Autor(s): Tatan Sukwika, Lidya Fransisca
DOI: 10.20886/ijfr.2021.8.2.135-157


Developing and maintaining forest sustainably is a way to support sustainable development. From the technical point of view, the sustainability of community forest could be articulated not only based on the three aspects i.e. economic (ECO), social culture (SOC), ecology (EGY), but it can also include dimensions of legal & institutional (LIT), and accessibility & technology (ACT). This study aims to determine variables of sustainability dimensions that have a direct positive effect on the sustainability of the community forests (SCF), to identify variables that affect SCF and variables of sustainability dimensions that have  dominant effect on SCF. This study employed 70 samples of forest farmers’ group in Bogor regency. The respondents were purposively selected based on consideration of the criteria for forest farmer groups namely beginner, intermediate, and advanced. The Analysis tools used PLS-SEM. Sustainability dimensions of ECO, EGY, LIT, and ACT have a significant positive direct effect on SCF. The mediational hypothesis testing suggested that there is a partial mediation from ECO and EGY to SCF, which is consistent and have a positive value. Based on the coefficient value of the total-effect, among the five dimensions, ecology value was the biggest and the most robust. The policy implies that the ecological aspects considered the importance and strategy. Therefore, the value and productivity of the community forest structure and composition need to be maintained.


Direct-indirect effect; effect mediation-total; PLS-SEM; sustainability

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Afanadorac, N. L., Tranb, T. N., & Buydensc, M. C. (2013). Use of the bootstrap and permutation methods for a more robust variable importance in the projection metric for partial least squares regression. Analytica Chimica Acta, 768, 49-56. doi:10.1016/j.aca.2013.01.004

Ali, Z., & Bhaskar, S. B. (2016). Basic statistical tools in research and data analysis. Indian Journal of Anaesthesia, 60(9), 662-669. doi:10.4103/0019-5049.190623

AmirKhali, S. S. (2013). Predictive efficiency of random effects approach: A real model simulation study. Journal of Business & Economics Research, 11(11), 1-6.

Apipoonyanon, C., Kuwornu, J. K. M., Szabo, S., & Shrestha, R. P. (2020). Factors influencing household participation in community forest management: evidence from Udon Thani Province, Thailand. Journal of Sustainable Forestry, 39(2), 184-206. doi:10.1080/10549811.2019.1632211

Baral, S., Gautam, A. P., & Vacik, H. (2018). Ecological and economical sustainability assessment of community forest management in Nepal: A reality check. Journal of Sustainable Forestry, 37(8), 820-841. doi:10.1080/10549811.2018.1490188

Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173-1182.

Bryman, A., & Bell, E. (2007). The nature of qualitative research. In Business Research Methods (pp. 402-437). New York: Oxford University Press.

Carrión, G. C., Nitzl, C., & Roldán, J. L. (2017). Mediation analyses in partial least squares structural equation modeling: Guidelines and empirical examples. In H. Latan & R. Noonan (Eds.), Partial Least Squares Path Modeling: Basic Concepts, Methodological Issues and Applications (pp. 173-195). Cham: Springer International Publishing.

Cham, H., West, S. G., Ma, Y., & Aiken, L. S. (2012). Estimating Latent Variable Interactions With Non-Normal Observed Data: A Comparison of Four Approaches. Multivariate behavioral research, 47(6), 840-876. doi:10.1080/00273171.2012.732901

Chernick, M. R. (2011). Bootstrap methods: A guide for practitioners and researchers. New York: John Wiley & Sons, Inc.

Cheung, G. W., & Lau, R. S. (2007). Testing mediation and suppression effects of latent variables: Bootstrapping with structural equation models. Organizational Research Methods, 11(2), 296-325. doi:10.1177/1094428107300343

Costa, C., Menesatti, P., & Spinelli, R. (2012). Performance modelling in forest operations through partial least square regression. Silva Fennica, 46(2), 241-252.

Dawson, J. F. (2014). Moderation in management research: What, why, when, and how. Journal of business and psychology, 29(1), 1-19.

Eisingerich, A. B., & Rubera, G. (2010). Drivers of Brand Commitment: A CrossNational Investigation. Journal of International Marketing, 18(2), 64-79. doi:10.1509/jimk.18.2.64

Ekanayake, E. M. B. P., Xie, Y., Ahmad, S., Geldard, R. P., & Nissanka, A. H. S. (2020). Community Forestry for livelihood Improvement: evidence from the intermediate zone, Sri lanka. Journal of Sustainable Forestry, 1-17. doi:10.1080/10549811.2020.1794906

Fritz, M. S., Taylor, A. B., & Mackinnon, D. P. (2012). Explanation of two anomalous results in statistical mediation analysis. Multivariate Behavioral Research, 47, 61-87. doi:10.1080/00273171.2012

G-Assembly. (2005). World Summit Outcome : resolution / adopted by the General Assembly on 16 September 2005. (A/RES/60/1). UN General Assembly Retrieved from

Ghozali, & Latan. (2015a). Partial Least Squares (Konsep, Teknik, dan Aplikasi Menggunakan Program SmartPLS 3.0) Untuk Penelitian Empiris. Semarang: Badan Penerbit Undip.

