Business Model Innovation of Chinese Logistics Enterprises from the Perspective of Ecosystems: The Case of Cainiao Network

doi:10.21203/rs.3.rs-3584501/v1

Download PDF

Research Article

Business Model Innovation of Chinese Logistics Enterprises from the Perspective of Ecosystems: The Case of Cainiao Network

https://doi.org/10.21203/rs.3.rs-3584501/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

With the development and application of digital technology, a new logistics ecology based on the internet and big data is emerging through collaborative innovation models and advanced Artificial Intelligence technology. Building on the event system theory, we analyze Cainiao’s business model innovation from the perspective of ecosystem research through three aspects: value proposition, value co-creation, and value capture. The research concludes that Cainiao should realize business model innovation from the following three aspects: (1) clearing value proposition, (2) co-creating value through ecological cooperation and an open platform, and (3) capturing value by positioning precisely, distributing legitimately, and managing the supply chain.

business model innovation

ecosystem

event system theory

digital technology

logistics industry

In recent years, the development of digital technology has had a subversive and innovative impact on the production, operation, sales, and service models of traditional industries. The digital economy, represented by new technology, has become a new driving force for social development and constantly promotes the digitization and intelligent processes of industrial development. As a productive service industry, the logistics industry plays a strategically supportive role in the development of the national economy.

However, under the background of the ‘digital economy,’ Chinese logistics enterprises still need to solve the problems of improving distribution networks, promoting the efficient connection of logistics facilities, strengthening the efficient sharing of information, and reducing the institutional cost and comprehensive cost of logistics. Therefore, changing the organizational logic of value co-creation and deepening management innovation has become an inevitable choice for logistics enterprises to realize the transformation from being element-driven to innovation-driven and accelerating reductions in cost reduction and increases in efficiency.

Most scholars have studied business model innovation and business model innovation orientation. Amit and Zott (2009) studied business model innovation from a systemic perspective, including design themes and design components. From the perspective of business model components, Weill (2001) and Osterwalder (2010) proposed that in a business model’s value system, innovation can be stimulated by changing the combination of factors. From the perspective of value chains, Magretta (2002) concludes that product or process innovation can lead to enterprise business model innovation. In addition, Afuah (2001), Weill (2002), Chesbrough (2007), and Giesen (2007) proposed approaches to business model innovation based on dynamic orientation, arguing that the power of innovation affects the choice of innovative approaches, and is the entry point and driving force of business model innovation.

Recently, many scholars, such as Teece et al. (2018), have called for the study of digital business models from the perspective of the ecosystem. In addition, most existing studies focus on the manufacturing industry, and few studies have focused on the business model innovation of logistics enterprises. Compared to the manufacturing industry, the industrial characteristics of logistics enterprises determine the unique framework of business model innovation. Therefore, this study takes the logistics enterprise Cainiao Network as an example and studies the business model innovation of Chinese logistics enterprises from the ecosystem perspective. It argues that Chinese logistics enterprises should realize business model innovation from the following three aspects: (1) clearing value proposition, (2) co-creating value through ecological cooperation and an open platform, and (3) capturing value by positioning precisely, distributing legitimately, and managing the supply chain.

The remainder of this paper is organized as follows. First, we briefly review event system theory and the background of the business model and ecosystem. Taking the Cainiao Network as an example, we analyze a company’s business model innovation from the perspective of ecosystem research through three aspects: value proposition, value co-creation, and value capture. Finally, we explain the important role of ecosystem theory in the realization of disruptive business model innovation in logistics enterprises, which expands the content of the current theoretical framework.

2.1 Event System Theory

An event system is a complex of three interacting event components: event strength, space, and time. Morgeson et al. (2015) proposed event system theory, which suggests that novel, disruptive, and/or critical events (reflecting an event’s strength) are influential enough to produce variations in subsequent events over time, ultimately driving changes in organizational structure and the formation of new norms within the organization.

Moreover, events and their effects can travel within or across all organizational levels (e.g., individuals, teams, organizations, and the environment). Hartmann et al. (2022) studied the importance of entrepreneurs’ psychological resilience at the individual level. They also proposed promising future research grounded in linking the psychological resilience of entrepreneurs to other research areas related to the new venture development process. At the team level, Ye et al. (2022) used event systems theory to explore how the spatial and temporal issues inherent in ex-leaders’ entrepreneurial endeavors may combine to influence employees’ entrepreneurial intention. At the organizational level, Leonhardt et al. (2020) considered digital innovation projects as events and used the characteristics of event strength to describe the impact of digital innovation projects on the organizational logic of IT functions. At the environmental level, many scholars have focused on the impact of COVID-19 on individuals (Li et al., 2022), and organizations (Chen et al., 2022), etc.

2.2 Business model

The business model is a cross-border activity system centered on the focus enterprise, which reflects the process of creating value for customers and partners, transferring this value to customers and partners, and transforming it into profits (Amit & Zott, 2001). The business model describes the design or architecture of value creation, transmission, and acquisition mechanisms (Teece, 2010). The business model includes three main aspects: value proposition, creation, and acquisition.

Value proposition is an important condition for driving the formation and development of innovation ecosystems, a value vision created by enterprises for innovation participants, and value commitment delivered to users. First, the design of the core value proposition is very important for enterprises to explore the possibility of a future vision and the user market, which helps enterprises create competitive advantages in an uncertain market environment. Second, the development of the core value proposition can bring new opportunities for innovation participants in different fields to attract external participants to join voluntarily and take continuous improvement of technology as a positive motivation for participation. Finally, the core value proposition is dynamic, and innovation participants must adjust and reformulate the value proposition according to the changing external environment.

