Masterarbeit, 2022
137 Seiten, Note: 1,3
1 Introduction
1.1 Context and Problem Definition
1.2 Research Aim and Objectives
1.3 Research Questions and Study Relevance
1.4 Research Design
1.5 Research Structure
2 Literature Review
2.1 Background of e-commerce in Germany
2.1.1 E-commerce context before the COVID-19 pandemic in Germany
2.1.2 E-commerce context during the COVID-19 pandemic in Germany
2.1.3 Germany's e-commerce adoption compared to other European countries
2.1.4 Motivating and demotivating factors: Online shopping in Germany
2.2 Background of e-commerce in Peru
2.2.1 E-commerce context before the COVID-19 pandemic in Peru
2.2.2 E-commerce context during the COVID-19 pandemic in Peru
2.2.3 Peru's e-commerce adoption compared to other Latin American countries
2.2.4 Motivating and demotivating factors: Online shopping in Peru
2.3 Introduction to the Theoretical Frameworks
2.3.1 The Technology Acceptance Model
2.3.2 Limitations of the Technology Acceptance Model
2.3.3 Hypotheses based on the Technology Acceptance Model
2.3.4 The Theory of Planned Behavior
2.3.5 Limitations of the Theory of Planned Behavior
2.3.6 Hypotheses based on the Theory of Planned Behavior
2.4 Introduction to the intrinsic and extrinsic motivation factors
2.4.1 Perceived External Pressure (Pressure)
2.4.2 Perceived Lack of Alternatives (Alt)
2.4.3 Risk-taking Propensity (RTP)
2.4.4 Perceived Punishable Infractions (PPI)
2.4.5 Perceived Risk (Risk)
2.4.6 Government Support (Gov)
2.5 Conceptual Framework
2.6 Chapter Conclusion
3 Research Methodology
3.1 Research Design: Research Philosophy and Research Logic
3.2 Research Strategy and Data Collection Instrument
3.2.1 The Survey Method
3.2.2 Structured Online Questionnaire
3.3 Target Population Definition and Sampling Technique
3.4 Research Ethics
3.5 Pilot Studies
3.6 Methodology for Data Analysis
3.6.1 First Assessment: The Partial Least Squares-Structural Equation Model
3.6.2 PLS-SEM: Introduction to Validity Assessment in the Measurement Models
3.6.3 PLS-SEM: Convergent Validity in the Measurement Models
3.6.4 PLS-SEM: Discriminant Validity in the Measurement Models
3.6.5 PLS-SEM: Assessment in the Structural Model
3.6.6 Second Assessment: The one-way ANOVA
3.6.7 Second Assessment: Hypothesis testing using the one-way ANOVA
4 Data Analysis
4.1 Consumer Socio-demographic Findings
4.2 One-way ANOVA Findings
4.3 PLS-SEM Model: Measurement Models Findings
4.3.1 Convergent Validity Findings
4.3.2 Discriminant Validity Findings
4.4 PLS-SEM Model: Structural Model Findings
4.4.1 Collinearity Findings
4.4.2 Hypothesis Testing Findings
4.4.3 Coefficient of Determination (R2) Findings
4.4.4 Structural Model’s Effect Size (F2) Findings
4.4.5 Predictive Relevance (Q2) Findings
4.4.6 Summary of Structural Model’s Findings
5 Conclusion
5.1 Introduction: Implication & Interpretation of Findings
5.1.1 Interpretation of Significant Relationships for Peru
5.1.2 Interpretation of Non-Significant Relationships for Peru
5.1.3 Interpretation of Significant Relationships for Germany
5.1.4 Interpretation of Non-Significant Relationships for Germany
5.1.5 Interpretation of one-way ANOVA Findings for Peru and Germany
5.2 Practical Recommendations for Governments and Food Retailers
5.2.1 Recommendations for the Peruvian Government and Food Retailers
5.2.2 Recommendations for the German Government and Food Retailers
5.3 Limitations and Delimitations
5.3.1 Limitations
5.3.2 Delimitations
5.4 Recommendations for Further Research
This study investigates consumer behavior regarding online grocery shopping adoption during the COVID-19 pandemic by conducting a quantitative comparative analysis between the markets of Peru and Germany using the Technology Acceptance Model (TAM), the Theory of Planned Behavior (TPB), and situational factors.
