Int. Journal of Business Science and Applied Management, Volume 16, Issue 2, 2021
Component suppliers in the commodity battle: Can digital
technology in multi-tier supply chains help to transform
liabilities into opportunities?
Tobias D. Herbst
School of Business Administration and Economics, Osnabrück University
Rolandstr. 8, Osnabrück, 49078, Germany
Tel: +495419696147
Email: toherbst@uni-osnabrueck.de
Abstract
This conceptual study analyzes how digital technologies can create opportunities for component
suppliers in multi-tier supply chains facing the issue of commoditization and it develops a strategic
framework based on prior studies. This study finds that modularity facilitates the understanding of the
dynamics of commoditization and knowledge sharing. Furthermore, modularization drives the
asymmetric distribution of information in a multi-tier supply chain. Finally, digital technologies can
offer strategic opportunities for targeting different stages of the value chain. Component suppliers
should evaluate the criticality of products in new business models and advanced services to reduce the
complexity of the landscape of strategic options and, thus, reduce wrong decisions. Managers should
encourage general information sharing and open data exchange in a multi-tier supply chain. They
should focus on vertical and horizontal partnerships and collaborations to foster the benefits of digital
technologies. Conclusively, component suppliers should cooperate to build a counterweight to original
equipment manufacturers in the vertical partnership. This study is the first to integrate the benefits of
commodities and digital technologies in a strategic framework. It contributes to the literature on
competition in the background of commoditization by outlining the concept of information asymmetry
within a multi-tier supply chain driven by modularity. Thus, it advances the literature on digital
technology and commoditization.
Keywords: multi-tier supply chain, strategy, modularity, servitization, commoditization, digitalization,
knowledge-based view
Acknowledgements:
The author thanks J. Piet Hausberg and Michael Holzapfel for their helpful
comments and discussions. He is also grateful to the editors and the anonymous reviewers for their
valuable feedback. All errors remain the author’s.
This research received no grant from any funding agency in public, commercial, or not-for-profit
sectors.
Tobias D. Herbst
23
1. INTRODUCTION
Manufacturing firms in multi-tier supply chains face highly competitive, rapidly changing, and
severe market conditions (Tate, Ellram, Schoenherr, & Petersen, 2014). Furthermore, the
standardization of processes and products and the development of interfaces can reduce component
suppliers’ ability to offer added value (Cabigiosu, Zirpoli, & Camuffo, 2012; Camuffo, 2004).
Therefore, component suppliers often lack the opportunity to differentiate their offerings in the light of
reduced innovation awareness (Gebauer, Fleisch, & Friedli, 2005; Ulaga & Reinartz, 2011).
Specifically, the lack of innovation can lead to an increasingly homogenous offering, with no product
differentiation that fosters increased competition (Reimann, Schilke, & Thomas, 2010). Increased
standardization within a multi-tier supply setting contributes to commoditization. Commoditization
refers to a competitive environment with low product differentiation, which leads to interchangeable
products, high price sensitivity among the buyers, low switching costs, and high industry stability
(Reimann et al., 2010). Since products become commoditized (even in knowledge-intensive industries)
in shorter cycles after investing in new capabilities and production assets, it is challenging to generate
sustainable profits (Uehara et al., 2018). Hence, innovation is vital to counteract commoditization and
generate new value continuously to ensure sustainable profit and competitive advantage (Gomes &
Wojahn, 2017; Martín-de Castro, Delgado-Verde, Navas-López, & Cruz-González, 2013). In this
context, firms offer more services to differentiate their offerings (Gebauer et al., 2005; Ulaga &
Reinartz, 2011). In the case of manufacturing firms, they switch focus from merely adding services to
making services their key offering (Kastalli & Van Looy, 2013; Smith, Maull, & Ng, 2014). A firm’s
transformation from being solely a manufacturer to a firm offering increased service offerings is called
servitization (Baines & Lightfoot, 2014). While many scholars have explored the benefits of
servitization, others warn about the disadvantages of generalizing the servitization approachthat is,
servitization could lead to reduced profits (Benedettini, Neely, & Swink, 2014; Gebauer et al., 2005).
Recent studies have revealed that, to cope with the complexities and risks of servitization, firms are
increasingly relying on their ability to leverage digitalization (Parida, Sjödin, & Reim, 2019).
Digitalization has been widely discussed in past research (Baines et al., 2007; Baines & Lightfoot,
2014; Bharadwaj, El Sawy, Pavlou, & Venkatraman, 2013; Mathieu, 2001; Yoo, Boland, Lyytinen, &
Majchrzak, 2012). Scholars have identified multiple advantages of applying digital technology (e.g.,
information technology, components such as sensors that generate digital output, and data analytics) to
firm operations, including the application of new product or service innovations, utterly novel business
models, and options for value creation (Bharadwaj et al., 2013; Hess, Benlian, Matt, & Wiesböck, 2016;
Pagani & Pardo, 2017; Svahn & Mathiassen, 2017). However, studies have also indicated the possible
challenges of applying digital technologies in multiple domains (e.g., Singh & Hess, 2017; Svahn,
Mathiassen, Lindgren, & Kane, 2017). Component suppliers may perceive digitalization as an
opportunity to innovate and consider their position within the multi-tier supply chain as a strength for
changing the supply chain game in their multi-tier supply chain. Therefore, it is crucial to demonstrate
how the described concepts and digitalization can be linked to offer a comprehensive framework for
facilitating a competitive advantage for component suppliers.
