As the development of digital technologies continues, scenario-based innovation driven by digital technologies has become a great concern. It is the process of applying existing digital technologies to specific scenarios to generate value. However, previous research primarily focused on transaction value and application value created by conventional product innovation without a deep revelation about the creation mechanism of scenario value. In the context of digitalization, the value creation of scenario-based innovation manifests two prominent features: on the one hand, the resource of scenario-based innovation value creation relies more on big data; on the other hand, the process of scenario-based innovation emphasizes the co-creation between users and enterprises. The theory of big-data-based cooperative assets holds the view that enterprises and consumers could transform into digital assets that could be possessed and utilized by each other and generate current or future economic returns during the digital service interaction process, of which the core proposition could theoretically provide internal logic to the value creation mechanism of scenario-based innovation.#br#Therefore, this paper combines the theory of big data-based cooperative assets with scenario-based innovation, proposes the concept of scenario-based big data cooperative asset, and discusses its four types with practical examples to deeply explore the value creation mechanism of scenario-based innovation.#br#Three findings are presented in this paper. Firstly, the content and features of scenario value are identified. Scenario value is defined as the experience value perceived by customers in the case of the matchingbetween the product service and the time, space, and emotional state where the customers are positioned. It has three features derived from the interaction between enterprises and customers: co-creativity, experience and adaptability. Co-creativity highlights the feature of value creation process, while experience and adaptability emphasize the features of the demand side and supply side relatively. In addition, experience and adaptability are outcomes of co-creativity. Secondly, the concept of scenario-based big data cooperative assets is proposed. It refers to the transformation of enterprises and customers into digital assets through digital service interaction in the context composed of time, space, and behavior relations. On the one hand, the proposition of scenario-based big data cooperative assets provides a theoretical lens for the mechanism of scenario-based innovation in the digital economy. It not only fundamentally answers the question of the source of factors in scenario-based innovation, but also shares the same internal logic as scenario-based innovation. On the other hand, the proposition of scenario-based big data cooperative assets extends the big data-based cooperative asset from the perspective of application. It acts as a micro-depiction of the digital assets generated from the interaction between users and enterprises in the digital economy, comprehensively revealing the underlying mechanism of the bilateral interaction between users and enterprises of scenario value creation process. Thirdly, four types of scenario-based big data cooperative asset are divided by two dimensions of the online/offline scenes and the proactiveness of enterprises/users: enterprise-led online scenario, enterprise-led offline scenario, user-led online scenario, and user-led offline scenario. There are generalities and differences of the value creation mechanisms of these four types in the dimensions of the agents, processes, and outcomes of value creation. This paper reveals the mechanism logic of value creation of scenario-based innovation based on the analysis above. First, the big data transforms to scenario-based big data cooperative assets based on the data-generated scenarios and agent-led behaviors. Second, the value creation based on the scenario-based big data cooperative assets is realized through the digital interaction between the enterprises and users.#br#Different from the previous literature that mainly focused on value creation by conventional product innovation, this paper introduces the theory of big data-based cooperative assets as theoretical lens to explore the value creation mechanism and logic of scenario-based innovation in digital economy,which extends the research on scenario-based innovation by revealing its value creation mechanism and facilitates the application of big data-based cooperative assets. This paper suggests that different characteristics of big data-based cooperative assets in various contexts should be analyzed in detail in future research, and the research on value creation mechanism of scenario-based innovation should be combined with frontier practice.#br#

With the development of information technology, China has moved from the consumer Internet stage to the industrial Internet stage. The industrial Internet platform is a cloud platform based on the Internet of Things, supported by interconnection capabilities based on digital technology, and targeted at enterprise users. Extensive connectivity enables the industrial Internet platform to greatly promote the development of the business ecosystem. In the digital business environment, the competition among enterprises has gradually turned to the competition among business ecosystems, and the innovation of business ecosystem is the guarantee for enterprises to obtain sustainable competitive advantages. Therefore, it is a key theoretical problem to study how the industrial internet platform drives the innovation of the business ecosystem. In the era of the digital economy, context has become a new paradigm that drives service innovation and business ecosystem innovation of the industrial Internet platform. Context-driven innovation is the process of breaking through the existing model and developing new technologies, products, services and ecological networks based on the diversified demands of the context. As the key empowerment dimension of the industrial Internet platform, digital empowerment is the key mechanism of context-driven business ecosystem innovation. However, the existing studies have not paid enough attention to the relationship among context-driven innovation, digital empowerment and business ecosystem innovation, and have failed to reveal the complex dynamic mechanism of context-driven business ecosystem innovation.