‘Reverse innovation’ refers to the case where an innovation is adopted first in poor (emerging) economies before ‘trickling up’ to rich countries. Although examples of reverse innovation are still ...rare, it raises interesting theoretical questions, such as what kinds of innovation emerging economies are likely to spawn, why such innovations might diffuse to rich countries, what competitive advantages local and foreign firms enjoy in this process, and how it affects the global strategy and organization of established MNEs. Research on reverse innovation can enrich and extend mainstream theories of innovation, internationalization, MNE management, and FDI spillovers.
The merits of being customer‐oriented for firm innovation have long been debated. Firms focused on their existing customers have been argued to be less innovative. This paper distinguishes between ...mainstream and emerging customer orientations and examines their effects on the introduction of disruptive and radical product innovations. Radical product innovations draw on a substantially new technology and could initially be targeted at a mainstream or an emerging market. In contrast, disruptive innovations are initially targeted at an emerging market, and may not involve the newest technology. This paper hypothesizes that mainstream customer orientation is negatively related to disruptive innovation and positively related to radical innovation, and that emerging customer orientation is positively related to disruptive innovation. To test these hypotheses, longitudinal and multiple informant data from senior executives in 128 SBUs of 19 Fortune 200 corporations are analyzed, with technology scanning and willingness to cannibalize as key control variables. The results support the hypotheses, providing evidence for contrasting effects of being oriented to mainstream customers and/or emerging customers on radical and disruptive innovations. Mainstream customer orientation has a positive impact on the introduction of radical innovations but a negative impact on disruptive innovation, while emerging customer orientation has a positive effect on disruptive innovation and is unrelated to radical innovations. Technology scanning is positively related to radical innovation but not to disruptive innovation, supporting the idea that disruptive innovation may not require new technology. In contrast, willingness to cannibalize is positively related to disruptive innovation but not to radical innovation, supporting the idea that radical innovation does not require cannibalization of existing investments. Additionally, mainstream customer orientation is found to have a near‐zero correlation with emerging customer orientation, indicating that the two can coexist and can be pursued simultaneously.
Strategic management scholars have long explored the broad topic of innovation, a cornerstone in creating competitive advantage. Any attempt at theory construction in this area must encompass ...reliable and valid measures for key innovation characteristics. Yet, with respect to an important construct, i.e., disruptiveness of innovations, there has been relatively little academic research. Without formalizing the disruptiveness concept with a reliable and valid measure, it is difficult to conduct rigorous research to uncover the causes of the innovator's dilemma and identify mechanisms to help incumbents develop such innovations. In this paper, we develop a scale for the disruptiveness of innovations. We collected data from senior executives (vice president or general manager level) at 199 strategic business units (SBUs) in 38 Fortune 500 corporations and performed a series of analyses to establish the reliability and validity of the disruptiveness scale. The reliability measures, exploratory factor analysis, confirmatory factor analysis, and subsequent statistical tests strongly support our measure. Further, we also present nomological validity of the disruptiveness construct, thus establishing its predictive validity. Thus, this paper distinguishes the disruptiveness concept from other established innovation constructs, such as radicalness and competency destroying. Finally, we discuss the significance of our results and how this study might be useful to other researchers.
Broadly speaking, this article addresses three issues. First, we discuss a way to measure low-end disruptions, where the innovations are offered at a lower price and initially attract the more ...price-sensitive segments. Second, we provide a more general measure of disruptiveness that includes both low-end and high-end disruptions. Third, we address one of Danneels's (2004) criticisms of Christensen's (1997) disruptiveness notion that all of his examples are ex post and that with such hindsight it is not possible to make ex ante predictions regarding a technology's disruptiveness. Danneels also suggest that is one reason why established companies are skeptical about the concept of disruptiveness. The goal of this article is to add rigor to an important, substantive area of research on disruptiveness.
