Research on Business Model Innovation of Enterprises in the Context of Digital Transformation ()
1. Introduction
In today’s rapidly changing business environment, digital transformation has become a critical strategic imperative for companies to maintain competitiveness and drive innovation. With the rapid development and widespread application of emerging technologies, such as artificial intelligence, big data, cloud computing, and the Internet of Things, traditional business models are facing unprecedented challenges and opportunities. Digital transformation is not merely a technological upgrade; it represents a profound business revolution that reshapes how enterprises create, deliver, and capture value. In this context, business model innovation has become the core driving force for companies to achieve digital transformation and maintain market leadership. In recent years, both academia and industry have delved deeper into the study of digital transformation and business model innovation. Vial (2019) points out that digital transformation is a multi-level organizational change process involving multiple dimensions such as technology, organizational structure, processes, and culture. Warner and Wäger (2019) emphasize the importance of dynamic capabilities in digital transformation, arguing that enterprises need to continuously perceive changes in the environment and reconfigure resources to adapt to the digital age. Regarding business model innovation, Teece (2010) proposed a theoretical framework for business model innovation, highlighting the synergistic effects of value proposition, value creation, and value capture. Foss and Saebi (2017) further explored the dynamic processes of business model innovation, noting that environmental changes are key drivers of business model innovation. However, despite existing research providing valuable insights into understanding digital transformation and business model innovation, there are still significant research gaps. Systematic studies on how digital technologies specifically influence and reshape the elements of business models are still lacking. The theoretical motivations and pathways for achieving business model innovation in the context of digital transformation have yet to be adequately explored. The roles of non-technical factors, such as organizational change, cultural reshaping, and talent strategy in the process of digital business model innovation require further clarification (Nambisan et al., 2017). The theoretical resistance and potential risks that may arise during digital transformation also need more in-depth research. Based on the aforementioned research background and existing literature deficiencies, this study aims to delve into the theoretical foundations, implementation pathways, and influencing factors of business model innovation for enterprises in the context of digital transformation. Through systematic theoretical analysis and the construction of a conceptual framework, this research seeks to provide theoretical guidance and practical insights for enterprises to achieve successful business model innovation in the digital age. Furthermore, this study lays the groundwork for future empirical research in this field, offering new research directions for both academia and industry.
The remainder of this paper is structured as follows: Section 2 presents the theoretical foundation and implementation path of digital transformation, including its definition, characteristics, impact mechanisms on business models, and typical innovation patterns. Section 3 analyzes the key influencing factors of digital business model innovation from organizational, technological and market perspectives. Section 4 concludes the paper with theoretical implications and future research directions.
2. The Theoretical Foundation and Implementation Path of Digital Transformation
2.1. Definition and Characteristics of Digital Transformation
Digital transformation is a complex, multi-dimensional concept involving changes at multiple levels, including technology, organization, strategy, and culture. According to Vial (2019), digital transformation is “a process aimed at significantly improving organizational performance through the application of digital technologies”. This definition emphasizes the goal-oriented and comprehensive nature of digital transformation. The core characteristics of digital transformation include being technology-driven, comprehensive, continuous, value-reconstructive, and ecosystem-oriented. Being technology-driven means that digital technologies such as artificial intelligence, big data, cloud computing, and the Internet of Things serve as the foundation and enabler of the transformation. Comprehensive nature reflects that digital transformation affects all aspects of an organization, including business processes, customer experience, organizational structure, and business models. Continuous nature emphasizes that digital transformation is not a one-time technological upgrade but an ongoing process of adaptation and innovation. Value reconstruction refers to how enterprises redefine and create value through digital transformation, including value propositions, creation, delivery, and capture. Ecosystem thinking highlights collaborative innovation with partners, customers, and other stakeholders. These characteristics collectively form the theoretical foundation of digital transformation, providing guidance for enterprises’ transformations in the digital era. However, digital transformation is not merely about applying technology; it represents a systematic change process involving multiple layers such as organization, strategy, and culture. When advancing digital transformation, companies need to comprehensively consider these characteristics and develop integrated transformation strategies to achieve comprehensive digital upgrades (Warner & Wäger, 2019). Figure 1 presents the main dimensions and characteristics of digital transformation, visually illustrating its multi-dimensional nature and core features.
