International Journal of Innovation and Technology Management

This paper looks at the vital role of industrial research and development (R&D). The increased outsourcing of industrial R&D is contrasted with a resource-based view of competitive advantage which maintains capabilities that are valuable, rare, imitable, and non-substitutable (VRIN), and should be internalized in the firm. Traditional business formation literature is also supportive of keeping R&D “inhouse”. R&D outsourcing research is leveraged to posit possible reasons for the increased amount of outsourced R&D. Testable propositions are included that look at factors for R&D outsource decisions and also the impact of these decisions on firm performance. An R&D entropy statistic is introduced as well as several R&D characteristics useful in the decision-making process to create R&D.

This study seeks to understand how professionals’ (creative) Adaption-Innovation behaviors and prior knowledge influence successful participation in two-sided competitive crowdsourcing. Using Kirton’s Adaption-Innovation Theory, the study examines the influence of creatives’ diversity, skills, experience, and activity level on crowdsourcing outcomes. Analysis of cross-sectional data of participants on a popular competitive crowdsourcing platform show that, while diversity and skills do not necessarily lead to higher performance, activity level and experience contribute to creatives’ higher performance. Contribution to literature is by extending Kirton’s Adaption-Innovation Theory objectively as a lens to understand creative participation in crowdsourcing, highlighting key features of crowdsourcing as unbounded by place and skills.

This paper aims to create a quantitative model of World Class Manufacturing (WCM) using the findings of Oliveira (2015) who identified six constructs using the PLS-PM method to create a WCM-LHEMI model, which is an acronym for Lean Manufacturing, Human Resource Management, Environmental Practices, and Marketing Integration. We created a questionnaire using the variables that exploratory factor analyses identified as consistent and distributed it to 1000 professionals using the LinkedIn professional network. From these, our final sample consisted of 180 completed questionnaires, which exceeded the 68 answers needed to have an adequate sample based on suggestions by G*Power Software. Eleven hypotheses were analyzed and six were accepted and considered valid. A goal of this research was to examine the professional’s perception about the need for enterprises to have environmental practices to become WCM enterprises. A main contribution of this study was to propose a WCM model using professional perceptions about what denotes a WCM enterprise through a PLS Statistics method.

There is a gap in research literature between cross-industry innovation (CII), knowledge transfer, and relational proximities. In this study, we analyze contributions from these three streams of literature and an empirical case of CII, and propose a conceptual model for knowledge transfer in CII, which also incorporates the influences of proximities. The focus of our study is on CII from the petroleum industry to the medical industry. Theoretical and practical implications are discussed in the paper.

This research aims to analyze the factors influencing the adoption of cloud computing (CC) in public and private hospitals in a developing country setting, specifically in Brazil’s hospital industry. We interviewed IT professionals from four hospitals. The study demonstrates that concerns with security and availability matter more to the hospitals than the expected benefits of CC, such as flexibility and cost reduction. In addition, the findings show that there are relevant differences between public and private organizations, such as regulatory issues and cost, which influence the adoption of cloud computing in each context. Cloud-based resources continue to worry companies that deal with sensitive data as healthcare institutions. Knowledge acquired from this study is particularly beneficial to IT executives to guide their decision to create or adjust CC initiatives in healthcare.

Aristotle’s dictum scio nescio (I know that I don’t know) may serve as a source of enhanced performance for organizations. Awareness of nescience sets the direction for further inquiry, as managers tend to move in the direction that they believe will reduce nescience most. However, nescience is difficult to quantify, so, to date, managers have primarily relied on intuition. This paper introduces a theoretical framework for managing nescience that is based on information theory. This framework is tested in three exploratory empirical studies that take place in highly contrasting settings: semiconductor manufacturing, medical diagnostics and social media analytics. All three studies demonstrate that metrics related to information entropy can be used to quantify nescience. However, practitioners value the framework and its metrics more highly in the settings where the quality of or access to information drives successful product development. The problems encountered in these settings tended to be well-structured, or they were converted from being ill-structured to being well-structured. Further study of more highly contrasting practical settings will be required to determine whether frameworks based on information theory can serve as foundations for a broadly based, pragmatic theory for managing nescience.

By linking theoretical perspectives on human resource diversity to the distinction between knowledge exploration and exploitation, this paper contributes to the growing research literature on diversity and innovation by following up on the original argument by March [1991] that different dimensions of organizational learning depend on different inputs and processes. Empirically, the paper draws on a unique dataset constructed by merging Norwegian employer–employee register data for 2004–2008 with Community Innovation Survey (CIS) data covering the years 2008–2010. Bivariate probit regressions with controls for innovation strategy find patenting propensities more responsive to the diversity of experience-based knowledge accumulated in firms, than the propensities to improve production processes or introduce new products onto the market. The latter depends foremost on firms’ investments in innovation, and responds positively to human resource diversity only when the financial commitment of firms to development work is limited.

This research was directed at the impact of innovation strategy complexity on the breadth of innovation strategy objectives achievement. The context is automotive component manufacturing in developing economies. Given the risk associated with innovation activity, the question is whether firms can improve their success by adopting a complex market access strategy. The methodology was survey based, utilizing data on the innovation activities of some 530 automotive component manufacturing firms obtained by a questionnaire applied in the Pune region in India, Beijing region in China and in South Africa. Path analysis by structural equation modeling was applied to analyze the data for the hypothesized relationships. It was found that strategic complexity in the larger combined country data set is positively and significantly related to a greater breadth of impact of innovation in terms of the market access strategies implemented. It was also observed that diversity of technology and knowledge sources, and innovation types, play a fundamental role in this relationship. The results for individual countries are different from those of all countries combined and yielded varying conclusions. The SA data set was unfortunately too small to meet the requirements for reliable results on its own, but served to support understanding of the influence of its different environment. The findings support the proposition that a diverse innovation strategy should be developed and executed in a business strategy directed at innovation.