Pasaribu
| Rahmat Hashim | Mohamad Hazeem Sidik | Alfi Husni Fansurya*
© 2026 The authors. This article is published by IIETA and is licensed under the CC BY 4.0 license (http://creativecommons.org/licenses/by/4.0/).
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This study addresses a persistent limitation in length-of-stay research, which often records duration as the number of nights while overlooking whether destinations continue to generate value as time passes. It proposes Destination Length of Stay Performance (DLP) as a temporal-capacity construct that complements satisfaction, experience quality, memorability, and revisit intention by focusing on the perceived productivity of additional time within a trip. The study develops and validates DLP through a sequential mixed-methods design in the Mentawai Islands, Indonesia, where ferry schedules create clustered stays of 2, 4, 6, and 8 nights. Qualitative interviews informed item generation, followed by exploratory factor analysis and partial least squares structural equation modelling using a total sample of 565 respondents. The validated 11-item scale distinguishes Planned DLP, reflecting pre-visit appraisal of worthwhile additional time, from Experienced DLP, reflecting on-site value accumulation. Results show that curiosity is more strongly associated with Experienced DLP than Sense of Purpose. Activity, adventure, intellectual, and nature motivations positively shape these mechanisms, whereas escape is not significant. The findings suggest that destination planning should move beyond attracting longer stays toward designing meaningful time-use, diversified activities, and transport-sensitive itineraries that sustain visitor value across duration.
Destination Length of Stay Performance, tourist behavior, indigenous tourism, Mentawai Islands
Tourist length of stay (LoS) remains one of the most widely used indicators in destination management. It informs expenditure forecasting, capacity planning, sustainability assessment, and evaluations of destination appeal and performance [1-3]. Yet its practical usefulness rests on an assumption that is rarely examined: that observed duration can be read as a meaningful signal of destination value. This assumption is problematic because the same number of nights may arise from different mechanisms. A four-night stay may reflect sustained curiosity, cultural engagement, and the perception that additional time remains worthwhile. It may also result from the absence of an earlier ferry departure. LoS records the same duration in both cases, but the performance meaning of that duration is different.
This ambiguity is especially visible in the Mentawai Islands, West Sumatra, Indonesia, where inter-island ferry services operate at approximately two-day intervals and make stays of 2, 4, 6, or 8 nights common. These clustered durations reveal how intention, experience, and logistical structure jointly shape time allocation. They also show why LoS should not be read as a direct proxy for destination appeal, particularly in indigenous and remote destinations where cultural rhythms, uneven service availability, environmental conditions, and access constraints shape the experience of staying. The Mentawai context is therefore not merely an empirical site, but a setting in which the time-value ambiguity of LoS becomes theoretically visible.
Previous LoS research has made substantial contributions by identifying factors associated with longer or shorter stays, including destination image, price conditions, climate, visitor characteristics, and activity engagement [4-7]. Much of this work models duration as a behavioural outcome and helps explain who stays longer and under what conditions. However, it is less able to answer a more specific performance question: whether tourists perceive additional time at the destination as continuing to generate value. The gap addressed in this study is therefore not the absence of LoS research, but the absence of a construct that directly captures the perceived productivity of destination time.
Existing attempts to refine LoS interpretation largely remain within the duration paradigm by adding controls, segmenting tourists, disaggregating trip characteristics, or linking stay length to expenditure and related outcomes [6, 8-11]. These strategies improve explanations of observed duration, but they do not fully distinguish between staying longer and perceiving longer time as worthwhile. Nor is this distinction fully captured by adjacent constructs. Satisfaction reflects an evaluative judgment against expectations [12, 13], while experience quality and memorability capture the perceived quality, intensity, or salience of tourism episodes [14, 15]. Revisit intention indicates the likelihood of returning, which may be influenced by factors beyond value accumulation during the current stay [16, 17]. These constructs are not inadequate; they answer different questions. What remains underspecified is whether a destination continues to make additional time feel worthwhile within the same visit.
This study introduces Destination Length of Stay Performance (DLP) as a time-value construct that evaluates tourists’ appraisal of a destination’s capacity to make time spent there feel worthwhile, meaningful, and value-generating. DLP is positioned as a complementary construct rather than a replacement for LoS or established experience constructs. It shifts the analytical focus from how long tourists stayed to how tourists evaluate the perceived return on time as the stay unfolds. The construct consists of two temporally ordered dimensions: Planned DLP, which captures pre-visit appraisal of whether allocating more time to the destination appears worthwhile, and Experienced DLP, which captures on-site appraisal of whether the destination continues to generate value during the visit. Planned DLP draws on expectancy-value theory, which explains how anticipated benefits and pre-travel signals shape expected value [18, 19]. Experienced DLP draws on affective events theory, which explains how discrete on-site episodes recalibrate evaluations over time [20-22].
The study employs a sequential mixed-methods design with 565 total participants to develop and validate the DLP construct and to examine the psychological mechanisms associated with Experienced DLP. The structural model links push and pull motivations to Experienced DLP through Curiosity and Sense of Purpose, explaining how motivational forces may be translated into tourists’ appraisal of value accumulation during the stay.
