How Cultural Tourism Itineraries Shape Tourist Guide Satisfaction and Retention

Abstract

Tourist guides remain understudied in tourism workforce research, particularly regarding the conditions shaping satisfaction and career retention. This study examines how cultural tourism itinerary characteristics are associated with tourist guides’ job satisfaction and career retention intentions. Data were collected through a convenience sample survey of 127 active tourist guides in Portugal. Grounded in the Job Satisfaction Survey and the Theory of Planned Behaviour frameworks, the study utilised exploratory factor analysis and multiple linear regression to analyse the data. Results indicate positive associations between itinerary characteristics, job satisfaction and career retention intentions, with Components (accommodation, meals, accessibility) and Sustainability emerging as the strongest predictors. These findings extend the Job Demands–Resources model to a supervisory-free work context and highlight itinerary design as a previously underexplored human resource management mechanism shaping workforce outcomes in tourism, with implications for tour operators, destination managers and policymakers.

1. Introduction

In addition to their interpretative and communicative functions, tourist guides can be understood as cultural mediators who actively construct and frame the narratives through which destinations are experienced (EylülKoç & Ulema, 2024). Rather than merely transmitting information, they negotiate meanings, selectively emphasising aspects of history, identity and heritage in ways that resonate with diverse audiences (Huang et al., 2015). Through this process of storytelling and real-time interaction, tourist guides influence not only visitors’ perceptions of a destination but also the depth and authenticity of the tourism experience itself (Ninpradith et al., 2018).

Cultural tourism has grown into one of the most economically and socio-culturally significant segments of the global tourism industry (Bayram, 2020; Organisation for Economic Co-Operation and Development, 2022). However, tourism scholarship has historically centred the visitor, focusing on satisfaction, behaviour and destination choice, while leaving the workforce that delivers these experiences comparatively undertheorised (Philips, 2024; Weiler & Black, 2014). This imbalance is consequential: tourist guides, who are primarily responsible for the quality of cultural tourism experiences, remain among the least studied professional groups in the field (Akgunduz & Eser, 2022; Ertan & Çeşmeci, 2025; Ladkin et al., 2023), and the operational conditions shaping their professional experience have received limited empirical attention.

Three concepts are central to this study. Cultural tourism refers to forms of tourism motivated by the desire to engage with the tangible and intangible cultural heritage of a destination, including its history, architecture, traditions and living culture (United Nations Tourism Organisation, 2017). Itinerary design refers to the structured planning of touristic routes and experiences, encompassing decisions about points of interest, sequencing, timing, logistics and cultural content (González-Navasa et al., 2023; Rutledge, 2023). Job satisfaction, understood here as tourist guides’ evaluative response to the characteristics of their work (Spector, 1985, 1997), is treated in this study not as a global attitudinal outcome but as a construct specifically anchored in tourist guides’ perceptual evaluation of the itineraries they are required to deliver. These three concepts intersect in a way that tourism research has not yet examined systematically: itinerary design represents both a visitor experience instrument and a structural work design condition. Consequently, it determines not only tourist encounters but also the operational requirements imposed on tourist guides, including their professional autonomy, experienced meaningfulness, and daily operational burden.

Itinerary design has been studied almost exclusively from the visitor’s perspective, as a tool for optimising tourist experience, satisfaction and destination competitiveness. Its implications for the professionals who deliver it have been largely overlooked, despite the fact that the characteristics of an itinerary, its pace, its cultural depth, its logistical quality, its sustainability orientation, directly determine what tourist guides are asked to do, under what conditions and with what degree of professional autonomy and support. A key structural condition shaping this professional experience, namely the design of the cultural itineraries that tourist guides are required to deliver, has received limited direct theoretical attention as an integrated construct in relation to job satisfaction or career retention. While adjacent fields such as service design, experience economy and tourism operations research have examined aspects of experience orchestration, service delivery design and operational coordination, none has explicitly conceptualised itinerary design as a work design resource for tourism professionals, nor tested its relationship with individual-level professional outcomes. Critically, no previous study has operationalised itinerary characteristics as a formative construct comprising distinct operational dimensions, ranging from points of interest and time management to budget, accessibility and sustainability, and examined their combined predictive value for tourist guides’ satisfaction and retention decisions. This study addresses that gap by doing precisely that, extending the JD-R model (Bakker et al., 2023), the Theory of Planned Behaviour (TPB, Ajzen, 1985, 1991) and job satisfaction theory (Spector, 1985, 1997) into an operational domain where none has been previously applied in an integrated manner (Nascimento et al., 2023; Rutledge, 2023). The central research question is: to what extent are the characteristics of cultural tourism itineraries associated with tourist guides’ job satisfaction and career retention intentions?

Accordingly, the general objective of this research is to analyse the associationbetween cultural tourism itinerary characteristics and tourist guides’ job satisfaction and career retention. More specifically, the study aims to (i) assess the association of itinerary characteristics with tourist guides’ job satisfaction; (ii) examine the relationship between itinerary characteristics and career retention; and (iii) examine the association between job satisfaction and career retention intentions among tourist guides. In doing so, the study makes three distinct contributions. Theoretically, it introduces itinerary characteristics as a formative work design construct in tourism and operationalises job satisfaction not as a global attitudinal measure but as tourist guides’ perceptual evaluation of specific itinerary dimensions, an approach that allows the study to identify which components of itinerary design carry the greatest weight for professional outcomes extending the JD-R model into a previously unexamined operational context. Empirically, it provides the first integrated test of the chain linking itinerary design to job satisfaction and career retention in tourist guiding. Practically, it generates actionable evidence for tourism operators and professional associations seeking to improve workforce sustainability through itinerary design, an instrument they already control.

2. Literature Review

2.1. Cultural Tourism and Cultural Tourism Itineraries

Tourist guides are essential actors within the tourism industry, serving as the primary interface between destinations and visitors. They play a critical role in shaping overall impressions, visitor satisfaction and cultural understanding of a location (Plecha, 2020; Yi & Yun, 2024). Beyond logistical coordination, tourist guides are expected to provide informative and engaging interpretation of cultural, historical and environmental features, often tailoring their communication to different languages, cultural contexts and visitor profiles (Ap & Wong, 2001; Laosrirattanachai & Laosrirattanachai, 2021). In doing so, they act as educators, ambassadors, facilitators and hosts, co-creating experiences that inspire, inform and encourage repeat visitation (Pond, 1993). According to the World Federation of Tourist Guide Associations (2024), a professional tourist guide is “a person who guides visitors in the language of their choice and interprets the cultural and natural heritage of an area, usually possessing an area-specific qualification issued or recognised by the appropriate authority”.

Despite their pivotal role, the professional experiences of tourist guides have received remarkably little systematic attention. Huang et al. (2010), Scherle and Kung (2010) and Zhao and Timothy (2017) all note the scarcity of research on working conditions and career well-being in this group, a gap that Melia and Rice (2012) attribute in part to the structural precarity of the profession itself: seasonality, part-time contracts, and variable working conditions that make longitudinal study difficult and retention chronically unstable (Irish Tourism Industry Confederation [ITIC], 2008). Furthermore, the work environment of tourist guides can exert significant psychological pressure, with certain job characteristics contributing to stress or burnout (Yetgin & Benligiray, 2019). Constant adaptation to fluctuating tourist numbers, cultural and educational diversity and evolving visitor expectations underscores the dynamic nature of their work (Kapa et al., 2023; Tribe & Lewis, 2003).

Itinerary characteristics directly structure tourist guides’ daily activities, determining their interpretive workload, degree of autonomy, emotional demands and operational complexity (Rutledge, 2023). Nevertheless, a professional career remains viable for those who adapt to the dynamic and evolving demands of the industry, combining interpersonal skills, cultural knowledge and operational competence to meet diverse tourist expectations (Calvo, 2010; Cheong & Miller, 2000; Zammit, 2020). Understanding how itinerary design shapes tourist guides’ professional experience is therefore a critical, yet insufficiently examined, question with direct implications for job satisfaction and career retention in the profession.

