Fortune Favors The Prepared

Technological Forecasting & Social Change 132 (2018) 2–17
Contents lists available at ScienceDirect
Technological Forecasting & Social Change

journal homepage: www.elsevier.com/locate/techfore
Fortune favors the prepared: How SMEs approach business model T

innovations in Industry 4.0
⁎
Julian Marius Müller , Oana Buliga, Kai-Ingo Voigt
School of Business and Economics, Friedrich-Alexander University Erlangen-Nürnberg, Lange Gasse 20, 90403 Nürnberg, Germany
A R T I C L E I N F O A B S T R A C T
Keywords: The article analyzes how Industry 4.0 triggers changes in the business models of manufacturing SMEs (small and
Industry 4.0 medium-sized enterprises), by conducting a qualitative research with a sample of 68 German SMEs from three
Business model innovation industries (automotive suppliers, mechanical and plant engineering, as well as electrical engineering and ICT).
Manufacturing industry As SMEs play an essential role in industrial value creation, the article examines significant, yet at present un-
SME
derstudied implications of Industry 4.0 along industrial value chains. First, the results show that Industry 4.0
Multiple case study
encompasses three dimensions, namely high-grade digitization of processes, smart manufacturing, and inter-
company connectivity. Second, the article shows how Industry 4.0 affects the three business model elements of
manufacturing SMEs – value creation, value capture, and value offer – by giving specific examples for business
model innovation in each of the three elements. Third, it shows that both the role as a user and/or provider of
Industry 4.0 and whether a company is internally motivated and/or externally pressured towards im-
plementation have an impact on which business model elements are innovated. Fourth, the study delineates four
SME categories, designed to help managers to evaluate their own company's positioning towards Industry 4.0:
craft manufacturers, preliminary stage planners, Industry 4.0 users, and full-scale adopters.
Article classification: multiple case study.
1. Introduction from the integration of CPS have a revolutionary impact on industrial

