Supply Chain Consumer Research Articles

Prediction Of Vegetable Pricing and Replenishment Based on ARIMA Model

Vegetables are indispensable consumer goods in the daily diet of the majority of consumers. Reasonable pricing and replenishment strategies of vegetables are conducive to maintaining the interests of agricultural producers and promoting the stable development of the market. The main contents of this paper are two points: one is to visualize the pre-processed data and establish the distribution map of vegetable sales in recent years; Secondly, the ARIMA time series prediction model was established by linear fitting of the data, and the feasibility test of the prediction results was carried out to obtain the total daily replenishment quantity and price of each vegetable category in a period of time. Under the background of the new era with low-carbon green as the mainstream, this research has broad development space and prospect. The pricing and replenishment strategies formulated in this study can reduce the waste of vegetables in the whole consumption supply chain, maintain the purchasing power and living standard of consumers, and meet the market demand. Marketing techniques that promote healthy foods in supermarkets are important to encourage healthy eating at the population level. The content of this study can provide ideas for the optimization of vegetable supply chain, further use of new technology, reduce waste, improve efficiency, and ensure the quality and supply stability of vegetables. This study is also helpful to analyze consumer behavior and understand consumers' reactions to vegetable price fluctuations and changes in purchasing behavior in order to better predict market trends and adjust production and supply strategies.

Pathogenic Microorganisms Linked to Fresh Fruits and Juices Purchased at Low-Cost Markets in Ecuador, Potential Carriers of Antibiotic Resistance

The pathogenic microorganisms linked to fresh fruits and juices sold out in retail low-cost markets raise safety concerns as they may carry multidrug-resistant (MDR) genes. To evaluate the microbiological quality and safety of highly consumed fruits and derivatives in Imbabura Province, Ecuador, ready-to-eat strawberries (5 independent batches; n = 300 samples), and gooseberries (5 separate batches; n = 500 samples), purchased from a local fruit farm grower and low-cost retail market, along with 20 different natural fruit- and vegetables-based juices (3 independent batches; n = 60 samples) purchased from food courts located within the low-cost markets were analyzed. Bacteriological analysis showed that the microbial quality was lower as several indicators (n = 984) consisting of total coliforms (TCOL), total aerobes (AEROB), Enterobacter spp. (ENT), Shigella spp., (SHIGA), yeasts (YE), and molds (M) were detected. Staphylococcus spp. (STAPHY) was found in both fruits regardless of origin, while Escherichia coli (EC) isolates were found in strawberries but not gooseberries. Salmonella spp. (SALM) were detected in juices only. Antibiotic susceptibility testing showed multidrug resistance of several isolates. The hemolytic pattern revealed that 88.89% of EC and 61.11% of ENT isolates were beta-hemolytic. All STAPHY isolates were beta-hemolytic while SALM and SHIGA were alpha-hemolytic. Plasmid curing assay of MDR isolates (ENT, EC, SALM, and STAPHY) showed that the antibiotic resistance (AR) was highly indicative of being plasmid-borne. These results raise concerns about the consumption of MDR bacteria. However, good agricultural and industrial practices, behavioral change communication, and awareness-raising programs are necessary for all stakeholders along the food production and consumption supply chain.

Recommendations from cold starts in big data

This paper examines the challenging problem of new user cold starts in subset labelled and extremely sparsely labelled big data. We introduce a new Isle of Wight Supply Chain (IWSC) dataset demonstrating these characteristics. We also introduce a new technique addressing these challenges, the Transitive Semantic Relationships (TSR) model, which infers potential relationships from user and item text content and few labelled examples. We perform both implicit and explicit evaluation of TSR as a recommender system and from new user cold starts we achieve a hit-rate@10 of 77% on a collection of 630 items with only 376 supply-chain consumer labels, and 67% with only 142 supply-chain supplier labels, demonstrating a high level of performance even with extremely few labels in challenging cold-start scenarios. TSR is suitable for any dataset featuring few labels and user and item content, where similarity of content indicates similar relationship forming capability. TSR can be used as a standalone recommender system or to complement existing high-performance recommender models that require more labels or do not support cold starts.

An overview of the role of informatics-based systems in furthering an integrated paddock to plate food supply system

Food, nutrition and dietary-related information are increasingly available in a digital form within the food production and consumption supply chain, including: identifier and inventory systems; digitised nutrient component databases; databases of consumer packaged foods indexed by universal product codes (UPCs); greater use of digital point-of-sale systems; and the rapid emergence of health and diet-related mobile ‘apps’. While these developments have emerged somewhat independently, they allow further integration and processing capabilities, with significant potential impact upon the efficiency and sophistication of the food supply chain, individual and society-wide health, statistics gathering and further environmental, materials and energy optimisation within the food supply chain – we refer to the enabling research field as nutrition informatics. In this article, we discuss the technological underpinnings, analyse the implications and applications of increasing digitisation of food-related information, and identify seven priority directions to advance informatics-based systems for achieving an integrated ‘paddock to plate’ food supply system.