Prior studies have focused on firms’ abilities to innovate and create competitive advantages
(Porter, 1985; Sirmon, Hitt, & Ireland, 2007). A manufacturing firm’s challenge to leverage knowledge
implies the need for a more network-oriented collaboration within the multi-tier supply chain (Adner &
Kapoor, 2010; Pagani, 2013). Adner and Kapoor (2010) refer to an ecosystem perspective, comprising
all stakeholders affected by innovations. However, despite acknowledging the benefits, previous
studies have focused on unilateral relationships (e.g., buyer-supplier relationship, bargaining power,
and the comparison of single-tier value creation stages) and neglected the impact of the relationships
within a multi-tier supply chain (Adner & Kapoor, 2010). Furthermore, as specified by Vial (2019),
prior research has often focused on particular digitalization issues involving comprehensive strategies,
innovation strategies, organizational structures, or processes. However, no specific frameworks have
dealt with detailed value creation stages. Therefore, no theoretical framework can explain how
component suppliers can use digital technologies to escape the commodity battle. A framework for
joining the concepts and for appreciating component suppliers’ contexts and market settings could
enable firms to adopt an efficient approach (e.g., resource allocation) for the strategic development of
their current positioning and value creation, thus contributing toward creating competitive development
advantages in various market settings.
It is against this backdrop that this study develops a strategic framework for component suppliers
to consider digitalization as an opportunity and to realize strategic options in an exemplary manner to
foster competitive advantage. First, this study reviews relevant literature in the field of innovation
capability, modularity, commoditization, digitalization, and advanced services. Second, it derives a
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new concept of information sharing in multi-tier supply chains enabled by digital technology. Third,
based on these insights, strategic implications are drawn for component suppliers to leverage their
position.
This study focuses on capital- and knowledge-intensive, slow-moving (in terms of technological
innovation) industries that feature long product life cycles and the highest safety requirements. Thus,
this study presents a multilateral approach, encompassing a multi-tier perspective on innovations (i.e.,
original equipment manufacturer [OEM], module supplier [tier-1], and component supplier [tier-2]
perspectives). First, it extends the management literature to explicitly take account of the strategic
implications of digital technologies for component suppliers in a multi-tier supply chain. Second, it
improves the understanding and transparency of digital technologies as a source of disruption by
clearly showing their impact on the competitive landscape in a multi-tier supply setting (Loebbecke &
Picot, 2015; Pagani, 2013). Third, this study sheds light on strategic responses to digital disruption and
provides a clear framework for how digital technologies can be considered a risk by increasing
commoditization and disadvantaging the companies that want to remain in their established position. It
also shows how component suppliers can adjust their strategic orientation to use digital technology to
enable a profitable new positioning within the existing multi-tier supply chain. Therefore, this study
answers a call for research investigating firms’ strategies and information system strategies (Bharadwaj
et al., 2013) and how digitalization strategies can be integrated into firms (Matt, Hess, & Benlian,
2015). Finally, it explains why and how firms need to leverage digital technologies to enable new value
creation paths by leveraging data in defined networks as a strategic response (Vial, 2019). Component
suppliers facing commoditization have to understand the phenomenon’s drivers and digitalization
benefits in a multi-tier supply chain.
The rest of the study is structured as follows. Section 2 presents the theoretical background of the
research. Section 3 describes the fundamental concepts and reviews the literature. Section 4 presents
the conceptual implications and an illustrative example that applied the strategic framework in the
railway industry, and Section 5 provides the conclusion.
2. THEORETICAL BACKGROUND
Various contextual determinants at the product level and outsourcing initiatives, combined with
globally oriented procurement activities, have led to the emergence of more complex multi-tier supply
chains (Contractor, Kumar, Kundu, & Pedersen, 2010). A multi-tier supply chain consists of the end
customers, OEMs, module suppliers, and component suppliers (Figure 1). End customers are the final
product users, OEMs provide the finished products to end customers and source (multiple) modules
from (diverse) module suppliers (tier-1 supplier), and module suppliers source the relevant components
from tier-2 suppliers (component supplier). Components may consist of further parts, referred to as
modules of the module. As a result, firms cooperate in more complex and dynamic networks
comprising multiple firms (Carter, Rogers, & Choi, 2015; Pagani, 2013).
