Global-Local Integrated Path Planning Strategy for Agricultural Robots in Complex Hilly Orchard Environments

About us
All journals
All articles
Submit manuscript
Submit data
Search
Login
Frontiers in Sustainable Food Systems
Sections
Articles
Research Topics
Editorial board
About journal
Published in

Frontiers in Sustainable Food Systems

Agricultural and Food Economics
4.1
impact factor
6
citescore

Part of a Research Topic

Strengthening Community Governance for Resilient and Sustainable Food Futures

15k views
14 articles
Editor & Reviewers

Edited by

IVAN ANTONIO GARCIA-MONTALVO

Reviewed by

Jessa Frida Festijo

Oliver Eboy

Outline

Abstract

1 Introduction

2 Literature review

3 Research design

4 Analysis of the online fresh produce market

5 Market research and analysis

6 Conclusions and recommendations

Data availability statement

Ethics statement

Author contributions

Funding

Conflict of interest

Generative AI statement

Publisher’s note

Supplementary material

References

Figures and Tables

Figure 1

View in article

Figure 2

View in article

Figure 3

View in article

Figure 4

View in article

Figure 5

View in article

Figure 6

View in article

Figure 7

View in article

Figure 8

View in article

Figure 9

View in article

Figure 10

View in article

Table 1

Satisfaction reliability test table.

View in article

Table 2

Significance and reliability test table.

View in article

Table 3

KMO and Bartlett’s test of sphericity.

View in article

Table 4

KMO and Bartlett’s test of sphericity.

View in article

Table 5

Thematic feature keywords.

View in article

Table 6

Weight allocation table for fresh food theme.

View in article

Table 7

Self-adjoint fuzzy matrix table.

View in article

Table 8

Corresponding numbers for online fresh food platforms.

View in article

Table 9

Improved specification weighting matrix.

View in article

Table 10

Results of the improved intuitive fuzzy TOPSIS evaluation.

View in article

Table 11

Product data characteristics and descriptive statistics.

View in article
ORIGINAL RESEARCH article

Front. Sustain. Food Syst., 02 July 2026

Sec. Agricultural and Food Economics

Volume 10 - 2026 | https://doi.org/10.3389/fsufs.2026.1866736

Fresh food retail satisfaction and sales forecasts: digital integration for sustainability in Guiyang, China

Changpeng Yang 1†

K
H

Keyan He 2†

F
H

Fu Hong 3†

Y
Z

Yufeng Zhu 4

Liming Chen 1*

1. School of Tourism and Resource Environment, Qiannan Normal University for Nationalities, Duyun, China

2. Party School of the Libo County Committee of the Communist Party of China, Libo, Guizhou, China

See more

Article metrics

View details

1,4k

Views

118

Downloads

Abstract

Introduction:

Driven by the digital economy, China’s fresh food retail sector is accelerating its transition toward omnichannel integration. However, existing research has largely focused on first-tier cities in eastern China, paying insufficient attention to the heterogeneity of underdeveloped regions in southwestern China, and lacking a systematic analytical framework that integrates multi-source data and multiple methodologies.

Methods:

This study takes six mainstream online fresh food platforms in Guiyang, China (including the local platform ‘Guihuihui’) as its research subjects. By integrating two rounds of stratified sampling questionnaire surveys (1,744 valid responses) with 16,321 online review data points, we constructed a multi-model integrated analytical framework comprising an LDA topic model, an improved intuitive fuzzy TOPSIS method, and the AT-DeepAR deep learning model. This framework was used to systematically investigate the mechanisms underlying the evolution of fresh food retail formats, the factors influencing consumer satisfaction, and market sales forecasting.

Results:

The study found that: (1) transaction costs and service quality are the core drivers of digital transformation in fresh food retail, with consumers placing the greatest emphasis on delivery speed and shopping experience; (2) platform satisfaction rankings are as follows: Duoduo Grocery > Meituan Youxuan > JD NOW > Freshippo > Guihuihui > Dingdong Maicai, with national platforms enjoying significantly higher brand recognition than local platforms; (3) the AT-DeepAR model, incorporating an attention mechanism, can accurately capture the seasonal fluctuations in fresh produce sales, with predicted values closely matching actual figures (within a 95% confidence interval). It forecasts that the average monthly sales of fresh produce platforms in Guiyang will steadily increase to approximately 340 million yuan by 2025.

