The article "Using advanced mixed methods approaches: Combining PLS-SEM and qualitative studies" by Fidan Kurtaliqi, Caroline Lancelot Miltgen, Giampaolo Viglia, and Gaëlle Pantin-Sohier explores the integration of PLS-SEM (Partial Least Squares Structural Equation Modeling) with qualitative methods to enhance the understanding of consumer behavior in retail contexts. The authors argue that while PLS-SEM is a robust quantitative method, it may not be sufficient on its own to fully understand complex phenomena. They propose an advanced mixed methods approach that combines exploratory and intervention designs to complement PLS-SEM results with qualitative insights. The study is divided into three main components: 1. **Exploratory Study (Study 1)**: This qualitative study uses focus groups to identify the benefits and costs associated with using shopping applications in retail stores. It also develops scale items for new constructs or adapts existing scales to the specific context. 2. **Quantitative Study (Study 2)**: This study uses PLS-SEM to test the hypotheses derived from Study 1, focusing on the antecedents of perceived value and their influence on engagement. The study employs projective techniques and a hybrid approach of perceived value, integrating both benefits and costs. 3. **Qualitative Study (Study 3)**: This final qualitative study provides fine-grained insights by complementing the quantitative findings with additional qualitative evidence, addressing ecological validity and providing context-specific insights. The authors highlight the importance of the mixed methods approach in enriching PLS-SEM results, particularly in scenarios where field access is limited. They provide a checklist for researchers to guide the integration of advanced mixed methods and PLS-SEM, emphasizing the need for a progressive and context-specific methodology. The study's findings suggest that the combined approach can help retailers develop more effective mobile apps that create customer value and engagement. The methodology is particularly useful for testing and developing retail apps in a low-risk environment, providing actionable insights for managers.The article "Using advanced mixed methods approaches: Combining PLS-SEM and qualitative studies" by Fidan Kurtaliqi, Caroline Lancelot Miltgen, Giampaolo Viglia, and Gaëlle Pantin-Sohier explores the integration of PLS-SEM (Partial Least Squares Structural Equation Modeling) with qualitative methods to enhance the understanding of consumer behavior in retail contexts. The authors argue that while PLS-SEM is a robust quantitative method, it may not be sufficient on its own to fully understand complex phenomena. They propose an advanced mixed methods approach that combines exploratory and intervention designs to complement PLS-SEM results with qualitative insights. The study is divided into three main components: 1. **Exploratory Study (Study 1)**: This qualitative study uses focus groups to identify the benefits and costs associated with using shopping applications in retail stores. It also develops scale items for new constructs or adapts existing scales to the specific context. 2. **Quantitative Study (Study 2)**: This study uses PLS-SEM to test the hypotheses derived from Study 1, focusing on the antecedents of perceived value and their influence on engagement. The study employs projective techniques and a hybrid approach of perceived value, integrating both benefits and costs. 3. **Qualitative Study (Study 3)**: This final qualitative study provides fine-grained insights by complementing the quantitative findings with additional qualitative evidence, addressing ecological validity and providing context-specific insights. The authors highlight the importance of the mixed methods approach in enriching PLS-SEM results, particularly in scenarios where field access is limited. They provide a checklist for researchers to guide the integration of advanced mixed methods and PLS-SEM, emphasizing the need for a progressive and context-specific methodology. The study's findings suggest that the combined approach can help retailers develop more effective mobile apps that create customer value and engagement. The methodology is particularly useful for testing and developing retail apps in a low-risk environment, providing actionable insights for managers.