Blockchain adoption in logistics companies in Ho Chi Minh City, Vietnam

Figures & data

Figure 1. Proposed model.

Table 1. Descriptive statistics

Demographic characteristics		Frequency (Total: 414)	Percentage
Gender	Female	297	71.74%
	Male	117	28.26%
Age	22 and 30 years old	366	88.41%
	above 30 years old	48	11.59%
Education level	Bachelor’s degree/ Professional qualification	341	82.37%
	Master/Ph.D. degree	73	17.63%
Experience	1–2 years	321	77.72%
	3–4 years	74	17.92%
	Over 5 years	18	4.36%

Note: n=414

Table 2. Loading, composite reliability, Dijkstra Henseler, and average variance extracted

Latent Construct	Items	Outer loading	${\rho }_A$	Composite Reliability	Average Variance Extracted (AVE)
BI	BI1	0.901	0.912	0.938	0.790
	BI2	0.880
	BI3	0.890
	BI4	0.884
EE	EE1	0.875	0.912	0.933	0.737
	EE2	0.849
	EE3	0.870
	EE4	0.870
	EE5	0.826
FC	FC1	0.922	0.945	0.960	0.858
	FC2	0.932
	FC3	0.938
	FC4	0.913
PE	PE1	0.842	0.900	0.926	0.714
	PE2	0.813
	PE3	0.891
	PE4	0.848
	PE5	0.830
SI	SI1	0.894	0.955	0.963	0.838
	SI2	0.925
	SI3	0.936
	SI4	0.915
	SI5	0.905

Note(s): PE = Performance Expectancy; EE = Effort Expectancy; FC = Facilitating Conditions; SI = Social Influence; BI = Behavioral Intention; EXP = Experience.

Table 3. Hetero-Trait-Mono-Trait (HTMT inference)

	Original Sample (O)	Sample Mean (M)	2.50%	97.50%
EE -> BI	0.686	0.685	0.602	0.761
EXP -> BI	0.052	0.065	0.015	0.158
EXP -> EE	0.035	0.060	0.019	0.129
FC -> BI	0.635	0.635	0.547	0.718
FC -> EE	0.599	0.598	0.498	0.687
FC -> EXP	0.054	0.066	0.022	0.150
PE -> BI	0.747	0.747	0.658	0.821
PE -> EE	0.783	0.783	0.716	0.844
PE -> EXP	0.032	0.061	0.025	0.127
PE -> FC	0.536	0.535	0.426	0.638
SI -> BI	0.417	0.416	0.329	0.495
SI -> EE	0.415	0.414	0.327	0.494
SI -> EXP	0.086	0.09	0.019	0.19
SI -> FC	0.375	0.374	0.265	0.472
SI -> PE	0.41	0.409	0.312	0.499
EXP -> PE and BI	0.039	0.075	0.019	0.191
EXP -> EE and BI	0.021	0.067	0.02	0.168
EXP -> FC and BI	0.013	0.056	0.015	0.14
EXP -> SI and BI	0.032	0.055	0.017	0.129

Note(s): PE = Performance Expectancy; EE = Effort Expectancy; FC = Facilitating Conditions; SI = Social Influence; BI = Behavioral Intention; EXP = Experience.

Table 4. Cross loadings

	BI	EE	FC	PE	SI
BI1	0.907	0.361	0.656	0.655	0.613
BI2	0.904	0.358	0.595	0.597	0.522
BI3	0.893	0.330	0.578	0.593	0.496
BI4	0.879	0.311	0.609	0.604	0.622
EE1	0.364	0.896	0.395	0.389	0.374
EE2	0.334	0.926	0.406	0.362	0.380
EE3	0.379	0.936	0.406	0.353	0.374
EE4	0.314	0.915	0.338	0.306	0.302
EE5	0.341	0.904	0.351	0.328	0.338
FC1	0.635	0.351	0.851	0.648	0.619
FC2	0.586	0.349	0.875	0.655	0.605
FC3	0.585	0.388	0.892	0.669	0.616
FC4	0.532	0.342	0.823	0.608	0.549
PE1	0.591	0.285	0.641	0.842	0.668
PE2	0.575	0.332	0.582	0.813	0.553
PE3	0.590	0.339	0.641	0.890	0.597
PE4	0.559	0.302	0.622	0.847	0.608
PE5	0.576	0.352	0.686	0.831	0.568
SI1	0.570	0.347	0.631	0.613	0.874
SI2	0.529	0.313	0.610	0.572	0.849
SI3	0.536	0.352	0.592	0.567	0.869
SI4	0.557	0.342	0.591	0.655	0.871
SI5	0.515	0.308	0.557	0.635	0.827

