The research was published in Frontiers in Psychology on October 20, 2026. It combined partial least-squares structural equation modeling, or PLS-SEM, with fuzzy-set qualitative comparative analysis, or fsQCA. The former estimates the net statistical association of each motivational factor after accounting for the others; the latter identifies combinations of conditions associated with high sharing intention. This pairing was not intended to make two methods produce identical answers. Instead, it allowed the researchers to distinguish a motive’s independent relevance from its importance within a broader motivational mix.

Before the survey, researchers interviewed 24 active Douyin users, six each from Chengdu, Aba, Ganzi and Liangshan. Participants were aged 18–24, had basic awareness of intangible cultural heritage and had experience using the platform beyond simply watching videos. Two researchers independently coded their accounts for reasons, expected benefits, concerns, values and anticipated outcomes associated with sharing heritage knowledge. Seven domains from the Motives, Values, and Preferences Inventory emerged spontaneously and recurrently: aesthetic, affiliation, altruistic, commercial, hedonistic, recognition and tradition motives. Scientific, power and security motives were not spontaneously identified in the open-ended accounts, so they were not included in the quantitative model. Their exclusion reflects limited salience in this particular population, platform and behavioral context, not proof that they are irrelevant in every context.

The final online survey was conducted from July 30 to October 30, 2023. Of 500 questionnaires collected, 400 met eligibility and data-quality criteria, with exactly 100 respondents from each study region. Men represented 52.8% of the sample and women 47.3%; 83.8% were aged 18–21, while 16.3% were 22–24. Most, 74.0%, were college or university students. Recruitment used exponential non-discriminative snowball sampling through university associations, volunteer networks and cultural-interest groups on WeChat. Equal regional quotas balanced the analytical sample across the four areas, but they were not population-proportional and do not make the participants a representative sample of Sichuan’s youth.

All predictors and the outcome were measured in the same questionnaire. The measurement model showed indicator loadings from 0.719 to 0.911, Cronbach’s alpha values from 0.700 to 0.839, composite reliability values from 0.834 to 0.886 and average variance extracted values from 0.581 to 0.702. Every heterotrait–monotrait ratio was below the 0.90 discrimination criterion, with the highest, 0.866, occurring between altruistic motive and sharing intention. A Harman single-factor test attributed 32.68% of variance to the first unrotated factor, while full-collinearity VIF values ranged from 1.417 to 2.879, below the conservative threshold of 3.3. These diagnostics did not indicate substantial common-method bias, although post hoc statistical tests cannot completely exclude it.

In the PLS-SEM model, altruistic motive had the largest positive path coefficient, at 0.264, followed by aesthetic motive at 0.216 and recognition motive at 0.177. Commercial motive had a coefficient of 0.161, tradition motive 0.134 and affiliation motive 0.124; all were statistically significant. Hedonistic motive, by comparison, had a coefficient of 0.001 and a p-value of 0.484. Together, the seven motives explained 65.3% of the variance in intention to share intangible cultural heritage knowledge, with an adjusted R² of 0.646 and a Stone–Geisser Q² of 0.680. PLSpredict assessment also produced positive out-of-sample Q² values of 0.318–0.524 for the three outcome indicators, with lower prediction errors than the linear-model benchmark.

The fuzzy-set analysis produced a notably different picture. The researchers calibrated each condition using sample-relative anchors: the 95th percentile for full membership, the 50th for the crossover point and the 5th for full non-membership. A truth-table frequency threshold of three cases, raw-consistency threshold of 0.80 and PRI-consistency threshold of 0.80 led to nine sufficient configurations associated with high sharing intention. The overall solution consistency was 0.96 and solution coverage was 0.69. Individual configuration consistencies ranged from 0.96 to 0.97, but unique coverage was only 0.00–0.03, indicating substantial overlap among the pathways. No individual condition was necessary for high intention; tradition motive came closest, with a necessity consistency of 0.82, below the 0.90 criterion.

Several recurring patterns emerged. Some high-intention combinations joined affiliation, commercial and tradition motives; others paired aesthetic expression, altruism and cultural commitment with either enjoyment or recognition. Four configurations combined hedonistic and recognition motives with tradition, while a ninth included those two motives but treated tradition as a “do not care” condition. Tradition appeared in eight of the nine baseline configurations, followed by hedonistic motive in seven; aesthetic, altruistic, commercial and recognition motives each appeared in six, and affiliation appeared in five. These frequencies describe the configurations rather than ranking motives in isolation. Alternative calibration anchors and a stricter consistency threshold produced broadly consistent results, with only minor changes to individual configurations.

The contrast between the analyses is the study’s most notable result. Hedonistic motive was nearly irrelevant as an isolated net predictor yet recurrent in high-intention combinations, showing that a nonsignificant coefficient does not exclude configurational relevance. Tradition motive showed a modest positive coefficient and frequent appearance in configurations, but it was not necessary for the outcome. Altruistic motive had the strongest net association without appearing in every configuration, and one high-intention pathway explicitly included the absence of affiliation motive. The findings therefore support an equifinal account, in which different motivational combinations can be associated with the same strong intention to share.

Several limits constrain the conclusions. The data were cross-sectional and self-reported, so the results establish statistical and set-theoretic associations rather than causal effects or observed sharing. Intention was measured instead of actual posting, forwarding, commenting or sustained creator activity. The age range, four-region setting, single platform and non-probability recruitment also limit generalizability. The study did not directly measure algorithmic recommendation, platform affordances, cultural identity or perceived authenticity, and it did not test whether platform features alter motives or behavior. Longitudinal, experimental and behavioral research would be needed to determine whether these motivational combinations translate into durable heritage communication and whether they differ across platforms, age groups and cultural settings.

Subject of Research: Motives and motivational combinations associated with young adults’ intention to share intangible cultural heritage knowledge on Douyin

Article Title: Motivational predictors and configurations associated with youths’ intention to share intangible cultural heritage knowledge on Douyin: a PLS-SEM and fsQCA study

Article References: Hu, J., Noor, S. M., & Rasoolimanesh, S. M. (2026). Motivational predictors and configurations associated with youths’ intention to share intangible cultural heritage knowledge on Douyin: a PLS-SEM and fsQCA study. Frontiers in Psychology, 17, Article 1935285. https://doi.org/10.3389/fpsyg.2026.1935285

Image Credits: AI Generated

DOI: 10.3389/fpsyg.2026.1935285

Keywords: intangible cultural heritage, Douyin, young adults, knowledge sharing, motivation, PLS-SEM, fuzzy-set analysis, digital heritage, social media, short-video platforms, cultural communication, Motivational