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The purpose of this paper is to investigate aerosol evolution in a planar mixing layer from a Lagrangian point of view. After using Monte Carlo (MC) method to simulate the evolution of aerosol dynamics along particles trajectories, the particles size distributions are obtained, which are unavailable in mostly used methods of moments.

Nucleation and growth of dibutyl phthalate (DBP) particles are simulated using the quadrature method of moments in a planar mixing layer, where a fast hot stream with DBP vapor is mixing with a slow cool stream without vapor. Trajectories of aerosol particles are recorded. MC method is used to simulate the aerosol evolution along trajectories.

Investigation on aerosol evolution along the trajectories prompts to classify these trajectories into three groups: first, trajectories away from the active nucleation zone; second, trajectories starting from the active nucleation zone; and third, trajectories crossing over the active nucleation zone. Particle size distributions (psds) along selected representative trajectories are investigated. The psd evolution exhibits interesting behavior due to the synthetic effects of nucleation and condensation. Condensation growth tends to narrow down the psd, and form a sharp front on the side of big particle size. Nucleation is able to broaden the psd through generating the smallest particles. The duration and strength of nucleation have significant effect on the shape of psd.

As far as the authors knowledge, it is the first simulation of aerosol evolution that takes a Lagrangian point of view, and uses MC simulation along particles trajectories to provide the particles size distribution.

The evolution of technology has become the mainstream of the current technological innovation era. Technological change is organized in its unique pattern and a new approach that takes place in a systematic and selective manner. Such change is generally molded with the amalgamation of various factors, namely, economic, social or scientific and technological. This paper aims to focus on identifying technological trajectories in a technological ecosystem with the case of m-payment technology.

This study constructs a patent citation network for mobile payment service technology through patent citation data and identifies the main evolution process using the main path analysis of the network. The scope of this study focuses on key innovation using social network analysis and patent citation network, validated using the case of a mobile payment system and analyzing its technological trajectory.

Analyzing technology evolution provides a greater insight of the overall technology landscape to the researcher and practitioner. Analyzing the m-payment technology landscape gives three main categories of m-payment systems: the mobile financial transaction system), the payee mobile device payment selection system and e-wallet services.

The novelty of this research lies in the process of identifying technological evolution using social network and patent citation network analysis. The case of m-payment technology ecosystem is studied quantitatively which is not explored by previous researchers. This research provides a way to develop the main path technology of innovative products or services to identify technology evolution using the case of m-payment landscape.

The use of the 4D trajectory operational concept in the future air traffic management (ATM) system will require the aircraft to meet very accurately an arrival time over a designated checkpoint. To do this, time intervals known as time windows (TW) are defined. The purpose of this paper is to develop a methodology to characterise these TWs and to manage the uncertainty associated with the evolution of 4D trajectories.

4D trajectories are modelled using a point mass model and EUROCONTROL’s BADA methodology. The authors stochastically evaluate the variability of the parameters that influence 4D trajectories using Monte Carlo simulation. This enables the authors to delimit TWs for several checkpoints. Finally, the authors set out a causal model, based on a Bayesian network approach, to evaluate the impact of variations in fundamental parameters at the chosen checkpoints.

The initial results show that the proposed TW model limits the deviation in time to less than 27 s at the checkpoints of an en-route segment (300 NM).

The objective of new trajectory-based operations is to efficiently and strategically manage the expected increase in air traffic volumes and to apply tactical interventions as a last resort only. We need new tools to support 4D trajectory management functions such as strategic and collaborative planning. The authors propose a novel approach for to ensure aircraft punctuality.

The main contribution of the paper is the development of a model to deal with uncertainty and to increase predictability in 4D trajectories, which are key elements of the future airspace operational environment.

The current air traffic management (ATM) operational approach is changing; “time” is now integrated as an additional fourth dimension on trajectories. This notion will impose on aircraft the compliance of accurate arrival times over designated checkpoints (CPs), called time windows (TWs). This paper aims to clarify the basic requirements and foundations for the practical implementation of this functional framework.