#br#In view of this, this paper studies how the industrial internet platform can drive business ecosystem innovation through digital empowerment in different contexts. According to the principles of typicality and inspiration, Huitongda is selected for the study. In order to enhance the reliability and validity of the data and conclusions, this study collects data through various methods to form a triangular verification, including in-depth interviews, participatory observation, and second-hand information. By performing the three-level encoding on the data, 28 first-order concepts, 12 second-order themes and 4 aggregate constructs are obtained. On the basis of data coding, this paper analyzes the evolution process of Huitongda's business ecosystem, and constructs a mechanism model of context-driven business ecosystem innovation.#br#The results show that (1) the evolution process includes three stages: transaction context-network construction, service context-network extension, and open context-network enhancement. (2) The logical basis of context-driven business ecosystem innovation is "context insight-context creation-context empowerment-network innovation". Context insight determines what kind of application context the platform should create, and each context acts on stakeholders through digital empowerment to realize the expansion of the business ecological network and value co-creation. (3) The dynamic mechanism of context-driven business ecosystem innovation is the value co-creation subject (the ecological network node) and object (business value and social value) innovation driven by the digital empowerment of the context under the "triple embedding". Contextual insights are based on the excavation of pain points, the arrangement of resources and the traction of missions. On the one hand, context creation depends on the structural support of digital technology. On the other hand, it depends on the institutional support of social relations. Requirements, technology and relationships collectively trigger context innovation, and the digital empowerment of each context triggers business ecosystem innovation.#br#In summary, this paper creatively proposes the mechanism model of context-driven business ecosystem innovation, which contributes to the relevant research of context-driven innovation theory, business ecosystem innovation theory and digital empowerment theory; moreover, it constructs a digital empowerment system covering seven aspects of three dimensions, which enriches the research results on the methods of digital empowerment. The research conclusions of this study provide useful reference for the context innovation and the business ecosystem construction of platform enterprises and start-up enterprises. First, enterprises should strengthen their ability to identify demand because the essence of context innovation is to accurately meet the needs of users. Second, it is essential to make good use of social relations, because trust can improve the efficiency of the business ecosystem. Finally, enterprises should cultivate a sense of symbiosis and altruism, and create social value together with stakeholders.#br#

As a major innovation in the field of science and technology, artificial intelligence plays an important role in alleviating the social pressures brought by population aging and insufficient resources, meeting the national requirements for sustainable development, and improving the efficiency of economic structural transformation and upgrading. It is a historic strategic opportunity that cannot be ignored. Artificial intelligence is regarded as the main development direction of national information technology and the Chinese government is making every effort to integrate artificial intelligence technology with real economy development. Additionally, the government strongly proposes to actively explore and continuously develop the opportunities of artificial intelligence application scenarios and create significant scenarios in the medical field, with a more intelligent city and a more intimate society as the guide. In recent years, domestic and foreign technology enterprises, traditional medical device providers, and related scientific research teams are actively promoting the intelligent upgrade of the medical and health industry to provide more efficient and convenient services for patients, medical practitioners, medical institutions, and medical research teams. Since 2020, intelligent medical products and services have provided important support and guarantees for epidemic prevention, control and vaccine research. As a result, the penetration of artificial intelligence technology in the medical field is accelerating, and the application scenarios are becoming more diverse. A comprehensive review of existing relevant studies shows that the research achievements of scenario-driven innovation and the intelligent medical industry have been continuously enriched in recent years, but the intelligent medical industry is still in its infancy. As an emerging industry, the intelligent medical industry lacks systematic identification and industry analysis based on scenario-themed classification processing.#br#It is conducive to a better understanding of the development of this industry and figuring out potential opportunities and challenges to identify the application scenarios of the industry from three dimensions of technology, market and policy. Therefore, by taking 53 581 intelligent medical patents as the source data and using the LDA thematic model to identify the application scenarios of the intelligent medical industry, this paper explores the evolution of China's intelligent medical industry in the three dimensions by combining the results of application scenario recognition and conducting an analysis framework of industry evolution. It first introduces the technological evolution of the intelligent medical industry through the analysis of patents and technologies. Second, it clarifies the market analysis from the perspective of market scale and application scenarios, showing China's current situation in every aspect of intelligent medicine. Third, it illustrates the domestic policy related to the intelligent medical industry, presenting the concern and attention to the development of this cutting-edge industry at the national level.