Research on the influencing factors of Chinese agricultural brand competitiveness based on DEMATEL-ISM – Scientific Reports

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Abstract

Agricultural products are pivotal to the national economy, and a comprehensive analysis of brand competitiveness significantly contributes to the support of agricultural structural adjustment and modernization. Focusing on the Yangtze River Delta region of China, this study develops an evaluation index system encompassing four dimensions: core brand competitiveness, brand management, market competitiveness, and innovation in branding. Utilizing a DEMATEL-ISM model, this research elucidates the intrinsic relationships among factors that influence brand competitiveness, resulting in a four-tier hierarchical model. The analysis delineates key factors at superficial, intermediate, and profound levels that influence brand competitiveness. Notably, regional production bases, along with innovations in brand technology and systems, emerge as profound influencers. Drawing on these findings, the study recommends strategies to enhance production foundations, accurately define development trajectories, spearhead technological innovation to foster collective reform efforts, and advocate for institutional advancements to bolster healthy brand growth.

Introduction

As a principal agricultural producer, China’s agricultural product competitiveness significantly influences the country’s agricultural progress. Over the past four decades, due to reform and opening-up policies, China has seen substantial improvements in agricultural productivity. However, its agricultural development remains less advanced compared to developed nations. Agricultural product branding, a critical element of the rural revitalization strategy, plays a pivotal role in fostering agricultural advancement and transformation, enhancing the quality and efficiency of products, increasing farmers’ incomes, and broadening consumer demand. Since 2007, the Chinese government has repeatedly underscored the significance of agricultural product branding, advocating for robust initiatives to promote the establishment of regional public brands, corporate brands, and enhance branding efforts, and to implement the ‘three products and one standard’ (variety optimization, quality improvement, brand creation, and standardized production) strategy to facilitate higher levels of green agricultural development. The 19th National Congress of the Communist Party of China in 2017 highlighted the critical issues of agriculture, rural areas, and farmers as fundamental to national welfare, placing the resolution of these ‘three rural issues’ at the forefront of its agenda.

Enhancing agricultural product brand competitiveness through the rural revitalization strategy is vital for market expansion, income increase, brand loyalty enhancement, international trade promotion, industrial chain optimization, and rural industry restructuring. The No. 1 central document of 2017 advocated for the development of regional public brands and encouraged local governments to develop regional specialty brands supported by leading enterprises and industry associations. The “National Rural Revitalization Strategy Plan (2018–2022)” explicitly called for a faster development of these brands to boost market competitiveness. Subsequent documents in 2020, 2021, and 2022 emphasized strengthening brand building and creating distinctive, ‘small yet beautiful’ specialty agricultural brands, reinforcing China’s commitment to branded agricultural development.

The ongoing refinement of the agricultural branding system underscores its strategic significance in China’s agricultural advancement. Currently, China’s agricultural product market confronts several significant challenges, including variable product quality, redundant branding for single products, low brand recognition, and inadequate branding efforts. The uneven and insufficient development of agricultural product branding is increasingly evident, becoming a major constraint on the rising consumer demand.

Literature Review

Brand Competitiveness of Agricultural Products

Agricultural product branding significantly enhances farmers’ incomes and elevates the quality and efficiency of agricultural practices. This branding is fundamental to achieving greater market influence, increased market share, and enhanced added value for branded products over unbranded counterparts. Serving as an extension of branding within the agricultural sector, it plays an essential role in facilitating communication between agricultural operators and consumers. Moreover, it boosts consumer recognition of agricultural enterprises, as well as the origin and quality of their products.

Branding fundamentally involves an implicit contractual relationship between businesses and consumers. Agricultural product brand competitiveness is defined by a company’s capacity to integrate both internal and external resources while considering consumer psychology. Effective branding strategies—including positioning, communication, operation, and management—help cultivate a favorable brand image, enhance consumer recognition, stimulate purchase behavior, and foster brand loyalty. Additionally, research suggests that the competitiveness of agricultural product brands is intricately linked to commitments to social responsibility and sustainable development.

The millennia-old agricultural civilization of China has created substantial historical wealth. However, due to the smallholder economic structure and cultural traditions, Chinese agricultural practitioners often exhibit weak brand awareness. This shortfall in strong, sustainable competitive brands significantly limits the enhancement of China’s agricultural competitiveness.

