Risk-induced competitive productivity in times of recession: a chaordic tourism decision-making perspective

Abstract

Purpose This study aims to explore the interface of competitive productivity (CP) levels in times of turbulence. Design/methodology/approach Drawing from a sample of 507 Athenian holidaymakers, the study uses 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 using necessary condition analysis (NCA). Findings fsQCA revealed three sufficient configurations: price-quality nexus (micro); generated experience (meso) and perceived destination image (macro). NCA showcased that the effect size of the examined perceived risks is relatively low, while destination risks have the highest impact. Research limitations/implications Only a few studies use 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 CP levels are still unexplored. Originality/value This is the first study examining the nonlinearity of risk-induced decision-making triggers of holidaymakers affected by the recession in line with the principles of CP. Its theoretical contribution lays in the exploration of the interface of CP and its three levels of application (micro [tourist], meso [firm/business], macro [destination]) in times of turbulence. Managerially, it strengthens the assumption that 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.

How hotels adjust technology-based strategy to respond to COVID-19 and gain competitive productivity (CP): strategic management process and dynamic capabilities

“…Therefore, outlining a multilevel study that is capable of explaining SST application from the perspectives of more stakeholders such as customers, employees, managers and even governments will be of great interest and significance. Additionally, as CP is a three-level model (micro-meso-macro) (Baumann et al, 2019;Hoadley, 2020), it would be of interest to examine the interaction among the micro (individual), meso (firm) and macro (country) levels' strategy management and the corresponding productivity and competitiveness (Pappas and Glyptou, 2021).…”

“…When unanticipated and disruptive changes (e.g. COVID-19) occur, businesses are naturally inclined to renew or update their stock of resources to achieve a novel fit within the new environment (Colombo et al, 2020;Pappas and Glyptou, 2021). COVID-19 has given rise to several changes including service innovation motivations and practices (Heinonen and Strandvik, 2020).…”

Poverty and tourism decision-making: a chaordic perspective

“…Overall, Williams and Bal až (2013) conclude that tourism decision-making is a mixture of cognitive contextual facts and affective perceptions. Evidently, causality in tourism decision-making is more complex than anticipated (Edwards and Potter, 1992;Pappas and Glyptou, 2021) as it is context-dependent and socially constructed (Smallman and Moore, 2010). It is worth noting that recent studies identify the heightened levels of uncertainty characterising global tourism as influencers on tourism decision-making (Papatheodorou and Pappas, 2017).…”

“…Tourism decision-making is fundamentally complex (Pappas, 2017; Williams and Baláž, 2013) involving several sub-decisions taken prior and during the trip (Smallman and Moore, 2010) whilst carrying a high perceived risk due to the unique characteristics of tourism products and services (Pappas and Glyptou, 2021). Numerous studies have attempted to uncover the factors shaping the tourism decision-making process, borrowing mostly from consumer behaviour models.…”

“…This analytical method was chosen to study the complexity concerning rising poverty levels in developed destinations and tourism decision-making because previous research shows that fsQCA is the most versatile method for the examination of complexity (Olya and Al-Ansi, 2018; Ordanini et al , 2014) and of chaordic systems (Pappas, 2021; Pappas and Glyptou, 2021) in tourism and hospitality. Contrary, linear analysis (e.g.…”