Attention to innovation risks and firm performance: a configurational approach

Lin, Nidthida, Gudergan, Siggi, and Coltman, Tim (2019) Attention to innovation risks and firm performance: a configurational approach. In: [Abstracts from the International Choice Modelling Conference 2019]. From: International Choice Modelling Conference 2019, 19-21 August 2019, Kobe, Japan.

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Abstract

An innovation ecosystem perspective implies that a firm manages not only the conventional execution challenge facing the focal firm but also the upstream and downstream innovation challenges required to create value for the end customer (Adner, 2006, 2012). Innovation management requires the focal firm to expand their capabilities beyond their own boundary and work in collaboration with suppliers and customers to innovate. The attention-based view (Ocasio, 1997) argues that managerial attention is a scarce resource and hence managers need to be selective in their choices of what they should focus on and attend to. Building on this line of thinking, we argue that empirical research is required to understand the selective set of risks that are considered when making resource allocation decisions. Further, how decision-makers in high performing firms allocate attention to innovation risks remains underexplored.

We draw on Adner’s innovation ecosystem concept that implies that risks associated with innovation should not be limited to the focal firm itself, but also include risks involving partners in the innovation network. We offer a configurational view on innovation ecosystem risks and examine how the emphasis on various innovation risks relates to heterogeneity in firm performance. We argue that high performing firms are not driven only by a focus on a specific type or all of innovation risks but by how firms strategically focus on a specific combination of these risk that matter most to them. We also include the level of risk-taking of firms and their experience in risky decision-making to examine potential differences in risk assessment models of high versus low risk-taking firms and firms with high versus low experience in innovation decision-making.

Theoretical Background

The concept of innovation ecosystems extends the traditional view of innovation which places a primary focus on an innovation itself and ignores a larger set of actors that need to come together for the innovation to deliver its value. Innovation ecosystems-thinking suggests that all dependencies and partnerships should be considered explicitly as members of the ecosystem are necessary for the success of innovation. Adner proposes three risks of innovation. Execution risk refers to the challenges a firm faces in delivering innovation to the required specification within the required time. Co-innovation risk refers to the extent to which the success of innovation depends on the successful commercialization of other innovations. Adoption risk refers to the extent to which partners will need to adopt your innovation before customers can assess the full value proposition. The latter two are often overlooked in the traditional view of innovation. The success of innovation leading to high firm performance requires that each risk be addressed. Decision-makers are expected to make sound judgments based on an appropriate alignment of internal and ecosystem risks and benefits.

Research shows that a firm’s performance relative to its aspiration level determines risk-taking behavior (Bromiley, 1991). A poor past performance leads to higher levels of risk-taking behavior and risk-taking appears to result in further poor performance. Drawing on this line of arguments, we argue that a combination of firms’ attention to sets of innovation risks influences the outcome of their innovation decision and, hence, firm performance. We further argue that attention on innovation risks of risk-taking firms—with high performance discrepancy—are likely to be different from that of risk-averse firms.

Method

This study applied discrete choice experiment to collect data concerning the risk assessment model for innovation decisions in the context of high-risk environments. We identified a sample of executives and senior managers involved in making innovation decision from the membership of Ports Australia. Thirty-seven executives and senior managers agreed to participate. Each of them was asked to make 8 decisions, giving us the total of 296 choices for the analysis. The design of the DCE was based on the orthogonal fractional factorial design, allowing orthogonal estimations of the effect of each innovation risks. Each firm representative was put into a scenario in which he/she was asked to make a decision whether to adopt an innovation for his/her organization with various levels of execution, co-innovation, and adoption risks associated with each innovation being considered. We instructed respondents to make decisions about 8 innovation pairs with varying levels across three innovation risks by indicating which of the options “would be their most preferred option?”

The data collected through DCE were analyzed using mixed logit to estimate the orthogonal effect of each risk underlying the decision to adopt an innovation. This helps understand the trade-off between various risks in innovation adoption decisions. The mixed logit model also allows extracting individual weigh each respondent put into each type of risks. To examine how a firm’s emphasis on various innovation risks relates to high performance, we employed a set-theoretic approach based on fuzzy set Qualitative Comparative Analysis. fsQCA allows examining members of the set of firm’s attention on innovation risks with high performance and identifying the combinations of emphasis on execution, co-innovation and adoption risks associated with such performance.

Conclusion

Despite a growing recognition of the importance of dependencies on other parties in an innovation ecosystem, our understanding of what kind of different combinations of the attention placed on innovation risks relate to higher performance remains poorly understood. We argue that one of the challenges is the complex causal conditions and equifinality of the relationships leading to high firm performance. This study adopts the configurational approach to investigate the combinations of firms’ attention to various innovation risks leading to high performance for different types of firms. We contribute to the innovation literature in several ways. First, we extend research in microfoundations of innovation management by using a configurational approach to study how firms’ attention on various innovation risks combines to shape the success of innovation projects and, hence, firm performance. Second, we contribute to the decision-making literature on the effect of experience in decision-making by examining heterogeneity in risk assessment model of experienced vs. less experienced managers. Our study further sheds light on the question of how firms allocate their limited attention to various innovation risks as proposed in innovation ecosystem.

Item ID: 75390
Item Type: Conference Item (Abstract / Summary)
Keywords: innovation
Date Deposited: 12 Sep 2022 02:53
FoR Codes: 35 COMMERCE, MANAGEMENT, TOURISM AND SERVICES > 3507 Strategy, management and organisational behaviour > 350718 Strategy @ 100%
SEO Codes: 15 ECONOMIC FRAMEWORK > 1503 Management and productivity > 150306 Technological and organisational innovation @ 100%
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