Recent contributions in heritage tourism research further contextualise this gap by highlighting the growing complexity of operational planning and management in culturally rich destinations. Nag and Mishra (2023, 2024a, 2024b, 2024c, 2024d) examine the structural determinants of heritage site competitiveness, demonstrating how the governance of tourism experiences, including the design of heritage routes and the management of stakeholder expectations, shapes both visitor outcomes and the conditions under which tourism professionals operate. Extending this line of inquiry to the intersection of digital innovation and destination management, Nag and Rathore (2025) show how organisational frameworks mediating the relationship between technological systems and on-the-ground tourism delivery are becoming increasingly consequential for professional practice. Together, these studies reinforce the argument that operational design is not merely a visitor experience concern but a structural determinant of professional conditions in heritage tourism, lending further support to the examination of itinerary characteristics as a key factor shaping tourist guides’ working experience. However, these contributions stop short of examining the professional implications of itinerary design at the individual level, leaving unanswered how specific operational characteristics translate into tourist guides’ experienced satisfaction or retention decisions.

Characteristics of Cultural Tourism Itineraries

Tourism itineraries are structured plans that combine touristic products and points of interest, considering the most significant attractions, available time, distances and costs (González-Navasa et al., 2023; Ruiz-Meza & Montoya-Torres, 2022). In cultural tourism contexts, itinerary design assumes a central role in structuring the professional activities and responsibilities of tourist guides, directly shaping their daily work experience in terms of workload, autonomy, interpretive demands and operational complexity (Rutledge, 2023).

Beyond tourism studies, related insights can be found in work design, service systems and service operations literature. Research on work design highlights how task structure, autonomy and workload distribution shape employee motivation and well-being (Hackman & Oldham, 1976; Bakker & Demerouti, 2017). Similarly, service operations and service design literature emphasise the importance of orchestrating customer journeys and service encounters in ways that balance efficiency with employee experience. The experience economy literature further underscores how value creation depends on the design of staged experiences, where frontline employees play a central role in delivery. However, these strands of literature have not been systematically integrated with the specific operational realities of tourist guiding or itinerary execution.

The literature identifies fourteen key characteristics that collectively define the design and implementation of cultural tourism itineraries, each discussed below from the perspective of their implications for tourist guides’ work. These characteristics can be summarised as follows: (1) Points of Interest (POI); (2) Diversity of attractions; (3) Cultural integration; (4) Interaction with the territory; (5) Personalisation; (6) Technology; (7) Time management; (8) Schedule flexibility; (9) Budget; (10) Transportation; (11) Accommodation; (12) Meals; (13) Accessibility; and (14) Sustainability.

POI are the primary structural component of any cultural itinerary. How they are selected and ordered shapes the interpretive demands placed on the tourist guide (including the depth of knowledge required, the rhythm of the tour and the cognitive load sustained across the working day) (Padia et al., 2019; Sarkar & Majumder, 2021; Taylor et al., 2018). A coherent POI sequence gives the tourist guide a manageable interpretive thread to follow; a poorly assembled one compounds navigational and logistical pressure in ways that compound throughout the tour (Lim et al., 2019; Yoon et al., 2010).

Itineraries that mix cultural, historical, natural and recreational sites make broader demands on the tourist guide’s interpretive range (Huang et al., 2015; Kapa et al., 2023). This diversity is professionally stimulating, which introduces the task variety that the JD-R model literature identifies as a job resource, but it also raises the preparation burden. A tourist guide moving between a Roman ruin and a contemporary art space in the same afternoon is managing not just content but register, audience expectation and interpretive mode simultaneously.

Among the characteristics examined, cultural integration stands out as particularly consequential for how tourist guides experience their work. When an itinerary is genuinely embedded in local heritage, traditions and community life, it gives the tourist guide substantive material to interpret (not just sites to describe) and reinforces the sense of acting as a cultural mediator rather than a logistics manager (Scherle & Kung, 2010; Huang et al., 2015; Zammit, 2020). Closely related, the interaction with the territory extends this dimension by embedding the itinerary within the social and economic fabric of the host community, enabling tourist guides to act as genuine mediators between visitors and local culture rather than mere logistical coordinators (Bayram, 2020; Scherle & Kung, 2010; Zammit, 2020).

Personalisation introduces a layer of complexity that is difficult to standardise. When tourists arrive with divergent interests, varying budgets and compressed schedules, the tourist guide must continuously recalibrate: adjusting interpretation, pace and communication style in real time (Halder et al., 2024; Padia et al., 2019). To a moderate extent, this demands creativity and reinforces professional agency. However, when personalization becomes excessive, the absence of a stable operational framework transforms this job resource into a prominent job demand, potentially decreasing job satisfaction and escalating professional stress (Bakker et al., 2023).

Technology is reshaping how itineraries are managed and delivered, but its effects on tourist guides are uneven. Digital platforms and AI-assisted tools can reduce logistical uncertainty and freetourist guides to focus on interpretation (Ivanov & Webster, 2019). In practice, however, adoption is often uneven, as tourist guides who received their professional training before the current wave of digital tools may find new requirements disorienting rather than enabling. The critical variable is not technology per se but whether its introduction is accompanied by adequate support (Padia et al., 2019). Without it, what was designed as a resource functions as an additional demand.

If there is one characteristic that tourist guides consistently identify as a source of daily strain, it is time. Itineraries lacking adequate buffers between scheduled activities, unrealistic travel estimates, or inadequate visiting time at key sites impose severe operational constraints on tourist guides. Under these conditions, guides must simultaneously maintain group engagement and continuously recalibrate schedules to mitigate upstream planning deficiencies (Lim et al., 2019; Taylor et al., 2018; Yoon et al., 2010). Schedule flexibility works in the opposite direction: when tourist guides have sufficient temporal flexibility to accommodate an unexpected delay or extend a conversation that is genuinely engaging the group, they can exercise professional judgement rather than simply execute a timetable (Akkuş & Arslan, 2023; Rutledge, 2023).

Budget constraints create a specific form of professional discomfort that is relational as much as operational. When planned activities cannot be delivered because financial allocations were unrealistic from the outset, it is the tourist guide, who acts as the primary frontline representative absorbs tourist frustration (Baizal et al., 2018; Ruiz-Meza & Montoya-Torres, 2022). Adequate budget planning removes this source of interpersonal strain and allows the tourist guide to focus on the work itself.

Transportation, accommodation and meals constitute the logistical infrastructure within which interpretation takes place. When any of these elements is poorly coordinated—delayed coaches, inaccessible sites, inadequate meal arrangements—the guide is repositioned from cultural interpreter to complaint manager, absorbing visitor frustration generated by planning failures that originated upstream (González-Navasa et al., 2023; Kapa et al., 2023; Rizzo et al., 2015). Accessibility gaps compound this further, requiring real-time improvisation for visitors with mobility limitations. While seamless logistical execution remains unobserved within daily routines, operational failures systematically shift the burden of conflict resolution and tourist dissatisfaction directly onto the guide.

Sustainability is the most recent addition to the itinerary design literature, but its professional implications for tourist guides are highly significant. Tourist guides who see themselves as cultural and environmental mediators, as many do, find that itineraries incorporating eco-friendly transport, community-based experiences and responsible practices give their work a dimension of social contribution that purely logistical itineraries do not (Cardia, 2018; Ruiz-Meza & Montoya-Torres, 2022). This alignment between professional identity and itinerary values appears to function as a source of occupational meaning that extends beyond day-to-day satisfaction (Lin & Heeren, 2024).

