Knowledge transfer in institutionalised supplier development and operational performance: the mediating role of absorptive capacity

Figures & data

Figure 1. Conceptual model

Table 1. Factor and reliability analyses

	Component	Eigenvalues	Variance explained
Transformation (α = .898)
Our employees have the ability to structure and use collected knowledge.	0.856	10.181	35.106
Our employees have the ability to absorb new knowledge as well as to prepare it for further purposes.	0.812
Our employees successfully link existing knowledge with new insights.	0.765
Our employees are able to apply new knowledge in their construction work.	0.7
Employees in my company are willing to accept changes that come as a result of the lessons learnt in a particular construction project	0.634
My company is able to take advantage of new knowledge and apply it to other construction projects.	0.599
My company is able to apply knowledge to cope with changing competitive conditions in the construction industry.	0.565
Operational performance(α = .929)
My company is able to meet budgeted cost targets.	0.851	3.785	13.052
My company is able to deliver projects to quality standards.	0.814
My company has improved its project costing compared to three years ago	0.801
My company is able to meet project technical objectives.	0.792
My company is able to meet schedule targets.	0.789
My company is able to comply with health and safety standards.	0.788
Knowledge transfer (α = .924)
My company has acquired important knowledge in supervision skills.	0.889	2.367	8.161
My company has acquired important knowledge in project management.	0.854
My company has acquired important knowledge in road maintenance.	0.847
My company has acquired important knowledge in road construction.	0.845
My company has acquired important knowledge in designing structures.	0.833
My company has acquired important knowledge in occupational health and safety.	0.755
Exploitation/application (α = .742)
The main contractor and my company make joint decisions on the project	0.828	1.971	6.796
My company is using knowledge from the main contractor or reserved projects to solve new construction problems.	0.687
The main contractor’s and my company’s employees interact frequently.	0.608
We share changes in project requirements with the main contractor based on the preferences of our client	0.575
Acquisition (α = .795)
My company expects employees to deal with information beyond our industry.	0.8	1.522	5.247
The search for relevant information concerning our industry is an every-day activity in my company.	0.75
My company motivates its employees to use information sources within our industry.	0.698
Assimilation(α = .678)
In my company, supervisors and subordinates frequently share information on construction techniques.	0.547	1.013	3.493
New ideas from the main constructors are often communicated between internal departments/units in my company.	0.701
Employees in my company share ideas freely with each other.	0.668

Table 2. Construct measures

Measures	Definitions	References
KT	KT involves the organisation’s ability to acquire knowledge from the external environment and sharing it internally to improve its operations through the application of knowledge for commercial value. This can be achieved through, among other things, supplier development, where a buying organisation with vast experience and knowledge, transfers knowledge to a less experienced supplier organisation to improve its performance	Nagati and Rebolledo (2012); Gosling et al. (2015)
AC	AC is a four-dimensional construct comprising of knowledge acquisition, assimilation, transformation, and exploitation/application as follows:	Davila et al. (2019); Flatten, Englen et al. (2011); Saenz et al. (2013)
KAC	Knowledge acquisition involves recognising and comprehending external relevant information from a variety of sources, such as supplier development initiatives.	Davila et al. (2019); Flatten, Englen et al. (2011); Saenz et al. (2013)
KAS	Knowledge assimilation involves the conversion and interpretation of acquired information and the development of a suitable internal organisational context to facilitate knowledge sharing internally	Saenz et al. (2013)
KTR	Knowledge transformation combines new and prior knowledge to develop and refine organisational routines that facilitate knowledge conversion and internalisation	Davila et al. (2019); Flatten, Englen et al. (2011);
KAP	Knowledge application involves the application of knowledge to create commercial value. Knowledge exploitation involves the application of knowledge for new product development, innovative practices, and the execution of projects that could not have been carried out in the past	Saenz et al. (2013)
PERF	Operational performance refers to the performance related to the productive and measurable output of an organisation’s internal operation, such as productivity, product quality, cost of operations, delivery, flexibility, innovation, and customer satisfaction. Project performance outcomes focus on the project schedule, budget, quality and technical project objectives.	Modi and Mabert (2007); Gosling et al. (2015); Lawson et al. (2015)

KT-knowledge transfer; AC-absorptive capacity; KAC-knowledge acquisition; KAS-knowledge assimilation; KTR-knowledge transformation, KAP-knowledge application, and PERF-operational performance

