Interactive Voice Assistants for Travel Planning. Insights for Tourism Marketing Communication of Destination Management Organizations

Table of Contents

1. Introduction

1.1 Statement of the Problem

1.2 Purpose

1.3 Research Questions

1.4 Research Method

1.5 Overview of the Thesis

2. Theoretical Foundation of Marketing Communications of DMOs

2.1 Functions and Tasks of DMOs

2.2 Trends and Challenges in Destination Marketing

2.3 Experience Design in Destination Marketing

2.4 Relevance of the UX for the Experience Marketing of DMOs

2.5 Designing the UX in Travel Planning

3. Definition and Application Fields of Intelligent Voice Assistants

3.1 Definition, Application Fields and Development of IVAs

3.2 Relevance of IVAs for Marketing Communication

3.3 Information Processing in Voice Content Marketing

3.4 Use of IVAs in Tourism Context

3.5 IVAs for Consumer Use

4. Tourism-specific Consumer Behavior of Different Generations

4.1 Target Market Analysis in Destination Marketing

4.2 Demographic Change as Challenge in Tourism Marketing

4.2.1 Consumer Behavior of Best Agers

4.2.2 Consumer Behavior of Millennials

4.3 Use and Consumption of IVAs by Different Generations

5. Acceptance and Influencing Factors of IVAs for Travel Planning

5.1 Explanation of Acceptance and -Models for Technological Innovation

5.2 Acceptance Factors of IVAs in Travel Planning

5.2.1 Factors of the Technology Acceptance Model

5.2.2 Factors of the Technology Acceptance Model 2

5.2.3 Factors of the Technology Acceptance Model 3

6. Interim Conclusion of Theoretical Foundations

7. Empirical Analysis

7.1 Research Method

7.2 Sampling

7.3 Quantitative Data Collection

7.4 Data Analyzing

7.5 Analysis and Results

7.5.1 Descriptive Characteristics of the Sample

7.5.2 Results of the Acceptance Factors of IVAs for Travel Planning

7.5.3 Sample Distribution

7.5.4 Results of the Hypothesis Test

7.5.4.1 Differences in the Acceptance Factor Fun

7.5.4.2 Differences in the Acceptance Factor Computer Anxiety

7.5.4.3 Differences in the Acceptance Factor Complexity

7.5.4.4 Differences in the Acceptance Factor Output Quality

7.5.4.5 Differences in the Acceptance Factor Subjective Norm

7.5.4.6 Differences in the Acceptance Factor Perceived Ease of Use

7.5.4.7 Differences in the Acceptance Factor Perceived Usefulness

7.5.4.8 Differences in the Acceptance Factor Attitude Towards Use

7.5.4.9 Differences in the Acceptance Factor Behavioral Intention to Use

8. Conclusion

8.1 Answering the Overall Research Question

8.2 Discussion of the Results

8.3 Recommendations

8.4 Outlook

Objectives and Key Themes

This master's thesis investigates the consumer acceptance of Interactive Voice Assistants (IVAs) for travel planning, focusing on the differences between the generation of "Millennials" and "Best Agers". The core research objective is to identify critical acceptance factors that influence the intent to use these technologies, thereby providing actionable insights for Destination Management Organizations (DMOs) to integrate IVAs effectively into their marketing communications and visitor journeys.

• Technology acceptance and consumer behavior in the tourism sector.
• Comparative analysis of Millennials and Best Agers regarding technological adoption.
• Application of the Technology Acceptance Model (TAM 3) in a travel planning context.
• Strategies for designing User Experience (UX) and voice content for travel destinations.
• Empirical evaluation of factors like Perceived Usefulness, Perceived Ease of Use, and Computer Anxiety.

Excerpt from the Book

Summary of Chapters

1. Introduction: Outlines the rising importance of experience marketing in tourism and introduces the research problem regarding the integration of Interactive Voice Assistants (IVAs) within the travel planning phase.

2. Theoretical Foundation of Marketing Communications of DMOs: Examines the evolving roles of DMOs, the necessity of experience design, and the critical importance of User Experience (UX) design in modern destination marketing.

3. Definition and Application Fields of Intelligent Voice Assistants: Defines IVAs based on AI technology, explores their role in the marketing ecosystem, and presents current use cases for voice content within the tourism sector.

4. Tourism-specific Consumer Behavior of Different Generations: Analyzes the demographic shifts in tourism, focusing on the distinct behavioral characteristics, technological affinity, and travel patterns of "Best Agers" and "Millennials."

5. Acceptance and Influencing Factors of IVAs for Travel Planning: Introduces the Technology Acceptance Model (TAM 3) to build a theoretical framework for identifying factors that determine consumer willingness to adopt voice-based technologies.

6. Interim Conclusion of Theoretical Foundations: Synthesizes the literature review and provides preliminary answers to theoretical research questions regarding the intersection of technology acceptance and destination marketing.

7. Empirical Analysis: Details the quantitative survey methodology, sampling criteria, and the results of hypothesis testing regarding acceptance factors like perceived usefulness, ease of use, and anxiety among the study participants.

8. Conclusion: Summarizes the research findings, addresses the overarching research question, provides strategic recommendations for DMOs, and suggests avenues for future research.

Keywords

Interactive Voice Assistants, IVA, Destination Management Organizations, DMO, Experience Marketing, Travel Planning, Technology Acceptance Model, Millennials, Best Agers, Tourism Marketing, User Experience, UX, Artificial Intelligence, Digitalization, Consumer Behavior

Frequently Asked Questions

What is this research paper primarily about?

This thesis examines the consumer acceptance of Interactive Voice Assistants (IVAs) as a tool for travel planning, specifically focusing on the differences in behavior and attitudes between the "Millennial" and "Best Ager" generations.

What are the core topics covered in this study?

The study covers the transformation of DMO marketing, the role of Artificial Intelligence in tourism, the principles of experience design, and the application of the Technology Acceptance Model (TAM 3) to understand human-computer interaction in travel.

What is the central research question?

The research asks what differences exist between Millennials and Best Agers in the factors that influence their acceptance of Interactive Voice Assistants specifically for the purpose of planning travel.

Which scientific methods are employed?

The paper uses a quantitative research approach, utilizing a standardized questionnaire distributed to 205 participants (162 completed), with data analysis conducted via statistical methods including ANOVA and the Kruskal-Wallis test.

What does the main body address?

The main body integrates a literature review on DMO marketing and IVA technology with an empirical study that analyzes various acceptance factors like "Perceived Usefulness," "Perceived Ease of Use," and "Computer Anxiety" across different age cohorts.

Which keywords best describe this study?

The study is best characterized by terms such as Interactive Voice Assistants (IVA), DMO marketing, Technology Acceptance Model, Millennials, Best Agers, and User Experience (UX) in tourism.

How do "Best Agers" differ from "Millennials" in their interaction with IVAs?

While both groups remain cautious due to immature AI technology, Best Agers tend to value the potential time-saving and simplicity aspects of voice control more positively than Millennials, despite a higher initial skepticism toward the technology.

What is the conclusion regarding DMOs' use of IVAs?

The research concludes that while there is no immediate revolution in the travel market through IVAs, DMOs should focus on creating helpful and entertaining voice content tailored to specific search intentions rather than treating IVAs purely as a sales channel.