Discussion:

At the theoretical level, this paper fills a research gap on fresh food e-commerce in southwestern China by establishing an integrated analytical paradigm combining questionnaire data, text mining, and deep learning. At the practical level, it provides empirical evidence to support differentiated competition, transaction cost optimization, and the digital upgrading of the regional fresh food industry for local platforms in Guiyang. It holds significant practical value for promoting the sustainable development of fresh food retail, enhancing the efficiency of urban–rural food distribution, and facilitating the low-carbon transition of supply chains.

1 Introduction

The rapid development of internet technology and shifts in consumer behavior have made online shopping an integral part of daily life. Against this backdrop, online fresh food shopping has emerged and is growing rapidly. As a key province in south-western China, Guizhou has seen sustained growth in the demand for fresh produce in recent years, driven by both urbanization and consumption upgrades (Guizhou Provincial Bureau of Statistics, Guizhou Provincial Office of the Leading Group for the Seventh National Population Census, 2021). Fueled by the pandemic, more consumers have turned to ‘online shopping’, presenting numerous challenges to traditional fresh food retail models, which suffer from low delivery efficiency, high costs and a lack of personalized service.

In recent years, the evolution of the fresh food retail sector has become increasingly evident. Traditional farmers’ markets and supermarkets have gradually shifted from offline to online operations, while new retail models such as front-end warehouses (e.g., Freshippo, Dingdong Maicai) and community group-buying platforms (e.g., Meituan Youxuan, Duoduo Grocery) have rapidly emerged. These platforms meet consumers’ demands for timeliness and convenience through an ‘online ordering + offline delivery’ model, making the integrated online-offline retail model increasingly prominent.

Against this background, Guizhou Province launched the “Guihuihui” online fresh produce platform in 2022, integrating high-quality fresh produce resources from Guiyang and its surrounding areas (Zhongwang News, 2022). The platform breaks through the spatial and temporal barriers of traditional retail, centring on the digital reconstruction of the “people-goods-place” model to drive the transformation of supermarket retail formats. Through efficient service and high-quality products, it has rapidly gained market recognition and consumer trust, demonstrating strong growth momentum.

As a critical link in the food supply chain, the digital transformation and service optimization of fresh food retail have a direct bearing on food security, resource conservation, the reduction of wastage and losses, and the improvement of the quality of life for urban and rural residents. This study focuses on consumer groups in Guiyang, China, conducting an empirical analysis of consumer satisfaction through a questionnaire survey (Hongxin and Yuhui, 2015). It examines online fresh produce platforms in Guiyang, analyses the evolution of the fresh produce retail sector, explores the extent to which these platforms meet consumer needs and their impact on market development, reviews the current state of the fresh produce market, identifies shortcomings, and offers constructive suggestions and references for the market’s future development.

2 Literature review

Driven by the dual forces of the digital economy and consumption upgrades, China’s fresh food retail sector is rapidly shifting from traditional offline models toward diverse business formats such as omnichannel integration, community group buying and forward-depot models. Online fresh food retail has become the mainstream consumption channel due to its convenience, efficiency and value for money. The evolution of fresh food retail formats is the result of the combined influence of transaction costs, digital technology, cold-chain logistics and consumer behavior, whilst consumer satisfaction serves as a core indicator influencing repeat purchases and brand loyalty. Existing research has yielded substantial findings regarding the mechanisms of business model evolution, factors influencing satisfaction, evaluation models and sales forecasting; however, studies have generally focused on first-tier cities in the east and national platforms. There remains a notable lack of integrated research that targets south-western China, focuses on provincial capitals, compares local and national platforms, and combines multi-source data with multiple methodologies. This paper systematically reviews the relevant literature and identifies research gaps, thereby providing a theoretical foundation for subsequent empirical analysis.

