The Consequences of Illegal Mining in the Environment: Perspectives Behavioral, Knowledge and Attitude
DOI:
https://doi.org/10.55151/ijeedu.v1i1.10Keywords:
Activities Sustainably, Lawrence Green's Theory, Structural Equation Model (SEM), Traditional Gold MinersAbstract
Environmental problems can overcome by changing the mental attitude of humans as environmental destroyers to humans who are aware of their environment. The focus in research is to find out and then interpret the results obtained related to the presence or absence of influence between the level of knowledge and attitudes of traditional miners on behavior. The number of samples used was 212 respondents spread over traditional mining areas of the community. Data is obtained from surveys using questionnaire instruments and interviews with traditional miners. The data is then analyzed Structural Equation Model (SEM) using IBM AMOS 23. The results of validation and reliability and goodness of fit (GOF) indicate that the model is feasible and fit. The results of the analysis show that there is a significant impact between the variables of knowledge and attitudes towards the behavior of the mining community. The condition of enough knowledge is not able to change people's behavior to manage the environment. The results obtained are the same as attitudinal variables that show contra to the environment. All ways are done to get profits without seeing the consequences. The attitude of the government must be more assertive in controlling illegal mining that has damaged the surrounding environment. Humans who are aware of their environment are humans who already understand and apply attitudes and behaviors that care about the environment and apply the principles of ecology and environmental ethics.
References
G. Hilson, “An overview of land use conflicts in mining communities,” Land use policy, vol. 19, no. 1, pp. 65–73, 2002.
C. Vintró, L. Sanmiquel, and M. Freijo, “Environmental sustainability in the mining sector: Evidence from Catalan companies,” J. Clean. Prod., vol. 84, no. 1, pp. 155–163, 2014.
G. M. Mudd, “Global trends in gold mining: Towards quantifying environmental and resource sustainability,” Resour. Policy, vol. 32, no. 1–2, pp. 42–56, 2007.
M. I. Ali, “Environmental Pollution Knowledge of Small Scale Miners in Bombana Regency, Indonesia,” Pollut. Res., vol. 37, no. 1, pp. 56–62, 2018.
A. Kumah, “Sustainability and gold mining in the developing world,” J. Clean. Prod., vol. 14, no. 3–4, pp. 315–323, 2006.
M. I. Ali, G. D. Dirawan, H. Syam, and Mulyadi, “Effect of Knowladge Toward the Behavior of Gold Miners Environmentally Sound : A Case in Bombana Regency,” Int. J. Appl. Environ. Sci., vol. 9, no. 4, pp. 1275–1289, 2014.
Ismawati, Yuyun Yunia., “Opening the Pandora’s Box of Poboya: The Social and Environmental Production of Suffering in Central Sulawesi, Indonesia,” Dissertation, University of Oxford, United Kingdom, 2011.
M. Babut, R. Sekyi, and A. Rambaud, “Improving the environmental management of small-scale gold mining in Ghana: a case study of Dumasi,” J. Clean. Prod., vol. 11, pp. 215–221, 2003.
D. Limbong, J. Kumampung, J. Rimper, T. Arai, and N. Miyazaki, “Emissions and environmental implications of mercury from artisanal gold mining in north Sulawesi, Indonesia,” Sci. Total Environ., vol. 302, no. 1–3, pp. 227–236, 2003.
U. S. EPA, “United States Environmental Protection Agency,” Qual. Assur. Guid. Doc. Qual. Assur. Proj. Plan PM Ambient Air, vol. 2, 2001.
Basri, M. Sakakibara, K. Sera, and I. A. Kurniawan, “Mercury Contamination of Cattle in Artisanal and Small-Scale Gold Mining in Bombana, Southeast Sulawesi, Indonesia,” Geosciences, vol. 7, no. 4, p. 133, 2017.
Meisanti, M. S. S. Ali, K. Jusoff, D. Salman, and D. Rukmana, “The impacts of gold mining on the farmer’s community,” Am. J. Sustain. Agric., vol. 6, no. 4, pp. 209–214, 2012.
A. Dewulf, M. Craps, R. Bouwen, T. Taillieu, and C. Pahl-Wostl, “Integrated management of natural resources: Dealing with ambiguous issues, multiple actors and diverging frames,” Water Sci. Technol., vol. 52, no. 6, pp. 115–124, 2005.
J. F. Hair, W. C. Black, B. J. Babin, and R. E. Anderson, Multivariate Data Analysis, 7th ed. Harlow, England: Pearson New International Edition, 2014.
