Content area
Purpose
This study examines the use of a dynamic value-based approach to analyze the business model structuration of smart service providers in Brazil, mapping their value creation, configuration and appropriation strategies, and determining how well-defined their current business models are.
Design/methodology/approach
This is a qualitative study based on semi-structured interviews with entrepreneurs (or CEOs and directors of technology) of seven business ventures in three different phases of business model structuration: (1) academic: companies or innovation and research centers linked to universities; (2) startups: technology-based companies originating from the technological needs of clients, be they new branches of the traditional business of incumbents or new entrants and (3) autonomous service providers whose offerings are related to master’s or doctoral projects.
Findings
We propose a typology of business model structuration with four stages. At first (individual or initial business model), albeit with high skilling of owners, only manual or adaptation services are offered. In the second stage (platform business model), although services offered are oriented toward the entire process automatization of the client (Factory integrated), technologies are restricted to the client company (or even one department) and these clients' needs are mainly data processing and connectivity. In the third stage (scaling digital business model), although the services offered are oriented toward greater digitalization through an entire array of field devices connected to the internet (IoT) and organized in a more formalized structure, the business model is still being constructed, companies in this stage are mainly startups. In the fourth stage (innovation ecosystem business model), the entire manufacturing process is digitized, with integration and network connectivity, both between service providers and the extended supply chain of their clients, and new technologies are customized and developed through the interaction of a whole innovation ecosystem.
Research limitations/implications
Mapping value-based strategies aids in understanding business model structuration in Industry 4.0. Future research should focus on parameterizing the dimensions founded of each value strategy.
Originality/value
This study advances the comprehension of the business model in |Industry 4.0 by providing a value-based strategy perspective of business model structuration. Practically, by focusing on smart service providers, it contributes to a greater understanding of smart service providers in Brazil and their strategic challenges.
Quick value overview
Interesting because: Entrepreneurs frequently encounter substantial challenges in structuring business models, particularly when engaging with groundbreaking technologies associated with Industry 4.0. While existing literature provides frameworks and guidelines outlining the fundamental components of a business model, it often falls short of elucidating the actual process of business model structuring. Drawing on a dynamic value-based strategy perspective, this paper introduces a novel approach to understanding this process by mapping the stages experienced by several Brazilian companies in their journey to structure their business models.
Theoretical value: By examining the value creation, configuration and appropriation processes of smart service providers, we propose a typology of business model structuring (see figure ahead). As a new theoretical insight, we found that the three aspects—service orientation, knowledge base and application of technology—must be analyzed at the individual, organizational and community levels. This approach reveals four stages in business model structuring: the individual or initial business model, the platform business model, scaling digital business models and the innovation ecosystem business model.
Practical value: Industry 4.0 represents a convergence of technology and functionality that facilitates self-organization and the provision of smart products and services, integrating customer information and data across production, distribution and purchasing processes. By analyzing seven cases of smart service providers at various stages of business model structuring, this study offers support for emerging ventures, addressing both the new technologies and the evolving relationships with customers and suppliers necessary for implementing and evolving their business models.
1. Introduction
Industry 4.0, a concept that has emerged in the last decade, reflects the convergence of various trends observed in countries at the forefront of technology, encompassing diverse activities and tools (Lasi et al., 2014), such as cyber-physical systems, artificial intelligence (AI) (Zhong et al., 2017; Wang et al., 2016; Lee et al., 2014), big data and the internet of Things (IoT) (Lee et al., 2017). Together, these emerging technologies provide interconnection and integration of products and processes that generate value not only for companies, but also for consumers and the public sector, primarily through greater productivity, speed and efficiency in decision-making (Frank et al., 2019a). For this reason, Industry 4.0 processes are also referred to as high value-added manufacturing processes (Lee et al., 2017) or high value-added services and products (Wang et al., 2020; Dalenogare et al., 2018).
There has been a revolutionary change in the way services are produced and offered. The new set of services, named smart services, employs Industry 4.0 technologies from process, physical/digital interface, network and data processing perspectives (Frank et al., 2019b). However, Industry 4.0 is still in its infancy, such changes take time to materialize.
As part of an emerging phase in the industry's architecture (Jacobides et al., 2006), smart service providers encounter significant challenges due to the diverse applications and customer relationships associated with Industry 4.0 technologies. These challenges stem from varying levels of digitalization and the complexity inherent in implementing business operations, resulting in diverse business models that target either customers alone or both processes and customers (Frank et al., 2019b).
However, the characteristics of the business models of smart service providers, such as applied technology and customer relationships, are insufficient to fully describe the entire structure necessary for creating, delivering and capturing value, which is the essence of a business model. A business model is the architecture of a firm's mechanisms for creating, delivering and capturing value. In contexts of innovation, it represents the enterprise's solution to the challenges of profitably implementing new technologies (Teece, 2010).
Since we are in the early stages of shaping the industry's architecture, new methods of creating and appropriating value remain open (Jacobides et al., 2006), indicating that business models are not yet well-defined. This is particularly evident in the context of Industry 4.0 in Brazil. Over the last five years, the landscape in the Brazilian industry seems to be still at the initial stage of Industry 4.0, many have not accomplished the transition process through digitization or digital transformation. Research by Project I-2027 (IEL, 2018) revealed that 36.8% of companies in Brazil were in a late stage of automation and 38.8% have only partially installed digital systems (some monitored assembly lines using PCPs, non-integrated management and control modules); thus, 75.6% of Brazilian industry had not fully embraced the Industry 4.0 paradigm or even achieved complete mastery over lean production.