The set of characteristics identified in this study reflects a synthesis of existing discussions across tourism operations and itinerary design literature. The construct of itinerary characteristics is conceptualised as a formative construct, in which each dimension represents a distinct component of work design contributing to the overall configuration of the itinerary. Accordingly, the dimensions are not assumed to be interchangeable or necessarily highly correlated, but instead collectively define the construct. Importantly, the construct is operationalised in this study through tourist guides’ perceptual evaluations of each dimension, that is, how they experience and assess these characteristics in their daily professional practice, rather than through objective measures of itinerary features. This approach is consistent with work design research, which recognises that the psychological experience of job characteristics, rather than their objective configuration alone, is the proximal determinant of motivational and attitudinal outcomes (Hackman & Oldham, 1976; Bakker & Demerouti, 2017). From the perspective of the JD-R model (Bakker et al., 2023), well-designed itinerary characteristics, such as meaningful cultural content, schedule flexibility and adequate logistical support, function as job resources that enhance professional engagement, autonomy and satisfaction. Conversely, poorly managed characteristics, such as rigid schedules, excessive personalisation demands, or inadequate budget and logistical planning, function as job demands that generate occupational strain and may ultimately reduce career retention (Akkuş & Arslan, 2023; Lesener et al., 2019). Building on this synthesis, the characteristics of cultural tourism itineraries are conceptualised in this study as the independent variable, with job satisfaction and career retention as the dependent outcomes.

2.2. Job Satisfaction

Job satisfaction is not a simple construct, and the tourism literature has been appropriately cautious about treating it as one. The affective, cognitive and behavioural dimensions that Locke (1976) and Spector (1985, 1997) identified as its components do not operate independently in practice, with a touristguide who finds deep meaning in cultural interpretation and may accept lower financial compensation in ways that a tourist guide motivated primarily by income will not (Amissah et al., 2022; Ozturk et al., 2014; Nguyen et al., 2023). In service-intensive industries, the intangible dimensions such as recognition, autonomy, the quality of interactions with visitors, often carry more predictive weight than the tangible ones, a dynamic that is particularly pronounced in tourist guiding where the relational and interpretive dimensions of the role are central to professional identity.

In tourist guiding specifically, the emotional labour of sustained visitor interaction compounds these dynamics: the same interpersonal engagement that generates professional meaning also constitutes a significant demand, making the availability of job resources, including operational support, autonomy and task variety, particularly consequential for satisfaction outcomes (Amissah et al., 2022; Kong et al., 2018). The JD-R model suggests that when such resources are adequate, they buffer the negative effects of high job demands, enhancing engagement, well-being and career retention (Bakker et al., 2023; Lesener et al., 2019).

Moreover, job satisfaction in tourism is closely linked to perceived career meaningfulness and opportunities for professional development (Lam et al., 2022). In cultural tourism, satisfaction is often driven by the ability of employees to creatively engage with visitors, interpret heritage and contribute to meaningful experiences (Sun et al., 2022). A notable limitation of existing research is that most studies operationalise job satisfaction as an outcome of interpersonal or organisational factors, such as supervisor support, pay, recognition, while systematically neglecting operational work design variables, such as the structure of the tasks tourist guides are required to execute daily. Understanding job satisfaction in tourism therefore requires consideration of both traditional work environment factors and industry-specific contexts, including task complexity, emotional engagement and the interactive nature of the role.

Recent research in the hospitality sector suggests that improving working conditions, particularly through management practices that better align with employees’ expectations, has a significant positive effect on job satisfaction and employer attractiveness, even in contexts characterised by structural constraints such as low pay and irregular hours (Liang et al., 2026).

Overall, the literature suggests that the design and features of cultural tourism itineraries can be positively associated with tourist guides’ job satisfaction, a relationship that is formally examined in this study.

2.3. Career Retention

Career retention in tourism is a problem the industry has largely chosen to manage reactively rather than prevent structurally (Chiavenato, 2009). High turnover rates, seasonal contracting and the emotional demands of frontline roles create workforce instability that is well documented but inadequately theorised (Amissah et al., 2022; Baum et al., 2020; Kilson, 2025; Kong et al., 2018; Sun et al., 2022). What is less examined is the role that specific operational characteristics of the work, such as the design of itineraries, the management of time, the logistical infrastructure within which tourist guides operate, may play in that decision to stay or leave (Karatepe & Sokmen, 2006; Rutledge, 2023; Zopiatis et al., 2014).

The evidence that does exist points in a consistent direction: tourist guides who have clear career paths, access to skill development and adequate organisational support are more likely to remain in the profession (Karatepe & Sokmen, 2006; Zopiatis et al., 2014). The inverse, including high workload, emotional exhaustion and structural under-resourcing, predicts exit, particularly in roles requiring the sustained interpersonal engagement that guiding demands (Amissah et al., 2022; Avan & Öcal, 2025; Kong et al., 2018). This pattern is consistent with findings from the hospitality and tourism education literature, which identifies the gap between career expectations and professional reality as a primary driver of early exit, particularly among workers who entered the sector with strong intrinsic motivations (de Carvalho & Raimundo, 2025). What this literature has not yet done is connect these dynamics to the specific operational instrument through which they are experienced daily: the itinerary itself. This omission is theoretically significant: if the itinerary is the primary instrument through which guides experience their working conditions, then studies of retention that ignore itinerary design are, by definition, incomplete accounts of professional exit.

The TPB (Ajzen, 1985, 1991) informed the conceptualisation and item development of the career retention measure used in this study. Its three-component structure, comprising attitudes toward remaining in the profession, subjective norms and perceived behavioural control, provided the theoretical basis for generating items that capture the motivational calculus underlying the decision to stay or leave. However, it is important to note that the present study does not constitute a full empirical test of the TPB: the three components were not measured and analysed as separate predictors. As reported in the methodology, exploratory factor analysis indicated that TPB-derived items converged into a single higher-order factor of career retention intention, consistent with the behavioural intention construct commonly modelled in TPB-based research (Armitage & Conner, 2001; Ajzen, 1991). The TPB should therefore be understood as a conceptual framework that informed item development rather than as a theory subjected to structural empirical testing in this study. This constitutes a limitation that future research should address by measuring and analysing attitude, subjective norms and perceived behavioural control as distinct variables.

The relevance of the TPB as a framework for understanding behavioural intentions in tourism contexts has been recently confirmed within the literature. Liu et al. (2025), applying an integrated TPB model to revisit intention at a heritage site, demonstrated that attitude, subjective norms and perceived behavioural control operate through distinct mechanisms depending on the cultural and experiential context of tourism, a finding that underscores the importance of context-sensitive applications of the model, such as the one pursued in the present study in the professional domain of tourist guiding.

In cultural tourism specifically, itinerary characteristics, including content richness, interpretive complexity, the rhythm of visitor interaction, directly shape whether tourist guides experience their work as manageable and meaningful (Rutledge, 2023). An itinerary that is well-paced, culturally substantive and operationally sound gives the tourist guide both the conditions and the reasons to stay. Pairing the TPB with the JSS allows this study to capture that dynamic: the JSS measures the satisfaction that emerges from those conditions; the TPB explains how that satisfaction translates (or fails to translate) into a decision to remain.

However, the role of itinerary characteristics as a structural dimension of tourist guides’ work environment remains underexplored, particularly in relation to career retention outcomes. This gap is addressed in the present study.

2.4. Cultural Tourism Itineraries, Job Satisfaction and Career Retention

Job satisfaction and career retention do not operate independently of the conditions in which work is performed. In tourist guiding, these conditions are structured, often by the itinerary. This relationship can be examined through the lens of the JD-R model (Bakker et al., 2023), that is particularly useful because it resists the assumption that any itinerary characteristic is inherently positive or negative. The same characteristic, such as a high degree of personalisation, can function as a resource when it provides creative latitude and as a demand when operational support is insufficient.

Itineraries that combine meaningful cultural content, coherent POI sequencing and adequate logistical support give tourist guides the conditions to perform their work effectively and, in doing so, to find it professionally rewarding (Lesener et al., 2019). Conversely, rigid schedules, unrealistic time allocations and poor logistical planning generate chronic strain that can progressively erode professional commitment (Akkuş & Arslan, 2023).

