Technological Capabilities and Institutional Pressures in Green Logistics Adoption: Evidence from an Emerging Economy's Freight Forwarding Sector

Authors

  • Erkan Duzgun School of Business, International University, Vietnam National University, Ho Chi Minh City, Vietnam Corresponding Author
  • Tuyen Thi Hoang Nguyen School of Business, International University, Vietnam National University, Ho Chi Minh City, Vietnam Author

DOI:

https://doi.org/10.47654/v30y2026i1p222-260

Keywords:

Green logistics adoption, Institutional pressures, Supply chain collaboration, Organizational size, Emerging markets, Structural equation modeling

Abstract

Purpose: This study examines how access to green technologies, institutional pressures, and supply chain collaboration influence green logistics adoption and organizational performance in Vietnam’s logistics industry. Motivated by inconsistent findings in prior sustainability research and concerns about model validity in emerging-market studies, the paper integrates the Resource-Based View and Institutional Theory to explain how internal capabilities and external constraints jointly shape sustainability outcomes.

Design/methodology/approach: Data were collected through a structured questionnaire survey, yielding 334 valid responses from logistics firms operating in Vietnam. Partial least squares structural equation modeling (PLS-SEM) using SmartPLS was employed to test direct, moderating, and mediating relationships, supported by bootstrapping. To enhance robustness and address spurious inference concerns, extensive diagnostic tests were conducted, and key results were cross-validated using covariance-based SEM (CB-SEM).

Findings: The results indicate that access to green technologies has a limited direct effect on green logistics adoption, whereas supply chain collaboration significantly enhances adoption and environmental awareness. Institutional pressures primarily influence organizational performance rather than operational adoption decisions. Moderation and mediation analyses show that organizational size and environmental awareness condition and partially transmit the effects of technological access and collaboration. By clarifying how organizational and institutional factors shape sustainability adoption under uncertainty, these findings provide evidence-based insights that support managerial and policy decision-making in Decision Sciences.

Theoretical implications: The study challenges technology-centric explanations of green logistics adoption by demonstrating that organizational and institutional mechanisms play a more decisive role in emerging markets, thereby extending sustainability and logistics theory through a combined moderation–mediation framework.

Practical implications: Logistics firms should complement green technology investments with organizational capability development and supply chain collaboration. Policymakers should strengthen institutional frameworks and support collaborative sustainability initiatives, particularly for small and medium-sized firms.

Originality/value: This study is among the first to integrate extended survey data, dual SEM estimation, comprehensive diagnostics, and moderation–mediation analysis to examine green logistics adoption in an emerging economy, offering robust empirical and methodological contributions to sustainability and decision sciences research.

References

Allen, S. D., Zhu, Q., & Sarkis, J. (2021). Expanding conceptual boundaries of the sustainable supply chain management and circular economy nexus. Cleaner Logistics and Supply Chain, 2, 100011. https://doi.org/10.1016/j.clscn.2021.100011

An, H., Razzaq, A., Nawaz, A., Noman, S. M., & Khan, S. A. R. (2021). Nexus between green logistic operations and triple bottom line: evidence from infrastructure-led Chinese outward foreign direct investment in Belt and Road host countries. Environmental Science and Pollution Research, 28(37). https://doi.org/10.1007/s11356-021-12470-3

Bag, S., Dhamija, P., Bryde, D. J., & Singh, R. K. (2022). Effect of eco-innovation on green supply chain management, circular economy capability, and performance of small and medium enterprises. Journal of Business Research, 141, 60–72. https://doi.org/10.1016/j.jbusres.2021.12.011

Barney, J. B. (2021). The Emergence of Resource-Based Theory: A Personal Journey. Journal of Management, 47(7), 014920632110152. https://doi.org/10.1177/01492063211015272

Benitez, J., Henseler, J., Castillo, A., & Schuberth, F. (2020). How to perform and report an impactful analysis using partial least squares: Guidelines for confirmatory and explanatory IS research. Information & Management, 57(2), 103168. https://doi.org/10.1016/j.im.2019.05.003

Boutabba, I., Pan, S.-H., & Wong, W.-K. (2024). An Empirical Validation of a Behavioral Finance Model:

The 52-week High as a Benchmark for an Index. Advances in Decision Sciences, 28(4), 74–91. https://doi.org/10.47654/v28y2024i4p74-91

