Technology Emergence as a Structuring Process:A Complexity Theory Perspective on Blockchain

Drawing on complexity theory, we investigate the structuring processes and underlying mechanisms underpinning the emergence of a new technology. Empirically, we track the emergence of blockchain technology by examining international patents issued between 2009 and 2020. Our results indicate that technology emergence follows an evolutionary trajectory that progresses from disordered to structured interactions among the technological elements, culminating in the formation of a technological core that acts as a pole of attraction for further interactions and delineates boundaries within the technological domain. Technology structuring is fueled by what we term “technology fitness” and “self-reinforcing” mechanisms that progressively transform primitive structures into more complex, self-organized configurations. Our study offers a novel framework of technology emergence, highlighting how dispersed bits of technological knowledge gradually aggregate into complex structures that define the specific trajectory of a particular domain

Combining exploitation and exploration through crowdsourcing: The case of Starbucks

In this paper, we explore the concept of crowdsourcing as a driver of the ambidexterity innovations capabilities and as a strategic tool to combine exploitation and exploration strategies in the innovation generation process. In doing so, we focus on the case of Starbucks Corporation, an international coffee and coffeehouse chain considered the largest coffeehouse company in the world

Predicting dissolved organic carbon partition and distribution coefficients of neutral and ionizable organic chemicals

Estimating KDOC (dissolved organic carbon/water partition coefficient) and DDOC (dissolved organic carbon/water distribution coefficient) of neutral and ionizable organic chemicals is a crucial task for assessing mobility, modelling transport, environmental fate of a variety of chemicals and for evaluating their bioavailability in terrestrial and aquatic environments. A critical literature search of reliability-selected KDOC and DDOC values was performed to setup novel predictive relationships for KDOC and DDOC of neutral and ionizable organic chemicals. This goal was pursued by using: 1) LSER (linear solvation energy relationship) models to predict KDOC for neutral chemicals using Abraham solute parameters calculated for different DOC sources (all DOC sources together, soil porewater, surface water, wastewater and Aldrich humic acid (HA)); 2) linear regressions for predicting DDOC of organic acids from the octanol/water partition coefficient (Log KOW or Log P) and the dissociation constant (pKa), accounting separately for the contribution of the neutral and ionic fraction. The proposed models predicted Log KDOC and DDOC values within a root mean square deviation (RMSD) generally smaller than 0.3 log units

A collective reasoning on the automotive industry: A patent co-citation analysis

While collective cognition has received increasing attention in the broader field of organization, academic research has largely overlooked its potential role on shaping innovation trajectories and technological change adaptation at a firm and industrial levels. Through a strategic lens and based on the patent bibliometrics and patent co-citation methods, we integrate and extend the cognition and technology strategy literatures by proposing an invention behavior map of leading companies and groups in the automotive industry. How collective cognition influence patent strategies? How economic trends impact on patent paths? Empirical evidence for these reasons is drawn from a longitudinal patent analysis quantitative approach of the period 1991-2013 considered overall and consequently subdivided into three sub periods of seven years each 1991-1997, 1998-2004, 2005-2013. About 443.000 patents, 1.108.356 citations and 1.234.623 co-citations of 49 automotive assignees were collected from Derwent Innovation Index (DII), the largest world patent and innovation database. Multi dimensional scaling and cluster analysis techniques are employed to detect embryonic cognition homogeneity measures and provide an overview of groups technology composition and companies innovation strategies trends. Finally, explorative findings are discussed below with suggestions about how they might be translated into managerial implications

The Challenges of Deliberative Decision Process: an Italian Case

The potential impact of new ICT on efforts to enhance citizen engagement in the policy process is now widely recognized, but the academic research on design, use and evaluation of e-engagement tools is still in its infancy. Through the use of an explorative case study, the aim of this paper is to consider how new ICT tools can be used to reinforce e-democracy and how the design of technology can facilitate citizen engagement. To this intent, we apply a new framework to evaluate the efficacy of some electronic tools used by a specific e-democracy project that involve, with different results, eight Italian Administrations. We have assessed the level of e-democracy developments based on four different dimensions: transparency, interactivity, usability and web site maturity