Switching intention to online channel in Vietnam – A case study of consumer electronics goods

Figures & data

Figure 1. The Push-Pull-Mooring framework.

Source: Bansal et al. (2005)

Figure 2. Research model.

Table 1. Demographic information.

Demographic Characteristics	Nominal/Ordinal scale	Number	Percentage
Gender	Male	559	50.63%
	Female	545	49.37%
Age	Under 23	384	34.78%
	23–30	519	47.01%
	30–40	126	11.41%
	Over 40	75	6.79%
Profession	Student	348	31.52%
	Working	756	68.48%
Place	Hanoi	496	44.93%
	Da Nang	80	7.25%
	Ho Chi Minh city	528	47.83%
Online buy times	0	176	15.94%
	1–2	451	40.85%
	3–4	210	19.02%
	Over 5	267	24.18%
Product type	Smartphone	254	23.01%
	Sound devices	437	39.58%
	Television	14	1.27%
	Visual devices	25	2.26%
	Appliance	208	18.84%
	Others	166	15.04%
Buying channel	Pure online	209	18.93%
	Click-and-mortar	775	70.20%
	Facebook	120	10.87%
Expenditure (USD)	Under 216	584	52.90%
	216–432	214	19.38%
	432–2160	279	25.27%
	Over 2160	27	2.45%
Phase	Controlled	405	36.69%
	Widespread	312	28.26%
	Normal	387	35.05%

+ Male accounted for 50.63% (559) compared to 49.37% of females.

+ The percentages of age of the respondents are 34.78%, 47.01%, 11.41%, 6.79% for age groups of under 23, 23–30, 30–40, and above 40, respectively.

+ Respondents who are students, and those who are having a job account for 31.52% and 68.48%, respectively.

+ Those who live in Hanoi, Da Nang and Ho Chi Minh account for 44.93%, 7.25%, and 47.83%, respectively. This is appropriate with population size ratio (8; 1.2; 9 million in these cities, respectively) when comparing these three cities.

+ Times of buying goods in online channel account for 15.96%, 40.85%, 19.03% and 24.18% for 0, 1–2, 3–4, above 5 times, respectively.

+ The types of products bought in online channel are mobile phones, sound devices, televisions, visual devices, appliances and others (23.01%, 39.58%, 1.27%, 2.21%, 18.84% and 15.04%, respectively).

+ Types of online channel include pure online retailer, brick-and-mortar, Facebook (18.93%, 70.20% and 10.87%).

+ Expenditure of under 216 USD (equal to 5 million VND), 216–432 2160 USD, 432–2160 USD and above 2160 USD accounts for 52.90%, 19.38%, 25.27% and 2.45%, respectively.

+ The phases that COVID-19 was basically controlled (2020–28/01/2021), COVID-19 was spreading in the community (28/01/2021–01/2022) and the period that people were adapting to new normal conditions in the society (from 01/2022 on) were also surveyed (with responses accounting for 36.69%, 28.26%, 35.05%, respectively.

Table 2. Internal consistency and convergent validity (first order latent variables).

	Cronbach’s Alpha	Composite Reliability	Average Variance Extracted (AVE)
Attitude	0.879	0.917	0.735
Convenience (online)	0.945	0.955	0.751
Disadvantages (offline)	0.816	0.879	0.645
Habit	0.894	0.926	0.759
Perceived Risk (online)	0.908	0.927	0.618
Perceived ease of use	0.905	0.933	0.778
Physical store Experience	0.918	0.934	0.671
Price (online)	0.871	0.912	0.721
Subjective Norms	0.887	0.922	0.747
Switching Intention	0.895	0.934	0.826
Vicarious Experience	0.906	0.935	0.782

Table 3. Internal consistency and convergent validity (second order latent variables).

	Cronbach’s Alpha	Composite Reliability	Average Variance Extracted (AVE)
Push	0.863	0.834	0.717
Pull	0.955	0.925	0.805
Mooring	0.941	0.889	0.729

Table 4. Discriminant validity (among first order latent variables with reflective constructs).