This study makes three contributions. First, it introduces and validates DLP as a two-dimensional construct that separates tourists’ appraisal of destination time-value from the behavioural count of nights stayed. Second, it clarifies why DLP is not reducible to adjacent constructs by focusing on the perceived productivity of time within the current visit. Third, it provides an initial structural explanation of Experienced DLP by integrating push-pull motivation theory with expectancy-value theory and affective events theory in an indigenous and logistically constrained destination context.
2.1 The structural inadequacy of length of stay as a performance indicator
Research on tourist length of stay has followed two broad trajectories. The first, and more extensive, is econometric modelling: studies using survival analysis, count-data regression, and duration models have identified correlates of LoS including destination image, accommodation type, travel party composition, climatic conditions, and activity engagement [6, 10, 11, 23]. This tradition treats LoS as a behavioral outcome to be explained rather than as a performance signal to be evaluated. The second trajectory, smaller and more recent, attempts to connect LoS with experiential or psychological constructs, including flow experience, tourist satisfaction, and memorable experiences [3, 24, 25]. Neither trajectory has addressed the construct-level gap: there is no established measure that directly evaluates whether a destination is generating sustained value across the duration of a stay.
This gap matters because LoS is fundamentally a behavioral output that conflates tourist preference with external constraint [26-28]. Budget limits, transport schedules, packaged itineraries, and social commitments frequently cap duration in ways external to the destination. Vieira et al. [29] and Oklevik et al. [2] have separately noted that established predictors of LoS often show inconsistent effects across studies, a pattern consistent with LoS collapsing preference and constraint into a single measure. More fundamentally, a night-count reveals nothing about value dynamics within the stay: whether each additional hour continues to yield meaningful experiential return, when psychological saturation begins, or how pre-visit marketing compares to on-site delivery.
LoS may obscure distinctions between promise-side expectations and on-site delivery by reducing both into a single behavioural outcome. A construct is therefore needed that evaluates the process of value accumulation across time and separates pre-visit promise from on-site delivery as distinct performance dimensions. DLP is proposed to serve this function.
2.2 Positioning Destination Length of Stay Performance against adjacent constructs
Several constructs in tourism research address themes adjacent to DLP, and a principled justification for introducing a new measure requires specifying precisely how DLP differs from each. Table 1 presents a systematic positioning. The core argument is that DLP is evaluative in a temporal-capacity sense: it asks whether the destination continues to sustain perceived value as the stay lengthens, a question that none of the established constructs directly addresses.
Tourist satisfaction is an affectively laden, post-hoc evaluation of outcomes against prior expectations [12, 13]. DLP, by contrast, is prospective and evaluative of a destination's capacity: it asks, at any point in the stay, whether additional time would continue to be productive. Satisfaction can be high even when marginal value fades quickly, or low even when time is densely productive. The two constructs are therefore not interchangeable; DLP is expected to inform time-allocation decisions in ways that satisfaction, as a retrospective summary judgment, may not fully capture. Empirically adjudicating this requires a study measuring satisfaction, Experienced DLP, and time-extension intentions simultaneously, which is a priority for future research.
Experience quality and memorability focus on the depth, salience, and lasting impression of specific experiential episodes [14, 15]. They describe the quality of what happened, not the structural capacity of the destination to sustain productive encounters across time. DLP asks a different but complementary question: across all episodes experienced so far, does the pattern suggest that additional time would continue to be worthwhile? The empirical boundary between DLP and these constructs is a theoretical argument grounded in the construct's internal structure; full discriminant validity testing against experience quality and memorability scales awaits future work.
Table 1. Positioning Destination Length of Stay Performance (DLP) against adjacent constructs
|
Construct |
Primary Temporal Focus |
Core Evaluative Question |
Limitation for LoS Performance Diagnosis |
|
Length of Stay (LoS) |
Past/observed behavior |
How long did the visitor stay? |
Conflates destination appeal with logistical, budgetary, and itinerary constraints. |
|
Satisfaction |
Post-visit outcome |
How pleased was the visitor with the overall experience? |
Does not isolate whether additional time would continue to generate value. |
|
Experience Quality |
During/episodic evaluation |
How good or meaningful were the experienced episodes? |
Captures episode quality, not the marginal productivity of time across the stay. |
|
Memorability |
Post-visit memory |
What will remain salient after the visit? |
Indexes lasting impression, not whether the destination sustained value as duration increased. |
|
Revisit Intention |
Future behavioral intention |
Is the visitor likely to return? |
Focuses on return likelihood, not value accumulation within the current stay. |
|
DLP (proposed) |
Planned and experienced time appraisal |
Does perceived value continue to accumulate as the stay lengthens? |
Addresses the temporal-capacity gap by evaluating how effectively the destination converts time into sustained visitor value. |
Note: This distinction does not imply that Destination Length of Stay Performance (DLP) replaces satisfaction, experience quality, memorability, or revisit intention. DLP is positioned as a complementary construct that captures a temporal-capacity dimension not directly isolated by those established measures.