value creation or rather resemble an evolutionary process, which is
The term Industry 4.0 is derived from an initiative launched by the addressed in the course of the present paper.
German government for safeguarding the long-term competitiveness of Furthermore, academic investigation into Industry 4.0 extensively
the manufacturing industry (Kagermann et al., 2013). By integrating focuses on large enterprises (Arnold et al., 2016; Radziwon et al., 2014)
cyber-physical systems (CPS) in industrial manufacturing (Lasi et al., and only marginally on SMEs (small and medium-sized enterprises)
2014), Industry 4.0 aims at establishing intelligent, self-regulating, and (Schmidt et al., 2015). Yet many large companies act as suppliers to
interconnected industrial value creation (Liao et al., 2017). CPS com- SMEs and have SMEs as suppliers. Their actions affect the actions of
prise smart machines, storage systems, and production facilities, which their smaller supply chain partners and their requirements influence the
are able to exchange information, initiate actions, and mutually control positioning of SMEs towards the technological developments derived
each other. Their interconnection via the Internet, also termed as the from Industry 4.0. Therefore, it is important to consider how SMEs
Industrial Internet of Things (IIoT) generates technological leaps in implement Industry 4.0 and how the latter impacts industrial value
engineering, manufacturing, material flow, and supply chain manage- creation in SMEs. For example, the adoption of ERP systems, which are
ment (Kagermann et al., 2013). Newly emerging research on Industry a technological precursor to CPS, was approached differently in SMEs
4.0 focuses on technological developments related to CPS and on their than in large companies (Buonanno et al., 2005), because SMEs fre-
organizational implementation (Ehret and Wirtz, 2017; Kang et al., quently have lower digitization levels than their large counterparts,
2016; Lasi et al., 2014). In addition to investigations in the technical which is likely to affect the implementation of CPS. Further, a high
field, current research analyzes how Industry 4.0 affects value creation number of SMEs is active in niche markets (Knight, 2000), offering
in manufacturing, for instance how new technologies can be used to products manufactured in small series or on an individual basis. Such
provide new services and product-service systems. Nonetheless, an companies frequently require basic versions of the machinery and tools
open research question remains whether the developments resulting employed in the production facilities of large organizations. Analyzing
⁎
Corresponding author.
E-mail address: julian.mueller@fau.de (J.M. Müller).
https://doi.org/10.1016/j.techfore.2017.12.019
Received 21 September 2017; Received in revised form 8 December 2017; Accepted 26 December 2017
Available online 05 January 2018
0040-1625/ © 2018 Elsevier Inc. All rights reserved.
J.M. Müller et al. Technological Forecasting & Social Change 132 (2018) 2–17
the perspective of SMEs on how feasible it is for them to follow Industry interpretations of the term increasingly converge towards its con-
4.0 helps to gather a more comprehensive picture of the phenomenon's ceptualization as the sum of complementary elements, primarily value
organizational implications spanning industrial value chains. SMEs creation, value capture, and value offer (Bocken et al., 2014;
provide a fruitful research sample, as those represent over 99% of the Chesbrough, 2007; Saebi et al., 2017; Schneckenberg et al., 2017; Velu
companies located in the EU and hire between 50 and 70% of the full and Stiles, 2013). The present paper defines a business model as the
time equivalent of persons employed. With a gross value added share of sum of the value creation mechanisms, value offer, and value capture
over 50% of the European economy (Airaksinen et al., 2015), SMEs mechanisms and their links, in line with a substantial number of
require research that helps them sustain their economic significance in scholars, who explicitly (Björkdahl and Holmén, 2013; Spieth et al.,
times of unrelenting technological developments. 2014; Svejenova et al., 2010) or implicitly (Chesbrough and
To study how SMEs respond to Industry 4.0, the present paper fol- Rosenbloom, 2002; Johnson et al., 2008; Timmers, 1998) define it in
lows a business model perspective. Business models show how organi- this manner. Value creation refers to the tasks, which a company per-
zations design and conduct activities in order to provide value to their forms in order to provide an offer to its customers. In manufacturing
customers (Chesbrough and Rosenbloom, 2002; Taran et al., 2015; Zott organizations, value creation is the sum of the tasks undertaken at own
et al., 2011), how they interact with their suppliers, partners, and production locations and of the ones performed by suppliers and part-
customers (Bouncken and Fredrich, 2015; Ng et al., 2013), and how ners in the business ecosystem (Schneider and Spieth, 2013; Wei et al.,
they are compensated by customers (Massa et al., 2017). As well, the 2014). Value capture, also termed as monetization (Baden-Fuller and
business model concept is intrinsically linked to the exploitation of Haefliger, 2013) refers to the means, by which a company is compen-
opportunities (DaSilva and Trkman, 2014; George and Bock, 2011), sated by customers and, by which it sustains itself through commercial
such as the ones brought by novel technologies (Chesbrough, 2010; activity (Sosna et al., 2010; Teece, 2010). Since many companies
Sabatier et al., 2012; Spieth and Schneider, 2016; Zott et al., 2011). The choose to subsidize some customers in order to better monetize the
business model concept hereby generates an understanding of how offers to complementary customers, three value capture components
organizations can use Industry 4.0 to provide suitable value offers and can be distinguished: customer groups (Günzel and Holm, 2013), cus-
pricing models to their customers. The purpose of the study is to show tomer interaction (Baden-Fuller and Mangematin, 2013), and payment
whether and how the pursuit of Industry 4.0 reflects in business model methods (Baden-Fuller and Haefliger, 2013; Casadesus-Masanell and
innovations of manufacturing SMEs, i.e. in their value creation, value Zhu, 2013). Customer interaction refers to the type and amount of
capture, and value offers. Further, as researchers point out the need to support customers receive on a scale from individually tailored assis-
analyze the social implications of Industry 4.0 (Frazzon et al., 2013; tance to a help-yourself, automated support provision. The payment
Kagermann et al., 2013; Oesterreich and Teuteberg, 2016), the business methods describe how a company monetizes its offers, for instance
model concept allows the examination of consequences for employees, whether it offers pay-per use, pay-per-feature or cyclical payments as in
in particular for those requiring new skills and expertise. Based on the subscriptions. Concerning customer groups, companies can distinguish,
arguments above, the present paper aims to provide answers to the among other criteria, between B2B and end-customers. Finally, the
following two research questions: value offer is the assortment of products and services individual to each
RQ1: How do manufacturing SMEs perceive and understand the company and can be conceptually located on a continuum from pro-
Industry 4.0 phenomenon? In order to answer this question, the paper duct-only offers to service-only offers (Oliva and Kallenberg, 2003).
analyzes the familiarity of SMEs with the Industry 4.0 concept, their Hereby, a growing research stream discusses servitization or service
perception of the phenomenon as evolutionary or revolutionary, and business model innovation in manufacturing (Kastalli and Van Looy,
their interpretation of its implementation challenges. 2013; Lee et al., 2012), service infusion in manufacturing (Kowalkowski
RQ2: How do manufacturing SMEs innovate their business models in et al., 2013), and service provision through Industry 4.0 (Rennung
result of Industry 4.0? Here, the paper analyzes how SMEs forge value et al., 2016).
creation innovations, value capture innovations, and value offer in- A business model innovation represents the “designed, novel, nontrivial
novations by taking advantage of Industry 4.0. As well, the implications changes to the key elements of a firm's business model and/or the architecture
for employees are considered in this research question. linking these elements” (Foss and Saebi, 2017: 201). This definition implies
Based on the novelty of Industry 4.0, an exploratory approach with that the company's management takes a substantial role in designing the
a qualitative research setting (Strauss and Corbin, 1998) was chosen, business model innovation. It also signals that a business model in-
encompassing 68 manufacturing SMEs from three industries: auto- novation introduces new tasks that go beyond slight adaptions to the
motive suppliers, mechanical and plant engineering, as well as elec- company's environment, such as value offer variations through market-
trical engineering and ICT. Due to their high technological compe- adjusted products. In contrast, a business model innovation attracts new
tencies towards CPS development and usage, the three industries have a customers, who are either not satisfied with current solutions (Johnson
pioneering character in manufacturing and a leading role in the In- et al., 2008) or cannot access them (Yunus et al., 2010). Besides ad-
dustry 4.0 initiative (Kagermann et al., 2013). Additionally, they are dressing new customer groups, business model innovations aim to in-
among the largest industries in Germany. The following section 2 of the crease customer loyalty through more comprehensive value offers (Enkel
article provides the theoretical background on business model innova- and Mezger, 2013) or to reduce the costs faced by customers (Mitchell
tion and Industry 4.0, while section 3 describes the empirical setting and Coles, 2004). This can be done by re-distributing tasks between the
and research design. Section 4 presents the findings, which are followed company and its customers (Zott et al., 2011) or by adopting novel ap-
by a discussion of the theoretical and managerial contributions in sec- proaches for commercializing new technologies (Gambardella and
tion 5, and by the limitations and future research avenues in section 6. McGahan, 2010). In line with Clauss (2016), the present paper viwes that
a business model innovation can originate from and predominate in one
2. Theoretical background of the three business model elements: value creation, value offer (or
value proposition), and value capture. The analysis of those second order
2.1. Business model innovation dimensions of business model innovation allows finer distinctions to be
drawn from empirical findings (Clauss, 2016) on how companies pursue
The business model term has gained widespread recognition in business model innovation. Nevertheless, the present paper acknowl-
corporate practice (Baden-Fuller and Morgan, 2010) and high visibility edges that the three business model elements are highly interconnected,
in entrepreneurship and innovation research (Spieth et al., 2016; Zott so that an innovation in one element by definition leads to changes of
et al., 2011). Although the research community points out the lack of a varying degrees in the other two elements (Johnson et al., 2008; Zott and
generally accepted business model definition (Massa et al., 2017), Amit, 2010).
3
Further, research discusses how technologies such as additive Maynard, 2015) by making it more efficient. Also, similarly to past
manufacturing (Jia et al., 2015; Jiang et al., 2017; Mahindru and Industrial Revolutions, Industry 4.0 eases the proliferation of new
