Exploring Social Aspects Influence on Change in Network Relationships: A Case Study of Digital Innovation

Exploring Social Aspects Influence on Change in Network Relationships: A Case Study of Digital Innovation

Jesper Svensson (School of Information Science, Computer and Electrical Engineering, Media IT Group, Halmstad University, Halmstad, Sweden) and Carina Ihlström Eriksson (School of Information Science, Computer and Electrical Engineering, Media IT Group, Halmstad University, Halmstad, Sweden)
DOI: 10.4018/ijsodit.2012100102
OnDemand PDF Download:
$37.50

Abstract

Digital innovation processes are becoming more and more networked, and actors are growing dependent on each other’s competences, resources and knowledge. In networks developing digital innovation actors need to identify, mobilize, and integrate diverse and heterogeneous knowledge resources to be able to innovate successfully. Social aspects are important where heterogeneous actors connect, negotiate, and adjust to each other’s perspectives. The aim of this paper is to explain how social aspects such as trust, commitment and power, influence changes in relationships in digital innovation networks. A case study approach was selected to study events involving multiple actors in an innovation and development project aimed at introducing technology that aids elderly, home care personnel and next of kin by improving the management of home care visits. Based on the authors’ findings they present a model for how social aspects influence changes in relationships and conclude by making six propositions.
Article Preview

Introduction

Digital innovation is the process of a) creating new combinations of digital and physical components that produce novel products or services and b) embedding digital computer and communication technology into a traditionally non-digital product or service (Yoo et al., 2010; Henfridsson et al., 2009). Digital innovation processes are becoming more and more networked (Boland et al., 2007; Yoo et al., 2009; Yoo, 2010), where actors are growing dependent on each other’s competences, resources and knowledge (Vanhaverbeke & Cloodt, 2006). Digital innovation therefore drives a need for collaboration which spans over organizational realms (Yoo et al., 2010). Current research highlights the importance to study multi-organizational forms to investigate e.g. value creation, risk allocation, capability building, and incentives among the involved organizations (Grover & Kohli, 2012). According to these scholars it is important to learn more about how different organizations can join together to create new value that either firm is unlikely to create by its own. Innovation networks in this paper are seen as socio-technical networks that produce and consume knowledge necessary for innovation. In these networks innovation is enabled by the organizational actors, information, and communication tools (Yoo et al., 2009).

Innovation networks need to support the whole innovation process including e.g. business modeling and the support of the diffusion of an innovation. In networks working with digital innovation actors need to identify, mobilize, and integrate diverse and heterogeneous knowledge resources to be able to innovate successfully (Yoo et al., 2009). In particular, digital innovation processes are becoming complex when heterogeneous networks are formed across organizational boundaries (Boland et al., 2007; Yoo et al., 2009). Therefore it is important to be able to address challenges such as differences in ownership and governance of an innovation, and the heterogeneity of values and knowledge bases in an innovation network (Yoo et al., 2009). Scholars have realized the messiness, ambiguity, multiplicity, and volatility of innovation spawning from distributed and dynamic networks of heterogeneous actors (Lyytinen & Damsgaard, 2001). In these settings the relationships between organizations are important to enable resources needed for successful collaborations (Grover & Kohli, 2012).

Research has increased the attention towards cooperative and networked aspects of innovation and argues that increased network heterogeneity promotes new combinations, supports learning, and enables faster diffusion (Yoo et al., 2009). However, heterogeneity also creates learning boundaries and inhibits the spread of ideas and innovations (Carlile, 2002). To better understand these bipolar impacts of heterogeneity, scholars have begun to examine in more detail the types of interactions, the knowledge creation and communication, and the barriers in different types of innovation networks (Carlile, 2002; Yoo et al., 2009).

Complete Article List

Search this Journal:
Reset
Open Access Articles: Forthcoming
Volume 6: 2 Issues (2017): 1 Released, 1 Forthcoming
Volume 5: 2 Issues (2016)
Volume 4: 2 Issues (2015)
Volume 3: 4 Issues (2013)
Volume 2: 4 Issues (2012)
Volume 1: 4 Issues (2011)
View Complete Journal Contents Listing