Value creation comprises four aspects: (1) the source of value creation, that is, what resources and elements enterprises use to carry out value creation activities; (2) the participants in value creation, including customers, consumers, enterprises, and stakeholders in the ecosystem; (3) the process of value creation, or how enterprise leaders change their own perceptions to adjust the company’s strategy, business operations, product and process transformation, business model and organizational structure, and using resources and capabilities to create value (Vial, 2019); and (4) the target results of value creation, including meeting the needs of target customers, realizing the enterprise’s own value proposition, obtaining profits, and realizing value appreciation.

Value capture is a way for enterprises to obtain profit. Defects in business models (Chesbrough & Rosenbloom, 2002), problems at the broader ecosystem level, including the lack of complementary products or services (Adner, 2012) and regulatory uncertainty (Schiller et al., 2014), and government policies that may affect the current operating mechanism (Adamides & Mouzakitis, 2009; Liu et al., 2012) all pose challenges to value capture.

Teece (1986) conducted a pioneering study on how enterprises can benefit from value creation activities. He believes that the strength of property rights protection, complementary assets of enterprises, complementary technologies, industry standards, etc., will affect the ability to obtain value. Lippman and Rumelt (2003) studied the relationship between land as a complementary asset and value acquisition capability, and believed that enterprises should take the acquisition or possession of complementary assets that play an important role in value acquisition as a key strategy. MacDonald and Ryall (2004) propose that when an enterprise does not have certain complementary assets, it can cooperate with multiple enterprises with complementary assets and competition, but it should pay attention to the protection and control of intellectual property rights. Henkel and Baldwin (2013) emphasized the importance of property rights protection for value acquisition and argued that enterprises can obtain value through the modularization of intellectual property rights. Later, after the changes in the digital economy era, Teece (2018) studied the impact of platforms, ecosystems, general-purpose technologies, business models, etc. on value acquisition capability based on the original theoretical framework.

2.3 Ecosystem perspective

With the emergence of a large number of new technologies, the rise of market trends, such as the sharing economy, and the reform of organizational models such as platform-based organizations, new thinking on technology innovation, and management paradigms under conditions of volatility, uncertainty, complexity, and fuzziness has emerged in research and practice. In this context, ‘the ecosystem,’ as a new paradigm, has gradually attracted the attention of theoretical research and organizational practice over the past 20 years and has become a hot topic in innovation and strategic management.

Moore put forward the concept of ‘business ecosystems’ in 1993, and Ander then took the lead in developing research on the concept of ‘innovation ecosystems’ in 2006. As a leading topic, the innovation ecosystem has been deeply integrated with digital technology (Yoo et al, 2010), platforms (Gawer & Cusumano, 2014), cooperation (Hannah & Eisenhardt,2018), networks (McIntyre & Srinivasan, 2017), value creation, and value capture (Adner & Kapoor, 2010). Consensus has been reached that innovation ecosystems are multilateral. They involve an alliance structure established between heterogeneous participants to realize a common value proposition (Adner, 2017), and everyone widely recognizes their organizational characteristics. In an innovation ecosystem, the significance of technological progress and change has been emphasized. The realization of technological breakthroughs through the structure of alliances is one of the main common value propositions.

The term ‘digital ecosystem’ first appeared in the early twenty-first century. It refers to a self-organizing, scalable, and sustainable system composed of heterogeneous digital entities and their interrelationships. It focuses on interactions between entities to increase system effectiveness, gain benefits, and promote information sharing, internal cooperation, and system innovation (Li & Badr, 2012). Digital ecosystems have become an important research topic for practitioners and scholars.

With the rapid development and impact of digitalization, the digital ecosystem concept has been affected by a series of ecological, economic, and technological factors in its definition and has attracted discussion across disciplines. A digital ecosystem is a complex adaptive system composed of digital elements, providers, users, and other heterogeneous digital agents and their complex relationships. It can improve system efficiency, promote information sharing, enhance cooperation within and between agents, and promote system innovation through interactions between digital agents (Helfat & Raubitschek, 2018; Sussan & Acs, 2017; Teece, 2018; Li et al., 2012). Digital ecosystems can rely on virtual reality technology to expand the information space, so platform organizations play an increasingly important role in supporting socio-economic development (Helfat & Raubitschek, 2018). Modularity causes the digital platform to have a network effect, and the value of the ecosystem increases with an increase in platform participants (Song, 2019).

3.1 Research design

We study the question of the detailed process of ‘how,’ and therefore adopts the case study method for inductive theory construction (Eisenhardt, 1989; Eisenhardt & Graebner, 2007). First, identifying multiple key events in the vertical development of the target enterprise and seeking out how the ecosystem perspective affects the business model innovation process of the enterprise can effectively establish a causal chain. Second, it covers the entire vertical process from the establishment of the enterprise to the present stage, which is very effective in deconstructing the dynamic process of business model innovation. Finally, in view of the purpose of our study to explore how logistics enterprises carry out business model innovation, we choose the longitudinal case method discussed by Langley et al. (2013), which is suitable for process research.

