Urban Land Use and Value in the Digital Economy: A Scoping Review of Disrupted Activities, Behaviours, and Mobility

Abstract

The digital economy is fundamentally transforming urban landscapes by disrupting traditional relationships between land use and land value. This scoping review aims to examine how digital transformations alter urban activities, human behaviours, and mobility patterns, and to assess the subsequent impacts on land use planning and land valuation frameworks. Following PRISMA guidelines, Scopus, Web of Science, Google Scholar, and ProQuest databases were systematically searched for peer-reviewed articles published between 2019 and 2024. Inclusion criteria comprised empirical studies, theoretical papers, and case studies examining digital economy impacts on urban land use or land value. Grey literature, non-English publications, and studies without clear urban spatial implications were excluded. The data were synthesised using bibliometric analysis and thematic analysis to identify patterns of disruption across three domains: urban activities, behaviours, and mobility. Of the 512 initially identified articles, 66 studies met the inclusion criteria. The evidence demonstrates significant geographic bias and methodological limitations, including the scarcity of longitudinal studies tracking actual land value changes and inconsistent metrics for measuring disruption intensity. Despite these limitations, findings indicate that the digital economy is decoupling land value from traditional determinants, such as physical proximity to services and employment centres. These transformations necessitate fundamental revisions to urban planning frameworks, land valuation models, and regulatory approaches to ensure equitable and sustainable urban development in the digital age.

1. Introduction

The advent of the digital economy has brought about significant changes in how people live, work, and interact within urban environments. Traditional urban activities, such as retail, commerce, and recreation, are increasingly being augmented or replaced by digital alternatives [1]. This shift is influencing human behaviour, leading to new patterns of consumption, communication, and social interaction [2,3,4]. Simultaneously, digital technologies are transforming mobility with the rise of shared mobility platforms, electric vehicles, and autonomous transportation systems [5,6]. These changes collectively impact land use patterns and, consequently, land value within cities [7].

The conventional understanding of land use and land value is predicated on physical proximity and accessibility to economic opportunities, amenities, and transportation infrastructure [8,9]. Nevertheless, the digital economy challenges these assumptions by reducing the importance of physical location for certain activities and creating new forms of value that are not directly tied to traditional land uses [1,10,11]. For instance, the rise of remote work has decoupled employment from physical workplaces, potentially leading to shifts in residential preferences and demand for office spaces [12]. Similarly, the growth of e-commerce has altered retail patterns, impacting the demand for brick-and-mortar stores and transforming commercial districts [13,14].

Understanding these transformations is essential for urban planners, policymakers, and real estate professionals. Traditional land use regulations and valuation models may no longer accurately reflect the realities of the digital economy, leading to inefficiencies, inequities, and unsustainable development patterns [15,16]. This study will address the following key research questions: (a) how does the digital economy disrupt traditional urban activities, and what are the implications for land use patterns? (b) How does the digital economy influence human behaviour in urban environments, and how do these behavioural shifts affect land demand and value? (c) How does the digital economy transform urban mobility through the emergence of new transportation technologies and platforms, and what are the consequences for land use, accessibility, and urban form? By examining the disruptions caused by the digital economy on urban activities, behaviour, and mobility, this research aims to provide insights that can inform more effective land use policies, valuation methodologies, and urban development strategies. To provide analytical clarity and theoretical coherence, this review employs a tripartite framework that examines digital disruption through these three interconnected lenses.

2. Literature Background

2.1. The Digital Economy and Urban Activities

The digital economy has significantly altered traditional urban activities, such as retail, commerce, and recreation [17,18,19]. The rise of e-commerce has disrupted traditional retail patterns, leading to a decline in brick-and-mortar stores and the emergence of new forms of online shopping [13]. This transformation has implications for the demand for commercial spaces and the vitality of traditional commercial districts. Similarly, the digital economy has facilitated the growth of online services, such as online education, telemedicine, and remote entertainment, which have reduced the need for physical spaces dedicated to these activities [20,21,22]. The shift towards a digital economy has also led to the emergence of new types of urban activities, such as co-working spaces, maker spaces, and innovation hubs [23,24]. These spaces cater to the needs of digital workers, entrepreneurs, and startups, fostering collaboration, creativity, and innovation. They often require different types of land use and infrastructure compared to traditional office spaces, necessitating a re-evaluation of zoning regulations and development policies.

