What Do We Know about Co-Working Spaces? Trends and Challenges Ahead

Future workspace needs flexibility and diversity: A machine learning-driven behavioural analysis of co-working space

The future of workspace is significantly shaped by the advancements in technologies, changes in work patterns and workers' desire for an improved well-being. Co-working space is an alternative workspace solution, for cost-effectiveness, the opportunity for diverse and flexible design and multi-use. This study examined the human-centric design choices using spatial and temporal variation of occupancy levels and user behaviour in a flexible co-working space in London. Through a machine-learning-driven analysis, we investigated the time-dependent patterns, decompose space usage, calculate seat utilisation and identify spatial hotspots. The analysis incorporated a large dataset of sensor-detected occupancy data spanning 477 days, comprising more than 140 million (145×106) data points. Additionally, on-site observations of activities were recorded for 13 days spanning over a year, with 110 time instances including more than 1000 snapshots of occupants' activities, indoor environment, working behaviour and preferences. Results showed that the shared working areas positioned near windows or in more open, connected and visible locations are significantly preferred and utilised for communication and working, and semi-enclosed space on the side with less visibility and higher privacy are preferred for focused working. The flexibility of multi-use opportunity was the most preferred feature for hybrid working. The findings offer data-driven insights for human-centric space planning and design of office spaces in the future, particularly in the context of hybrid working setups, hot-desking and co-working systems.

Clustering Cities over Features Extracted from Multiple Virtual Sensors Measuring Micro-Level Activity Patterns Allows One to Discriminate Large-Scale City Characteristics

The impact of micro-level people's activities on urban macro-level indicators is a complex question that has been the subject of much interest among researchers and policymakers. Transportation preferences, consumption habits, communication patterns and other individual-level activities can significantly impact large-scale urban characteristics, such as the potential for innovation generation of the city. Conversely, large-scale urban characteristics can also constrain and determine the activities of their inhabitants. Therefore, understanding the interdependence and mutual reinforcement between micro- and macro-level factors is critical to defining effective public policies. The increasing availability of digital data sources, such as social media and mobile phones, has opened up new opportunities for the quantitative study of this interdependency. This paper aims to detect meaningful city clusters on the basis of a detailed analysis of the spatiotemporal activity patterns for each city. The study is carried out on a worldwide city dataset of spatiotemporal activity patterns obtained from geotagged social media data. Clustering features are obtained from unsupervised topic analyses of activity patterns. Our study compares state-of-the-art clustering models, selecting the model achieving a 2.7% greater Silhouette Score than the next-best model. Three well-separated city clusters are identified. Additionally, the study of the distribution of the City Innovation Index over these three city clusters shows discrimination of low performing from high performing cities relative to innovation. Low performing cities are identified in one well-separated cluster. Therefore, it is possible to correlate micro-scale individual-level activities to large-scale urban characteristics.

Understanding the shared working spaces: a Geography of Co-working supply in Delhi

The present paper investigates the location pattern of co-working spaces in Delhi which is absent in the existing body of knowledge. Delhi is a political, administrative, educational, scientific and innovation capital that accommodates many co-working spaces in India. We developed Ordinary least squares (OLS) and geographically weighted regression (GWR) models to understand the associations of co-working spaces of digital labourers with other urban socio-economic, services and lifestyle variables in Delhi using secondary data for 117 coworking locations in 280 municipal wards of NCT-Delhi. Model diagnostic suggested that the GWR model provides additional information regarding geographical distribution of coworking spaces, and density of bars, median house rent, fitness centres, metro train stations, restaurants, cinemas, cafés, and creative enterprises are statistically significant parameters to estimate them. The importance of coworking spaces has increased in the post-disaster period, so this study informs public policies to benefit people and companies who choose coworking routes, and recommends urban planners, developers, and real-estate professionals to consider the proximity of creative industries in planning and developing coworking spaces in the future. Also, in the post COVID-19 period, to increase local jobs and long-term place sustainability, a localised policy intervention for coworking spaces in Delhi is highly recommended.