Figure 1: Generic schema of a multi-tier supply chain
Tobias D. Herbst
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Prior research has used the resource-based view (RBV) and the knowledge-based view (KBV) as
lenses to deconstruct firms’ participation and resulting sources of competitive advantage in such multi-
tier supply chains (Barney, 1991; Grant, 1996). The RBV is an essential framework for achieving
competitive advantage. RBV sees a firm’s strategic assets (e.g., resources and capabilities) as the key to
gaining sustainable competitive advantage (Conner & Prahalad, 1996; Grant, 1996). The KBV emerges
from the RBV and focuses on leveraging knowledge management, knowledge-based resources, and
their limitations within a firm (e.g., tangible resources; Gardner, Gino, & Staats, 2012; Gassmann &
Keupp, 2007). KBV highlights knowledge as the most important resource fostering competitive
advantage (Amit & Schoemaker, 1993; Kogut & Zander, 1992; Spender, 1996). Furthermore, previous
studies have demonstrated the link between KBV and innovation, underlining the point that thriving
innovators successfully build and manage knowledge within and outside their own firm’s borders
(Díaz-Díaz, Aguiar-Díaz, & De Saá-Pérez, 2008; Gomes & Wojahn, 2017; Martín-de Castro et al.,
2013; Tamayo-Torres, Gutiérrez-Gutiérrez, Llorens-Montes, & Martínez-Loopez, 2016). Particularly,
the orchestration of resources and assets may result in competitive advantages (Sirmon, Hitt, Ireland, &
Gilbert, 2011). However, the complexity of a multi-tier supply chain has an impact on various
economic parameters (e.g., costs). Consequently, firms are constantly striving to reduce complexity,
and, thus, improve the efficiency of multi-tier supply chains (Choi & Krause, 2006). Furthermore,
confronted by high market uncertainty, competitive intensity, and diverse customer demands,
manufacturers try to reduce overall product and organizational complexity.
Previous studies demonstrate that standardized structures enable modularity to reduce product
complexity by breaking up complex products into smaller systems, bridging coordination and
information exchange needs (Baldwin, 2008; Langlois, 2002; Pil & Cohen, 2006; Sanchez & Mahoney,
1996; Seyoum & Lian, 2018; Sosa, Eppinger, & Rowles, 2003; Worren, Moore, & Cardona, 2002).
Standardized interfaces between components and codified knowledge, and reduced interdependencies
between modules (loosed coupling), enable modularity (e.g., Campagnolo and Camuffo, 2010) and are
vital for outsourcing assets to suppliers and developing hierarchically organized supply chain structures
(e.g., multi-tier supply chain; Cabigiosu et al., 2012; Camuffo, 2004; Zirpoli & Becker, 2011). This
study demonstrates that standardized interfaces lead to commoditization of modules and components.
OEMs increase competitive advantage by focusing on core competencies in a modular environment
(Langlois, 2002). OEMs and module suppliers then transfer value and knowledge to suppliers (Doran,
Hill, Hwang, & Jacob, 2007). However, only specific information related to the dedicated
development-production task is transferred down (Cabigiosu et al., 2012). Thus, component and
commodity suppliers are barely involved in the general product development process and receive no
general system knowledge vital for innovation and differentiation opportunities, which further drives
commoditization (Von Corswant & Fredriksson, 2002; Wynstra, Von Corswant, & Wetzels, 2010).
Hence, modularity further impels asymmetric information distribution within the supply chain.
To ensure continued innovation and improve business performance, firms in various fields (e.g.,
supply chains, sales channels, and processes) should deploy digital technologies (Matt et al., 2015).
Recent research and empirical studies have shown the benefit of digitalization in firms’ internal and
external settings (see Vial ,2019, for an extensive overview). Digitalization enables new business
models (BMs; Cenamor, Rönnberg Sjödin, & Parida, 2017), thus driving servitization and advanced
services (Baines & Lightfoot, 2014; Cenamor et al., 2017; Parida et al., 2019). Specifically, new BMs
enable suppliers to support their customers by fostering innovative activities (e.g., predictive
maintenance schemes using sensors for monitoring tasks) built on digital technologies (Baines &
Lightfoot, 2014; Jabbour, Jabbour, Sarkis, & Filho, 2017; Nobre & Tavares, 2017). Yoo, Henfridsson,
and Lyytinen (2010a) demonstrate that digital technologies allow existing products and services to be
combined in order to provide new digital offerings. Adding various digital technologies to the existing
product portfolio could offer additional innovation potential or generate new value paths (Loebbecke &
Picot, 2015). Further, research often underlines the significance of companies’ data analysis ability
with regard to developing new BMs and product and service combinations; this is even more the case
in the setting of new value paths (Günther, Rezazade Mehrizi, Huysman, & Feldberg, 2017). The
ability to analyze data at the product level is the most critical role of advanced maintenance schemes
(Bressanelli, Adrodegari, Perona, & Saccani, 2018; Gebauer, Gustafsson, & Witell, 2011). Moreover,
in order to offer and use these advanced maintenance schemes, the development of product
knowledgeespecially the product architectureis essential (Baines et al., 2017; Cabigiosu et al.,
2012; Kapoor & Adner, 2012). That said, one disadvantage component suppliers face is the fact that
OEMs primarily define product architecture (Cabigiosu & Camuffo, 2011). However, continuous
outsourcing and a multi-tier set-up increase OEMs’ challenges in analyzing component data and
leveraging it for providing advanced services to customers. Therefore, OEMs are willing to share data
and knowledge when offered an added value by the component supplier, thus enabling innovation on
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the component supplier side (Wang, Sharma, & Cao, 2016). Component suppliers can use the product-
specific and far-reaching data for product and service innovation and differentiation.