2.1 Research on the evolution of fresh produce retail formats
2.1.1 The evolutionary trajectory of fresh produce retail formats

Existing literature has established a relatively systematic research framework concerning the evolution of fresh produce retail formats. This framework primarily unfolds along three main threads: the iteration of new retail models, the integration of digital technologies, and consumer behavior-driven trends. It provides a theoretical foundation for understanding the transformation of China’s fresh produce distribution system from traditional channels toward an integrated online-offline model characterized by intelligence, efficiency and diverse coexistence. Regarding new retail models and business formats, the digital economy has driven the rapid proliferation of models such as forward-depot logistics, store-warehouse integration and community group buying, which have become the core directions for business format upgrading. Relevant studies, using cases such as Freshippo, have revealed the organizational logic, supply chain coordination and fulfilment efficiency characteristics of new retail models (Chen et al., 2022; Zhang et al., 2024). Omnichannel integration is regarded as a core feature of new retail, capable of significantly enhancing consumer engagement and channel loyalty (Chen et al., 2022) Meanwhile, traditional farmers’ markets have achieved modernisation through semi-formalization, forming a complementary and co-existing relationship with e-commerce platforms (Yao, 2025; Yuan et al., 2026). The retail sector’s overall evolution toward digitalisation, sustainability, platformisation and ecosystem-based models aligns closely with the reality of multi-platform coexistence in Guiyang (Akhtoian, 2023). In terms of digital technology integration, big data, artificial intelligence and supply chain optimization are deeply intertwined, driving the fresh produce retail sector toward precision and intelligence. Blockchain and green low-carbon technologies help reduce coordination costs and enhance supply chain transparency (Chen and Yin, 2023); the integration of online and offline channels significantly improves service quality and customer loyalty (Zhang and Liang, 2023); deep learning models based on LSTM and GWO-LSTM have been widely applied to sales forecasting and pricing optimization (Wang et al., 2024). Innovations in logistics models and carbon reduction practices play a crucial role in ensuring fresh produce quality and stabilizing supply (He and Sun, 2025). On the consumer-driven front, consumption preferences, value perceptions and channel choices directly shape the retail landscape. Research indicates that segmentation of consumption motives, quality demands, freshness preferences and price sensitivity significantly influence channel decisions (Kamal, 2025; Naveuler, 2025; Sarker et al., 2024), whilst consumption upgrades are driving the fresh produce supply chain toward greater health-consciousness, experiential value and immediacy (White, 2022). These findings provide the theoretical foundation for this study’s examination of business format evolution, consumer behavior and service experience in Guiyang. At the same time, digital transformation not only improves operational efficiency but also reduces wastage of fresh produce through accurate forecasting, optimizes delivery routes, and facilitates low-carbon logistics and the sustainable use of resources.

2.1.2 Factors influencing the evolution of fresh food retail formats

Existing research has systematically analyzed the driving mechanisms behind the evolution of fresh food retail formats from multiple perspectives, including digitalisation, consumer behavior, product quality, supply chain efficiency, physical retail environments and the policy landscape. Digital transformation and the O2O model are the core drivers of format upgrading, whilst the optimization of digital processes can reduce wastage and enhance fulfilment efficiency (Ma et al., 2022; Yang et al., 2022; Belwal et al., 2024). Consumer perceived value, service quality and trust in food safety significantly influence purchase intention and channel loyalty (Činčalová et al., 2021; Xing et al., 2024; Thuannadee and Praneetpholkrang, 2025), whilst product safety, traceability and supply chain efficiency constitute key constraints on the sustainable development of business formats (Cheng et al., 2026; Lestari et al., 2024). The physical environment, spatial layout and location selection of brick-and-mortar stores also influence the consumer experience (Maciel et al., 2023). At the macro level, policy regulations, urbanization and consumption upgrading collectively drive the transformation of traditional retail formats (Yuan et al., 2026).

2.2 Theoretical framework and influencing factors of consumer satisfaction with online fresh food purchases
2.2.1 Theoretical foundations of consumer satisfaction

The theoretical framework of consumer satisfaction is well-established, providing a solid academic foundation for research into satisfaction with online fresh produce. Cardozo (Cardozo, 1965) pioneered the revelation of the role satisfaction plays in promoting repeat purchases (Cardozo, 1965); the Expectation-Confirmation Theory (ECT) is widely used to explain the mechanisms underlying the formation of satisfaction (Shen et al., 2022). Satisfaction is a multidimensional construct influenced by multiple factors such as product attributes, demographic characteristics and context (Yılmaz and Balcıoğlu, 2026), and its application continues to expand across scenarios including omnichannel retail, service interactions and green consumption (Yaqub et al., 2022; Xu et al., 2022; Wang et al., 2023). In marketing and logistics theory, satisfaction often serves as a core mediating or outcome variable, significantly driving customer loyalty and willingness to continue using a product or service (Kerschbaumer et al., 2022; El Moussaoui et al., 2022; Kovalskii, 2024). This theoretical framework lays the foundation for the use of LDA and the improved intuitive fuzzy TOPSIS method in this study to evaluate satisfaction.