At the same time, based on the particularity of the case study method, it is better to take typical examples (Eisenhardt, 1989). Single-case selection should be both extreme and inspiring (Eisenhardt, 1989; Eisenhardt & Graebner, 2007). We chose the Cainiao network as the object of the case study, considering the typicality and inspiration of the case. (1) The Cainiao Network is the first platform logistics enterprise, aiming to establish the backbone network of intelligent logistics in China, and empower the operations, scenarios, and facilities of the logistics industry with digital technology; (2) the platform is in a leading position in the development of e-commerce logistics; and (3) a logistics service ecosystem led by Cainiao, dominated by Post, Zhongtong, Yunda, Baishi, Debang, and other logistics enterprises, and participated in by many warehousing, instant logistics, logistics technology companies, and other enterprises has been formed. (4) The relevant case data of the enterprise are sufficient to ensure that they can reflect the overall business model transformation process of the case.

3.2 Data Collection

We mainly adopted triangulation verification as a data collection strategy (Yin, 1994), which collected data from multiple sources and cross-compared them with interviewees many times to avoid errors and improve data reliability. We obtained a large amount of relevant data from the CNKI China journal full-text database, Wanfang Information Resource System, the company’s official website, WeChat public accounts (such as the logistics salon and logistics reference), and other channels. From the perspective of the subject of data generation, the collected data include not only the speech reports of Cainiao’s senior managers, interview records, news reports, and comments from mainstream media, but also the external publicity materials and internal archives of enterprises. In addition, the first-hand data came from the author’s semi-structured open interviews with three middle- and high-level management personnel of the company (see Table 1). All the interviews were conducted for one and a half hours to two hours.

Table 1

Interview implementation and data acquisition source
Interview objects	Interview form	Interview times	Main contents
Strategic department manager (Chao Jiang)	Open semi-structured interview	2hours	What is the background and development history of the company? What milestone events have occurred in the development process (such as business model change, strategic transformation, major product/technological innovation, entry into new markets, etc.)? What do you think is the core competence or competitiveness of the enterprise? What are the future strategic goals of the company? In the future strategic layout, which actors (universities, investment institutions, governments, other enterprises, etc.) will be expanded? How is it considered?
Director of operations (Qingxin Dong)	Open semi-structured interview	1 and a half hours	What is the relationship between the business and the customer? Which actors do you have strong relationships with? Why do you want to connect with these actors? What mechanisms exist in interactions with other actors to maintain relationships with these actors? How do enterprises cooperate and interact with different actors to achieve value co-creation?
Senior business administrator (Jie Wang)	Open semi-structured interview	1 and a half hours	What are the difficulties and pain points faced by enterprises in the process of development? What is the solution? What new products, services or markets have been developed through the collaboration? What is the connection between these new products/services and other products/services of the enterprise?

3.3 Key Construction and Description

Our case study deals with key constructs such as event strength, event space, value proposition, value creation, and value capture. Before the case analysis, we reviewed the existing literature and clarified the meaning and measurement of key constructs. The key constructs are defined as follows:

Event attribute. Event system theory argues that each event contains three-dimensional attributes: strength, time, and space. According to Morgeson et al. (2015), event strength includes novelty, disruption and criticality. Event space refers to the spatial hierarchy of event occurrence and its diffusion range, among which the spatial hierarchy is divided into environment, organization, team, and individual.

Value proposition. The value proposition reflects the overall goal of the business model, including meeting customer needs, creating a consumer surplus, realizing the value of stakeholders, and bringing profits to partners. A common value proposition can balance the complex interdependence between ecological participants and the external environment in the process of ecosystem evolution to regulate the growth and stability of the ecosystem dynamically.

Value creation. Value creation refers to how an enterprise creates value by combining resources and activities. The digital process can support successful innovation, enable enterprises to create novel product configurations (Cenamor et al., 2017), enhance the understanding of customer needs (Metallo et al., 2018), and establish a cooperative ecosystem with participants outside the company’s boundaries (Hakanen & Rajala, 2018).

Value capture. Value capture is a method for enterprises to obtain profits when delivering value to users. The value-capture process is inherent in a company’s business model (Osterwalder & Pigneur, 2010). However, from the perspective of companies and ecosystems, the value obtained differs to some extent (Borgh et al., 2012).

Event coding analysis. Referring to Liu et al. (2017), we hold that event strength includes three characteristics: novelty, disruption, and criticality. The spatial diffusion range is divided into +++ reachable outside the industry, ++ reachable inside the industry, and + reachable inside the organization, and is divided into three levels: +++ strong representativeness, ++ representative, and + Weak representation. Specific descriptions and event attributes are listed in Table 2.

