Organizational structure as antecedent of dynamic capability

Gonzalez, Rodrigo Valio Dominguez

doi:10.1590/1806-9649-2022v29e1821

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ORIGINAL ARTICLE • Gest. Prod. 29 • 2022 • https://doi.org/10.1590/1806-9649-2022v29e1821 copy

Organizational structure as antecedent of dynamic capability

A estrutura organizacional como antecedente da capacidade dinâmica

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

Dynamic capability is recognized in the academic and business context as an essential factor for the firm to build differential and remain competitive in dynamic markets. Most of these preliminary studies assess dynamic capability from the perspective of the resource-based view of the firm. This study advances on this theme by analyzing the impact of knowledge-based dynamic capability, based on the knowledge based vision of firm, about innovation of project team. Previous studies have identified the relationship between dynamic capability and innovation or organizational performance, but there is a gap in the theory that relates antecedents of dynamic capability. Thus, this research aims to analyze the relationship between organizational structure and dynamic capability on the innovative capacity of project teams. To achieve this objective, 65 project teams from industrial companies in the state of São Paulo were studied and the data were analyzed using the technique of structural equation modeling - partial least squares (SEM_PLS). The results show that structures with a higher degree of formalization and centralization have a negative impact on knowledge-based dynamic capability, and integration has a positive relationship with dynamic capability. Furthermore, the research shows that the innovative capacity of project teams is directly affected by the ability to generate and combine knowledge, however, the acquisition / absorption of knowledge does not interfere with the innovation activity of these teams.

Keywords:
Knowledge-based dynamic capability; Organizational structure; Innovation; Project team; Industry

Measurements	Items	Frequency	Percentage
Empresas pesquisadas
Industry	Machinery and Equipment	60	22.90
	Automotive	57	21.76
	Metallurgy and Steel industry	44	16.79
	Chemistry	39	14.12
	Food	26	9.92
	Computers and home appliances	20	7.63
	Pharmaceutical and Cosmetic	13	4.96
	Paper And Cellulose	3	1.15
	Textile	2	0.76
Number of employees	50 or less	78	29.77
	51-100	87	33.21
	101-500	48	18.32
	501-1000	26	9.92
	Above 1000	23	8.78
Teams
Team size	3-5	51	19.47
	6-10	88	33.59
	11-20	80	30.53
	Above 20	43	16.41
Team tenure	3-6 months	118	45.04
	7 months-1 year	72	27.48
	1y-2y	42	16.03
	Above 2 years	30	11.45
Respondents
Gender	Male	158	60.31
	Female	104	39.69
Educational level	Undergraduate	37	14.12
	Graduate	160	61.07
	Master or above	65	24.81
Position	Coordination/Supervision	86	32.82
	Manager	142	54.20
	Senior Manager/CEO	34	12.98
Age range	18-25	64	24.43
	26-35	87	33.21
	36-45	75	28.63
	Above 45	36	13.74

Variable	Items	Loading	α	CR	AVE	ρA	VIFa
B
Formalization	Form1	0.842	0.815	0.798	0.776	0.811	1.60
	Form2	0.881					1.74
	Form3	0.793					2.31
Centralization	Cent1	0.765	0.795	0.776	0.712	0.785	2.26
	Cent2	0.810					2.43
	Cent3	0.798					2.12
Integration	Int1	0.741	0.766	0.784	0.743	0.768	1.92
	Int2	0.720	0.766	0.784	0.743	0.768	1.71
Dynamic Capability
KAC	KAC1	0.812	0.780	0.816	0.680	0.736	1.55
	KAC2	0.886					2.65
	KAC3	0.838					2.05
	KAC4	0.873					1.77
	KAC5	0.855					2.08
KGC	KGC1	0.803	0.796	0.804	0.673	0.828	1.90
	KGC2	0.818					2.47
	KGC3	0.773					2.76
	KGC4	0.792					2.53
	KGC5	0.836					1.89
KCC	KCC1	0.773	0.792	0.788	0.715	0.861	1.74
	KCC2	0.781					1.68
	KCC3	0.765					2.43
	KCC4	0.773					2.06
	KCC5	0.778					1.79
	KCC6	0.845					1.90
Teams Innovative Capability	CIT1	0.780	0.778	0.765	0.812	0.864	1.95
	CIT2	0.766					1.73
	CIT3	0.787					1.44
	CIT4	0.790					2.06
	CIT5	0.808					1.63
	CIT6	0.827					2.23
	CIT7	0.818					2.45
	CIT8	0.806					2.81
Task Interdependence	TI1	0.836	0.812	0.844	0.831	0.817	2.03
	TI2	0.820					2.15
	TI3	0.841					2.23
	TI4	0.791					2.67
	TI5	0.856					2.80
	TI6	0.883					1.78

Construct	Form	Cent	Int	KAC	KGC	KCC	CIT	IT
Form	0.881	0.344	0.288	0.120	0.190	0.216	0.145	0.166
Cent	0.320	0.844	0.218	0.188	0.288	0.268	0.253	0.255
Int	0.263	0.193	0.862	0.293	0.283	0.317	0.388	0.289
KAC	0.131	0.164	0.267	0.825	0.304	0.283	0.293	0.235
KGC	0.188	0.224	0.243	0.328	0.820	0.316	0.351	0.212
KCC	0.105	0.235	0.288	0.253	0.265	0.846	0.222	0.246
CIT	0.089	0.318	0.315	0.342	0.388	0.213	0.901	0.188
IT	0.123	0.194	0.288	0.091	0.133	0.148	0.215	0.912

Hypothesis	Relationship	Path coefficient	t-statistics	p-value	Sig. level	Results	f²
H1a	Form $\to$ KAC(-)	-0.255	-2.560	0.000	***	Supported	0.218
H1b	Form $\to$ KGC(-)	-0.203	-1.983	0.004	**	Supported	0.162
H1c	Form $\to$ KCC(+)	0.117	1.119	0.043	*	Supported	0.094
H2a	Cent $\to$ KAC(-)	-0.295	-2.873	0.000	***	Supported	0.236
H2b	Cent $\to$ KGC(-)	-0.227	-.2115	0.003	**	Supported	0.182
H2c	Cent $\to$ KCC(-)	-0.124	-1.308	0.038	*	Supported	0.100
H3a	Int $\to$ KAC(+)	0.072	0.691	0.062	NS	Not Supported	0.042
H3b	Int $\to$ KGC(+)	0.337	4.436	0.000	***	Supported	0.270
H3c	Int $\to$ KCC(+)	0.438	5.222	0.000	***	Supported	0.343
H4a	KAC $\to$ CIT(+)	0.078	0.765	0.056	NS	Not Supported	0.046
H4b	KGC $\to$ CIT(+)	0.493	6.125	0.000	***	Not Supported	0.394
H4c	KCC $\to$ CIT(+)	0.555	7.842	0.000	***	Supported	0.444
Control Variables	TAT $\to$ CIT	-0.069	0.584	0.067	NS	Not Supported	0.040
	TET $\to$ CIT	0.128	1.290	0.037	*	Not Supported	0.105
	TI $\to$ CIT	0.080	0.792	0.055	NS	Supported	0.049

Universidade Federal de São Carlos Departamento de Engenharia de Produção , Caixa Postal 676 , 13.565-905 São Carlos SP Brazil, Tel.: +55 16 3351 8471 - São Carlos - SP - Brazil
E-mail: gp@dep.ufscar.br

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[1] Notes: α: Cronbach’s α; CR: composite reliability; ρA: Dijstra-Henseler’s rho; AVE: average variance extracted; ^apercentage of variance of item explained by the latent variable.