Abstract

Although one of the main goals of supply-chain management is to maximize consumer values, the research to date has mainly focused on the supply side. In the case of the food industry, understanding consumer needs and maximizing its utility are essential. In this study, we analyze consumers’ 12 meta-values (e.g., safety, taste, health, price, environment, etc.), then suggest the strategy of food cold-chain management satisfying consumers’ perception. We focused on consumers from three countries in Asia: Korea, China, and Japan. The survey was conducted with over 1000 consumers in those three countries, and a random parameter logit model was utilized to determine the importance of each food value that could affect consumers’ food choice. Similarities and differences were both found in share of preference of each food value across countries. While safety is one of the top three values in all three countries, naturalness and nutritional value ranked among the top three only in China. To propose the consumer-centric strategy of food cold-chain management, we investigated the relationship between each food value and each node of supply chain based on the big data analysis. It shows that consumers prefer when the entire supply chain is managed where each node is organically connected with each other instead of individual nodes being managed separately. Further, strategies for food cold-chain management should be developed differently by country, incorporating differences of consumers’ preferences on food value. These results would motivate governments and companies related to food cold chain to reconsider their marketing strategies on the import and export food market.

Highlights

  • Transitioning from the third industrial revolution into the current era of the fourth industrial revolution has altered the circumstances around supply-chain logistics

  • The implication is extracted from a research direction based on 22,399 tweets and meta data collected with the hash tag #supplychain from Twitter and uses three methodologies: descriptive analytics (DA), content analytics (CA) integrating text mining and sentiment analysis, and network analytics (NA)

  • The importance of each food value is estimated by random parameter logit model (RPL) and relative to novelty

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Summary

Introduction

Transitioning from the third industrial revolution into the current era of the fourth industrial revolution has altered the circumstances around supply-chain logistics. Gutman [11] introduced a means-end chain theory, which links perceived product attributes (A) to consequences of the product (C) to personal values (V) It offers a mechanism for understanding what values are important to consumers to motivate their purchasing decisions based on the attributes. Big data analysis allows atypical data, such as those from social media, the Internet, journals, and media news, to be analyzed; it is widely used in analyzing consumer attributes, measuring demand for policy, and developing corporate marketing materials. In this regard, studies on supply-chain management (SCM) started to recognize the importance of utilizing the potential role of social media and applying big data analysis to establish the consumer-centric marketing strategies. Its impact is mediated by the fashion retailer’s prior attitude towards the market demand

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