Revisit intention measures the probability or desire to return, influenced by switching costs, variety-seeking, and loyalty mechanisms largely independent of within-stay value accumulation [16]. A visitor might have high Experienced DLP yet low revisit intention if the destination feels fully explored, or vice versa. DLP is therefore a within-trip performance indicator that complements, rather than replaces, revisit intention.
2.3 Theoretical foundations: Expectancy-Value Theory and Affective Events Theory
DLP is grounded in two complementary theoretical frameworks. Expectancy-Value Theory (EVT) explains how anticipated benefits and competence beliefs shape evaluative judgments about the worthiness of investing further resources, including time [19]. Before travel, visitors form expectancy-by-value appraisals from market signals: destination positioning, reviews, itineraries, and reputational cues. The relevant EVT question for DLP is not how long visitors stayed, but whether allocating additional time would continue to pay off. That forward-looking, time-sensitive judgment constitutes Planned DLP. EVT also explains how appraisals are revised as experiences accumulate, making the theory relevant to both dimensions.
Affective Events Theory (AET) explains how discrete on-site events trigger emotional responses that in turn recalibrate cognitive evaluations. Stylos et al. [30] applied AET specifically to tourism LoS outcomes, demonstrating that on-site episodes are associated with the perceived return on time investment in ways consistent with the mechanism underlying Experienced DLP. AET and EVT are complementary: EVT provides the cognitive-evaluative architecture of both DLP dimensions, while AET explains the affective recalibration processes that are most active during the on-site phase.
2.4 The Planned–Experienced structure of Destination Length of Stay Performance
Decisions about time allocation involve at least two evaluative moments: a pre-visit appraisal of whether additional time would be worthwhile (Planned DLP) and on-site assessments of whether value continues to accumulate as the stay unfolds (Experienced DLP). Planned DLP is primarily shaped by how clearly and credibly the destination communicates what can be achieved across time [18, 31]. Because it is a perceptual appraisal rather than a behavioral outcome, it may remain elevated even when logistical constraints cap actual LoS. Experienced DLP is shaped by the density, sequencing, and novelty of on-site episodes and by the degree to which the destination continues to supply non-redundant content as the stay extends [30, 32, 33]. Together, these dimensions provide separate accountability: shortfalls in Planned DLP point toward marketing and communication, while shortfalls in Experienced DLP point toward experience design and operations.
2.5 Psychological mechanisms: Curiosity and Sense of Purpose
The empirical model focuses on Experienced DLP and proposes that Curiosity and Sense of Purpose serve as the proximal mechanisms through which push–pull motivations shape the on-site appraisal of value accumulation. Curiosity sustains exploratory engagement with non-redundant experiences and preserves the perceived marginal return on each additional unit of time. In a tourism context, Davari and Jang [34] showed that destination curiosity is associated with travel-based learning and sustained engagement, while Poli et al. [35] demonstrated that curiosity is linked to expected learning progress and perceptual novelty. Sense of Purpose aligns activities with personally meaningful aims, maintaining goal-congruent value per unit of time [36, 37]. Hill et al. [37] showed that purpose is associated with daily positive event appraisals, and Lengieza [38] connected purposeful engagement with eudaimonic experience in nature-based contexts, which is relevant to the Mentawai indigenous setting.
3.1 Curiosity, Sense of Purpose, and Experienced Destination Length of Stay Performance
Experienced DLP is an on-site appraisal that each additional unit of time continues to yield meaningful incremental value. In the EVT–AET framework, on-site episodes trigger psychological states that recalibrate evaluations in the sequence: episode, psychological state, appraisal [39, 40]. Curiosity is expected to sustain exploratory engagement with novel, non-redundant experiences, preserving the perceived marginal return on time [35, 41]. Sense of Purpose is expected to align activities with meaningful personal aims, so that each unit of time is appraised as goal-congruent progress [42, 43]. Both states are therefore proposed to be positively associated with Experienced DLP.
H1: Curiosity is positively associated with Experienced DLP.
H2: Sense of Purpose is positively associated with Experienced DLP.
3.2 Push–pull motivations as antecedents of curiosity
Curiosity on site is expected to arise when motivations orient attention toward novelty and challenge and when the environment supplies rich, non-redundant content for exploration [34, 44]. An intellectual motivation orients visitors toward information gaps and learning opportunities embedded in the destination [45, 46], activating epistemic curiosity associated with novelty-seeking and comparative interpretation.
H3a: Intellectual motivation is positively associated with on-site Curiosity.
Adventure motivation elevates exploratory arousal and preference for non-routine experiences [47-49]. Visitors with strong adventure motivation are likely to sample unfamiliar routes, attempt new activities, and tolerate uncertainty, behaviors that increase encounters with novel cues and may thereby strengthen Curiosity.
