Guest editorial

Citation

Eloranta, V. and Turunen, T. (2018), "Guest editorial", Journal of Business & Industrial Marketing, Vol. 33 No. 6, pp. 745-748. https://doi.org/10.1108/JBIM-07-2018-325

Internet of Things – Driven B2B service networks

Digitalization and Internet of Things as change drivers in firm networks

The digitalization of products, services and processes is a prevailing trend across nearly all industries (Brynjolfsson and McAfee, 2011). One key area of interest in digitalization seems to be evolving around the concept of Internet of Things (IoT) (Atzori et al., 2010; Porter and Heppelmann, 2014). IoT is defined as “a global infrastructure for the information society, enabling advanced services by interconnecting (physical and virtual) things based on existing and evolving interoperable information and communication technologies” (ITU-T, 2012, p. 7).

In practice, IoT refers to a widespread propagation of communications technology such as RFID tags or embedded sensors (Atzori et al., 2010; Gubbi et al., 2013; Mashal et al., 2015). Through these technologies, physical objects, such as machines, devices and materials, can communicate with each other and cooperate to reach common goals (Atzori et al., 2010). Connecting objects and orchestrating collaboration between them are often done with different kinds of platforms, ranging from digital infrastructures (Tilson et al., 2010) to socio-technical institutions (meta-organizations and ecosystems) (Eloranta et al., 2016; Gawer, 2014; Thomas et al., 2014).

IoT-driven digital business systems can be argued to have a disruptive effect on business models, organizational structures and competence requirements (Atzori et al., 2010; Barua and Mukhopadhyay, 2000; Kettinger et al., 1994). In digital infrastructures and platforms, actors across organizations are enabled to interact efficiently, especially in terms of resource discovery, exchange and reconfiguration (Gawer, 2014; Tilson et al., 2010). This implies that diversifying customer needs, changing power structures of complex inter-firm networks, and the constant need to seek new business opportunities have become the prevailing state of many companies (D’Aveni et al., 2010; Wiggins and Ruefli, 2005).

The focus area of this special issue: Internet of Things and the networked service business

In the B2B services business, IoT developments are perceived to lead to increased market complexity due to vertical and horizontal integration (Kagermann et al., 2013). IoT increases the availability of data and opens up opportunities for process optimization, collaborative value creation, business model innovation and consequently the restructuring of existing industries. New value network participants, especially from the software industry, are constantly entering the market (McAfee and Brynjolfsson, 2012; Yang et al., 2009). These changes lead to the blurring of product and industry boundaries. The traditional service provider–client interface is also being reshaped (Porter and Heppelmann, 2014).

This special issue aims to contribute to the service management literature and management practice in several important areas. The themes addressed in the articles in this issue include:

• IoT-driven service business models;

• IoT-enabled service network orchestration;

• the special role of information in the IoT services business; and

• the changes driven by IoT in firms’ capability requirements.

Most of the articles gather their empirical evidence from large organizations providing manufacturing solutions and industrial services. One article also complements the incumbent perspective with data from high-growth software companies.

The articles in this special issue

The special issue opens with an article on the business model implications of IoT. In their article “The Future of the Internet of Things: Towards Heterarchical Ecosystems and Service Business Models,” Leminen, Rajahonka, Westerlund and Wendelin examine the emergence and types of business models in the IoT ecosystems. Their study provides three theoretical contributions to the discussions of business models and ecosystems and puts forward the concept of “value design” as a business model in the ecosystem context. First, the paper introduces a conceptual framework for classifying IoT business models. Second, the conceptual framework distinguishes four IoT business models based on the type of ecosystem and the nature of services involved:

• value chain efficiency;

• industry collaboration;

• horizontal market; and

• platform.

The study applies qualitative research methods to analyze seven industry cases. Third, the study discusses three evolutionary paths for the emergence of new business models:

• opening up the ecosystem for industry collaboration;

• replicating the solution in multiple services; and

• returning to a closed ecosystem as technology matures.

Ultimately, the article identifies four archetypical IoT business models based on a novel framework that is independent of any specific industry. It argues that IoT business models follow an evolutionary path from closed to open and, reversely, from open to closed ecosystems and that the value created in the networks of organizations and things will be shareable value rather than exchange value.

