The management of organizational ambidexterity through alliances in a new context of analysis: Internet of Things (IoT) smart city projects

Stefano Bresciani, Alberto Ferraris and Manlio Del Giudice

Technological Forecasting and Social Change, 2018, vol. 136, issue C, 331-338

Abstract: In the last decade, the Internet of Things (IoT) has affected the approach of organizations to innovation and how they create and capture value in everyday business activities. This is compounded in the so-called Smart Cities, where the objective of the IoT is to exploit information and communication technologies (ICTs) to support added-value services for citizens, giving companies more opportunities to innovate through the use of the latest technologies. In this context, multinational enterprises (MNEs) are building alliances, starting several projects with public and private city stakeholders aimed at exploring new technologies for cities but also at exploiting new IoT-based devices and services in order to profit from them. This implies that companies need to manage and integrate different types of knowledge to efficiently and effectively support the simultaneous pressure of exploration and exploitation, at a project portfolio level. Using structural equations modeling with data collected from 43 IoT smart city project alliances in Italy, this paper tests and finds evidence that MNEs need to develop knowledge management (KM) capabilities combined with ICT capabilities if they want to obtain greater ambidexterity performance at the project portfolio level. More specifically, we highlight that KM capabilities enhance alliance ambidexterity indirectly through firms' ICT capabilities, suggesting that MNE managers should design KM tools and develop new ICT skills. Implications for academics, managers and future lines of research are proposed.

Keywords: Internet of Things; Smart City; Alliances; Ambidexterity; Knowledge management; ICT (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (93)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:136:y:2018:i:c:p:331-338

DOI: 10.1016/j.techfore.2017.03.002

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