H4a: Adventure motivation is positively associated with on-site Curiosity.
Escape motivation may foster curiosity by alleviating the cognitive demands associated with daily routines and occupational responsibilities [50, 51]. These demands often consume attentional resources and limit individuals' capacity to engage with novel stimuli. By providing temporary psychological detachment from everyday pressures, escape-motivated travel can restore attentional capacity and create greater openness to unfamiliar experiences. As a result, tourists may become more sensitive to novel, unexpected, and distinctive aspects of the destination, thereby stimulating on-site curiosity.
H5a: Escape motivation is positively associated with on-site Curiosity.
Nature motivation is expected to activate effortless, involuntary fascination that broadens attentional scope, facilitating micro-discoveries and follow-up questions about observed phenomena [52-54].
H6a: Nature motivation is positively associated with on-site Curiosity.
Activity-richness motivation reflects a preference for varied, non-redundant engagement [55, 56]. When visitors actively seek diverse episodes, they accumulate encounters with distinct stimuli that invite comparison and sampling, which may strengthen on-site Curiosity.
H7a: Activity motivation is positively associated with on-site Curiosity.
3.3 Push–pull motivations as antecedents of Sense of Purpose
Sense of Purpose is expected to strengthen when motivations provide internal goal frames and the setting supplies clear pathways and feedback toward those goals [43, 57]. Intellectual motivation embeds learning goals that organize meaning and set internal standards of progress [58, 59]. When destinations provide knowledge-oriented pathways with clear feedback, intellectual goals may translate into actionable steps that visitors can track, strengthening the perception that time is purposefully invested.
H3b: Intellectual motivation is positively associated with Sense of Purpose.
Adventure motivation is likely to supply mastery and achievement cues that frame challenges as directional goals [60-62]. In settings with graded difficulty and visible progress markers, adventure motivation may translate into felt purposefulness through competence signals.
H4b: Adventure motivation is positively associated with Sense of Purpose.
Escape motivation may facilitate a stronger sense of purpose by enabling temporary psychological detachment from everyday demands and reducing the cognitive burden associated with routine responsibilities [63, 64]. This psychological space creates opportunities for self-reflection and reassessment of personal priorities, values, and life goals. Through this reflective process, tourists may gain greater clarity regarding what is meaningful and important in their lives, thereby strengthening their sense of purpose.
H5b: Escape motivation is positively associated with Sense of Purpose.
Nature settings are expected to afford eudaimonic meaning through awe, connection, and restoration [38, 65]. These experiences may broaden perspective and connect personal aims with larger narratives of place and ecology [65], deepening the sense that time is purposefully used.
H6b: Nature motivation is positively associated with Sense of Purpose.
Activity-richness motivation is expected to provide scaffolded tasks, visible milestones, and competence feedback across varied episodes [52, 66, 67]. This structure may convert time spent into perceived purposeful advancement, thereby strengthening Sense of Purpose.
H7b: Activity motivation is positively associated with Sense of Purpose.
4.1 Research design
This study adopts a sequential exploratory mixed-methods design to develop and validate the DLP construct within a logistically constrained indigenous tourism context. The research proceeded in three sequential phases: qualitative item generation (Phase 1), scale purification via Exploratory Factor Analysis (EFA) (Phase 2), and structural model testing via confirmatory factor analysis within a PLS-SEM framework (Phase 3). Total participants across all three phases: N = 565.
The empirical context is the Mentawai Islands, West Sumatra, Indonesia, an indigenous archipelago accessible primarily by inter-island ferry from Padang. The ferry service operates at approximately two-day intervals, producing observable stay-length clustering: departures typically available every two days mean that practical stay lengths cluster at 2, 4, 6, and 8 nights. This transport structure is analytically useful for DLP development because it makes the preference–constraint distinction contextually salient and provides a setting in which the proposed design properties of DLP can be conceptually examined.
The Mentawai ferry schedule supports the argument that realized LoS may be partly shaped by transport availability rather than visitor preference alone; however, the present study does not report a direct statistical comparison between actual LoS and Experienced DLP and should therefore be read as providing contextual and psychometric support for DLP rather than a full empirical test of behavioral independence from LoS.
Participation was voluntary and anonymous. Before participating, respondents were informed about the purpose of the study, the voluntary nature of participation, and their right to decline or withdraw at any time. Consent was indicated by respondents’ willingness to participate and complete the interview or questionnaire. No personally identifying information was collected, and all results are reported in aggregate form. For qualitative interviews, permission to audio-record was obtained before recording began, and transcripts were anonymized during analysis.
4.2 Phase 1: Qualitative item generation (N = 28)
Using purposive sampling, 28 domestic and international tourists were recruited at departure gates immediately following their stay. In-depth semi-structured interviews were audio-recorded, transcribed verbatim, and analyzed using a three-step coding procedure (open, axial, and selective coding), with the core category of “value across time” organizing the conceptual structure [68-70]. The initial item pool comprised 24 candidate items capturing both Planned and Experienced aspects of DLP. Items were evaluated by three academic experts in tourism and consumer behavior and two destination management practitioners; based on their feedback, wording was refined and one redundant item was removed, yielding 23 items. Cognitive debriefing with five additional tourists confirmed clarity and contextual relevance.