The second article of the issue, by Löfberg and Åkesson, focuses on using platforms in the orchestration of the IoT services business. Along with being a specific type of business model, as Leminen et al. state, platforms have been identified to play a significant role as an ecosystem-level organization structure (Gawer, 2014). Löfberg and Åkesson develop the knowledge on platforms in the services business further and clarify the definition of a service platform in an industrial context. To do so, an understanding of the foundations for platforms, which is based on a service perspective, is created. Having performed a qualitative case study with remote service teams in two multinational firms, the authors argue that the foundations for successful service platforms consist of modularizing resources, integrations, and service processes to create value propositions. The value propositions could result in variations of a service or of different services. Building on these foundations, the service perspective is made evident in the authors’ new definition of a service platform: value proposition (s) consisting of a modular structure that invites and facilitates value co-creation between resources through integration opportunities in a continuous service process. The study offers empirical contributions on platforms from a service perspective. In terms of theory, the study contributes to servitization, service modularity and service (dominant) logic research.

In the third article by Osmonbekov and Johnston, the domain of IoT and service networks is further addressed under the topic of “Adoption of The Internet of Things Technologies in Business Procurement: Impact on Organizational Buying Behavior.” The conceptual paper touches specifically on the area of business to business procurement. Specific propositions regarding buying situations and increased machine-to-machine interactions are developed. The impacts on the buying center structure, including size, participation and the hierarchical level, are also explored: buying center processes such as coordination and conflict are argued to be affected. As a result of these changes, the authors predict that business procurement may become more effective and efficient. However, security and privacy issues will have to be addressed from many new perspectives.

It seems that one of the most essential change processes driven by digitalization and IoT is that the role of information has become more prevalent in the respective companies’ business models (Porter and Heppelmann, 2014). The fourth article of the special issue, by Momeni and Martinsuo, focuses on the pivotal role of information in industrial IoT networks. In their article “Remote Monitoring in Industrial Services: Need-to-have Instead of Nice-to-have,” the authors address the issue of creating business value through advanced IT technologies. Based on the issues identified in relation to relationship-based customer information channels, the authors highlight the need for advanced technologies, such as remote monitoring systems (RMS), in enabling manufacturing firms to complement their knowledge about their customers and improve service efficiency through improved knowledge access, the removal of physical distances and better validity and quality of data. The empirical findings from six engineering companies show that successful adoption of RMS in manufacturing firms’ service business comprises business-related factors that can enhance or restrict the use of technology in these companies. The paper highlights possible broader applications of RMS in a manufacturing firm’s business, in customer relationship management, marketing, product and service development and the customization process. The authors argue that manufacturers cannot succeed in enhancing the adoption of RMS with a sole focus on technical enablers; they should use the collected data and convert it into business values for their business processes.

Emphasizing data gathering and utilization in IoT business models, however, increases the perceived risks of IoT technology adoption among those from whom data is collected. Jayashankar, Nilakanta, Johnston, Pushpinder and Burres address this issue in their study, which was conducted in the smart agriculture context. Despite the obvious economic and environmental benefits of IoT technology, farmers and policy makers are expressing legal and ethical concerns about the rise in information asymmetry, as well as the lack of privacy of farm-level data in the digital agriculture market, in which agriculture technology providers have become dominant players. Therefore, the authors of this study determine how perceived value and risk impact farmers’ adoption of IoT technology and also how trust can affect perceived risk. The authors draw on different elements of the value-based adoption model, the technology acceptance model and service-dominant logic to develop their research design. The study participants include 492 US farmers, and the results are analyzed through a structural equation model. The authors find a positive relationship between trust and perceived value and a negative relationship between trust and perceived risk. There is also a positive impact of perceived value on IoT adoption as well as a negative impact of perceived risk on IoT adoption. In this article, the authors contribute to a richer conceptualization of IoT functions, as they discover that perceived economic, green and epistemic value attract farmers to IoT technology.

Increasing levels of information-intensivity also affect the capability requirements of industry players. The article authored by Hasselblatt, Huikkola, Nickell and Kohtamäki forms a holistic framework for those capabilities in an industrial services context. The authors study six large manufacturing companies and identify five capabilities that industrial companies need to possess to be able to offer IoT solutions to their customers:

1. the capability of developing a digital business model;

2. the capability to build a scalable solution platform;

3. the capability to sell IoT value;

4. the capability to deliver IoT value; and

5. business intelligence (BI) and measurement capability.

The main outcome of the study, a theoretical model, identifies the key resources, processes and competencies under the identified capabilities. Together with key strategic business processes (value identification, quantification, communication and verification) and the identified IoT-enabling capabilities, manufacturers can offer preventive and optimized maintenance, increase product safety, reduce operation costs and gather information for solution development. The study contributes to the servitization literature by defining a capability combination that enables manufacturers to develop, build, sell and deliver IoT-enabled solutions.