Mahendru, 2013; Potstada et al., 2016; Rayna and Striukova, 2015) and business models, increasing not only the scope of activities performed
general purpose technologies (GPTs) (Gambardella and McGahan, by manufacturing SMEs, but also their depth. Nonetheless, Industry 4.0
2010) create new business models and challenge established ones. represents a “new paradigm” in manufacturing, which leads to “swifter
While extant studies show that innovative technologies are devoid of and more accurate decision-making” (Kang et al., 2016: 124) and to a
economic value when they are not embedded in an adequate business “completely new approach to production” (Veza et al., 2015: 556). This
model that capitalizes on their potential (Chesbrough, 2010; Wirtz new approach leads to industrial value creation that is not only auto-
et al., 2010), their discussion needs to be extended to the emerging mated, mostly within single manufacturing plants, but also inter-
Industry 4.0. connected between objects, products, and humans, building on the
concept of the Internet of Things. Thus, Industry 4.0 relates to the in-
2.2. Industry 4.0 terconnection of different functions within the supply chain, also based
on the usage of artificial intelligence (Kagermann et al., 2013). This
In an international context, alongside the German initiative Industry enables a much higher degree of transparency and efficiency in trans-
4.0, the EU initiated a public-private partnership under the title actions compared to the third Industrial Revolution and brings new
Factories of the Future, designed to ensure sustainable and competitive questions in the already established debate on cyber security.
production. In the U.S., similar ideas are encouraged through the The following Table 1 provides an overview of definitions regarding
Industrial Internet Consortium with founding members such as AT&T, Industry 4.0 and its synonym terms from scholarly articles and from
CISCO, GE, IBM, and INTEL (Pike, 2014). In China, the Internet Plus or publications of governmental and public research institutions. Fol-
Made in China 2025 initiative integrates current technological devel- lowing a description of the research method, the next sections illustrate
opments such as cloud computing and big data to enable state-of-the-art whether and how SMEs approach business model innovations to derive
manufacturing, while South Korea announced the Manufacturing In- benefits from Industry 4.0.
novation 3.0 (Kang et al., 2016). In all named regions as well as in
countries such as Japan and Singapore (Liao et al., 2017) high invest- 3. Research method
ments are anticipated, whereas in Germany those are expected to ex-
ceed two billion Euro annually between 2018 and 2020 (Kagermann 3.1. Research design and empirical setting
et al., 2013).
The concept of Industry 4.0 suggests an outlook from governmental As academic investigation on Industry 4.0 is novel (Arnold et al.,
institutions and corporate practice towards the fourth Industrial 2016) and business model innovation represents a relatively recent
Revolution in manufacturing (Kagermann et al., 2013; Lasi et al., 2014; notion in scholarship (Foss and Saebi, 2017), this paper employs an
Liao et al., 2017). Similarly to the past Industrial Revolutions, Industry exploratory research design through a multiple case study (Blumberg
4.0 aims to transform working (and living) environments. It hereby et al., 2014; Bryman and Bell, 2011). Case studies are recommended in
represents an “unprecedented fusion” among digital, physical, and bio- exploratory research, as they provide rich data and allow the in-
logical entities (Maynard, 2015: 1005) with the purpose of creating vestigation of contemporary managerial challenges (Yin, 2009). Fol-
social, economic, and environmental advances (Kiel et al., 2017). The lowing empirical work on how emerging technologies impact business
past three Industrial Revolutions have achieved high productivity in- models (de Reuver et al., 2013; Demil et al., 2015; Ernkvist, 2015;
creases, driven by a few, fast-spreading GPTs: mechanization, elec- Ferreira et al., 2013), the present paper uses a multiple case study re-
tricity, and IT (Veza et al., 2015). GPTs result in significant technical search design in order to show the range (Eisenhardt and Graebner,
improvements and initiate further complementary developments 2007) of technology-derived value creation, value capture, and value
(Bresnahan and Trajtenberg, 1995). For Industry 4.0, CPS represent the offer innovations.
GPTs that are integrated in industrial value creation (Ivanov et al.,
2016; Schmidt et al., 2015; Vogel-Heuser and Hess, 2016). To achieve 3.2. Data collection and analysis
this integration, traditional industrial machinery and products are
equipped with sensors, microprocessors, ports, antennae, and software The qualitative nature of the paper raises issues concerning the
(Porter and Heppelmann, 2015) for data collection and analysis (Pfohl generalizability of the results. To respond to such concerns, companies
et al., 2015). The application of CPS in industry enables physical pro- were selected by using the company database Bisnode. The database
cesses to be accompanied by digital ones (Liao et al., 2017), the latter provides summary profiles and contact information of 300,000 German
either replicating or augmenting the former. This can be realized across enterprises. Following the SME definition of the German Institute for
products, production facilities, and supply networks, achieving value SME research (IfM Bonn, 2016), two criteria were applied in the da-
creation that is interconnected in real-time (Hermann et al., 2016; tabase search: staff headcount below 500 employees and annual turn-
Oesterreich and Teuteberg, 2016; Pfohl et al., 2015). The introduction over below 50 million euro. Through quota-based sampling (Robinson,
of virtual processes in industrial value creation enables machine-to- 2014), we contacted an evenly distributed amount of enterprises with
machine and human-to-machine communication, autonomous machine regard to company size and industry sector, totaling 295 approached
learning, and decision-making. companies, none of which were start-ups. Out of those, 68 participated
Since the 1970s up to the present day, the third Industrial in the study, representing a response rate of around 25%. The high
Revolution has been unfolding. It describes the use of electronics and IT number of companies in the sample lowered the sample bias, in the
in production automation (Schmidt et al., 2015) and has bought a sense that it reduced the risk that participating companies were more
widespread digitization wave. In turn, this digitization wave created the technologically savvy than those that did not participate. In turn, this
suitable environment for Industry 4.0 and for the introduction of smart allowed the investigation of a broad and representative group of
objects such as CPS-based products and machines (Lasi et al., 2014). manufacturing SMEs headquartered in Germany. In contrast to large
Thus, Industry 4.0 and the convergence of digital and physical tech- organizations, which simultaneously employ several business models in
nologies rely on the third Industrial Revolution and on the develop- their different business divisions (Aspara et al., 2013), SMEs frequently
ments from this industrialization stage (Maynard, 2015). In several have a single business model, which allows the examination of business
ways, Industry 4.0 is not different from the preceding Industrial Re- model innovations that affect the company as a whole. Analyzing the
volution: comparably to its predecessor, Industry 4.0 aims to transform entire business model of an organization in turn allows more precise
the production of goods and services (Kagermann et al., 2013; conclusions regarding the changes in value creation, value offer, and
4
Table 1
Extant research definitions on the Industry 4.0 term and its synonyms.
Author (year: page) Term Definition
Hermann et al. (2016: Industrie 4.0 “The convergence of industrial production and information and communication technologies, called Industrie
3928–3929) 4.0 […]”; “In this publication, the authors name three key components of Industrie 4.0: the IoT, Cyber-
Physical Systems (CPS), and Smart Factories.”
Hossain and Muhammad (2016: Industrial Internet of Things “The Industrial IoT is the combination of big data, IoT, Machine to Machine (M2M) communication, cloud
194) (Industrial IoT) computing, and real-time analysis of data from interconnected sensor devices.”
Ivanov et al. (2016: 386) Industry 4.0 “Industry 4.0 represents a smart manufacturing networking concept where machines and products interact
with each other without human control.”
Kagermann et al. (2013: 14) Industrie 4.0 “In essence, Industrie 4.0 will involve the technical integration of CPS into manufacturing and logistics and the
use of the Internet of Things and Services in industrial processes. This will have implications for value creation,
business models, downstream services and work organisation.”
Kang et al. (2016: 124) Industry 4.0/Smart manufacturing “Industry 4.0 or Smart Manufacturing is the fourth industrial revolution. It is a new paradigm and convergence
of cutting-edge ICT and manufacturing technologies. It provides ground for making effective and optimized
decisions through swifter and more accurate decision-making processes.”
Kolberg et al. (2017: 2845) Industrie 4.0 “Industry 4.0 is the vision of smart components and machines which are integrated into a common digital
network based on the well-proven internet standards.”
Lasi et al. (2014: 240) Industry 4.0 “The term Industry 4.0 collectively refers to a wide range of current concepts, whose clear classification
concerning a discipline as well as their precise distinction is not possible in individual cases. […] The concepts
are: smart factory […], cyber-physical systems […], self-organization […], new systems in distribution and
procurement […], new systems in the development of products and services […], adaptation to human needs
and corporate social responsibility […].”
Oesterreich & Teuteberg (2016: Industry 4.0 “The term Industry 4.0 comprises a variety of technologies to enable the development of a digital and
122) automated manufacturing environment as well as the digitisation of the value chain.”
Pfohl et al. (2015: 37) Industry 4.0 “Industry 4.0 is the sum of all disruptive innovations derived and implemented in a value chain to address the
trends of digitalization, autonomization, transparency, mobility, modularization, network-collaboration and
socializing of products and processes.”
Sadeghi et al. (2015: 2) Industrial Internet of Things “Industrial IoT is the basis for a new level of organization and management of industrial value chains and
(Industrial IoT) enables highly flexible and resource-saving production as well as enhanced individualization of products at the
cost of mass production.”
Schmidt et al. (2015: 17) Industry 4.0 “In this paper Industry 4.0 shall be defined as the embedding of smart products into digital and physical
processes. Digital and physical processes interact with each other and cross geographical and organizational
borders.”
Vogel-Heuser & Hess (2016: 411) Industry 4.0 “Industry 4.0 – derived from the German term Industrie 4.0 – is used as a synonym for Cyber-Physical
Production Systems (CPPS), i.e., Cyber-Physical Systems applied in the domain of manufacturing/
production.”
value capture. Hereby, the results are not skewed by synergies or by focal point shifted towards the business model in the third section.
competition for resources between different business units as in large Data from the 68 interviews was triangulated by examining all
organizations. company websites, several industrial databases (Bisnode, LexisNexis,
Of the 68 companies, two are micro SMEs with less than 10 em- Statista, the electronic German Federal Gazette as well as databases