4.3 Phase 2: Exploratory Factor Analysis and scale purification (N = 200)
The 23-item pool was administered to N = 200 departing tourists recruited via a seat-number randomized intercept procedure at the Mentawai ferry departure gates. For each departure, a seat predicate was pre-randomized (row last digit r ∈ {0–9}); passengers whose seat numbers satisfied the predicate were approached sequentially. Eligibility required being at least 18 years old and having stayed in the Mentawai Islands for at least one night. This design approximated equal a priori inclusion probabilities and was fully independent of the Phase 1 sample [71].
EFA was conducted using principal axis factoring with oblique (Promax) rotation. Items were retained when the primary loading was at least .60 and any cross-loading below .30 on the pattern matrix, with communalities at least .40 and Cronbach’s α at least .70. Reverse-worded items meeting these criteria were scored forward prior to analysis.
The retained reverse-coded items were scored forward prior to analysis. Their retention was not based solely on statistical loading but also on conceptual coverage. Planned5 (“I do not need to plan to stay long at this destination”) captures the absence of time-extension intention, which is the logical complement of planned time-worthiness and therefore reflects a theoretically meaningful boundary of the Planned DLP dimension. Experienced5 (“If the stay is too long, the destination loses its appeal”) captures perceived saturation, which is central to evaluating whether value continues to accumulate or begins to decline as the stay lengthens, a conceptually essential component of Experienced DLP. Content validity was protected by retaining only reverse-coded items judged by expert reviewers to represent theoretically meaningful boundaries of DLP and that also met all psychometric criteria in both EFA and Confirmatory Factor Analysis (CFA). The slightly lower CFA loadings of these items (Planned5 = 0.66; Experienced5 = 0.65) are acknowledged; both are statistically significant and serve to protect the content coverage of each dimension.
4.4 Phase 3: Confirmatory Factor Analysis and structural model testing (N = 337)
A new, independent sample of N = 337 departing tourists was recruited using the same seat-number randomized intercept as in Phase 2. The measurement model was estimated in SmartPLS 4 using reflective specification for all constructs. Global fit met standard PLS-SEM criteria (SRMR = 0.062; RMS_theta = 0.10).
Planned DLP was developed and validated as part of the two-dimensional DLP scale but was not specified as a structural outcome in the present model. This decision reflects the timing of data collection: Phase 3 surveys were administered at departure, making the data best suited to explaining Experienced DLP as an on-site and post-visit appraisal formed through direct engagement with the destination. Testing the structural antecedents and downstream consequences of Planned DLP requires pre-travel or longitudinal measurement design and is therefore beyond the scope of the present study. Post-visit outcomes such as loyalty and behavioral intentions were similarly not included in the final structural model and are treated as future research directions.
The structural model tests pathways from five push–pull motivations, specifically Intellectual, Adventure, Escape, Nature, and Activity, through Curiosity and Sense of Purpose as psychological mechanisms, to Experienced DLP as the dependent variable. Model evaluation used SRMR, RMS_theta, R², f², Q², and PLSpredict. Bootstrapping with 5,000 subsamples was used for significance testing.
4.5 Measures
All constructs were specified as reflective and measured on a five-point Likert scale (1 = Strongly Disagree, 5 = Strongly Agree). Sense of Purpose was measured with four items adapted from Lengieza [38] and Masnan et al. [72]. Intellectual was captured with five items from Yousaf et al. [73]. Escape drew on five items from Yousaf et al. [73]. Nature Motive comprised four items adapted from Jones and Nguyen [74] and Yoon and Uysal [75]. Adventure was assessed with three items adapted from Kim et al. [76] and Sato et al. [77]. Activity consisted of three items from Pesonen et al. [78]. The two DLP dimensions used the 11 items retained from Phase 2. All items underwent forward-back translation between English and Indonesian with bilingual expert review.
5.1 Qualitative item generation
Semi-structured interviews with 28 tourists revealed several recurring themes about how visitors plan and experience their stays in the Mentawai Islands. Prominent among these were anticipatory planning for extended visits (“I purposely prepared extra leave and additional budget for this destination”); desire for continued discovery (“There are still many places I wish I had the chance to explore here”); cumulative revelation during longer stays (“The longer I stayed, the more new things I found”); and recognition of a saturation threshold (“If I stay too long, it might start to feel boring”). These themes map onto the theoretical structure of DLP: the first two reflect Planned DLP as a pre-visit appraisal of time-worthiness, while the latter two reflect Experienced DLP as the on-site judgment of whether value continues to accumulate. The saturation comment supports the theoretical inclusion of reverse-worded items that capture the perceived boundary of value accumulation.