2.2. Digital Economy and Human Behaviour

The digital economy has profoundly influenced human behaviour in urban environments, including consumption patterns, social interactions, and mobility choices [25,26,27]. The proliferation of smartphones, social media, and online platforms has transformed how people consume goods and services, communicate with each other, and access information [28]. These behavioural shifts have implications for land demand and value. For instance, the rise of online shopping has altered consumer behaviour, leading to a greater emphasis on convenience, personalisation, and price transparency [29]. This has reduced the demand for traditional retail spaces and increased the demand for logistics and distribution centres [30,31]. Similarly, the growth of social media has transformed social interactions, leading to a greater emphasis on online communities and virtual experiences [32]. This has implications for the demand for public spaces and community facilities.

2.3. Digital Economy and Urban Mobility

The digital economy has revolutionised urban mobility through the emergence of new transportation technologies and platforms. Shared mobility platforms, such as Uber and Lyft, have transformed how people move around cities, providing convenient and affordable transportation options [33]. Electric vehicles are gaining popularity, reducing reliance on fossil fuels and promoting sustainable transportation [34]. Autonomous vehicles hold the promise of further transforming urban mobility, potentially leading to safer, more efficient, and more accessible transportation systems [35]. These transformations have significant consequences for land use, accessibility, and urban form. The rise of shared mobility platforms may reduce the need for private car ownership, leading to a decrease in demand for parking spaces and a shift towards more pedestrian-friendly and bike-friendly urban environments [36,37,38]. The adoption of electric vehicles may require the development of new charging infrastructure, which could impact land use patterns and energy consumption [39,40]. The deployment of autonomous vehicles may lead to more efficient use of road space, potentially reducing traffic congestion and improving accessibility [41].

3. Research Design

3.1. Methodological Approach

This study employs a scoping review methodology, using PRISMA guidelines to investigate how the digital economy disrupts traditional urban activities, behaviour, and mobility patterns, and their subsequent impacts on land use and land value. This review follows a rigorous three-stage methodological approach adapted from [42], ensuring comprehensive coverage and systematic analysis of the relevant literature. This review is guided by three key research questions, each corresponding to one lens in our analytical framework: (a) Activities Lens: How does the digital economy disrupt traditional urban activities, and what are the implications for land use patterns? (b) Behaviours Lens: How does the digital economy influence human behaviour in urban environments, and how do these behavioural shifts affect land demand and value? (c) Mobility Lens: How does the digital economy transform urban mobility through the emergence of new transportation technologies and platforms, and what are the consequences for land use, accessibility, and urban form? This tripartite structure ensures comprehensive coverage while maintaining analytical coherence throughout this review. This scoping review has been registered with PROSPERO (International Prospective Register of Systematic Reviews), registration number: CRD420251107307, which is an open-access online database for registering review protocols. The full registration record can be accessed at: https://www.crd.york.ac.uk/PROSPERO/view/CRD420251107307, accessed on 10 August 2025.

3.2. Literature Search Strategy

The first stage (Stage 1) was to define the literature search strategy. To ensure comprehensive coverage of the relevant literature, a structured search strategy was developed using Boolean operators to combine key terms related to each research question. Three distinct search queries were formulated: (“urban activities” OR “urban land use” OR “urban functions”) AND (“digital transformation” OR “digital economy”) for addressing urban activities; (“urban behaviour” OR “consumer behaviour” OR “lifestyle changes”) AND (“digital transformation” OR “digital economy”) for examining behavioural aspects; and (“urban mobility” OR “travel behaviour” OR “commuting patterns”) AND (“digital transformation” OR “technological disruption”) for investigating mobility transformations. These search queries were applied to the title, abstract, and keywords fields across four major academic databases. Scopus was selected for its comprehensive coverage of peer-reviewed literature across multiple disciplines, being particularly strong in urban studies, geography, and technology research. Web of Science was utilised for its rigorous selection criteria and citation indexing, ensuring high-quality scholarly publications. Google Scholar was included to capture a broader range of academic literature, including recent publications and interdisciplinary research that might not yet be indexed in traditional databases. ProQuest was employed to access additional academic journals and ensure coverage of publications from diverse geographic regions and emerging research areas.