ployees and an annual turnover below two million euro. 23 companies from the German Mechanical Engineering Industry Association and the
are small SMEs with less than 50 employees and an annual turnover German Association of the Automotive Industry), as well as press re-
below 10 million euro. Finally, 43 companies are medium SMEs with leases and press interviews. This allowed for a more refined perspective
less than 500 employees and an annual turnover below 50 million euro. on the Industry 4.0 activities of the analyzed organizations. Construct
The companies belong to three industries: mechanical and plant en- validity, which refers to choosing appropriate operational measures for
gineering (36), automotive suppliers (28), as well as electrical en- the studied concepts, was ensured by data triangulation and by main-
gineering and ICT (4). Only companies that could provide interviewees taining continuous chains of evidence on the methodical choices
holding leading roles were considered, the sample comprising CEOs (Eisenhardt, 1989; Gibbert et al., 2008; Huber and Power, 1985). We
(29), CTOs (5), and the heads of the following departments: sales (12), ensured internal validity, namely the act of unveiling causal relation-
manufacturing (6), R&D (2), logistics (1), quality management (2), and ships, through explanation building and addressing rival explanations
strategy (1). Seasoned, authorized company representatives (10) in the in the discussion section (Yin, 2014). External validity, which refers to
following departments rounded off the sample: assistant to CEO, lo- the generalizability of research results, was established by analyzing a
gistics, manufacturing and sales engineering, controlling, HR, and IT. substantial number of 68 cases (Voss et al., 2002). Reliability, namely
Table 3 in Appendix A shows a delineation of the organizational and the degree to which the exact method used in this paper leads further
personal characteristics of the interviewees (N = 68). Lasting between researchers to the same results, was ensured by thoroughly doc-
25 and 90 min, the interviews were conducted between July 2015 and umenting the research process, including case study protocols and a
February 2016 via telephone and were recorded on audio files. Subse- case study database (Yin, 2014).
quently, the interviews were formally transcribed in spreadsheets. Based on the theoretical background, we deductively developed a
The interview guideline, which is shown in Table 4 (Appendix B), coding manual, which was further inductively supplemented and re-
consists of three sections: in the opening one, the respondent stated his/ vised through interview data. Hand-coding and iterative identification
her function and discussed his/her areas of responsibility. The second, of patterns were used for within-case analysis, while differences and
Industry 4.0-focused section, analyzed the interviewee's understanding similarities between cases were analyzed during the cross-case analysis
of the term, its enablers, and its implications. In this section, the au- (Taran et al., 2015). Three coding types were combined, namely open,
thors' and interviewees' understanding of Industry 4.0 were compared, axial, and selective coding. Inductively derived from the data, the codes
in order to clarify differences. Finally, in the business model-centered created a frame for the research and helped us to expand the initial,
section, the effects of Industry 4.0 on organizational value creation, theory-driven perspective (Charmaz, 2006) on the wealth of meaning
value capture, and value offer were discussed. While Industry 4.0 behind Industry 4.0 and on its business model implications. Two of the
served as unit of analysis in the second section of the interview, the authors independently coded 20 interviews and subsequently discussed
5
the differences in individual codes in order to ensure an objective benefits require time to unfold. To give an example, one of the SMEs
analysis (Duriau et al., 2007). After an initial inter-coder reliability of invests 360,000 euro for enabling CPS among its 180 machines, in-
84%, agreement upon all codes from the 68 interviews was reached stallation costs amounting 2000 euro per machine. This investment
successively through a series of feedback rounds with the third author. only allows the collection of real-time information, while further ex-
Table 5 in Appendix C shows an excerpt from the coding tables, while penditures are required for data analysis. Several interviewees call at-
Table 6 in Appendix D shows the coding manual. tention to this issue, namely that Industry 4.0 increases their costs
substantially, while their customers' willingness to pay does not pro-
4. Results portionally increase. Second, over a fourth of the interviewees (18)
have data security concerns, discussing data lacks, stolen proprietary
4.1. Understanding of the term Industry 4.0 information and the external deactivation of production systems. While
many of those companies aim to establish an IT-facilitated, automated
The first interview question, concerning the familiarity of the in- interconnection with suppliers and customers, they struggle with the
terviewees with the Industry 4.0 term, brings several insights: Over half resulting uncertainties and complexities, for instance in case of dis-
of the interviewees (34) have detailed knowledge of Industry 4.0 and its turbances. As one respondent explained, “We already experienced that if
underlying ideas, around a third (22) show general knowledge, while an interconnected machine malfunctions, it drags a disruption in the entire
12, representing less than a fifth of the sample, are barely aware of production”. Third, around a fifth of the respondents (15) view the small
Industry 4.0. The well-informed respondents gave both extensive and batch sizes as an obstacle to Industry 4.0, in particular to the im-
compact own definitions, for which the following are exemplary: plementation of smart manufacturing, because of the reduced output
“[Industry 4.0 represents] production networking and the digitized con- per production line that is to be equipped for Industry 4.0. Fourth,
nectivity between suppliers and customers across the complete value chain” difficulties are also imposed by the varying automation degrees and
or “[Industry 4.0 embodies] IT solutions bundled in products”. Compiling lifecycle stages of the machinery, since some machines have to be re-
the views of those 34 respondents, three dimensions of Industry 4.0 are placed, whereas others require varying degrees of retrofitting. As an
revealed: 1) high-grade digitization of processes, most notably manu- interviewee mentioned, “[We find it] difficult to master the complexities
facturing ones, 2) smart manufacturing through CPS, resulting in self- resulting from the different automation degrees of our machines”.
controlled production systems, and 3) inter-company connectivity be- Fifth, value creation challenges can develop into value offer chal-
tween suppliers and customers within the value chain. To underline the lenges. This is reflected by companies, which invest in gathering in-
importance of the third dimension of Industry 4.0, one interviewee formation through Industry 4.0 technologies, while facing challenges in
defines Industry 4.0 as “web-based industrial communication”. Several putting the information to commercial use. Exemplary is the following
interviewees further share their vision of what Industry 4.0 can achieve: statement: “Industry 4.0 initially generates information, yet no solutions for
“intelligent production with batch size one” and “increased resource effi- our customers”. Sixth, the highly individual customer demands hamper
ciency through higher customer and partner integration”. Desired outcomes the implementation of interconnected and standardized Industry 4.0
also include improved production and project control. As one inter- solutions in form of CPS. Individual customer demands lead to low
viewee mentions, “Industry 4.0 may be a marketing gag or a political standardization rates in inter-company information transfer, triggering
catchphrase, as developments are running since longer – yet the political challenges in value creation. This shows that value offer and value
forces hope to speed up this technological process”. creation are closely intertwined and that the challenges faced by one
While over half of the respondents (40) view Industry 4.0 as an element of the business model reflect in challenges for another business
evolutionary sum of adaptions in production, supply chain con- model element. Here, over a third of the interviewees (25) discuss how
nectivity, and digitization, 18 perceive it as an outright Industrial low standardization rates delay the implementation of Industry 4.0,
Revolution. Five interviewees mention that this evaluation depends on which was conveyed through statements such as: “[For Industry 4.0]
individual company characteristics. Interviewees from the first group standardization is essential, but unlikely in the short term”. One respondent
exemplary view Industry 4.0 as “[an] evolutionary process […], not as mentioned that despite existing standards for electronic data inter-
abrupt or sudden as a revolution “and “currently [it] is a minor matter, […] change (EDI) in the German Association of the Automotive Industry
the more companies join the trend, the higher its implications regardless of (VDA), many automotive suppliers still have to adjust to individual
the industry.” Some refer to the term as entailing “stepwise changes”, OEM standards. Finally, concerning the challenges for value capture,
“continuous improvements” or “consistent adjustments”. Contrarily, re- five companies fear losing their customers, as those can, via online
spondents that view Industry 4.0 as a genuine Industrial Revolution platforms, gather real-time information on price shifts and turn to other
state: “[Industry 4.0] will fully impact SMEs, [while those] are not yet ready providers with each new transaction.
for the changes, digitization still being in its infancy in many of them”. The SMEs revealed their lack of expertise for mastering such chal-
Finally, one interviewee considers that the nature of Industry 4.0 de- lenges as well as their derived need for external assistance, which can
pends on the size of the company implementing it: “For many SMEs it is be provided by governmental institutions and by work groups of the
a sum of adaptions, for larger companies it can be a real manufacturing trade community. Nevertheless, the interviewees generally acknowl-
revolution”. The previous two quotes bring up the question whether edged that if their companies do not consider the possibilities brought
SMEs tend to be reactive, rather than proactive in the context of by Industry 4.0, technologically more advanced competitors will soon
Industry 4.0. The following sections help to shed light on this issue. drive them out of the market.
4.2. Challenges affecting Industry 4.0 implementation across the business 4.3. Industry 4.0-enabled innovations across the business model elements
model elements
To show the impact of Industry 4.0 on the business models of the
The implementation of Industry 4.0 carries challenges across all SMEs in the sample, 26 companies were excluded from the further
three business model elements: value creation, value offer, and value analysis, which could not state any present or expected business model
capture. First, concerning value creation, almost two-thirds of the implications. Consequently, the paper analyzes how Industry 4.0 drives
sample (43) perceive the substantial organizational efforts required for innovation in the remaining 42 companies, as illustrated in Table 2. The
implementation as challenging. Here, respondents mention high in- number of mentions for each innovation area is shown in brackets.
