Consumers’ Attitudes and Purchase Behavior of HMR (Home Meal Replacement) Using Locally Sourced Food

Figures & data

Figure 1. Research model.

Table 1. Demographics of respondents

Demographic variable	Frequency (%)
Gender
Male	338 (41.9)
Female	469 (58.1)
Age
20 to 29 years old	103 (12.8)
30 to 39 years old	115 (14.3)
40 to 49 years old	176 (21.8)
50 to 59 years old	212 (26.3)
60 years old or older	201 (24.9)
Education level
High school or less	170 (21.1)
Bachelor’s degree	533 (66.0)
Master’s degree or higher	104 (12.9)
Household income (per-month)
Less than 3 million KRW/3,000 USD	212 (26.3)
3 to 6 million KRW/3,000 ~ 6,000 USD	363 (45.0)
More than 6 million KRW/6,000 USD	232 (28.7)
Marital Status
Married	503 (62.3)
Non-married	304 (37.7)
Total	807 (100.0)

Table 2. Questionnaire items and reliability

Items	Mean	S.D.^1)	Cronbach’s α
Attributes of HMR using locally sourced food			0.806
Price	4.12	0.64
Taste	4.12	0.63
Quantity	3.70	0.73
Cooking convenience	3.82	0.70
100% domestic ingredients	4.16	0.76
Eco-friendly ingredients	4.02	0.77
Origin of ingredients	3.96	0.73
Package design	3.10	0.77
Frequency of promotions	3.26	0.76
Brand awareness	3.40	0.82
Consumer trust of HMR using locally sourced food			0.746
Producers of HMR using locally sourced food are reliable	3.64	0.69
Retailers of HMR using locally sourced food are reliable	3.41	0.73
Purchase intention of HMR using locally sourced food			0.875
I will purchase HMR using locally sourced food in the near future.	3.43	0.79
I am willing to invest time and money to purchase HMR using locally sourced food.	3.36	0.81
When purchasing food, I will prioritize HMR using locally sourced food over regular HMR.	3.43	0.82

^aS.D.: Standard deviation.

Table 3. Results of exploratory factor analysis of perceived importance of attributes of HMR using locally sourced food

Variable	Loading	Eigen value	% of variance	Cumulative %	Cronbach’s α
		3.690	36.9	36.9	0.765
Product attributes
Price	0.830
Taste	0.779
Quantity	0.706
Cooking convenience	0.614
Ingredient attributes		1.513	15.131	52.031	0.766
100% domestic ingredients	0.863
Eco-friendly ingredients	0.843
Origin of ingredients	0.633
Retail attributes		1.325	13.252	65.283	0.725
Package design	0.833
Frequency of promotions	0.784
Brand awareness	0.708

Table 4. Goodness-to-fit index of the measurement model with confirmation factor analysis

Model	χ2^1)	df^2)	CFI^3)	TLI^4)	RMR^5)	RMSEA^6)
Optimum model	p-value < 0.05	-	0.9 ≤ ~ < 1	0.9 ≤ ~ < 1	~ < 0.05	~ < 0.05
Measurement model	25.151*	13	0.994	0.987	0.012	0.034

¹⁾χ2: Chi-square.

²⁾df: Degree of freedom.

³⁾CFI: Comparative fit index.

⁴⁾TLI: Tuker-Luwis index.

⁵⁾RMR: Root mean residual.

⁶⁾RMSEA: Root means squared error of approximation.

* p < .05

Table 5. Results of hypothesis testing

Path		B^1)	β^2)	S.E.^3)	C.R.^4)	p-value	Hypothesis testing
H1a	Product attributes → Consumer trust	0.090***	0.160***	0.021	4.181	0.000	Accepted
H1b	Ingredient attributes → Consumer trust	0.148***	0.264***	0.022	6.787	0.000	Accepted
H1c	Retail attributes → Consumer trust	0.162***	0.290***	0.022	7.427	0.000	Accepted
H2a	Product attributes → Purchase intention	−0.014	−0.021	0.022	−0.64	0.522	Rejected
H2b	Ingredient attributes → Purchase intention	0.116***	0.169***	0.023	5.015	0.000	Accepted
H2c	Retail attributes → Purchase intention	0.004	0.006	0.023	0.18	0.858	Rejected
H3	Consumer trust → Purchase intention	0.761***	0.623***	0.060	12.587	0.000	Accepted

¹⁾B: Unstandardized coefficients.

²⁾β: Standardized coefficients.

³⁾S.E.: Standard error.

⁴⁾C.R.: Critical ratio.

*** p < .001

Figure 2. Results of structural equation modeling.