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Multi-sided platforms (MSPs) are one of the dominant designs of the digital age. However, prior research focuses mainly on established MSPs, leaving little insight into their emergence. We use the literature on technological trajectories and technology diffusion to derive four propositions that increase our understanding on the emergence of MSPs. The propositions include the emergence of native MSPs based on the assimilation of technologies in technological trajectories; how uncertainty influences incumbents to not follow those trajectories; how native MSPs create new demand; and how this demand eventually triggers the transformation process of incumbents to transform toward an MSP provider. We conduct a multiple-case study in the context of mobility services with three native MSP companies along with an incumbent that is transforming toward an MSP provider. The resulting process model shows that MSPs follow a process of sense-making and bricolage to assemble a service-oriented architecture, contrary to the incumbent who adopts technologies according to its institutional logic to improve existing products and processes.

This article theorizes the relationship between two ways of “seeing” and organizing urban mobility markets: the abstract, algorithmic vision of the mobility platform and the experiential, relational vision of the platform driver. Using the case of mobility platforms in Jakarta, we empirically demonstrate how drivers experience the limitations of the platform's visions and how they deploy their own alternative visions of work and the city. We offer this drivers’ “View from Within” as a counterpoint to the visions of the platform, decentering the platform's visions as the sole arbiter of change and optimization in the city. At the same time, we disrupt the assumed binary between these views, showing how they exist in a complex dance of complementarity and contestation. We conclude with a discussion on the opportunities this entanglement presents for worker agency in the algorithmic market, the hurdles toward more “worker centered design” in platform economies and the tensions between globalizing technological solutions and their localized instantiations. Through this article, we argue for seeing deep, embedded relationships as culturally and historically important modes of urban life which technology has to interact with but cannot fully capture nor do away with.

Background: Mobility plays a fundamental role in causal reasoning (causal inference or cause–effect learning), which is essential for brain development at early ages. Children naturally develop causal reasoning through interaction with their environment. Therefore, children with severe motor disabilities (GMFCS levels IV–V), who face limited opportunities for interaction, often show delays in causal reasoning. Objective: This study investigates how a wheelchair-mounted, semi-autonomous mobility platform operated via a simple switch may enhance causal learning in children with severe disabilities, compared with traditional therapies. However, due to the scarcity of participants who meet the inclusion criteria and the need for long-term evaluation, recruitment poses a significant challenge. This study aims to provide an initial assessment of the platform and collect preliminary data to estimate the required sample size and number of sessions for future studies. Methods: We conducted a pilot randomized controlled trial (RCT) to assess platform usability and its effect on reaction time and keystroke accuracy. Four children, aged 8.5 ± 2.38, participated in seven 30 min sessions. They were randomly assigned in equal numbers, with two participants in the intervention group (using the platform) and two in the control group (receiving standard therapy). Usability was evaluated through a questionnaire completed by two therapists. Key outcome measures included the System Usability Scale (SUS), reaction time (RT), and keystroke accuracy (NIS). Results: Despite the small sample size and recruitment challenges, the data allowed for preliminary estimates of the sample size and number of sessions required for future studies. Therapists reported positive usability scores. Children using the platform showed promising trends in RT and NIS, suggesting improved engagement with cause–effect tasks. Conclusions: The findings support the feasibility and usability of the mobility platform by therapists, although some improvements should be implemented in the future. No conclusive evidence was found regarding the platform’s effectiveness on causal learning, despite a positive trend over time. This pilot study also provides valuable insights for designing larger, statistically powered trials, particularly focused on NIS.

The aim of the study is to present a methodology for analyzing pollution emissions in a medium-sized city using modern traffic simulations in the aspect of minimizing exhaust emissions. The scope of the research and the methods of analysis used differ from those applied in big cities projects that can be found in the literature, Therefore the progressive elaboration model has been applied methodically to formulate and carry out the feasibility study. To perform microscopic traffic simulations, the software Simulation of Urban Mobility (SUMO—German Aerospace Center (DLR), Berlin, Germany) was applied. Thanks to the simulations, changes in traffic organization were accurately identified in the context of pollution emissions before they were implemented. The proposed approach allows a smooth flow of vehicles and a reduction of exhaust emissions. The experiments, supported by visual modelling of traffic with respect to pollution emissions, were performed on one of the main arteries of the city of Czestochowa (Poland). The results were used to explain the benefits of planned roadworks and convince the city government of the necessity to modernize the communication network.