The systematic search was conducted between November 2024 and December 2024 across all four databases. The initial searches were performed on 15–18 November 2024. To ensure the currency of this review, an update search was performed across all databases on 10 December 2024, which identified an additional eight articles that met the preliminary screening criteria. The temporal restriction to publications from 2019 to 2024 was consistently applied across all search dates to capture recent developments in the rapidly evolving digital economy. Additional filters were applied to ensure quality and relevance, including limiting results to peer-reviewed journal articles, research papers only (excluding reviews, editorials, and conference papers), English language publications, and full open-access articles. The initial search yielded 512 articles across all databases, providing a substantial corpus for systematic review.

In Stage 2, the selection process involved a multi-stage screening approach with clearly defined inclusion and exclusion criteria applied at primary and secondary levels. The primary inclusion criteria specified peer-reviewed research articles with full-text availability online and articles published in academic journals. The primary exclusion criteria eliminated duplicate records across databases, books and book chapters, industry reports, government reports, and policy documents. Application of the primary criteria reduced the initial 512 articles to 244 unique research articles.

Secondary screening criteria were then applied in two phases. The inclusion criteria at this stage required direct relevance to digital transformation impacts on urban activities, behaviour, or mobility; clear alignment with one or more research questions; demonstrable methodological rigour; and provision of empirical evidence or robust theoretical contributions. Articles were excluded if they had only tangential relationships to digital transformation in urban contexts, lacked a clear connection to urban activities, behaviour, or mobility, showed insufficient relevance to the research aims, or were purely descriptive studies without analytical depth. The first phase involved screening the titles, abstracts, and keywords of the 244 articles, resulting in 77 articles deemed potentially relevant. The second phase consisted of a full-text review of these 77 articles against the secondary criteria, yielding a final sample of 66 articles for in-depth analysis. Figure 1 presents a summary of the methodology described above, including the Boolean search terms applied.

3.3. Data Extraction Process

Following the identification of the final 66 articles, a systematic data extraction process was implemented to ensure consistent and comprehensive data collection. A standardised data extraction form was developed and piloted on five randomly selected articles to ensure completeness and usability. The final extraction form captured the following information from each study:

• Bibliographic details (author(s), year, title, journal, country/region);
• Study characteristics (research method, study design, sample size);
• Key findings related to digital economy disruptions;
• Specific impacts on urban activities, behaviours, or mobility;
• Implications for land use patterns and land value;
• Theoretical frameworks or models employed;
• Geographic context and scope of application.

Two reviewers independently extracted data from all the included studies, with each reviewer responsible for the initial extraction from 33 articles. Subsequently, each reviewer verified the extractions completed by the other reviewer to ensure accuracy and completeness. Any discrepancies in data extraction were resolved through discussion and re-examination of the source articles. Where interpretations of implications for land use and value differed, both reviewers jointly reviewed the article to reach a consensus. The extracted data were compiled in a structured spreadsheet, which formed the basis for the thematic analysis and synthesis presented in

Table A1. Urban activity disruption.