#br#In conclusion, this study discovers 12 application scenarios of the intelligent medical industry, and identifies 5 major application scenarios based on the theme meanings and the industry's current status, including intelligent diagnosis and treatment, medical robots, drug development, intelligent medical imaging, and intelligent health management. In terms of technology, intelligent medical technology is in a stage of continuous innovation and development, and China's key research and development directions are laid out in various application fields. In terms of the market, different types of enterprises at home and abroad have actively explored the five application scenarios of the industry with different focuses. The market scale is gradually expanding, but the products and medical solutions are still in the stage of scenario testing. In terms of policies, China has tried to use a variety of policy tools to comprehensively support the development of the intelligent medical industry in an all-round way. However, there are degree differences in the policy support in different application scenarios. #br#This paper enriches the current research on intelligent medical application scenario identification and industrial evolution, and puts forward some countermeasures and suggestions for the future development of the industry. Meanwhile, it provides data reference and decision-making support for China's intelligent medical industry planning and policymaking in the future.#br#

The development of information technology has made data information an important tool for exploring users' real needs in today's society, and various consumption contexts composed of data information are more important paths to identifying user demand. Intelligent products, as the core components of context, will innovate under the guidance of context theory to better meet user needs. The single technology-driven innovation model is no longer suitable for the needs of product innovation in today's era. While design, as an important innovation driving force in today's era, is receiving more and more attention from researchers. Therefore, the driving effect of design on intelligent product innovation should also be given more attention. The perceived emotions generated by consumers towards products can more finely display consumer preferences, and word-of-mouth communication which is an important component of consumer behavior, can better reflect consumers' acceptance of products. Thus, this article chooses to study the relationship between intelligent products under design-driven innovation, perceived emotions, and word-of-mouth communication under the guidance of the perspective of context to fill the gap in related research fields.#br#This article first summarizes the relevant definitions and composition of context and proves that intelligent products play an important role in contexts. The context should be composed of five major elements: intelligent products, big data, mobile apps, sensors, and positioning systems. Second, it conducts a literature review and induction of design-driven product innovation. On the one hand, the important driving role of design in product innovation is clarified; on the other hand, it is determined that research should start with the three dimensions of design-driven innovation: aesthetics, semantics and interaction of intelligent products. Furthermore, by constructing a model of design-driven intelligent product innovation dimensions, perceived emotions, and word-of-mouth communication, it explores the relationship among the three dimensions of intelligent products and word-of-mouth communication, and focuses on the mediating role of customers' perceived emotions to analyze the innovation mechanism of intelligent products,while perceived emotions can be divided into two dimensions: "pleasure" and "arousal". Finally, it collects empirical analysis data through a questionnaire survey on the customers of intelligent products and tests the mediation effect through data analysis software.#br#The results show that the aesthetic, semantic and interactive dimensions of design-driven intelligent product innovation have significant positive effects on perceived emotion and word-of-mouth communication, and "pleasure" and "arousal" in perceived emotion play mediation roles between different design dimensions and word-of-mouth communication, which is reconfirmed in the further chain mediation effect test, and "pleasure" is proven to have a stronger mediation effect than "arousal". As a result, this article proposes three suggestions: first, the guiding role of context based thinking in intelligent product innovation, user-centeredness, and the differentiated needs of users in different contexts should be stressed; second, in product innovation, emphasis should be placed on bringing high comfort, rather than deliberately pursuing novelty and differentiation; third, the interactive experience of the products is also essential, because as the core function of intelligent products, the functional design of interactive functions will greatly affect the realization of context value.#br#In conclusion, the research contributions of this article mainly include the following points. It is pointed out firstly that the context theory is mainly divided into product contexts and media contexts, with intelligent products being an important component of product contexts. This result enhances researchers' attention to researching intelligent products, especially intelligent products in contexts, and provides clearer research ideas for conducting studies of contexts. Furthermore, it summarizes the constituent elements and characteristics of product contexts through research on previous literature and practical experience, which provides assistance in a more detailed exploration of the functions and innovation paths of each element in the product contexts. Lastly, the empirical analysis results provide new references for the production and design of intelligent products, assist in the successful implementation and application of intelligent technology, and provide stronger assistance for the realization of context value.#br#

