Industry 4.0 technologies in the purchasing process
| Date | 23 February 2020 |
| Pages | 730-748 |
| DOI | https://doi.org/10.1108/IMDS-05-2019-0304 |
| Published date | 23 February 2020 |
| Author | Simon Gottge,Torben Menzel,Helena Forslund |
| Subject Matter | Information & knowledge management,Information systems,Data management systems,Knowledge management,Knowledge sharing,Management science & operations,Supply chain management,Supply chain information systems,Logistics,Quality management/systems |
Industry 4.0 technologies in the
purchasing process
Simon Gottge, Torben Menzel and Helena Forslund
School of Business and Economics, Linnaeus University, Vaxjo, Sweden
Abstract
Purpose –The aim of the study is to explore thepossible practical impact of big data/business intelligence and
Internet of Things on the purchasing process of premium automotive manufacturers, and to evaluate its
theoretical impact with a transaction cost economics approach.
Design/methodology/approach –An exploratory multiple-case study was carried out, using qualitative
content analysis and cross-case synthesis.
Findings –Collaborative platforms and a new purchaser role were found to impact the entire process. In the
strategic purchasing 4.0 process, co-creation of specifications, automated prequalification, and parameter-
based negotiations are some expected changes. The operative purchasing 4.0 process is shaped by, for
example, interactive call-offs. Transaction cost is expected to decrease by reduced uncertainty and supplier
specificity, as well as by lowered information search, negotiation, and monitoring costs.
Research limitations/implications –The description of a potential purchasing 4.0 process for premium
automotive manufacturers is given.
Practical implications –Premium automotive manufacturers can develop strategies to push the existing
standards of purchasing. Suppliers can create scenarios to allowfor future compliance at the purchasing–sales
interface.
Social implications –New technologies’effects on the workforce are considered.
Originality/value –No identified study focused on the impact of Industry 4.0 technologies on the purchasing
process of premium automotive manufacturers.
Keywords Industry 4.0 technologies, Internet of Things, Big data/business intelligence, Purchasing process,
Premium automotive manufacturers, Transaction cost economics
Paper type Conceptual paper
1. Introduction
The fourth industrial revolution or Industry 4.0 is taking place (Lin et al., 2018), pushed by
customer expectations of technological developments like digitalization (Nazir and
Shavarebi, 2019;Lin et al., 2018;Foerstl et al., 2017). Industry 4.0 implies benefits based on
automation and increased amounts of accessible data (Weyer et al., 2015). Real-time
information sharing (Glas and Kleemann, 2016) and enhanced data processing further enable
more flexible planning (Weyer et al., 2015;Zhou et al., 2015). Industry 4.0 consists of a number
of vaguely defined and partly overlapping technologies (Lin et al., 2018;Glas and Kleemann,
2016), such as cyber-physical systems, big data/business intelligence, Internet of Things, and
smart factories. One content analysis by Oesterreich and Teuteberg (2016) within Industry
4.0 publications, and another broad overview provided by Pfohl et al. (2015), signaled the need
to limit and focus on certain technologies. Therefore, this study focuses on two central
technologies: big data/business intelligence or BD/BI (Popovic et al., 2019;Wang et al., 2016;
Kagermann, 2015) and Internet of Things or IoT (Lin et al., 2018;Osmonbekov and Johnston,
2018;Smit et al., 2016).
The importance of purchasing continues to increase (Bals et al., 2019:Osmonbekov and
Johnston, 2018;GEP, 2018). By leveraging purchasing potentials, companies strive to achieve
low cost, high quality, and low risk while realizing synergies for increasingly individualized
products (Feng and Zhang, 2017;Foerstl et al., 2017). Few studies examine the impact of new
technologies on purchasing (Osmonbekov and Johnston, 2018;Glas and Kleemann, 2016).
One exception is a recent study identifying future competency demands on purchasing
professionals. Reflected by the latest development in Industry 4.0, digitalization, including,
IMDS
120,4
730
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/0263-5577.htm
Received 31 May 2019
Revised 8 October 2019
Accepted 24 December 2019
Industrial Management & Data
Systems
Vol. 120 No. 4, 2020
pp. 730-748
© Emerald Publishing Limited
0263-5577
DOI 10.1108/IMDS-05-2019-0304
for example, automation, and big data were identified as important future competencies (Bals
et al., 2019). Consultancy reports further confirm the practical challenges that come with
Industry 4.0. Pellengahr et al. (2016) showed that 37 percent of German companies have
implemented some Industry 4.0 technologies, but only one-third of them have made
purchasing adjustments. GEP (2018) claims that the use of real-time data in purchasing will
accelerate. How this development will impact purchasing can be explored through the
purchasing process, where concrete changes on sub-process level can be seen. A focus on
increased digitalization of the purchasing process for companies to stay competitive was
encouraged by Bals et al. (2019),Zafari and Teuteberg (2018), and Yu et al. (2017). Purchasing
processes differ due to various industry specifics (Wynstra et al., 2018;Osmonbekov and
Johnston, 2018).
Studies of how, for instance, IoT impacts purchasing processes generally were
encouraged by Bals et al. (2019), and particularly in high-technology industries
(Osmonbekov and Johnston, 2018) such as the automotive industry (Goyal et al., 2018),
with outsourcing levels of up to 80 percent and renowned for its pioneer and innovative role
(Manello and Calabrese, 2019;Stock and Seliger, 2016;Kagermann, 2015;Zhou et al., 2015). No
identified study described the purchasing process of automotive manufacturers under new
technologies. It would be practically relevant to make such a description in line with Lin et al.
(2018), to support companies for successful implementation. The automotive industry is
complex. A distinction can be made between high volume and premium brands; this study
focuses on premium automotive manufacturers producing sophisticated and highly
appointed cars (Hertenstein and Williamson, 2018), as this segment is increasing in
importance and volume (Manello and Calabrese, 2019). Combining the partial knowledge in
Industry 4.0, purchasing process, and premium automotive manufacturing into a coherent
study, formulating:
RQ1. How can BD/BI and IoT practically impact the purchasing process of premium
automotive manufacturers?
To root new, exploratory research in consolidated theoretical frameworks in purchasing
research was encouraged by Foerstl et al. (2017) and Spina et al. (2016). Transaction cost
economics (TCE) has its focus on costs for buyer and sellers to complete a transaction
(Williamson, 1981). TCE is applied to evaluate the potential theoretical impact on the
purchasing process, caused by BD/BI and IoT technologies.
RQ2. How can BD/BI and IoT in the purchasing process of premium automotive
manufacturers theoretically impact TCE?
The purpose is to explore the possible practical impact of BD/BI and IoT on the purchasing
process of premium automotive manufacturers, and to evaluate its theoretical impact with a
TCE approach.
2. Literature review
For RQ1, the literature review deals in 2.1 with the focused Industry 4.0 technologies, in 2.2
with the purchasing process under these technologies, and in 2.3 with automotive
manufacturing characteristics. For RQ2,2.4 contains TCE theory, and 2.5 provides the
research model.
2.1 Big data/business intelligence and Internet of Things
Big data refers to high-volume, high-velocity, and high-variety data (Wang et al., 2016) that
are difficult to analyze with traditional data processing methods (Popovic et al., 2019;Kang
et al., 2016). Through BD, new technologies extract information from various data types and
Industry 4.0
technologies
731
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