Table 2

Summary of key events in the growth of Cainiao
Event codes	Event types		Event descriptions	Event strength			Events space
Event codes	Active	Passive	Event descriptions	Novelty	Disruption	Criticality	Events space
I20130518		√	In order to improve the quality of express delivery service on the platform, Alibaba joined forces with retail, real estate, logistics and other enterprises to create Cainiao Network.	++	+++	+++	+
I201412	√		Cainiao’s first self-developed WMS system “Dabao” issued the first formal order.	+++	++	++	++
I201504	√		Cainiao Station cooperation platform launched.	++	+++	++	++
I201509		√	Cainiao Network and the United States Postal Service reached a strategic cooperation.	+	+	++	+++
I201512	√		Cainiao Network officially launched China’s first logistics cloud platform, and Yunda Express became the first strategic partner.	+++	+++	+++	+
I20160314		√	Cainiao received a total of 10 billion yuan in financing from institutions such as Singapore’s Government Investment Corporation and Temasek Holdings, to jointly promote the establishment of a big data logistics network.	+	+++	++	+++
I201608	√		Cainiao Network and Nippon Express reached a cooperation, which will provide direct mail (collection) service for Japanese goods for consumers of Tmall International.	+	+	++	+++
I201610	√		Cainiao Guoguo launched the ‘one-click out of the cabinet’ function, which can realize “code-free pickup” for self-pickup cabinets.	++	+++	++	++
I201709		√	Cainiao received 5.3 billion yuan strategic investment from Alibaba, and announced that it would invest 100 billion yuan in the next five years to build a logistics network, achieving China 24 hours, global 72 hours delivery.	+	+++	++	+
I201802	√		Cainiao and Tmall International jointly announced that they have started using blockchain technology to track, upload and verify the logistics information of cross-border imported goods.	++	+++	++	+++
I201902		√	The ‘smart supply chain brain’ jointly innovated by Nestlé and Cainiao Network was officially launched at Nestlé’s Beijing headquarters.	++	++	+	++
I201905	√		Alibaba integrated the resources of four ground distribution companies: Zhima Open Door, Dongjun Logistics, Lianbao Wanxiang and Shengbang Logistics, combined with the technology of intelligent algorithms, and launched Danniao Logistics.	++	++	++	+++
I20210610	√		At the Global Smart Logistics Summit, Cainiao Network CEO Wan Lin gave a new definition of the company’s positioning: a customer value-driven globalized industrial Internet company, emphasizing the leading role of customer needs for the company and the importance of internationalization in Cainiao Network’s future development.	+	++	++	+
I2022	√		Cainiao has built and put into operation distribution centers in Israel, Mexico, and South Korea, with a daily production capacity of over 100,000 orders each.	++	++	+++	+++
I202303	√		Cainiao and Tmall Supermarket launch ‘1212 half-day delivery’ service.	+	+	+	++

4.1 Value Proposition

At the beginning of its establishment, the Cainiao Network adhered to Alibaba’s consistent platform mode of thinking, aiming to establish a logistics system through data-driven and socialized collaboration, integrate warehouse distribution, express delivery, terminal and other logistics links, build a global smart logistics backbone network, and become the ‘public infrastructure’ of the logistics industry.

As Alibaba Executive Chairman Daniel Zhang emphasized, ‘Cainiao must be a logistics network, not a logistics company. Technology is the core of Cainiao. Cainiao needs to do things that other companies cannot do.

Cainiao is positioned as a technology company that focuses on empowering logistics companies. The purpose of the establishment is to realize the digitalization and visualization of the logistics process by integrating the data of logistics companies, merchants, consumers, and third-party social organizations, and to improve the degree of information symmetry between logistics companies and merchants. To this end, Cainiao has promoted a ‘one horizontal and two vertical’ strategy recently, including building digital infrastructure for the entire logistics industry, building future-oriented smart logistics supply chain solutions based on new retail and building a global logistics network. The positive reactive type of events positioned Cainiao itself as an activity supporter in the logistics ecosystem, which also determined that Cainiao was destined to adopt a completely different logistics system establishment strategy from that of other e-commerce enterprises. This feature was reflected in events I20130518 and I201709.

The Cainiao Network insists on being a global industrial Internet company, driven by customer value. As Chao Jiang, strategic department manager, said, ‘Cainiao Network will always be customer-oriented, driven by technological innovation, based on the principle of win-win cooperation, and with social responsibility as its mission, and is committed to creating a data-driven, open, collaborative, and shared social logistics platform to provide smart supply chain services for global merchants and consumers.’

From the perspective of supply chain management, the Cainiao Network, as a part of the Alibaba Group, enjoys unparalleled advantages in terms of capital, technology, and customer base. These strengths offer a significant edge to the fiercely competitive platform business landscape. To sustain and expand this advantage, platform enterprises should focus on capital optimization and technological innovation while also introducing a suite of tailored services to attract collaborators from various industries and sectors. As the platform scales and ecosystem strengthens, the cost and risks associated with default for participating entities increase, thereby enhancing the stability and efficiency of the supply chain.

Furthermore, once platform enterprises attain a certain size and influence, they can emulate Cainiao’s strategy of elevating the utilization of internal funds to minimize the complicated procedures required for using external capital, thus shortening the transaction cycle and reducing transaction costs. Adopting such a strategy can grant platform enterprises greater strategic autonomy in their business.

With the affordance of digitization, the scope, target audience, and value proposition of enterprises have expanded, enabling the Cainiao Network to capture information more flexibly and dynamically, and to better forecast market demand. In 2020, the Cainiao Network officially announced the transformation of Cainiao Stations into one-stop digital community service centers. Moving beyond last-mile delivery, Cainiao Stations will no longer offer only package pick-up and sending services; instead, they will cater to a broader range of scenarios, such as community commerce and household consumption, offering diverse and replicable lifestyle services.

It is evident that the Cainiao Network has decisively disrupted traditional organizational models and initiated digital transformation. This enables the enterprise to adjust and allocate resources in real time, dynamically and accurately identify customer needs, and offer new products and services. Consequently, it paves the way for the emergence of diversified value propositions. We posit:

Proposition 1: Logistics enterprises should have clear value propositions. The affordance of digitization provides diverse novel products and services to realize multiple-value propositions.

