Sustainable supply chain, digital transformation, and blockchain technology adoption in the tourism sector

Globalization and technological advancement have intensified environmental pressures, prompting firms—especially in tourism—to adopt sustainability-oriented strategies. The tourism sector’s environmental footprint and heightened stakeholder expectations necessitate sustainable supply chain approaches to reduce waste and enhance operational transparency. Despite widespread interest, traditional supply chain strategies often fail to mitigate environmental degradation fully, motivating firms to innovate through sustainable supply chain strategies (SSCS) and to leverage digital technologies. Blockchain technology (BCT) has emerged as a prominent tool to support sustainable practices by enhancing transparency, trust, and efficiency across complex tourism supply chains. As digitalization reshapes operations, hotels increasingly adopt technologies that improve services, processes, and performance, contributing to sustainable competitive advantage (SCA). Addressing gaps in prior research, this study investigates how SSCS influences SCA via BCT adoption as a mediator, and how digital transformation (DT) and sustainable supply chain practices (SSCP) moderate key relationships. The research focuses on hotels and resorts, where misalignment between IT and business strategies underscores the need for digital transformation to achieve sustainable competitiveness. The study offers a sustainability-technology model for tourism, extending understanding of BCT’s strategic role and informing managers and policymakers seeking to improve competitiveness through sustainable strategies and technologies.

The study develops a theoretical model grounded in the Technology-Organization-Environment (TOE) framework and Resource-Based View (RBV). TOE explains organizational adoption of technological innovations in context, emphasizing alignment of technology (e.g., BCT) with sustainable strategy to enable long-term advantage. RBV posits that valuable, rare, inimitable, and non-substitutable resources and capabilities (including BCT-related competencies) underpin sustained competitive advantage. The literature links SSCS to improved environmental and competitive performance by streamlining operations and proactively adapting to ecological challenges, particularly salient in competitive hotel markets. SSCS is proposed to directly enhance SCA (H1). SSCS is also seen as a driver of BCT adoption, as sustainability goals spur firms to integrate digital innovations that improve efficiency, traceability, and productivity (H2). BCT adoption itself is theorized to bolster SCA through transparency, data security, and process improvements in tourism supply chains (H3). BCT adoption is posited to mediate SSCS’s effect on SCA by translating strategic sustainability intent into operational capabilities and competitive outcomes (H3a). DT is expected to strengthen SSCS’s impact on BCT adoption by providing the digital infrastructure and competencies that facilitate technology assimilation (H4, H4a). SSCP are proposed to directly enhance SCA and to amplify the effect of BCT adoption on SCA by providing a supportive set of practices that allow blockchain capabilities to create value (H5, H5a). Collectively, the framework posits: H1 SSCS → SCA; H2 SSCS → BCT adoption; H3 BCT adoption → SCA; H3a BCT mediates SSCS → SCA; H4 DT → BCT adoption; H4a DT moderates SSCS → BCT adoption; H5 SSCP → SCA; H5a SSCP moderates BCT adoption → SCA.

Design and sampling: A time-lagged survey design was employed to reduce common method bias. Convenience sampling targeted managers working in hotels and resorts. Data were collected in three waves separated by approximately 2–3 weeks: Time 1 measured SSCS and DT; Time 2 measured BCT adoption and SSCP; Time 3 measured SCA. Of 550 managers contacted at Time 1, 480 usable responses were obtained (87%). At Time 2, 395 complete responses were received (82% of Time 1 respondents). At Time 3, 331 complete responses were received (overall response rate 60%). The final sample included 331 managers (178 male, 153 female). Age distribution: 19–30 (13%), 31–40 (26%), 41–50 (24.8%), 51–60 (21.5%), over 60 (14.8%). Education: Intermediate (21.5%), Bachelor (30.8%), Master (33.2%), MPhil/Others (14.5%). Marital status: Single (17.2%), Married (82.8%). Measures: SSCS was measured with three items from Nayal et al. (2022). BCT adoption used three items from Wamba et al. (2020) (e.g., resource investment in blockchain-enabled supply chain applications). SCA used a five-item scale from Nayal et al. (2022) (e.g., digital technology and coordination enhance process effectiveness and flexibility). DT and SSCP were measured using a seven-item scale (Nayal et al., 2022) and a five-item scale (Gopal and Thakkar, 2016), respectively. All items used five-point Likert scales (strongly disagree to strongly agree), except SSCP using a 1 (not implemented) to 5 (fully implemented) implementation scale. Analyses: Common method bias was assessed using Harman’s single-factor test; one-factor variance was 8.653% (<50%), indicating no substantial bias. Measurement model reliability and validity were assessed via Cronbach’s alpha, composite reliability (CR), average variance extracted (AVE), and Fornell-Larcker discriminant validity. Structural equation modeling (SEM) with AMOS tested hypotheses. Model fit indices indicated excellent fit: χ2=243.639, df=220, χ2/df=1.107, RMSEA=0.018, SRMR=0.0279, NFI=0.957, IFI=0.996, TLI=0.995, CFI=0.996. Reliability/validity: All factor loadings >0.704; alphas and CRs ≥0.876; AVEs ≥0.664 across constructs (SSCS, SSCP, SCA, BCT adoption, DT). Discriminant validity was confirmed (square roots of AVEs exceeded inter-construct correlations). Descriptive statistics indicated means around 3.3–3.6 with moderate variability (SD ~1.1–1.26).

