Analyzing hospitality leader–follower dyads with polynomial regression: a critical reflection

Purpose Congruence serves as a key framework in many leader–follower dyad theories. This paper aims to introduce polynomial regression analysis with response surface methodology (PRA with RSM) as a statistical technique for investigating research questions concerning leader–follower dyadic relationships in the hospitality context. Design/methodology/approach First, this paper illustrates the necessity of applying PRA with RSM to more effectively address the research issues related to leader–follower dyadic relationships. Next, this paper presents an overview and the key concepts of PRA with RSM. Critical issues that need to be noted and two recent hospitality leadership studies that have used PRA with RSM are discussed. Third, an empirical example in the hotel context is provided to illustrate the application of PRA with RSM. Findings By applying this methodology to the study of hospitality leader–follower dyadic relationships, researchers will be able to address a range of topics related to dyadic theory, such as leader–member exchange and value congruence. Practical implications PRA with RSM reveals that congruence effects vary within leader–follower dyads. Industry professionals can promote a better leader–follower fit by incorporating dyadic surveys to understand mutual agreement and perceptions regarding same-workplace phenomena. Originality/value The paper addresses the misalignment between leader–follower dyadic theory and the methodology used in hospitality leadership studies.