2.2.2 Factors influencing satisfaction with online fresh food

In the context of online fresh food, satisfaction is driven by multiple factors, including logistics services, product quality, service quality and brand image. Confirmed that logistics services are the most significant factor influencing satisfaction (Guan et al., 2022); product quality, freshness and safety also play a crucial role (Kang and Namkung, 2024); service quality indirectly influences behavioral intention through perceived value (Wang and Theerakittikul, 2022; Thuannadee and Praneetpholkrang, 2025); and brand image has a significant positive effect on satisfaction and purchase intention (Erkmen and Turegun, 2022). These findings provide direct justification for the selection of evaluation indicators in this study, including product source safety, product integrity, delivery service, and after-sales response. Furthermore, from a sustainability perspective, high satisfaction levels help to improve user retention, reduce customer acquisition costs and minimize waste of resources, and are central to the platform’s long-term sustainable operation.

2.3 Research progress on evaluation methods and sales forecasting models for fresh food E-commerce
2.3.1 Satisfaction evaluation models and methods

Traditional satisfaction evaluation has primarily relied on methods such as IPA and TOPSIS; in recent years, it has been upgraded through the integration of positive text mining and machine learning. Developed a food quality evaluation mode (Valderrama et al., 2021); emphasized the necessity of a multi-dimensional service quality framework (Yuan et al., 2026); and (Mao, 2025) highlighted the superior accuracy and adaptability of intelligent models. With the digital transformation, technologies such as AI-powered recommendations, dynamic pricing and sentiment analysis have been employed to enhance satisfaction (Dai and Liu, 2024; Kumari et al., 2024; Mittal, 2025). Text mining and LDA topic modeling can efficiently extract consumer concerns and sentiment tendencies, thereby enhancing the objectivity of evaluations (Singh and Glińska-Neweś, 2022; Song et al., 2022; Arifin and Purnama, 2023), providing methodological support for the adoption of LDA and the improved intuitive fuzzy TOPSIS in this study.

2.3.2 Deep learning models for sales forecasting

Deep learning has demonstrated superior capabilities in capturing time-series patterns and volatility in sales forecasting. LSTM and its variants are widely used in retail sales forecasting (Hu et al., 2022; Samonte et al., 2022), and the introduction of self-attention mechanisms can further enhance the capture of key information (Kossen et al., 2021). Confirmed the accuracy advantages of deep learning in time series forecasting (Messaoudi et al., 2023); however, research also suggests a risk of overfitting in scenarios involving small sample sizes and high volatility (Peng et al., 2022; Tilshi and Punsisi, 2022). Accordingly, this paper introduces the AT-DeepAR model—which utilizes an attention mechanism to enable accurate sales forecasting, thereby significantly reducing inventory wastage in the fresh produce sector and lowering energy consumption in the cold chain. It serves as a key technological enabler for achieving low-carbon, efficient and sustainable operations in fresh produce retail.

2.4 Research on the sustainable development of fresh food

Existing research provides a solid foundation for the sustainable development of fresh food and highlights the intrinsic links between food safety, environmental sustainability and economic viability. Enhancing the environmental sustainability of food supply chains is crucial to achieving several of the United Nations Sustainable Development Goals (SDGs), particularly Zero Hunger (Goal 2) and Responsible Consumption and Production (Goal 12); They emphasize that food safety measures must be balanced against environmental factors to avoid adverse effects (López-Gálvez et al., 2021). Further research supports this view, highlighting the necessity of establishing a sustainable fresh food cold chain system that balances environmental, social and economic benefits; a systematic review indicates that sustainable practices in this field can enhance market viability and resource utilization efficiency (Liao et al., 2021). Furthermore, innovations in food packaging, such as biodegradable materi