Table 5. Fornell-Larker criterion

	BI	EE	FC	PE	SI
BI	0.896
EE	0.380	0.915
FC	0.682	0.416	0.861
PE	0.684	0.381	0.751	0.845
SI	0.632	0.388	0.695	0.709	0.858

Table 6. Outcome of the structural model examination

PLS Path	Original Sample (O)	Sample Mean (M)	Standard Deviation (STDEV)	T Statistics (|O/STDEV|)	P Values	2.50%	97.50%	Remarks
PE -> BI**	0.397	0.408	0.064	6.251	0.000	0.658	0.821	Supported
EE -> BI**	0.164	0.160	0.057	2.864	0.004	0.602	0.761	Supported
FC -> BI**	0.271	0.267	0.051	5.367	0.000	0.547	0.718	Supported
SI -> BI*	0.082	0.079	0.036	2.273	0.023	0.329	0.495	Supported
EXP -> PE and BI^NS	−0.038	−0.010	0.090	0.423	0.672	0.019	0.191	Unsupported
EXP -> EE and BI^NS	0.006	−0.006	0.063	0.092	0.927	0.020	0.168	Unsupported
EXP -> FC and BI^NS	−0.018	−0.028	0.056	0.313	0.754	0.015	0.140	Unsupported
EXP -> SI and BI^NS	0.054	0.045	0.041	1.332	0.183	0.017	0.129	Unsupported

Note(s): PE = Performance Expectancy; EE = Effort Expectancy; FC = Facilitating Conditions; SI = Social Influence; BI = Behavioral Intention; EXP = Experience. * Significant at 5% level, p < 0.05. ** Significant at 1% level, p < 0.01.

Figure 2. Structural model testing.

Table 7. PLS predict

	PLS-SEM			Linear Model Benchmark
	Q^2 _predict	RMSE	MAE	RMSE	MAE
BI1	0.400	1.032	0.807	1.029	0.800
BI3	0.440	0.988	0.771	1.012	0.781
BI4	0.442	1.055	0.819	1.078	0.844
BI2	0.374	1.009	0.777	1.036	0.794

Note(s): PE = Performance Expectancy; EE = Effort Expectancy; FC = Facilitating Conditions; SI = Social Influence; BI = Behavioral Intention; EXP = Experience.

Table 8. Predictive relevance, ${\mathrm{Q}}^2$

Endogenous Constructs	Q^2 (=1-SSE/SSO)
BI	0.633
EE	0.596
FC	0.742
PE	0.564
SI	0.746

Note(s): PE = Performance Expectancy; EE = Effort Expectancy; FC = Facilitating Conditions; SI = Social Influence; BI = Behavioral Intention; EXP = Experience.

Table 9. Effect Size, ${\mathrm{f}}^2$

Predictor Construct/Dependent Construct	Original Sample (O)	T Statistics (|O/STDEV|)	P Values
PE -> BI	0.174	2.904	0.004
EE -> BI	0.027	1.386	0.166
FC -> BI	0.111	2.667	0.008
SI -> BI	0.013	1.105	0.269
EXP -> EE and BI	0.000	0.006	0.995
EXP -> FC and BI	0.001	0.062	0.951
EXP -> PE and BI	0.002	0.165	0.869
EXP -> SI and BI	0.006	0.712	0.477

Note(s): PE = Performance Expectancy; EE = Effort Expectancy; FC = Facilitating Conditions; SI = Social Influence; BI = Behavioral Intention; EXP = Experience.

