Evaluation of food suppliers by multi-channel buyers: Focusing on the moderating effect of distribution channel

Figures & data

Figure 1. Research model.

Table 1. Demographics of responding buyers and evaluated suppliers

Variables	Description	N	Percentage (%)
Distribution channel	Multi-channel retailer = 1	66	60.0
	Only e-commerce = 2	44	40.0
Format of retailer	Hyper market = 1	42	38.2
	Supermarket = 2	11	10.0
	Department store = 3	13	11.8
	E-commerce = 4	33	30.0
	Home & Internet shopping = 5	11	10.0
Buyer gender	Men = 1	72	65.5
	Women = 2	38	34.5
Buyer category	Produce = 1	28	25.5
	Meat and Seafood = 2	16	14.5
	Dried food = 3	14	12.7
	Deli and Bakery = 4	14	12.7
	Chilled and frozen food = 5	15	13.6
	Ambient food = 6	9	8.2
	Snack and Beverages = 7	12	10.9
	Others = 8	2	1.8

Note: Multi-channel retailer (Hyper market, Supermarket, Department store).

Table 2. Descriptive Statistics

Variables		Unit	References	Mean	SD	Min	Max
Buyer	Buyer age	Years	Davies and Treadgold (1999)	36.6	6.5	24	55
	Buyer experience			7.8	4.9	0.9	21
Supplier	Firm size of supplier	Total sales of 2021 (0.1bil. KRW)	Villena et al. (2011)	45.0	132.4	0.08	900
	Experience with the retailer	Months	Jap and Ganesan (2000)	15.8	7.2	1	24
	Criticality in buyer’s category	Sales part% in category	Villena et al. (2011)	17.1	20.2	1	99

Table 3. Constructs and measures

Indicators	References	Loadings	T-value	CR		AVE	α
Product Competency				0.878		0.591	0.826
Offering a competitive price	Lin and Wu (2011)	0.714	11.255
Reducing costs of purchasing activities	Xie et al. (2013)	0.766	14.005
Product quality and freshness	Rong et al. (2022)	0.759	12.795
Product safety		0.849	26.240
Consistency of product quality	Lin and Wu (2011)	0.749	12.390
Offering a variety of products *
Delivery Reliability				0.84		0.725	0.622
On time delivery and ability to reduce damage	Lin and Wu (2011)	0.872	22.671
Volume flexibility to meet the retailer’s demand		0.831	16.289
Service Quality				0.906		0.763	0.845
Rapid response to buyer’s requests	Rong et al. (2022)	0.877	21.745
Quick response time in case of emergency, problem		0.893	31.580
Appropriate handling of customer complaints		0.85	19.522
Technology Level				0.894		0.738	0.823
Quality traceability in the whole process of transaction	Rong et al. (2022)	0.872	42.875
Real time sharing of information		0.863	34.632
Product technology and manufacturing skills	Xie et al. (2013)	0.842	348.673
Innovation Capability				0.886		0.796	0.744
Creating market demand and enhancing competitiveness	Rong et al. (2022)	0.883	35.286
Raising and using of financial funds for R&D		0.901	26.129
Buyer Satisfaction				0.941		0.8	0.916
Relationship with XYZ	Abdul-Muhmin (2005)	0.94	74.007
Products and services we get from XYZ		0.88	26.078
Income received from the sales and margins of XYZ’s products	Jap and Ganesan (2000)	0.853	31.815
XYZ is good company to do business with	Gaski (1986)	0.902	40.002

Notes: * Deleted from final scale.

Table 4. Discriminant validity

Factors	Product Competency	Delivery Reliability	Service Quality	Technology Level	Innovation Capability	Buyer Satisfaction
Product Competency	-
Delivery Reliability	0.719	-
Service Quality	0.804	0.828	-
Technology Level	0.671	0.836	0.704	-
Innovation Capability	0.738	0.73	0.625	0.816	-
Buyer Satisfaction	0.826	0.864	0.776	0.701	0.707	-

Table 5. Item loadings and cross loadings

	Product Competency (PC)	Delivery Reliability (DR)	Service Quality (SQ)	Technology Level (TL)	Innovation Capability (IC)
PC1	0.714	0.401	0.51	0.301	0.41
PC2	0.766	0.418	0.573	0.358	0.49
PC3	0.759	0.31	0.438	0.43	0.35
PC4	0.849	0.442	0.601	0.547	0.528
PC5	0.749	0.417	0.462	0.497	0.448
DR1	0.473	0.872	0.546	0.549	0.419
DR2	0.408	0.831	0.481	0.473	0.429
SQ1	0.599	0.505	0.877	0.514	0.357
SQ2	0.603	0.575	0.893	0.536	0.497
SQ3	0.575	0.499	0.85	0.494	0.446
TL1	0.522	0.555	0.538	0.872	0.574
TL2	0.445	0.477	0.494	0.863	0.565
TL3	0.451	0.516	0.486	0.842	0.51
IC1	0.489	0.395	0.434	0.543	0.883
IC2	0.55	0.488	0.452	0.598	0.901

Note: Bold numbers indicate loadings on the assigned constructs.

Table 6. Wald test results

Block	F	Block	Residual	R^2	Adj. R^2	Change in
		Df	df			ΔR^2	ΔF
Model 1	12.98***	17	92	70.58	65.14	70.58	12.98
Model 2	12.13***	1	91	70.58	64.77	0.0000	0.01
Model 3	13.55***	3	88	76.38	70.75	0.0580	7.20***

Note: ΔR² is the change of R² from the previous model to the next model; ΔF is the change of F value between models.

Table 7. Hierarchical linear model results for buyer satisfaction

		Model 1	Model 2	Model 3
(Intercept)		0.015	−0.002	−0.883
Buyer Characteristics	BC1	−0.026	−0.029	0.088
	BC2	−0.016	−0.018	0.115
	BC3	0.113	0.110	0.013
	BC4	0.126	0.124	0.057
	BC5	−0.198	−0.199	−0.285*
	BC6	−0.119	−0.117	−0.211
	BC7	−0.169	−0.167	−0.222
	BG	−0.071	−0.072	−0.096
	BE	−0.009	−0.009	−0.003
Supplier factors	SS	−0.0001*	−0.0001*	0.0002*
	ER	0.011	0.011	0.055**
	CC	−0.001	−0.001	−0.003
Evaluation factors	PC	0.484***	0.484***	0.553***
	DR	0.219*	0.219*	0.207*
	SQ	0.123	0.124	0.142
	TL	0.059	0.060	0.030
	IC	0.113	0.113	0.091
Moderator	DC		0.011	0.642**
Supplier factors x DC	SS X DC			−0.0002**
	ER X DC			−0.037**
	CC X DC			0.001

Standardized beta coefficients *P < 0.05, **P < 0.01, ***P < 0.001.

where, BC1 ~ BC7 denote buyer category dummy variables (meat and seafood, dried food, deli and bakery, chilled and frozen food, ambient food, snack and beverages, others vs. produce, respectively BC1 to BC7); BG is buyer gender; BE refers to buyer experience; SS is the firm size of supplier; ER denotes experience with the retailer; CC is the criticality (percentage of sales in buyer category); PC is product competency; DR denotes delivery reliability; SQ is service quality; TL is technology level; and IC refers to innovation capability; DC refers to distribution channel.

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Data availability statement

The participants of this study did not give written consent for their data to be shared publicly, so due to the sensitive nature of the research supporting data is not available.