Access-Based Consumption in the Built Environment: Sharing Spaces

The pressing need to implement a more circular economy has led to advancements in the research field. In the spatial context, sharing spaces and access-over-ownership models have the potential to mitigate the detrimental environmental impacts of space use. This study aims to adapt an existing theoretical framework on access-based consumption to the spatial context. We utilise a qualitative case study approach exploring a variety of shared spaces from Northern Europe. Our findings suggest that shared spaces and their organisation are inherently fluid. The study further reveals that the physical object of sharing, even in the case of shared spaces, is being partially replaced with virtual and hybrid solutions. In fact, a hybrid solution seems to enable organisations delivering shared spaces to be more dynamic. Finally, we find that in the spatial context, two types of political consumerism prevail: decommercialization of spaces on the one hand and promoting environmental sustainability on the other. This study is the first to suggest a holistic framework for access-based consumption in the spatial context. The findings will be useful to scholars and practitioners engaged in developing, owning and providing services for shared spaces.

Analogy in the Civil Law Assessment of Co-Working Agreements in Russia

The study’s relevance stems from the wider and more active use of shared workstations and the increasing demand for an adequate civil law assessment of contractual co-working relations. The research goal was to identify and, using the analogy, evaluate possible models of legal assessment of co-working contracts from the perspective of civil law. The research methods include special technical and legal tools, such as legal modeling, doctrinal civil means of analysis and synthesis, induction and deduction, and generalization. The research identified the theoretical and law enforcement ambiguity in the legal assessment of co-working contracts and the recommendations on the direct and analogic application of existing civil law instruments to solve this problem. The significance of the study includes its potential to promote co-working as an innovative format for organizing business, work activities, and contributing to an overall increase in the efficiency of civil transactions in Russia. The results of the work may be useful not only for Russian actors, but also for actors in those jurisdictions where co-working also does not have a direct civil law enforcement. At the same time, the research focuses on the potential of analogy in overcoming the ambiguity of the legal regime of new economic phenomena and in creating new legal structures.

Smart City Thailand: Visioning and Design to Enhance Sustainability, Resiliency, and Community Wellbeing

A “Smart City” framework was used to investigate and develop visions of alternative futures for a peri-urban superblock north of Bangkok, Thailand. The Smart City framework considers seven smart pillars: environment, economy, energy, mobility, people, living, and governance, with a focus on community wellbeing that is supported by information and communication technology (ICT). A mixed-method approach that included: community and industry surveys, both online and face-to-face (total n = 770); in depth, semi-structured, stakeholder interviews; passive participant observation; and photo-documentation was used to inform and organize the project visions and designs. Several themes emerged from the community surveys and key stakeholder interviews: (i) connected green space is highly valued and effectively links multiple smart pillars, enhancing community wellbeing and resiliency to flooding; (ii) superblock mobility, connectivity, and sustainable development could be achieved through a seamless, integrated public-transit system following the principles of transit-oriented development (TOD); (iii) the superblock should prepare for the implementation of Thailand 4.0 through the improved programmatic and physical integration of local industry, community, and universities, including plans for a Digital Village and co-work space. Example designs that address these considerations and vision alternative futures for the superblock are presented in this Smart City case study.

Learnings from User Digital Trail Post-Occupancy Evaluation before COVID-19 for Future Workplace Analysis and Design

Data are required for optimizing workplace design, assessing user experience, and ensuring wellbeing. This research focuses on the benefits of incorporating post-occupancy evaluation (POE) data analysis by studying the digital trail of employees generated by the existing Wi-Fi infrastructure of the office. The objective is to enable a safe return to offices through compliance with COVID-19 space-capacity regulations and in consideration of the health and wellbeing of employees. Workplaces, teams, and people have become more digitalized and therefore more mobile due to the globalization of knowledge and cutting-edge technological innovations, a process that has been accelerated by the COVID-19 crisis. Now, hybrid work and fully remote working routines are increasing in a significant number of companies. Nevertheless, with the return to the office, understanding how to calibrate spatial capacity is now key for workplaces and companies. Traditional assessment methods are obsolete; new methods that respond to mobility, changing occupancy rates, and comfort are essential. This paper analyzes, through the case study of a pre-COVID-19 activity-based office, the advantages of using digital indoor-location techniques (such as Wi-Fi networks, which additionally have the advantage of being previously installed in the majority of these spaces). The paper demonstrates that the incorporation of digital POE of user trends enabled a more seamless, accurate, and scalable return to a new normal office work scenario and an improved post-COVID-19 design of workplaces.