BackgroundMerwede is an envisioned neighbourhood in Utrecht (the Netherlands) that provides an instructive case to learn about the governance challenges of digital mobility platforms. Unique about Merwede is how the development of a mobility platform is envisioned to be integrated into the development of a new neighbourhood.MethodologyThis article discusses the case of Merwede and provides insights into its proposed mobility platform and how it is made. It illuminates governance challenges relevant to the design and operation of an unconventional mobility concept by disentangling outstanding practical issues concerning three key governance dimensions—organizational structures, decision-making processes, and instruments.ResultsThe research provides an empirical illustration of governance questions that come up when mobility becomes a service and is integrated into the urban fabric from the very beginning of a development process. Already in the plan development stage, Merwede illustrates that difficult decisions are to be made and competing interests come to the fore.

Bioinformatics is research intensive field where agents operate in highly dynamic environment. Due to extensive research in this domain leads to basic but important problems for the researchers that are (1) Bandwidth (2) storage and (3) computation. We are using agent migration approach to reduce the network load and resolve the resource problem for the client by using server side resources for the computations on large data. The proposed approach does not demand extra storage and extensive computational resources on clients slide fsage. It solves the problem of bandwidth, storage, computation. Our results show that this approach saves the time of the user up to 12.5 % approximately, depending on the size of the data. Similarly the agent can work like a mashup to get heterogeneous data from different service providers and presents in homogeneous shape to its owner.

In recent years, the number of urban travel modes has increased significantly and now includes services such as carsharing, e-hailing, ridesharing and bikesharing. This development potentially contributes to more sustainable urban mobility, but also creates complexity for the customer. To simplify customer offerings, so-called multimodal mobility platforms (MMPs) have emerged, bundling the different mobility services to find the best route for the user. These platforms also function as marketplaces where customers can purchase mobility services from different suppliers. As part of this process, data is being generated, which can be utilized to yield valuable insights for suppliers and platform operators. In this paper, we describe the business model of MMPs and provide an overview of currently active solutions. Subsequently we present specific use cases, showing how suppliers can leverage the analytics possibilities of MMPs and how this affects the business model.

In this paper the authors explain the use of gamification as a way to optimize mobility patterns within a heavily congested European City. They explore this from two perspectives, first by outlining a gaming concept and secondly by explaining how the use of a mobility game that took place in two locations can be used to explore incentives and design issues.

PurposeMobility as a service (MaaS) is a new model of bundling personal transport options from multiple providers to provide frictionless service. The model integrates information and service to enable users to search, book and pay through a single digital platform. The aim of MaaS is to minimize individual car ownership and revolutionize personal mobility habits in favour of sustainable modes. Thus, it is important to understand consumers' readiness for MaaS. This study explains the factors that influence MaaS adoption.Design/methodology/approachA comprehensive review of the related literature has been conducted, leading to the development of a conceptual model for investigating the key factors that influence MaaS adoption. The model draws upon the digital platform, schema congruity and planned behaviour theories. The model is then tested using structural equation modelling and survey data collected from 331 respondents.FindingsThe findings indicate that MaaS information schema congruity, the digital platform's personalizability, customizability, functional integration, network integration and governance of data together with attitude towards MaaS and subjective norm concerning MaaS influence MaaS adoption. Furthermore, MaaS digital platform expectation and MaaS information schema congruity contribute to users' attitude towards MaaS use.Originality/valueThe paper highlights the design and informational attributes of MaaS platforms that influence their adoption and contributes an integrated research model that links digital platform characteristics, behavioural factors and information schema congruity. Future research can use the constructs and measures we developed in this study to build deeper understanding of what contributes to the success of digital platforms.

The major benefits of integrating ion mobility (IM) into LC–MS methods for small molecules are the additional separation dimension and especially the use of IM-derived collision cross sections (CCS) as an additional ion-specific identification parameter. Several large CCS databases are now available, but outliers in experimental interplatform IM-MS comparisons are identified as a critical issue for routine use of CCS databases for identity confirmation. We postulate that different routine external calibration strategies applied for traveling wave (TWIM-MS) in comparison to drift tube (DTIM-MS) and trapped ion mobility (TIM-MS) instruments is a critical factor affecting interplatform comparability. In this study, different external calibration approaches for IM-MS were experimentally evaluated for 87 steroids, for which TWCCSN2, DTCCSN2 and TIMCCSN2 are available. New reference CCSN2 values for commercially available and class-specific calibrant sets were established using DTIM-MS and the benefit of using consolidated reference values on comparability of CCSN2 values assessed. Furthermore, use of a new internal correction strategy based on stable isotope labelled (SIL) internal standards was shown to have potential for reducing systematic error in routine methods. After reducing bias for CCSN2 between different platforms using new reference values (95% of TWCCSN2 values fell within 1.29% of DTCCSN2 and 1.12% of TIMCCSN2 values, respectively), remaining outliers could be confidently classified and further studied using DFT calculations and CCSN2 predictions. Despite large uncertainties for in silico CCSN2 predictions, discrepancies in observed CCSN2 values across different IM-MS platforms as well as non-uniform arrival time distributions could be partly rationalized.