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The purpose of this article is to study what platform-related user factors influence the employment potential of a lean platform for self-employed professionals.

The article employs the system data of a Dutch platform firm, which include consumers looking for painters (N = 17,224) and self-employed painters (N = 1,752) who pursue client acquisition by submitting proposals (N = 101,974). This data is analysed using non-parametric tests.

Study of this platform shows that the platform functions as a channel of acquisition for self-employed professionals. This lean platform enables matching of information of supply and demand, thereby facilitating processes of acquisition. The number of competitors, distance to a potential job and non-standard proposals are statistically significant factors that influence whether a consumer is interested in a proposal. Effect sizes are very small.

This platform is a two-way market for information about service jobs, which excludes a price setting mechanism. The findings of this study cannot be generalized to other forms of platforms.

The market for service professionals is very local; therefore, the platform firm may alter the algorithm to accommodate this. Self-employed professionals should approach using the platform in the same way as normal forms of acquisition.

This particular type of two-sided market is an extension of regular forms of acquisition by creating “weak ties” through the platform.

The article uses a unique data set to study the impact and limitations of digitalization of the (labour) market for service professionals.

This article aims to understand the role of intermediaries that manage innovation challenges in the healthcare scenario. More specifically, it explores the role of digital platforms in addressing data challenges and fostering data-driven innovation in the health sector.

For exploring the role of platforms, the authors propose a theoretical model based on the platform’s dynamic capabilities, assuming that, because of their set of capabilities, platforms may trigger innovation practices in actor interactions. To corroborate the theoretical framework, the authors present a detailed in-depth case study analysis of Apheris, an innovative data-driven digital platform operating in the healthcare scenario.

The paper finds that the innovative data-driven digital platform can be used to revolutionize established practices in the health sector (a) accelerating research and innovation; (b) overcoming challenges related to healthcare data. The case study demonstrates how data and intellectual property sharing can be privacy-compliant and enable new capabilities.

The paper attempts to fill the gap between the use of the data-driven digital platform and the critical innovation practices in the healthcare industry.

This paper aims to provide top-level design and basic platform for intelligent application in China high-speed railway.

Based on the analysis for the future development trends of world railway, combined with the actual development needs in China high-speed railway, The definition and scientific connotation of intelligent high-speed railway (IHSR) are given at first, and then the system architecture of IHSR are outlined, including 1 basic platform, 3 business sectors, 10 business fields, and 18 innovative applications. At last, a basic platform with cloud edge integration for IHSR is designed.

The rationality, feasibility and implementability of the system architecture of IHSR have been verified on and applied to the Beijing–Zhangjiakou high-speed railway, providing important support for the construction and operation of the world’s first IHSR.

This paper systematically gives the definition and connotation of the IHSR and put forward the system architecture of IHSR for first time. It will play the most important role in the design, construction and operation of IHSR.

The paper aims to explore the value generated by a specific configuration of a smart city's infrastructure by proposing a comparison between a silos configuration versus a crowd configuration at the data storage and processing level.

A system dynamics simulation is adopted to determine and compare the value created by the two configurations of smart city's infrastructure. The simulation outlines the flow of data and their positive and negative feedback that reinforce and hinder the smart city value generation.

The results demonstrate the huge impact of the availability of data for App developers when crowdsourcing configuration is adopted. Furthermore, results unveil the potential in value generation of a crowdsourcing smart city platform configuration compared to a silos architecture.

The authors have proposed a comparison between two alternative smart city digital platform configurations. The paper seeks to test the magnitude of the pros and cons of a crowdsourcing approach in setting up a smart city digital platform. The paper provides new guidelines for improving the data management of smart cities.

The paper explores the emergence of smart city governance with a particular focus on the cognitive value of the new technologies and the different accountabilities emerging in the digital infrastructures attempting to visualize and rationalize urban dynamics.

Drawing on ethnographic, netnographic and interview data from an empirical case study of the Smart and Wise City Turku spearhead project, the study builds on the assumption that smart cities emerge from the interaction between the characteristics of technologies, constellations of actors and contextual conditions.

The results report smart city activities as an organizational process and a reconfiguration that incorporates new technology with old infrastructure. Through the lens of the empirical examples, we are able to show how smart city actors, boundaries and infrastructures are mobilized, become valuable and are rendered visible. The smart cities infrastructure traces, values and governs actors, identities, objects, ideas and relations to animate new desires and feats of imagination.

In terms of implications to practice, the situated descriptions echo recent calls to leaders and managers to ask how much traceability is enough (Power, 2019) and limits of accountability (Messner, 2009).

The central theoretical concept of “thinking infrastructure” highlights how new accounting practices operate by disclosing (Kornberger et al., 2017) new worlds where the platforms and the users discover the nature of their responsibilities to the other. The contribution of this paper is that it examines what happens when smartness is understood as a thinking infrastructure. Different theorizations of infrastructure have implications for the study of smart cities. The lens helps us grasp possible tensions and consequences in terms of accountability that arise from new forms of participation in smart cities. It helps urban governance scholarship understand how smartness informs and shapes distributed and embodied cognition.

This article examines the ways in which the popular music industry markets artists through integrated transmedia marketing campaigns. These campaigns unfold across multiple media and create multiple pathways for audience engagement, particularly fan engagement, across social media platforms. The purpose is to further theorise the relationship between artists, the music industry and audiences.

The study used digital ethnography to scrutinise the activities within a contemporary music transmedia marketing campaign, focusing on the release of Taylor Swift's album Reputation as an illustrative case.