4.2 Value Co-creation

Ecological cooperation. As a leading enterprise in the platform ecosystem, the Cainiao Network had to correctly identify and attract partners with complementary capabilities and roles to enter the system to meet the diverse needs of consumers in different business links. In this process, it was found that express delivery enterprises could not guarantee service efficiency and quality due to limited capacity or content with the status quo. The Cainiao network designed a performance evaluation and incentive mechanism for express delivery enterprises, observed and scored them, and encouraged express delivery enterprises to optimize their internal operations. Thus, express delivery enterprises realized that through cooperation, they could improve their service ability. For example, in events I201509, I201512, I201608, and I201802, Cainiao Network cooperates with various ecological partners to achieve value co-creation.

In events I201509 and I201512, the Cainiao Network, United States Postal Service, and Yunda Express reached strategic cooperation. Moreover, through cooperation with STO, ZTO, and other target customers established a strong connection with Cainiao to form a complete set of efficient product architectures. By allocating extensive basic resources and innovative resources with both depth and breadth, the Cainiao Network has built an intelligent logistics network with data analysis as the core and has promoted the deep transformation and upgrading of the industry under the role of the data platform.

In addition, Cainiao has developed strategic cooperation with DHL, an international logistics company, to complement and coordinate business and cooperate with industry associations and local enterprises to develop new technologies. Therefore, while improving the comprehensive service capability of enterprises, they have also formed an interdependent relationship with a large number of heterogeneous and diverse species, successfully stimulating network effects and realizing a large number of strategic resources for ecosystem development. Our case study finds that reactive event strength lays a foundation for multi-subject value co-creation and collaborative development on the logistics ecological platform.

Through ecological cooperation, Cainiao has become the world’s fourth largest cross-border logistics provider. Senior business administrator Jie Wang said, through cooperation with the government, customs, airlines and other companies, Cainiao have established a global intelligent logistics network (GLN), created a number of cross-border e-commerce integrated logistics centers, provided cross-border e-commerce with fast, traceable and low-cost logistics solutions, and achieved the world’s Top20 cities in 5 days. Cainiao has developed smart supply chain services. Through cooperation with many industries, such as FMCG, tobacco, steel, and automotive, the company provides digital supply chain management systems to provide customers with intelligent solutions such as collaborative planning, commodity replenishment, and allocation, thereby helping customers optimize supply chain efficiency and cost. These services complement each other with other logistics services of enterprises, forming a complete national logistics system. Thus, we posit:

Proposition 2a: Logistics enterprises may forge alliances with platform participants to share and co-create value within an ecosystem.

Open platform. Traditionally, most firms have adhered to a relatively insular approach to innovation, concentrating efforts within the confines of organizational boundaries. However, in contemporary contexts marked by a paradigmatic shift from entity-based organization and value-creation logic to platform-centric models and co-creative value mechanisms, the delineation of boundaries increasingly prioritizes collaborative endeavors. Enabled by the advent of digital technologies, organizational identity transforms into a more fluid and dynamic construct, thereby dissolving traditional barriers to innovation. Consequently, a growing number of enterprises are transitioning toward increasingly open and diverse innovation models.

The metamorphosis from a more rigid, entity-based system to a fluid, platform-oriented configuration has been catalyzed by the pervasive influence of digital technologies. Such technologies have transformed the essence of what an organization is, turning it from a monolithic entity into a fluid, dynamic construct. This elasticity transcends traditional barriers to innovation, fostering an increasingly open environment wherein diverse innovation models flourish. In the era of digital ecology, more innovative activities are systematic, complex, and modular, and each innovation subject has become the most basic component node in the activities of the digital ecosystem, interdependent and self-organizing, both competing and cooperating with each other, and ultimately achieving co-evolution.

The contemporary landscape of logistics is undergoing a seismic shift buoyed by a trio of transformative technologies such as Digital Twins, Artificial Intelligence (AI), and the Internet of Things (IoT). The genesis of the Logistics IoT Open Platform, a collaborative venture spearheaded by Cainiao, Ali Cloud, and a consortium of strategic partners, epitomizes this tectonic transformation. This endeavor signifies a confluence of disparate yet interconnected domains, rendering the logistics ecosystem not just a mere backdrop for transportation and delivery, but a hotbed for technological synergies and data-driven intelligence.

Gu Xuemei, the CTO of Cainiao Network, said, ‘Only by building this open platform can we make the Internet of Things expand at a low cost and scale, improve the level of digitalization and intelligence, let practitioners have better experience and let consumers feel better service.’

The logistics IoT open platform was jointly established by Cainiao, Ali Cloud, and partners based on digital twins, AI, and IoT technology. After access, any logistics scenario can be turned into a digital twin that can be intelligently scheduled, and logistics tasks are automatically planned by algorithms according to orders, etc.. The open logistics IoT platform will be fully open to the logistics industry. The development of various application products should be based on their own needs, participate in information sharing with each other, and jointly share the business value brought by cloud computing and logistics big data. This opening move will effectively promote digitalization and intelligence in the logistics industry. We propose:

Proposition 2b: Logistics enterprises may build an open platform to foster cooperation among diverse stakeholders, enabling the cultivation of an open innovation model to achieve value co-creation.