Author	Year	Title	Journal	Method	Finding	Reframe the Use and Value of Urban Form	Region
Audouin and Neves [72]	2017	What Regulations for ICT-Based Mobility Services in Urban Transportation Systems? The Cases of Ride-Booking Regulation in São Paulo and Rio de Janeiro	Urban Transport	Case study	Integrating ride-booking services with public transport.	Enhance the efficiency and sustainability of urban mobility.	Brazil
Allam and Newman [75]	2018	Redefining the Smart City: Culture, Metabolism and Governance	Smart Cities	Literature review	Smart City initiatives often focus on technology and corporate branding, neglecting cultural and historical contexts.	Promotes the preservation and enhancement of urban identity and history.	Australia
Caprotti and Cowley [69]	2019	Varieties of smart urbanism in the UK: Discursive logics, the state and local urban context	Trans Inst Br Geogr	Thematic review	Smart-city strategies often invoke crisis to justify technological and policy interventions.	Highlights the need for resilient and adaptive urban forms.	UK
Lee et al. [68]	2020	Mapping Platform Urbanism: Charting the Nuance of the Platform Pivot	Urban Planning	Landscape scan	The growth of markets for smart city products, primarily driven by corporate actors.	Limits the availability of alternatives and raises concerns about the influence of corporate interests on urban governance.	Australia
Rose et al. [71]	2020	Platform Urbanism, Smartphone Applications and Valuing Data in a Smart City	Trans Inst Br Geogr	Interviews	Data generated by the apps were intended to create various forms of value beyond financial profit.	Smart city initiatives can generate multiple forms of value.	UK
Söderström and Mermet [83]	2020	When Airbnb Sits in the Control Room: Platform Urbanism as Actually Existing Smart Urbanism in Reykjavík	Frontiers in Sustainable Cities	Case study	Neighbourhoods with high concentrations of Airbnb listings have experienced changes in their demographic features, retail structures, and local sense of place.	The integration of short-term rentals into residential neighbourhoods blur the boundaries between residential and commercial uses of urban space.	Iceland
Busch et al. [76]	2021	Digital Urban Production: How Does Industry 4.0 Reconfigure Productive Value Creation in Urban Contexts?	Regional Studies	Multiple case study	Urban areas offer a pool of highly skilled workers with the necessary technical and digital skills.	Underscores the value of urban areas as centres of knowledge, innovation, and skilled labour.	Germany
Elwood [67]	2021	Digital geographies, feminist relationality, Black and queer code studies: Thriving otherwise	Progress in Human Geography	Theoretical and analytical approach	Digital urbanism mediates for precarity and racialised inequalities.	Highlight the potential for urban spaces to be re-mediated for collective wellbeing and mutual support.	USA
Hodson and McMeekin [73]	2021	Global technology companies and the politics of urban socio-technical imaginaries in the digital age: Processual proxies, Trojan horses and global beachheads	EPA: Economy and Space	Case study	Sidewalk Labs (SLs) project: a new model of private digital governance that could be circulated globally.	Highlights the potential for global dissemination of urban governance practices.	UK
McGuirk et al. [63]	2021	Municipal Statecraft for the Smart City: Retooling the Smart Entrepreneurial City?	EPA: Economy and Space	Interviews	Municipalities engaged in diverse activities to build public legitimacy for smart city governance.	Municipalities are not merely reactive enablers of smart city initiatives but are actively shaping and directing smart city trajectories.	Australia
Sadowski [70]	2021	Who owns the future city? Phases of technological urbanism and shifts in sovereignty	Urban Studies	Critical commentary	Phases of technological urbanism: different degrees of control over urban governance, services, and space.	The rise of platform urbanism changes the economic landscape of cities.	Australia