vestments in machine parks and IT infrastructure, as well as costs for IT As regards the left column of Table 2, value creation innovations,
personnel and technical trainings. Commonly, the interviewees per- respondents mention that the high-grade digitization of processes in-
ceive Industry 4.0 as costly in the short-term, whereas its expected creases their data availability and enables faster decision-making. For
6
Table 2
The effect of Industry 4.0 on the business model elements of manufacturing SMEs.
Value creation Value offer Value capture
Production equipment (26) Products (20) Customer groups (11)
- Productivity increases - Larger product spectrum - New customer groups addressed within the B2B
- Energy savings - Less maintenance required customer base
- Load balancing - Versatile, flexible products (particularly machines) - Both the risks and the opportunities for
- Higher fault resistance of production equipment - Higher quality and output of the produced machines customer retention are intensified
- Fast access to manufacturing data - Incorporation of manufacturing data in products and
- Machine-health monitoring in production management systems Customer interaction (23)
- Self-controlled production - Products tailored to customer demands
- Increased in-house production - Human-machine-interfaces - Customer contact via digital platforms
- Lower stocks - Eased interaction through digital
- Easier production maintenance Services (15) communication
- Retrofitting of older machinery and new equipment required - Co-design and co-engineering
- Machine retrofitting services - Higher cost transparency
Workforce (22) - Condition monitoring - Joint decision-making
- Remote maintenance - Value chain integration of customers
- Attenuation of job shortages in manufacturing, yet likely - Digitization services for customers - Suppliers become more transparent to
shortages in Industry 4.0-qualified personnel - Data analytics services customers
- Better integration of lower qualified and elderly personnel - Manufacturing and product simulations - Decreases in customer loyalty due to higher
- New job profiles - Virtual product development anonymity
- New workplaces - Engineering and product configuration services
- Higher technical expertise and employee trainings required Payment methods (12)
- Technology-based trainings
- Support in failure recognition - Digital accounting and automated invoices
- Decreasing number of manufacturing jobs - Increased payment reliability
- Streamlined payment documentation
Partners and suppliers (16) - Increase in subscription models, pay-per-use
and pay-per-feature
- Higher inter-company connectivity
- Co-design of the value offers
- Joint data analysis
- Higher information transparency
- Higher delivery reliability
- Innovative partnerships
- Increased virtual contact
- Higher standardization required
instance, one of the CTOs mentioned that each morning he receives an Suppliers are invited to participate on such platforms and list their
automated e-mail with information on production status-quo, including prices. When the price is above the customer's expectation, no customer
bottlenecks and production output. The sample in general expects In- contact takes place. In such automated processes, human interference is
dustry 4.0 to improve their speed, reaction capacity, and flexibility: low, which increases the efficiency of order placement and the cost
“Industry 4.0 allows us to more quickly react to malfunctions, as different transparency. Interviewees also mention that Industry 4.0 fosters pay-
interfaces become faster and more precise”; “Production know-how can seep per-use models, replacing invoices by EDI-managed cyclical payments
faster in new product development”. Industry 4.0 also aims to enhance the from customers. Finally, the increased inter-company connectivity
efficiency and information transparency of shop floor processes, creates a more comprehensive interaction between suppliers and cus-
through systems that show the tasks performed at each machine, task tomers. This is reflected by higher customer involvement in product
duration, given commands, and eventual failures. Moreover, several engineering and design, as enabled by product configuration tools. A
companies indicate that they already profit from smart manufacturing striking example for how Industry 4.0 impacts the relationship with
in counteracting a lack of available job applicants: “It becomes increas- customers is the following statement: “Companies will either fully retain
ingly difficult to find qualified personnel to do highly skilled manual work in their customers or completely lose them to technologically leading competi-
the technical field – and Industry 4.0 helps us with that”. Industry 4.0 can tors”, showing that Industry 4.0 increases both the opportunities and
also ease task assignments to employees: “Our employees use a smart- the risks of customer retention.
phone app, on which they inform us fast and flexibly whether they can take
an additional work shift during peak times”. 5. Discussion
To summarize the second column of Table 2, the value offer in-
novations, most companies in the sample expect their product spectrum Two main research questions were addressed in the present study.
to become broader in result of Industry 4.0: “[We plan to] extend the The first one (RQ1) considers how manufacturing SMEs perceive and
value offer following the Lego-principle, while remaining in [our] traditional understand the phenomenon Industry 4.0, while the second (RQ2) re-
industry of metal processing”. As well, companies expect an increased gards the ways how companies attempt to innovate their business
ability to provide customer-tailored products with higher quality: “CPS models resulting from Industry 4.0. The next section provides a dis-
create higher flexibility in responding to customer wishes and fulfilling or- cussion of the two questions.
ders”. Several respondents also envision additional services: “[Our]
product segment is likely to benefit from improved service, maintenance, and
5.1. Theoretical contributions
retrofitting solutions”.
Regarding value capture innovations, the third column of Table 2, a
5.1.1. Towards a common understanding of the Industry 4.0 concept
number of interviewees points out the benefits of automated online
Concerning the first research question, the empirical results reveal
platforms, which enable eased customer contact and order placement.
the following dimensions of Industry 4.0: 1) high-grade digitization of
7
processes, most notably manufacturing ones, 2) smart manufacturing importance of identifying new technological trends early and of
through CPS resulting in self-controlled production systems, and 3) promptly responding to them (Radziwon et al., 2014).
inter-company connectivity between suppliers and customers within Second, the results show that while most companies in the sample
the value chain. This extends current research by providing a con- lack expertise in implementing Industry 4.0 (Kowalkowski et al., 2013),
ceptual base for future studies, as Industry 4.0 is an emerging research this deficiency can open new doors for cooperation and value creation
topic, which has gained increased attention from corporate practice and innovation with partnering companies and institutions. Governmental
for which theoretical contributions are still lagging behind (Arnold and industrial initiatives can incentivize and support SMEs in their ef-
et al., 2016). Hereby, theoretical contributions are encouraged con- forts, for instance by bringing together companies with complementary
cerning how the three dimensions of Industry 4.0 interact in generating capabilities (He and Xu, 2015; Ren et al., 2013). As investments in ICT
economic value. Further, the results reveal that despite company-in- are high and often risky, SMEs can join information sharing networks or
ternal efforts, Industry 4.0 can represent an intimidating concept for platforms for Industry 4.0 implementation (Shin et al., 2014). Hereby,
many SMEs. The findings illustrate that SMEs generally approach In- clouds assist in the outsourcing of data storage and data sharing with
dustry 4.0 with caution, several explicitly indicating that high pro- partners (Xu, 2012). In order to receive widespread acceptance in
duction process transparency will be detrimental to them. While most SMEs, such platforms need to be easily accessible, secure, and efficient
researchers emphasize the novel elements of Industry 4.0 (Lasi et al., in usage (Davis et al., 2012).
2014; Maynard, 2015), the present results highlight a more nuanced Third, as companies rely on suppliers and customers in their value
perspective from the interviewees, most of whom are on the one hand creation activities, the present findings extend research on inter-com-
more pragmatic concerning implementation challenges and on the pany connectivity with those groups (Ehret and Wirtz, 2017). The in-
other hand are still trying to comprehend how to take advantage of the terviews raise an important issue, namely that transparency can be
business model innovation opportunities in value creation, value offer, detrimental. One group of SMEs shows little enthusiasm towards real-
and value capture. Extending current research (Radziwon et al., 2014), time information sharing, fearing the implications of becoming a
the results show that the newness of Industry 4.0 makes it expensive for “transparent supplier”. This is because Industry 4.0 can enable un-
SMEs to implement. In spite of such challenges, most interviewees are precedented customer access to real-time information concerning the
aware of the importance of understanding the phenomenon and its exact manufacturing stage of the products ordered. A second group
implications on their business models. Further, despite short-term sa- views increased connectivity as beneficial, yet only reactively follows
crifices derived from Industry 4.0 implementation, the SMEs in the developments from their large customers, mainly due to the costs in-
sample are largely aware of the long-term performance benefits of In- curred. A third group of proactive SMEs highlights improvements
dustry 4.0. Consequently, the following sections explain these benefits through connectivity in production monitoring and control across the
along the three business model elements, providing a discussion of the value chain and is already pursuing an increased connectivity with its
second research question. customers and suppliers. The present paper argues that in order to
benefit from Industry 4.0, companies need to learn to share production-
5.1.2. Value creation innovations related data with suppliers and customers in a manner that benefits all
First, the findings support current research stating that manu- partners within the supply chain (Schuh et al., 2014). As the shared
facturing SMEs often lack real-time, accurate, and consistent informa- information includes sensitive data about inventories, bottlenecks, and
tion concerning own shop-floor resources (Zhang et al., 2014). Such incidents (Meyer et al., 2011), new ethical, technical, and legal ap-
data lacks make it difficult for companies to evaluate their manu- proaches are needed in Industry 4.0. Those are also required for
facturing performance (Shin et al., 2014) and create a demand for In- counteracting cyber criminality, as companies are not only responsible
dustry 4.0. The paper shows that proactive SMEs hope to counteract for their own data security, but also for the data security of supply chain
information deficits through innovations such as the high-grade digi- partners linked to them.
tization of manufacturing data, which allows demand optimization, Fourth, the findings show how companies can work together with
failure reduction, and productivity increases (Flammini et al., 2009; their employees to generate value creation innovations. With generally