4.3 Value Capture

Value positioning. Cainiao Network embarked on a novel developmental trajectory, distinguishing itself from traditional logistics firms by evolving into a logistics service integrator, commonly referred to as fourth-party logistics. The company prioritizes a global strategy, leveraging data technology to construct its core platform and extending its reach from traditional offline operations into the online space. Unlike its traditional counterparts, the Cainiao Network does not consider transportation and warehousing to be its core businesses. Instead, they concentrate on both high-end and emerging markets. As articulated during Event I20210610, Cainiao Network positions itself as a customer-value-driven, globalized industrial Internet company, accentuating the centrality of customer needs and the imperative of internationalization in its future development.

Network By judging the trend of technological and professional development in the Chinese logistics market, Cainiao Network has used customized product portfolios that are highly matched with different market characteristics to complete its penetration from the edge market into the mainstream market. On the one hand, it has developed the software of logistics networks and provides logistics technical services, management, and investment advisory services; on the other hand, Cainiao station is laid into the community and campus to tap the potential of the end of the sinking market distribution. By fully sorting and deploying resources such as technical channels available to enterprises, innovation opportunities from both sides of the sinking and high-end markets can be identified. We propose:

Proposition 3a: Logistics enterprises should clarify value positioning, focus on their core competencies, and expand their market scope to facilitate value capture.

Value distribution. By instituting robust governance and incentive mechanisms, Cainiao Network adeptly navigates overlapping responsibilities and potential conflicts among its various partners. This strategy allows each stakeholder to optimize their contributions at distinct logistics junctures, fulfilling diverse service requirements while reaping commensurate profits. Collaboration is further facilitated through effective labor division and synergistic partnerships, leading to more efficient distribution services.

As the Director of Operations Qingxin Dong said,” there is interaction and collaboration between enterprises and multiple entities. e.g., enterprises and merchants carry out logistics marketing cooperation, using logistics scenes for brand promotion and sales promotion; Enterprises and express companies to carry out logistics cooperation, using the data platform for order allocation and capacity scheduling; Enterprises collaborate with the government in logistics planning and use their expertise to build logistics infrastructure and policies’. It can be seen that through interaction with various subjects such as merchants, courier companies, and the government, Cainiao has realized its own resource integration and ability improvement to promote its value co-creation process. Thus, we propose:

Proposition 3b: Logistics enterprises should strengthen their cooperation and interaction with various stakeholders and establish a reasonable value distribution mechanism to facilitate the process of value capture.

Value supply chain. The Cainiao Network, using data technology to enable more partners, supports supply chain cross-border logistics, covering 224 countries and regions worldwide and 231 cross-border warehouses. The company built a cross-border logistics backbone network with global distribution capabilities for cross-border e-commerce and consumers to provide one-stop logistics solutions. Cainiao’s supply chain not only provides high-quality warehouse services and digital intelligence systems but also plans to build a next-generation digital intelligence supply chain together with merchants to help merchants build supply chain competitiveness in the future. This feature is reflected in events I201902, I201905, and I202303. For example, in event I201905, the ‘smart supply chain brain, ’ jointly innovated by Nestlé and Cainiao Network, was officially launched at Nestlé’s Beijing headquarters. As a global leader in the fast-moving consumer goods industry, Nestlé chose the Cainiao Network as its supply chain partner in China when it entered the Chinese e-commerce market, thus solving many problems in Nestlé’s supply chain.

The Cainiao Network will build a value supply chain with four advantages. The first is higher supply chain returns, relying on Ali Big Data and Cainiao number intelligence ability, enabling merchants to accurately forecast, make scientific decisions, optimize links, reduce inventory, and improve turnover. The second is greater supply chain resilience, relying on its warehouse distribution network, professional operation, and digital intelligence technology with strong flexibility to meet merchants’ demands and promote the peak guarantee. The third is faster supply chain innovation, which means keeping up with new retail and other business model innovations, innovation for merchants through rapid iteration, and having an agile response to supply chain problems. Fourth is gaining wider supply chain resources, such as efficient collaboration with Ali Digital Economy volume logistics ecological enterprises to provide merchants with abundant optional, stable, and reliable warehouse transportation and distribution resources.

Proposition 3c: Logistics enterprises should enhance the digital and intelligent value supply chain to facilitate the optimal allocation of warehousing and distribution resources and improve logistical timeliness, thereby contributing to value capture for the enterprise.

5.1 Contributions

This study contributes to a preliminary theoretical understanding of business model innovation in logistics enterprises. First, it explains the important role of ecosystem theory in the realization of business model disruptive innovation of logistics enterprises, which expands the content of the current theoretical framework. Second, the main axis of the research framework of this study is business model innovation, which integrates ecosystem structure embedding theory (Adner, 2017), cooperation theory (Hannah & Eisenhardt, 2018) and verifies the theoretical complexity and systematization of business model transformation and innovation based on the perspective of ecosystem activities (Holtstrom, 2022). This suggests that researchers should be more detailed and comprehensive when using business model innovation to investigate organisational practice, so as to see through the basic law of organisational transformation.

5.2 Implications for Practice

This study sheds important light on the transformation practices of enterprise management decision-makers. It focuses on enterprise business model innovations. Business model innovation is an effective way to improve enterprise performance, especially in volatile and complex environments, as it helps enterprises enhance competitiveness and maintain competitive advantage. Simultaneously, the implementation of business model innovation requires the support of resources and capabilities. Platform-oriented enterprises should identify and attract partners with complementary capabilities and roles to the ecosystem.