Factors Affecting the Competitiveness of Agricultural Brands

The foundational studies on brand competitiveness date back to the 1950s when Levy identified that brands significantly enhance consumer advantages in market competition. Following this, scholarly research systematically explored brand competitiveness theory from diverse perspectives. For instance:

1. Motamenti introduced a global asset model that evaluates brand competitiveness using customer potential, competitive potential, and global potential.
2. Tao Cai and colleagues developed a brand evaluation index system considering six dimensions: positioning, personality, innovation, culture, communication, and customer engagement.
3. Suraksha Gupta determined that brand differentiation positively impacts brand competitiveness.
4. Yishu Liu examined the relationship between the agglomeration effect of agricultural products and brand competitiveness.
5. Yaqi Jin highlighted that market environment, regulations, consumer demand, and technological innovation are critical determinants.

Overview of the Study Area and Extraction of Influencing Factors

Overview of the Study Area

The Yangtze River Delta includes Jiangsu, Zhejiang, Shanghai, and Anhui. Renowned as one of China’s most open and economically robust regions, it plays a significant role in the country’s market dynamics. Analysis reveals that 22 out of China’s top 100 agricultural enterprises are located in this region.

Influence Factor Extraction and Interpretation

Initially, literature review findings were integrated with expert interviews to pinpoint twelve determinants of agricultural product brand competitiveness. These were organized into four categories: foundational, management, market, and innovative competitiveness.

Research Methodology and Process

Overall Process

DEMATEL is a methodology devised by BOTTELLE Laboratories employing graph theory and matrix tools to identify factors influencing brand competitiveness. This method operates without assumptions but lacks intuitive representation of interactions between internal factors. To overcome this shortcoming, ISM (Interpretive Structure Modeling) was introduced.

DEMATEL Method

Determine Influencing Factors and Establish Relationship Matrix X

Identify the set of influencing factors (S = left{ {S_{i} left| i right. = 1,2,ldots,n} right}), with Sij denoting the degree of influence of factor Si on Sj.

Calculation of Integrated Impact Matrix

Normalize using row and maximum value methods to derive standardized direct impact matrix Z. Construct comprehensive impact matrix T using formula (T=Z{left(A-Zright)}^{-1}).

Analysis of the Article on Agricultural Brand Competitiveness in the Yangtze River Delta

1. Which SDGs are addressed or connected to the issues highlighted in the article?

1. SDG 2: Zero Hunger
2. SDG 8: Decent Work and Economic Growth
3. SDG 9: Industry, Innovation, and Infrastructure
4. SDG 12: Responsible Consumption and Production

2. What specific targets under those SDGs can be identified based on the article’s content?

1. SDG 2: Zero Hunger
   • Target 2.3: By 2030, double the agricultural productivity and incomes of small-scale food producers.
   • Target 2.4: Ensure sustainable food production systems and implement resilient agricultural practices.
2. SDG 8: Decent Work and Economic Growth
   • Target 8.2: Achieve higher levels of economic productivity through diversification, technological upgrading, and innovation.
   • Target 8.3: Promote development-oriented policies that support productive activities, decent job creation, entrepreneurship, creativity, and innovation.
3. SDG 9: Industry, Innovation, and Infrastructure
   • Target 9.1: Develop quality, reliable, sustainable, and resilient infrastructure.
   • Target 9.5: Enhance scientific research, upgrade technological capabilities of industrial sectors in all countries.
4. SDG 12: Responsible Consumption and Production
   • Target 12.2: By 2030, achieve the sustainable management and efficient use of natural resources.
   • Target 12.3: By 2030, halve per capita global food waste at the retail and consumer levels and reduce food losses along production and supply chains.

3. Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?

1. Indicators for SDG 2:
   • Indicator 2.3.1: Volume of production per labor unit by classes of farming/pastoral/forestry enterprise size.
   • Indicator 2.4.1: Proportion of agricultural area under productive and sustainable agriculture.
2. Indicators for SDG 8:
   • Indicator 8.2.1: Annual growth rate of real GDP per employed person.
   • Indicator 8.3.1: Proportion of informal employment in non-agriculture employment, by sex.
3. Indicators for SDG 9:
   • Indicator 9.1.1: Proportion of the rural population who live within 2 km of an all-season road.
   • Indicator 9.5.1: Research and development expenditure as a proportion of GDP.
4. Indicators for SDG 12:
   • Indicator 12.2.1: Material footprint, material footprint per capita, and material footprint per GDP.
   • Indicator 12.3.1: Global food loss index.

4. Findings from Analyzing the Article