	Attitude	Convenience (online)	Disadvantages (offline)	Habit	Perceived Risk (online)	Perceived ease of use	Physical store Experience	Price	Subjective Norms	Switching Intention	Vicarious Experience
Attitude	0.857
Convenience (online)	0.282	0.866
Disadvantages (offline)	0.260	0.329	0.803
Habit	−0.194	−0.035	−0.088	0.871
Perceived Risk (online)	−0.192	0.120	0.039	0.284	0.786
Perceived ease of use	0.280	0.742	0.346	−0.066	0.058	0.882
Physical store Experience	−0.086	0.181	0.093	0.207	0.587	0.155	0.819
Price (online)	0.218	0.715	0.384	−0.057	0.034	0.696	0.121
Subjective Norms	−0.004	0.224	0.158	0.178	0.543	0.197	0.672	0.849	0.865
Switching Intention	0.550	0.418	0.335	−0.274	−0.229	0.435	−0.087	0.164	−0.046	0.909
Vicarious Experience	0.266	0.434	0.439	−0.045	0.051	0.424	0.164	0.397	0.189	0.348	0.884

Table 5. Discriminant validity (second order and first order latent variables with reflective constructs).

	Attitude	Habit	Mooring	Pull	Push	Switching Intention
Attitude	0.857
Habit	−0.194	0.871
Mooring	−0.125	0.267	0.700
Pull	0.292	−0.055	0.178	0.785
Push	0.310	−0.076	0.150	0.511	0.718
Switching Intention	0.550	−0.274	−0.153	0.460	0.403	0.909

Table 6. Colinearity between latent variables.

	Switching Intention
Att*Ha	1.003
Attitude	1.208
Habit	1.117
Mooring	1.201
Pull	1.431
Pull*Moor	1.628
Push	1.434
Push*Moor	1.601

Table 7. Regression analysis results.

	Original Sample	P Values	Hypothesis
Push -> Switching Intention	0.150	0.000	H1: supported
Pull -> Switching Intention	0.294	0.000	H2: supported
Mooring -> Switching Intention	−0.140	0.000	H3: supported
Push*Moor -> Switching Intention	0.002	0.932	H3d: unsupported
Pull*Moor -> Switching Intention	0.018	0.448	H3e: unsupported
Perceived Risk (online) -> Attitude	−0.192	0.000	H4: supported
Attitude -> Switching Intention	0.374	0.000	H5: supported
Habit -> Switching Intention	−0.136	0.000	H6: supported
Att*Ha -> Switching Intention	−0.031	0.311	H6a: supported

Figure 3. Research results.

Table 8. Prediction performance test.

	PLS	LM	Difference	PLS	LM	Blindfolding
	RMSE	MAE		Q^2	Q^2	Q^2
SI1	1.240	1.241	−0.001	0.274	0.263	0.376 (SI)
SI2	1.317	1.324	−0.007	0.224	0.199
SI3	1.278	1.281	−0.003	0.279	0.267

Table

Item <—Latent variable	Factor 1 (EFA)	Factor 2 (EFA)	Loading (CFA)	CR (>0.7)	AVE (>0.5)
DIS1<—Disadvantages	0.825		0.724	0.894	0.685
DIS2<—Disadvantages	0.823		0.818
DIS3<—Disadvantages	0.701		0.688
DIS4<—Disadvantages	0.741		0.635
VE1<—Vicarious Experience		0.887	0.908	0.809	0.517
VE2<—Vicarious Experience		0.909	0.919
VE3<—Vicarious Experience		0.875	0.860
VE4<—Vicarious Experience		0.696	0.578
KMO = 0.841, Bartlett = 1218.176 (sig 0.00); Total variance = 69.698%, Eigen values 2 components
Fornell-Larcker
	Vicarious Experience
Disadvantages
Vicarious Experience	0.82806
Disadvantages	0.474	0.71935