Pursuing a nodal (i.e., subsidiary) level of analysis, this paper advances and tests an overarching theoretical framework pertaining to intracorporate knowledge transfers within multinational ...corporations (MNCs). We predicted that (i) knowledge outflows from a subsidiary would be positively associated with value of the subsidiary's knowledge stock, its motivational disposition to share knowledge, and the richness of transmission channels; and (ii) knowledge inflows into a subsidiary would be positively associated with richness of transmission channels, motivational disposition to acquire knowledge, and the capacity to absorb the incoming knowledge. These predictions were tested empirically with data from 374 subsidiaries within 75 MNCs headquartered in the U.S., Europe, and Japan. Except for our predictions regarding the impact of source unit's motivational disposition on knowledge outflows, the data provide either full or partial support to all of the other elements of our theoretical framework.
Transcatheter aortic valve replacement (TAVR) is now a standard treatment for high-surgical-risk patients with severe aortic valve stenosis. TAVR is being explored for broader indications including ...degenerated bioprosthetic valves, bicuspid valves and for aortic valve (AV) insufficiency. It is, however, challenging to predict whether the chosen valve size, design or its orientation would produce the most-optimal haemodynamics in the patient. Here, we present a novel patient-specific evaluation framework to realistically predict the patient's AV performance with a high-fidelity fluid-structure interaction analysis that included the patient's left ventricle and ascending aorta (AAo). We retrospectively evaluated the pre- and post-TAVR dynamics of a patient who underwent a 23 mm TAVR and evaluated against the patient's virtually de-calcified AV serving as a hypothetical benchmark. Our model predictions were consistent with clinical data. Stenosed AV produced a turbulent flow during peak-systole, while aortic flow with TAVR and de-calcified AV were both in the laminar-to-turbulent transitional regime with an estimated fivefold reduction in viscous dissipation. For TAVR, dissipation was highest during early systole when valve deformation was the greatest, suggesting that an efficient valve opening may reduce energy loss. Our study demonstrates that such patient-specific modelling frameworks can be used to improve predictability and in the planning of AV interventions.
Single ventricle (SV) patients with interrupted inferior vena cava (iIVC) and azygos continuation are at high risk for unbalanced hepatic venous flow (HVF) distribution to the lungs after Fontan ...completion and subsequent pulmonary arteriovenous malformations (AVMs) formation.
The aim of the study was to utilize computational fluid dynamics (CFD) analysis to avoid maldistribution of HVF to the lungs after Fontan surgery.
Four SV subjects with iIVC were prospectively studied with a 3-dimensional (3D) modeling workflow with digital 3D models created from segmented magnetic resonance images or computer tomography scans, virtual surgery, and CFD analysis over multiple physiologic states for the evaluation of operative plans to achieve balanced HVF to both lungs. Three of the patients were Fontan revision candidates with existing AVMs. All patients underwent Fontan completion or revision surgery.
CFD predicted that existing or proposed Fontan completion in all patients would result in 100% of HVF to one lung. Improved HVF balance was achieved with CFD analysis of alternative surgical approaches resulting in the average distribution of HVF to the right/left pulmonary arteries of 37%/63% ± 10.4%. A hepatoazygos shunt was required in all patients and additional creation of an innominate vein in one. CFD analysis was validated by the comparison of pre-operative predicted and postoperative MRI-measured total right/left pulmonary flow (51%/49% ± 5.4% vs 49%/51% ± 8.5%).
A 3D modeling workflow with CFD simulation for SV patients with iIVC may avoid HVF maldistribution and development of AVMs after Fontan completion.
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Given the current capabilities of autonomous vehicles, one can easily imagine autonomous vehicles being released on the road in the near future. However, it can be assumed that this transition will ...not be instantaneous, suggesting that autonomous vehicles will have to be capable of driving in a mixed environment, with both humans and autonomous vehicles. To guarantee smooth integration and maintain the nuanced social interactions on the road, a shared mental model must be developed. This means that the behaviors of human-driven vehicles and their typical interactions in collaborative maneuvers must be modeled and understood in an accurate and precise manner. Then, by integrating such models into autonomous planning, we can develop control frameworks that mimic this shared understanding. We present a driver modeling framework that estimates an empirical reachable set to capture typical lane changing behaviors. This method can predict driver behaviors with up to 90% accuracy and cumulative errors less than 1 m. Leveraging this driver model in an optimization-based trajectory planning framework, we can generate trajectories that are similar to those performed by humans. By using this modeling and planning framework, we can improve understanding and integration of nuanced interactions to improve collaboration between humans and autonomy.
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