The Role of Lean Innovation Capability in Resource-Limited Innovation: Concept, Measurement, and Consequences: An Abstract
The importance of fostering the creative use of resources, especially as environments become more turbulent, competitive, and resource limited, is increasing. There are several arguments from the management literature on how the amount of resources is linked to innovation performance. One research stream, the slack resources literature, emphasizes the idea that limited resources (what we conceptualize as negative relative slack) inhibit the innovation process and have a negative impact on performance. Researchers in this school of thought argue that firms involved in innovation practices must mobilize excess amounts of resources to incorporate new technologies, invent new processes, and develop new capabilities to create new markets.
A second view, though it is not as extensive as the first, has emphasized that the very presence of limited resources makes firms more focused, requiring them to seek diverse information in both close and distant proximity networks and be more creative. This literature also discusses how the abundance of resources can detract from an organization’s innovation capabilities.
The current study explores how firms in this second view can achieve high innovation performance with limited resources. Our qualitative inquiry with ten startup companies and an extensive literature review on resource limitation led us to a concept called lean innovation capability (LIC). We conceptualize LIC as a higher-order distinct firm capability. Further, we aim to develop a new LIC scale and test its moderating role in a resource-limited innovation model in a multi-industry context. To do so, we follow established scale development process. Case studies with startups and extensive literature review generated 73 items for a total of four dimensions. Because a scale with 73 items is too lengthy to be usable in practice, we had to reduce the initial item pool. Reducing a scale to an acceptable number of items first relies on the use of expert judgments and then the statistical purification process with a larger sample size. Expert judgment process with 12 lean innovation consultants in an expert panel reduced the item pool to 37 items. The final stage had the survey with 340 marketing and technology managers. EFA and CFA statistical procedures reduced the item pool to 13 items. The final construct had three dimensions: focus on product-market fit, networking capability, and mission-oriented leadership.
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