Consumer Behavior on Online Grocery Shopping Adoption. A Quantitative Analysis in the Context of the COVID-19 Pandemic, Contrasting the Markets of Peru and Germany

Table of Contents

• 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

Objectives and Key Themes

This research aims to analyze the factors influencing the intention to adopt online grocery shopping in both Germany and Peru. The study investigates the impact of cultural context on consumer behavior in the face of the COVID-19 pandemic, given the limited attention this aspect has received in previous studies. The research seeks to identify both common and distinct factors driving adoption in these two countries.

• Influence of cultural context on consumer behavior
• Factors affecting adoption of online grocery shopping
• Comparison of online grocery shopping adoption in Germany and Peru
• Role of the Technology Acceptance Model and Theory of Planned Behavior
• Impact of situational factors related to the COVID-19 pandemic

Chapter Summaries

The introductory chapter sets the context and defines the problem, outlining the research aim, objectives, questions, design, and structure. Chapter 2 presents a thorough literature review, examining the background of e-commerce in both Germany and Peru, including its context before and during the COVID-19 pandemic. The chapter also explores the e-commerce adoption rates in comparison to other countries and identifies motivating and demotivating factors for online shopping in both contexts. It introduces the theoretical frameworks, including the Technology Acceptance Model and the Theory of Planned Behavior, highlighting their limitations and formulating hypotheses. The chapter then introduces intrinsic and extrinsic motivation factors related to online grocery shopping, including Perceived External Pressure, Perceived Lack of Alternatives, Risk-taking Propensity, Perceived Punishable Infractions, Perceived Risk, and Government Support. The chapter concludes by presenting a conceptual framework that integrates these factors and theoretical models.

Chapter 3 delves into the research methodology, outlining the research design, strategy, and data collection instrument. It describes the survey method and structured online questionnaire used for data collection. The chapter also defines the target population, sampling technique, and research ethics. Finally, it outlines the methodology for data analysis, including the Partial Least Squares-Structural Equation Model (PLS-SEM) and one-way ANOVA.

Chapter 4 presents a comprehensive analysis of the collected data, including consumer socio-demographic findings and results from the one-way ANOVA test. The chapter further analyzes the PLS-SEM model, presenting findings for both measurement and structural models, including convergent validity, discriminant validity, collinearity, hypothesis testing, coefficient of determination (R²), effect size (F²), and predictive relevance (Q²).

Keywords

The main keywords and focus topics of this research include online grocery shopping, consumer behavior, Technology Acceptance Model (TAM), Theory of Planned Behavior (TPB), cultural context, COVID-19 pandemic, Germany, Peru, e-commerce adoption, situational factors, data analysis, PLS-SEM, one-way ANOVA, and predictive relevance.