Clusters Of Innovative Firms: Absorptive Capacity In Larger Networks?

Firms are often compared in terms of their resources or capabilities (resource based view of the firm (Barney, 1991, 1997) dynamic capabilities (Eisenhardt & Martin, 2000) and their performance on knowledge transfer (Argote & Ingram, 2000), absorptive capacity and relative absorptive capacity. Innovative firms are often located with other firms in clusters, with relationships and networks that have developed over time or in response to particular drivers and conditions. This paper investigates assumptions related to innovative firms and their environments and brings together research relevant to individual firms, notions of absorptive capacity and findings about clusters of firms. Firm relationships in cluster configurations are discussed and a research agenda proposed

Contextual impacts on industrial processes brought by the digital transformation of manufacturing: a systematic review

The digital transformation of manufacturing (a phenomenon also known as "Industry 4.0" or "Smart Manufacturing") is finding a growing interest both at practitioner and academic levels, but is still in its infancy and needs deeper investigation. Even though current and potential advantages of digital manufacturing are remarkable, in terms of improved efficiency, sustainability, customization, and flexibility, only a limited number of companies has already developed ad hoc strategies necessary to achieve a superior performance. Through a systematic review, this study aims at assessing the current state of the art of the academic literature regarding the paradigm shift occurring in the manufacturing settings, in order to provide definitions as well as point out recurring patterns and gaps to be addressed by future research. For the literature search, the most representative keywords, strict criteria, and classification schemes based on authoritative reference studies were used. The final sample of 156 primary publications was analyzed through a systematic coding process to identify theoretical and methodological approaches, together with other significant elements. This analysis allowed a mapping of the literature based on clusters of critical themes to synthesize the developments of different research streams and provide the most representative picture of its current state. Research areas, insights, and gaps resulting from this analysis contributed to create a schematic research agenda, which clearly indicates the space for future evolutions of the state of knowledge in this field

Lock-in & Break-out from Technological Trajectories: Modeling and policy implications

Arthur [1,2] provided a model to explain the circumstances that lead to technological lock-in into a specific trajectory. We contribute substantially to this area of research by investigating the circumstances under which technological development may break-out of a trajectory. We argue that for this to happen, a third selection mechanism--beyond those of the market and of technology--needs to upset the lock-in. We model the interaction, or mutual shaping among three selection mechanisms, and thus this paper also allows for a better understanding of when a technology will lock-in into a trajectory, when a technology may break-out of a lock-in, and when competing technologies may co-exist in a balance. As a system is conceptualized to gain a (third) degree of freedom, the possibility of bifurcation is introduced into the model. The equations, in which interactions between competition and selection mechanisms can be modeled, allow one to specify conditions for lock-in, competitive balance, and break-out

Optimal Posted Prices for Online Cloud Resource Allocation

We study online resource allocation in a cloud computing platform, through a posted pricing mechanism: The cloud provider publishes a unit price for each resource type, which may vary over time; upon arrival at the cloud system, a cloud user either takes the current prices, renting resources to execute its job, or refuses the prices without running its job there. We design pricing functions based on the current resource utilization ratios, in a wide array of demand-supply relationships and resource occupation durations, and prove worst-case competitive ratios of the pricing functions in terms of social welfare. In the basic case of a single-type, non-recycled resource (i.e., allocated resources are not later released for reuse), we prove that our pricing function design is optimal, in that any other pricing function can only lead to a worse competitive ratio. Insights obtained from the basic cases are then used to generalize the pricing functions to more realistic cloud systems with multiple types of resources, where a job occupies allocated resources for a number of time slots till completion, upon which time the resources are returned back to the cloud resource pool

Knowledge management, innovation and big data: Implications for sustainability, policy making and competitiveness

This Special Issue of Sustainability devoted to the topic of “Knowledge Management, Innovation and Big Data: Implications for Sustainability, Policy Making and Competitiveness” attracted exponential attention of scholars, practitioners, and policy-makers from all over the world. Locating themselves at the expanding cross-section of the uses of sophisticated information and communication technology (ICT) and insights from social science and engineering, all papers included in this Special Issue contribute to the opening of new avenues of research in the field of innovation, knowledge management, and big data. By triggering a lively debate on diverse challenges that companies are exposed to today, this Special Issue offers an in-depth, informative, well-structured, comparative insight into the most salient developments shaping the corresponding fields of research and policymaking