Bouzari, M., Safavi, H. P., & Foroutan, T. (2022). Outcomes of environmental awareness. International Journal of Contemporary Hospitality Management, 34(10), 3655–3676. https://doi.org/10.1108/ijchm-11-2021-1412

Byrne, B. M. (2013). Structural Equation Modeling with Mplus. Routledge. https://doi.org/10.4324/9780203807644

Carifio, J., & Perla, R. (2008). Resolving the 50-year debate around using and misusing Likert scales. Medical Education, 42(12), 1150–1152. https://doi.org/10.1111/j.1365-2923.2008.03172.x

Centobelli, P., Cerchione, R., & Esposito, E. (2020a). Pursuing supply chain sustainable development goals through the adoption of green practices and enabling technologies: A cross-country analysis of LSPs. Technological Forecasting and Social Change, 153, 119920. https://doi.org/10.1016/j.techfore.2020.119920

Centobelli, P., Cerchione, R., Esposito, E., & Shashi. (2020b). Evaluating environmental sustainability strategies in freight transport and logistics industry. Business Strategy and the Environment, 29(3), 1563–1574. https://doi.org/10.1002/bse.2453

Chen, I. J., & Kitsis, A. M. (2017). A research framework of sustainable supply chain management. The International Journal of Logistics Management, 28(4), 1454–1478. https://doi.org/10.1108/ijlm-11-2016-0265

Chen, Y., Zhu, Q., & Sarkis, J. (2022). Green supply chain management practice adoption sequence: a cumulative capability perspective. International Journal of Production Research, 61(17), 1–16. https://doi.org/10.1080/00207543.2022.2118891

Cheng, Y., Hui, Y., Liu, S., & Wong, W.-K. (2022). Could significant regression be treated as insignificant: An anomaly in statistics? Communications in Statistics Case Studies Data Analysis and Applications, 8(1), 133–151. https://doi.org/10.1080/23737484.2021.1986171

Cheng, Y., Hui, Y., McAleer, M., & Wong, W.-K. (2021). Spurious Relationships for Nearly Non-Stationary Series. Journal of Risk and Financial Management, 14(8), 366. https://doi.org/10.3390/jrfm14080366

Cohen, J. (1988). Set Correlation and Contingency Tables. Applied Psychological Measurement, 12(4), 425–434. https://doi.org/10.1177/014662168801200410

Diamantopoulos, A., & Siguaw, J. A. (2006). Formative Versus Reflective Indicators in Organizational Measure Development: A Comparison and Empirical Illustration. British Journal of Management, 17(4), 263–282. https://doi.org/10.1111/j.1467-8551.2006.00500.x

Do, A. D., Nguyen, T. T. H., Nguyen, T. H. T., Nguyen, T. O., & Do, T. T. D. (2024). The Role of Infrastructure in Green Logistics Development: A Case Study of Vietnamese Logistics Enterprises. European Journal of Business and Management Research, 9(3), 135–141. https://doi.org/10.24018/ejbmr.2024.9.3.2358

Duzgun, E., & Atay, E. (2025). The moderating role of stakeholder involvement in GHRM-GSCM integration: Evidence from Vietnamese logistics firms. Journal of Open Innovation: Technology, Market, and Complexity, 11(2), 100562. https://doi.org/10.1016/j.joitmc.2025.100562

Duzgun, E., Duzgun, O., Phuong, N. N.-D., & Ty, N. N. (2024). Sustainable Economic Growth in Vietnam: Exploring Resilience, Global Integration, and Innovation in a Changing Landscape. Journal of Electrical Systems, 20(10s), 5482–5495. https://journal.esrgroups.org/jes/article/view/6373

El-Garaihy, W. H., Badawi, U. A., Seddik, W. A., & Torky, M. S. (2022). Investigating performance outcomes under institutional pressures and environmental orientation motivated green supply chain management practices. Sustainability, 14(3), 1523. https://doi.org/10.3390/su14031523

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104

Gerlitz, L., & Meyer, C. (2021). Small and Medium-Sized Ports in the TEN-T Network and Nexus of Europe’s Twin Transition: The Way towards Sustainable and Digital Port Service Ecosystems. Sustainability, 13(8), 4386. https://doi.org/10.3390/su13084386

Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2019). Multivariate Data Analysis. Kennesaw.edu. https://digitalcommons.kennesaw.edu/facpubs/2925/

Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://link.springer.com/article/10.1007/s11747-014-0403-8

