Data, attitudinal and organizational determinants of big data analytics systems use

Figures & data

Figure 1. Research model.

Table 1. Survey items

Construct	Item	Reference
Data Connectivity (DC)	Compared with our competitors in the same industry, our company’s IT and BDA systems have better connectivity (DC1). Our company has a central control system, which connects all functions, equipment, and the BDA system (DC2). Our company utilizes open systems network mechanisms to boost the connectivity (DC3).	Kim et al. (2012)
Data Integrity (DI)	The data used by the BDA system is in a clear format and conforms to library standards (DI1). The information used by the BDA system is consistent with structural integrity (DI2). The data used by the BDA system is consistent with the content (DI3).	Cai and Zhu (2015)
Data Timeliness (DT)	The information used by the BDA system can be transmitted within a given time (DT1). The BDA system will update the database regularly (DT2). The data used by the BDA system conforms to the data used by the pre-system from the time of collection, processing, and release (DT3).	Cai and Zhu (2015)
Organizational Readiness (OR)	Lack of funding or financial resources will prevent companies from using BDA (OR1). Lack of necessary IT infrastructure will hinder companies from using BDA systems (OR2). Lack of analytical capabilities will hinder companies from using the BDA system (OR3).	Chen et al. (2015)
Relational Knowledge (RK)	Our company’s BDA personnel can plan, organize, and lead the project (RK1). Our company’s BDA personnel can plan and execute work in a group environment (RK2). Our company’s BDA personnel can teach others (RK3). Our company’s BDA personnel work closely with customers and maintain good relationships (RK4).	Kim et al. (2012)
Satisfaction (SAT)	The BDA system was very helpful for me to complete my work and responsibilities (SAT1). The BDA system greatly helped me work efficiently (SAT2). The BDA system is effective for my work (SAT3).	Urbach et al. (2010)
BDA Usage (BU)	The frequency of using the BDA system (BU1) The weekly duration of using the BDA system (BU2)	Urbach et al. (2010)

Table 2. Demographical analysis

Categories	Variables	Frequency (%)
Age	20–29 years old	112 (47.5)
	30–39 years old	84 (35.6)
	40–49 years old	32 (13.6)
	50–59 years old	7 (2.9)
	60 years old and above	1(0.4)
Gender	Female	67 (28.3)
	Male	169 (71.7)
Education	High school	4 (1.7)
	Vocational school	3 (1.3)
	Bachelor	66(28.0)
	Graduate degree	153(64.8)
	Doctorate	10(4.2)
Business Domain	IT	104 (44.1)
	R&D	47 (19.9)
	Sales	24 (10.2)
	Manufacturing	22 (9.3)
	Marketing	15 (6.4)
	HR	5 (2.1)
	Finance	3 (1.3)
	Purchasing	2 (0.8)
	Others	14 (5.9)
Company Size	More than 500	153 (64.8)
	200–499	25 (10.6)
	50–199	27 (11.4)
	30–49	17 (7.2)
	Fewer than 29	14 (5.9)
BDA Stage in Company	Adopted	168 (71.1)
	In the adoption process	68 (18.9)

Table 3. Quality indicators and correlations with square root of AVE on the diagonal

Const.	CA	AVE	CR	DC	DI	DT	OR	RK	SAT	USE
DC	0.784	0.700	0.860	0.837
DI	0.913	0.850	0.934	0.547**	0.922
DT	0.752	0.669	0.928	0.500**	0.695**	0.818
OR	0.829	0.654	0.878	−0.031	0.137	0.145	0.809
RK	0.809	0.638	0.871	0.568**	0.628**	0.556**	0.224**	0.799
SAT	0.912	0.793	0.934	0.441**	0.503**	0.588**	0.169*	0.516**	0.890
USE	0.830	0.853	0.946	0.252**	0.298**	0.353**	0.188*	0.369**	0.5458**	0.923**

※CA: Cronbach’s α, CR: Composite Reliability, AVE: Average Variance Extracted, Square of AVE on the diagonal, ** p < 0.01, *p < 0.05

Table 4. Results of hypothesis testing

Hypothesized Path	Path Coefficient	T-statistics	Hypothesis Test Results
H1: DI → DC	0.386556	3.646**	Supported
H2: DT → DC	0.231516	2.388**	Supported
H3: OR → SAT	0.079100	0.967	Not Supported
H4: RK → SAT	0.367273	4.306**	Supported
H5: DC → SAT	0.230214	2.609**	Supported
H6: DC → USE	0.014014	0.233	Not Supported
H7: SAT → USE	0.538953	10.261**	Supported

※ Significance: *p < 0.01

Figure 2. Theoretical model with results of hypothesis testing.※ Significance: *p < 0.01

Table

Items	Mean	S.D.	DCON	DI	DT	OR	RK	SAT	BU
DCON1	3.606	0.059	0.607	0.280	0.107	0.013	0.223	0.233	−0.077
DCON2	3.708	0.066	0.714	0.243	0.106	−0.011	0.114	0.183	0.146
DCON3	3.593	0.072	0.575	0.294	−0.033	−0.124	0.167	0.135	0.134
DI1	3.919	0.052	0.347	0.733	0.174	0.058	0.189	0.158	0.195
DI2	3.903	0.052	0.119	0.854	0.032	0.046	0.125	0.220	0.047
DI3	3.826	0.054	0.097	0.862	0.032	0.033	0.160	0.218	0.015
DT1	3.979	0.048	0.213	0.424	0.481	0.091	0.128	0.327	0.099
DT2	3.881	0.051	0.232	0.450	0.452	−0.023	0.036	0.329	0.118
OR1	4.119	0.057	0.112	0.119	−0.106	0.735	0.050	−0.011	0.023
OR2	4.174	0.051	−0.120	0.080	0.098	0.729	0.023	0.119	0.049
OR3	4.169	0.052	−0.034	−0.037	0.041	0.788	0.068	0.104	0.052
RK1	3.792	0.053	0.235	0.326	−0.010	0.038	0.616	0.259	−0.032
RK2	3.987	0.046	0.132	0.370	0.026	0.134	0.630	0.201	0.134
RK3	3.996	0.051	0.243	0.291	0.213	0.099	0.500	0.266	0.210
SAT1	4.047	0.050	0.103	0.204	0.069	0.092	0.152	0.833	0.154
SAT2	4.021	0.051	0.127	0.246	0.119	0.054	0.120	0.768	0.234
SAT3	4.038	0.051	0.145	0.242	0.021	0.056	0.102	0.775	0.201
BU1	3.949	0.067	0.086	0.177	0.051	0.102	0.104	0.355	0.724
BU2	3.301	0.085	0.060	0.017	0.030	0.019	0.018	0.275	0.730

※DC = Data Connectivity, DI = Data Integrity, DT = Data Timeliness, OR = Organizational Readiness, RK = Relational Knowledge, SAT = Satisfaction BU = BDA Usage

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