Wang [65]	2021	Development Trend of Urban Design in ‘Digital Age’: Pan-dimensionality and Individual-Ubiquity	Front. Struct. Civ. Eng	Literature review	Urban development is moving from a three-dimensional city to a pan-dimensional digital city.	Urban spaces are no longer static but dynamic and multi-dimensional.	China
Allam et al. [2]	2022	The Metaverse as a Virtual Form of Smart Cities: Opportunities and Challenges for Environmental, Economic, and Social Sustainability in Urban Futures	Smart Cities	Literature review	The Metaverse can reduce the need for physical infrastructure and promoting virtual interactions.	Optimise resource use and reduce environmental impact.	Australia
Ouda and Aziz [82]	2022	Digital Placemaking: Perceiving Meaningful Spaces Through the Digital Environment	Contingency planning of adaptive urbanism	Comparative analysis	Digital placemaking practices have successfully created a sense of place, belonging, and community engagement.	Transforming public spaces into interactive and engaging environments.	Egypt
Santos et al. [78]	2022	Determinants of e-inclusion and digital inequality in the use of urban mobility applications in mobility	Research, Society and Development	Mixed method	Income was found to be a significant factor in digital inclusion and digital inequality.	The significant influence of income on digital inclusion suggests the need for targeted interventions to support lower-income groups.	Brazil
Tang et al. [79]	2022	Does the Digital Economy Improve Urban Tourism Development? An Examination of the Chinese Case	Sustainability	Benchmark regression model, panel threshold model (PTM), and spatial Durbin model (SDM)	The digital economy improves connectivity and accessibility.	There are positive spatial spillover effects, meaning the digital economy in one city can positively influence tourism development in neighbouring cities.	China
Basaraba [81]	2023	The emergence of creative and digital place-making: A scoping review across disciplines	New Media & Society	Scoping review	Digital place-making: engaging the public in co-creation processes.	Not only boosts tourism but also fosters a sense of community and belonging among residents.	The Netherlands
Carpentiere et al. [64]	2023	Innovative Business Models for the Future Smart City	Proceedings of Science and Technology	Multiple case study	Helps users find parking, reduces unnecessary driving, and offers real-time data.	Focus on user-centric solutions improves the quality of life and encourages citizen engagement.	Italy
Shi et al [77]	2023	Digital Economy, Technological Innovation and Urban Resilience	Sustainability	Regression model	The digital economy exhibits positive spatial spillover effects on urban resilience.	Cities should work together to leverage the benefits of the digital economy.	China
Hodson et al. [74]	2024	How have digital mobility platforms responded to COVID-19 and why does this matter for ‘the urban	Urban Studies	Critical review and database analysis	Growth of platforms supporting homeworking, home entertainment, and rapid delivery services, reconstituting the home as a bio-secure site.	The rise of homeworking and delivery platforms is decentralising economic activity, disrupting the traditional urban agglomeration model.	UK
Kırdar and Çağdaş [80]	2024	Digital Participatory Model as Part of a Data-Driven Decision Support System for Urban Vibrancy	Urban Planning	Survey	High likability areas are associated with cultural landmarks, urban greening, and scenic vistas.	The image value of place, defined through likability and likability features.	Turkey
Yeo [66]	2024	Negotiating Digital Urban Futures: The Limits and Possibilities of Future-Making in Singapore	Trans Inst Br Geogr	Ethnographic fieldwork	Urban dwellers employ various tactics to negotiate digital urban futures.	Demonstrating that urban futures are not entirely predetermined.	Singapore