When referring to the amount of relevant data within a product component, suppliers can occupy
various modules within a complex product and leverage the information for future product- or service-
specific innovation to gain competitive advantage. Thus, component suppliers can offer vital
knowledge regarding various assets at the component level compared to a single module supplier,
which further reduces OEMs’ coordination efforts. Moreover, digitalization enables the bundling of
module-specific components related to operational performance (e.g., remaining useful life), which in a
service environment enables component suppliers to integrate forward in the supply chain.
3. THEORY AND RESEARCH CONSTRUCTS
3.1 Knowledge sharing supporting innovation capability
Beginning with the well-known work by Penrose (1959), previous literature began to underline the
importance of knowledge that enables competitive differentiation. Over recent years, researchers have
investigated how knowledge or information is transferred within companies and beyond their borders
through a process that is referred to as “knowledge sharing” (Appleyard, 1996; Darroch, 2005;
Loebbecke, van Fenema, & Powell, 2016). Specifically, scholars have emphasized the relevance of
knowledge sharing, the improvement of firms’ innovation capacity, and the fostering of competitive
advantages (Chiu, Hsu, & Wang, 2006; Wang et al., 2016). Scholars have categorized knowledge into
explicit and tacit knowledge (Trkman & Desouza, 2012; von Krogh, 2009; Wang & Wang, 2012). Due
to its codable and articulated nature, explicit knowledge is transferable (by communication or written
documents; Simonin, 1999). Tacit knowledge is non-verbalized, gained by experience, unarticulated,
and cannot be easily transferred (Weick & Westley, 1996). Loebbecke et al. (2016) established a
detailed approach to knowledge sharing with multiple classifications following Matusik and Hill (1998),
who investigated leveraging knowledge to achieve competitive advantage. Nevertheless, this study
focuses on general knowledge sharing. The remainder of the study follows James, Guile, and Unwin
(2013), who distinguish between individual (e.g., firm-specific) and collective knowledge, private and
public knowledge (knowledge owner), component (work element knowledge) and architectural
(general process knowledge) knowledge, and tacit and explicit knowledge. No level is exclusive (e.g.,
architectural knowledge can be private, collective, and tacit; Loebbecke et al., 2016; Matusik & Hill,
1998).
Knowledge sharing, a concept within knowledge management (Foss, Husted, & Michailova, 2010;
Ghosh, 2010), is grounded in the KBV (Wang, Wang, & Liang, 2014). Prior studies have considered
the knowledge sharing process within and across firm boundaries (Ayala, Paslauski, Ghezzi, & Frank,
2017; Conner & Prahalad, 1996; Loebbecke et al., 2016; Wang et al., 2016) and defined it as a process
wherein know-how is transferred (e.g., by communication and interaction) to improve innovation
capability and sustainable competitive advantage (Foss et al., 2010; Wang et al., 2016). As products
become sophisticated and new digital technology emerges, cooperation becomes a vital corporate
strategy (Chen et al., 2017; Feller, Parhankangas, Smeds, & Jaatinen, 2013; Un & Asakawa, 2015).
Loebbecke et al. (2016) emphasize the paradox of sharing knowledge with vertical or horizontal
partners. According to them, though knowledge sharing may contribute to business opportunities (e.g.,
new capabilities), it may negatively affect a firm’s market differentiation and reduce competitive
advantage (Loebbecke et al., 2016). Therefore, firms must focus on both competitive advantages and
the disadvantages of partnerships to secure long-term success (Becerra, Lunnan, & Huemer, 2008;
Trkman & Desouza, 2012).
3.2 Modularity and the commodity battle
3.2.1 Modularity
Reducing the overall product complexity is possible (Seyoum & Lian, 2018) by breaking up
products into modules comprising smaller systems and subsystems (Cabigiosu & Camuffo, 2011). The
decomposition of the product design into different modules is a concept known as modularity, which
allows further characterization of different product designs (Cabigiosu & Camuffo, 2011). Modularity
has been the subject of many systematic investigations (Baldwin & Clark, 1994, 2000; Cabigiosu &
Camuffo, 2011; Frandsen, 2017; Sanchez & Mahoney, 1996; Sosa et al., 2003; Ulrich, 1995).