- Direct effects (SEM): SSCS → SCA: β=0.374, SE=0.051, t=7.333, p<0.001 (H1 supported). SSCS → BCT adoption: β=0.537, SE=0.062, t=8.661, p<0.001 (H2 supported). BCT adoption → SCA: β=0.370, SE=0.065, t=5.692, p<0.001 (H3 supported). DT → BCT adoption: β=0.202, SE=0.075, t=2.693, p<0.05 (H4 supported). SSCP → SCA: β=0.251, SE=0.078, t=3.218, p<0.01 (H5 supported). - Mediation: SSCS → BCT adoption → SCA: indirect effect β=0.199, SE=0.036, t=5.455, p<0.001 (H3a supported), indicating BCT adoption mediates the SSCS–SCA relationship. - Moderation: DT moderates SSCS → BCT adoption: interaction β=0.169, SE=0.076, t=2.223, p<0.05 (H4a supported). Conditional effects of SSCS on BCT adoption at DT levels: +1 SD β=0.651 (Boot SE=0.079, 95% CI [0.496, 0.805]); Mean β=0.518 (0.053, [0.412, 0.623]); −1 SD β=0.384 (0.060, [0.267, 0.501]). SSCP moderates BCT adoption → SCA: interaction β=0.149, SE=0.065, t=2.292, p<0.01 (H5a supported). Conditional effects of BCT adoption on SCA at SSCP levels: +1 SD β=0.666 (Boot SE=0.070, 95% CI [0.527, 0.804]); Mean β=0.552 (0.048, [0.456, 0.647]); −1 SD β=0.434 (0.051, [0.337, 0.538]). - Model explanatory power: R²: BCT adoption=0.346; SCA=0.514. - Overall, all hypothesized relationships (H1–H5, including H3a, H4a, H5a) were supported. The findings show that SSCS enhances SCA both directly and indirectly via BCT adoption; DT strengthens the SSCS→BCT link, and SSCP both directly improves SCA and amplifies the BCT→SCA relationship.

The study demonstrates that a robust sustainable supply chain strategy (SSCS) is a critical antecedent of sustainable competitive advantage (SCA) in the hotel and tourism sector. SSCS not only directly improves competitiveness through efficiency, resource stewardship, and stakeholder alignment, but also catalyzes the adoption of blockchain technology (BCT), which further enhances transparency, data security, and supply chain coordination. The mediation results clarify the mechanism through which SSCS translates into SCA: by fostering BCT capacities that deliver operational and strategic benefits. Digital transformation (DT) acts as an enabling condition that strengthens the effect of SSCS on BCT adoption, reflecting how digital infrastructure and capabilities help embed new technologies into supply chain processes. Sustainable supply chain practices (SSCP) both contribute directly to SCA and increase the returns from BCT adoption, indicating that practices such as eco-design and lean processes create an environment where blockchain-enabled capabilities can more effectively generate competitive value. These findings extend RBV by highlighting sustainable and digital resources as sources of inimitable competitive advantages and inform TOE by illustrating context-specific adoption dynamics in tourism supply chains.

This study advances sustainable supply chain management and technology adoption research in tourism by empirically validating a model linking SSCS, DT, BCT adoption, SSCP, and SCA. SSCS has significant direct and indirect effects on SCA, with BCT adoption mediating the SSCS–SCA relationship. DT significantly moderates the SSCS–BCT adoption link, and SSCP significantly moderates the BCT adoption–SCA link while also directly enhancing SCA. The results suggest that firms should integrate sustainability-focused strategies with digital transformation and blockchain capabilities, supported by robust sustainable practices, to achieve and sustain competitive advantage in dynamic market conditions. Future research should further unpack contextual and organizational factors that influence adoption pathways and performance impacts across diverse tourism settings.

- The study focuses on firms’ sustainable supply chain practices without incorporating consumers’ perceptions; future work should include customer perspectives given close firm–consumer linkages in tourism. - The research uses a survey design; case studies or mixed methods could provide deeper insights into supply chain issues and implementation processes. - While blockchain adoption is modeled as a mediating mechanism, potential organizational capabilities or barriers that affect efficiency could be examined as moderators. - Convenience sampling in a specific sector and geography may limit generalizability; broader, cross-country samples could enhance external validity.