and relatives believe
I should use the food delivery application
I decided to try food delivery applications after hearing about them from both people in my social circle and the media
I was encouraged to use the food delivery application by friends and colleagues who had already tried and recommended it.