Abstract
The basic concept underpinning the Internet of Things (IoT) is the possibility
of connecting objects to the Internet, typically by means of a small
and inexpensive “smart label”. The transition from a world of objects to a
world of smart objects connected, identified, and monitored in real time
paves the way for radical innovations in the field of manufacturing: a development
known as Smart Manufacturing (also referred to as Industry 4.0,
Factory 4.0, Smart Enterprise, Industrial IoT). Over the past five years,
Smart Manufacturing has gained significant momentum in terms of market
diffusion, levels of investment, and productivity gains, as reported by a
body of analytical studies (McKinsey & Co, 2015; GE & Accenture, 2014;
DHL & Cisco, 2015; PWC, 2014).
Market diffusion. For example, one study indicates that the deployment
of IoT by businesses has grown by 333% since 2012, reporting that 65% of
companies sampled deployed IoT technologies in 2014 (compared to 15%
in 2012) (Forrester Research, 2014). A survey of 235 German industrial
companies conducted by the market research institution TNS Emnid found
that “while today only one fifth of the industrial companies have digitized
their key processes along the value chain, in five years’ time, 85% of companies
will have implemented Industry 4.0 solutions in all important business
divisions” (PWC, 2014:7)
1 A previous version of this research was presented at ItAIS 2016, the annual conference
of the Italian chapter of the Association for Information Systems, Verona, October
7-8, 2016.
4 Human Resource Management and Digitalization
Investment levels. Furthermore, investments in Industry 4.0 solutions
are forecast to account for over 50% of planned capital investment over the
next five years (PWC, 2014). German industry will thus invest a total of
€40 billion in Industry 4.0 every year by 2020. Applying the same investment
level to the European industrial sector, the annual investments will be
as high as €140 billion per annum” (PWC, 2014:7). In Italy, “Industria 4.0
National Plan 2017-2020” – recently promoted by the Italian Government –
provides for a wide array of initiatives aimed at promoting investment in
innovation and competitiveness according to the Industry 4.0 approach.
Productivity gains. Again, IoT is predicted to generate productivity gains
of over 18% over the next five years, with estimated additional revenues
averaging between 2% and 3% per annum (PWC, 2014). However, it
should be frankly acknowledged that the long-term impact of IoT is currently
difficult to estimate. Early ongoing projects show that the potential
of IoT for manufacturing may only be unlocked by adopting new, and still
largely unexplored, organizational solutions at a range of levels, including
new organizational structures, systems, processes, and relationships. Innovative
people management and HR development approaches are likely to
be key success factors in Smart Manufacturing initiatives, and this generates
novel research requirements in the field of organizational studies.
The aim of this chapter is to examine these requirements, contributing
to the development of an organizational research agenda. More specifically,
we first provide a brief macro overview of IoT innovations, emphasizing
the factors underpinning their development as well as currently unresolved
problem areas. Second, we outline the potential of IoT to enhance manufacturing
via new business models and production paradigms. Third, we
discuss the critical challenges associated with implementing IoT models, in
terms of the organizational traits, work organization, workforce characteristics,
change management, and organizational relationships required for
their potential to be fully realised. Finally, we describe promising lines of
enquiry and theoretical frameworks for future research programmes, with a
view to defini
Lingua originale | English |
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Titolo della pubblicazione ospite | Human Resource Management and Digitalization |
Pagine | 4-24 |
Numero di pagine | 21 |
Stato di pubblicazione | Pubblicato - 2018 |
Keywords
- Information Systems
- Human Resource Management
- Internet of Things