FROM GREEN TRAINING AND INVOLVEMENT TO AN ORGANIZATIONAL RATIONALE FOR SUSTAINABILITY: DOES IT IMPROVE INDIVIDUAL GREEN PERFORMANCE?

Colombo, Valter Luís Barbieri; Frare, Anderson Betti; Beuren, Ilse Maria

doi:10.1590/S0034-759020220508x

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FORUM • Rev. adm. empres. 62 (5) • 2022 • https://doi.org/10.1590/S0034-759020220508x copy

FROM GREEN TRAINING AND INVOLVEMENT TO AN ORGANIZATIONAL RATIONALE FOR SUSTAINABILITY: DOES IT IMPROVE INDIVIDUAL GREEN PERFORMANCE?

Authorship SCIMAGO INSTITUTIONS RANKINGS

ABSTRACT

Organizations are pressured by their stakeholders to promote sustainable actions, so they need to adopt strategies that encourage their employees to engage in green behaviors. Our aim was to analyze the effects of green training and involvement on individual green performance, with the intervention of the interactive and diagnostic use of Performance Measurement Systems (PMS), organizational rationale for sustainability, and organizational identification. A survey was conducted with employees of a private electric power generator operating in Brazil, and 101 valid responses were obtained. The analysis used mixed methods: partial least squares structural equation modeling and fuzzy-set qualitative comparative analysis. The findings suggest the influence of green training and involvement on the interactive and diagnostic use of PMS, and on the organizational rationale for sustainability, which influences individual green performance moderated by organizational identification. Furthermore, two (four) combinations of the conditions promote high (low) individual green performance.

Keywords:
green training and involvement; performance measurement systems; organizational rationale for sustainability; organizational identification; individual green performance.

	Loadings	Cronbach's Alpha	rho_A	CR	AVE
1.GTI	[0.833; 0.875]	0.877	0.888	0.915	0.729
2.iPMS	[0.754; 0.895]	0.924	0.925	0.939	0.687
3.dPMS	[0.901; 0.963]	0.951	0.953	0.965	0.873
4.ORS	[0.830; 0.865]	0.805	0.805	0.885	0.720
5.OI	[0.715; 0.823]	0.828	0.845	0.876	0.587
6.IGP	[0.818; 0.947]	0.940	0.944	0.937	0.833

	1	2	3	4	5	6	7	8	9
1.GTI	0.854	0.550	0.465	0.505	0.336	0.678	0.230	0.144	0.177
2.iPMS	0.503	0.829	0.646	0.558	0.444	0.405	0.061	0.076	0.173
3.dPMS	0.437	0.608	0.934	0.665	0.402	0.280	0.049	0.017	0.128
4.ORS	0.427	0.483	0.583	0.848	0.485	0.356	0.072	0.143	0.098
5.OI	0.301	0.396	0.353	0.379	0.766	0.345	0.085	0.097	0.073
6.IGP	0.618	0.388	0.269	0.309	0.330	0.912	0.215	0.095	0.201
7.Age	0.210	0.049	0.048	0.065	0.067	0.212	-	0.026	0.372
8.Gender	-0.136	0.035	0.002	0.028	0.069	0.084	-0.026	-	0.121
9.Tenure	0.159	0.166	0.124	-0.005	-0.057	0.194	0.372	-0.121	-

Type of relationship	H	Relationship	Beta (β)	Valor-p
Main effects	H1	GTI→ORS	0.172	0.055^* * p<0.10;
	-	GTI→iPMS	0.503	0.000^* ***** p<0.01, one-tailed test when the sign of the relationship is predicted, and two-tailed otherwise (control variables).
	-	iPMS→ORS	0.139	0.097^* * p<0.10;
	H2	GTI→iPMS→ORS	0.070	0.122
	-	GTI→dPMS	0.437	0.000^* ***** p<0.01, one-tailed test when the sign of the relationship is predicted, and two-tailed otherwise (control variables).
	-	dPMS→ORS	0.424	0.001^* ***** p<0.01, one-tailed test when the sign of the relationship is predicted, and two-tailed otherwise (control variables).
	H3	GTI→dPMS→ORS	0.185	0.007^* ***** p<0.01, one-tailed test when the sign of the relationship is predicted, and two-tailed otherwise (control variables).
	H4	ORS→IGP	0.279	0.008^* ***** p<0.01, one-tailed test when the sign of the relationship is predicted, and two-tailed otherwise (control variables).
	-	OI→IGP	0.298	0.002^* ***** p<0.01, one-tailed test when the sign of the relationship is predicted, and two-tailed otherwise (control variables).
	H5	ORS^* * p<0.10; OI→IGP	0.299	0.003^* ***** p<0.01, one-tailed test when the sign of the relationship is predicted, and two-tailed otherwise (control variables).
Control variables	-	Age→IGP	0.142	0.109
	-	Gender→IGP	0.077	0.377
	-	Tenure→IGP	0.149	0.083^* * p<0.10;
Other specific indirect effects	-	GTI→ORS→IGP	0.048	0.141
	-	iPMS→ORS→IGP	0.039	0.141
	-	dPMS→ORS→IGP	0.118	0.014^ p<0.05;
	-	GTI→iPMS→ORS→IGP	0.019	0.171
	-	GTI→dPMS→ORS→IGP	0.052	0.040^ p<0.05;

Panel A - High individual green performance
Configurations	GTI	iPMS	dPMS	ORS	OI	Coverage		Consistency
Configurations	GTI	iPMS	dPMS	ORS	OI	Raw	Unique	Consistency
Model: IGP = f (GTI, iPMS, dPMS, ORS, OI)
1	●	●	●	●	○	0.297	0.151	0.917
2	●	●	○	●	●	0.218	0.071	0.928
Overall coverage: 0.368
Overall consistency: 0.921
Panel B - Low individual green performance
Configurations	GTI	iPMS	dPMS	ORS	OI	Coverage		Consistency
Configurations	GTI	iPMS	dPMS	ORS	OI	Raw	Unique	Consistency
Model: ~ IGP = f (GTI, iPMS, dPMS, ORS, OI)
1	○	○	○		○	0.395	0.179	0.890
2	○	●	●	●	○	0.239	0.060	0.910
3		○	○	○	●	0.237	0.049	0.875
4	○	●	●	○	●	0.204	0.047	0.915
Overall coverage: 0.598
Overall consistency: 0.853

Fundação Getulio Vargas, Escola de Administração de Empresas de S.Paulo Avenida Nove de Julho, 2.029, Bela Vista, CEP: 01313-902, Telefone: +55 (11) 3799-7718 - São Paulo - SP - Brazil
E-mail: rae@fgv.br

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[1] AUTHOR’S CONTRIBUTION

Valter Luís Barbieri Colombo, Anderson Betti Frare and Ilse Maria Beuren declare that they also contributed to the development of the article, including its conceptualization and theoretical-methodological approach, theoretical review (literature survey), data collection and analysis, writing and the final review.