With the advancement of the digital economy, context-driven innovation, as a new innovation paradigm, has become a key path to create new technologies, new products, new channels, new business models and even open up new markets and new areas. The trend of context-driven innovation has made a considerable impact on the original business model in the industry, and the service innovation practice of enterprises has been injected with new context-driven elements, and solutions that meet customer-specific value propositions have become a key path for enterprises to increase their potential for value creation, and it promotes context application as a powerful tool for product innovation and business model innovation for enterprises. For this reason, many high-tech enterprises have shifted to provide solution business, build context-driven solutions based on the characteristics of fissionable growth of emerging context, and create new personalized experiences and context values for customers by exploring the integration point of new technologies with context and new ways of product interaction design.#br#Context-driven solutions involve a new service business model based on context application and context value construction to respond to customer needs. It follows the basic logic of using context value building to gain insight and explore customer needs, and being forward-looking to provide customers with surpassing service expectations, thus realizing the transformation of technological advantages into business value. Although existing research has focused on context-driven solutions as a new feature of context-driven enterprise service innovation model, the value co-creation logic of helping customers to complete "to-do tasks" based on the value insight of context-driven solutions has not been fully explained, and the understanding and deconstruction of context-driven solutions still needs to be further deepened.#br#In order to figure out how enterprises develop context-driven solutions, this paper selects four enterprises, namely, Hikvision, iFLYTEK, Neusoft and Inspur, as case study objects, deconstructs the inner law of context-driven solution development and builds a theoretical model. It is found that, first, context-driven solution development has the key feature of context-driven, which is mainly manifested in two dimensions of context penetration and context coverage. Second, under the context-driven approach, enterprises develop context-driven solutions based on the realization path of "requirement identification—technology integration—service operation and maintenance". Specifically, enterprises transforming into context-driven solution providers follow the realization path of "forward-looking requirement identification-technology external integration-exploratory service operation and maintenance", while natural context-driven solution providers follow the realization path of "responsive requirement identification-technology internal integration- exploitative service operation and maintenance". Third, data enabling is the endogenous driving force of context-driven solution development, and it can facilitate the transition between the development of context-driven solutions such as requirements identification, technology integration, and service operation and maintenance.#br#The theoretical contributions of this paper lie in three aspects. First, this study combines context theory and customer solution theory, and innovatively proposes a new model for enterprises to carry out service value creation in the era of digital intelligence, that is, the new concept of context-driven solution. It identifies the context-driven solution's context-driven characteristics that distinguish it from customer solutions in a general sense, which enriches the theoretical cognition of context-driven solutions, and contributes to deepening the understanding of the context-driven service innovation model. Second, unlike previous studies on the development process of customer solutions, this paper focuses on the deconstruction of the inner laws of the context-driven solution development process. By refining the realization path and endogenous driving of context-driven solution development, it complements the theoretical gap caused by the lack of discussion on the logic of context-driven solution development in existing research. Third, this paper introduces the concept of data enabling into the exploration of context-driven solution development process. By identifying data enabling as the endogenous driving of context-driven solution development, the study enables a more theoretically inclusive analysis of the role of "data actors" in context-driven solution development, providing a new analytical perspective to clarify the inner workings of solution development. Moreover, it provides a paradigm reference for enterprises to effectively embed technological advantages into the development process of new scenarios, inspiring enterprises to develop their capabilities following changes in the policy environment, industry technology environment and customer needs.#br#

The gradual embedding of elements of context in business models has brought the value-dominant logic transformation of enterprises driven by users' spatio-temporal consumer expectations from "product functionality" to "service utility" and then to "context experiences". The shift from "seller's market" to "buyer's market" is prevalent for most industries, because just improving product quality and service capabilities could not meet the ever-changing consumer expectations. The advanced interaction and collaborative evolution of value-dominant logic and the enterprise dynamic capabilities are important strategic means to respond to the changes in users' consumption expectations and achieve sustainable growth for enterprises. Context is the bridge between value-dominant logic evolution and the enterprise dynamic capabilities, and it has become a new driving force for business model innovation. In this situation, how to target digital contexts and combine users' sore points of consumption needs, consumption habits and consumption preferences to deconstruct, modify, and reconstruct business models to satisfy users' new demands and new experiences has become a hot and difficult research topic in context-driven business model innovation.