Table

Item <—Latent variable	Factor 1 (EFA)	Factor 2 (EFA)	Factor 3 (EFA)	Loading (CFA)	CR (>0.7)	AVE (>0.5)
PEOU1<—PEOU	0.770			0.614	0.839	0.570
PEOU2<—PEOU	0.779			0.692
PEOU3<—PEOU	0.782			0.885
PEOU4<—PEOU	0.790			0.803
Pr1<—Price		0.827		0.768	0.849	0.584
Pr2<—Price		0.700		0.735
Pr3<—Price		0.757		0.762
Pr4<—Price		0.790		0.792
CO1<—Convenience			0.682	0.743	0.912	0.601
CO2<—Convenience			0.691	0.658
CO3<—Convenience			0.760	0.795
CO4<—Convenience			0.735	0.750
CO5<—Convenience			0.776	0.797
CO6<—Convenience			0.772	0.841
CO7<—Convenience			0.830	0.827
KMO = 0.915, Bartlett = 2599.009 (sig 0.00); Total variance = 68.212%, Eigen values 3 components
Standard Fornell-Larcker
	Price	PEOU	Conveni-ence
Price	0.76452
PEOU	0.553	0.75563
Convenience	0.626	0.628	0.77515

Table

Item <—Latent variables	Factor 1 (EFA)	Factor 2 (EFA)	Factor 3 (EFA)	Loading (CFA)	CR (>0.7)	AVE (>0.5)
SN1<—SN	0.815			0.833	0.901	0.504
SN2<—SN	0.783			0.857
SN3<—SN	0.725			0.781
SN4<—SN	0.719			0.640
PRON1<—Perceived risks		0.808		0.781	0.861	0.612
PRON2<—Perceived risks		0.633		0.628
PRON3<—Perceived risks		0.734		0.687
PRON4<—Perceived risks		0.629		0.642
PRON5<—Perceived risks		0.802		0.788
PRON6<—Perceived risks		0.779		0.774
PRON7<—Perceived risks		0.623		0.693
PRON8<—Perceived risks		0.685		0.694
PRON9<—Perceived risks		0.652		0.687
PsE1<—PhysicalStoreEXP			0.637	0.743	0.901	0.566
PsE2<—PhysicalStoreEXP			0.764	0.782
PsE3<—PhysicalStoreEXP			0.694	0.70
PsE4<—PhysicalStoreEXP			0.766	0.763
PsE5<—PhysicalStoreEXP			0.769	0.732
PsE6<—PhysicalStoreEXP			0.759	0.732
PsE7<—PhysicalStoreEXP			0.820	0.812
KMO = 0922, Bartlett = 3438.71 (sig 0.00); Total variance = 62.627%, Eigen values 3 components
Fornell-Larcker
	Perceived Risks	Subjective Norms
PhysicalStoreExp
Perceived Risks	0.78229
Subjective Norms	0.606	0.71043
PhysicalStoreExp	0.535	0.618	0.75278

Table

Item <—Latent variable	Loading (EFA)	Loading (CFA)	CR (>0.7)	AVE (>0.5)
AT1<—Attitude	0.842	0.842	0.867	0.62
AT2<—Attitude	0.817	0.833
AT3<—Attitude	0.791	0.768
AT4<—Attitude	0.818	0.702
HA1<—Habit	0.882	0.850	0.885	0.659
HA2<—Habit	0.856	0.796
HA3<—Habit	0.849	0.790
HA4<—Habit	0.861	0.810
SI1<—Switching intention	0.827	0.768	0.798	0.569
SI2<—Switching intention	0.773	0.716
SI3<—Switching intention	0.825	0.778

Table

Perspective	Validation	Thresholds
Reflective construct	- Internal consistency (Cronbach’s alpha, CR) - Convergent validity (AVE) - Discriminant validity (Fornell-Larcker)	- Cronbach’s alpha > 0.6; 0.6 < CR < 0.95 - AVE > 0.5 - $\sqrt{\mathrm{A}\mathrm{V}\mathrm{E}}$> correlation coefficient between a latent variable and other
Formative construct	- Convergent validity (AVE, w) - Colinearity between indicators (VIF) - Significant and relevance of outer weight (p-value and hypothesis)	- AVE > 0.5, w > 0.8 (path between formative and reflective constructs of the same latent variable) - VIF < 5 - p-value < 0.05 and reasonable with hypothesis
Inner model (among latent variables)	- Colinearity between variables - P regression path coefficient - Determination coefficient	- VIF < 5 - P suitable to hypothesis and p-value <0.05 - 0 < R^2 < 1
Predictivity	- Apply the blindfolding and PLSpredict	- Q^2: weak (<0.02), moderate (>0.15 and <0.35), strong (>0.35); RMSE(or MAE) of PLS-SEM < those of LM