Therefore, the central question driving this research is how smart service providers of Industry 4.0 in Brazil are structuring their business models, and to what extent do they have a well-defined business model?
This article addresses the research question by presenting a dynamic perspective on the value-based strategy approach to business model structuration within the specific context of Industry 4.0. In a seminal article, Brandenburger and Stuart (1996) proposed that the most suitable approach for studying unstructured business situations is the value-based business strategy, wherein firms collaboratively create value with their suppliers and buyers. This stakeholder perspective is particularly useful for understanding value creation and capture within a business model, as it encompasses both internal and external constituents, not merely the consumers and owners (Biloshapka and Osiyevskyy, 2018).
However, this perspective remains static as it does not elucidate the dynamics of value creation, configuration and appropriation, which are essential to the process of business model structuration (Meirelles, 2019). In the specific context of Industry 4.0, the technologies and their applications (Culot et al., 2020; Frank et al., 2019a), particularly in relation to service orientation (Frank et al., 2019b), themselves become the sources of these dynamics. From a theoretical standpoint, the analysis of a business model's structure through the value cycle offers a dynamic perspective that is particularly well-suited to contexts involving shifts in technological paradigms (Meirelles, 2021).
Therefore, the research is guided by three propositions regarding value-based strategies that support business model structuration. Proposition 1: Value-creation strategy is characterized by the way companies use the enabling technologies of Industry 4.0, expressed in terms of their digitalization level and service orientation; Proposition 2: Value configuration is defined by how smart service providers integrate with the Industry 4.0 production chain activities and Proposition 3: Value appropriation is defined as how a company secures an architectural advantage in Industry 4.0 throughout competitive and innovative strategies.
The status or degree of implementation of each value-based strategy defines the extent to which the company has a well-defined business model.
2. Theoretical background
2.1 Technology used in Industry 4.0: scope, functionality and value creation
Industry 4.0 collectively refers to a wide range of concepts without a clear classification. It is a blend of technology and functionality that enables self-organization and the delivery of smart products and services, integrating customer information and data throughout production, distribution and purchasing processes. Therefore, it is referred to as smart manufacturing (Frank et al., 2019a).
Technologies that support Industry 4.0 are AI, the IoT, big data and machine learning. AI refers to human-like intelligence evolved through certain mechanisms or software. It is a rapidly emerging field of engineering and “has many definitions linked to process approaches of thought and reasoning or behavior” (Russel and Norvig, 2013).
According to Frank et al. (2019a), it is possible to visualize the technologies related to smart manufacturing in terms of six main purposes: (1) vertical integration, (2) virtualization, (3) automation, (4) traceability, (5) flexibility and (6) energy management. Vertical integration in Industry 4.0 involves the integration and interoperability of information (Xu et al., 2018) by modern sensors and software for the remote management and planning of industrial processes (Patnaik, 2020). This includes the machine-to-machine communication, an evolution from traditional telemetry (Bali et al., 2022), as well as the entire activities of manufacturing planning, operation and execution systems (Misra et al., 2021). Other functions, such as virtualization, automation and flexibility, primarily involve robotics, AI, 3D design software and 3D printing.
To map the technological components of Industry 4.0, as cited in RAMI (2016), Culot et al. (2020) proposed a classification system based on the prevalence of hardware or software, and the degree of connectivity. The smart service providers employ’s Industry 4.0 technologies from process, physical/digital interface, network and data processing perspectives (Frank et al., 2019b). According to Frank et al. (2019b), there are three service offerings for Industry 4.0: support, adaptation and replacement. Each of these modalities exhibits varying degrees of digitalization and complexity in implementing business operations, resulting in diverse business models targeting either customers alone or both processes and customers. The first group encompasses services with low to moderate degrees of digitization (manual services). The second group comprises services with an elevated level of digitalization, effectively linked to Industry 4.0 and characterized by overly complex business implementation, both from the point of view of technology use and industrial integration.
The various applications of technology combined with different customer relationships and service orientations result in different value-adding. As proposed by Martin et al. (2019), the value delivered includes economic benefits (efficiency, market share and profit), knowledge (market intelligence, innovation and co-development), marketing (fidelity and reputation) and strategy (access, strategic positioning, risk and uncertainty). Together, these aspects result in increased market share, reduction of the innovation period, individualization/customization, product and production flexibility, mitigation of risks and uncertainty, decentralization of the decision-making process and efficiency, which includes both mechanization and automation, as well as digitization and miniaturization (Lasi et al., 2014).
Based on this literature review, we can state that the complete range of enabling technologies employed by smart service providers according to service orientation, as indicated by their degree of digitalization and service customization, creates value (Figure 1). However, this sequence is not enough to comprehend the process itself of business model structuration. As discussed in the following section, from a process perspective of business model structuration, the degree of implementation of the value-based strategy adopted by smart service providers dictates how well-defined their business models become.
2.2 Business model structuration of smart service providers: a proposal based on a dynamic value-based strategy perspective
The business model outlines how the company creates and delivers value to customers, subsequently converting revenue into profit. However, identifying an ideal business model is not an easy task because it is a conceptual and hypothetical framework describing a company’s approach in reaching the market (Teece, 2010).
The value-based strategy approach, as proposed by Brandenburger and Stuart (1996), is the most appropriate method of analyzing developing and implementing a viable business model (Biloshapka and Osiyevskyy, 2018), especially in studying unstructured business situations such as smart service providers in Industry 4.0. From the perspective of value-based business strategy, in such situations, there is an “active search for value creation and appropriation opportunities,” in which the interaction of several players in a cooperative game, including suppliers and buyers at each stage of the chain of activities (Brandenburger and Stuart, 1996).