#br#Therefore, taking M-Grass Ecology as the research object, this study adopts a combination of vertical single case study and procedural grounded analysis to explore the interactive evolution mechanism by which value-dominant logic evolution, enterprise dynamic capabilities, and contexts guide and adjust the dynamic matching of supply and demand between users' consumption expectations and the supply reality of enterprises. The research results indicate that (1) the value proposition of goods is focused on product functional values. In order to centralize the dominant logic of product functional value, enterprises utilize the dynamic capabilities of "Perception+ Integration" to meet consumers' product functional expectations based on users' consumption expectations and contextual standardized configurations. For the differently categorized goods, M-Grass has constructed a path on which the customers looking for goods can depend on the business logic of thousands of customers matching with one context for the same categorized goods. (2)The value proposition of customers is focused on service utility values. In order to concentrate the dominant logic of service utility value, enterprises utilize the dynamic capabilities of "Perception Ability+Integration Ability+Learning Ability" to satisfy consumers' service utility expectations based on users' consumption expectations and contextual personalized configuration. For different groups of consumers, M-Grass has achieved goods matching for customers depending on the business logic of one customer matching with thousands of contexts. (3) The value proposition of contexts is focused on the context experience values. For concentrating the dominant logic of scene experience values, M-Grass utilizes the dynamic capabilities of "perception ability+integration ability+learning ability+innovation ability" to meet consumers' context experience expectations based on users' consumption expectations and contextual dual path configuration. The context matching for customers depending on the business logic of thousands of customers matching with thousands of contexts is achieved so as to construct different interesting contexts. #br#From the perspective of the dynamic interaction of value-dominant logic evolution, enterprise dynamic capability advancement and context iteration, this study discusses how the contexts empower business model innovation based on the collaborative evolution of value-driven logic evolution and enterprise dynamic capability advancement in the Chinese context. The empowered business model innovation based on the integration of "supply chain-value chain-context chain" is proposed. At the same time, the evolution of value-driven logic utilizes contexts to stimulate changes in user consumption expectations based on context driven enterprise dynamic capability enhancement, thereby stimulating the evolution of value driven logic. Enterprises should timely and proactively integrate the elements of context into their business models, promote the evolution of value-dominant logic and enhance their dynamic capabilities, and dynamically choose different context-based business model innovation strategies. This study provides theoretical support for the ecological innovation practice of enterprise business models, compensates for the shortcomings of research on cross-sectional data from a static perspective , and also enriches the context-driven innovation theory.#br#

In the era of the digital economy, "context" has become a new channel for manufacturing enterprises to interact with users. More and more manufacturing enterprises try to improve service innovation performance by carrying out in-depth excavation of context and context iteration on the demand side. However, there are still some deficiencies in practice and theory on how in-depth excavation of context affects service innovation performance. As a context-driven service innovation activity, the realization of in-depth excavation of context focuses on the use of digital technology and other means to transmit demand data to the supply side, promote the occurrence of value co-creation behavior, and quickly transform user needs into products or services. In view of this, following on the value co-creation and big data cooperative asset theory of the service innovation ecosystem, this paper integrates the demand side and supply side, takes the value co-creation behavior of the service innovation ecosystem as the mediating variable, and uses digital ability as the moderating variable to construct the model to explain the impact of in-depth excavation of context on the service innovation performance of manufacturing enterprises on the demand side. It analyzes the role of manufacturing enterprises' demand-side in-depth excavation of context on their service innovation performance, the mediating role of the value co-creation behavior of service innovation ecology in the relationship between in-depth excavation of context and service innovation performance, and explores how digital ability moderates the relationship between manufacturing enterprises' in-depth excavation of context and service innovation ecological value co-creation behavior.#br#The data is collected by means of a questionnaire survey, and a measurement scale for in-depth excavation of context is made on the basis of existing research. The survey samples involve manufacturing enterprises in different fields, which ensures the external validity of the research structure to a certain extent. On this basis, the hypothesis test is carried out by hierarchical regression, the Bootstrap method and Process V3.3, and the structural equation model is used to verify the relationship between variables. The results of the two verifications are basically the same, which proves the robustness of the model.#br#The empirical results show that in-depth excavation of context has a direct effect on the service innovation performance of manufacturing enterprises, and it plays a positive role; value co-creation behavior can be used as a mediating variable to explain the relationship between in-depth excavation of context and service innovation performance of manufacturing enterprises; digitization ability positively moderates the relationship between in-depth excavation of context and value co-creation behavior; further analysis confirms that digital capabilities positively moderate the mediating role of value co-creation between in-depth excavation of context and service innovation performance. It can be seen that manufacturing enterprises carry out in-depth excavation of context on the demand side, and this promotes their value co-creation behavior with users and other stakeholders, and improves their service innovation performance. Digital ability is an important guarantee for manufacturing enterprises to coordinate different subjects of service innovation ecology and integrate different resources to create value, and it plays an important role in promoting the process of in-depth excavation of context to promote value co-creation behavior.