Francesco Paolo Appio

Unveiling the intellectual origins of Social Media-based innovation: insights from a bibliometric approach

This article uses a bundle of bibliometric and text-mining techniques to provide a systematic assessment of the intellectual core of the Social Media-based innovation research field. The goal of this study is to identify main research areas, understand the current state of development and suggest potential future directions by analysing co-citations from 155 papers published between 2003 and 2013 in the most influential academic journals. The main clusters have been identified, mapped, and labelled. Their most active areas on this topic and the most influential and co-cited papers have been identified and described. Also, intra- and inter-cluster knowledge base diversity has been assessed by using indicators stemming from the domains of Information Theory and Biology. A t test has been performed to assess the significance of the inter-cluster diversity. Five co-existing research streams shaping the research field under investigation have been identified and characterized.

Academics as orchestrators of continuous innovation ecosystems: towards a fourth generation of CI initiatives

In this paper, we shed light on why academics are in one of the best positions to orchestrate inter–organisational initiatives of continuous innovation (CI) within an innovation context that is shifting towards an open collaborative ecosystem mode. Two rationales seem to explain the potential key role of academics within a CI ecosystem: 1) their independence; 2) their compliance to CI ecosystems purposes - independently by its type. The implications of the five papers invited to be part of the special issue, and formerly presented at the 14th International CINet Conference in Nijmegen, The Netherlands, are also discussed.

Visualizing the structure and bridges of the intellectual property management and strategy literature: a document co-citation analysis

This article uses document co-citation analysis to objectively explore the underlying structure of the intellectual property research domain, taken from a managerial and strategic standpoint. The goal of this study is identifying its main research areas, understanding its current state of development and suggesting potential future directions, by analyzing the co-citations from 181 papers published between 1992 and 2011 in the most influential academic journals. Five main clusters have been identified, mapped, and labeled as follows: Economics of patent system, technological and institutional capabilities, university patenting, intellectual property exploitation, and division of labor. Their most active areas on this topic, and the most influential and co-cited papers have been identified and described. Also, intra- and inter-cluster knowledge base diversity has been assessed by using indicators stemming from the domains of information theory and biology. A t test has been performed to assess the significance of the inter-cluster diversity. The knowledge bases of these five clusters are significantly diverse, this meaning that they are five co-existing paradigms.

Collaborative network of firms: antecedents and state-of-the-art properties

The concept of collaborative networks has attracted considerable attention, especially in two knowledge domains: innovation and operation management. Although collaborative networks have evolved into many forms, their central role in triggering debates has not gone unnoticed. In this paper, we aim to contribute to these debates through a bibliometric review of a decade of research on collaborative networks (2002–2015). By using a combination of document co-citation and bibliographic coupling analyses, we unveil the origins and evolution of collaborative networks over time by analysing the references from the most important academic contributions. Our goal is threefold: first, to systematise the state of the art in the Input-Process-Output (IPO) framework; second, to elucidate the antecedents of the research field on collaborative networks (research streams originating from the field, main authors and journals) by organising them in six thematic clusters; and third, to show how the antecedents shaped the IPO framework. While ‘collaborative networks’ used to belong to two distinct domains, the research agendas seem to converge because of the interactions between their most active authors. As such, cross-fertilisation occurs with the International Journal of Production Research, which plays a central role in this process.

On designers’ use of biomimicry tools during the new product development process: an empirical investigation

ABSTRACT As technological problems and societal challenges become increasingly complex, designers are urged to recombine knowledge from different sources in order to innovate. In this article we question how nature may be the key source of inspiration and whether it can impact the new product development (NPD) process. We shed new light on whether designers and researchers are: first, familiar with biomimicry tools; second, aware of their characteristics; third, in favour of using biomimicry tools in the NPD process; and fourth, able to assess the impact of biomimicry tools on the NPD performance. By analysing survey data, counterintuitive results emerged concerning both the awareness of the biomimetic tools and their impact on the NPD innovation outcomes.