Business model structuration involves implementing three strategic decisions: value creation, value configuration and value appropriation (Meirelles, 2019). Together, the three processes of value creation, configuration and appropriation comprise a business model that operates in a continuous cycle (Figure 2).
Value creation encompasses the composition of products or services offered, the targeted customer segments and the necessary resources and partners to support the value proposition (Meirelles, 2019). The value proposition requires a thorough understanding of consumers' most pressing problems and needs, such as speed, reliability, accessibility, capacity, status and convenience (Biloshapka and Osiyevskyy, 2018).
In the specific context of smart service providers, all the functionalities of Industry 4.0–enabling technologies previously presented are value-adding, reflecting the qualities perceived by customers in relation to their needs (Bowman and Ambrosini, 2000). The value delivered includes gains and benefits from economic, knowledge, market and strategic perspectives (Martin et al., 2019).
Enabling technologies involve a range of physical and digital processes (such as new materials, 3D printing and advanced robotics solutions), physical and digital interfaces (including IoT, visualization technologies and cyber-physical systems), data processing (big data analytics, modeling and simulation, machine learning and AI) and networks (cloud computing, blockchain technology, interoperability solutions and cybersecurity). These technologies can be applied in various scopes: narrowly through smart service providers, internally within firms or specific departments (such as manufacturing, information or communication) or more broadly by involving network connectivity (products, devices, workstations) or extending to the entire supply chain and business operations (Culot et al., 2020; Frank et al., 2019a).
Therefore, we formally state that:
Value configuration is defined by the organization of value chain activities and decisions regarding the governance structure of assets with suppliers and customers, as well as the internal decisions pertaining to organizational structures (Meirelles, 2019). In the specific context of smart service providers, the broader the integration of technologies related to Industry 4.0, the greater the need to define a governance structure and mechanisms for the internal coordination of organizational structures.
In this transition process toward an interconnected manufacturing, there is an intense process of search and learning in which companies that are engaged with these new technologies require the support of an entire ecosystem of technologies, products and services. In this regard, certain aspects of value configuration in Industry 4.0 can be understood from horizontal integration strategies across the value-creation network, end-to-end engineering throughout the product lifecycle and vertical integration and network manufacturing (Stock and Selinger, 2016, p. 537).
Therefore, the proposition regarding value configuration can be stated as such:
The definition of value configuration strategies affects value appropriation since they allow for efficient and effective performance, particularly in defining organizational limits most suited to protecting innovation from imitation and maximizing results (Teece, 1986). However, smart service providers are part of the architecture of Industry 4.0, which is a typical stage of a new configuration. At this stage, companies can create an architectural advantage, that is they can explore value appropriation without the need to engage in vertical integration (Jacobides et al., 2006).
The profitability of these companies' innovation depends on the creation of an architectural advantage. In other words, the companies must ensure their presence in an articulated network of partnerships that signals sustained future growth. When a company possesses an architectural advantage, it can afford to not worry about protecting or investing in complementary assets. Instead, it can focus on preserving its edge by prioritizing one part of the production process (or assets) while increasing mobility in the other. Thus, the objective of the company is to increase complementarity and mobility in the parts of the value chain where it is inactive (Jacobides et al., 2006).
The value appropriation strategy encompasses not only strategic positioning regarding prices but also innovation and growth from a dynamic perspective of value cycle renewal. An evaluation of strategic positioning directs the future formats of products and processes to satisfy customers’ dynamic expectations of user experience, accompanying the evolution of technology and its own perception of its product or service.
Therefore, we propose that value appropriation is:
This literature review and how it supports the answer to the posited research question can be visualized at Figure 3 (analytical research model. Summarizing, we propose that the value creation of smart service providers is based on the use of enabling technologies related to Industry 4.0 and service orientation. The second proposition concerns value configuration, which is defined as how activities are structured in the value chain and articulated by suppliers and partners. Third, the value appropriation proposition is defined by competitive and innovation strategies to secure architectural advantages in Industry 4.0 (Figure 3).
3. Methodology
This was a qualitative study based on semi-structured interviews, as we aimed to explore the experiences of individuals with specific phenomena, which referred to concrete episodes in particular contexts.
The validation of the research, as proposed by Brinkmann and Kvale (2015), included seven stages: thematizing, designing, interviewing, transcribing, analyzing, validating and reporting (Table 1).
Thematizing concerns the theoretical presuppositions and logical derivations when transitioning from theory to research questions (Brinkmann and Kvale, 2015). In this research, the three propositions (see Figure 3) are related to the dimensions of value creation, configuration and appropriation of the business model structure (Meirelles, 2019), the way these dimensions are presented in Industry 4.0, according to enabling technologies (Culot et al., 2020; Frank et al., 2019a) and the way they are applied by smart service providers according to service orientation (Frank et al., 2019b).
The second stage is designing, which involves planning the interviews (Brinkmann and Kvale, 2015), and consisted of two steps. First, we sought out respondents who were users or developers of enabling technologies related to Industry 4.0, such as AI, the IoT, big data and other disruptive technologies. Based on the website information, we selected 124 potential interviewees.
Second, because the purpose of the survey was to understand the process of business model structuration within the specific context of Industry 4.0, we selected seven cases of business ventures representing different levels of business model development.
