Integrating industrial engineering tools and behavioral modeling for optimizing operational efficiency in nature-based tourism services

Abstract

This study proposes a hybrid approach integrating behavioral modeling (PLS-SEM) and engineering diagnostics (Value Stream Mapping, Time Study, and Spaghetti Diagram) to evaluate and optimize service performance in nature-based tourism. Using survey data from 280 visitors to two West Java destinations, we test the effects of ergonomic design, service quality, technology integration, and environmental perception on operational efficiency, tourist satisfaction, and revisit intention. The structural model indicates that ergonomic design and environmental perception significantly enhance operational efficiency (ERG→OPE β = 0.404; ENV→OPE β = 0.552), which in turn strongly predicts satisfaction (OPE→SAT β = 0.944) and revisit intention (OPE→RI β = 0.619). The model shows substantial explanatory power (R²: OPE = 0.621; SAT = 0.891; RI = 0.383). Field diagnostics corroborate these findings: non-value-added time accounts for 38% of the end-to-end process, with notable delays at ticketing (+2.3 minutes vs standard) and route overlaps in high-density zones. Results suggest that environmental and ergonomic factors outperform technology and formal service attributes in driving outcomes within nature-based contexts. Theoretically, the study extends the S-O-R framework by positioning operational efficiency as a meso-level mediator linking physical stimuli to behavioral responses and bridging perception-based modeling with systems diagnostics. It provides actionable guidance for lean service redesign, wayfinding, and spatial reconfiguration to improve operational performance and visitor experience.