2.2. The Mechanisms of Digital Technologies’ Impact on Business Models
The impact of digital technologies on business models is multifaceted, reshaping the logic and processes of value creation. Based on Teece’s (2010) theoretical framework for business models, we can analyze the impact mechanisms of digital technologies from four aspects: value proposition, value creation, value delivery, and value capture. Regarding value proposition, digital technologies enable
Figure 1. Dimensions and characteristics of digital transformation. Source: Compiled by the author based on Vial (2019) and Warner & Wäger (2019).
companies to provide more personalized and intelligent products and services. Data-driven precise recommendation systems can significantly enhance user experiences, while artificial intelligence technologies can achieve product intelligence and adaptability. In terms of value creation, digital technologies change how companies produce and operate. The application of the Internet of Things and artificial intelligence technologies realizes intelligent and automated production processes, significantly improving production efficiency and product quality. Meanwhile, digital platforms and collaborative tools promote knowledge sharing and innovation collaboration within and outside the organization. In terms of value delivery, digital platforms and mobile technologies completely transform how companies interact with customers. Mobile applications and social media provide new channels for customer outreach, while virtual reality and augmented reality technologies revolutionize customer experiences. For value capture, digital technologies introduce entirely new revenue models and profit opportunities. Subscription models, sharing economies, and platform economies are innovative commercial models brought about by digital technologies, which not only expand companies’ revenue sources but also reshape the value distribution patterns across entire industries. It is noteworthy that these four aspects are not independent; they influence and promote each other. Data-driven personalized services (value proposition) may require new production methods (value creation) and delivery channels (value delivery), which may also lead to new revenue models (value capture). Therefore, enterprises need to consider these impacts systematically and pursue holistic business model innovation during digital transformation (Nambisan et al., 2017). Figure 2 visually illustrates the mechanisms of digital technologies’ impact on the various elements of business models, aiding in our comprehensive understanding of the profound impacts of digital transformation on corporate business models.
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Figure 2. Impact of digital technologies on business models. Source: Compiled by the author based on Nambisan et al. (2017).
2.3. Typical Patterns of Digital Business Model Innovation
With the continuous development and application of digital technologies, several typical patterns of digital business model innovation have been validated and promoted in practice. This study summarizes the following typical patterns: Platform Model leverages digital platforms to connect multiple participants, achieving value co-creation and network effects. For instance, Didi Chuxing connects passengers and drivers to create a new mode of transportation. Subscription Model provides continuous digital services or content to secure stable revenue streams, such as Netflix’s streaming services. Sharing Economy Model utilizes digital technologies to activate idle resources, improving resource utilization efficiency, with Airbnb as a typical representative. Data-Driven Model collects and analyzes vast amounts of data to offer personalized services or insights, as exemplified by Google’s advertising business. Ecosystem Model builds open digital ecosystems, attracting partners for collaborative innovation, with Apple’s App Store ecosystem being a successful case. Product-as-a-Service Model transforms traditional products into services through digitization, such as Rolls-Royce’s “Power-by-the-Hour” model. These patterns are not mutually exclusive; companies can choose to combine one or more models based on their circumstances and market demands. It is important to note that the successful application of these models often requires companies to make corresponding adjustments and innovations in organizational structure, technical capabilities, and corporate culture. For example, the platform model may require companies to establish new governance mechanisms to manage multi-party relationships; the data-driven model demands strong data analysis capabilities and data security guarantees. The choice and implementation of these models also need to consider industry characteristics, competitive environments, regulatory policies, and other external factors (Weill & Woerner, 2015). Therefore, when pursuing digital business model innovation, enterprises must comprehensively assess internal and external conditions and formulate innovation strategies suitable for their needs.