The interviews also indicated that transport logistics shaped visitor planning. Multiple respondents mentioned consulting the ferry schedule when deciding how long to stay, with several indicating that their preferred duration was shaped by the available ferry schedule and departure times. This qualitative pattern provides contextual support for the premise that observed LoS in this setting may be partly structured by transport availability, and that DLP, as a perceptual appraisal of value capacity, is conceptually distinct from the behavioral LoS outcome.
5.2 Scale purification: Exploratory Factor Analysis results
The EFA yielded a clean two-factor solution consistent with the Planned–Experienced theoretical structure. Sampling adequacy was strong (KMO = 0.89) and Bartlett’s test confirmed factorability (χ² = 2,135.47, df = 253, p < 0.001). Planned DLP explained 33.1% and Experienced DLP explained 29.8% of variance (total 62.9%), with an inter-factor correlation of ϕ = 0.24, indicating related but empirically distinct dimensions. Table 2 presents the 11 retained items with their pattern loadings.
Table 2. Factor loadings of retained items from Exploratory Factor Analysis (EFA) (N = 200)
|
Item |
English Wording |
|
Planned1 |
I plan to stay long enough at this destination. |
|
Planned2 |
I intend to stay long enough to explore the destination fully. |
|
Planned3 |
I plan to extend my visit if the opportunity arises. |
|
Planned4 |
I believe this destination could keep me comfortable during a fairly long stay. |
|
Planned5* |
I do not need to plan to stay long at this destination. (R) |
|
Experienced1 |
The longer I stayed, the more interesting things I discovered. |
|
Experienced2 |
This destination kept me excited to continue exploring. |
|
Experienced3 |
I felt motivated to stay longer. |
|
Experienced4 |
My time was not enough to try all the interesting things. |
|
Experienced5* |
If the stay is too long, the destination loses its appeal. (R) |
|
Experienced6 |
Adding days to my stay was the right decision. |
Note: * Reverse-coded items, scored forward prior to analysis. (R) = reverse-coded. Primary loadings ≥ 0.60; cross-loadings < 0.30.
5.3 Respondent profile (phase 3)
The structural model sample (N = 337) was predominantly male (58.2%), with ages concentrated in the 25–34 (38.0%) and 35–44 (27.9%) brackets. Domestic visitors comprised 62.0% of the sample; among international visitors (38.0%), Australia was the largest origin group (35.9%), followed by the United States (14.8%) and the United Kingdom (12.5%). First-time visitors predominated (70.9%). Table 3 presents the full respondent profile, including the observed stay-length distribution.
Table 3. Respondent profile, phase 3 (N = 337)
|
Variable |
Categories |
n (%) |
|
Gender |
Male |
196 (58.2) |
|
|
Female |
141 (41.8) |
|
Age |
18–24 |
47 (13.9) |
|
|
25–34 |
128 (38.0) |
|
|
35–44 |
94 (27.9) |
|
|
45–54 |
47 (13.9) |
|
|
55 and above |
21 (6.2) |
|
Origin |
Domestic |
209 (62.0) |
|
|
International (total) |
128 (38.0) |
|
International breakdown (n = 128) |
Australia / USA / UK / NZ / Brazil / France / Malaysia / Thailand / China |
46 / 19 / 16 / 13 / 11 / 8 / 7 / 5 / 3 |
|
Visit type |
First-time |
239 (70.9) |
|
|
Repeat |
98 (29.1) |
|
Stay length |
2 nights |
105 (31.2) |
|
|
4 nights |
130 (38.6) |
|
|
6 nights |
65 (19.3) |
|
|
8 or more nights |
37 (10.9) |
Note: The concentration of stays around 2-, 4-, 6-, and 8-or-more-night categories is consistent with the ferry schedule described in Section 4.1 and supports the contextual premise that realized LoS in Mentawai may be partly structured by transport availability.
5.4 Measurement model
The measurement model demonstrated adequate global fit (SRMR = 0.062; RMS_theta = 0.10). All standardized outer loadings were at least .70 except for the two reverse-worded indicators (Planned5 = 0.66; Experienced5 = 0.65), both statistically significant in bootstrapping and retained on the conceptual grounds described in Section 4.3. Internal consistency was satisfactory (Cronbach’s α: Planned = 0.85, Experienced = 0.83; composite reliability: Planned = 0.86, Experienced = 0.85). Convergent validity held (AVE = 0.55 for Planned DLP; 0.52 for Experienced DLP). Discriminant validity was established via the Fornell–Larcker criterion and HTMT ratios below 0.85 for all construct pairs. Prediction-oriented diagnostics were acceptable: PLSpredict returned predominantly positive Q² values, and blindfolding Q² values were 0.313 (Curiosity), 0.127 (Sense of Purpose), and 0.124 (Experienced DLP), with corresponding R² values of 0.520, 0.320, and 0.370.
5.5 Structural model and hypothesis testing
Experienced DLP is the dependent variable in the structural model and is significantly predicted by both Curiosity (β = 0.434, t = 5.60, p < 0.001; H1 supported) and Sense of Purpose (β = 0.311, t = 5.20, p < 0.001; H2 supported), with Curiosity showing a somewhat stronger association. Table 4 presents the full structural results.
