Industrial agglomeration and product quality improvement of food enterprises: empirical analysis based on data from Chinese enterprises

ZHENG, Jiyuan; HU, Hao

doi:10.1590/fst.38521

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Review Article • Food Sci. Technol (Campinas) 42 • 2022 • https://doi.org/10.1590/fst.38521 copy

Industrial agglomeration and product quality improvement of food enterprises: empirical analysis based on data from Chinese enterprises

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

This study utilized data on dairy enterprises, which are representative of China's food industry, to investigate the relationships and mechanisms between industrial agglomeration and the product quality of food enterprises. The results show that industrial agglomeration significantly improves the product quality of Chinese food enterprises. In general, the economic effect of China's food industry agglomeration is greater than that of excessive competition. The heterogeneity analysis showed that industrial agglomeration plays a more important role in promoting the product quality of non-state-owned enterprises and food enterprises in the eastern region than in state-owned enterprises and the central and western regions. Further mechanistic analysis showed that industrial agglomeration promotes food quality improvement by improving enterprise productivity and fixed cost input efficiency. Therefore, this study confirms that industrial agglomeration can be used as an external driving force for China's food quality improvement. On the basis of market mechanisms, through the guidance of the macro policy of industrial agglomeration, the external economies of the scale effect of agglomeration are of great significance for helping the food industry become high quality and high end.

Key words:
industrial agglomeration; product quality; scale economy; empirical analysis

Variable	Mean	Std. Dev	Min	Max
$E S a f$	3.352	0.439	2.990	4.555
Agg	2.216	0.155	0.051	8.207
Hum	0.348	0.104	0.023	0.663
Cap	258.027	493.307	3.869	4215.739
Age	13.447	11.990	0.000	59.000
Sca	112.295	19.803	0.115	198.857
Fin	0.0113	0.337	-1.518	0.671
Gov	0.259	0.438	0	1

Explanatory variables	Explained variables: $E S a f$
Explanatory variables	FE	FE-IV
Agg	0.7476^* ***** Represent significance at the critical levels of 1%;	0.8145^***
Agg	(4.40)	(5.01)
Hum	0.1810^ Represent significance at the critical levels of 5%;	0.5351^**
Hum	(2.15)	(2.26)
Cap	0.1171^* * Represent significance at the critical levels of 10%.	0.2529
Cap	(1.86)	(1.27)
Age	0.8354^**	0.0595^**
Age	(2.12)	(1.98)
Sca	0.4972	0.0008
Sca	(0.51)	(0.01)
Fin	0.2606	0.0186
Fin	(1.08)	(0.94)
Gov	1.0090^***	0.2963^**
Gov	(3.18)	(2.49)
Cons	-0.0748^***	-0.0781^***
Cons	(-7.42)	(-7.67)
Ent	Yes	Yes
Year	Yes	Yes
R²	0.3770	0.7317
N	228	228

Explanatory variables	Explained variables: $E S a f$
Explanatory variables	FE	FE-IV
$A g g$ 2	0.1994^* ***** Represent significance at the critical levels of 1%;	0.3331^***
$A g g$ 2	(4.87)	(7.16)
$H u m$	0.0379^* * Represent significance at the critical levels of 10%.	0.2032^ Represent significance at the critical levels of 5%;
$H u m$	(1.78)	(2.25)
$C a p$	-0.0193	-0.0093
$C a p$	(-0.76)	(-0.28)
$A g e$	0.1985^**	0.7143^***
$A g e$	(2.10)	(3.47)
$S c a$	0.037^*	0.0129
$S c a$	(1.77)	(0.50)
$F i n$	0.0579	0.0535
$F i n$	(1.05)	(1.20)
$G o v$	0.0729^***	0.2006^***
$G o v$	(2.67)	(5.00)
Cons	-0.0012	-0.0605
Cons	(-0.42)	(-0.23)
Ent	Yes	Yes
Year	Yes	Yes
R²	0.5564	0.4945
N	228	228

Explanatory variables	Explained variables: $E S a f$
Explanatory variables	Enterprise heterogeneity	Regional heterogeneity	Enterprise heterogeneity	Regional heterogeneity
$A g g$	0.6874^* ***** Represent significance at the critical levels of 1%;	0.9936^***	—	—
$A g g$	(3.40)	(3.09)	—	—
$A g g 2$	—	—	0.3773^***	0.3991^***
$A g g 2$	—	—	(7.31)	(7.10)
$A g g \times PE$	0.1937^ Represent significance at the critical levels of 5%;	—	—	—
$A g g \times PE$	(2.11)	—	—	—
$A g g \times AE$	0.0125^* * Represent significance at the critical levels of 10%.	—	—	—
$A g g \times AE$	(1.82)	—	—	—
$A g g \times East$	—	3.354^**	—	—
$A g g \times East$	—	(2.07)	—	—
$A g g 2 \times PE$	—	—	0.0108^**	—
$A g g 2 \times PE$	—	—	(2.39)	—
$A g g 2 \times AE$	—	—	0.090^*	—
$A g g 2 \times AE$	—	—	(1.90)	—
$A g g 2 \times East$	—	—	—	0.3142^***
$A g g 2 \times East$	—	—	—	(4.16)
Cont	Yes	Yes	Yes	Yes
Ent	Yes	Yes	Yes	Yes
Year	Yes	Yes	Yes	Yes
Cons	-1.2104	-0.0674	0.207^***	0.0447
Cons	(-1.42)	(-0.08)	(5.83)	(1.44)
R²	0.50	0.45	0.47	0.72
N	228	228	228	228

	$E S a f$	$T f p$	$C a r$	$E S a f$	$E S a f$	$E S a f$
	(1)	(2)	(3)	(4)	(5)	(6)
Agg	0.8145^* ***** Represent significance at the critical levels of 1%;	0.7087^***	0.5161^***	0.2510^***	0.0560^ Represent significance at the critical levels of 5%;	0.0333^* * Represent significance at the critical levels of 10%.
Agg	(5.01)	(3.51)	(3.90)	(2.79)	(2.15)	(1.82)
$T f p$	—	—	—	0.0427^***	—	0.0334^***
$T f p$	—	—	—	(3.30)	—	(3.80)
$C a r$	—	—	—	—	0.9259^***	0.5482^***
$C a r$	—	—	—	—	(3.28)	(3.26)
Cont	Yes	Yes	Yes	Yes	Yes	Yes
Ent	Yes	Yes	Yes	Yes	Yes	Yes
Year	Yes	Yes	Yes	Yes	Yes	Yes
Cons	-0.0781^*** (-7.67)	-2.0933 (-0.97)	-0.0203 (-1.25)	0.3657^*** (3.87)	0.0478 (0.16)	0.0242 (0.85)
R2	0.7317	0.7984	0.7200	0.7889	0.7605	0.7782
N	228	228	228	228	228	228

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[1] *Corresponding author: huhao@njau.edu.cn