The use of smart phones has changed the lifestyle of the society. Almost all kind of useful tools you can find on your smart phone. People used to buy goods every day. And for the purchase of goods they must pay. Security is very important while payment is concern. In this thesis we have designed and demonstrated a mobile phone application that can be used for a small shop or a big market. For any kind of commerce application, three different kind of entities are mostly involved: the customer, the sales person, and the management of the shop. Our designed mobile application has three different interfaces for three different kind of users: Manager Interface, Employee Interface, and Customer Interface. An interface for the system administrator is also designed, which should be used as an desktop application on the point of sale server. This application is flexible with capabilities of different payment options. Our proposed design can be implemented in any smart phone environment for example Android, iOS or Windows phone. This design provides availability, confidentiality, and integrity of payment data.

Background: Emerging in December 2019, the COVID-19 pandemic profoundly changed consumer behaviour leading to social distancing and mitigating physical contact. Statistics show an increased use of contactless and mobile payment usage and adoption during the pandemic. It is unclear how valid previous models on mobile payment adoption explain adoption behaviour in emergency situations. While there are few studies approaching the adoption behaviour during the pandemic, there is also little previous research on mobile payment adoption prior to the pandemic in Germany. Purpose: The present thesis intends to advance several previously researched technological adoption frameworks to focus on and measure consumers’ perception of mobile payment technology adopting during the COVID-19 pandemic. Hence, our model provides a basis to understand mobile payment adoption in Germany during the pandemic. Method: Based on hypotheses derived from an adapted UTAUT2 model, we conducted quantitative deductive research reaching 258 questionnaire participants based in Germany. The empirical data was analysed through structural equation modelling. Conclusion: The findings show that Performance Expectancy still represents the primary driver of intention to adopt mobile payments during the pandemic, yet it is strongly supported by the initially contextualised Contamination Avoidance element and complemented by Habit, Effort Expectancy. Practitioners benefit from the study to better tailor campaigns in accordance with the main driver of adoption behaviour, while our findings contribute new insights into technology adoption in Germany during emergency situations.