The relationship between itinerary design and professional outcomes is further shaped by tourist guides’ perceptions of meaningfulness and behavioural control. Within the TPB (Ajzen, 1991), tourist guides who perceive their itineraries as professionally meaningful and operationally manageable develop more positive attitudes toward their work, stronger commitment to the profession and greater perceived control over their career trajectory, all of which support retention. An itinerary-specific satisfaction scale, grounded in job satisfaction theory (Spector, 1985, 1997), provides the measurement framework to operationalise tourist guides’ perceptual evaluation of itinerary characteristics across multiple dimensions.

Each framework alone offers only a partial account: the JD-R model explains how work design features produce satisfaction or strain but does not theorise how satisfaction translates into behavioural decisions; the TPB identifies attitudes, subjective norms and perceived behavioural control as antecedents of career retention but does not specify the work design conditions that shape them; and job satisfaction theory (Spector, 1985, 1997) provides the conceptual architecture to operationalise satisfaction across itinerary-specific dimensions. Taken together, these three perspectives are integrated into a sequential explanatory model linking work design (JD-R) to attitudinal outcomes (JSS) and from there to career intentions (TPB), that none of the frameworks could sustain independently.

The evidence reviewed converges on two testable propositions. First, the JD-R literature consistently shows that job resources embedded in work design (here operationalised as itinerary characteristics) predict satisfaction outcomes (Bakker et al., 2023; Lesener et al., 2019); itinerary studies in tourism corroborate this at the operational level (Rutledge, 2023; Akkuş & Arslan, 2023). This supports:

H1. 

The characteristics of cultural tourism itineraries are positively associated with tourist guides’ job satisfaction.

Second, the career retention literature identifies operational under-resourcing as a primary structural driver of exit (Karatepe & Sokmen, 2006; Zopiatis et al., 2014), while the TPB locates the mechanism in tourist guides’ perceived behavioural control over their professional trajectory (Ajzen, 1991). This supports:

H2. 

The characteristics of cultural tourism itineraries are positively associated with tourist guides’ career retention intentions.

The Mediating Role of Job Satisfaction in Career Retention

Beyond the direct association of itinerary characteristics on each outcome, job satisfaction plays a critical role in supporting career retention. The link between these constructs is well-established in organisational behaviour research and has been consistently observed in tourism and hospitality contexts.

Meta-analytic evidence (Park & Min, 2020; Erkasap & Özkan, 2022) demonstrates that higher job satisfaction strongly predicts lower turnover intention. Conservation of Resources theory (Hobfoll, 1989) explains this in terms of resource depletion: dissatisfied employees face a deficit and continuing in the profession requires investing further in a role that returns less than it costs. TPB adds a behavioural dimension: satisfied tourist guides develop positive attitudes toward staying, perceive social support for remaining, and feel greater control over their career decision (Ajzen, 1991; Duarte & Silva, 2023).

In the specific context of tourist guiding, tourist guides with high job satisfaction, driven by meaningful interpretive tasks, autonomy and engaging visitor interactions, are more likely to form a strong professional identity and commit long-term to the profession (Linh et al., 2023; Hu et al., 2024; Sun et al., 2022). Conversely, dissatisfaction resulting from excessive workload, lack of recognition, or poorly designed itineraries increases the likelihood of career abandonment (Akkuş & Arslan, 2023; Yetgin & Benligiray, 2019).

This chain (itinerary characteristics—job satisfaction—career retention) has not been examined in the specific context of tourist guiding, where itinerary design itself is an underexplored predictor. Examining the direct association between job satisfaction and career retention in this context is therefore both theoretically warranted and empirically novel:

H3. 

Job satisfaction is positively related to career retention among tourist guides.

3. Methodology

3.1. Research Design

This study adopts a quantitative survey design to examine the associations between cultural tourism itinerary characteristics, job satisfaction and career retention among tourist guides. Quantitative methods allow the systematic measurement of theoretically derived variables and the statistical examination of relationships between constructs (Field, 2024). Causal interpretations are not inferred and all relationships should be interpreted as associative.

3.2. Participants

The sample comprised 127 active tourist guides with experience in cultural itineraries. Portugal was selected as the empirical context due to its high short-tenure rates in the tourism sector, making career retention particularly relevant (Mira et al., 2025).

Participants were predominantly mid-to-late career professionals with substantial experience (81.1% with more than seven years) and high educational qualifications (87.4% with a Bachelor’s or Master’s degree).

The sample size was confirmed as adequate via a priori power analysis (G*Power 3.1.9.7, Faul et al., Universität Düsseldorf, Germany), which indicated a minimum of 92 participants for regression analyses with medium effect size; the final sample exceeded this threshold (Faul et al., 2007).

The sampling strategy was non-probabilistic and based on convenience sampling through professional networks and tourist guide associations. While this approach allowed access to a specialised professional population, it introduces potential self-selection bias, as participation may be more likely among individuals with stronger engagement in the profession or more positive perceptions of their work conditions. In addition, although the sample was targeted at active tourist guides, it is possible that individuals who are no longer working in the profession also participated; however, this characteristic could not be systematically identified during data collection. Consequently, the sample should not be interpreted as statistically representative of the entire population of tourist guides, and findings should be interpreted with caution regarding potential survivorship effects.

3.3. Survey Instrument

Data were collected using a structured online questionnaire with three sections: (1) sociodemographic and professional characteristics, including age, gender, education, experience, itinerary volume, certification and work scope; (2) tourist guides’ perceptual evaluation of itinerary characteristics, measured through an itinerary-specific satisfaction scale developed for this study and theoretically grounded in job satisfaction theory (Spector, 1985, 1997). Rather than applying the standard JSS dimensions, which were developed for organisational contexts and do not map onto the operational realities of tourist guiding, items were developed to capture satisfaction with the specific characteristics of cultural tourism itineraries identified in the literature. This approach preserves the theoretical logic of job satisfaction measurement, namely the evaluation of work characteristics as sources of positive or negative affect, while adapting the construct to the professional context under study; and (3) career retention intentions, operationalised through the TPB framework (Ajzen, 1985, 1991), capturing attitudes, perceived social norms and perceived behavioural control in relation to each itinerary characteristic. Items were rated on a six-point Likert scale to avoid a neutral midpoint and reduce central tendency bias, thereby encouraging directional responses and improving measurement sensitivity (Chomeya, 2010). The absence of a neutral option was considered appropriate given the evaluative nature of satisfaction and behavioural intention constructs in this study. The questionnaire ensured anonymity, confidentiality and voluntary participation, with informed consent obtained prior to data collection.

Prior to full data collection, the adapted instrument was piloted with a group of 15 professional tourist guides, who assessed item clarity, contextual fit and appropriateness of wording in relation to their daily professional practice. Feedback confirmed overall comprehensibility and led to minor linguistic refinements to ensure natural expression in the professional context of tourist guiding.

The JSS (Spector, 1985, 1997) was not applied in its original organisational format. Instead, items were carefully adapted to reflect the specific context of tourist guiding and itinerary-based work. Item adaptation followed semantic and contextual equivalence principles, ensuring that wording preserved the theoretical meaning of each dimension while making the instrument applicable to non-organisational, itinerant professional settings. No items were added or removed from the conceptual domains of the original scale, but linguistic modifications were introduced to align statements with the operational reality of cultural tourism work. This approach is consistent with established guidelines for scale adaptation and cross-context measurement equivalence, which emphasise the preservation of conceptual meaning while allowing contextual and linguistic modifications (Boateng et al., 2018). It is important to note that this study does not measure overall job satisfaction in the traditional sense, nor satisfaction with itinerary design as a global construct. Rather, it measures tourist guides’ perceptual evaluation of satisfaction with specific itinerary dimensions, an approach that allows differential analysis of which components are most consequential for professional outcomes.

Career retention intentions were operationalised through items informed by the three components of the TPB (Ajzen, 1985, 1991): attitudes toward remaining in the profession, subjective norms, and perceived behavioural control. However, as reported in Section 3.6, exploratory factor analysis indicated that these items converged into a single higher-order factor rather than three distinct components, precluding the separate analysis of each TPB dimension as an independent predictor. The resulting construct is therefore best understood as a unified measure of career retention intention, theoretically informed by the TPB but not constituting a full structural test of its three-component model. This is acknowledged as a limitation of the present study, and future research should aim to measure and analyse the three TPB components separately to enable a more complete test of the theory in this professional context.