Table 4. Structural model results
|
Path |
β |
t |
p |
Decision |
|
Curiosity → Experienced DLP (H1) |
0.434 |
5.60 |
< 0.001 |
Supported |
|
Sense of Purpose → Experienced DLP (H2) |
0.311 |
5.20 |
< 0.001 |
Supported |
|
Intellectual → Curiosity (H3a) |
0.360 |
7.20 |
< 0.001 |
Supported |
|
Intellectual → Sense of Purpose (H3b) |
0.180 |
2.90 |
0.004 |
Supported |
|
Adventure → Curiosity (H4a) |
0.380 |
8.00 |
< 0.001 |
Supported |
|
Adventure → Sense of Purpose (H4b) |
0.200 |
3.20 |
0.002 |
Supported |
|
Escape → Curiosity (H5a) |
−0.020 |
0.30 |
0.780 |
Not supported |
|
Escape → Sense of Purpose (H5b) |
0.100 |
1.40 |
0.160 |
Not supported |
|
Nature → Curiosity (H6a) |
0.180 |
2.80 |
0.005 |
Supported |
|
Nature → Sense of Purpose (H6b) |
0.210 |
3.50 |
0.001 |
Supported |
|
Activity → Curiosity (H7a) |
0.400 |
8.50 |
< 0.001 |
Supported |
|
Activity → Sense of Purpose (H7b) |
0.280 |
5.00 |
< 0.001 |
Supported |
Figure 1. Structural model results
For Curiosity, four of the five motivations were significantly associated: Activity (β = 0.400), Adventure (β = 0.380), Intellectual (β = 0.360), and Nature (β = 0.180), supporting H7a, H4a, H3a, and H6a respectively. Escape was not significant (β = −0.020, p = 0.780); H5a was rejected. For Sense of Purpose, four motivations were again significant: Activity (β = 0.280), Nature (β = 0.210), Adventure (β = 0.200), and Intellectual (β = 0.180), supporting H7b, H6b, H4b, and H3b respectively. Escape was not significant (β = 0.100, p = 0.160); H5b was rejected (see Figure 1).
6.1 What the present study demonstrates
This paper should be read as both a scale-development contribution and a structural explanation of Experienced DLP. What the study demonstrates is the initial development and validation of a two-dimensional DLP scale, showing that Planned and Experienced DLP are empirically distinct yet correlated dimensions (ϕ = 0.24 in EFA; primary loadings ≥ 0.60 with cross-loadings below 0.30; AVE ≥ 0.52 in CFA). It also demonstrates that Curiosity and Sense of Purpose are significant pathways from push–pull motivations to Experienced DLP, and that Activity, Adventure, Intellectual, and Nature motivations are positively associated with these mechanisms, whereas Escape does not reach significance in either pathway.
What the present study does not yet demonstrate is full discriminant and incremental validity of DLP against satisfaction, experience quality, memorability, or revisit intention; full behavioral independence of Experienced DLP from actual LoS; or the formal validity of the Planned × Experienced matrix as a diagnostic dashboard with validated thresholds. These issues require future comparative, longitudinal, or multi-construct designs. The present study provides initial psychometric and contextual support for the DLP construct's internal structure and theoretical grounding.
6.2 The evaluative structure of Destination Length of Stay Performance
DLP is designed to reduce the confounding influence of logistical constraints, observed duration, and behavioral outputs. It is capacity-based and temporal: it evaluates whether the destination can continue to supply value per unit of time, not whether a specific episode was satisfying or memorable. It is evaluative in the EVT sense, reflecting a judgment about the marginal return on additional time invested, and processual in the AET sense, emerging from the ongoing interaction between episodic experience and appraisal recalibration as the stay progresses. The present study supports the internal structure and initial construct validity of DLP; a full empirical test of constraint-robustness or behavioral independence across contexts is a matter for future research.
DLP is positioned as complementary to, rather than a replacement for, satisfaction and tourist experience constructs. Satisfaction captures how pleased the visitor ultimately was; DLP asks to what extent this destination can continuously convert time into value. Similarly, DLP differs from experience quality and memorability by targeting the aggregate capacity of the destination across the full stay rather than the depth or salience of individual episodes. Whether DLP partially overlaps with satisfaction or experience in particular measurement contexts is an empirical question requiring simultaneous multi-construct testing.
6.3 Theoretical contributions
The study advances LoS research in three empirically grounded ways. First, the EFA and CFA confirm that Planned and Experienced DLP are empirically distinct yet related dimensions, creating accountability at two decision points in the visitor journey without collapsing them into a single retrospective measure. Planned DLP is retained as a validated dimension; its causal role, meaning its structural antecedents and downstream consequences, remains a future research agenda requiring pre-visit data.