An Adaptive Stigmergy-based System for Evaluating Technological Indicator Dynamics in the Context of Smart Specialization

Regional innovation is more and more considered an important enabler of welfare. It is no coincidence that the European Commission has started looking at regional peculiarities and dynamics, in order to focus Research and Innovation Strategies for Smart Specialization towards effective investment policies. In this context, this work aims to support policy makers in the analysis of innovation-relevant trends. We exploit a European database of the regional patent application to determine the dynamics of a set of technological innovation indicators. For this purpose, we design and develop a software system for assessing unfolding trends in such indicators. In contrast with conventional knowledge-based design, our approach is biologically-inspired and based on self-organization of information. This means that a functional structure, called track, appears and stays spontaneous at runtime when local dynamism in data occurs. A further prototyping of tracks allows a better distinction of the critical phenomena during unfolding events, with a better assessment of the progressing levels. The proposed mechanism works if structural parameters are correctly tuned for the given historical context. Determining such correct parameters is not a simple task since different indicators may have different dynamics. For this purpose, we adopt an adaptation mechanism based on differential evolution. The study includes the problem statement and its characterization in the literature, as well as the proposed solving approach, experimental setting and results.

Fuzzy Decision Support in the Early Phases of the Fuzzy Front End of Innovation in Product Development

The innovation process may be divided into three areas: the fuzzy front end (FFE), the new product development (NPD) process, and commercialization. Every NPD process has a FFE in which products and projects are defined. Companies tend to begin the stages of FFE without a clear definition and analysis of the process to go from opportunity identification to concepts, and often they even abort the process or start over. Koen’s Model for the FFE is composed of 5 different phases, the first two being Opportunity Identification and Opportunity Analysis, which are the focus of this paper. Furthermore, several tools can be used by designers/managers in order to improve, structure and organize their work during the FFE. However, these tools tend to be selected and used in a heuristic manner. Additionally, some tools are preferred and more effective during specific phases of the FFE; hence an economic evaluation of the cost of their usage is very critical and there is also a need to characterize them in terms of their influence on the FFE. This paper focuses on decision support for managers/designers in their process of assessing the cost of choosing/using tools in the core front end activities, namely Opportunity Identification and Opportunity Analysis. This is achieved by analyzing the Influencing Factors (Firm context, Industry context, Macro environment) along with data collection from managers followed by the automatic construction of fuzzy decision support models (FDSM) of the discovered relationships. The decision support focuses upon the estimate investment needed for the use of tools during the 2 phases cited above. The generation of FDSMs is carried out automatically using a specialized genetic algorithm applied to learning data obtained from 5 experienced managers from 5 different companies. The automatically constructed FDSMs accurately reproduced the managers’ estimations using the learning data sets and were very robust when validated with hidden data sets.Copyright

Fostering distributed business logic in Open Collaborative Networks: an integrated approach based on semantic and swarm coordination

Given the great opportunities provided by Open Collaborative Networks (OCNs), their success depends on the effective integration of composite business logic at all stages. However, a dilemma between cooperation and competition is often found in environments where the access to business knowledge can provide absolute advantages over the competition. Indeed, although it is apparent that business logic should be automated for an effective integration, chain participants at all segments are often highly protective of their own knowledge. In this paper, we propose a solution to this problem by outlining a novel approach with a supporting architectural view. In our approach, business rules are modeled via semantic web and their execution is coordinated by a workflow model. Each company’s rule can be kept as private, and the business rules can be combined together to achieve goals with defined interdependencies and responsibilities in the workflow. The use of a workflow model allows assembling business facts together while protecting data source. We propose a privacy-preserving perturbation technique which is based on digital stigmergy. Stigmergy is a processing schema based on the principle of self-aggregation of marks produced by data. Stigmergy allows protecting data privacy, because only marks are involved in aggregation, in place of actual data values, without explicit data modeling. This paper discusses the proposed approach and examines its characteristics through actual scenarios.

ANTECEDENTS OF RADICAL INNOVATIONS: THE DISCOVERY OF DNA STRUCTURE AND THE INVENTION OF DSL

Outlining and characterizing the antecedents of Radical Innovation is the only way to unveil the complex traits of the path to those innovations that dramatically and irreversibly alter the status quo of the economic and industrial context and structure in which they come to life. The two brief accounts presented in this paper attempt to sketch the paths characterizing both the discovery of DNA structure and the invention of DSL. By digging into the chain of historical events, we aim at understanding the role of time in nurturing ex ante radicalness, the technological combinatorial evolution unchained by different degrees of knowledge recombination, the importance of forgotten and unpublished discoveries, the influence of experimental systems in determining the course of scientific and technological developments, the role of market and technological attributes in redefining the boundaries of industries, the more than often neglected role of the personality of inventors. Accordingly, a number of propositions are advanced and implications concerning ex ante indicators building, policy and ingredients of innovative processes discussed.