Following Simon's (1962) work on nearly decomposable systems, scholars have employed modularity
as a general framework to describe different economic phenomena (MacDuffie, 2013; Ponte &
Sturgeon, 2014; Schilling, 2000; Sturgeon, 2002) and analyze organizations and processes (Baldwin &
Clark, 2000; Sanchez & Mahoney, 1996). Modularity has also been frequently discussed in services
Tobias D. Herbst
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and BMs (de Blok, Luijkx, Meijboom, & Schols, 2010; Cabigiosu, Campagnolo, Furlan, & Costa, 2015;
Voss & Hsuan, 2009). Studies have proposed several definitions (Baldwin & Clark, 2000; Ulrich,
1995). Ulrich (1995) defines architectures as modular if a one-to-one mapping of functional elements
and components exists. Baldwin and Clark (2000) describe modularity as a decomposition scheme that
assumes independence across product modules, and high interdependence between the module
components characterizes modules. The former concept is referred to as “loose coupling” and posits
that changes in one module barely impact other modules within the product (Orton & Weick, 1990;
Sosa et al., 2003).
From a practical perspective, modularity adds value by reducing complexity, increasing
outsourcing opportunities, and providing design advantages, thus increasing firmsstrategic flexibility
(Baldwin & Clark, 2000; Ethiraj & Levinthal, 2004; Sanchez & Mahoney, 1996). Specifically,
modularity enables firms to respond more efficiently to environmental shifts, increase the range of
products and services, and increase the firm’s versatility to substitute modules or “mix and match”
(Baldwin & Clark, 2000; Cabigiosu et al., 2015; Garud & Kumaraswamy, 1993; Pil & Cohen, 2006;
Sanchez & Mahoney, 1996; Worren et al., 2002). Furthermore, by using the same module in different
products, firms can employ economies of scale (Baldwin & Clark, 2000). Moreover, modules can be
designed independently, which can reduce the specificity of a module (Baldwin, 2008) and lead to
outsourcing modular product designs and engineering efforts (Baldwin & Clark, 1997; Schilling &
Steensma, 2001; Zirpoli & Becker, 2011). Consequently, Langlois (2002) argues that modular assets
reduce buyer-supplier coordination efforts.
3.2.2 Commoditization and the commodity battle
Preliminarily, this study follows Lager and Blanco's (2010) definition that commodity products
are interchangeable assets of uniform quality and standard specifications, which exhibit low-level
differentiation and are offered by many suppliers. Given the lack of differentiation, firms compete
based on price (Greenstein, 2004). The low degree of differentiation leads to an increasingly
homogeneous product range and comparatively low switching costs for price-sensitive customers; this
circumstance is referred to as commoditization (Reimann, Schilke, & Thomas, 2010). Commoditization
thus describes a competitive environment in which the product offerings of many supply alternatives
are increasingly aligned from the customer's perspective (Davenport, 2005). This may affect functional
products, which Lager and Blanco (2010) define as differentiated assets. Differentiated products have
less interchangeability, prices can be set on a cost-plus basis, and suppliers are limited (Lager & Blanco,
2010). Thus, merging both concepts (commodity and functional products) into a process-oriented
approach, the commodity battle can be defined as firms’ approach to staying competitive by
contributing to the product differentiation factors perceived by customers (Lager & Blanco, 2010).
The commodity battle has two perspectives: commoditized products trying to achieve product
differentiation or functional products trying to avoid commoditization via continuous innovation (Lager
& Blanco, 2010; Linn, 1984). This effort may secure profitability (Matthyssens & Vandenbempt, 2008;
Narver & Slater, 1990; Rangan & Bowman, 1992) and address price wars (Davenport, 2005; Guiltinan
& Gundlach, 1996; Heil & Helsen, 2001).
3.3 Digitalization leading to advanced services approaches
3.3.1 Business model innovation and servitization
Researchers have increasingly emphasized the importance of business model innovation (BMI) to
achieve sustained competitive advantage and increase firm performance (Bashir & Verma, 2017; Bock,
Opsahl, George, & Gann, 2012; Bogers, Hadar, & Bilberg, 2015; Chesbrough, 2002; Chesbrough, 2010;
Foss & Saebi, 2016; Spieth, Schneckenberg, & Ricart, 2014; Wei, Yang, Sun, & Gu, 2014). BMI is a
novel BM or changes to established critical principles and architecture of a BM (a product or service;
Bock et al., 2012; Foss & Saebi, 2016). Furthermore, BMI is a conceptual configuration wherein firms
employ new ideas (e.g., technologies for product or service development) regarding established ways
of doing business (Baden-Fuller & Haefliger, 2013; Osterwalder, Pigneur, & Tucci, 2005). Thus, it
encompasses major trades and BM novelties, including innovative technology (Chesbrough, 2002,
2010; Foss & Saebi, 2016) or the foundation of innovation itself (Snihur & Wiklund, 2019). Moreover,
by adding services to their established BMs and product portfolios, many firms innovate in direct
response to customers’ needs to achieve differentiation (Kowalkowski & Brehmer, 2008).