The study demonstrates how strategically curated activities encompass platforms' affordances and industry events by making use of fan engagement across social media platforms and streaming services. Fans shift through platforms, as well as across digital and physical spaces, through defined marketing activities at specific times. This article proposes the concept of choreographed engagement to specifically address the ways in which the temporal and spatial aspects of social media marketing are used at the intersection of platform logic, algorithm economy and fan engagement to reach wider audiences.

By proposing the concept of choreographed engagement, the authors bridge the gap between fan practices and marketing practices, providing insight into how commodification of fan engagement is utilised spatially and temporally within the contemporary platform economy. Choreographed engagement constitutes a significant aspect of strategic communication and marketing. The term expands the vocabulary used in the debate on the commodification of artistic work, and audience engagement in the platform era.

Buildings and their use is a complex process from design to occupation. Buildings produce huge volumes of data such as building information modelling (BIM), sensor (e.g. from building management systems), occupant and building maintenance data. These data can be spread across multiple disconnected systems in numerous formats, making their combined analysis difficult. The purpose of this paper is to bring these sources of data together, to provide a more complete account of a building and, consequently, a more comprehensive basis for understanding and managing its performance.

Building data from a sample of newly constructed housing units were analysed, several properties were identified for the study and sensors deployed. A sensor agnostic platform for visualising real-time building performance data was developed.

Data sources from both sensor data and qualitative questionnaire were analysed and a matrix of elements affecting building performance in areas such as energy use, comfort use, integration with technology was presented. In addition, a prototype sensor visualisation platform was designed to connect in-use performance data to BIM.

This work presents initial findings from a post occupancy evaluation utilising sensor data. The work attempts to address the issues of BIM in-use scenarios for housing sector. A prototype was developed which can be fully developed and replicated to wider housing projects. The findings can better address how indoor thermal comfort parameters can be used to improve housing stock and even address elements such as machine learning for better buildings.

This study aims to present a guide for using grounded theory methods for exploring organizational phenomena of the new online era.

A reflexive account is adopted on how one can build upon the foundations of traditional offline grounded theory for conducting grounded theorizing with online-based data.

Guidelines for conducting grounded theory on online contexts are presented for crafting research questions, gathering online data and using consolidated methods for analyzing online data. This study shows future and present challenges posed by the new online era for grounded theorizing, as well as helpful lessons to be learned from traditional offline grounded theory to mitigate them.

The implications are helpful for established qualitative organizational scholars that are yet to catch-up in the boundary spanning process of using the digital sources of data in grounded theory. They are equally helpful for newcomers on qualitative grounded theory by guiding them on where and how to start these challenging research endeavors of grounded theorizing in this new online era.

Scant attention has been given on applications of grounded theory in the new online era. The differences between online and offline settings have not been clearly defined to this date, and neither do guidelines exist for how qualitative grounded theorists can take advantage of online data to build theory about new organizational phenomena emerging in the online era.

This study aims to provide a systematic and complete knowledge map for use by researchers working in the field of research data. Additionally, the aim is to help them quickly understand the authors' collaboration characteristics, institutional collaboration characteristics, trending research topics, evolutionary trends and research frontiers of scholars from the perspective of library informatics.

The authors adopt the bibliometric method, and with the help of bibliometric analysis software CiteSpace and VOSviewer, quantitatively analyze the retrieved literature data. The analysis results are presented in the form of tables and visualization maps in this paper.

The research results from this study show that collaboration between scholars and institutions is weak. It also identified the current hotspots in the field of research data, these being: data literacy education, research data sharing, data integration management and joint library cataloguing and data research support services, among others. The important dimensions to consider for future research are the library's participation in a trans-organizational and trans-stage integration of research data, functional improvement of a research data sharing platform, practice of data literacy education methods and models, and improvement of research data service quality.

Previous literature reviews on research data are qualitative studies, while few are quantitative studies. Therefore, this paper uses quantitative research methods, such as bibliometrics, data mining and knowledge map, to reveal the research progress and trend systematically and intuitively on the research data topic based on published literature, and to provide a reference for the further study of this topic in the future.

Crowdfunding (CF) is a digital-financial innovation that, bypassing credit crisis, bank system rigidities and constraints of the capital market, is allowing new ventures and established companies to get the needed funds to support innovations. After one decade of research, mainly focused on relations between variables and outcomes of the CF campaign, the literature shows methodological lacks about the study of its overall behavior. These reflect into a weak theoretical understanding and inconsistent managerial guidance, leading to a 27% success ratio of campaigns. To bridge this gap, this paper embraces a “complex system” perspective of the CF campaign, able to explore the system's behavior of a campaign over time, in light of its causal loop structure.

By adopting and following the document model building (DMB) methodology, a set of 26 variables and mutual causal relations modeled the system “Crowdfunding campaign” and a data set based on them and crafted to model the “Crowdfunding campaign” with a causal loop diagram. Finally, system archetypes have been used to link the causal loop structure with qualitative trends of CF's behavior (i.e. the raised capital over time).

The research brought to 26 variables making the system a “Crowdfunding campaign.” The variables influence each other, thus showing a set of feedback loops, whose structure determines the behavior of the CF campaign. The causal loop structure is traced back to three system archetypes, presiding the behavior in three stages of the campaign.

The value of this paper is both methodological and theoretical. First, the DMB methodology has been expanded and reinforced concerning previous applications; second, we carried out a causation analysis, unlike the common correlation analysis; further, we created a theoretical model of a “Crowdfunding Campaign” unlike the common empirical models built on CF platform's data.