2.4. Implementation Pathways for Digital Business Model
Innovation
Implementing digital business model innovation is a complex systemic project that requires companies to adopt systematic and comprehensive approaches. Based on an analysis of successful cases and theoretical research, this study proposes a framework for the implementation pathway of digital business model innovation. This framework includes the following key steps: Digital Diagnosis evaluates the current digital level and business model of the enterprise, identifying potential innovation opportunities and challenges. This step requires a comprehensive analysis of the company’s internal capabilities, market position, competitive environment, and technological trends. Vision Formulation establishes clear digital transformation visions and objectives based on diagnostic results. This vision should align with the company’s overall strategy and receive strong support from top management. Model Design designs new digital business models according to the company’s characteristics and market demands. This may involve innovations in aspects such as value proposition, value creation, value delivery, and value capture. Capability Building identifies the key capabilities required to realize the new business model and builds these capabilities through internal training, external cooperation, or acquisitions. This may include technical capabilities, data analysis capabilities, ecosystem management capabilities, and so on. Pilot Implementation selects suitable business units or markets for small-scale pilots to verify the feasibility and effectiveness of the new business model. Scale Promotion makes necessary adjustments to the business model based on pilot experiences and feedback, and then promotes it on a larger scale. Continuous Optimization establishes mechanisms for ongoing monitoring and optimization, continuously adjusting and refining the business model based on market responses and technological advancements. In this implementation process, companies need to pay particular attention to the following points: establish cross-functional teams to ensure collaboration across departments; prioritize change management to help employees adapt to new working methods and mindsets; create flexible organizational structures and decision-making mechanisms to quickly respond to market changes; and emphasize data security and privacy protection by establishing corresponding management systems and technical measures. Companies should also focus on building industry ecosystems and establishing new collaborative relationships with partners, customers, and even competitors (Matt et al., 2015). Figure 3 illustrates this implementation pathway framework, providing a clear action guideline for enterprises.
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Figure 3. Theoretical framework for business model innovation in a digital context. Source: Compiled by the author based on Matt et al. (2015) and Hess et al. (2016).
3. Key Influencing Factors of Digital Business Model
Innovation
3.1. Organizational Factors
Organizational factors play a crucial role in the process of digital business model innovation. These factors not only influence the speed and quality of innovation but also determine whether new business models can be successfully implemented and continuously optimized. Leadership is essential; digital transformation requires senior management to possess a forward-looking strategic vision and unwavering commitment to execution. They must clearly communicate the digital vision, drive cultural transformation, and prioritize digital initiatives in resource allocation and decision-making. The flexibility of organizational structure is also a key factor. Traditional hierarchical structures may not meet the rapid-changing demands of the digital age; companies need to establish flatter, networked organizational structures to promote cross-departmental collaboration and information flow. Many companies are adopting matrix structures or project-based approaches to enhance responsiveness and innovation capabilities. Talent strategy plays a decisive role in digital transformation. Enterprises need to attract and cultivate talent with digital skills while helping existing employees adapt to new working methods and skill requirements. This may involve establishing a digital talent development system and reforming performance evaluation and incentive mechanisms (Hess et al., 2016). The transformation of corporate culture is also a critical factor. Digital business model innovation requires a cultural atmosphere that encourages innovation, tolerates failure, and emphasizes continuous learning. Companies need to foster such a culture through various means, such as setting up innovation incubators or hosting hackathons. The organization’s data governance capabilities are also essential. In data-driven business models, effectively managing, analyzing, and utilizing data becomes a core competitive advantage. This necessitates establishing robust data management frameworks, formulating data security and privacy protection strategies, and fostering data literacy across the organization. It is noteworthy that these organizational factors are not independent; they influence and promote each other. Strong leadership can drive organizational structural adjustments and cultural transformations, while flexible organizational structures can facilitate talent mobility and the dissemination of innovative ideas.
3.2. Technological Factors
Technological factors are the core driving forces behind digital business model innovation, providing both the possibilities for innovation and shaping its direction and boundaries. The level of digital infrastructure development directly affects a company’s digital capabilities. This includes hardware facilities (such as cloud computing platforms and IoT devices) and software systems (such as enterprise resource planning systems and customer relationship management systems). Advanced digital infrastructure enables companies to develop and deploy new business models more quickly and flexibly. The application level of data analysis technologies is also a key factor. In data-driven business models, companies need robust capabilities in data collection, storage, processing, and analysis. This may involve the use of cutting-edge technologies like big data analytics, machine learning algorithms, and artificial intelligence. The degree of adoption of technologies such as APIs and microservices also influences a company’s innovation capabilities. These technologies enhance the modularity and flexibility of systems, allowing companies to rapidly integrate internal and external resources to launch new products or services. Additionally, the maturity of cybersecurity and privacy protection technologies cannot be overlooked. As data becomes increasingly important in business models, ensuring data security and compliance emerges as a significant technical challenge. The development and application of emerging technologies also continuously reshape the possibilities for business model innovation. For example, blockchain technology provides technical support for decentralized business models; the proliferation of 5G technology may bring entirely new mobile internet application scenarios; and advancements in quantum computing could fundamentally change the operational modes of certain industries. Importantly, the impact of technological factors is dynamic; companies must continuously monitor technological trends and possess the ability to rapidly absorb and apply new technologies. Furthermore, the selection and application of technology should serve business objectives rather than merely pursuing technology for its own sake. Companies need to find a balance between technological investment and business value, avoiding the pitfall of technology supremacy. The interaction between technological factors and other elements (such as organizational and market factors) is complex. The application of advanced technologies may necessitate corresponding adjustments in organizational structure and talent strategy (Fitzgerald et al., 2014), while changes in market demand may drive companies to adopt new technological solutions. Therefore, companies must adopt a holistic perspective when considering technological factors, comprehensively evaluating the interactions among various influences.
