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With the rapid growth of the economy, people have increasingly higher living standards, and although people simply pursued material wealth in the past, they now pay more attention to material quality and safety and environmental protection. This paper discusses the lack of motivation for investing in fresh-keeping technology for agricultural products by individual members of an agricultural supply chain composed of a supplier and a retailer by means of mathematical models and data simulations and discuss the optimal price-invest strategies under different sales models.

First, based on the model of no investment by both sides (NN), this paper considers three models: supplier only (MN), retailer only (NR) and cooperative investment (MR). Then, the authors analyze the influence of consumer price sensitivity and freshness sensitivity on the investment motivation of agricultural products under four models. Subsequently, the paper makes a sensitivity analysis of the optimal strategies under several models, and makes a game analysis of the suppliers and retailers of agricultural products. Finally, we conduct an empirical analysis through specific values.

The results show that (a) when the two sides cooperate, the amount of investment is largest, the freshness of the agricultural products is highest, and the sales volume is greatest; however, when both sides do not invest, the freshness of agricultural products and sales volume are lowest. (b) The price and freshness sensitivity of the consumer have an impact on investment decisions. Greater freshness sensitivity corresponds to a higher investment, higher agricultural product price, greater sales volume, and greater supply chain member income and overall income; however, greater price sensitivity corresponds to a lower investment, lower agricultural product price, lower sales volume, fewer supply chain members and lower overall income. (c) The investment game between the supplier and retailer is not only related to the sensitivity to price and freshness but also to the coordination coefficients of interest. At the same time, the market position of agricultural products should be considered when making decisions. The market share of agricultural products will affect the final game equilibrium and then affect the final benefit of the supply chain and individual members.

These results provide managerial insights for enterprises preparing to invest in agricultural products preservation technology.

At present, the main problem is that member enterprises of agricultural supply chains operate based on their own benefits and are resistant to investing alone to improve the freshness of agricultural products. Instead, they would prefer that other members invest so that they may reap the benefits at no cost. Therefore, the enterprises in each node of the agricultural product supply chain are not motivated enough to invest, and competition and game states are observed among them, and such behavior is definitely not conducive to improving the freshness of agricultural products. However, the current research on agricultural products is more about price, quality and greenness, etc., and there are few studies on agricultural investment. Through the establishment of the model, this paper is expected to provide theoretical suggestions for the supply chain enterprises that plan to invest in agricultural products preservation technology.

As one of the omnichannel sales models, “buy online and pick up in store” (BOPS) not only is used in the commercial field but also has gradually attracted many scholars’ interests. However, although there are numerous research ideas, most of the current work is still limited to theoretical and empirical research, and few scholars study BOPS through models. This paper aims to discuss the best market conditions and opportunities for the implementation of BOPS against the backdrop of omnichannel by means of mathematical models and data simulations and discuss the optimal price–service strategies under different sales models.

First, from the perspective of different consumer shopping types, this paper separately divides consumers into different groups in traditional “dual channel” and BOPS models. Then, the authors analyze the impact of company market size, consumer service sensitivity and the scale of BOPS on companies’ strategies and the profit of the supply chain. Subsequently, they conduct an empirical analysis through specific values. Finally, the authors further expand the model on the basis of the original research, and discuss the retailer’s fairness concerns and unit compensation strategy to ensure that the research content is more rigorous.

It is observed that whether companies adopt BOPS depends on consumers’ service sensitivity degree and the scale of BOPS consumers and online retailers: when the sensitivity and the proportion of online consumers are high or the number of BOPS consumers is large, it is more advantageous for companies to implement BOPS. Moreover, companies should not only consider the market scale and production cost but also have a precise orientation of consumers’ experience sensitivity and willingness to engage in extra consumption when making price and service strategies. At the same time, the compensation strategy of companies and the peer-regarding fairness concern behavior of offline retailers will affect the optimal price and service strategy in the BOPS model.

These results provide managerial insights for companies preparing to implement BOPS and promote the development of relevant theories in the channel field.

At present, most of the research on BOPS is based on empirical reviews. However, this paper analyzes the applicability and feasibility of implementing BOPS by using specific models, and it will provide some reference for companies preparing to implement BOPS. In addition, this paper also discusses the unit compensation strategy and peer-regarding fairness concern behavior in the BOPS model, which have not been studied by relevant scholars.

While the growth of emerging technologies like Blockchain has created significant market opportunities and economic incentives for firms, it is valuable for both researchers and practitioners to understand their creation mechanisms. This paper aims to discuss the aforementioned objective.

Based on the knowledge search perspective, this study examines the impact of search boundary on innovation novelty and quality. Additionally, innovation targets, namely R&D innovation and application innovation, are proposed as the moderator of the knowledge search effect. Using a combination of machine learning algorithms such as natural language processing and classification models, the authors propose new methods to measure the identified concepts.

The empirical results of 3,614 Blockchain patents indicate that search boundary enhances both innovation novelty and innovation quality. For R&D innovation, the positive impact of search boundary on innovation quality is enhanced, whereas for application innovation, the positive effect of search boundary on innovation novelty is improved.

This study mainly contributes to the growing literature on emerging technologies by describing their creation mechanisms. Specifically, the exploration of R&D and application taxonomy enriches researchers' understanding of knowledge search in the context of Blockchain invention.