Table 10. Importance of performance map analysis

	Behavioral intention
Latent variables	Importance (Total Effect)	Performance (Index value)
PE	0.405	65.529
EE	0.161	65.424
FC	0.231	59.633
SI	0.065	44.069
Mean value	0.216	58.664

Note(s): PE = Performance Expectancy; EE = Effort Expectancy; FC = Facilitating Conditions; SI = Social Influence; BI = Behavioral Intention; EXP = Experience.

Figure 3. The artificial neural network architect.

Note(s):

Table 11. RMSE values for independent variables

Input neurons: EE, FC, PE, SI
Output nodes: BI
Neural network	Training			Testing			Total
	N	SSE	RMSE	N	SSE	RMSE
1	371	843.877	0.850	43	92.235	0.784	414
2	366	858.906	0.840	48	96.771	0.789	414
3	363	831.190	0.839	51	102.811	0.732	414
4	357	822.595	0.836	57	117.389	0.766	414
5	369	862.700	0.893	45	84.754	0.714	414
6	367	828.094	0.814	47	91.472	0.892	414
7	368	839.787	0.859	46	87.141	0.806	414
8	359	855.464	0.834	55	87.389	0.778	414
9	356	831.971	0.840	58	90.766	0.805	414
10	362	826.543	0.845	52	101.039	0.805	414
Mean		835.879	0.840		91.854	0.787
SD		13.824	0.020		9.35	0.046

Note(s): PE = Performance Expectancy; EE = Effort Expectancy; FC = Facilitating Conditions; SI = Social Influence; BI = Behavioral Intention; EXP = Experience.

Table 12. Sensitivity analysis with normalized importance for independent variables

Neural network	Relative importance
	EE	FC	PE	SI
1	0.116	0.340	0.187	0.357
2	0.195	0.278	0.135	0.392
3	0.115	0.165	0.214	0.506
4	0.202	0.255	0.191	0.352
5	0.169	0.183	0.201	0.447
6	0.252	0.181	0.151	0.416
7	0.198	0.237	0.190	0.375
8	0.251	0.228	0.128	0.393
9	0.188	0.286	0.110	0.416
10	0.243	0.211	0.189	0.357
Mean relative importance	0.1929	0.2364	0.1696	0.4011
Normalized importance	26.40%	84.40%	0.09%	100%

Note(s): PE = Performance Expectancy; EE = Effort Expectancy; FC = Facilitating Conditions; SI = Social Influence; BI = Behavioral Intention; EXP = Experience

Table

Demographic variable
Gender	Female
	Male
Age	20–30
	30 and above
Education level	Bachelor’s degree/Professional qualification
	Master/PhD degree
Experience	1–2 years
	3–4 years
	Over 5 years

Table

Constructs	Items
Performance Expectancy	PE1: Blockchain is useful in my company operation PE2: Using blockchain can enhance the efficiency of firm’s operations PE3: Using blockchain is convenient for managing PE4: Using blockchain can eliminate processing cost and increase firm’s profits PE5: Blockchain helps me accomplish duties more quickly
Effort Expectancy	EE1: Blockchain is easy to use EE2: I believe that learning how to use blockchain is easy for me EE3: My interaction with blockchain is clear and understandable EE4: I believe that migrating to blockchain is simple for my firm EE5: I believe that my firm comprehend how to implement blockchain in operations
Social Influence	SI1: Blockchain is a new trending system in my sector SI2: I think there are many enterprises using this system SI3: I think the number of people know how to use blockchain is large SI4: People whose opinions that I value prefer that I use Blockchain SI5: People who influence my behavior think that I should learn and use blockchain
Facilitating Conditions	FC1: I believe that my company has the resources necessary to use Blockchain FC2: Blockchain is compatible with other technologies I use FC3: My company will train me knowledge necessary to use Blockchain FC4: I can get help from others when I have difficulties using blockchain
Behavioral Intention	BI1: I would use Blockchain technologies BI2: I expect to use blockchain frequently on the job BI3: My firm intend to digitally transform Logistic BI4: I predict my firm would adopt blockchain in near future