
Business
Resilience and individual competitive productivity: the role of age in the tourism industry
D. R. Toubes, N. Araújo-vila, et al.
This study explores the intriguing link between individual resilience and Competitive Productivity in the tourism industry, emphasizing how age plays a crucial role. Conducted by Diego R. Toubes, Noelia Araújo-Vila, Arthur Filipe de Araújo, and José Antonio Fraiz-Brea, the research highlights the importance of diverse recruitment policies, enhancing organizational resilience during challenging times like the COVID-19 crisis.
~3 min • Beginner • English
Introduction
The study investigates how individual resilience relates to Individual Competitive Productivity (ICP) and explores age as an influence variable on individual resilience within the tourism industry. Organisational resilience supports adaptation to changing environments and is positively associated with organisational effectiveness. Prior research acknowledges a positive relationship between organisational resilience and employee resilience, but the influence of employee resilience on business competitiveness is underexplored. Building on the concept of competitive productivity (an attitude and behaviour to outperform competition through pragmatism) and core resilience characteristics (flexibility, rapid shifting, recognition and adaptation to unanticipated events), the study proposes and tests a set of items operationalising personal resilience and examines their correspondence with ICP components. Data were collected during the COVID-19 crisis, an apt context given resilience’s focus on responding to change. The goals are to identify dimensions of individual resilience, test their links to ICP, and assess age-related differences to inform recruitment and talent strategies that enhance organisational ambidexterity and resilience.
Literature Review
Theoretical framework connects individual resilience and ICP. Resilience is the capacity to respond, learn, adapt, and thrive amid change; resilient systems absorb disturbances and self-organise. In organisations, employee resilience contributes to adaptive, learning, and network-leveraging behaviours that strengthen organisational resilience and can improve job performance and timing advantages. People and their skills are central to competitiveness, making HR practices critical to building resilience capacity. Organisational resilience and recruitment: Talent management that develops resilience improves well-being and performance; personal development emphasis can be beneficial. Ambidexterity (simultaneously pursuing exploration and exploitation) enhances performance but is challenging; personnel characteristics and recruitment, including inclusion of young employees in decision-making, can support ambidexterity by bringing market-proximate insights and creative actions, while senior experience contributes stability. Tourism industry context: Tourism is highly vulnerable to crises due to mobility restrictions, image and risk perceptions, perishability of services, seasonality, and high fixed costs. Prior studies in tourism highlight planning for change and broad participation as key to resilience, and advocate a greater role for destination management organisations in promoting knowledge management for SMEs. The present study posits a close connection between ICP and individual resilience, and explores age as a proxy for life experience within ICP’s drivers.
Methodology
Design: Quantitative survey during the COVID-19 pandemic to measure individual resilience at work among tourism professionals and students in Spain. Construct basis: Adapted indicators from organisational resilience scales (Lee et al., 2013; Orchiston et al., 2016) to an individual-level tourism work context, aligning with ICP components (Baumann et al., 2019). Two ICP statements about competitive versus collaborative attitude (in normal and crisis conditions) were added; a stress-testing item was also included for theoretical reasons. Instrument: 13 resilience items rated on a 5-point Likert scale (1=strongly disagree to 5=strongly agree) plus an 'I don't know' option; two 9-point bipolar items for competitive vs collaborative attitude (normal and crisis). Sociodemographics included sex, age, education, profession, and country. Pre-test with 12 respondents ensured conceptual validity. Sampling and data collection: Spain; initial database of current and former tourism students from Universidade de Vigo supplemented via non-probabilistic snowball sampling. Fieldwork from May 20 to July 10, 2020. Inclusion required a professional or educational link to tourism. Final valid sample n=425. Analysis: Exploratory factor analysis (EFA) to identify underlying dimensions of individual resilience; listwise deletion for missing values yielded n=381 for EFA. Correlations mostly 0.458–0.658; adjusted p-values (Holm) <0.01; KMO=0.754 indicating adequacy. Varimax rotation; factors retained if SS loadings >1; item loadings threshold >0.5. Reliability assessed via Cronbach’s alpha. Subsequently, two-sample Z-tests assessed mean differences across three age groups: juniors 17–28 (n=136), mid-career 29–39 (n=181), seniors 40–53 (n=65).