This paper reviews the operational deployment of 4D trajectories, by defining its relationship with other concepts and systems of the future ATM and communications, navigation and surveillance (CNS) context. This allows to establish the main tools that should be considered to ease the application of the 4D-trajectories approach. This paper appraises how 4D trajectories must be managed and planned (negotiation, synchronization, modification and verification processes). Then, based on the evolution of a simulated 4D trajectory, the necessary corrective measures by evaluating the degradation tolerances and conditions are described and introduced.

The proposed TWs model can control the time tolerance within less than 100 s along the passing CPs of a generic trajectory, which is in line with the expected future ATM time-performance requirements.

The main contribution of this work is the provision of a holistic vision of the systems and concepts that will be necessary to implement the new 4D-trajectory concept efficiently, thus enhancing performance. It also proposes tolerance windows for trajectory degradation, to understand both when an update is necessary and what are the conditions required for pilots and air traffic controllers to provide this update.

This paper aims to examine whether in old industrial regions, the trajectory of clusters follows that of their corresponding industry or deviates from it and which are the factors that account for cluster evolution. This paper deals with the issue of how established clusters either renew or transform themselves in such regions and how they adapt to changes in their corresponding international industries.

This research paper draws from in-depth case studies on six industrial clusters, takes a longitudinal perspective and uses a multi-level and qualitative analysis. Based on existing literature, the paper suggests and exploratory analytical framework with four alternative scenarios for cluster evolution and three broad factors: cluster knowledge base, social capital at cluster and region-level and public policies.

Clusters do not always follow the life cycle of its dominant industry. The paper clearly shows a diversity of cluster evolution across clusters and even within clusters (at subcluster level). This study suggests that cluster knowledge diversity and heterogeneity allow to broaden the scope of evolutionary trajectories available; the same goes for social capital at cluster and region levels.

The main limitation of this paper lies in its qualitative approach that makes its conclusions more suggestive than conclusive. In any case, further research on other Basque clusters may corroborate or question its findings.

The paper offers an empirical and longitudinal study on cluster evolution, very much needed to the ongoing theoretical discussion on this issue. So far, there are very few empirical studies on cluster evolution with this perspective. At the same time, it presents a theoretical framework to analyse diversity of cluster evolution in old industrial regions that builds on Menzel and Fornah’s (2010) model.

This study aims to propose a visualized model of hot technology evolution to describe its development.

The basic concept is to divide a technological field into a timeline consisting of several patent clusters. Hot technology trajectories are then explored using their continuity, as well as the point in time at which they occur.

Patents in orthopaedics between 1999 and 2014 have been chosen as the research subjects and the field is divided into several hot technology trajectories. A further step is taken by interpreting high-frequency key terms. Three categories – spine-related materials, bone repairing materials and bone plates – have been identified.

The trajectories presented by evolving diagrams allow readers to understand the evolution of hot technology and help analysts to plan layout and strategies to remain competitive.

Patent clusters reflect the knowledge context of technology development. Previous studies have focused on only new technology evolution and have rarely explored the knowledge context of hot patents that have been frequently cited in recent years. Such patents often guide the development of technology.

The thought and rationale of sustainable competitive advantage in strategy are significantly influenced by the Schumpeterian models of dynamic competition in IO and evolutionary economics. Yet, most analytical accounts of sustainable competitive advantage fail to explain how firms' investment choices influence, and are simultaneously influenced by, the co‐evolution of “external” industry competition and “internal” firm competences. This paper aims to contribute to the development of a theory of endogenous market structure in strategy.

Two alternative assumptions are developed – concerning temporally heterogeneous firm investment strategy – that lie central to a proposed behavioral theory of endogenous market structure. Additionally, a theoretical description is provided of the endogeneity of the demand‐side determinants of firm investment strategy and industrial market structure. Finally, guidelines are provided for empirical application of [incorporating] the alternative assumptions and theoretical arguments.

