THE ADOPTION OF BIG DATA SERVICES BY MANUFACTURING FIRMS: AN EMPIRICAL INVESTIGATION IN INDIA

Verma, Surabhi

doi:10.4301/S1807-17752017000100003

Surabhi Verma

National Institute of Industrial Engineering, India

Figures (4)
Tables (6)

Thumbnail

Figure 1.
Proposed research framework

Thumbnail

Figure 2.
Results of PLS structural model analysis (SmartPLS snapshot)

Thumbnail

Figure 3.
The stars represent those three hypotheses which are not supported

Thumbnail

Figure 4.
Results of PLS structural model analysis Note: Significant relation(→), Insignificant relation( ⇢ ).

Thumbnail

Table 1.
Research studies on the usage and adoption of big data by firms

Thumbnail

Table 2.
Summary of respondent’s profile

Thumbnail

Table 3.
Reliability Validation for Latent Constructs

Thumbnail

Table 4.
Item loading for indicators of latent constructs

Thumbnail

Table 5.
Reliability and inter-construct correlations for reflective scales

Thumbnail

Table 6.
Summary of hypotheses tests (Path coefficients and hypotheses testing).

IT adoption (dependent variable)	Constructs/factors (independent variables)	Methods	Data and context	Author
Behavioral intention to use big data services	Big data system features (Relative advantage, Quality, Security, Inter-operability); Perceived Value( Perceived usefulness, Perceived ease of use); implement intention	Qualitative and quantitative methodology	Survey of 398 firms in Korea.	Shin, 2015Shin, D. (2013). User centric cloud service model in public sectors. Government Information Quarterly, 30(2), 194-203.
Acquisition intention of big data analytics	Degree of data consistency; Degree of data completeness; Perceived benefits of external data usage; Perceived benefits of internal data usage; Resource Facilitating condition	Partial least square	Survey of 306 firms in Korea	Kwon et al., (2014Kuan, K. K., & Chau, P. Y. (2001). A perception-based model for EDI adoption in small businesses using a technology-organization-environment framework. Information & management, 38(8), 507-521.).
Behavior intention	Organization innovativeness, organization slank; IS infra maturity; perceived benefits of big data system; Perceived usefulness; Perceived ease of use	Conceptual	Conceptual model	Kim et al., (2013)
Intention to adopt big data and actual adoption of big data	Big data dimensions; Perceived usefulness; Perceived ease of use; Compatibility; Self-efficacy; Facilitating conditions; Perceived benefits; Perceived costs; Subjective norms	Partial least square	Survey of 53 firms in Spain	Esteves and Curto (2013Esteves, J., & Curto, J. (2013). A risk and benefits behavioral model to assess intentions to adopt big data. Journal of Intelligence Studies in Business, 3(1), 37-46.)
Adoption and assimilation	Perceived direct benefit; perceived indirect benefit; perceived financial readiness; perceived IS competence; Perceived industry pressure; perceived government pressure	Partial least square	Case-based and survey based study of 58 firms in Korea	Nam et al., (2015)
Organizational intention to adopt big data solutions	Perceived complexity; perceived compatibility; top management support; information security culture; organizational learning culture; security/privacy regulatory concerns, risks in outsourcing	Conceptual	Conceptual model	Salleh et al., (2014)

Variables	Frequency	Percentage (%)
Number of employees
<=200	25	12.3%
201-400	75	36.8%
400-800	57	28.2%
>800	48	22.7%
Role in organization
CEO/COO/CIO/CFO	31	15.2 %
V.P., General Manager, etc.	52	25.6 %
Director, Controller, etc.	63	31 %
Manager, Senior Analyst, etc.	59	28.2 %
Age of the responding firms (years)
1-10	30	15.2 %
11-20	58	28.5 %
>20	117	56.3 %
Annual Revenue (turnover)
Less than USD 40000	34	17 %
USD 40000- USD 1 million	58	28.5 %
USD 1 million- USD 4 Million	40	19.5 %
More than USD 4million	73	35 %

Overview	AVE	Composite reliability	Cronbach’s alpha	R square	LV index values
Big Data quality	0.501	0.831	0.745	0.000	3.882
Absorptive Capacity	0.689	0.869	0.774	0.129	3.465
Perceived benefits of big data services	0.503	0.855	0.796	0.409	4.070
Perceived costs of big data services	0.832	0.952	0.933	0.251	3.654
Adoption of big data services	0.862	0.926	0.839	0.582	4.291

Construct	Loadings	Ave	Composite reliability	Cronbach’s alpha	R square
Data Quality		0.501	0.831	0.745	0.000
Rapidly increasing size of data	0.8264
Getting data timely.	0.6119
Access to unstructured data	0.6849
Diversity in data.	0.7188
Implications from social media	0.663
Truthfulness in text data	0.8264

*Absorptive Capacity*		0.689	0.869	0.774	0.129
Data scientists with the domain knowledge	0.7326
Skills in handling large data sets.	0.8801
Analysts for interpretation of information.	0.8659

*Perceived benefits of big data*		0.503	0.855	0.796	0.409
Better understanding of the nature of customers’ demands.	0.7692
Prevent fraudulent events.	0.7895
Developing strategies from social media data.	0.7423
Monitor markets in real time.	0.6809
Dynamic pricing of products.	0.4262
Reduce maintenance costs.	0.7782

*Perceived costs of big data*		0.832	0.952	0.933	0.251
Data sharing threatens business competitiveness.	0.9146
Vulnerability of sensitive data.	0.9219
High initial investment costs.	0.8943
High operational costs.	0.9178

*Adoption of big data*		0.862	0.926	0.839	0.582
Use BDA in next few years.	0.923
Already using big data services.	0.9336

Significant values		P<0.1 P<0.05 P<0.01	1.652 1.971 2.599
Hypothesis No.	Hypothesis (direction)	Path coefficient	T-value	Significance (one-tailed)	Supported
H1	BDQ -> ITA	0.4882	4.5371	P<0.01	Yes
H2	BDQ -> PB	0.7127	7.5829	P<0.01	Yes
H3	BDQ -> PC	0.4141	3.9013	P<0.01	Yes
H4	BDQ -> TR	0.3432	2.7351	P<0.01	Yes
H5	PB -> ITA	0.41	4.0289	P<0.01	Yes
H6	PC -> ITA	-0.0861	1.1889	n.s	No
H7	PC -> PB	0.0353	0.4675	n.s	No
H8	TR -> ITA	0.0801	1.2587	n.s	No
H9	TR -> PB	0.1998	2.0125	P<0.01	Yes
H10	TR -> PC	-0.1559	1.6155	P<0.1	Yes

[TFN1] Note: Value on the diagonal is the square root of AVE.

LV construct	Big data quality	Adoption of big data	Perceived benefits of big data	Perceived costs of big data	Absorptive Capacity
BDQ	0.707814	0	0	0	0
ITA	0.6778	0.92844	0	0	0
PB	0.6176	0.6784	0.709225	0	0
PC	0.4635	0.2228	0.2668	0.91214	0
TR	0.3603	0.1081	0.0717	0.3429	0.83006

Brasil

Brasil

THE ADOPTION OF BIG DATA SERVICES BY MANUFACTURING FIRMS: AN EMPIRICAL INVESTIGATION IN INDIA

ABSTRACT