As presented in Table 2, these cases be divided into three groups by different phases of business model structuration: (1) academic: companies or innovation and research centers linked to universities (IPFacens and LSI-TEC); (2) startups: technology-based companies originating from the technological needs of clients, be they knew branches of the traditional business of incumbents (Telefonica TEC) or new entrants (SUIV and Infinity) and (3) autonomous service providers whose offerings are related to master’s or doctoral projects (iCubics and StackX).
The interviewers were owners, CEOs, founding partners or directors of technology, mainly comprising engineers with a master’s or doctoral degree, and with extensive experience in the Industry 4.0 market, consulting and projects.
The third stage (interviewing) consisted of a detailed guide that follows the three proposition dimensions of value creation, configuration and appropriation of business model structuration. The pre-categories of the dimensions of value creation included not only the business idea and the main components of value proposition (customer segments, products and services offered), but also resources (enabling technologies and human resources (skills needed) and partners).
The fourth stage (analysis) involved categorizing the interviews. As proposed by Miles et al. (2014), we adopted a bricolage approach for our interview analysis. We used a content analysis technique (Bardin, 2011) to identify categories emerging from the aspects of value creation, configuration and appropriation strategy. The categories that emerged from the research field are described under the research results in the following section (see Tables 4 and 6 next).
In the fifth stage (reliability and validity of interpretations), the interview guide upheld through the construction of a comprehensive research structure encapsulated in detail in Table 3 tie matrix (Telles, 2001), where we present the theoretical foundation of each dimension of value creation, configuration and appropriation, with the description and detailed interview guideline.
Finally, the fifth stage (reporting) is reported here in this paper, as presented in next items.
4. Research results
The value-creation strategies developed by each smart service provider were analyzed based on the following categories: business ideas, customer segments, products and services offered, enabling technologies, human resources (skills needed) and partners.
The companies studied offer solutions related to Industry 4.0. They all utilize and provide Industry 4.0–enabling technologies, primarily focusing on data processing (big data analytics, modeling and simulation, machine learning and AI) and networks (cloud computing and integration/interoperability solutions). The academic institutes are more diversified, offering both hardware and software solutions tailored to client demands (LSI-TEC) or comprehensive technologies and services to Industry 4.0 (IPFacens), such as smart cities, energy efficiency, simulation and virtual labs or fabrics. Some focused on one or two segments, such as agribusiness and tourism (Telefonica-TEC) or automotive (SUIV Infinity), whereas others are more diversified, especially those offering consultancy services (iCubics), training and education (StackX) or gamification and simulation (Infinity).
The services offered, even those by the academic institutes, are mainly customer-process-oriented, because they were created to develop market-adapted technologies. Therefore, most benefits to clients relate to efficiency through digital transformation and connectivity through system integration.
As the interviewee representing SUIV declared, “digitization is not a desire anymore but a survival.” As a first step, clients want to know more about their own databases. As they encounter new issues, new solutions are explored, eventually resulting in complete process automatization to provide a better service experience.
As argued by the interviewee representing Infinity, only clients with technology maturity (according to ACATECH classification) demand a more homogeneous system/process integration. Some customers still experience gaps in industrial connectivity, and their main demand is integration with their old-fashioned machinery. As stated by the interviewee representing StackX, “only 2% of Brazilian industry are from the second generation of Industry 4.0.” Moreover, as the interviewees from IPFacens pointed out, “most companies still do not know where they are in relation to Industry 4.0. They demand consultancy to understand at what level they are and only after updating, promote any kind of change.”
Human resources, together with partners, are based on skills and technology that support the development of smart services related to Industry 4.0, such as engineering, data processing and mathematics. However, business and strategy skills were also identified as relevant, including expertise in economics, to develop games (Infinity). All cases are based on partnerships, including innovation centers, such as CPS abilities and automation know-how (LSI-TEC) (See Table 4).
From the perspective of value configuration (Table 5), the following categories were analyzed: primary and support activities of the value chain, organizational structure and service coordination (governance structure, integration with clients, feedback and follow-up).
All cases promote the interactive development of chain activities involving both suppliers and buyers. The two academic institutes, IPFacens and LSI-TEC, originated from the business idea of “connection with the market,” and as such, all their projects are customer-oriented but on a B2B basis.
Chain activities involve identifying customer needs, and ways to better apply technology. It is a typical innovation management process that begins with consultation to identify problems rather than the development of the product, review (prototype evaluation) delivery or follow-up (client satisfaction and new improvement possibilities).
Most cases seek partnerships to complement their expertise and enhance their capacity to offer more advanced services, whether in response to new demands that are beyond the scope of the service offered or to complement workers’ skills, such as the IoT and AI. Except for the Unified Vehicle Information System (SUIV), which performs the service by itself, and Infinity, which tends to verticalize, all other companies frequently seek partnerships.
The organizational structure at Telefonica TEC is more formalized through partnership contracts coordinated by headquarters. Others adopt a project-based structure primarily with an operational function, some with a shared service center (IPFacens) or some centralized functions, especially marketing, finance and contracts. Considering the diversity of potential projects and the size of the client portfolio, most of them have support areas for marketing and finance/contracts. When monitoring supplier quality and internal processes, as well as information about partners, an informal process usually prevails, with companies focusing on customer feedback. None of the companies have inventories or receivables. They do not possess information about inventories and receivables, supplier quality and service improvement.
Service coordination relies on contracts, whereas delivery is based on technologies that support integration through API interfaces that connect the smart service provider with the customers' platforms. Some of the companies offer a total digital base (StackX). Companies such as SUIV see the potential for achieving absolute customer integration through cloud computing and big data investments, supported by AI, to expand their services beyond a single platform.