Servitization as an approach necessitates that firms relate services directly to their products to
extend their traditional product portfolios (Baines et al., 2007). There has been an increase in research
focusing on service-dominant business logic (Vargo & Lusch, 2016). Scholars have discussed
servitization characteristics with regard to the synergies of these characteristics (Baines & Lightfoot,
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2014; Lenka, Parida, & Wincent, 2017; Mathieu, 2001; Oliva & Kallenberg, 2003; Parida, Sjödin,
Wincent, & Kohtamäki, 2014; Tukker, 2004). Mathieu (2001) builds his topology via two key variables
(organizational focus and service specificity), and Tukker (2004) develops his theory via eight so-
called product service systems (PSSs; e.g., ranging from asset use to performance). Although Tukker's
(2004) PSS approach is acceptable (Baines et al., 2017; Bocken, Short, Rana, & Evans, 2014; Reim,
Parida, & Örtqvist, 2015; Smith et al., 2014), an arguable weakness is the generalization of the
categories (Parida et al., 2014). Thus, this study employs Oliva and Kallenberg's (2003) service-
oriented categorization for servitization, an impact-oriented view on whether firms offer customized
services or service supported products that address customer services. The company providing the
service may either offer a combination of products and services or directly impact customers’ business
processes (Kowalkowski, Gebauer, & Oliva, 2017; Kumar & Reinartz, 2016; Reim et al., 2015; Ulaga
& Reinartz, 2011). Accordingly, the primary goal is to achieve customer process integration to enable
the highest possible differentiation.
Servitization offers many benefits to manufacturing firm performance via differentiation, creating
value by addressing customer needs, and achieving sustainable competitive advantage (Baines,
Lightfoot, Benedettini, & Kay, 2009; Gebauer et al., 2011; Oliva & Kallenberg, 2003; Parida et al.,
2014). However, it is no panacea for solving the firm’s business challenges. Specifically, scholars
discuss the interrelation between service-oriented BMI and performance decline (e.g., reduced profit)
of the service provider (Benedettini et al., 2014; Visnjic, Wiengarten, & Neely, 2014). Studies refer to
this interplay as the “servitization paradox,” and the associated risk is called the risk of servitization
(Benedettini et al., 2014; Cenamor et al., 2017; Fang, 2008; Gebauer et al., 2005; Kastalli & Van Looy,
2013). Although many studies recognize the importance of conceptualized service approaches, a
generalized approach to successfully implementing servitization is missing (Coreynen, Matthyssens, &
Van Bockhaven, 2017).
3.3.2 Digitalization, advanced services, and platforms
Many scholars acknowledge that digitalization’s benefits enabled servitization approaches to
overcome the servitization paradox (Ardolino et al., 2018; Kindström & Kowalkowski, 2014;
Rymaszewska, Helo, & Gunasekaran, 2017). This study defines digitalization as the “use of digital
technology (e.g., sensors) to enable BMI and contribute to a firm’s value proposition via digitized
product information” (Gobble, 2018; Parida et al., 2019; Roblek, Meško, & Krapež, 2016).
Accordingly, as defined in this study, digital technologies suit the SMACIT acronym (social, mobile,
analytics, cloud, internet of things) coined by Sebastian et al. (2017). However, it is not limited to one
field of technology in an operational setting but rather a combination of technologies or applications
(Bharadwaj et al., 2013). Scholars refer to the need to apply digital technologies in an operative setting
(Loebbecke & Picot, 2015). Firms can combine digital technologies with existing products and services
to enable new offerings (Yoo et al., 2010a). By focusing on services (Barrett, Davidson, Prabhu, &
Vargo, 2015), firms may offer digital services by implementing digital technology, which may extend
their service portfolio (Coreynen et al., 2017; Dalenogare, Benitez, Ayala, & Frank, 2018; Vendrell-
Herrero, Bustinza, Parry, & Georgantzis, 2017) and monitor product conditions and health on a
digitally accessible and shareable system. Thus, firms may receive real-time information from
monitored data (e.g., usage, status, location; Ardolino et al., 2018; Baines & Lightfoot, 2014; Spring &
Araujo, 2017), resulting in increased customer proximity (Rymaszewska et al., 2017) to bypass the
OEM. Furthermore, service suppliers could use this customer-specific information to leverage their
situation “from bargaining to communication” (Baines & Lightfoot, 2014; Bressanelli et al., 2018;
Lenka et al., 2017; Rust & Huang, 2014). Thus, firms can derive useful life and apply maintenance
schemes via specific asset information (e.g., condition-based maintenance; Baines & Lightfoot, 2014;
Jabbour et al., 2017; Nobre & Tavares, 2017).