J. W. Creswell, Research Design : Qualitative, Quantitative, and Mixed Method Approaches, 4th ed. Thousand Oaks, California: SAGE Publications, Inc., 2014.
R. P. Bagozzi and C. Fornell, “Theoretical concepts, measurements, and meaning,” A Second Gener. Multivar. Anal., vol. 2, no. 2, pp. 5–23, 1982.
K. A. Bollen and J. S. Long, Testing structural equation models, vol. 154. Sage, 1993.
L. W. Green, M. W. Kreuter, S. G. Deeds, K. B. Partridge, and E. Bartlett, “Health education planning: a diagnostic approach.,” 1980.
B. F. Skinner, About behaviorism. Vintage, 2011.
G. W. Bock and Y.-G. Kim, “Breaking the myths of rewards: An exploratory study of attitudes about knowledge sharing,” Inf. Resour. Manag. J., vol. 15, no. 2, pp. 14–21, 2002.
I. Ajzen and M. Fishbein, “Attitude-behavior relations: A theoretical analysis and review of empirical research.,” Psychol. Bull., vol. 84, no. 5, p. 888, 1977.
J. Hulland, “Use of partial least squares (PLS) in strategic management research: a review of four recent studies,” Strateg. Manag. J., vol. 20, no. 2, pp. 195–204, 1999.
C. Fornell and D. F. Larcker, “Evaluating structural equation models with unobservable variables and measurement error,” J. Mark. Res., vol. 18, no. 1, pp. 39–50, 1981.
P. M. Bentler and L. T. Hu, “Evaluating model fit,” in Structural equation modeling: Concepts, issues, and applications, Thousand Oaks, CA: SAGE Publications, 1995, pp. 76–99.
K. G. Jöreskog and D. Sörbom, LISREL 8: Structural equation modeling with the SIMPLIS command language. Scientific Software International, 1993.
G. D. Garson, Partial Least Squares: Regression & structural equation modeling. Asheboro, USA: Statistical Publishing Associates, 2016.
J. J. Hox and T. M. Bechger, “An introduction to structural equation modeling,” 2007.
J. S. Tanaka and G. J. Huba, “A general coefficient of determination for covariance structure models under arbitrary GLS estimation,” Br. J. Math. Stat. Psychol., vol. 42, no. 2, pp. 233–239, 1989.
R. E. Schumacher and R. G. Lomax, A Beginner’s Guide to Structural Equation Modeling: Third Edition, 3rd ed. Mahwah, NJ: Lawrence Erlbaum Associates, 2010.
J. H. Steiger and J. C. Lind, “Statistically based tests for the number of common factors,” in Paper presented at the annual meeting of the Psychometric Society, May 1980, 1980.
M. W. Browne and R. Cudeck, “Alternative ways of assessing model fit,” Sage Focus Ed., vol. 154, p. 136, 1993.
L. J. Williams and E. O’Boyle Jr, “The myth of global fit indices and alternatives for assessing latent variable relations,” Organ. Res. Methods, vol. 14, no. 2, pp. 350–369, 2011.
F. Chen, P. J. Curran, K. A. Bollen, J. Kirby, and P. Paxton, “An empirical evaluation of the use of fixed cutoff points in RMSEA test statistic in structural equation models,” Sociol. Methods Res., vol. 36, no. 4, pp. 462–494, 2008.
L. Hu and P. M. Bentler, “Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives,” Struct. Equ. Model. a Multidiscip. J., vol. 6, no. 1, pp. 1–55, 1999.
K. A. Bollen, “A new incremental fit index for general structural equation models,” Sociol. Methods Res., vol. 17, no. 3, pp. 303–316, 1989.
P. M. Bentler and D. G. Bonett, “Significance tests and goodness of fit in the analysis of covariance structures.,” Psychol. Bull., vol. 88, no. 3, p. 588, 1980.
P. M. Bentler, “SEM with simplicity and accuracy,” J. Consum. Psychol., vol. 20, no. 2, pp. 215–220, 2010.
T. A. Brown, Confirmatory factor analysis for applied research. New York: Guilford Publications, 2014.
L. James, S. Mulaik, and J. M. Brett, Causal analysis: Assumptions, models, and data. Beverly Hills: Sage publications, 1982.
C. C. DiClemente and J. O. Prochaska, “Self-change and therapy change of smoking behavior: A comparison of processes of change in cessation and maintenance,” Addict. Behav., vol. 7, no. 2, pp. 133–142, 1982.