Schlechtendahl et al., 2015), enabling a more efficient value creation at lower automation levels than large companies, SMEs tend to rely more
own manufacturing sites. The paper extends current research by profoundly on their manufacturing employees (Hirsch-Kreinsen, 2016).
showing that in spite of the perceived benefits, SMEs are frequently While researchers underline the need for studies concerning how In-
aversive towards the costs incurred from integrating CPS, requiring new dustry 4.0 affects employees, particularly those requiring new skills
machinery purchase and/or the retrofitting of existing machinery as development (Chryssolouris et al., 2013; Gorecky et al., 2014; Weber,
well as the integration of sensors and software. The pursuit of Industry 2016), the present findings are among the first to do so in an SME
4.0 requires high computing capacities, which are necessary for a context. The results show that SMEs need more substantial employee
multitude of tasks: planning, processing, simulating, and monitoring trainings, as fully new skills are required for human intervention in case
production lines, performing optimizations, and analyzing the data of machine failures. An interviewee hereby discussed his company's
generated during the product life cycle (Lee et al., 2014). SMEs there- strategy of upskilling a third of their employees, training as apprentices
fore require support, for instance from governmental institutions, in a second third, and hiring a third from candidates who are already
understanding the financial and technological prerequisites for CPS experienced in Industry 4.0. Further, extant studies reveal that due to
implementation. The paper further argues that SMEs need to sense the increasing industry dynamics, SMEs are likely to become dependent on
right timing for introducing CPS within their own manufacturing pro- college level education, while trainings and reallocations of manu-
cesses. This is important, as extant research shows that financial and facturing employees along the value chain will become more frequent
human resource limitations (Kowalkowski et al., 2013) impede many (Davis et al., 2012). While researchers argue that since workers are the
SMEs from looking beyond current technical capabilities and identi- most flexible production factor, their responsibilities will become more
fying emerging technologies. Such activities require highly skilled diverse (Gorecky et al., 2014), an interesting question is whether those
employees and the necessary managerial support (Eppler et al., 2011), companies with flexible workforce tend to introduce Industry 4.0, or
which is constrained in most SMEs in the sample through the demands whether the lack of human resources imposes a need for Industry 4.0.
of the day-to-day business. Moreover, SMEs tend to avoid technologies The present findings indicate that whereas CPS can compensate for the
with uncertain results (Hirsch-Kreinsen, 2016), so investments as early lack of unexperienced manufacturing employees, it cannot offset a lack
adopters are often evaded, due to the risk of investing in the wrong of specialists, particularly in IT and manufacturing. On the contrary,
technologies (Faller and Feldmüller, 2015). This conservative invest- Industry 4.0 increases the need for experts. The findings also signal that
ment strategy has shortcomings, as researchers highlight the Industry 4.0 facilitates the employment of lower qualified workforce,
8
since machines can visually explain the proceeding steps and guide low- willingness to pay and reduce payment documentation efforts (He and
qualified workers through processes. This can shorten basic trainings Xu, 2015; Xu, 2012), improving both transaction transparency and ef-
and allow low-qualified workforce to start employment faster. Industry ficiency. Industry 4.0 also brings new mechanisms for customer inter-
4.0 implementation in SMEs should not go without considering em- action, for instance platforms for online-based communication. Yet
ployee needs (Stock and Seliger, 2016). As the results show, labor un- while the high anonymity of digital communication increases price
ions and works councils are frequently critical towards Industry 4.0, transparency, it can also end long-established business partnerships.
since many employees fear the full traceability of their own errors and Therefore, many SMEs are shifting their value capture logic to a cus-
mistakes. Digitization can be particularly difficult for elder employees tomer-oriented one, understanding that the importance of customer
and for those who are not computer- and technology-savvy or are un- retention is intensified through Industry 4.0 (Wu et al., 2013).
motivated to change their means of work. A further socially sensitive
matter emerges from the results, namely that Industry 4.0 not only 5.1.5. Synthesis of the business model implications of Industry 4.0
eases physical work, but can also fully replace blue-collar workers. This The findings of the present study extend current research on
confirms literature discussing that Industry 4.0 is a two-sided coin: Industry 4.0 by showing that SMEs can take two roles: user and pro-
while monotonous tasks are expected to decrease, manufacturing jobs vider of Industry 4.0 (Kagermann et al., 2013). Whereas users mainly
in sum are also likely to decrease (Kiel et al., 2017; Stock and Seliger, implement CPS-based solutions in production, services, and related
2016). Cooperation with labor unions and the establishment of em- data exchanges, providers are those companies that manufacture CPS
ployee agreements as well as the provision of trainings and professional solutions, which are further required by Industry 4.0 users. Nine of the
re-education are therefore recommended for easing the transition to- interviewed companies take both roles towards Industry 4.0. Further,
wards Industry 4.0. the results show that a company's motives for implementing Industry
4.0 also impact its business model. We distinguish between two cate-
5.1.3. Value offer innovations gories of motives: internal ones, derived from perceived market op-
A prevailing business model research stream focuses on servitization portunities (Schaltegger et al., 2016) and external ones, derived from
or service business model innovation in manufacturing firms demands exercised by large customers, which, to quote one inter-
(Cusumano et al., 2015; Kastalli and Van Looy, 2013; Oliva and viewee, “set the tone regarding Industry 4.0”. The interviews show that
Kallenberg, 2003; Raja et al., 2013; Rennung et al., 2016), showing how internally motivated SMEs proactively conduct research projects with
manufacturers can redesign their business models from product-only universities and supply chain partners. In contrast, such research
offers to service-oriented offers. Research hereby progresses from a partnerships were not mentioned by externally motivated companies,
resource-based view (Barney, 1991) to a demand-based view (Priem, indicating that those SMEs perceive Industry 4.0 as a requirement ra-
2007) on business model innovation, emphasizing how new value offers ther than as an opportunity and are one-sidedly pressured by custo-
including services can solve customer problems by saving them time, mers. Interestingly, nine companies specify that they are both ex-
efforts, and investments (Visnjic et al., 2016). Concerning service internally and internally motivated, as for them, the drivers are closely
fusion in manufacturing, researchers focus on large companies, as op- intertwined.
posed to SMEs (Davies et al., 2007; Kowalkowski et al., 2013; Raddats Derived from those two perspectives towards Industry 4.0, SMEs
and Easingwood, 2010). However, the present paper shows that servi- resort to different innovations in their value offer, creation, and cap-
tization is a worthy pursuit for SMEs, leading to innovative business ture. In Fig. 1, these findings are condensed in a cross-case analysis,
models, beginning with repair and maintenance, followed by techno- encompassing both the role as user and/or provider as well as the
logical trainings and consulting as well as CPS-related services, such as motivation towards Industry 4.0. As six of the 42 SMEs could not clearly
digitization of processes, real-time product co-development or data identify their motivation towards Industry 4.0, those were excluded
processing and analysis (Eggert et al., 2014; Mathieu, 2001). The paper from the cross-case analysis, which resulted in a reduced sample of 36
also argues that additional services are important in justifying higher cases. Fig. 1 shows those business model elements, the innovation of
price points, as researchers show that while Industry 4.0 decreases costs which was named by at least half of the companies from each combi-
for individualized products in the long term, those will continue to be nation of user/provider/both and internally motivated/externally mo-
above the ones for mass production, due to investments in new tech- tivated/both. Fig. 1 only shows the business model innovations from
nologies (Schlechtendahl et al., 2015; Xu et al., 2014). the groups of SMEs with at least three members, due to reasons of
clarity and representativeness.
5.1.4. Value capture innovations As the figure above illustrates, a first group can be identified as
While the first two Industry 4.0 dimensions of process digitization companies that are primarily users of Industry 4.0. Those companies in
and smart manufacturing through CPS mainly influence the value the lower, left part of the figure expect business model changes in the
creation mechanisms illustrated above, the third Industry 4.0 dimen- elements of value creation and value capture. This applies regardless of
sion, inter-company connectivity, additionally affects the value capture whether they are internally motivated or externally pressured towards
mechanisms. Connectivity along the value chain allows wider customer Industry 4.0. A second group of enterprises subsumes providers and
reach, easier communication processes regarding order placement and SMEs, which act as both users and providers of Industry 4.0. Those
fulfilment as well as eased payments. Furthermore, data exchange SMEs are either motivated through existing market demand by custo-
among the entire supply chain and in real-time allows optimization mers (externally) or by proactively conducting research projects (in-
through data analysis, demand balancing, and predictive analytics. ternally). These enterprises expect changes throughout all three ele-
As the previous section shows, servitization represents a perspective ments of their business models. In contrast to the first group, the
shift from a product-based business model to a demand-oriented one number of business model elements innovated by the second group is
(Visnjic et al., 2016). The present results illustrate that servitization significantly larger, as value offer innovations through Industry 4.0 play
allows new forms value capture and that companies, which introduce a significant role here as well.
services in their value offers, are the ones likely to profit the most from
value capture innovation through Industry 4.0. Those companies are 5.2. Managerial implications
currently moving from being product manufacturers to becoming pro-
viders of Industry 4.0 solutions. This allows them, on the one hand, to By analyzing all 68 cases underlying this research, it became clear
target new B2B customers, and on the other hand, to switch from that SMEs follow different response strategies to Industry 4.0. As shown
payments per product to pay-per-feature, pay-per-use, or pay-per- in Fig. 2 below, those are derived, on the one hand, from the degree of
output models. Such value capture forms can increase customer internal motivation towards implementing Industry 4.0, and on the
9
Fig. 1. Cross-case analysis of predominant business