Key Findings
Reliability and factor structure: Cronbach’s alpha for the 13-item construct was 0.92, indicating strong internal consistency. Two factors with SS loadings >1 were identified (SS=3.87 and 3.65), explaining 57.8% of variance. Factor 1 (Openness & Ideals) comprised leveraging knowledge, breaking silos, strategic partnerships, unity of purpose, staff engagement, situation awareness. Factor 2 (Competencies) comprised decision-making, planning strategies, leadership, internal resources, proactive posture. Innovation and creativity showed low communality (~0.47); stress-test planning had high uniqueness (0.734) and was poorly explained by the model; leveraging knowledge had low uniqueness (0.116) and high communality; model p-value near 0 suggested more than two factors may be needed for a complete explanation. Age differences: Z-tests (p<0.05) showed significant differences between seniors and mid-career across all resilience items except innovation and creativity; significant differences between juniors and mid-career except innovation and creativity, planning strategies, and breaking silos; between juniors and seniors, only planning strategies differed significantly (p<0.05). Means by indicator and age group (scale 1–5): Seniors had the highest values on all indicators except leveraging knowledge; juniors had the highest score on leveraging knowledge; mid-career group had the lowest values across indicators. Within each age group, indicators in Openness & Ideals scored higher than those in Competencies, most pronounced among juniors. Competitive vs collaborative attitudes (9-point scale; higher = more collaborative): Overall collaborative attitudes dominated in normal conditions (M=7.17, SD=1.87) and crisis (M=7.69, SD=1.58). By age, all three groups showed more collaborative than competitive attitudes in both contexts. Highly competitive attitudes (1–3) were reported by 1.5–7.3% across groups. Proportion highly collaborative (6–9 points): juniors 71.6% normal, 79.4% crisis; mid-career 77.1% normal, 89.3% crisis; seniors 60.0% normal, 78.5% crisis, indicating seniors comparatively more inclined to competition than other groups. ICP–resilience correspondence: Conceptual and measurement correspondences were observed between ICP components (e.g., benchmarking, culture, education/development, environment, performance, values) and resilience indicators (e.g., leadership, breaking silos, innovation and creativity, unity of purpose).
Discussion
Findings in a crisis context (COVID-19) underscore that context moderates ICP-related components. Older respondents exhibited greater resilience and a higher inclination toward competitive attitudes, while juniors excelled in leveraging knowledge and showed stronger collaborative orientations. The two-factor structure suggests a distinction between internal/psychological dimensions (Openness & Ideals) and operational skills (Competencies). Unlike organisational-level adaptive vs planning resilience, individual-level factors clustered into social–ideational and operational competencies. HR implications: Talent management should deliberately build personal resilience, especially operational competencies which were comparatively weaker across all groups. Diversity in recruitment and empowerment across junior and senior levels can foster integrative thinking and organisational ambidexterity, improving performance in both mature and emerging market conditions. Aligning HR practices to enhance employee resilience can strengthen organisational resilience, enabling faster responses, resourcefulness, and better utilisation of capabilities. Tourism-specific implications highlight the need for resilience due to heightened exposure to crises; building resilient individuals contributes to organisational continuity and competitiveness during disruptions.
Conclusion
The study provides evidence of close conceptual and metrical alignment between individual resilience and the ICP model. An individual resilience scale adapted for tourism work identified two underlying dimensions: Openness & Ideals (solidarity, communication, collaboration, networking, priority setting) and Competencies (decision-making, response capability, leadership, control, preparedness). Using age as a proxy for life experience, older individuals demonstrated higher resilience levels and more competitive attitudes in both normal and crisis conditions, while juniors were notably strong in knowledge leveraging and collaboration. Managerially, organisations should enhance operational resilience competencies across all employees and design recruitment policies that balance young talent with experienced staff to promote diversity of perspectives and ambidexterity. Strengthening individual resilience can bolster organisational resilience and competitive advantage, which is particularly critical in tourism during crises. Future research should refine the factor structure of individual resilience, incorporate objective productivity measures, consider additional experience-related variables, and test generalisability across different crisis types and non-crisis conditions.
Limitations
Sample heterogeneity (professionals and students) may affect generalisability. Data were collected during the disruptive COVID-19 crisis, potentially biasing reported behaviours and attitudes toward immediate survival concerns. Age was the sole proxy for life experience; other relevant variables (managerial level, tenure inside and outside the organisation) were not included. The study did not incorporate objective productivity metrics alongside perceptions. Results may be context dependent; further studies across different crisis intensities and in normal conditions are recommended.
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