Finally, value appropriation (Table 6) was analyzed using the following categories: competition, pricing and profit, growth (new technologies and markets/potential clients), innovation and patents.
The academic institutions do not have direct competitors. Others faced a more competitive environment, particularly smaller service providers (iCubics and StackX).
The price is determined by a project or contracted module, typically measured in man-hours. The companies LSI-TEC, IPFacens and TelefonicaTEC focus on costs, StackX focuses on the customer's perception and the other companies prioritize hours worked on each project.
Most companies report high growth rates while also seeking opportunities in new potential markets. The growth rate of SUIV is approximately 150%, and that of iCubics is 10%, whereas at the other extreme, that of TelefonicaTEC, the youngest company, is between 18 and 25%. The others report an average growth of 30–50%. LSI-TEC is waiting for the market reaction, and all claim to have faced difficulties during the pandemic period. Nonetheless, they reinvest their profits.
A variety of options exist for potential customers as well as ways to explore new technologies in emerging markets, with the exception of SUIV, which operates in a niche market where the market owns it and offers the platform.
Regarding innovation, most companies do not generate patents, owning only their brand or solution. Only IPFacen, which has a patent office, and TelefonicaTEC, which directs patent considerations to ANATEL are open to any opportunity, whereas others have voluntarily or involuntarily did so in their past.
5. Discussion
The research question posed was: how do smart service providers structure their business models, and to what extent do they have a well-defined business model? The research is posited on two guiding premises (see Figure 3). The first one is that the process of business model structuration relies on a value-based strategy adopted by smart service providers. The second is that the degree of implementation of these strategies dictating how well-defined their business models become.
The process of business model structuration was defined here as following the dimensions of value creation, configuration and appropriation (Meirelles, 2019). Regarding value creation, we propose that the potential for value creation is determined by the degree of use of Industry 4.0-enabling technologies (Culot et al., 2020); the extent of their application in partnerships and customer relationships, ranging from a narrow internal company application to the extended network of suppliers (Frank et al., 2019a) and the degree of digitization and customization (Frank et al., 2019b).
We proposed defining the value configuration process based on how smart service providers align with the activities of the production chain of Industry 4.0. The integration of different enabling technologies begins with data collection by sensors. These data are stored in the cloud and, through big data and data mining tools, are processed as information that is fed to service projects by providers through AI and machine learning solutions.
Finally, we proposed that value appropriation is defined by architectural advantage in Industry 4.0. The studied companies usually formed partnerships to secure support for meeting specific demands and enhancing product value, in addition to composing the product/service mix, as presented in the servitization approaches.
From the result obtained in the research we added the knowledge base (human resources and skills) and how this extends from individual to organization and community.
Value is co-created within the context of smart service providers. Manufacturing firms, together with knowledge-intensive business services (Kohtamaki and Partanen, 2016), explore a new set of products related to servitization processes (Martin et al., 2019). But this interaction goes beyond firms, encompassing the whole innovation ecosystem, especially in the case of academic institutes.
As proposed by Bowman and Ambrosini (2000), the process of value creation consists of producing new use value by combining acquired use value with (entrepreneurial) labor. However, from the perspective of collaboration proposed by value-based strategy approach, technological resources, acting as enabling technologies for Industry 4.0, are harnessed by people within organizations or communities, as well as by independent entrepreneurs.
The inclusion of these three analytical levels (individual, organization and community) is crucial to validate the second premise. As shown in Figure 4, the degree to which smart service providers use and apply enabling technologies defines a sequence of stages in business model structuration. In the first stage (individual or initial business model), albeit with high skilling of owners, only manual or adaptation services are offered. The enabling technologies primarily consist of data processing and connectivity, leading to limited application of technology to chain activities within the company.
In the second stage (platform business model), although services offered are oriented toward the entire process automatization of the client (Factory integrated), technologies are restricted to the client company (or even one department) and these clients' needs are mainly data processing and connectivity.
In the third stage (scaling digital business model), although the services offered are oriented toward greater digitalization through an entire array of field devices connected to the internet (IoT) and organized in a more formalized structure, the business model is still being constructed, companies in this stage are mainly startups.
In the fourth stage (innovation ecosystem business model), the entire manufacturing process is digitized, with integration and network connectivity, both between service providers and the extended supply chain of their clients, and new technologies are customized and developed through the interaction of a whole innovation ecosystem.
The inclusion of these three analytical levels—individual, organizational and community—provides a novel perspective on the potential and limitations of the processes of value creation, configuration and appropriation. Technological resources are harnessed by individuals both within and outside organizations, encompassing the entire community of customers and partners.
The greater the number of participants in the knowledge base, such as the academic centers presented here (group A), the higher the potential for value creation. However, this alone is insufficient to define a well-structured business model, as it remains a company incubated within an academic setting. Companies linked to research and protected by academic institutions possess greater production potential and the capacity to pursue more complex and profitable projects, thus creating jobs within their own structures. Science and technology institutes, such as IPFacens, also belong to this group, serving as gateways to the high-tech market and ultimately seeding new startups created by their graduates. However, these institutions are not fully exploiting the potential of value appropriation necessary to support this growth.
Companies in the middle ground (group B) have more promising business models as they are already well-established entities seeking greater scalability. This may be achieved through exploring business opportunities via partnerships, as exemplified by Infinity, or through integrating with their customers by utilizing cloud computing and investing in big data, supported by AI, thus expanding their services beyond mere platform offerings, as seen with SUIV.