5.3 Limitations and Future Research

Although this study has deeply refined the theoretical process mechanism of Cainiao Network’s business model innovation, relevant empirical data are still needed to test them one by one to further improve and supplement the theoretical framework of the study. Specifically, this study only proposes business model innovation from the perspective of the ecosystem based on the existing literature, and subsequent exploratory studies based on cases can be further explored and supplemented. In addition, we hope that subsequent studies will further explore the mediating and moderating mechanisms in the process of business model innovation to improve its framework of business model innovation.

Taking the Cainiao Network as an example, we analyze its business model innovation of Cainiao Network from the perspective of ecosystem research through three aspects: value proposition, value co-creation, and value capture. We argue that Chinese logistics enterprises should realize business model innovation from the following three aspects: (1) clearing value proposition, (2) co-creating value through ecological cooperation and an open platform, and (3) capturing value by positioning precisely, distributing legitimately, and managing the supply chain. We also explain the important role of ecosystem theory in the realization of business model disruptive innovation of logistics enterprises, which expands the content of the current theoretical framework.

Ethical Approval

not applicable

Funding

Funding Statement: The study was supported by grant Academic Research Projects of Beijing Union University No. ZK10202307 from the Foundation of Basic Research.

Author Contribution

Jian Wang (First Author):Conceptualization, Methodology, Software, Investigation, Formal Analysis, Writing - Original Draft;Fan si(Corresponding Author):Conceptualization, Funding Acquisition, Resources, Supervision, Writing - Review & Editing.Siyu Yang:Data Curation, Writing - Original Draft;Lin Wang:Writing - Review & Editing