#br#This paper further clarifies the meaning of in-depth excavation of context and develops a measurement scale for subsequent reference. Compared with the existing research, this paper extends the research of the context to the manufacturing industry, integrates the demand side and the supply side, reveals the improvement mechanism of the service innovation performance of the manufacturing enterprise from the in-depth excavation of context, enriches the relevant research of the context, applies the big data cooperative asset theory to the research of the context business model, and discusses the promotion effect of digital ability on the value co-creation behavior of the in-depth excavation of context on the service innovation ecosystem. At the same time, it has certain guiding significance for manufacturing enterprises to promote the value co-creation behavior of service innovation ecology by conducting in-depth excavation of context and improving digital capability so as to realize the improvement of service innovation performance. The related research on context is in its infancy at present, and this paper is only concerned with the depth and breadth of value co-creation brought by in-depth excavation of context; the cost of service innovation driven by in-depth excavation of context and the relationship between the degree of excavation and its improved service innovation performance are not touched, which presents opportunities for future research.#br#

With the deepening embedding of the digital economy in rural revitalization in recent years, data has become a new production factor and an important innovation driving force, as well as a core element in rural construction and agricultural development. In the digital economy, various contexts and tracks keep emerging, and it can be considered that the agricultural whole industry chain is gradually entering the context era. Therefore, it is difficult to achieve the complex and comprehensive strategic needs of rural revitalization and common prosperity by only adopting the agricultural innovation development model aiming at a single technology field or market demand, and more attention should be paid to the theoretical research and practical application of context-driven agricultural whole industry chain innovation.#br#This study first explores the element system and theoretical logic of context-driven agricultural whole industry chain innovation based on the definition of agricultural whole industry chain by the Ministry of Agriculture and Rural Affairs. The context demand of agricultural whole industry chain innovation against the background of digital economy are analyzed into three dimensions: production, marketing and service. Second, the practical path of context-driven agricultural whole industry chain innovation is summarized. By analyzing three typical cases of Shunfeng Biotechnology, Adopt a Cow, and Yangjiale, the practical path of context-driven agricultural whole industry chain innovation in the production, marketing, and service dimensions is verified. Finally, the strategic logic of the intersection and integration of the theoretical fields of " context-driven innovation" and "agricultural whole industry chain innovation" is summarized as the context-chain structure of agricultural whole industry chain innovation.#br#The results show that context-driven agricultural whole industry chain innovation needs to rely on four factors: agricultural context demand (antecedent factor), high-energy innovation consortia (main factor), digital innovation platform (digital factor), and diversified context value (consequence factor). The theoretical logic of context-driven agricultural whole industry chain innovation can be summarized as four sections: mission driven which refers to the traction effect of rural revitalization strategy, digital economy background, and customer context demand characteristics; context-driven which refers to context demand-driven effect of three dimensions including production, marketing and service; agricultural whole industry chain innovation process which refers to the process of decoupling and reconstructing various elements on high-level innovation consortia and digital innovation platform into a new value co-creation system, meeting customers' consumption expectations in specific time and space; innovative achievement application which refers to innovative behavior implementation of agricultural whole industry chain in three aspects of production technology, business model and service channel, so as to achieve diversified context value. The practical path of context-driven agricultural whole industry chain innovation includes five steps: context demand analysis, context task design, context-driven innovation resource allocation, agricultural whole industry chain innovative behavior implementation and diversified context value realization. #br#The main contribution with this study is its focus on the theoretical logic and practice path of context-driven agricultural whole industry chain innovation. By analyzing the case studies of three typical enterprises, it exemplifies the practical forms of agricultural whole industry chain innovation driven by the demand for production, marketing, and service context. The analysis results help to construct an overall theoretical framework for context-driven agricultural whole industry chain innovation, making exploratory attempts for the research on national strategic needs, agricultural industry chain development needs, and major market demand context-driven agricultural whole industry chain innovation. The findings provide practical inspiration for strengthening the autonomy, security,and controllability of the agricultural whole industry chain, and building agricultural whole industry chain resilience.#br#In the context-driven era, the innovation of the whole agricultural industry chain focuses on the logic of context-value co-creation. In the future, with the continuous enrichment of context elements and the improvement of their functions, especially with the popularity of technological application, the connotation and extension of context value in the whole agricultural industry chain will continue to extend, and more types of value co-creation logic will be generated to meet customer consumption expectations in a broader spatio-temporal dimension, which helps to achieve the goals of rural revitalization and common prosperity.#br#