Companies such as iCubics emerge from master's or doctoral projects, recognizing the opportunity to be part of the Industry 4.0 wave. These startups view IoT as an efficient tool for new projects. Companies like StackX position themselves between existing intellectual capital and the substantial need for specialized labor in Industry 4.0–enabling technologies, thereby reorienting their technical training at various levels to align with market demands.
Therefore, based on these new findings, the previous propositions value-based strategies that support business model structuration, should be improved as follows:
Proposition 1: Value-creation strategy is characterized by the way companies, together with customers and partners, use technological resources.
1.1 The greater the intensity of use of Industry 4.0-enabling technologies, the higher the potential for value creation.
1.2 The greater the network connectivity, the higher the potential for value creation
1.3 The greater the degree of digitization and customization, the higher the potential for value creation
1.4 The greater the number of participants in the knowledge base, the higher the potential for value creation.
Proposition 2: Value configuration is defined by how smart service providers integrate with the Industry 4.0 production chain activities.
6. Conclusions
Using a dynamic value-based strategy approach to analyze business model structuration, this study maps the different stages of business models of smart service providers. The study advances theoretically by proposing a typology of business model structuration stages, encompassing four dimensions: (1) the degree of use of Industry 4.0-enabling technologies; (2) the degree of digitization and customization; (3) the extent of their application in partnerships and customer relationships, ranging from narrow internal company application to extended networks of suppliers; (4) the knowledge base (human resources and skills) and how this extends from the individual to the organization and community.
By assessing the seven cases of smart service providers studied, these four dimensions elucidate the different stages of their business model structuration. In the initial stage (individual or initial business model), despite the high skill levels of the owners, only manual or adaptive services are offered. In the second stage (platform business model), services are oriented toward the complete automation of the client's processes (Factory integrated), yet the technologies are restricted to the client company (or even a single department), with clients' needs primarily focused on data processing and connectivity. In the third stage (scaling digital business model), services are oriented toward greater digitalization through an array of field devices connected to the internet (IoT) and organized in a more formalized structure, though the business model is still under construction; companies in this stage are predominantly startups. In the fourth stage (innovation ecosystem business model), the entire manufacturing process is digitized, with integration and network connectivity between service providers and the extended supply chain of their clients, and new technologies are customized and developed through the interaction of an entire innovation ecosystem.
This typology offers both theoretical and practical contributions. Theoretically, it enhances the understanding of business model structuration stages. Practically, it aids managers in identifying the current stage of their company's business model structuration and provides guidance on how to advance. It is important to note that the business models of the smart service providers examined in this study are still evolving. Even companies such as technological institutes, which have achieved a high stage of value creation, have the potential to grow through more complex and profitable projects, thereby creating jobs within their own structures.
Regarding the specificities of Brazilian context, the main finding is that many of the disruptive technologies are still maturing at universities through innovative research centers or post-graduate programs, with the knowledge base ranging from business owners or a small group of specialists to a whole community of researchers. Field research suggests that service providers are striving to offer a high value-added service tailored to their client's process or product. They are actively seeking a business model that better accommodates market complexities and the diverse disruptive technologies, dynamically integrated with AI, the IoT and big data. However, clients are still becoming aware of the value added by Industry 4.0.
Figure 1
Use of Industry 4.0-enabling technologies by smart service providers: application, service orientation and value added
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Figure 2
Value cycle of smart services’ business model structuration
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Figure 3
Analytical research model: research question, premises and propositions
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Figure 4
Business model structuration of smart service providers: a proposal typology
[Figure omitted. See PDF]
Table 1
Seven stages of research validation
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Source(s): Authors’ own work based on Brinkmann and Kvale (2015)
Table 2
Profile of smart service providers interviewed
| Group | Company | Services | Total employees | Annual revenue | Number of clients | Age |
|---|---|---|---|---|---|---|
| Academic Research Lab/Innovation Centers | IPFacens | R&D service (innovation centers and labs focused on solutions and technologies related to Industry 4.0) | 500 | 25 million | 550 | 45 years |
| LSI-TEC | Lab for technology services | 15 | – | 5 | 23 years | |
| Startups (technology-based companies) | Telefônica TEC | IoT and big data to agribusiness sector (solutions to equipment, soil, clime, irrigation and transport) | 27 | 2 million | 11 | 10 months |
| Infinity | Modeling and simulation | 10 (Brazil) | 2 and a half million to 3 million | 20–25 | 5 years | |
| SUIV | Autotech (smart register) | 9 | 3.2 million | 22 | 6 years | |
| Service Providers | StackX | Consultancy and training in Industry 4.0 (inspired by the Lambda School) | 19 | 500 thousand | 250 | 2 years |
| iCubics | Consultancy in smart cities, health and environment, residential automation and IoT (sensors to collect information and monitoring) | 1 | 1 million | 4 | 2 years |
Source(s): Authors’ own work based on the research data
Table 3
Theoretical foundations of value creation, configuration and appropriation dimensions and guide interview
| Dimensions | Theoretical foundation | Guide interview |
|---|---|---|
| Value creation | Lasi et al. (2014), Biloshapka and Osiyevskyy (2018), Frank et al. (2019a), Culot et al. (2020), Meirelles (2019), Teece (2010) |
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| Value configuration | Meirelles (2019), Teece (2010), Frank et al. (2019b) |
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| Value appropriation | Jacobides et al. (2006), Meirelles (2019), Teece (1986) |
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Source(s): Authors’ own work
Table 4