3.4. Data Collection Process

The survey was distributed online via professional networks and tourist guide associations between 13 October and 15 December 2025. Data collection adhered to applicable data protection principles, ensuring confidentiality and secure handling of participants’ information.

3.5. Data Analysis Procedures

Data analysis was performed using IBM SPSS Statistics (version 31, IBM Corp., Armonk, NY, USA). Given the absence of prior validated scales capturing itinerary characteristics in this context, an exploratory factor analysis was conducted to identify the underlying dimensional structure. Therefore, the resulting dimensions should be interpreted as empirically derived rather than theoretically pre-established. An exploratory data analysis was initially carried out for all quantitative variables to examine the assumption of normality, based on skewness and kurtosis values and graphical inspection of distribution plots. Where normality was not met, both parametric and non-parametric tests were conducted; specifically, Mann–Whitney U tests were used as non-parametric alternatives to independent samples t-tests, and Spearman’s rank correlations as alternatives to Pearson correlations. As results were consistent across both approaches, parametric test results are reported throughout for ease of interpretation (Breakwell et al., 2006).

3.6. Statistical Procedures

Exploratory factor analyses were conducted using principal components analysis (PCA) with Varimax rotation. Varimax rotation was selected to produce a simpler and more interpretable factor structure in this exploratory stage. Although the factors may be theoretically correlated, Varimax was considered appropriate given the exploratory and scale development nature of the analysis. The use of oblique rotation, which would allow correlated factors, is recommended for future confirmatory work where the factor correlation structure can be more rigorously examined. While common factor analysis such as principal axis factoring is sometimes preferred for latent construct identification as it focuses on shared variance rather than total variance (Fabrigar et al., 1999; Costello & Osborne, 2005), PCA was adopted given its appropriateness for scale development in exploratory contexts and its widespread use in tourism research (Field, 2024). This choice is acknowledged as a limitation, and future research should consider common factor analytic approaches to validate the dimensional structure identified here. The assumptions for factorability were assessed using the Kaiser–Meyer–Olkin (KMO) measure of sampling adequacy (values > 0.50) and Bartlett’s Test of Sphericity, which confirmed the suitability of the data for factor analysis (Field, 2024). This approach ensured a theoretically grounded extraction of latent constructs underlying both satisfaction and career retention measures. It is acknowledged that a sample of 127 participants is relatively modest for factor analysis with 17 and 21 items, respectively, and may affect the stability of the factor solutions obtained. The adequacy of the sample was supported by KMO values above the recommended threshold and by the strength of factor loadings observed, but replication with larger samples is recommended before the dimensional structure is treated as definitive. Factor retention criteria included a priori theoretical considerations, inspection of the Scree plot, percentage of variance explained and parallel analysis. Factor loadings and communality values were examined, with values ideally above 0.50; items presenting cross-loadings were excluded (Hair et al., 2019).

The retention of factors with only two items, as observed in the Technology and Tourism Attractions dimensions, was justified on theoretical grounds: both dimensions correspond to conceptually distinct characteristics identified in the literature and presented strong, unambiguous factor loadings. While two-item factors are acknowledged as psychometrically less stable than those with three or more items (Costello & Osborne, 2005), their retention is consistent with recommendations that, in early-stage applied research, conceptual relevance and loading strength may appropriately guide retention decisions alongside strict psychometric thresholds (Hair et al., 2019). The internal consistency of both factors, assessed via Cronbach’s alpha, confirmed acceptable reliability (Technology: α = 0.902; Tourism Attractions: α = 0.849), further supporting their retention. Internal consistency for each factor was assessed using Cronbach’s alpha, with values above 0.70 considered adequate (Field, 2024).

The fourteen itinerary characteristics identified in this study served as the conceptual basis for item generation, with each characteristic informing one or more questionnaire items. The factorial structure of the resulting scales was not assumed a priori but allowed to emerge from the data through principal components analysis, meaning that the empirical dimensions do not correspond on a one-to-one basis to the theoretical characteristics. Rather, characteristics that loaded onto common factors were interpreted as reflecting shared underlying dimensions of tourist guides’ professional experience.

For the satisfaction scale, a principal components analysis with Varimax rotation was conducted on the seventeen initial items, yielding five factors that explained 69.45% of the total variance (KMO = 0.81; Bartlett’s χ²(136) = 1121.01, p < 0.001). One item was excluded due to cross-loading. The revised solution retained five factors explaining 71.31% of the total variance, corresponding to the following dimensions: Itinerary Organisation (five items, α = 0.827), Components (three items, α = 0.773), Technology (two items, α = 0.902), Tourism Attractions (two items, α = 0.849) and Sustainability (three items, α = 0.637). Although factors with only two items are considered less stable (Costello & Osborne, 2005), they were retained due to strong theoretical grounding and acceptable factor loadings, consistent with recommendations that exploratory scale development in applied contexts may prioritise conceptual relevance over strict psychometric thresholds in early-stage research (see

Table 1. Exploratory Factor Analysis: Factor Loadings, Communalities and Model Fit Statistics (N = 127).

Item	F1 Itinerary Org.	F2 Components	F3 Technology	F4 Tourism Attr.	F5 Sustainability	h2
11.7. Good time management helps me perform better	0.506					0.62
11.8. Flexible schedules contribute to my well-being	0.561					0.58
11.9. Well-planned budgets make my routine efficient	0.711					0.67
11.10. Well-planned budgets make my routine satisfying	0.716					0.65
11.13. Accessible itineraries make me feel more valued	0.785					0.71
11.14. Accommodation meeting needs makes experience positive		0.628				0.59
11.15. Quality of meals positively influences satisfaction		0.812				0.73
11.11. I feel satisfied when transportation is appropriate		0.853				0.78
11.5. Technology makes my work easier			0.898			0.81
11.6. Technology increases my satisfaction			0.914			0.84
11.1. POI enhance the value of my work				0.885		0.79
11.2. Diversity of attractions contributes to satisfaction				0.891		0.81
11.16. I feel more committed with sustainable itineraries					0.631	0.57
11.17. Territory interaction increases my professional pride					0.621	0.55
11.3. I feel fulfilled when itineraries promote local culture					0.763	0.69
Eigen value	6.072	1.667	1.424	1.156	1.090
% Variance explained	18.78%	15.88%	13.38%	11.82%	11.45%
Cumulative % variance	18.78%	34.66%	48.04%	59.86%	71.31%
Cronbach’s α	0.827	0.773	0.902	0.849	0.637

Note. Extraction: Principal Components Analysis. Rotation: Varimax. KMO = 0.81; Bartlett’s χ²(136) = 1121.01, p < 0.001. One item excluded due to cross-loading. Final solution retains 15 items across five factors explaining 71.31% of total variance. h² = communality. Factor loadings below 0.30 are suppressed. Item wording has been abbreviated for readability.

).

The Sustainability factor presented a Cronbach’s alpha of 0.637, below the conventional threshold of 0.70 (Field, 2024). This value is acknowledged as a psychometric limitation. However, the factor was retained on theoretical grounds, given the conceptual distinctiveness of the sustainability dimension in the itinerary design literature and the strength of its factor loadings. Readers should interpret findings related to this dimension with appropriate caution, and future research should seek to develop additional items to improve the internal consistency of this factor.

It is acknowledged that the factorial solution emerging from exploratory analysis does not map on a one-to-one basis onto the fourteen theoretical characteristics, as items reflecting conceptually adjacent characteristics converged into shared empirical dimensions. This is an inherent feature of exploratory approaches and reflects the tourist guides’ integrated experience of itinerary characteristics rather than a limitation of the theoretical framework. Future research employing confirmatory factor analysis with larger samples would allow a more stringent test of the proposed dimensional structure.