S. A. Mulaik, L. R. James, J. Van Alstine, N. Bennett, S. Lind, and C. D. Stilwell, “Evaluation of goodness-of-fit indices for structural equation models.,” Psychol. Bull., vol. 105, no. 4, pp. 430–445, 1989.
M. S. Khine, L. C. Ping, and D. Cunningham, Application of Structural Equation Modeling in Educational Research and Practice : Contemporary Approaches to Research, 7th ed. Rotterdam, Netherlands: Sense Publishers, 2013.
S. Sharma, Applied Multivariate Techniques. New York, USA: John Wiley & Sons, Inc., 1996.
B. M. Byrne, Structural Equation Modeling with AMOS : Basic Concepts, Applications, and Programming, 2nd ed. New York: Routledge, Taylor & Francis Group, 2010.
J. Angelovska, S. B. Sotiroska, and N. Angelovska, “The impact of environmental concern and awareness on consumer behaviour,” J. Int. Environ. Appl. Sci., vol. 7, no. 2, pp. 406–416, 2012.
A. H. L. Aman, A. Harun, and Z. Hussein, “The influence of environmental knowledge and concern on green purchase intention the role of attitude as a mediating variable,” Br. J. Arts Soc. Sci., vol. 7, no. 2, pp. 145–167, 2012.
R. Weigel and J. Weigel, “Environmental concern: The development of a measure,” Environ. Behav., vol. 10, no. 1, pp. 3–15, 1978.
P. C. Stern, “New environmental theories: toward a coherent theory of environmentally significant behavior,” J. Soc. Issues, vol. 56, no. 3, pp. 407–424, 2000.
T. D. Wilson, “Human information behavior,” Informing Sci. Int. J. an Emerg. Transdiscipl., vol. 3, pp. 49–56, 2000.
E. Conraud-Koellner and L. A. Rivas-Tovar, “Study of green behavior with a focus on Mexican individuals,” iBusiness, vol. 1, no. 02, p. 124, 2009.
R. F. Manzanal, L. M. Rodríguez Barreiro, and M. Casal Jiménez, “Relationship between ecology fieldwork and student attitudes toward environmental protection,” J. Res. Sci. Teach. Off. J. Natl. Assoc. Res. Sci. Teach., vol. 36, no. 4, pp. 431–453, 1999.
L. M. Rodríguez-Barreiro et al., “Approach to a causal model between attitudes and environmental behaviour. A graduate case study,” J. Clean. Prod., vol. 48, pp. 116–125, 2013.
R. Fernández‐Manzanal, L. Rodríguez‐Barreiro, and J. Carrasquer, “Evaluation of environmental attitudes: Analysis and results of a scale applied to university students,” Sci. Educ., vol. 91, no. 6, pp. 988–1009, 2007.
G. W. Allport, K. Clark, and T. Pettigrew, “The nature of prejudice,” 1954.
P. C. Stern and T. Dietz, “The value basis of environmental concern,” J. Soc. Issues, vol. 50, no. 3, pp. 65–84, 1994.
G. A. Guagnano, T. Dietz, and P. C. Stern, “Willingness to pay for public goods: A test of the contribution model,” Psychol. Sci., vol. 5, no. 6, pp. 411–415, 1994.
W. Kilbourne and G. Pickett, “How materialism affects environmental beliefs, concern, and environmentally responsible behavior,” J. Bus. Res., vol. 61, no. 9, pp. 885–893, 2008.
D. Gadenne, B. Sharma, D. Kerr, and T. Smith, “The influence of consumers’ environmental beliefs and attitudes on energy saving behaviours,” Energy Policy, vol. 39, no. 12, pp. 7684–7694, 2011.
G. T. Miller Jr, Living in the environment: an introduction to environmental science., no. Ed. 7. Wadsworth Publishing Company, Inc., 1992.
N. W. Heimstra and L. H. McFarling, Environmental psychology. Brooks/Cole Pub. Co., 1978.
B. C. Field and M. K. Field, “Environmental economics: an introduction,” Sustain. Hum. Dev. Rev., vol. 105, 1997.
L. Rook, “An economic psychological approach to herd behavior,” J. Econ. Issues, vol. 40, no. 1, pp. 75–95, 2006.
Y. Kim and S. M. Choi, “Antecedents of green purchase behavior: An examination of collectivism, environmental concern, and PCE,” ACR North Am. Adv., 2005.
T. Mainieri, E. G. Barnett, T. R. Valdero, J. B. Unipan, and S. Oskamp, “Green buying: The influence of environmental concern on consumer behavior,” J. Soc. Psychol., vol. 137, no. 2, pp. 189–204, 1997.
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