Ghozali, & Latan. (2015b). Partial least squares: Concepts, techniques and applications using SmartPLS 3 (2 ed.). Semarang: Diponegoro University Press.

Goodhue, D. L., Lewis, W., & Thompson, R. (2012). Does PLS have advantages for small sample size or non-normal data? MIS quarterly, 36(3), 981-1001. doi:10.2307/41703490

Hair, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM): Sage Publications.

Hair, J. F., Ringle, C. M., & Sarstedt, M. (2012). Partial least squares: the better approach to structural equation modeling? doi:

Hair, J. F., Ringle, C. M., & Sarstedt, M. (2013). Partial least squares structural equation modeling: Rigorous applications, better results and higher acceptance. doi:

Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24. doi:10.1108/EBR-11-2018-0203

Hair, J. F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2014). Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research. European Business Review, 26(2). doi:10.1108/EBR-10-2013-0128

Hair, J. F., Sarstedt, M., Ringle, C. M., & Gudergan, S. P. (2017). Advanced issues in partial least squares structural equation modeling: SAGE Publications.

Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach (1st ed.). New York: The Guilford Press.

Hayes, A. F., & Rockwood, N. J. (2016). Regression-based statistical mediation and moderation analysis in clinical research: Observations, recommendations, and implementation. Behaviour Research and Therapy, 98, 39-57. doi:10.1016/j.brat.2016.11.001

Hayes, A. F., & Scharkow, M. (2013). The relative trustworthiness of inferential tests of the indirect effect in statistical mediation analysis: Does method really matter? Psychological Science, 24, 1918-1927. doi:10.1177/0956797613480187

Holland, S. J., Shore, D. B., & Cortina, J. M. (2016). Review and recommendations for integrating mediation and moderation. Organizational Research Methods, 20(4), 686-720. doi:10.1177/1094428116658958

Karazsia, B. T., Berlin, K. S., Armstrong, B., Janicke, D. M., & Darling, K. E. (2013). Integrating mediation and moderation to advance theory development and testing. J Pediatr Psychol., 39(2), 163-173. doi:10.1093/jpepsy/jst080

Kenny, D. A. (2008). Reflections on mediation. Organisational Research Methods, 11(2), 353-358.

Kenny, D. A., & Judd, C. M. (2014). Power anomalies in testing mediation. Psychological Science, 25(2), 334-339. doi:10.1177/0956797613502676

Kock, N. (2014). Stable P value calculation methods in PLS-SEM. Laredo, TX: ScriptWarp Systems.

Kock, N., & Hadaya, P. (2018). Minimum sample size estimation in PLS‐SEM: The inverse square root and gamma‐exponential methods. Information Systems Journal, 28(1), 227-261. doi:10.1111/isj.12131

Kusmana, C., & Sukwika, T. (2018). Coastal community preference on the utilization of mangrove ecosystem and channelbar in Indramayu, Indonesia. AACL Bioflux, 11(3), 905-918.

MacKinnon, D., Coxe, S., & Baraldi, A. N. (2012). Guidelines for the investigation of mediating variables in business research. Journal of Business Psychology, 27, 1-14. doi:10.1007/s10869-011-9248-z

MacKinnon, D., Lockwood, C. M., Hoffman, J. M., West, S. G., & Sheets, V. (2002). A comparison of methods to test mediation and other intervening variable effects. Psychological Methods, 7, 83-104.

Malhotra, N. K. (2017). Marketing Research : An applied approach. Harlow: Pearson Education Limited.

Maslowsky, J., Jager, J., & Hemken, D. (2015). Estimating and interpreting latent variable interactions: A tutorial for applying the latent moderated structural equations method. International journal of behavioral development, 39(1), 87-96. doi:10.1177/0165025414552301

Memon, M. A., Cheah, J.-H., & Ramayah, T. (2018). Mediation analysis issues and recommendations. Journal of Applied Structural Equation Modeling, 2(1), 1-9.

Montoya, A. K. (2019). Moderation analysis in two-instance repeated measures designs: Probing methods and multiple moderator models. Behav Res Methods., 51(1), 61-82. doi:10.3758/s13428-018-1088-6

Muller, D. (2013). Design characteristics of virtual learning environments: A theoretical integration and empirical test of technology acceptance and is success research. Saarbrücken: Springer Gabler.

Munasinghe, M. (1992). Environmental economics and sustainable development. Paper presented at the UN Earth Summit, Rio de Janeiro.