It is expected that the theoretical arguments in the paper will influence strategy scholars to develop dynamic models of firm performance that render themselves amenable to sound empirical analyses.

The paper contributes towards developing a theory of endogenous market structure in strategy.

Despite the growing interest regarding the Brazilian rice industry, there is not much literature focusing on the role of the institutions in the process of technological capability accumulation and in the formation of the technological trajectories within this industry. This paper aims to discover the role of local institutions in the generation and dissemination of knowledge for creating the technological capability that can define different technological trajectories, using the Brazilian rice industry as an empirical field.

To achieve said objective, this paper uses secondary data (documental research) and a multiple case study design based on primary empirical evidence (content analysis and direct observation) about the Brazilian rice industry.

The paper’s main contribution is the empirical application of a framework that allows us to evaluate the institutions’ roles and activities and how these capabilities evolve as the firms’ technological levels progress and the technological trajectory is formed. Regarding aspects related to public policy, the authors found some implications that are mainly related to the need to consolidate this type of institution in developing countries with the goal of strengthening its technological capabilities, allowing these countries to operate on the technological boundary and to compete with developed countries.

There are few attempts to relate the technological capability, technological trajectories and institutions in the Brazilian rice industry. Therefore, to the best of the authors’ knowledge, the novelty of this study lies in the analysis of these theoretical approaches in this industrial sector, more specifically, in the Brazilian rice industry.

This study aims to propose a methodology by integrating three approaches, namely, internal core technology, external knowledge flow and industrial technology development to help companies improve their decision-making quality for technology planning and enhance their research and development (R&D) portfolio efficiency.

The primary focus of this study is thin-film solar technology and patent data is retrieved from the United States Patent and Trademark Office (USPTO) database. This study presents a methodology based on the proposed integrated analysis method, constructed with patent indicators, centrality analysis of social networks and main path analysis.

The results of this study can be itemized as – the core technological competency: companies involved in two specific technology fields have lower strength in R&D portfolio than leading companies with single-core technology. Knowledge flow: most companies in a network are knowledge producers/absorbers and technological development: diverse source and sink nodes were identified in the global main path during 1997-2003, 2004-2010 and 2011-2017.

Latecomer companies can emulate leaders’ innovation and enhance their technological competence to seek niche technology. Using the global main path, companies monitor outdated technologies that can be replaced by new technologies and aid to plan R&D strategy and implement appropriate strategic decisions avoiding path dependency.

The knowledge accumulation process helps in identifying the change of position and the role of companies; understanding the trend of industrial technology knowledge helps companies to develop new technology and direct strategic decisions. The novelty of this research lies in the integrated approach of three methods aiding industries to find their internal core technical competencies and identify the external position in the competitive market.

The goal of this chapter is to respond to the theoretical inquiries by scholars who are interested in how the public–private partnership (PPP) models adapt to China’s context where political power dictates economic strategies. We also want to provide suggestions to policy designers who aim to promote a sustainable investment environment for domestic and international investors. We review the literature that explains the upside and downside of PPP projects in contemporary China. (1) We classify the trajectory of PPP evolution into four phases, i.e., emergence, growth, recession and revival. (2) We note that private companies take a disadvantageous position in the partnership compared with governments and state-owned enterprises because of a lack of specialized legislation, unequal competition between private companies and state-owned enterprises and the opposition from the civic society. (3) We identify political risks as the most influential risks. Political risks also lead to the misallocation of other risks between public and private parties that contributes to the high failure rate of China’s PPP projects. Based on these findings, we recommend governments to draft specialized legislation, stabilize the political environment and provide favourable subsidies to local governments to limit the risks involved in PPP projects. We also advise private enterprises and state-owned enterprises to focus on negotiating over task and risk division with governments when they make decisions to participate in PPP projects. This full review of studies on PPP development in China provides reliable recommendations to scholars, governments and enterprises.