,

Table A2. Urban behaviour disruption.

Author	Year	Title	Journal	Method	Finding	Reframe the Use and Value of Urban Form	Region
Petković et al. [99]	2018	Digital Economy and (Non) Incremental Changes in Tourism and Retail Business Model	Ekonomika	Comparative analysis	Led to the development of personalised and experience-based tourism services.	Creates new economic opportunities within urban areas particularly in sectors like tourism and retail.	Serbia
Gillpatrick [89]	2019	The Digital Transformation of Marketing: Impact on Marketing Practice & Markets	Economics	Literature review	Three waves of digital disruption: unbundling, disintermediation, and decoupling.	Shifts the focus from traditional manufacturing to service-oriented and tech-driven industries.	Europe
Gillpatrick et al. [90]	2019	Understanding the Role of Consumer Behavior in Forecasting the Impact of Industry 4.0 and the Wave of Digital Disruption Driving Innovation in Retailing	DIEM	Literature review and exploratory interviews	Consumers now expect more personalised, convenient, and efficient shopping experiences.	Retail spaces are evolving to meet the demands of digitally savvy consumers.	Europe
Bozhuk et al. [101]	2020	Problems of transformation in the tourism industry in the digital economy	SHS Web of Conferences 73	Online survey	Tourism shifts: better service and personalised trips.	Digital era drives diverse tourism space demand.	Russia
Gazzola et al. [96]	2020	The sharing economy in a digital society: youth consumer behavior in Italy	Kybernetes	Mixed method	Key motivations include reducing waste, improving environmental efficiency, and saving money.	The sharing economy can enhance economic efficiency and reduce the cost of living in urban areas.	Italy
Khoa [92]	2020	The role of Mobile Skillfulness and User Innovation toward Electronic Wallet Acceptance in the Digital Transformation Era	International Conference on Information Technology Systems and Innovation (ICITSI)	Mixed method	Mobile skills boost e-wallet adoption intent.	Reduced physical bank branches.	Vietnam
Maslova et al. [100]	2020	Transformation of consumer behavior in the tourism industry in the conditions of digital economy	IOP Conference Series: Materials Science and Engineering	Online survey	There is a growing trend of tourists organising their trips independently using digital tools.	The transformation in consumer behaviour can lead to increased economic activity in urban areas.	Russia
Papagiannis et al. [96]	2020	The Sharing Economy in a Digital Society: Youth Consumer Behavior in Italy	Kybernetes	Questionnaires	Younger people prefer low-cost digital platforms and networks of shared products/services’ providers and on-demand access. Young people avoid ownership due to high management costs.	Increased demand for distribution centres and shared amenities.	Italy
Chatterjee & Kulkarni [91]	2021	Healthcare consumer behaviour: the impact of digital transformation of healthcare on consumer	Cardiometry	Interviews	Factors in healthcare choice: digital, service, brand.	Create welcoming space for positive customer vibes.	India
Räsänen et al. [103]	2021	Online information seeking patterns and social inequality in a digital economy	The International Review of Retail, Distribution and Consumer Research,	Survey	Digital divide: key to equitable economic access. City folk likely to browse online post-purchase. Rural areas: less inclined to shop online casually.	Brick-and-mortar stores face declining traffic. Retail closures reshape urban landscape. E-commerce spurs new industrial space development.	Finland
Singh [171]	2021	Digital Transformation Changes in the Producer Consumer Relationship	South Asian Journal of Marketing & Management Research (SAJMMR)	Literature review	Shifting the balance of power towards consumers, who now play a more active role in co-production and co-creation.	Businesses in urban areas focusing on personalised and hyper-differentiated products and services.	India