Table

	VIF RandomVar
AttitudeVar	1.498
ConvenienceVar	2.845
DisadvantagesVar	1.373
HabitVar	1.155
Perceived RiskVar	1.795
Perceived ease of useVar	2.648
Physical store ExperienceVar	2.120
PriceVar	2.474
RandomVar
Subjective NormsVar	2.024
Switching intentionVar	1.871
Vicarious ExperienceVar	1.484

Table

Code	Items	Source
Push – Disadvantages (store buying channels)
DIS1	Information at physical stores does not always meet my requirements	Lester et al. (2006); Gupta (2015); Sultan and Uddin (2011); Verhoef et al. (2007)
DIS2	There are fewer options at physical stores than through online channels	Santana and Loureiro (2010); Harn et al. (2006)
DIS3	I spend more time buying products at physical stores	Lester et al. (2006); Santana and Loureiro (2010); Gupta (2015)
DIS4	I am hesitant if I don’t buy	Santana and Loureiro (2010)
Pull – Vicarious experience (of other people)
VE1	My colleagues buy electronics consumer goods online successfully	Chiu et al. (2011)
VE2	My friends buy electronics consumer goods online successfully
VE3	My family members buy electronics consumer goods online successfully
VE4	My acquaintances buy electronics consumer goods online successfully
Pull – Price (online channels)
Pr1	Price in online channels is more reasonable than at physical stores	Swinyard and Smith (2003); Lester et al. (2006); Harn et al. (2006); Gupta (2015); Elida et al. (2019); Elida et al. (2019)
Pr2	I can compare prices through many online channels	Lester et al. (2006); Rahman et al. (2018);
Pr3	Online channels offer many promotional offers	Verhoef et al. (2007); Gupta (2015)
Pr4	Buying products online saves my money	Harn et al. (2006); Chang (2003); Elida et al. (2019); Yeo et al. (2017)
Pull – Convenience (online channel)
CO1	I can find good information about the products online	Forsythe et al. (2006); Santana and Loureiro (2010); Jiang et al. (2013); Duarte et al. (2018)
CO2	I can easily compare products and sellers	Santana and Loureiro (2010); Sultan and Uddin (2011); Duarte et al. (2018)
CO3	I have more alternatives of electronics consumer goods to make a choice thanks to searching online	Forsythe et al. (2006); Santana and Loureiro (2010); Swinyard and Smith (2003); Lester et al. (2006); Jiang et al. (2013)
CO4	I don’t need to take much effort (leaving home, travelling, queuing, waiting to be served …) when buying in online channels	Forsythe et al. (2006); Santana and Loureiro (2010); Rahman et al. (2018); Jiang et al. (2013)
CO5	Buying products through online channels saves my time.	Santana and Loureiro (2010); Sultan and Uddin (2011); Harn et al. (2006)
CO6	I can order products online any time.	Forsythe et al. (2006); Santana and Loureiro (2010); Sultan and Uddin (2011); Rahman et al. (2018); Lester et al. (2006); Uzan (2014); Jiang et al. (2013); Duarte et al. (2018)
CO7	I can track the order easily (via email, tracking system …)	Proposed by the authors, based on the research of Rao et al. (2011)
Pull - Perceived ease of use
PEU1	I can easily learn to buy products through online channels although this is the first time	Ho and Chen (2014), Perea et al. (2004), Lin (2007), Ye and Potter (2011a); Bauerová and Klepek (2018)
PEU2	It is easy for me to learn to buy products online
PEU3	I can easily buy products online
PEU4	For me, buying through online channels is easy to perform
Mooring - Perceived risks (online channels)
PRON1	I am concerned about the origin of products	Proposed by the authors
PRON2	My personal information may not be protected (hacked, or provided for other partners)	Forsythe et al. (2006); Santana and Loureiro (2010); Rahman et al. (2018); Wani and Malik (2013b)
