PurposeThe aim of the article is to determine research areas and to recognize the current direction in the development of maturity models, to indicate the key areas of organizational maturity models (OMMs) development and their classification as well as to pinpoint research gaps and areas of potential development of OMMs in the context of scientific research and the needs of management practitioners.Design/methodology/approachThe research was conducted using the literature review method, bibliometric analysis and visual mappings.FindingsThe empirical classification developed in this paper identified 12 categories based on management areas, constituting the criteria for classifying OMMs models, where OMMs are being developed: Information Technology, Project Management, Business Management and Strategy, Human Resource, Ergonomics, Health and Safety Management, Industry 4.0 concept, Knowledge Management, Process Management, Performance Management, Quality Management, Supply Chain Management, Risk Management and Innovation Management.Research limitations/implicationsThe main limitation is the analysis in the scope of topic OMMs including solely the Scopus and Thompson Reuters Web of Science database. Another shortcoming is conducting data analysis and classification based on the abstracts of the selected articles.Originality/valueThis work is a starting point to prospect trends for future revolving around the OMMs crossing different databases.

Cycling is gaining priority in urban mobility policies and smart cities should be prepared to offer smart cycling services that help to promote such transition. A key element for many of those services is a Geographic Information System and particularly a road network model that represents all the possible roads in a city. The main contribution of this work is the identification and characterization of an important gap between the GPS traces corresponding to the real routes made by cyclists and their representation in the road network model of Open Street Map (OSM). More specifically, there are parts of the GPS traces that cannot be mapped into the road network of OSM, because they have no matching representation. We call these segments, ad-hoc segments. To develop a deeper understanding about this problem, we collected data from a specially designed route and analysed how the respective trace was mapped into OSM. We identified all the occurrences of adhoc segments and categorized them according to their root cause. The results suggest that the main overall cause of these problems is directly linked with limitations of the road network model, such as missing roads. This seems to indicate that road network models, as commonly used in OSM, do not properly address the specificities of cycling, or micro-mobility in general. This problem has a major impact in the quality of the services provided to urban cyclists and in the value of the data available for micromobility planning and management.

Manufacturing leanness and agility are requirements of today's manufacturing systems. Leanness call for a best fit of the manufacturing systems to products, therefore requiring product oriented manufacturing systems (POMS). Manufacturing agility can be achieved through easy systems reconfiguration to

Bicycles equipped with sensors, processing capacity and communications can be a promising source of data about the personal and the collective reality of urban cycling. While this concept has been attracting considerable interest, the key assumption is the design of a closed system where a uniform set of sensing bicycles, with a concrete set of sensors, is used to support a specific service. The core challenge, however, is how to generalise sensing approaches so that they can be collectively supported by many heterogeneous bicycles, owned by a multitude of entities, and integrated into a common ecosystem of urban data. In this work, we provide a comprehensive analysis of the design space for onbike sensing. We consider a diverse set of sensing alternatives, the potential value propositions associated with their data, and the collective perspective of how to optimise sensing by exploring the complementarities between heterogeneous bicycles. This broader perspective should inform the design of more effective sensing strategies that can maximise the overall value generated by bicycles in smart cycling ecosystems and enable new cycling services.

The full potential of ITS can only be achieved in a global scale and combining the efforts and the knowledge of multiple entities. This is also true for the current efforts towards the application of data, communications and services, to improve cycling and its integration into general mobility systems. The currently prevailing paradigm is based on disperse and self-contained custom processes, which fail to promote distributed and open innovation. These models are hard to reproduce, generalize, recombine or improve outside the context in which they were originally implemented. A digital platform strategy might offer a viable and scalable way to support convergence between multiple models and promote their usage as shared references for cycling ecosystems. In this work, we aim to validate our assumptions about the limitations of current development paradigms and analyse the extent to which a platform strategy could offer a fundamentally different approach to address those limitations. To validate the problem and uncover generalisation opportunities, we study 3 cycling mobility models and make an initial analysis of how the general principles of digital platforms could be applied as a general framework for a new type of solution for cycling analytics. The results confirm a high potential for horizontal features and outline a set of key design principles for the development of a digital platform strategy for cycling analytics. This should constitute a major contribution to inform the development of a new generation of cycling platforms for urban environments.