model implications (N = 36).
Fig. 2. Stage model of manufacturing SMEs in the context

Role in Industry 4.0:
of Industry 4.0.
(user and) provider
Innovations in
production equipment,
Role in Industry workforce, partners,
4.0: user products, services, and
customer interaction
Motivation Innovations in Full-scale adopters

towards production (16)
Industry 4.0 equipment,
workforce, and
customer interaction
„We want to be the
Business model Industry 4.0 users leader in our
innovations (20) industry and can
envisioned, yet only achieve this
presently undecided through Industry
„More eficient usage
4.0“
of machines while
Craft manufacturers Preliminary stage achieving more with
(26) planners (6) less employees“
„We’ve always done „For us, Industry 4.0

things like this“ is imaginable in the
next ive to ten years“
other hand, from the company's own structural and technological retrofitting old machinery. A statement repeatedly mentioned from this
characteristics, which make it more or less compatible with the three group is “We've always done things like this”. Resulting from the im-
Industry 4.0 dimensions of process digitization, smart manufacturing, movable attitude of such companies, they do not expect changes from
and inter-company connectivity. The investigation of the results brings Industry 4.0 on their business models whatsoever.
forward four SME categories summarized in the following typology, Preliminary stage planners (6): Contrarily to the first group, the
which are designed to support practitioners in analyzing their own SMEs in the second group perceive a potential for themselves through
positioning towards Industry 4.0. Industry 4.0, while acknowledging their current unpreparedness for
Craft manufacturers (26): A first response is that of companies implementing new technologies. Their motivation leads them to expect
stating their disinterest towards Industry 4.0, based on their structural Industry 4.0 implementation in the mid- to long-term, stating that they
and manufacturing characteristics. Those SMEs were grouped under require up to 15 years for implementation. Recognizing that an initial
this category, which employ a high degree of human labor and, which stage for Industry 4.0 is the automation of manufacturing, the pre-
use flexible production equipment with little automation, as they do not liminary stage planners are currently undergoing this phase. For such
currently provide the right organizational setting for Industry 4.0. The companies, Industry 4.0 does not have an impact on their business
SMEs in this group are not only characterized by a lack of prerequisites, models at present, yet changes are envisioned. What delineates those
but also by a lack of motivation towards new technologies and towards companies from the first group is their interest in technological
10
advances in the context of Industry 4.0 and their curiosity towards models, as well as aiding companies in strengthening their interaction
future business model innovations. with customers and reaching new customers through individually-tai-
Users in value creation (20): A third SME group solely envisions lored value offers. The paper shows that the consideration of such
the usage of Industry 4.0 in their value creation processes, often tar- business model innovations generates benefits for SMEs that counteract
geting benefits such as production process efficiency and efficient data the perceived challenges, accelerating Industry 4.0 implementation.
exchange with customers and suppliers. As interviewees in this group The article concludes by acknowledging several limitations con-
frequently mention, large OEM customers accelerate changes and drive cerning methodology and findings. First, the qualitative nature of the
Industry 4.0 forward, by implementing it in own production facilities study does not allow generalizability, a limitation that is attenuated by
and demanding their suppliers to comply with new technological re- interviewing a large number of companies. As well, data triangulation
quirements. To quote one interviewee “Large companies call the shots and and systematic analysis increase the reliability of the findings. Second,
suppliers have to conform”. The findings show that SMEs in this group as Industry 4.0 is an emerging field in both research and corporate
often fear being driven out of the market, if they do not match customer practice, we recognize the earliness of the research. Future investiga-
requirements concerning automation, digitization, and connectivity. tion is encouraged to explain how Industry 4.0 longitudinally trans-
For those reasons, the reactive followers in this group mainly envision forms the business models of the organizations that implement CPS,
value creation innovations in their own production. which at the time of the study is not unambiguous. Third, the study
Full-scale adopters (16): The SMEs in this final group are highly acknowledges that single informant bias can be a concern, as only one
determined to profit from Industry 4.0, viewing it as the best way to senior staff member per company participated in each interview. Future
remain or become industry leaders. Such companies already have high research is encouraged to avoid such concerns by conducting secondary
automation degrees, which allows them to perceive opportunities ra- interviews with multiple informants from and outside the teams of the
ther than threats from Industry 4.0. What is striking about this strategy main interviewees. A fourth limitation of the article is that the inter-
is that proactive adopters are interested in supporting and equipping views were restricted to SMEs, leaving a gap as to the perspective of
other companies with tools for Industry 4.0, hereby preparing to act as large organizations on Industry 4.0. Future studies can capture this
providers or user/providers. As Industry 4.0 is expensive to implement perspective, in order to understand how the effect of Industry 4.0 on the
and thus challenging for many smaller SMEs, the development of so- relation between SMEs and large companies influences the formers'
lutions by SMEs for SMEs can be a feasible option. This creates possi- business models.
bilities for the proactive adopters to pursue innovations across all three Moreover, future research can analyze how Industry 4.0 affects the
business model elements, throughout value creation, offer, and capture. cooperation between companies from different industries, as com-
plementing abilities in value creation become increasingly important.
6. Conclusions, limitations, and future research Through grounded theory, scholars can develop novel theoretical and
conceptual approaches for industry-specific business model effects of
By highlighting four response strategies to Industry 4.0, the paper Industry 4.0, for which the sample did not provide the fitting context, as
shows that it is essential for SME managers to understand the different the respondent SMEs were not evenly distributed across the three in-
ways for approaching this phenomenon. Further, reflecting upon the dustries. As well, Industry 4.0 provides a new setting for studying the
own company's positioning helps to understand how to derive benefits diffusion of industry boundaries, enabling future researchers to provide
from Industry 4.0. Especially the positioning as user and/or provider of generalizable results as to how companies transfer or extend their
Industry 4.0 has a large impact on SME business models. The present business models from manufacturing to ICT and vice-versa. Finally, the
study shows several possibilities for manufacturing SMEs to innovate results show that most interviewed SMEs are interested in im-
their business models through Industry 4.0. While not disregarding the plementing Industry 4.0. Yet particularly in SMEs, the inadequate im-
benefits brought by value creation innovations, the study encourages plementation of new technologies severely limits a wide-scale accep-
SME managers to explore further forms of business model innovation. tance thereof, as shown in previous research (Huang et al., 2013). The
Those refer to the creation of customer-driven, rather than product- present study therefore encourages future studies to qualitatively and
oriented innovations. Moreover, Industry 4.0 supports the introduction quantitatively assess the implementation steps of Industry 4.0 in man-
of value capture or monetization innovations, such as pay-per-use ufacturing SMEs.
Appendix A
Table 3
Organizational and personal characteristics of respondents (N = 68).
No. Industry Yearly (2016) revenue in € No. of employees Interviewee function
1 Automotive supplier 47.800.000 265 CTO