Hooper, D., Coughlan, J., & Mullen, M. (2008). Evaluating model fit: a synthesis of the structural equation modelling literature. Google Books. https://books.google.com.vn/books?id=ZZoHBAAAQBAJ&lpg=PA195&ots=gX0RZsUr55&dq=Hooper%20-%20SEM%3A%20Guidelines%20for%20Determining%20Model%20Fit.%20Hooper&lr&pg=PA195#v=onepage&q=Hooper%20-%20SEM:%20Guidelines%20for%20Determining%20Model%20Fit.%20Hooper&f=false

Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55. https://doi.org/10.1080/10705519909540118

Hui, Y., Wong, W.-K., Bai, Z., & Zhu, Z.-Z. (2017). A new nonlinearity test to circumvent the limitation of Volterra expansion with application. Journal of the Korean Statistical Society, 46(3), 365–374. https://doi.org/10.1016/j.jkss.2016.11.006

International Energy Agency. (2024). Energy Efficiency Progress Tracker – Data Tools - IEA. IEA. https://www.iea.org/data-and-statistics/data-tools/energy-efficiency-progress-tracker

Jayarathna, C. P., Agdas, D., & Dawes, L. (2022). Exploring sustainable logistics practices toward a circular economy: A value creation perspective. Business Strategy and the Environment, 32(1). https://doi.org/10.1002/bse.3170

Kline, R. B. (2015). Principles and Practice of Structural Equation Modeling. In Google Books. Guilford Publications. https://books.google.com/books?hl=en&lr=&id=t2CvEAAAQBAJ&oi=fnd&pg=PP1&dq=Kline

Ko, W. W., Chen, Y., Chen, C.-H. S., Wu, M.-S. S., & Liu, G. (2021). Proactive Environmental Strategy, Foreign Institutional Pressures, and Internationalization of Chinese SMEs. Journal of World Business, 56(6), 101247. https://doi.org/10.1016/j.jwb.2021.101247

Kock, N. (2015). PLS-based SEM Algorithms: The Good Neighbor Assumption, Collinearity, and Nonlinearity. Information Management and Business Review, 7(2), 113–130. https://doi.org/10.22610/imbr.v7i2.1146

Lee, C.-W., Sohn, D.-G., Sang, M.-G., & Lee, C. (2025). Empirical Analysis of Barriers to Collaborative Information Sharing in Maritime Logistics Using Fuzzy AHP Approach. Sustainability, 17(4), 1721. https://doi.org/10.3390/su17041721

Lee, S.-Y. (2021). Sustainable Supply Chain Management, Digital-Based Supply Chain Integration, and Firm Performance: A Cross-Country Empirical Comparison between South Korea and Vietnam. Sustainability, 13(13), 7315. https://doi.org/10.3390/su13137315

Leung, T., Guan, J., & Lau, Y. (2023). Exploring environmental sustainability and green management practices: evidence from logistics service providers. Sustainability Accounting, Management and Policy Journal, 14(3). https://doi.org/10.1108/sampj-03-2022-0133

Li, J., Anser, M. K., Tabash, M. I., Nassani, A. A., Haffar, M., & Zaman, K. (2021). Technology- and logistics-induced carbon emissions obstructing the Green supply chain management agenda: evidence from 101 countries. International Journal of Logistics Research and Applications, 26(7), 1–25. https://doi.org/10.1080/13675567.2021.1985094

Liao, Z., Shi, X., & Wong, W.-K. (2012). Consumer Perceptions of the Smartcard in Retailing: An Empirical Study. Journal of International Consumer Marketing, 24(4), 252–262. https://doi.org/10.1080/08961530.2012.728503

Liao, Z., Shi, X., & Wong, W.-K. (2014). Key determinants of sustainable smartcard payment. Journal of Retailing and Consumer Services, 21(3), 306–313. https://doi.org/10.1016/j.jretconser.2014.02.001

Liao, Z., & Wong, W. K. (2008). The determinants of customer interactions with internet-enabled e-banking services. Journal of the Operational Research Society, 59(9), 1201–1210. https://doi.org/10.1057/palgrave.jors.2602429

Liu, J., Feng, Y., & Zhu, Q. (2021). Involving second-tier suppliers in Green supply chain management: drivers and heterogenous understandings by firms along supply chains. International Journal of Production Research, 61(14), 1–21. https://doi.org/10.1080/00207543.2021.2002966

