Variable Speed Limits. Review and development of an aggregate indicator based on floating car data.

Changing factors (mainly traffic intensity and weather conditions) affecting road conditions require a suitable optimal speed at any time. To solve this problem, variable speed limit systems (VSL) ? as opposed to fixed limits ? have been developed in recent decades. This term has included a number of speed management systems, most notably dynamic speed limits (DSL). In order to avoid the indiscriminate use of both terms in the literature, this paper proposes a simple classification and offers a review of some experiences, how their effects are evaluated and their results This study also presents a key indicator, which measures the speed homogeneity and a methodology to obtain the data based on floating cars and GPS technology applying it to a case study on a section of the M30 urban motorway in Madrid (Spain).

Homogeneization effects of variable speed limits.

Changing factors (mainly traffic intensity and weather conditions) affecting road conditions require a suitable optimal speed at any time. To solve this problem, variable speed limit systems (VSL) - as opposed to fixed limits - have been developed in recent decades. This term has included a number of speed management systems, most notably dynamic speed limits (DSL). In order to avoid the indiscriminate use of both terms in the literature, this paper proposes a simple classification and offers a review of some experiences, how their effects are evaluated and their results. This study also presents a key indicator which measures the speed homogeneity and a methodology to obtain the data based on floating cars and GPS technology applying it to a case study on a section of the M30 urban motorway in Madrid (Spain). It also presents the relation between this indicator and road performance and emissions values.

Identifying the core competence as a key requirement for business model innovation. The case of Airlines as a service industry

Core competencies form the basis of an organization’s skills and the basic element of a successful strategic execution. Identifying and strengthening the core competencies enhances flexibility thereby strategically positioning a firm for responding to competition in the dynamic marketplace and can be the difference in quality among firms that follow the same business model. A correct understanding of the concept of business models, employing the right core competencies, organizing them effectively and building the business model around the competencies that are constantly gained and assimilated can result in enhanced business performance and thus having implications for firms that want to innovate their business models. Flexibility can be the firm’s agility to shift focus in response to external factors such as changing markets, new technologies or competition and a firm’s success can be gauged by the ability it displays in this transition. Although industry transformations generally emanate from technological changes, recent examples suggests they may also be due to the introduction of new business models and nowhere is it more relevant than in the airline industry. An analysis of the business model flexibility of 17 Airlines from Asia, Europe and Oceania, that is done with core competence as the indicator reveals a picture of inconsistencies in the core competence strategy of certain airlines and the corresponding reduction in business performance. The performance variations are explained from a service oriented core competence strategy employed by airlines that ultimately enables them in having a flexible business model that not only increases business performance but also helps in reducing the uncertainties in the internal and external operating environments. This is more relevant in the case of airline industry, as the product (the air transportation of passengers) minus the service competence is all the same.

Developing ontologies for representing data about key performance indicators

Multiple indicators are of interest in smart cities at different scales and for different stakeholders. In open environments, such as The Web, or when indicator information has to be interchanged across systems, contextual information (e.g., unit of measurement, measurement method) should be transmitted together with the data and the lack of such information might cause undesirable effects. Describing the data by means of ontologies increases interoperability among datasets and applications. However, methodological guidance is crucial during ontology development in order to transform the art of modeling in an engineering activity. In the current paper, we present a methodological approach for modelling data about Key Performance Indicators and their context with an application example of such guidelines.