Oliva and Kallenberg (2003) add to the literature above by referring to service suppliers
development from services supporting a product to more advanced services and solutions (e.g., flexible
maintenance schemes). Given digitalization (Lenka, Parida, Sdin, & Wincent, 2018; Rönnberg Sjödin,
Parida, & Kohtamäki, 2016), scholars define advanced services as “a capability delivered through
product performance, adding critical value to customers’ business processes, and often featuring;
relationship over extended life cycle, extended responsibilities, and regular revenue payments” (Baines
& Lightfoot, 2014, p. 13). Incentivized contracting set-ups (e.g., power-by-the-hour) support advanced
services (Baines & Lightfoot, 2014), where the service supplier assumes responsibility for customer
availability or asset uptime. Scholars have examined the positive impacts of a platform approach on
advanced services (Bask, Lipponen, Rajahonka, & Tinnilä, 2010; Cenamor et al., 2017; Voss & Hsuan,
2009), where digital technology (based on a modular architecture) enables firms to flexibly use
modules to increase their offerings and keep complexity to a minimum (De Reuver, Sørensen, &
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Basole, 2018; Sawhney, 1998; Thomas, Autio, & Gann, 2014; Yoo et al., 2012; Yoo, Henfridsson, &
Lyytinen, 2010b). The ability (i.e., knowledge) to analyze extensive data using analytics and
pronounced analysis for justified decision-making is the most critical (Bressanelli et al., 2018; Gebauer
et al., 2011). As digitalized products become increasingly complex, manufacturing firms have to
develop new capabilities, engage in external cooperation, and share information to leverage advanced
services (Hakanen & Rajala, 2018; Leminen, Rajahonka, Wendelin, & Westerlund, 2019).
Cenamor et al. (2017) posit that platforms should escape the servitization paradox by integrating
digitalization with the general ecosystem approach. Platforms form the basis for exchanging digital
products and services regardless of the value-added stage or industry. This gives them a strong
influence on the existing market model (Tiwana, Konsynski, & Bush, 2010). More specifically, Lusch
and Nambisan (2015) underline the relevance of service platforms for increasing the flexibility of
resources, allowing an efficient exchange of services to enable further innovation. However, firms need
to develop integrative capabilities, as multiple actors from multiple industries and value-creation stages
participate in platforms (Jacobides, Cennamo, & Gawer, 2018). Hence, in this network of multiple
stakeholders from different industries and stages of the value chain, different relationships and interests
need to be managed to offer the customer added value (Li, Su, Zhang, & Mao, 2018; Tan, Pan, Lu, &
Huang, 2015).
Scholars have identified specific value-adding roles in this field: front- and back-end units
(Cenamor et al., 2017). Front-end units are responsible for offering services to the end customer. Back-
end units cater to the operational development (e.g., design, development, and production) of a service
(Cenamor et al., 2017; Gebauer & Fleisch, 2007; Grönroos, 2011; Oliva & Kallenberg, 2003). Parida et
al. (2014) specify communication between the two roles as vital for servitization success. Likewise,
studies on platforms distinguish between two distinctive actors: the orchestrator and the offering
builder (Aarikka-Stenroos & Ritala, 2017; Bask, Lipponen, Rajahonka, & Tinnilä, 2011; Thomas et al.,
2014). The orchestrator (defined as the platform owner, designer, and provider) coordinates
interactions within the platform network and is responsible for end customer offerings (Cenamor et al.,
2017; Ikeda & Marshall, 2019). The offering builder assumes the back-end unit’s role and adds value to
the offerings (Cenamor et al., 2017). This study employs platform roles as a construct for inter-firm
cooperation based on digital technology.
As noted above, manufacturing firms can improve their competitive advantage via servitization.
However, operating within an established multi-tier supply chain, actors (e.g., OEM and tier suppliers)
need to defend their current position, face the competition (horizontal or vertical), offer advanced
services, and dominate the new network (Dijkman, Sprenkels, Peeters, & Janssen, 2015; Kiel, Arnold,
& Voigt, 2017; Vendrell-Herrero et al., 2017). Thus, firms’ strategies on networks, partnerships, and
external factors should be highly prioritized and defined ex-ante (Kiel et al., 2017; Tee, Davies, &
Whyte, 2019).
Emerging studies on servitization focus on the specific benefits of digital technology tools (e.g.,
sensors, remote monitoring, cloud computing, big data, and predictive analytics; Ardolino et al., 2018;
Bressanelli et al., 2018; Grubic, 2014). However, the connection between both servitization and
digitalization has garnered little attention. Furthermore, previous studies have neglected
commoditization and its significant effect on competitive advantage. Thus, this study contributes to the
literature by integrating these concepts and deriving key implications for a conceptual framework.
Moreover, scholars have considered value co-creation with customers enabled by digital technology,
which might lead to an unclear allocation of roles and responsibilities within a supply chain and
ambiguities between actors, requiring role flexibility (Lenka et al., 2017; Rönnberg Sjödin et al., 2016).