Dimensions of value creation of smart service providers’ business model
| Dimensions | IPFacens | LSI-TEC | Telefonica TEC | Infinity | SUIV | StackX | ICubics |
|---|---|---|---|---|---|---|---|
| Business idea | Innovation center focused on technological solutions to market application of local industry and also improve students to help with their education/graduation | Technology lab focused on the interface with the market | Telecommunications using IoT and big data | Customization of business processes based on a methodology of integrated simulation (systems with several vectors in a single model) - Digital Gemini and Metaverse technology | Vehicle data processing (match parts in car maintenance) | Customized service training to Industry 4.0 | Digital transformation and development of sensors for data collection and monitoring |
| Clients/Segments | Local industry | Diverse segments | Agribusiness, mining and services (hotels and tourism) | Automotive (60%) and others (domestic appliances, naval and food) | Automotive industry (distributors, car maintenance, rental companies) | Big companies hiring technology | Health industry (smart watch) and smart cities |
| Services/Products | 8 technological centers providing services of gamification (virtual and augmented reality), online sensors and monitoring (IoT), energy efficiency and prototype development (FabLab) | Software, hardware and firmware projects | Smart solutions (transport and soil management) | Digitalization (LaserScan), modeling and simulation (virtual fab) | Process robotization through big data and API integration with the client system | Training (high school, corporate executives and entrepreneurs)/skill development | - Smart cities (emissions and waste) |
| Benefits | Technological solutions related to Industry 4.0: digitization, virtual reality and scenarios of training, monitoring and communication | Connectivity (different methods and approaches) and monitoring through big data | Economic efficiency. Digitization and innovation | Integration of systems related to Industry 4.0 (homogeneous and assertive business process) | Assertive information and a clean database for better management of vehicles | Integration and connectivity to real-time management transactions; Industry 4.0 tools: Product Data Management (PDM) and Product Lifecycle Management (PLM) | Cost reduction and efficiency in process analysis (problem identification and evaluation) and quality control; connectivity; smart capture and use of data for decision-making |
| Enabling technologies | IoT, sensor development and monitoring, software development, augmented reality, virtual reality, deep learning, big data and AI | Platform and other tools of Industry 4.0: microcontrollers and microprocessing; cloud computing | Machine learning, big data, sensors | Gamification and all technology resources (digital interface, sensor, cloud computing, big data, AI) | Big data and cloud computing to clients (API interface) | Web platform (100% digital) and interface tools | Sensorizing (IoT), computational vision, analytical resources of AI |
| Human resources and skills | - Product Development: Specialists/Tutors (with engineering, data processing and math degrees), with support of students (1st–3d year of college); business skills: focus on client pains | Master’s and PhD in computing science and engineering (web programming and database skills) | Engineers (electric with production profile) | Digital game experience and engineering. Age Profile: Young people (18–30 years old), with or without college degree and elderly (>55 years) | Technology and data development (five resources) | Master’s- and PhD-holding professors with eclectic skills (business, management, engineering, software and consultancy) | Electrical engineers with master’s degree in business; experience as a project manager in international companies |
| Partners | More than 550 partner companies (private, government and educational institutions) | Manufacturing, hardware and cloud computing | Connectivity equipment and startups searching for scaling | Hardware suppliers (notebooks and supplements) and specialists in strategy | Automobile supply chain and startups | Industry 4.0 specialists (IoT and software)/finance (billing/contracts) | Small service companies (software development); sensors and electronics manufacturers; data centers and AI |
Source(s): Authors’ own work based on the research data
Table 5
Dimensions of value configuration of smart service providers’ business model
| Dimensions | IPFacens | LSI-TEC | Telefônica TEC | Infinity | SUIV | StackX | ICubics |
|---|---|---|---|---|---|---|---|
| Primary value chain activities | (1) Sales funnel (loyal companies and market intelligence for search and prospecting). (2) Mapping the client’s needs (consulting, explaining the potential, mapping the pain), (3) Passing on the requirements to make a Proposal. (4) Proposal analyzed. (5) Solution production cycle (targeted at innovation centers). Coordination of the PMO with accompanying software. (6) Development looping until the final product. (7) technology transfer (adaptation and training period, warranty and support) (8) Finally after-sales (feedback) | (1) Client Prospection and or institutional channel (website). (2) Evaluation of clients’ needs and adequacy to platform (hardware, software, firmware). (3) Project development and contract signature (financial resources) to use the platform | (1) Sales: maps the need with the customer and brings it to the product area; (2) Products: talks and interacts with the customer to understand the need. (3) Engineering: technical design of the solution. (4) Presentation of the solution, price and deadline proposal, followed by recalibration; (5) Implementation (Delivery): monitor the customer's delivery with the technical area to guarantee deadline and budget (PMO). (6) Delivery of the final product and validation: customer tests the product and pays | (1) Ground Digitalization by Laser Scan (2) Modeling Process by CAD. (3) Game Platform (animation and rendering). (4) Connection with industrial scope. (5) Virtual Commissioning | Access to the customer catalog system, information via PDF, information outside the country | Activity flow is dynamic (it changes according to market needs) | First: initial analysis of the process (understanding current state). Assessment (understanding the type of problem: customer pain, proposing an improvement solution, using technology elements: monitoring and collected data, which are transformed into information for decision making) |
| Support activities | Shared Services (HR, Financial IT and Marketing). Not subordinate to the Research Institute, but providing support to it and to the academic, across the board | General Management and Finance | Support Activities are very important (contracts and marketing) | Marketing and Infrastructure (General Management and Finance) are all in-house | -Technical areas (solving doubts and providing information to clients) | Finance department already structured (billing and banking), marketing and social media channel. Centralized entry and communication platform (administrative, user support and academic area) | Prospecting for new business and evaluating and delivering projects. Financial part with the accountant. Activity concentrated in operations and IT |