Table 3. Paired samples test

		Paired Differences					t	df	Sig. (2-tailed)
		Mean	Std. Deviation	Std. Error Mean	95% Confidence Interval of the Difference
					Lower	Upper
Pair 1	KT_E—KT_L	.05556	1.26577	.23110	−.41709	.52820	.240	29	.812
Pair 2	ACQ_E—ACQ_L	−.37778	1.14381	.20883	−.80488	.04933	−1.809	29	.081
Pair 3	AS_E—AS_L	−.34444	1.10201	.20120	−.75594	.06705	−1.712	29	.098
Pair 4	TR_E—TR_L	−.30952	1.10024	.20088	−.72036	.10131	−1.541	29	.134
Pair 5	APP_E—APP_L	−.46667	1.25212	.22861	−.93422	.00088	−2.041	29	.050

Note: KT_E: denote early responses on KT and KT_L, late responses on KT, respectively.

Table 4. Descriptive statistics and correlations

	Mean	SD	1	2	3	4	5	6	7
Company age	8.32164	5.753418
No of employees	1.50292	0.890302	.174*
Knowledge acquisition	3.9084	0.76358	−.066	.031
Knowledge assimilation	3.8908	0.70185	−.115	.151*	.395**
Knowledge transformation	4.0886	0.65045	−.102	.043	.523**	.562**
Knowledge application	3.5819	0.78909	.015	.144	.462**	.530**	.483**
Knowledge transfer	3.4279	1.0031	−.050	.109	.176*	.203**	.253**	.266**
Operational Performance	4.1793	0.75277	−.004	.148	.355**	.431**	.560**	.394**	.292**

*.Correlation is significant at the 0.05 level (2-tailed).

**.Correlation is significant at the 0.01 level (2-tailed).

Table 5. Summary of hierarchical multiple regression

		Dependent variable: Operational performance
	Model 1		Model 2		Model 3		Collinearity statistics
	B	SE	B	SE	B	SE	VIF	Tolerance
Control variables
Company age	−.004	.010	−.001	.010	.006	.008	.937	1.067
Number of employees	.130	.065	.102	.064	.068	.055	.925	1.081
Independent variables
Knowledge transfer			.209***	.056	.100*	.049	.901	1.110
Knowledge acquisition					.041	.075	.667	1.500
Knowledge assimilation					.124	.088	.579	1.726
Knowledge transformation					.472***	.097	.552	1.813
Knowledge application					.066	.076	.604	1.656
R	.152		.315		.609
R Square	.023		.099		.371
Adjusted R Square	.011		.083		.344
R Square Change	.023		.076		.271
F	1.974		6.129**		13.709***
F Change	1.974		14.128***		17.57***

Table 6. Summary of direct and indirect effects KT-AC-operational performance

Paths for AC dimensional constructs	b	SE	t	p
K-transf→ Perform (c)	.220 [.110, .328]	.055	3.970	P < .001
K-transf $\to Acquisition$ (a1)	.134 [.021, .248]	.058	2.331	P < .05
K-transf $\to Assimilation$ (a2)	.142 [.038, .246]	.053	2.698	P < .01
K-transf $\to Transformation$(a3)	.164 [.069, .259]	.048	3.394	P < .001
K-transf $\to Application$(a4)	.209 [.094, .324]	.058	3.584	P < .001
$Acquisition$ → Perform (b1)	.036 [−.113, .184]	.075	.476	P = .635
$Assimilation$ → Perform(b2)	.130 [−.041, .300]	.087	1.500	P = .136
$Transformation$ → Perform (b3)	.460 [.269, .651]	.097	4.761	P < .001
$Application$ → Perform(b4)	.080 [−.069, .230]	.076	1.060	P = .029
K-transf→ Perform (c’)	.104 [.007, .201]	.049	2.119	P < .05
Indirect effects of X on Y	Effect (ab)	Bootstrap SE	Bootstrap Lower limit 95% CI	Bootstrap Upper limit 95% CI
K-transf $\to Acquisition\to$ Perform (ab1)	.0048	.0154	−.0225	.0420
K-transf $\to Assimilation\to$ Perform (ab2)	.0184	.0171	−.0080	.0589
K-transf $\to Transformation\to$ Perform (ab3)	.0754	.0370	.0166	.1595
K-transf $\to Application\to$ Perform (ab4)	.0168	.0174	−.0148	.0552
Total	.1154	.0473	.0352	.2206

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