Thus, using the theoretical model provided in Figure 2, this study contributes toward understanding
servitization and platform roles by further describing the interactions between actors offering advanced
services to end customers.
Int. Journal of Business Science and Applied Management / Business-and-Management.org
30
Figure 2: Theoretical model
4. IMPLICATIONS FOR COMPONENT SUPPLIERS: DIGITAL TECHNOLOGY IN
MULTI-TIER SUPPLY CHAINS
4.1 Digital technology: The window of opportunity to reduce the information asymmetry in a
multi-tier supply chain
Megatrends and diverse, rapidly changing market conditions that are contributing to diverse
customer needs have resulted in high-level complexity for manufacturing firms in knowledge-intensive
industries. By leveraging the benefits of modular concepts, OEMs focus on the primary managerial
purposes of modularization: managing complexity, parallel development, production, and the flexibility
to react efficiently to variable market needs (Baldwin, 2008; Baldwin & Clark, 2000; Frandsen, 2017;
Zirpoli & Becker, 2011). Standardized interfaces and design structures provide innovative ways to
outsource modules, thus reducing overall complexity, increasing firm flexibility, and reducing
coordination efforts between suppliers in the multi-tier supply chain (Pil & Cohen, 2006; Sosa et al.,
2003; Tee et al., 2019), which results in a low exchange of knowledge between each level. Furthermore,
studies have highlighted suppliers’ low involvement in the general product development process,
further reducing the product and system knowledge of component suppliers (Von Corswant &
Fredriksson, 2002; Wynstra et al., 2010). Since knowledge fosters innovation capability for gaining
competitive advantage, firms are reluctant to share knowledge (especially tacit knowledge) with
suppliers (Le & Lei, 2018; Wang et al., 2016). Thus, each multi-tier supply chain level only shares
minimum information. However, by outsourcing defined modules and products, specific production-
value stages transfer production value and knowledge to subsequent value-creation stages (Doran et al.,
2007). Hence, there is asymmetric dissemination of information regarding the product and its
surrounding systems within a multi-tier supply chain (Figure 3).
Tobias D. Herbst
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Figure 3: Multi-tier supplier structure, product view
By offering services, firms strive for increased customer proximity and direct customer feedback
(Rymaszewska et al., 2017). Component suppliers can benefit from first-hand user feedback, which
enables and fosters specific knowledge exchange. Digitalization enables the integration of more
products with digital technology for product-specific data. Component suppliers may efficiently deal
with information asymmetry and secure profitability, focusing on information exchange. However,
customers demand comprehensive solutions by few stakeholders to ensure reduced complexity, which
induces the need for single monitoring technology in emerging service solutions that monitor multiple
modules. This highlights the necessity of an overall monitoring approach with fewer interfaces at the
product level. Specifically, OEMs with general product responsibility and direct customer contact can
best offer monitoring solutions. Monitoring solutions enable firms to gain real-time knowledge of
product usage, status, and location (Baines & Lightfoot, 2014; Lenka et al., 2017; Rust & Huang, 2014).
Furthermore, data can be analyzed at the module and component levels. OEMs possess holistic real-
time information about products, enabling suppliers in a multi-tier supply chain to offer diverse
functionalities (Bressanelli et al., 2018). Sharing such knowledge with participating firms in the multi-
tier supply chain increases system and product transparency and fosters future innovation. Hence,
digital technology offers the potential to counterbalance information asymmetry within a multi-tier
supply chain.
4.2 Leveraging digital technology: Initiate knowledge exchange and achieve competitive
advantage
4.2.1 Knowledge exchange fostered by digital technology
Manufacturers can track and gain information to evaluate product usage and health via digital
technology (Baines & Lightfoot, 2014). Scholars have considered many benefits and applications of
such information to monitor products in real-time (Baines & Lightfoot, 2014). Bressanelli et al. (2018)
provide a good summary of the functionalities driven by real-time monitoring, ranging from product-
specific improvements to BMIs and process optimizations. Furthermore, Porter and Heppelmann (2014)
refer to the new strategic choices utilized for promoting smart, connected products. More specifically,
they present new value-creation opportunities with new and existing partners, thus enabling the
development of a competitive advantage. By building on these ideas and using a case study approach,
Lerch and Gotsch (2015) explore how digital technologies can optimize various processes within a firm
and between firms andmore importantlyhow they can optimize resource allocation. Creating
complex and knowledge-intensive products and services requires comprehensive industry knowledge,
which offers a high entry barrier for new competition. However, containing knowledge in one firm is
challenging; thus, firms rely on suppliers (Zirpoli & Becker, 2011). Since product-level knowledge is
vital for enabling competitive advantage (e.g., Martín-de Castro et al., 2013; Gomes and Wojahn, 2017),
it may lead to an (inter-firm) social dilemma (Bornstein & Ben-Yossef, 1994; Zeng & Chen, 2003).