| Organizational structure | Executive director, a CEO and three verticals: commercial (director of new business, relationship with companies and sales team); Operations Directorate (eight development centers) and Smart Services Directorate (sensing and governance) | Divisional Structure/Independent Business Units with some shared activities (certification, test and adequacy) | 1 Director of operations (coordination) and 5 senior managers (pre-sales, business development, products, after-sales/implementation/delivery) and Human Resources (finance, marketing and contract/law) | Horizontal structure (100%), all members deal with the whole process (from beginning to end) - a mixed method adapted from market insights | Co-founding partner: Database (Systemization, technical support), Technology partner (development of internal architectural applications, customer customizations and infrastructure), Support activities partner: financial, administrative, accounting, legal, business -business and strategies, partnership, sales | Three divisions: CEO who responds to the market (technological innovation, investor relations); CEO who takes care of internal operations (process issues, business rules and internal decision making) and marketing director | Outsourced financial or administrative support. Marketing and Sales (own work), Operational part (network to search for companies and engineers for hardware and software development) |
| Service coordination (governance and integration with client) | Co-creation process with suppliers and clients; consultancy to identify problems than development of the product, reviews (prototype evaluation) delivery and follow-up (client satisfaction and new improvement possibilities) | Customer is the manufacturer; the company only offers the software/hardware development and monitoring (user policies) | Customer process development (in-house); Cloud Computing and Platform Support (external suppliers | Software Activities Vertically Integrated (in-house); Hardware all bought in the market. | Autonomous development and APIs customization based on client's workflow (database integration regarding vehicle acquisition, renting and maintenance) | Digital platform | Yes, it normally occurs in the area of sensors (Partner in the USA and local company). Individual company that uses a network of contacts (startups). From the service contract, personal management |
Source(s): Authors’ own work based on the research data
Table 6
Dimensions of value appropriation of smart service providers’ business model
| Dimensions | IPFacens | LSI-TEC | Telefônica TEC | Infinity | SUIV | StackX | ICubics |
|---|---|---|---|---|---|---|---|
| Competition | No direct competition - only ICTs that accomplish the same job (university–market interface) | No direct competition - only ICTs that accomplish the same job (university–market interface) | Telecommunications companies | Digitization companies (SIEMENS) | Database systems companies (that sell login and password but not integration) | Companies with greater financial volume with the Lambda School model that operate in a higher social class, outside of social entrepreneurship | Small consultancies and professionals with experience in projects to improve industrial processes and integrate intelligent systems |
| Pricing and profit | Based on the value of man/hour, with the profit reinvested in the business | Based on the value of man/hour, with the profit reinvested in infrastructure | Pricing based on costs. Profits are coordinated by the company VIVO | Based on hours and square meters worked. Profits divided between the two partners | Contracted module versus request volume on the platform. The client says, “I want this information,” and I'm going to call you five thousand, ten thousand times. It is a recurring recipe. Today, 85% of our revenue volume is recurring. And as we are integrated into the system of a client of ours, our TR is zero, from the first time … in fact, we lost a client, because it went bankrupt during the pandemic. It was a client that we lost, because everyone else has been with us since the beginning. And profit distribution, we haven't had distribution yet. Everything that comes in we invest, everything that comes in we invest, we are in the survival kit there | Pricing based on customers’ perception of value. Profit distributed to shareholders | Per hour/consultancy, possibly including a portion of the unit manufactured or project sold. Profit belongs to the sole owner of the company |
| Growth and perspectives (new technologies and markets/potential clients) | Growth of 50% per year. The academic area has existed for 45 years; however, the research institute was created in 2003. It frequently seeks partners for new technologies and through a recently created technological innovation center. Each of the eight technology centers has the freedom to prospect the market and see which are the most recent technologies or those that can give better results | Growth decreased during the pandemic and remains stable, awaiting market reaction. It makes the connection between the high technology developed by USP and the needs of the market. It evolves its activities to serve a platform as a service to customers | Since 2018, it has grown by around 18%. There is a constant search to scale the needs of agribusiness customers, through the work of business developer manager-BDI and market forums, seeking customers who already use the VIVO company infrastructure | From 2021 to 2022, it maintained a growth rate of 75%; however, the normal average would be 35%. It seeks to have the widest range of deliverables possible and to be the most flexible and quickest in service. It seeks to focus on companies’ headquarters and customers’ logistics chains | It grew at a rate of 50% before the pandemic, 20% during it and is expected to reach up to 150% after. Searches for new technologies in the automotive database market and intends to work in agribusiness | 30% growth rate. They follow the evolution of the market's technological needs and seek to expand their training market in Industry 4.0 tools | It doubled its revenue in two years and expects to double it every year, seeking to grow beyond an individual company. It seeks to monitor the evolution of customers' needs for disruptive technologies in the areas of industry, healthcare and smart cities. It has no intention of entering agribusiness |
| Innovation/Patents | Within its technological information center, it has a patent office, working with development partner companies | It has a department that can be called upon request to verify and register a patent | Its telecommunications patents go through ANATEL | Development of a single architecture database and IT routine to client's system integration (including historical archive) | They have a trademark registration but no patent office. When necessary, they hire specialized offices | They prioritize the registration of the brand; however, they have plans for future patent registration | It complies with confidentiality agreements; however, the patent belongs to the client |
Source(s): Authors’ own work based on the research data
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