Availability of data and materials

not applicable

Adamides ED, Mouzakitis Y (2009) Industrial ecosystems as technological niches. J Clean Prod 17(2):172–180
Adner R (2006) Match your innovation strategy to your innovation ecosystem. Harvard Business Rev 84(4):98
Adner R (2012) The Wide Lens: A New Strategy for Innovation. Portfolio/Penguin, U.S.A.
Adner R, Kapoor R (2010) Value creation in innovation ecosystems: How the structure of technological interdependence affects firm performance in new technology generations. Strateg Manag J 31(3):306–333
Adner R (2017) Ecosystem as structure: an actionable construct for strategy. J Manag 43(1):39–58
Afuah A, Tucci C (2001) L. Internet Business Models and Strategies: Text and Cases. Internet business models and strategies: McGraw-Hill/Irwin. 242–245
Amit R, Zott C (2001) Value creation in e-business. Strateg Manag J 22:493–520
Borgh M, Cloodt M, Romme AGL (2012) Value creation by knowledge-based ecosystems: evidence from a field study. R&D Manage 42(2):150–169
Cenamor J, Sjodin DR, Parida V (2017) Adopting a platform approach in servitization: leveraging the value of digitalization. Int J Prod Econ 192:54–65
Chen LF, Liu HF, Zhou ZY, Chen M, Chen Y (2022) IT-business alignment, big data analytics capability, and strategic decision-making_ Moderating roles of event criticality and disruption of COVID-19. Decis Support Syst 161:113745
Chesbrough H (2007) Business model innovation: it’s not just about technology anymore. Strategy & Leadership 35(6):12–17
Chesbrough H, Rosenbloom RS (2002) The role of the business model in capturing value from innovation: evidence from xerox corporation's technology spina off companies. Ind Corp Change 11(3):529–555
Chesbrough H (2010) Business Model Innovation: Opportunities and Barriers. Long Range Plann 43(2):354–363
Dubosson-Torbay M, Osterwalder A, Pigneur Y (2002) E-business model design, classification and measurements. Thunderbird Int Bus Rev 44(1):5–23
Eisenhardt KM (1989) Building Theories from Case Study Research. Acad Manage Rev 14:532–550
Eisenhardt K, Graebner M (2007) Theory Building from Cases: Opportunities and Challenges. Acad Manag J 50:25–32
Foss NJ, Saebi T (2018) Business models and business model innovation: Between wicked
and paradigmatic problems. Long Range Plann, 51(1), 9–21
Gawer A, Cusumano M, A (2014) Industry platforms and ecosystem innovation. J Prod Innov Manage 31(3):417–433
George C, Bock AJ (2011) The Business Model in Practice and Its Implications for Entrepreneurship Research. Entrepreneurship Theory and Practice 35(1):83–111
Giesen E, Berman SJ, Bell R et al (2007) Three ways to successfully innovate your business model. Strategy & Leadership 35(6):27–33
Hakanen E, Rajala R (2018) Material intelligence as a driver for value creation in IoT-enabled business ecosystems. J Bus Industrial Mark 33(6):857–867
Hannah DP, Eisenhardt KM (2018) How firms navigate cooperation and competition in nascent ecosystems. Strateg Manag J 39(12):3163–3192
Hartmann S, Backmann D, Newman A, Brykman KM, Pidduck RJ (2022) Psychological resilience of entrepreneurs: A review and agenda for future research. J Small Bus Manage 60(5):1041–1079
Helfat CE, Raubitschek R (2018) Dynamic and integrative capabilities for profiting from innovation in digital platform-based ecosystems. Res Policy 47:1391–1399
Henkel J, Baldwin CY, Shih W (2013) IP Modularity: Profiting from Innovation by Aligning Product Architecture with Intellectual Property. Calif Manag Rev 55(4):65–82
Holtström J (2022) Business model innovation under strategic transformation. Technol Anal Strateg Manag 34(5):550–562
Langley A, Smallman C, Tsoukas H, Ven AHVD (2013) Process Studies of Change in Organization and Management: Unveiling Temporality, Activity and Flow. Acad Manag J 56:1–13
Leonhardt D, Hanelt A, Kranz J (2020) How digital innovation projects cultivate shifts in IT functions’ organizing logics: insight from a multiple case study. ECIS 2020 Research Papers. 160
Leviäkangas P, Öörni R (2020) From business models to value networks and business ecosystems – What does it mean for the economics and governance of the transport system? Utilities Policy
Lippman SA, Rumelt RP (2003) The payments perspective: micro-foundations of resource analysis. Strateg Manag J 24(10):903–927
Liu C, Ma C, Zhang K (2012) Going beyond the sectoral boundary: a key stage in the development of a regional industrial ecosystem. J Clean Prod 22(1):42–49
Liu D, Liu J (2017) Dissecting event system theory: tenets and opportunities for research and practice. Q J Manag 2:64–80. 10.14134/j.cnki.cn33-1336/f.2021.03.001
Li W, Badr Y, Biennier F (2012) Digital ecosystems: Challenges and prospects. In proceedings of the international conference on management of Emergent Digital Ecosystems, 117–122
Li Y, Chen H, Liu C, Liu H (2022) How does COVID-19 pandemic affect entrepreneur anxiety? The role of threat perception and performance pressure. Front Psychol 13:1044011
MacDonald G, Ryall M (2004) How Do Value Creation and Competition Determine whether A Firm Appropriates Value? Manage Sci 50(10):1319–1333
Magretta J (2002) Why Business Models Matter. Harvard Business Rev 80(5):86–92
McIntyre DP, Srinivasan A (2017) Networks, platforms, and strategy: Emerging views and next steps. Strateg Manag J 38(1):141–160
Metallo C, Agrifoglio R, Schiavone F, Mueller J (2018) Understanding business model in the Internet of Things industry. Technol Forecast Soc Chang 136:298–306
Mitchell D, Coles C (2003) The Ultimate Competitive Advantage of Continuing Business Model Innovation. J Bus Strategy 24(5):15–21
Moore JF (1993) Predators and prey: a new ecology of competition. Harvard Business Rev 71(3):75–86
Morgeson FP, Mitchell TR, Liu D (2015) Event System Theory: An Event-Oriented Approach to the Organizational Sciences. Acad Manage Rev 40(4):515–537
Osterwalder A, Pigneur Y (2010) Business Model Generation: a Handbook for Visionaries, Game Changers, and Challengers. Afr J Bus Manage 5(7):4
Osterwalder A (2010) The Business Model Ontology – A Proposition in a Design Science Approach. Ecole Des Hautes Etudes Commerciales Universite
Schiller F, Penn AS, Basson L (2014) Analyzing networks in industrial ecology-a review of social-material network analyses. J Clean Prod 76:1–11
Song AK (2019) The Digital Entrepreneurial Ecosystem—a critique and reconfiguration. Small Bus Econ 53(3):569–590
Sussan F, Acs ZJ (2017) The digital entrepreneurial ecosystem[J]. Small Bus Econ 49(1):55–73
Teece D, J (1986) Profiting from Technological Innovation: Implications for Integration, Collaboration, Licensing and Public Policy. Res Policy 15(6):285–305
Teece D, J (2018) Profiting from innovation in the digital economy: enabling technologies, standards, and licensing models in the wireless world. Res Policy 47(8):1367–1387
Teece D, J (2010) Business Models, Business Strategy and Innovation. Long Range Plann 43(2–3):172–194
Timmers P (1998) Business Models for Electronic Markets. J Electron Markets 8(2):3–8
Ye Q, Wang DX, Zeng K (2022) An event-oriented approach to the transmission of ex-leaders' entrepreneurial endeavor to employees’ entrepreneurial intention. Human Relations, pp 1–27
Yin R (1994) Case Study Research. Sage Publications
Yoo Y, Henfridsson O, Lyytinen K (2010) Research commentary—the new organizing logic of digital innovation: an agenda for information systems research. Inform Syst Res 21(4):724–735
Vial G (2019) Understanding digital transformation: A review and a research agenda. J Strateg Inf Syst 28(2):118–144
Weill P, Vitale MR (2001) Place to Space: Migrating to E-business Models. Harvard Business School Press
Weill P, Vitale M (2002) What IT Infrastructure Capabilities are Needed to Implement E-Business Models? MIS Q Exec 1(1):17–34
Zott C, Amit R (2009) Designing Your Future Business Model: An Activity System Perspective. Iese Research Papers, 43(D/781), 829

No competing interests reported.

Download PDF

Version 1

posted

You are reading this latest preprint version

Business Model Innovation of Chinese Logistics Enterprises from the Perspective of Ecosystems: The Case of Cainiao Network

Status:

Version 1

Abstract

Figures

1 Introduction

2 Theory Background

2.1 Event System Theory

2.2 Business model

2.3 Ecosystem perspective

3 Research Methodology

3.1 Research design

3.2 Data Collection

3.3 Key Construction and Description

4 Case Analysis

4.1 Value Proposition

4.2 Value Co-creation

4.3 Value Capture

5 Discussion

5.1 Contributions

5.2 Implications for Practice

5.3 Limitations and Future Research

6 Conclusion

Declarations

Author Contribution

Availability of data and materials

References

Additional Declarations

Status:

Version 1