For the retention scale, a principal components analysis with Varimax rotation on the twenty-one initial items initially suggested five factors explaining 64.70% of the total variance (KMO = 0.86; Bartlett’s χ²(210) = 2192.40, p < 0.001). However, as the theoretical distribution of items across five factors was not considered adequate, a parallel analysis was conducted, which suggested a single-factor solution. A principal components analysis forcing one factor was therefore performed, with four items subsequently excluded due to low communality values and factor loadings. The final single-factor solution explained 54.18% of the total variance across seventeen items (α = 0.95), providing a robust and theoretically coherent measure of career retention. Although the TPB theoretically comprises multiple components, the empirical results indicated that these dimensions converged into a single higher-order factor of career retention intention, consistent with the behavioural intention construct commonly used in TPB-based research.

For descriptive analysis, absolute frequencies and percentages were reported for categorical variables, and means and standard deviations for continuous variables. To test H1 and H2, one-sample t-tests were conducted comparing observed mean scores against the scale midpoint of 3.5. This procedure does not test causal relationships but rather assesses whether respondents’ perceptions deviate significantly from a neutral reference value, providing an indication of positive or negative orientation toward the constructs. Accordingly, the tests examine whether satisfaction and career retention scores significantly exceed the neutral midpoint, interpreted as absence of positive association with the constructs.

To examine gender and scope-of-activity differences, independent samples t-tests were used, with homogeneity of variances assessed via Levene’s test and effect sizes computed using Cohen’s d. To test H3, Pearson’s correlation coefficients were computed between the five satisfaction dimensions and career retention. A multiple linear regression model was subsequently conducted to examine the predictive value of the five satisfaction dimensions on career retention. All statistical assumptions for regression were verified, including independence of observations, absence of multicollinearity, absence of influential outliers, and normality of residuals. Statistical significance was set at p < 0.05, with a 95% confidence interval.

4. Results

4.1. Descriptive Analysis

Descriptive analysis of the main study variables revealed consistently high levels of satisfaction across all five itinerary dimensions, as well as high career retention scores (

Table 2. Descriptive Statistics for Satisfaction Dimensions and Career Retention.

Dimension	M	SD	Min	Max	Skewness	Kurtosis
Itinerary Organisation	5.53	0.66	1.60	6.00	−1.97	6.60
Components	5.41	0.78	2.33	6.00	−2.32	6.14
Technology	4.38	1.26	1.00	6.00	−0.53	−0.25
Tourism Attractions	5.21	0.92	1.00	6.00	−1.50	2.87
Sustainability	5.40	0.71	1.67	6.00	−1.78	4.97
Career Retention	5.30	0.75	2.86	6.00	−1.18	1.18

Note. N = 127. Scale range: 1–6. M = mean; SD = standard deviation. Skewness and kurtosis values indicate departure from normality; both parametric and non-parametric tests were conducted and results were consistent across approaches.

). Figure 1 illustrates the mean scores for each dimension relative to the scale midpoint, providing a visual overview of the distribution of responses and highlighting the comparatively lower scores observed for the Technology dimension. The highest mean scores were observed for Itinerary Organisation (M = 5.53, SD = 0.66) and Components (M = 5.41, SD = 0.78), followed by Sustainability (M = 5.40, SD = 0.71) and Tourism Attractions (M = 5.21, SD = 0.92). Technology presented the lowest mean score among the satisfaction dimensions (M = 4.38, SD = 1.26), suggesting that this aspect of itinerary design is perceived as comparatively less satisfactory by respondents. Career retention also presented a high mean score (M = 5.30, SD = 0.75), indicating a strong predisposition among tourist guides to remain in the profession. This pattern is theoretically consistent with the JD-R model’s distinction between job resources and job demands: while technology is designed to reduce logistical uncertainty, its comparatively lower satisfaction scores suggest that, in the present sample, digital tools may not yet be sufficiently integrated or supported to function reliably as a professional resource (Ivanov & Webster, 2019). The high scores observed for Itinerary Organisation and Components, by contrast, suggest that basic operational adequacy, including time management, budget planning and logistical coordination, constitutes a foundational resource layer that tourist guides rely upon to perform their interpretive role effectively (Bakker & Demerouti, 2017).

4.2. Gender and Scope-of-Activity Differences

Analysis of differences between male and female participants revealed one statistically significant difference, in the Tourism Attractions dimension (t(107.01) = 2.21, p = 0.030), with male tourist guides reporting higher scores (M = 5.39, SD = 0.65) than female tourist guides (M = 5.05, SD = 1.09) (Cohen’s d = 0.39, indicating a small to medium effect size). No statistically significant gender differences were found for the remaining satisfaction dimensions or for career retention. Similarly, no statistically significant differences were found between tourist guides operating at local/regional and national/international levels across any of the satisfaction dimensions or career retention (all p > 0.05).

4.3. Hypothesis Testing

Association of itinerary characteristics betweenitinerary characteristics andjob satisfaction: to test H1, one-sample t-tests were conducted comparing the mean scores of all satisfaction items against the scale midpoint of 3.5. All items yielded statistically significant results (all p < 0.001), with means ranging from 4.24 (technology satisfaction) to 5.70 (transport comfort), consistently and substantially exceeding the neutral reference value. These results indicate that tourist guides evaluated itinerary characteristics above the neutral midpoint, consistent with a positive orientation toward the constructs. H1 is therefore supported in the sense that tourist guides perceive itinerary characteristics favourably, though it is acknowledged that this procedure does not test the statistical association between itinerary characteristics and satisfaction as distinct variables. It should be noted that this procedure establishes positive orientation toward the constructs but does not test the association between itinerary characteristics and satisfaction as distinct variables. The relationship between these constructs is examined more directly through the correlation and regression analyses reported for H3.

Association between itinerary characteristics and career retention: to test H2, one-sample t-tests were conducted for all retention items against the midpoint of 3.5. All items yielded statistically significant results (all p < 0.001), with means ranging from 4.40 (technology retention) to 5.55 (adequacy of points of interest), uniformly exceeding the neutral reference value. These results indicate that tourist guides evaluated itinerary characteristics in relation to career retention above the neutral midpoint, consistent with a positive orientation toward remaining in the profession. H2 is therefore supported in the sense that tourist guides perceive itinerary characteristics favourably in relation to their career intentions, though it is acknowledged that this procedure does not test the statistical association between itinerary characteristics and career retention as distinct variables. The relationship between these constructs is examined more directly through the correlation and regression analyses reported for H3. The uniformly positive orientation of both satisfaction and retention scores relative to the neutral reference point suggests that the tourist guides in this sample work in conditions they find broadly adequate, which is consistent with the predominantly experienced and certified professional profile of the sample. However, the variability in mean scores across dimensions, particularly the comparatively lower scores for Technology, indicates that not all itinerary characteristics contribute equally to professional experience, a nuance that the one-sample t-test approach captures in terms of directional orientation but that is more fully illuminated by the regression analysis reported below.

Effect sizes for all one-sample t-tests, computed as Cohen’s d, ranged from 0.70 (Technology) to 3.08 (Itinerary Organisation), indicating large effects across all dimensions, with Technology presenting the most modest effect size, consistent with its comparatively lower mean score.

Relationship between job satisfaction and career retention: as shown in

Table 3. Pearson Correlations Between Satisfaction Dimensions and Career Retention (N = 127).

Variable	1	2	3	4	5	6
1. Itinerary Organisation	—
2. Components	0.52 ***	—
3. Technology	0.44 ***	0.30 ***	—
4. Tourism Attractions	0.43 ***	0.25 **	0.29 **	—
5. Sustainability	0.56 ***	0.40 ***	0.26 **	0.33 ***	—
6. Career Retention	0.47 ***	0.52 ***	0.23 **	0.29 ***	0.65 ***	—

Note. Values in the lower triangle. ** p < 0.01. *** p < 0.001.

, to test H3, Pearson’s correlation analysis was conducted between the five satisfaction dimensions and career retention. All correlations were positive and statistically significant (all p < 0.05). The strongest associations were observed between career retention and Sustainability (r = 0.65, p < 0.001) and Components (r = 0.52, p < 0.001), followed by Itinerary Organisation (r = 0.47, p < 0.001), Tourism Attractions (r = 0.29, p < 0.001), and Technology (r = 0.23, p = 0.008).

