Strategies for shifting technological systems : the case of the automobile system

Californian and Dutch efforts to produce electric vehicles are explored and compared. Three strategies are put forward that could turn electric vehicles from an elusive legend, a plaything, into a marketable product: technology forcing creating a market of early promises, experiments geared towards niche development and upscaling (strategic niche management), and the creation of new alliances (technological nexus) which bring technology, the market, regulation and many other factors together. These strategies deployed in the Californian and Dutch context are analysed in detail to explore their relative strengths and weaknesses and to argue in the end that a combined use of all three will increase the chances that the dominant technological system will change. The succesful workings of these strategies crucially depend on the coupling of the variation and selection processes, building blocks for any evolutionary theory of technical change. Evolutionary theory lacks understanding of these coupling processes. Building on recent insights from the sociology of technology, the authors propose a quasi-evolutionary model which underpins the analysis of suggested strategies

Optimal advertising campaign generation for multiple brands using MOGA

The paper proposes a new modified multiobjective genetic algorithm (MOGA) for the problem of optimal television (TV) advertising campaign generation for multiple brands. This NP-hard combinatorial optimization problem with numerous constraints is one of the key issues for an advertising agency when producing the optimal TV mediaplan. The classical approach to the solution of this problem is the greedy heuristic, which relies on the strength of the preceding commercial breaks when selecting the next break to add to the campaign. While the greedy heuristic is capable of generating only a group of solutions that are closely related in the objective space, the proposed modified MOGA produces a Pareto-optimal set of chromosomes that: 1) outperform the greedy heuristic and 2) let the mediaplanner choose from a variety of uniformly distributed tradeoff solutions. To achieve these results, the special problem-specific solution encoding, genetic operators, and original local optimization routine were developed for the algorithm. These techniques allow the algorithm to manipulate with only feasible individuals, thus, significantly improving its performance that is complicated by the problem constraints. The efficiency of the developed optimization method is verified using the real data sets from the Canadian advertising industry

Computing the set of Epsilon-efficient solutions in multiobjective space mission design

In this work, we consider multiobjective space mission design problems. We will start from the need, from a practical point of view, to consider in addition to the (Pareto) optimal solutions also nearly optimal ones. In fact, extending the set of solutions for a given mission to those nearly optimal significantly increases the number of options for the decision maker and gives a measure of the size of the launch windows corresponding to each optimal solution, i.e., a measure of its robustness. Whereas the possible loss of such approximate solutions compared to optimal—and possibly even ‘better’—ones is dispensable. For this, we will examine several typical problems in space trajectory design—a biimpulsive transfer from the Earth to the asteroid Apophis and two low-thrust multigravity assist transfers—and demonstrate the possible benefit of the novel approach. Further, we will present a multiobjective evolutionary algorithm which is designed for this purpose

The complexity of transitions

No abstract

Incrementalism of environmental innovations versus paradigmatic change: A comparative study of the automotive and chemical industries

Environmental innovations; technological regime; technological paradigm; environmental regulation; automotive industry; green chemistry