Moslehpour, M., Altantsetseg, P., Mou, W., & Wong, W.-K. (2019). Organizational Climate and Work Style: The Missing Links for Sustainability of Leadership and Satisfied Employees. Sustainability, 11(1), 125. https://doi.org/10.3390/su11010125

Moslehpour, M., Pham, V., Wong, W.-K., & Bilgiçli, İ. (2018). e-Purchase Intention of Taiwanese Consumers: Sustainable Mediation of Perceived Usefulness and Perceived Ease of Use. Sustainability, 10(1), 234. https://doi.org/10.3390/su10010234

Moslehpour, M., Wong, W.-K., Lin, Y. H., & Le Huyen Nguyen, T. (2017). Top purchase intention priorities of Vietnamese low cost carrier passengers: expectations and satisfaction. Eurasian Business Review, 8(4), 371–389. https://doi.org/10.1007/s40821-017-0093-5

Nazir, S., Zhaolei, L., Mehmood, S., & Nazir, Z. (2024). Impact of Green Supply Chain Management Practices on the Environmental Performance of Manufacturing Firms Considering Institutional Pressure as a Moderator. Sustainability, 16(6), 2278. MDPI. https://doi.org/10.3390/su16062278

Nguyen, X., & Le, T. (2020). The impact of global green supply chain management practices on performance: The case of Vietnam. Uncertain Supply Chain Management, 8(3), 523–536. http://growingscience.com/beta/uscm/3927-the-impact-of-global-green-supply-chain-management-practices-on-performance-the-case-of-vietnam.html

Norman, G. (2010). Likert scales, levels of measurement and the “laws” of statistics. Advances in Health Sciences Education, 15(5), 625–632. https://doi.org/10.1007/s10459-010-9222-y

Ouni, M., & Abdallah, K. B. (2024). Environmental sustainability and green logistics: Evidence from BRICS and Gulf countries by cross‐sectionally augmented autoregressive distributed lag (CS‐ARDL) approach. Sustainable Development, 32(4). https://doi.org/10.1002/sd.2856

Patel, A. B., & Desai, T. N. (2018). A systematic review and meta-analysis of recent developments in sustainable supply chain management. International Journal of Logistics Research and Applications, 22(4), 349–370. https://doi.org/10.1080/13675567.2018.1534946

Pham, V. K., Wong, W.-K., Moslehpour, M., & Musyoki, D. (2018). Simultaneous Adaptation of AHP and Fuzzy AHP to Evaluate Outsourcing Service in East and Southeast Asia. Journal of Testing and Evaluation, 48(2), 1594–1614. https://doi.org/10.1520/JTE20170420

Phung, T. B. P., Kim, S., & Chu, C. C. (2022). Transformational leadership, integration and supply chain risk management in Vietnam’s manufacturing firms. The International Journal of Logistics Management, 34(1). https://doi.org/10.1108/ijlm-06-2021-0317

Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40(3), 879–891. https://doi.org/10.3758/BRM.40.3.879

Razzak, M. R. (2022). Mediating effect of productivity between sustainable supply chain management practices and competitive advantage: evidence from apparel manufacturing in Bangladesh. Management of Environmental Quality: An International Journal, 34(2). https://doi.org/10.1108/meq-01-2022-0022

Roy, S., & Mohanty, R. P. (2023). Green logistics operations and its impact on supply chain sustainability: An empirical study. Business Strategy and the Environment, 33(4). https://doi.org/10.1002/bse.3531

Samper, M. G., Florez, D. G., Borre, J. R., & Ramirez, J. (2022). Industry 4.0 for sustainable supply chain management: Drivers and barriers. Procedia Computer Science, 203, 644–650. https://doi.org/10.1016/j.procs.2022.07.094

Sanusi, F. A., & Johl, S. K. (2022). Sustainable internal corporate social responsibility and solving the puzzles of performance sustainability among medium size manufacturing companies: An empirical approach. Heliyon, 8(8), e10038. https://doi.org/10.1016/j.heliyon.2022.e10038

Sarstedt, M., Hair, J. F., Pick, M., Liengaard, B. D., Radomir, L., & Ringle, C. M. (2022). Progress in partial least squares structural equation modeling use in marketing research in the last decade. Psychology & Marketing, 39(5). https://doi.org/10.1002/mar.21640