PRON3	I may not receive the order I make through online channels	Wani and Malik (2013b); Nguyễn Hoàng Diễm Hương et al. (2016); Hà Ngọc Thắng (2015)
PRON4	I may have to wait for the online delivery longer than expected	Forsythe et al. (2006); Lester et al. (2006); Corbitt et al. (2003)
PRON5	I believe that buying products through online channels has many risks because I cannot touch and feel the product	Forsythe et al. (2006); Lester et al. (2006); Swinyard and Smith (2003); Campo and Breugelmans (2015); Hà Ngọc Thắng (2015); Haridasan et al. (2021)
PRON6	I believe that buying products through online channels has many risks because I cannot try on the products	Forsythe et al. (2006); Lester et al. (2006); Santana and Loureiro (2010); Wani and Malik (2013b); Swinyard and Smith (2003); Nguyễn Hoàng Diễm Hương and cộng sự (2016); Hà Ngọc Thắng (2015); Haridasan et al. (2021)
PRON7	I don’t buy products through online channels if there is no refund policy	Javadi et al. (2012); Lester et al. (2006); Swinyard and Smith (2003); Nguyễn Hoàng Diễm Hương and cộng sự (2016); Verhoef et al. (2007)
PRON8	I feel it is difficult to solve conflicts when buying through online channels
PRON9	I feel worried when buying electronics consumer goods through online channels	Marriott and Williams (2018); Corbitt et al. (2003)
Mooring - Subjective norms
SN1	My influencers think that electronics consumer goods should be bought at physical stores	Bansal et al. (2005), Lian and Yen (2013), Zheng (2013) Ho and Chen (2014), Ye and Potter (2011a)
SN2	People who are important for me encourage me to buy electronics consumer goods at physical stores
SN3	People that I know encourage me to buy electronics consumer goods at physical stores
SN4	Generally, electronics consumer goods should be bought at physical stores
Mooring – (Lack of) physical store experience
PsE1	I find buying at physical stores interesting	Bustamante and Rubio (2017), Terblanche (2018)
PsE2	I find buying at physical stores relaxing
PsE3	I have a positive feeling when I buy at physical stores.
PsE4	Physical stores have attractive product display
PsE5	I can interact and communicate with other consumers at physical stores
PsE6	I need consultation from salespeople
PsE7	I can test products at physical stores	Swinyard and Smith (2003), Rahman and Mannan (2018)
Habit (buying electronics consumer goods)
HA1	I automatically buy at physical stores	Lai (2015); Sun et al. (2017); Cheng et al. (2019); Lin and Wang (2017); Xu et al. (2017); Ye and Potter (2011a)
HA2	Buying at physical stores is obvious to me
HA3	When I need to buy electronics consumer goods, physical stores are my obvious choice
HA4	I choose to buy at physical stores unconsciously
Attitude (toward switching to online channels
AT1	Switching to online channels is a _______ idea (scaling from bad to good)	Bansal et al. (2005), Madahi and Sukati (2014)
AT2	Switching to online channels is a _______ idea (scaling from harmful to beneficial)
AT3	Switching to online channels is a _______ idea (scaling from useless to useful)
AT4	Buying through online channels is a more attractive alternative than buying through traditional channels
Switching intention (from traditional channels to online channels)
SI1	I consider switching to buy electronics consumer goods through online channels	Lai (2015); Chen and Keng (2019); Cheng et al. (2019)
SI2	The possibility that I switch to buy electronics consumer goods in online channels is ______ (scaling from unlikely to likely)	Bansal et al. (2005); Lai (2015); Chen and Keng (2019); Cheng et al. (2019)
SI3	I will switch to buy electronics consumer goods online in the near future	Chen and Keng (2019); Zhou (2015)

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