Abstract

Purpose: The study explores the interface of Competitive Productivity (CP) levels in times of turbulence.

Methodology: Drawing from a sample of 507 Athenian holidaymakers, the study employs a fuzzy-set Qualitative Comparative Analysis (fsQCA) to examine the chaordic systems amongst perceived risks (social; destination; price; quality) in tourism purchasing intentions. It considers three grouping variables (age; monthly income; trip [domestic; overseas]). It further evaluates the effect sizes of those risks upon purchasing intentions by complementary employing Necessary Condition Analysis (NCA).

Findings: fsQCA revealed three sufficient configurations: (i) price-quality nexus (micro) (ii) generated experience (meso) and (iii) perceived destination image (macro). NCA showcased that the effect size of the examined perceived risks is relatively low, whilst destination risks have the highest impact.

Implications: Only a few studies employ fsQCA and NCA in the field of tourism and hospitality studies thus, their full potential and implications of exploring the interface of tourism decision-making components with Competitive Productivity (CP) levels is still unexplored.

Originality: This is the first study examining the nonlinearity of risk-induced decision-making triggers of holidaymakers affected by recession in line with the principles of Competitive Productivity (CP). Its theoretical contribution lays in the exploration of the interface of Competitive Productivity (CP) and its three levels of application (microtourist, meso firm/business , macro destination) in times of turbulence. Managerially, it strengthens the assumption that Competitive Productivity (CP) and customer loyalty are strongly associated even in times of turbulence when destinations and firms should make a strong point to maintain their competitive edge. Methodologically, the study highlights the value of fsQCA for identifying multiple pathways, a relatively new method in tourism. Furthermore, it introduces NCA, a new complementary method in tourism research.