2 Automotive supplier 45.000.000 179 Head of sales
3 Automotive supplier 40.000.000 100 Head of manufacturing
4 Automotive supplier 39.610.000 233 Head of logistics
6 Automotive supplier 34.040.000 200 Assistant to CEO
7 Automotive supplier 29.800.000 210 IT department
9 Automotive supplier 26.000.000 130 CEO
15 Automotive supplier 8.600.000 55 Logistics department
11

25 Automotive supplier 1.500.000 10 Head of quality management
27 Automotive supplier 650.000 14 CEO
28 Automotive supplier 450.000 12 CEO
29 Electrical engineering and ICT 9.500.000 65 Head of sales
30 Electrical engineering and ICT 7.900.000 25 Assistant to CEO
31 Electrical engineering and ICT 6.400.000 40 Sales department
32 Electrical engineering and ICT 1.750.000 10 Head of R&D
33 Mechanical and plant engineering 15.000.000 120 CTO
34 Mechanical and plant engineering 13.800.000 135 Controlling department
35 Mechanical and plant engineering 13.000.000 25 Head of quality management
36 Mechanical and plant engineering 4.570.000 55 Head of sales
37 Mechanical and plant engineering 4.000.000 34 Sales department
39 Mechanical and plant engineering 40.630.000 130 Head of manufacturing
40 Mechanical and plant engineering 40.060.000 250 CEO
43 Mechanical and plant engineering 38.100.000 160 Manufacturing department
45 Mechanical and plant engineering 33.000.000 230 Head of R&D
46 Mechanical and plant engineering 30.700.000 235 Head of strategy
47 Mechanical and plant engineering 27.600.000 230 HR department
49 Mechanical and plant engineering 23.630.000 175 Head of manufacturing
67 Mechanical and plant engineering 1.350.000 10 Engineering department
68 Mechanical and plant engineering 400.000 5 CEO
Appendix B
Table 4
Interview guideline.
Part I 1) What is your position and what are your functions in the organization?
2) Since when are you active in this role?
3) What specific tasks and areas of responsibility does your position encompass?
Part II 4) How familiar are you with the term “Industry 4.0”? What is your understanding of it?
5) Do you see Industry 4.0 as a sum of adaptions in supply chain connectivity and digitization or as an outright Industrial Revolution?
12
6) Is Industry 4.0 already relevant for your organization? If not, in which timeframe do you see Industry 4.0 as relevant to you? (short;
mid-term; long-term; irrelevant)
7) Which challenges do you see for yourself as an SME regarding Industry 4.0?
a) low standardization
b) highly individual customer demands
c) small batch sizes
d) costs and implementation effort
e) further?
8) Do you perceive your company as a future user of Industry 4.0 solutions or as a future provider thereof? (Both?)
9) In which of the following areas can Industry 4.0 improve your operations?
a) speed, reaction capacity and flexibility
b) production control and documentation
c) internal and external connectivity
d) automation
e) further?
10) Is Industry 4.0 relevant to your customers or competitors?
11) Which trends or developments do you think will have a substantial influence on the adoption of Industry 4.0 (in SMEs)?
Part 12) In which of the following areas of your business model do you expect Industry 4.0-driven changes and can you describe those
III changes?
a) Value offer: the products and services you offer
b) Value capture: customers and customer interaction
c) Value capture: methods of payment
d) Value creation: partners and suppliers
e) Value creation: production facilities and the corresponding workforce
13) Are you considering the implementation of an innovative business model derived from Industry 4.0 or rather the extension of your
current business model*?
*an innovative business model is one that:
a) provides products and/or services, which the company was not able to provide before and does so
b) by either reaching new customers or increasing the demand from current customers
14) Do you feel that your company internally drives the Industry 4.0-related changes on your business model or that those changes are
required by the market?
Appendix C
Table 5
Excerpt of the coding table.
No. Answer (English translation) Content reduction Codes

(question-
company)
4-1 Industry 4.0 is a broad term. I assume that even the • Fully-digitalized connectedness (between supplier Suitable
people who are working on it still have to figure out and large customers) understanding of the
towards what they are heading. In our company, we • Industry 4.0 driven by large companies term
basically mean through Industry 4. The full digital • Large companies call the shots
connectedness. This is at least what the large enterprises • Suppliers have to conform
aim for – they want fully transparent calculations and
this means that eventually the smaller firms play the role
of the servant for the large ones.
5-32 Industry 4.0 represents a revolution, as entire processes • Revolution, as entire processes become more Industrial Revolution
are improving through digitization. For instance, you can efficient through digitization
evaluate the status of your machinery through sensors • E.g., sensors which enable preventive
and you can coordinate the preventive maintenance by maintenance
enabling your machine to independently contact a service • Customer perspective: automated reordering
center. You could also simplify the processes for your through a shared interface with suppliers and
customers, so that orders do not run through the usual simplifies repeated purchases
channels anymore, but through online interfaces. When
the production department needs something, through
Industry 4.0 the order can reach the supplier without
human intervention, up to the point, that the warehouse
itself provides the articles and takes the orders directly in
the system.
6-39 We don't want to shut ourselves off to the whole thing, but • Relevant (in two–five years) Industry 4.0 planned
use it when it makes sense. I would say that in the next in the short-to mid-
two to five years we will have implemented a few things, term (up to five years)
13
particularly in the control system unit, i.e. manufacturing

control. The technologies are not yet mature or affordable
enough to be deployed and combined with software in
small firms with 24 employees, like us.
6-41 We are engaged in this topic since around 2007. At the • Relevant (since 2007) Company already
time, we introduced an MES system and began to gather • 2007: MES system ≥ Information from several pursuing Industry 4.0
real-time data from individual machines, but only for a machines captured in real time
part of the machine park. In 2013 we began to do fine- • 2013: Based on this information, fine-tuning of
tuned control based on that information and have been machines possible
since then participating in the ProSense Industry 4.0 • 2015: 35 further machines connected online to
research project as a user company. This year we will fine-tune control systems
connect further 35 machines online, so that we can • Participant in ProSense research project
include more real-time data in the control systems. And • Industry 4.0: lengthy and expensive undertaking
this is what I mean; it is a lengthy process, in which we
have been involved since several years.
11-45 Cyber criminality. If you're not approaching the topic with • Industry 4.0 opens new doors for cyber Cyber-criminality
the necessary responsibility, new doors for cyber criminality
criminality open up. There is the interplay with dubious • A company is not only responsible for itself, but
elements that makes companies not only responsible for for the other ones linked to it as well
themselves, but also for all companies connected to them. • A new ethical approach is needed for Industry
Also, the question arises, how to manage the increasing 4.0, as for all technological advances
machine autonomy in case of hazardous machines. You
need people, who understand these changes and who
integrate them in a new ethical approach, which is always
important when you have technical progress.
12-66 a) no application, b) yes, c) we already use reverse • All areas except a) 12-b)
invoicing, so we don't send out bills anymore, but our • b) and c): Customers pay only for what they are 12-c)
customers only retroactively pay for components and currently using, no more invoices issued but 12-d)
pieces, which they have already used in their instead payments managed via EDI 12-e)
manufacturing activities […] so that would be • e) each employee is able to see which tasks he/
expenditure-based payments, not invoice-based she performed at each machine, the duration of
payments. d) we do cooperation with machine builders, the tasks, which commands were given, and
so yes e) each employee is able to see the tasks he/she recognize failures
performed at each machine, how long the task took,
which commands were given and where the malfunctions
were.
Appendix D
Table 6
Coding manual.
Question Codes
no.
1 CEO/CTO/Head of sales/Head of manufacturing/Head of R&D/Head of logistics/Head of quality management/Head of strategy/

Assistant to CEO/Logistics/Manufacturing and sales/Engineering/Controlling/HR/IT
2 Period of employment
3 Individual areas of responsibility
4 • Detailed knowledge of the Industry 4.0 term and its underlying ideas
• General knowledge of the Industry 4.0 term
• Bare awareness of the Industry 4.0 term
5 • Industrial Revolution
• Sum of adaptions
• Depends on each individual company
• No answer
6 • Company already pursuing Industry 4.0
• Industry 4.0 planned in the short-to mid-term (up to five years)
• Industry 4.0 likely in the long term (six to fifteen years)
• Industry 4.0 not of interest or no information on Industry 4.0
7 • 7-a) low standardization
• 7-b) highly individual customer demands
• 7-c) small batch sizes
• 7-d) costs and implementation effort
• 7-e) further?
14
• No challenges experienced
8 • User
• Provider
• Both
• None
9 • 9-a) speed, reaction capacity, and flexibility
• 9-b) production control and documentation
• 9-c) internal and external connectivity
• 9-d) automation
• 9-e) further
10 • For customers primarily
• For competitors primarily
• For both
• For none
• Unknown
11 • Changes in employee requirements and qualifications
• Cyber criminality
• Data security and reliability of data transfer
• High-speed internet
• High manufacturing process transparency (seen as detrimental to suppliers)
• Reactions from labor unions and works councils
• Smart devices used in manufacturing
• SMEs should be supported during implementation
12 • Company does not plan for Industry 4.0, thus no business model implications
• Changes across the business model expected, yet no further specification
• 12-a) Value offer: product and service offer
• 12-b) Value capture: customers and customer interaction
• 12-c) Value capture: methods of payment
• 12-d) Value creation: partners and suppliers
• 12-e) Value creation: production facilities and the corresponding workforce
• No information
• No significant changes
• Business model innovation
• Business model extension
• Neither innovation nor extension
• No statement possible
• Internally
• Externally
• Both
• No influences currently
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Technological Forecasting & Social Change 132 (2018) 2–17

Contents lists available at ScienceDirect

Technological Forecasting & Social Change

Fortune favors the prepared: How SMEs approach business model T

1. Introduction from the integration of CPS have a revolutionary impact on industrial

Author (year: page) Term Deﬁnition

Value creation Value oﬀer Value capture

Production equipment (26) Products (20) Customer groups (11)

Fig. 1. Cross-case analysis of predominant business

Fig. 2. Stage model of manufacturing SMEs in the context

Motivation Innovations in Full-scale adopters

„We’ve always done „For us, Industry 4.0

No. Industry Yearly (2016) revenue in € No. of employees Interviewee function

1 Automotive supplier 47.800.000 265 CTO

16 Automotive supplier 7.800.000 66 CEO

No. Answer (English translation) Content reduction Codes

particularly in the control system unit, i.e. manufacturing

1 CEO/CTO/Head of sales/Head of manufacturing/Head of R&D/Head of logistics/Head of quality management/Head of strategy/

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