Ananjeva et al. [88]	2022	Digital Transformation Towards Sustainability A Case Study of Process Views in District Heating	Software Business	Case study	Digital shift: Tech, business, value chain changes. Org change key for digital skills and culture growth.	Digital tech: energy savings and business innovation boost. Digital platforms enable new energy stakeholder ties. Digital tech improves space use and energy efficiency.	Denmark
Atanasova [85]	2022	Characteristics of Digital Entrepreneurship	Entrepreneurship	Online survey	Digital entrepreneurship is an integral part of the digital economy.	Urban environments need to foster innovation and creativity.	Russia
Dewi [93]	2023	Changes In Retail Consumer Shopping Behavior After The End Of Covid 19 In Indonesia: Towards Digital Transformation Behavior	Proceeding of International Conference on Digital Advance Tourism, Management and Technology 2023	Literature review	Digital payments via e-wallets replace cash, optimising tech integration and transforming social behaviour.	Businesses must adapt to real-time tech in online shopping, supported by policy, as digital infrastructure becomes vital for retail and entrepreneurial space value.	Indonesia
Kalashnikova et al. [94]	2023	Global trends in the behavior of consumers of retail enterprises in the digital economy	IOP Conf. Series: Earth and Environmental Science	Mixed method	The pandemic accelerated the transition to online shopping.	Highlights the need for urban areas to build economic resilience by diversifying retail offerings and supporting local businesses.	Ukraine
Lin et al. [98]	2023	Digital menus innovation diffusion and transformation process of consumer behavior	Journal of Hospitality and Tourism Technology	Online survey	Perceived information quality, food quality, and service quality all significantly influence diners’ intentions to revisit.	Restaurants that adopt advanced digital menus may see increased customer satisfaction and loyalty.	China
Qadir et al. [97]	2023	Digital Consumer Behavior and Ecommerce Tendencies During the New War Crisis	Journal of Survey in Fisheries Sciences	Literature review	Traumatic events like war can permanently alter consumer purchasing behaviour.	Cities can adopt agile methodologies to respond swiftly to changing conditions.	Asia
Thompson & Turner [84]	2023	Navigating the Digital Transformation: How Businesses Adapt and Thrive in the Age of Disruption	Research Studies of Business	Literature review	Businesses must foster a culture of agility, encouraging continuous learning, experimentation, and rapid iteration.	Flexible zoning laws and adaptive reuse of spaces.	Europe
Zheng and Yang [95]	2023	Research on the Impact of Digital Economy on Residents’ Consumption Upgrading	Frontiers in Business, Economics and Management	Panel data analysis	The digital economy promotes the upgrading of residents’ consumption levels and structures.	Cities can become centres of technological innovation.	China
Chan & Yao [102]	2024	Understanding consumer behavior in phygital environments: an interpretivist methodological framework	Qualitative Market Research: An International Journal	Ethnographic observations, focus groups, and content analysis	Social dynamics, peer influences, and the role of influencers are critical in shaping consumer behaviour in phygital spaces.	Phygital environments create immersive and engaging consumer experiences by integrating physical and digital elements.	China
Rosales et al. [87]	2024	Digital Transformation and Elastic Demand: Assessment on the Impact of E-commerce Growth on Consumer Goods in the Philippines	SSRN Electronic Journal	Literature review	Income level influences online shopping behaviour. E-commerce benefits busy, higher-income individuals. E-commerce minimally impacts lower-income shopping habits.	E-commerce appeals to busy urban residents. Physical stores appeal to lower urban residents.	Philippines
Yadav et al. [86]	2024	Effects of the industrial 4.0 transition on consumer behavior: A systematic overview	International Conference on Contemporary Engineering, Technology and Management (ICCETM 2023)	Literature review	Digitalisation impacts employment patterns.	Reshape urban economies, creating new job opportunities and business models.	Asia