Sharma, M., Luthra, S., Joshi, S., Kumar, A., & Jain, A. (2022). Green Logistics Driven Circular Practices Adoption in Industry 4.0 Era: a Moderating Effect of Institution Pressure and Supply Chain Flexibility. Journal of Cleaner Production, 383, 135284. https://doi.org/10.1016/j.jclepro.2022.135284

Sharma, S., Mukherjee, S., Kumar, A., & Dillon, W. R. (2005). A simulation study to investigate the use of cutoff values for assessing model fit in covariance structure models. Journal of Business Research, 58(7), 935–943. https://doi.org/10.1016/j.jbusres.2003.10.007

Stefanelli, N. O., Chiappetta Jabbour, C. J., Liboni Amui, L. B., Caldeira de Oliveira, J. H., Latan, H., Paillé, P., & Hingley, M. (2021). Unleashing proactive low‐carbon strategies through behavioral factors in biodiversity‐intensive sustainable supply chains: Mixed methodology. Business Strategy and the Environment, 30(5), 2535–2555. https://doi.org/10.1002/bse.2762

Tetteh, F. K., Kwateng, K. O., & Mensah, J. (2024). Green logistics practices: A bibliometric and systematic methodological review and future research opportunities. Journal of Cleaner Production, 476, 143735–143735. https://doi.org/10.1016/j.jclepro.2024.143735

Thi Binh An, D., Nguyen, T. T. B., & Truong Quang, H. (2024). Service-oriented supply chain: what do we know about its risks?. International Journal of Logistics Research and Applications, 27(11), 2021-2048. https://doi.org/10.1080/13675567.2024.2319757

Varghese, A. M., & Pradhan, R. P. (2025). Transportation infrastructure and economic growth: Does there exist causality and spillover? A Systematic Review and Research Agenda. Transportation Research Procedia, 82, 2618–2632. https://doi.org/10.1016/j.trpro.2024.12.208

Vo, H. V., & Nguyen, N. P. (2023). Greening the Vietnamese supply chain: The influence of green logistics knowledge and intellectual capital. Heliyon, 9(5), e15953–e15953. https://doi.org/10.1016/j.heliyon.2023.e15953

Wang, J., Lim, M. K., Wang, C., & Tseng, M.-L. (2022). Comprehensive analysis of sustainable logistics and supply chain based on bibliometrics: overview, trends, challenges, and opportunities. International Journal of Logistics Research and Applications, 26(10), 1–30. https://doi.org/10.1080/13675567.2022.2052823

Wang, Y., Yang, Y., Qin, Z., Yang, Y., & Li, J. (2023). A literature review on the application of digital technology in achieving green supply chain management. Sustainability, 15(11), 8564. https://doi.org/10.3390/su15118564

Wong, W.-K., Cheng, Y., & Yue, M. (2024). Could Regression of Stationary Series Be Spurious? Asia Pacific Journal of Operational Research, 2024. https://doi.org/10.1142/s0217595924400177

Wong, W.-K., & Pham, M. T. (2022). Could the test from the standard regression model could make significant regression with autoregressive noise become insignificant? The International Journal of Finance, 34, 1–18.

Yan, X., Liu, W., Lim, M. K., Lin, Y., & Wei, W. (2022). Exploring the factors to promote circular supply chain implementation in the smart logistics ecological chain. Industrial Marketing Management, 101, 57–70. https://doi.org/10.1016/j.indmarman.2021.11.015

Yu, H., & Li, Z. (2024). Organizational green culture and employees’ green behavior: a moderated mediation model with employees’ environmental awareness and organizational disseminative capacity. Service Industries Journal/the Service Industries Journal, 45(11-12), 1–23. https://doi.org/10.1080/02642069.2024.2379013

Zhao, X., Lynch, J. G., & Chen, Q. (2010). Reconsidering Baron and Kenny: Myths and Truths about Mediation Analysis. Journal of Consumer Research, 37(2), 197–206.

Zhu, S., & Liu, L. (2025). Green institutional investors and corporate green innovation: Evidence from Chinese listed companies. International Review of Economics & Finance, 103, 104476. https://doi.org/10.1016/j.iref.2025.104476

Published

2026-03-14

How to Cite

Duzgun, E., & Nguyen, T. T. H. (2026). Technological Capabilities and Institutional Pressures in Green Logistics Adoption: Evidence from an Emerging Economy’s Freight Forwarding Sector. Advances in Decision Sciences, 30(1), 222-260. https://doi.org/10.47654/v30y2026i1p222-260