Determinants shaping consumer intentions for utilizing food delivery applications within the urban confines of kassel, germany

--- Page 1 --- MSC THESIS REPORT DETERMINANTS SHAPING CONSUMER INTENTIONS FOR UTILIZING FOOD DELIVERY APPLICATIONS WITHIN THE URBAN CONFIN ES OF KASSEL, GERMANY JUNE 25, 2024 A thesis submitted to University of Kassel and Fulda University of Applied Science In partial fulfillment of the requirements for the degree of Master in Food Busisness and Consumer studies Student name: Minh Tuan Nguyen Supervisor 1: Dr. Thomas Krikser Supervisor 2: Paula Krejbich --- Page 2 --- i ACKNOWLEDGEMENTS Firstly, I owe my deepest gratitude to my advisor, Dr. Thomas Krikser , for his vigilant guidance, erudite knowledge, valuable suggestions, and especially, his patience with my problems from the beginning to the end of this project. Secondly, I would like to thank M rs. Paula Krejbich who has provided many excellent advice and assisted me with the research. Finally, my deep and sincere gratitude to my family for their continuous and unparalleled love, help and support. I am grateful to my parents for always being there for me and support me with financial problems during my lab work. Without their support I could not have finished this research. --- Page 3 --- ii LIST OF ABBREVIATIONS --- Page 4 --- iii --- Page 5 --- iv DETERMINANTS SHAPING CONSUMER INTENTIONS FOR UTILIZING FOOD DELIVERY APPLICATIONS WITHIN THE URBAN CONFINES OF KASSEL, GERMANY Tuan M. Nguyena, Thomas Krikserb, Paula Krejbichc 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 the 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 --- Page 6 --- 1 I. Introduction In today''''s busy world, many people find grocery shopping or cooking to be time - consuming, and food delivery applications have emerged as a convenient solution. These apps allow users to easily browse local restaurants, view menus, prices, and reviews, and get meals delivered quickly, often within 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. Understanding why consumers choose or avoid these services is crucial. 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. 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 (Kasse l 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, D ominos, Uber Eats, and Flink, and the city even has its local food delivery application called Yuze. 1.1. Objective This research has two main objectives: firstly, to identify the key factors affecting the usage intention of food delivery applications (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. II. Methodology 2.1. Development of hypotheses

and Consumer studies Student name: Minh Tuan Nguyen Supervisor 1: Dr Thomas Krikser Supervisor 2: Paula Krejbich

ACKNOWLEDGEMENTS

Firstly, I owe my deepest gratitude to my advisor, Dr Thomas Krikser, for his vigilant guidance, erudite knowledge, valuable suggestions, and especially, his patience with my problems from the beginning to the end of this project

Secondly, I would like to thank Mrs Paula Krejbich who has provided many excellent advice and assisted me with the research

Finally, my deep and sincere gratitude to my family for their continuous and unparalleled love, help and support I am grateful to my parents for always being there for me and support me with financial problems during my lab work Without their support I could not have finished this research

LIST OF ABBREVIATIONS

DETERMINANTS SHAPING CONSUMER INTENTIONS FOR

UTILIZING FOOD DELIVERY APPLICATIONS WITHIN THE

URBAN CONFINES OF KASSEL, GERMANY

Tuan M Nguyena, Thomas Krikserb, Paula Krejbichc

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 the 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

I Introduction

In today's busy world, many people find grocery shopping or cooking to be consuming, and food delivery applications have emerged as a convenient solution These apps allow users to easily browse local restaurants, view menus, prices, and reviews, and get meals delivered quickly, often within an hour

time-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 Understanding why consumers choose or avoid these services is crucial

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

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

1.1 Objective

This research has two main objectives: firstly, to identify the key factors affecting the usage intention of food delivery applications (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

II Methodology

2.1 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)

H1: Perceived ease of use has positive (+) effects on the usage intention of food delivery applications within the urban confines of Kassel, Germany

H2: Perception of price has positive (+) effects on the usage intention of food delivery applications within the urban confines of Kassel, Germany

H3: Perception of trust has positive (+) effects on the usage intention of food delivery applications within the urban confines of Kassel, Germany

H4: Perceived usefulness has positive (+) effects on the usage intention of food delivery applications within the urban confines of Kassel, Germany

H5: Perception of risk has negative (-) effects on the usage intention of food delivery applications within the urban confines of Kassel, Germany

H6: Social influences have positive (+) effects on the usage intention of food delivery applications within the urban confines of Kassel, Germany

2.2 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

To adjust the scale, we interviewed experts and individuals selected using a convenient method, 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

2.3 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 and assess the appropriateness of the model and the relationship between the factors

2.3.1 Sampling

The sample is chosen using the convenience method, which is a form of probability sampling The determination of the sample size is contingent upon the data analysis technique applied, financial considerations, and accessibility to the target audience In the context of Confirmatory Factor Analysis (CFA), a commonly utilized rule

non-of thumb is the N:q ratio, representing the ratio non-of cases to free parameters Typically, minimum recommendations suggest a ratio within the range of 10:1 to 20:1 (Schumacker

& Lomax, 2015; Kline, 2016; Jackson, 2003) Based on the ratio, our sample size of 375

is adequate for the 21 observed variables

2.3.2 Data collection and analysis

The data will be collected through a questionnaire The survey was conducted through a combination of methods, both online through the EFS survey portal and printed surveys The process should take place for roughly one month (Paradis et al., 2016)

The data will be analyzed using IBM SPSS Statistics 29.0, with Cronbach’s alpha for testing the reliability of the determinants scale from the qualitative analysis, CFA to determine the compatibility of research data with the theoretical model, and multiple linear regression to estimate the influence of our factors on the consumer intention for utilizing food delivery applications

2.3.3 Cronbach’s alpha

The scale's reliability was assessed using the internal consistency method, specifically 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.)

2.3.4 Confirmatory Factor Analysis

CFA is a method to verify if research data matches a particular theoretical model

In contrast to Exploratory Factor Analysis (EFA), where researchers use study data to identify underlying factors, CFA involves confirming a model of these factors established through prior research or a predetermined theoretical model In CFA, researchers must predefine the number of factors and variables in each factor In this context, CFA assesses how well an existing model fits with research data, essentially examining if the theoretical model aligns with the study findings (Phùng, n.d.)

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 crucial 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 can be modeled through linear regression The study employed multivariate regression using the Enter method, where all variables were included at once, and the relevant statistical outcomes were considered (Hoàng Trọng & Chu Nguyễn Mộng Ngọc, 2005)

III Result

3.1 Qualitative research

Table 1: List of Variables of scales after adjustment

Variable Statement

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

loyalty programs

UF3 I can buy food any time I need with the food delivery application

without my consent

loss of my card details and money

SI1 My family and relatives believe I should use the food delivery application

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 information gathered from the interviews with 5 experts in the field of Food Delivery applicaiton Table 1 shows the list of statements for each preliminary scale after adjustment In summary, we have 7 preliminary

scales with 22 variables

3.2 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)

3.1.1 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

Table 2 illustrates the distribution of experience levels among our sample in using Food Delivery Services It shows that a small portion, only 18%, have less than one year

of experience In contrast, the majority have been using these services for longer periods: 33% have between 1 to 3 years of experience, 24% have between 3 to 5 years, and 25% have more than 5 years of experience These figures suggest that residents of Kassel City are generally well acquainted with food delivery services

b) Experience with the FDA

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

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 Whereas 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 on a daily basis 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

1-2 times

a month

Once aweek

3.1.2 Demographic of the sample

Table 4: Socio demography of observed sample

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 the 35-60 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