Musyoki, J. K., Mugwe, J., Mutundu, K., & Muchiri, M. (2016). Factors influencing level of participation of community forest associations in management forests in Kenya. Journal of Sustainable Forestry, 35(3), 205-216. doi:10.1080/10549811.2016.1142454

Namazi, M., & Navid-Reza, N. (2016). Conceptual analysis of moderator and mediator variables in business research. Economics and Finance, 36, 540-554. doi:10.1016/S2212-5671(16)30064-8

Nitzl, C., Roldan, J. L., & Cepeda, G. (2016). Mediation analysis in partial least squares path modelling: Helping researchers discuss more sophisticated models. Industrail Management & Data Systems, 116(9), 1849-1864. doi:10.1108/IMDS-07-2015-0302

Paul, E. J. (2013). Doing statistical mediation and moderation (methodology in the social sciences) (1st ed.). New York: Guilford Press.

Preacher, K., & Hayes, A. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior research methods, 40, 879-891. doi:10.3758/BRM.40.3.879

Preacher, K. J., & Hayes, A. F. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Research Methods, Instruments, & Computers, 36(4), 717-731.

Sarstedt, M., Ringle, C. M., & Hair, J. F. ( 2017). Partial least squares structural equation modeling. In C. H. e. al. (Ed.), Handbook of Market Research (pp. 41). New York: Springer International Publishing AG.

Singh, A. S., & Masuku, M. B. (2014). Sampling techniques and determination of sample size in applied statistics research: An overview. International Journal of Economics, Commerce and Management, 2(11), 1-22.

Sukwika, T., Darusman, D., Kusmana, C., & Nurrochmat, D. R. (2016). Evaluating the level of sustainability of privately managed forest in Bogor, Indonesia. Biodiversitas, Journal of Biological Diversity, 17(1), 241-248. doi:10.13057/biodiv/d170135

Sukwika, T., Darusman, D., Kusmana, C., & Nurrochmat, D. R. (2018). Policy scenarios for managing of sustainability private-forests in Bogor regency. Journal of Natural Resources and Environmental Management, 8(2), 207-215. doi:10.29244/jpsl.8.2.207-215

Sukwika, T., Yusuf, D. N., & Suwandhi, I. (2020). The institutional of local community and stratification of land ownership in surrounding community forests in Bogor. Jurnal Manajemen Hutan Tropika, 26(1), 59-71. doi:10.7226/jtfm.26.1.59

Taber, K. S. (2016). The use of cronbach’s alpha: When developing and reporting research instruments in science education. Research in Science Education, 2(2), 1-24. doi:10.1007/s11165-016-9602-2

Tadesse, S. A., & Teketay, D. (2020). Determinant Factors Predicting the Dependencies of Local Communities on Plantation Forests and Their Levels of Participation on Management Activities in Basona Worena District, Ethiopia. Journal of Sustainable Forestry, 39(8), 800-826. doi:10.1080/10549811.2020.1730907

Tenenhaus, M., Vinzi, V. E., Chatelin, Y. M., & Lauro, C. (2005). PLS path modeling. Computational Statistics & Data Analysis, 48(1), 159-205. doi:10.1016/j.csda.2004.03.005

Thoemmes, F., MacKinnon, D. P., & Reiser, M. R. (2010). Power analysis for complex mediational designs using Monte Carlo methods. Structural Equation Modeling, 17, 510-534.

Turnes, P. B., & Ernst, R. (2015). Strategies to measure direct and indirect effects in multi-mediator models. Business Review, 14(10), 504-514. doi:10.17265/1537-1514/2015.10.003

Ullman, J. B., & Bentler, P. M. (2013). Structural equation modeling. In I. B. Weiner (Ed.), Handbook of Psychology (Second ed., pp. 661-690). New York: John Wiley & Sons, Inc.

Ursachi, G., Horodnic, I. A., & Zait, A. (2015). How reliable are measurement scales? External factors with indirect influence on reliability estimators. Economics and Finance, 20, 679-686. doi:10.1016/S2212-5671(15)00123-9

Valentini, F., & Damasio, B. F. (2016). Average variance extracted and composite reliability: Reliability coefficients. Psicologia: Teoria e Pesquisa, 32(2), 1-7. doi:10.1590/0102-3772e322225

Van Gossum, P., Arts, B., De Wulf, R., & Verheyen, K. (2011). An institutional evaluation of sustainable forest management in Flanders. Land use policy, 28(1), 110-123. doi:10.1016/j.landusepol.2010.05.005

Vinzi, V. E., Chin, W. W., Henseler, J., & Wang, H. (2010). Handbook of partial least squares: Concepts, methods and applications: Springer Publishing Company, Incorporated.

Yamane, T. (1967). Statistics: An introductory analysis (2nd ed.). New York: Harper and Row.

Yzerbyt, V., Muller, D., Batailler, C., & Judd, C. M. (2018). New recommendations for testing indirect effects in mediational models: The need to report and test component paths. Journal of Personality and Social Psychology, 115(6), 929-943. doi:10.1037/pspa0000132


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