1.1 Context and Problem Definition
Despite being a relatively new phenomenon and therefore modest compared to different product categories, online grocery shopping has seen continued growth and considerable popularity in recent years, thus capturing the great attention of consumers and retailers worldwide. Online grocery shopping is defined as the way to purchase food and other household supplies through a web-based shopping service (Driediger & Bhatiasevi, 2019). Mckinsey's (2019) research has designated online food shopping as one of the fastest-growing markets of the future. Its annual growth between 2014 and 2019 was estimated at 21% worldwide (EuroMonitor International, 2020). However, although online grocery shopping has spread rapidly, the field of consumer attitudes has not received sufficient attention (ibid.).
Despite the rapid development of online grocery shopping, current literature shows that consumer adoption of online grocery retailing has been heterogeneous and thus differs widely from country to country (Anesbury et al., 2016). This can be attributed to different consumer habits (Sreeram et al., 2017) and the convenience of online shopping (Huang & Oppewal, 2006). According to Lee et al. (2017), developed economies such as China, the United States, and the United Kingdom have been quick to support the introduction of online food shopping. On the other hand, some studies have also highlighted, for instance, that customers in some Western European countries such as Germany tend to remain loyal to brick-and-mortar retail, which contributes to slower adoption of online food retail (Internetworld, 2019; Schulz et al. 2013).
1 Introduction: Provides an overview of the research background, goals, objectives, research questions, design, and structure of the study.
2 Literature Review: Discusses theoretical foundations of consumer perception in Peru and Germany, including the Technology Acceptance Model (TAM) and Theory of Planned Behavior (TPB), as well as situational motivation factors.
3 Research Methodology: Details the research philosophy, survey strategy, target population, ethical considerations, pilot studies, and statistical methods (PLS-SEM and one-way ANOVA) used for data analysis.
4 Data Analysis: Presents findings from socio-demographic data, ANOVA tests for cultural differences, and the validation and testing of the research model using PLS-SEM.
5 Conclusion: Summarizes the major research findings, offers practical recommendations for governments and retailers in both countries, and addresses study limitations and future research directions.
Online Grocery Shopping, Consumer Behaviour, Technology Acceptance Model, Theory of Planned Behavior, COVID-19 pandemic, Peru, Germany, PLS-SEM, Quantitative Analysis, E-commerce Adoption, Situational Factors, Consumer Attitudes, Predictive Modeling, Market Comparison.
This research focuses on identifying the factors that significantly influence consumers' intention to adopt online grocery shopping in Peru and Germany during the COVID-19 pandemic.
The study examines the intersection of technology adoption models (TAM and TPB) with situational factors in the specific context of the global pandemic's impact on two distinct national markets.
The main goal is to conduct a quantitative comparative analysis to determine drivers and barriers for online grocery shopping in both countries and scientifically explain differences in adoption rates.
The author employed a quantitative cross-sectional survey strategy, utilizing Partial Least Squares-Structural Equation Modeling (PLS-SEM) for model validation and one-way ANOVA to analyze differences between the two populations.
The core chapters explore literature backgrounds for both nations, define the theoretical and conceptual frameworks, detail the methodology for statistical assessment, and present the empirical analysis of the survey data.
Essential keywords include Online Grocery Shopping, Consumer Behaviour, Technology Acceptance Model, COVID-19 pandemic, PLS-SEM, and E-commerce Adoption.
The pandemic acted as a major situational factor that forced consumers to shift from traditional shopping habits to digital channels, providing an ideal scenario for analyzing technology adoption in countries with traditionally conservative buying habits.
By comparing these two countries, the study addresses a research gap, particularly in Peru, where little scientific research existed on this topic, and provides a comparative perspective against German market trends.
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