3.3. Market Factors
Market factors play a crucial role in digital business model innovation, influencing not only the direction and speed of innovation but also determining its success. Changes in customer demand are the core driving force behind business model innovation. The proliferation of digital technologies has transformed customer behavior and expectations; for example, customers now tend to prefer personalized, immediate, and cross-channel service experiences. Companies need to deeply understand these shifts in demand and adjust their value propositions and service models accordingly. The evolution of the competitive landscape is also an important market factor. Digitalization blurs traditional industry boundaries, making cross-industry competition the norm. For example, tech giants entering the financial sector or traditional manufacturing companies transitioning into service providers. This changing competitive landscape requires companies to continuously innovate their business models to maintain a competitive edge (Weill & Woerner, 2015). The development status of the industry ecosystem also affects business model innovation. In the digital era, no single company can independently meet all of a customer’s needs, necessitating collaboration with other businesses to form ecosystem partnerships. Therefore, the maturity of the industry ecosystem and the quantity and quality of partners can significantly influence the potential and effectiveness of a company’s business model innovation. Changes in the regulatory environment also represent market factors that cannot be overlooked. The rapid development of the digital economy brings forth a series of new regulatory challenges, such as data privacy, algorithm fairness, and platform liability. Changes in these regulatory policies may have substantial impacts on the feasibility of certain business models. Broader macroeconomic conditions and socio-cultural factors can also influence business model innovation. For instance, an economic downturn may accelerate companies’ pursuit of digital transformation, while societal focus on sustainability may drive companies to explore more environmentally friendly business models. Importantly, these market factors are not static but rather constantly evolving. Companies need to establish effective market insight mechanisms to continuously monitor and analyze these changes. Additionally, businesses should not merely adapt passively to market changes but proactively shape the market. By innovating business models, companies can create new market demands, reshape competitive landscapes, and even influence the development directions of industry ecosystems.
4. Conclusion
Digital business model innovation in the context of digital transformation represents a complex and dynamic process that demands a holistic approach. Through systematic analysis, this study provides comprehensive insights into the theoretical foundations, implementation frameworks, and critical success factors of digital business model innovation. Our findings reveal that successful transformation requires not only technological advancement but also synchronized evolution in organizational structure, corporate culture, and talent strategies. For practitioners, we propose several concrete recommendations: 1) Establishing cross-functional digital transformation teams to facilitate interdepartmental collaboration; 2) Implementing comprehensive digital talent development programs, including both technical and management training; 3) Building robust data governance capabilities to ensure data security and privacy protection; 4) Fostering an innovation-friendly culture that encourages experimentation and tolerates failure. For policymakers, we suggest: 1) Developing supportive policies for digital transformation, particularly for traditional industries; 2) Strengthening data protection regulations while promoting data sharing; 3) Investing in digital infrastructure development to support industry-wide transformation. These findings are particularly relevant for traditional enterprises seeking digital transformation, technology companies expanding into new sectors, and startups developing innovative business models. Looking ahead, as emerging technologies like artificial intelligence, blockchain, and 5G continue to evolve, business model innovation will face new opportunities and challenges. Future research should focus on empirical validation of digital transformation strategies across different industries and organizational contexts, as well as investigating the long-term performance implications of different digital business models. Companies that effectively leverage digital technologies, understand market demands, and successfully integrate ecosystem resources will likely gain competitive advantages in the digital economy.