A multiple linear regression model was subsequently conducted using the five satisfaction dimensions as predictors of career retention. The model was statistically significant (F(5,121) = 33.32, p < 0.001) and explained 56.2% of the variance in career retention (R² = 0.562). Among the five dimensions, only Components (β = 0.44, p < 0.001) and Sustainability (β = 0.43, p < 0.001) emerged as statistically significant predictors of career retention, providing support for H3 and further specifying which dimensions of itinerary satisfaction most strongly associated with professional retention intentions (see

Table 4. Multiple Linear Regression: Satisfaction Dimensions as Predictors of Career Retention (N = 127).

Predictor	B	SE	β	t	p
Itinerary Organisation	0.009	0.093	0.007	0.092	0.927
Components	0.420	0.069	0.435	6.089	<0.001
Technology	0.001	0.039	0.002	0.032	0.974
Tourism Attractions	0.045	0.054	0.055	0.828	0.409
Sustainability	0.452	0.075	0.430	6.052	<0.001
Model statistics: F(5,121) = 33.32, p < 0.001; R2 = 0.562; Adjusted R2 = 0.531

Note. B = unstandardised coefficient; SE = standard error; β = standardised coefficient. Significant predictors are Components (β = 0.44, p < 0.001) and Sustainability (β = 0.43, p < 0.001).

).

The differential predictive pattern observed in the regression model is theoretically significant. Components and Sustainability retained independent predictive value for career retention even when all other satisfaction dimensions were controlled, while Itinerary Organisation, Tourism Attractions and Technology did not. This suggests that not all job resources are functionally equivalent in their effects on retention: dimensions associated with the prevention of chronic operational strain, such as logistical adequacy, and with professional identity reinforcement, such as value alignment through sustainable practices, appear to operate as retention-specific resources. This distinction is consistent with Conservation of Resources theory (Hobfoll, 1989), which holds that resource loss is psychologically more salient than resource gain, and extends it to an itinerary-based work context where preventing daily depletion appears more consequential for career commitment than enriching interpretive content.

5. Discussion

The overall pattern of results is clear and consistent: tourist guides who report better-designed itineraries also report higher satisfaction and stronger intentions to remain in the profession. A more nuanced theoretical question concerns the specific dimensions of itinerary design driving these outcomes and the underlying mechanisms associated with this empirical pattern. Across all five dimensions, satisfaction scores substantially exceeded the scale midpoint, suggesting that the tourist guides in this sample work in conditions they find broadly adequate. The variability associated with retention intentions, however, is not captured by that general finding; it emerges from the differential statistical associations of specific dimensions, particularly Components and Sustainability, a pattern that warrants closer examination in light of both the JD-R model (Bakker et al., 2023) and Conservation of Resources theory (Hobfoll, 1989; Lesener et al., 2019).

The confirmation of H1 suggests that itineraries perceived by tourist guides as well-structured function as job resources in the sense of the JD-R model, providing tourist guides with task variety, interpretive autonomy and operational clarity that enhance professional satisfaction. Notably, Technology emerged as the dimension with the lowest satisfaction scores. The comparatively low satisfaction scores for Technology suggest that digital tools and platforms, despite their increasing presence in itinerary management, have not yet been sufficiently adapted to the specific operational realities of tourist guiding. Unlike organisational workers who receive structured onboarding and technical support, tourist guides typically operate autonomously and may lack access to adequate training when new digital requirements are introduced. This creates a situation where technology, designed as a resource, is experienced as an additional demand, consistent with the JD-R model’s prediction that resources without adequate support infrastructure can become demands (Bakker & Demerouti, 2017). Tour operators investing in digital transformation should therefore ensure that technological adoption is accompanied by targeted training and transition support for tourist guides. This finding aligns with Akkuş and Arslan (2023), who similarly found that operational work conditions are among the primary predictors of satisfaction in tourist guiding, and extends their work by identifying specific itinerary dimensions, rather than general working conditions, as the relevant unit of analysis.

H2 indicate that tourist guides who experience their itineraries as well-organised, culturally meaningful and operationally manageable report stronger intentions to remain in the profession, a result that aligns with what the TPB is associated with: perceived manageability and meaningfulness strengthen the behavioural intention to stay (Ajzen, 1991). That this pattern holds in a sample of predominantly experienced, certified professionals, not novices still calibrating their expectations, makes it harder to dismiss as an artefact of early-career uncertainty (Erkasap & Özkan, 2022; Kilson, 2025).

The relationship between satisfaction and career retention, examined through H3, yielded the most theoretically significant findings of the study. The regression model explained 56.2% of the variance in retention intentions, a notably strong result, and identified Components and Sustainability as the two primary significant variables. This finding is consistent with the interpretation that better-designed and sustainable cultural itineraries may be associated with lower turnover intentions in the cultural tourism sector (Linh et al., 2023; Park & Min, 2020). This result extends Park and Min’s (2020) meta-analytic finding that job satisfaction is a robust predictor of retention across service sectors, by specifying which dimensions of satisfaction carry the greatest predictive weight in the specific operational context of tourist guiding.

This pattern departs in a theoretically significant way from what conventional JD-R research would predict. In conventional organisational settings where the JD-R model is typically validated, retention is primarily driven by relational and developmental resources (e.g., supervisor support, opportunities for growth, and peer relationships) (Bakker et al., 2023; Lesener et al., 2019). In contrast, the freelance and itinerant nature of tourist guiding structurally precludes access to these traditional institutional resources. What the present findings suggest is that, in their absence, the itinerary may function as an important contextual job resource, with dimensions associated with the prevention of chronic strain, particularly logistical adequacy and value alignment, more strongly associated with professional commitment than those associated with resource gain, such as interpretive richness and task variety. This is consistent with Hobfoll’s (1989) proposition that resource loss is psychologically more salient than resource gain, and has practical implications for where tour operators and destination managers should prioritise their investments. However, the absence of comparative organisational variables, such as perceived organisational support or leadership, prevents establishing the relative importance of itinerary design in relation to other potential resource sources.

The finding that satisfaction with Components (accommodation, meals, accessibility) emerged as the strongest predictor of retention alongside Sustainability is coherent in retrospect. This dynamic aligns closely with Conservation of Resources theory (Hobfoll, 1989), suggesting that career attrition is driven not by isolated critical incidents, but rather by the cumulative effect of low-level resource depletion caused by managing continuous logistical failures. Sustainability warrants particular attention: tourist guides who perceive their itineraries as genuinely sustainable report stronger retention intentions, suggesting that value alignment between the itinerary and the tourist guide’s professional identity as a cultural and environmental mediator reinforces the sense of purpose that makes the work worth sustaining over time (Ertan & Çeşmeci, 2025; Hu et al., 2024). It should be noted, however, that the Sustainability factor presented a Cronbach’s alpha of 0.637, below the conventional threshold of 0.70. While the factor was retained on theoretical and structural grounds, the reliability limitation means that its strong predictive value for career retention should be interpreted with caution: the observed association may partly reflect measurement imprecision rather than a stable underlying dimension and replication with a more reliable sustainability scale is needed before drawing firm conclusions about this dimension’s role.

Regarding gender differences, male tourist guides reported significantly higher satisfaction with the Tourism Attractions dimension than their female counterparts (t(107.01) = 2.21, p = 0.030, d = 0.39). While this finding is statistically significant, its interpretation is necessarily limited by the absence of data on itinerary composition by gender in this study. One plausible explanation relates to professional specialisation patterns in Portugal, where certain categories of cultural and heritage attractions have historically been associated with male-dominated guiding specialisations (Durão et al., 2024), but this hypothesis cannot be tested with the present data. Future research designs should include itinerary composition as a variable when examining gender effects on satisfaction.

