A Standardized Field-Survey Protocol for Visitor Conservation Willingness and Self-Reported Responsible Travel Behavior at Longmen Grottoes

Summary

This protocol standardizes a minimum-disruption visitor survey at Longmen Grottoes by linking public-area interception, anonymous questionnaire administration, predefined screening, measurement validation, model checking, and reproducibility archiving.

Abstract

Heritage-site visitor surveys must generate usable behavioral evidence without disturbing site operations or weakening conservation priorities. However, recruitment boundaries, exclusion rules, measurement checks, model diagnostics, and data archiving are often incompletely reported in heritage tourism studies. This protocol presents a minimum-disruption field-survey workflow for measuring visitor conservation willingness and self-reported responsible travel behavior at Longmen Grottoes, Luoyang, China. The workflow integrates public-area visitor interception, anonymous electronic questionnaire administration, eligibility screening, attention checks, daily raw-data locking, predefined exclusion rules, construct scoring, reliability testing, confirmatory factor analysis, regression and path-model diagnostics, sensitivity checks, and reproducibility archiving. The questionnaire separates heritage knowledge, perceived heritage value, place attachment, pro-environmental message quality, perceived crowding, facility and service support, conservation attitude, conservation willingness, and self-reported responsible travel behavior. Representative implementation showed that the workflow produced an analyzable dataset with auditable exclusions, acceptable measurement diagnostics, and interpretable model outputs. The protocol is intended for heritage-site studies that need transparent visitor-behavior evidence rather than a single satisfaction measure. It can be adapted to other heritage settings by retaining the core procedural sequence while revising site-specific constructs, survey points, language versions, behavioral items, and fieldwork restrictions according to local conservation risks and visitor composition.

Introduction

Cultural heritage sites require visitor access for public education, cultural transmission, and tourism value, but visitor use can also place pressure on fragile material, spatial, and symbolic resources¹. This tension is especially visible at high-visitor-volume sites where movement routes are limited, interpretation areas are dense, and conservation rules must be understood during a short visit. Longmen Grottoes in Luoyang, China, provides an appropriate setting for a conservation-oriented visitor-survey workflow because it combines rock-carving heritage protection, public interpretation, visitor-flow management, and conservation education wi....

Protocol

The study was conducted in accordance with the Declaration of Helsinki and was approved by the SEGi Research Ethics Committee (Approval No. SEGiEC/SR/FOELPM/163/2025-2027) on 27 June 2025.Written or electronic informed consent was obtained before the questionnaire began.

NOTE: No names, identity card numbers, telephone numbers, facial images, home addresses, device identifiers, GPS coordinates, account identifiers, photographs, audio recordings, video recordings, or other directly identifiable information were collected. IP address collection was disabled before formal questionnaire release. No formal written site-management permission was ....

Results

Participant retention and fieldwork profile

A total of 480 questionnaires were obtained during formal fieldwork at Longmen Grottoes. After eligibility screening and data-quality checks, 430 questionnaires were retained for analysis, giving a valid-response rate of 89.6%. The final valid sample exceeded the pre-specified minimum requirement of 400 valid questionnaires. Excluded cases included eligibility failures, failed attention checks, fast completion, straight-lining or nea.......

Discussion

This protocol addresses a methodological problem in heritage tourism research: visitors may agree with heritage protection in principle, but their reported behavior during a visit is shaped by interpretation messages, route guidance, crowding pressure, facility support, and conservation rules at the same time. For Longmen Grottoes, the protocol therefore does not treat self-reported responsible travel behavior as a detached outcome. It places site-related perceptions, conservation attitude, conservation willingness, and .......

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
car (Regression diagnostic package)	Comprehensive R Archive Network	version 3.1–5	Used to calculate variance inflation factors and support regression diagnostics.
dplyr	Comprehensive R Archive Network	version 1.2.1	Data manipulation package; Used to filter valid cases, recode variables, create exclusion codes, calculate construct scores, and summarize fieldwork and model variables.
Electronic questionnaire platform	Wenjuanxing, Changsha Ranxing Information Technology Co., Ltd., Changsha, China		Web-based platform; registered-account access; accessed April–May 2026; Used to build the electronic questionnaire, set required-response fields, insert screening and attention-check items, generate the survey QR code, record completion time, and export raw responses in .xlsx format.
Field-administration tablet	Apple Inc., Cupertino, CA, USA		iPad, 10th generation; 10.9-inch display; 64 GB; Wi-Fi model; Used when participants completed the questionnaire on a research-team device at the survey point.
ggplot2	Comprehensive R Archive Network	version 4.0.3	Figure and diagnostic-plot package; Used to prepare diagnostic plots and figure source data when graphical statistical output was required.
lavaan	Comprehensive R Archive Network	version 0.7–2	Confirmatory-factor-analysis and path-model package; Used for the nine-factor confirmatory factor analysis, model-fit indices, standardized factor loadings, path model, and bootstrap indirect effects.
lm.beta	Comprehensive R Archive Network	version 1.7–3	Standardized regression package; Used to obtain standardized coefficients from linear regression models.
Microsoft Excel	Microsoft Corporation, Redmond, WA, USA	2021	Used for daily raw-file inspection, file naming, exclusion-log preparation, codebook preparation, and manual verification of .xlsx exports.
openxlsx	Comprehensive R Archive Network	version 4.2.8.1	Spreadsheet export package; Used to export cleaned datasets, codebooks, exclusion logs, reliability tables, correlation tables, regression outputs, and sensitivity-check tables.
Participant mobile-device access	Participant-owned smartphone or tablet	NA	Used when participants completed the questionnaire by scanning the QR code or opening the survey link on their own device.
psych	Comprehensive R Archive Network	version 2.6.5	Reliability and exploratory-factor-analysis package; Used to calculate Cronbach’s alpha, corrected item-total correlations, descriptive statistics, Kaiser-Meyer-Olkin value, Bartlett’s test, exploratory factor analysis, and Harman’s single-factor screen.
R Statistical computing environment	R Foundation for Statistical Computing, Vienna, Austria	version 4.6.1	Used for reliability testing, measurement diagnostics, descriptive statistics, regression analysis, path analysis, sensitivity checks, and output export.
readxl	Comprehensive R Archive Network	version 1.5.0	Spreadsheet import package; Used to import .xlsx raw data, codebooks, and exclusion logs into R.
semTools (Structural-equation-modeling utility package)	Comprehensive R Archive Network	version 0.5–9	Used to calculate composite reliability, average variance extracted, and HTMT values from the fitted measurement model.