Research Methodology for Quality and Risk Management in Logistics

This chapter sees an appropriate approach to build a quality management model by managing the risk of nonconforming logistics activities that result from dynamic environmental changes and contingencies. Logistics management has the misconception that reducing complaints would increase satisfaction to the same extent. Models for positively influencing satisfaction should contain much more than one variable. The customer satisfaction model used in this chapter contains six latent variables: Logistics satisfaction survey; analysis of data from the survey to measure satisfaction with logistics services; chapter to analyze the risk of noncompliant processes in logistics services; survey data analysis to measure the risk of noncompliant processes in logistics services. FMEA analysis was used as a method to investigate the consequences of emerging risks by quantifying the severity, likelihood of occurrence, and detection of nonconforming logistics services that further generated the RPN. The main objective of this chapter is to define the research design and the methods of data collection and analysis