Fachbuch, 2018
146 Seiten
1 Introduction
2 Theoretical Foundation and Literature Review
2.1 Definition and Classification of Dynamic Pricing
2.2 Literature Review
2.3 Identified Research Gap
3 Derivation of Hypotheses and Conceptual Model
3.1 Consumer Reactions on Dynamic Pricing
3.2 Status-based Dynamic Pricing
3.3 Influence Factors on Price Fairness Perception
3.4 Consumer Reactions on Price Fairness Perception
3.5 Control Variable
3.6 Conceptual Model
4 Design of Empirical Study
4.1 Survey Method
4.2 Survey Scenarios
4.3 Survey Items
5 Data Analysis and Results
5.1 Survey Sample
5.2 Measurement Reliability
5.3 Hypotheses Testing
5.4 Further Analyses
6 Concluding Discussion
6.1 Discussion of Results
6.2 Managerial Implications
6.3 Limitations and Further Research
This thesis examines how different customer status groups (new vs. existing) react to status-based dynamic pricing in e-commerce, specifically investigating the impact of price fairness perception on repurchase intention and the role of various moderating factors.
1 Introduction
During the last decade, companies had to set their strategic focus on digital transformation in order to fulfill the market’s need. It is nowadays almost inevitable for firms to digitize their corporate infrastructure, processes, products and services in order to increase market segment share (Bharadwaj et al. 2013).
According to the Global Pricing Study 2016 of Simon-Kucher & Partners, 60% of the participating companies see the growing online business as a significant opportunity to increase their sales. However, also 60% of the companies perceive the digitization as a threat to their prices and margin.
To address this threat, 40% of German companies vary their prices dynamically on the Internet and the trend is ongoing (Kohn 2017; Wenk-Fischer and Zirbes 2016). Dynamic pricing in the online environment is a strategic pricing tool, in which businesses flexible adapt their prices based on algorithms over time, across customer segments or depending on supply and demand (Haws and Bearden 2006; Krämer and Kalka 2017, p. 92). It is recognized as a possibility for companies to exploit the consumers’ maximum willingness to pay (WTP) (Grewal et al. 2011) resulting in an overall increase in the companies’ profits (Elmaghraby and Keskinocak 2003; Kohn 2017; Sahay 2007). Studies confirm those findings and state that companies which use dynamic pricing tools were able to reach 27% higher profits as the competition (Global Pricing Study 2016).
1 Introduction: Discusses the growing importance of digital transformation and the strategic role of dynamic pricing, while highlighting the potential for consumer dissatisfaction and the research focus on status-based pricing.
2 Theoretical Foundation and Literature Review: Provides a comprehensive overview of dynamic pricing definitions, explores behavioral price research, and identifies gaps concerning the influence of customer status and relationship factors.
3 Derivation of Hypotheses and Conceptual Model: Utilizes equity theory to develop hypotheses regarding consumer reactions to dynamic pricing and presents a conceptual model with various moderating variables.
4 Design of Empirical Study: Outlines the methodology of the web-based survey, including the experimental design of the eight scenarios and the selection of survey items.
5 Data Analysis and Results: Details the statistical evaluation of the gathered survey data, testing the hypotheses through ANOVA, regression, and mediation analyses.
6 Concluding Discussion: Interprets the findings in relation to marketing literature, discusses managerial implications, and identifies limitations and directions for future research.
Dynamic Pricing, Status-based Dynamic Pricing, Online Business, Price Fairness Perception, Repurchase Intention, Equity Theory, Consumer Behavior, E-Commerce, Prior Trust, Relationship Quality, Price Sensitivity, Norm Belief, Prior Experience, Consumer Status, Digitalization
The research focuses on the impact of status-based dynamic pricing on consumer behavior, specifically examining how new versus existing customers perceive price fairness and how this affects their intention to repurchase.
Key themes include dynamic pricing strategies, the influence of relationship quality and prior trust on price fairness, the role of individual consumer characteristics, and the mediating role of perceived price fairness on repurchase intention.
The aim is to investigate how new and existing customers react to status-based dynamic pricing techniques to provide e-commerce managers with insights on how to adapt their pricing strategies while minimizing negative consumer reactions.
The study utilizes a web-based empirical survey with a 2 x 2 x 2 between-subjects design. Data analysis includes ANOVA, ordinary least squares (OLS) regression, and mediation analysis using the PROCESS tool.
The work covers theoretical foundations (equity theory), develops a conceptual model with various moderators (relationship quality, prior trust, norm belief, etc.), describes an empirical experimental study, and analyzes the results to offer managerial implications.
Core keywords include Dynamic Pricing, Price Fairness, Repurchase Intention, Consumer Behavior, Equity Theory, and E-Commerce.
The study finds that new customers perceive higher price fairness and demonstrate higher repurchase intentions compared to existing customers when subjected to status-based dynamic pricing.
Based on the data analysis conducted, the study could not confirm a significant moderating effect of relationship quality (friend vs. stranger) on the relationship between dynamic pricing and price fairness perception.
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