The absence of significant differences between tourist guides operating at local/regional and national/international levels suggests that the associations between itinerary design and satisfaction and retention are consistent across groups, reflecting the job demands–resources dynamics described by the JD-R model.

6. Conclusions

6.1. Theoretical Implications

This study makes three distinct theoretical contributions. First, and most directly, it provides the first empirical test of cultural tourism itinerary characteristics as predictors of tourist guides’ job satisfaction and career retention, addressing a gap identified as persistent and consequential in the literature (Ertan & Çeşmeci, 2025; Weiler & Black, 2014). The finding that itinerary characteristics account for 56.2% of the variance in career retention intentions demonstrates a robust effect size, establishing itinerary design as a critical determinant of long-term workforce stability for this professional group. Second, the study extends the JD-R framework into a professional context where conventional organisational resources are structurally absent, suggesting that work design elements such as itinerary characteristics may absorb the functional role that managerial support, feedback mechanisms and institutional scaffolding play in standard organisational applications of the model. Third, the differential predictive pattern of Components and Sustainability extends Conservation of Resources theory (Hobfoll, 1989) by showing that, in autonomous frontline service roles, resources associated with the prevention of chronic strain and with value alignment are more strongly associated with retention than those associated with interpretive richness or task variety.

The study also extends the JD-R framework into a professional context where it had not previously been applied systematically. Tourist guiding operates without managerial supervision, in public space and under continuous audience pressure, conditions that eliminate traditional institutional resources. Bakker et al. (2023) identify the extension of the model to non-standard work arrangements as a field priority, and the present findings suggest that itinerary design may absorb the functional role that organisational resources play in standard applications of the model. This has implications beyond tourist guiding: in other autonomous frontline service roles, such as freelance interpreters or independent tour leaders, structured work design elements may similarly function as contextual resources in the absence of conventional organisational supports, a proposition that warrants further empirical investigation.

6.2. Practical Implications

The findings carry direct practical implications for tour operators, destination managers and tourism policymakers, but the nature of those implications is specifically human resource management in character, not merely operational. The findings suggest that itinerary design may have implications beyond product development, extending to workforce experience and retention considerations, as the structural features of the itineraries that organisations assign to their tourist guides appear to be associated with whether they remain in the profession. Tour operators who treat itinerary design as a commercial instrument, optimised for tourist satisfaction and market positioning, without considering its associations with the professional experience of the tourist guides who deliver it may be influencing workforce outcomes without explicitly framing itinerary design as a human resource consideration.

For tour operators, the identification of logistical infrastructure as a primary predictor of retention underscores the need to invest in the operational quality of itineraries beyond their cultural and interpretive content. Poorly managed logistics generate professional strain that undermines career commitment and represents a human resource management failure with measurable consequences for guide retention and, by extension, for the quality and consistency of cultural tourism experiences. Moreover, if tourist guides are dissatisfied or disengaged, the quality of service they provide is likely to decline, which can directly affect the reputation of the service provider, customer experience and even profitability.

For destination managers and policymakers, the sustainability finding carries a human resource management implication that tour operators and destination managers may find counterintuitive. Investing in eco-friendly transport, community-based experiences, and responsible itinerary design is conventionally framed as an environmental or reputational decision. The results of this study suggest that sustainability-oriented itineraries may also be associated with retention-related outcomes: tourist guides who work on itineraries that reflect their values as cultural and environmental mediators show stronger intentions to remain in the profession, not because working conditions are materially better, but because the work feels worth doing. This is a workforce sustainability argument that sits entirely outside the usual ethical or marketing framing of sustainable tourism, and one with direct implications for how destination managers design itinerary portfolios and how policymakers structure certification and incentive frameworks for sustainable cultural tourism. Organisations that align their itinerary values with the professional identities of their tourist guides are, in effect, investing in retention without additional labour costs, a finding that should interest human resources strategists in tourism organisations operating under tight margin constraints.

6.3. Limitations and Future Research

This study has several limitations. The most consequential is its cross-sectional design: while the observed relationships indicate robust associations and highlight the association of itinerary characteristics and retention intentions, causal direction cannot be established. Longitudinal data would be required to determine whether itinerary design actively shapes retention over time or whether guides with stronger retention intentions simply perceive their itineraries more favourably. This limitation is particularly consequential given the perceptual nature of the measures: satisfaction with itinerary characteristics and career retention intentions were both assessed through self-report at a single point in time, raising the possibility of common method variance inflating the observed associations (Podsakoff et al., 2003). Future studies should consider multi-wave designs or the inclusion of objective itinerary descriptors alongside perceptual measures to address this concern.

Sampling strategy represents a further limitation. Data were collected through professional networks, associations of tourist guides, and social media groups, producing a convenience sample that may not fully represent the broader population of active guides in Portugal. Despite contacting official certification registries, such as Sindicato Nacional de Actividade Turística, Tradutores e Intérpretes (SNATTI) and Associação Portuguesa dos Guias-Intérpretes e Correios de Turismo (AGIC), response rates were lower than desired. Respondents are plausibly more invested in their profession than non-respondents, introducing a self-selection bias. Readers should interpret descriptive findings, particularly the high mean satisfaction scores, with this limitation in mind.

The Portuguese context introduces additional boundary conditions. The national tourism sector has undergone rapid workforce expansion alongside persistently high short-tenure rates, making the study of professional retention context-sensitive (Mira et al., 2025). Structural heterogeneity across European tourism labour markets, including informality, seasonality, and certification requirements, suggests that the prominence of Components and Sustainability as retention predictors may not generalise. Whether these mechanisms reflect Portuguese professional culture, Mediterranean labour markets or autonomous frontline service work is an empirical question for future studies (Ladkin et al., 2023; Vazquez-Garcia et al., 2025).

Scope limitations should also be considered. This study isolates itinerary characteristics as predictors, excluding organisational support, peer relationships, and economic conditions that likely operate alongside them. Future research should situate itinerary design within a broader human resource framework rather than treating it as a standalone factor. This is a significant boundary condition on the interpretation of the present findings: the proportion of variance explained by itinerary characteristics alone (56.2%) should not be interpreted as evidence that itinerary design is the dominant determinant of retention in tourist guiding, but rather as evidence of its importance within the specific analytical model tested. Variables such as perceived organisational support, remuneration, peer relationships and professional recognition were not included, and their relative contribution to retention outcomes remains unknown.

The sample composition skews toward experienced, certified and professionally engaged guides. This implies that the observed associations between itinerary design on satisfaction and retention are likely conservative estimates; in less supported populations or under more precarious conditions, these effects may be even stronger.

As itinerary characteristics constitute the central construct of this study, the lack of prior validation represents an important limitation. Future research should aim to confirm the dimensionality and measurement properties of this construct using confirmatory approaches and in different empirical settings.

A further limitation concerns potential content overlap between predictor and outcome measures. The satisfaction items were developed to capture tourist guides’ evaluations of specific itinerary dimensions, while retention items capture career intentions partly anchored in the same professional context. To the extent that satisfaction and retention items refer to similar itinerary dimensions, observed correlations may partly reflect construct overlap rather than entirely distinct psychological processes. Future studies should ensure greater conceptual distance between predictor and outcome operationalisations, for instance by measuring career retention through objective behavioural indicators or by including a temporal lag between measurements.

Taken together, these limitations point to four specific directions for future research. First, longitudinal designs tracking the same tourist guides across multiple seasons would allow causal claims about whether itinerary design actively shapes retention trajectories or whether selection effects account for the observed associations. Second, confirmatory factor analysis with larger and more representative samples should be used to validate the dimensional structure of the itinerary characteristics construct developed in this study, testing its stability across different national and cultural tourism contexts. Third, future studies should integrate itinerary characteristics within a broader work environment model that includes organisational support, remuneration, peer relationships and professional recognition, to establish the relative predictive weight of itinerary design in relation to other known retention determinants. Fourth, cross-national comparative studies are needed to determine whether the prominence of Components and Sustainability as retention predictors is specific to the Portuguese context or reflects a more general pattern in autonomous frontline service work across diverse tourism labour markets.