Information resources have also grown to have significant strategic relevance. In an industrial services setting, the role of information has so far mainly been seen as a resource to be protected (Eloranta and Turunen, 2015). However, it could be argued that disruptive IoT-driven changes in industries might make it challenging to implement the resource protection approach (D’Aveni et al., 2010). This dissent is addressed by Turunen, Eloranta and Hakanen in the seventh article of this special issue. The connection between manufacturers’ servitization and the management strategy literature is used in the analysis. To avoid the possible path-dependency biases with regard to the existing position and resource leverage in the case of incumbent firms, the authors focus on new entrants to the industrial services market. The study explores how new entrants in the industrial services industry view the strategic role of information. The results of the study provide new insights into both the characteristics and boundary conditions of the new entrant approaches to strategically benefiting from information resources. Instead of aiming to possess and control data, the case companies:

• prefer access to large data volumes over exclusive access;

• render the question of data ownership to be largely irrelevant; and

• perceive that the strategic relevance of information lies in novel data combinations.

The study makes a contribution by providing a contemporary perspective on the prevailing information resource protection doctrine in the context of industrial services. Most importantly, the results challenge the hitherto unquestionable strategic relevance of customer relationships in the industrial services business.

All in all, leveraging IoT is not straightforward for organizations. The literature has so far identified several challenges, but a holistic view has been lacking. In the eighth paper of this issue, Klein, Biehl and Friedli identify and investigate barriers to smart services in the capital goods industry under the topic “Barriers to Smart Services for Manufacturing Companies: An Exploratory Study in the Capital Goods Industry.” In their multi-methodological paper, the authors especially focus on non-technical barriers. In addition to reviewing the existing research, qualitative interviews and workshops with 14 experts from five companies were used in the barrier identification process, resulting in a detailed list of 25 barriers that showcase the significance of each on smart services. The authors argue that both specific barriers to smart services and barriers that can be attributed to servitized companies in general have to be considered because of the relationships between them. Besides identifying the barriers, the authors also identify latent factors behind the barriers with an explorative factor analysis, which used a data set from a large-scale quantitative survey, as well as an assessment of the impact of the barriers on business performance. Based on the analysis, the authors conclude that all the surveyed barriers are impactful, but that the rationale behind the barriers varies. Thus, the study provides a way of classifying the barriers in developing and implementing smart services as well as some practical guidelines to address the barriers.

IoT has hitherto been elaborated mainly in the context of intelligent machinery and smart products. The final article of the special issue aims to extend the concept further. In their viewpoint article “Material Intelligence as a Driver for Value Creation in IoT-enabled Business Ecosystems,” Hakanen and Rajala discuss the possibilities and outcomes of managing information from material objects using Internet of Things technologies. The paper extends the current IoT and smart products discussion by presenting the concept of intelligent materials, which broadens the scope of items that are considered suitable to the IoT discourse. In particular, the authors describe how intelligent materials increase the potential for collective value creation among the firms in diverse business ecosystems. By re-analyzing the data from their prior empirical study, the authors present five key insights to guide further research in this area. First, they explain that questions in relation to collecting, storing, and sharing information need to be resolved so as to foster collaborative value creation and sharing mechanisms in ecosystems. Second, the authors allude to areas in which further research is needed to determine how companies can motivate their participation in information sharing and to initiate necessary actions within their business ecosystems. Third, the authors outline the benefits associated with collaborative value creation and call for more research to provide evidence of the competitive advantages associated with mastering material intelligence. Fourth, the authors suggest work for determining the barriers affecting the entry choices of companies in creating different information sharing systems such as material intelligence. Finally, the authors emphasize the importance of analyzing business risks and economic performance related to IoT systems to vindicate their existence. The insights reported in the paper are targeted at resolving current unknowns that hinder the development of information sharing systems in collaborative value creation. In conclusion, the study postulates that these systems are in demand, and as with IoT, competition does not occur only among companies but also, increasingly, between ecosystems.

Conclusion

Altogether, the nine articles selected for this special issue represent a vivid set of important perspectives on the IoT-driven services business. IoT seems to be opening up opportunities in many areas of managerial interest: process optimization, collaborative value creation, business model innovation and even the restructuring of existing industries. This special issue provides in-depth analyses of those aspects, providing insightful takeaways for practitioners as well as interesting paths for academic research.

Acknowledgements

We would like to thank Professor Wesley J. Johnston, Editor-in-Chief of the Journal of Business and Industrial Marketing, for giving us the opportunity to compose this special issue. We also express our greatest gratitude to the reviewers and authors for their invaluable contributions.

This research was conducted as part of the Platform Value Now program, financed by the Academy of Finland (Grant nr. 293446). The research also received funding from the Service Solutions for Fleet Management (S4Fleet) and Design for Value (D4V) programs, financed by the Finnish Funding Agency for Innovation (Business Finland, formerly TEKES), the Digital, Internet, Materials & Engineering Co-creation program (DIMECC) and the companies involved (Grant nr. 2634/31/2014 and 7546/31/2016).