Second, the mechanism test provides evidence that Curiosity and Sense of Purpose are significant pathways from push–pull motivations to Experienced DLP. Activity, Adventure, Intellectual, and Nature motivations are each significantly associated with one or both mechanisms, while Escape is consistently non-significant. This pattern is consistent with the view that escape functions as a threshold condition: restoration may reduce cognitive load and create space for Curiosity and Purpose to operate, without itself generating the exploratory or meaning-oriented engagement that sustains perceived value accumulation [79, 80].
Third, the indigenous contribution of this study is contextual rather than theory-building. The study uses the Mentawai Islands as an indigenous and logistically constrained destination context in which the limitations of raw LoS and the usefulness of DLP become especially salient. This is not a claim to advance indigenous tourism theory in a broad sense; stronger engagement with host-side implications, indigenous community perspectives, and cross-indigenous comparative designs would be required for a broader theoretical contribution.
6.4 Managerial implications
The results suggest three types of managerial implication, calibrated to the evidence available. First, because Curiosity has a somewhat stronger association with Experienced DLP than Sense of Purpose (β = 0.434 vs. 0.311), and because Activity, Adventure, and Intellectual motivations show the strongest associations with Curiosity, destination operators should consider strategies that sustain novelty and exploratory potential: staggered reveals of less-accessible sites, progressive itinerary design that does not exhaust the most compelling content on the first day, and programming that rewards extended stays with experiences unavailable to short-stay visitors. Second, Purpose-supporting strategies operate through different mechanisms: clear goal frames, cultural learning pathways, and competence feedback. Nature motivation's significant association with Sense of Purpose suggests that nature-based interpretive programming may simultaneously elevate both mechanisms, representing potentially high-leverage investment in indigenous settings. Third, the non-significance of Escape provides practical guidance: reducing arrival friction is worthwhile as a precondition but should not be positioned as a primary strategy for sustaining visitor value.
6.5 The Planned × Experienced interpretive framework
The Planned × Experienced DLP matrix should be interpreted as a theory-derived interpretive framework rather than a fully validated diagnostic dashboard. Its value lies in helping managers conceptually distinguish promise-side shortfalls (low Planned DLP: the destination's pre-visit signals are weak or unconvincing) from delivery-side shortfalls (low Experienced DLP: on-site value fades faster than expected). Its practical thresholds, predictive accuracy, and intervention effects require future validation before it can be recommended as a formal management tool.
Figure 2. Destination Length of Stay Performance (DLP) matrix illustration
Within these limitations, the four interpretive cells offer provisional guidance. High–High (both Planned and Experienced DLP elevated) indicates coherence between pre-visit promise and on-site delivery, suggesting a defend-and-scale orientation: maintain service standards and manage capacity. High–Low (Planned high, Experienced low) points toward over-promising: the intervention priority is operations, specifically redesigning experience sequencing and tightening communication to credible claims. Low–High (Planned low, Experienced high) indicates an under-marketed destination delivering well but communicating poorly, with the priority being improved discovery through pre-trip itinerary guidance and wider distribution. Low–Low requires focused experience redevelopment before any broad promotional investment (see Figure 2 for illustration).
This section distinguishes clearly between what the present study demonstrates and what remains to be established.
What the present study demonstrates: (a) initial development and validation of a two-dimensional DLP scale in an indigenous and logistically constrained destination context; (b) empirical distinctiveness of Planned and Experienced DLP as correlated but non-identical dimensions (ϕ = 0.24); (c) significant associations from Activity, Adventure, Intellectual, and Nature motivations through Curiosity and Sense of Purpose to Experienced DLP; and (d) the non-significance of Escape in both pathways, consistent with a threshold role.
What the present study does not yet demonstrate: full discriminant and incremental validity of DLP against satisfaction, experience quality, memorability, or revisit intention measured in the same study; full behavioral independence of Experienced DLP from actual LoS; the formal validity of the Planned × Experienced matrix with validated cut-points; or the generalizability of the findings to non-indigenous, non-constrained, or multi-cultural destination settings.
These limitations define a clear agenda for future research. A cross-sectional exit-survey design cannot capture how DLP evolves within the trip; longitudinal panels or experience sampling methods administered during the visit would provide greater temporal resolution. Replication across destination types with multi-group invariance testing would establish the scope conditions of the construct. A study simultaneously measuring DLP, satisfaction, experience quality, memorability, and time-extension intentions in a single model would provide the discriminant and incremental validity evidence needed to more fully justify DLP as a distinct construct.
The non-significance of Escape generates specific testable hypotheses: nonlinear threshold effects; indirect mediation through a decompression window; and moderation of other motivations by cognitive load levels at arrival. Finally, Planned DLP requires integration into a pre-visit structural model, with antecedents in marketing and communication and consequences for intended stay duration, through a longitudinal design that goes beyond the current study.
By shifting attention from the number of nights stayed to the perceived productivity of time, DLP offers a promising but still developing lens for understanding destination performance in constrained tourism settings. Future work integrating DLP with satisfaction, memorability, and behavioral outcomes will clarify the precise role of this construct within the broader tourism performance literature.
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