and

Table A3. Urban mobility disruption.

Author	Year	Title	Journal	Method	Finding	Reframe the Use and Value of Urban Form	Region
vom Berg et al. [125]	2017	ICT-Platform to Transform Car Dealerships to Regional Providers of Sustainable Mobility Services	Interdisciplinary Journal of Information	Interviews	New mobility services by car dealerships.	The floating car sharing are only feasible in urban or confined areas. Suitable for rural areas where public transport services are declining.	Germany
Starĉević & Konjikušić [110]	2018	Why Millenials as Digital Travelers Transformed Marketing Strategy in Tourism Industry	Tourism in Function of Development of The Republic of Serbia. International Scientific Conference	Meta-analysis	Millennials are price sensitive, not predictable, and seek shareable social media experiences.	Offer unique, sharable, and mobile-bookable travel experiences.	Europe
Suel & Polak [109]	2018	Incorporating online shopping into travel demand modelling: challenges, progress, and opportunities	Transport Reviews	Literature review	Individual trips to stores may be replaced by home deliveries by retailers or third-party carriers.	The growing importance of urban logistics in planning.	Europe
Zahraei et al. [116]	2019	A foresight study on urban mobility: Singapore in 2040	Foresight	Scenario planning workshop	The shared world scenario: community focus on safety, cost, local travel, and bonds. The virtual world scenario: speed key in travel, and distance no longer a barrier.	The shared world scenario: local govt key in shaping urban development. The virtual world: society leads tech, and govt supports urban change.	Singapore
Ammar et al. [120]	2020	Studying of Sharing Economy in Egypt as a Destination for Tourism and Hospitality	JAAUTH	Questionnaires	The sharing economy influences travellers’ choice of destinations, frequency of travel, and length of stay.	Enhances urban resilience and community revitalization but also poses challenges regarding regulatory frameworks and sustainability.	Egypt
Leontev & Magera [114]	2020	Digitalization of the transport industry: social-and psychological emphasis	VIII International Scientific Conference Transport of Siberia	Case study	Social and psychological impacts on digitalisation of transport industry.	Cities might evolve towards more flexible, hybrid uses of space, accommodating both physical and virtual functions.	Singapore
Silva et al. [104]	2020	The Outsourcing Urban Mobility in Industry 4.0 and the Challenges Faced by The Category of Workers In Search Of Rights and Occupational Safety	Journal of Engineering and Technology for Industrial Applications	Interviews	Startups link services and consumers via cheap labour. Industry 4.0 safety: adapt to worker health needs.	Urban labour impact: living costs vs. wages gap.	Brazil
Viri et al. [113]	2020	Connected and Multimodal Passenger Transport Through Big Data Analytics: Case Tampere City Region, Finland	20th Working Conference on Virtual Enterprises (PRO-VE),	Case study	Big data reveals passenger behaviour and travel paths.	Improved traffic management.	Finland
Ghonimi [111]	2021	Smart City: A Question of Social Sustainability in Urban Spaces? Assessing The Impacts of ICT on Changing Urban Behavioral Patterns in Urban Spaces of Madinaty, Egypt	Journal of Urban Research	Case study	ICT encourages people to depend on private modes for long-distance trips. Minimise urban mobility to short distance trip services and trips will be reduced.	Reduce road width and parking requirements. The growth of self-contained communities.	Egypt
Sonnberger and Graf [108]	2021	Sociocultural dimensions of mobility transitions to come: introduction to the special issue	Sustainability: Science, Practice and Policy	Ethnographic	Sociocultural factors play a crucial role in shaping mobility transitions.	The importance of cultural and social innovations in shaping future mobility systems.	Germany
Šulskytė [123]	2021	Mobility-As-A-Service: Concepts and Theoretical Approach	IEEE International Conference on Technology and Entrepreneurship (ICTE)	Literature review	Digital illiteracy persists in tech-averse older travellers.	Trigger gentrification processes and displacement risks.	Europe
Gonzalez & Quadros [118]	2022	Digital Transformation and New Business Models in Urban Mobility: The Case of Carsharing in Brazil	Proceedings of PICMET ‘22: Technology Management and Leadership in Digital Transformation	Multiple case studies	Carsharing offer affordable, sustainable, and convenient transportation services.	Reduce the need for private car ownership.	Brazil
Gupta et al. [119]	2022	Role of Technological Transformation in Shaping Millennials’ Travel Behaviour: A Review	10th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)	Literature review	Millennials favour freestyle travel, new experiences, and heritage. Millennials rely on tech and social media for travel choices.	Urban areas are being reimagined to include more cultural and social spaces that cater to the experiential preferences of Millennials.	Asia
Shatnawi & Zoltan [115]	2022	Digital Transformation during Covid-19 and Its Impact on Transportation and Mobility	IEEE 16th International Symposium on Applied Computational Intelligence and Informatics	Questionnaires	Remote work trend driven by desire to avoid transit.	Housing value will be not affected by the proximity to transit.	Budapest and Amman
Zha et al. [106]	2022	The impact of digital economy development on carbon emissions-- based on the Yangtze River Delta urban agglomeration	Frontiers in Environmental Science	Panel data and multiple econometric models	Showing that as work becomes increasingly remote, traditional peak hour transportation demand is altered, leading to varied usage of transport systems at different times.	Reducing commuting demands and reshaping spatial density patterns.	China
Baudens et al. [122]	2023	Women’s (im)mobility strategies and digital platform adoption: the case study of employees doing desk work in Pune, India	Gender, Technology and Development	Interviews	The women participants chose their transport mode based on their perceptions and personal priorities.	Highlighting the importance of considering social conditions and cultural bias.	India
Mentsiev et al. [121]	2023	Digital transformation in transport infrastructure energy efficiency: smart cities and sustainable mobility	E3S Web of Conferences 460, 07018	Literature review	AI-powered personalised routing for city residents.	Facilitate more polycentric urban development by enabling easier access across urban sub-centres.	Russia
Paköz & Kaya [107]	2023	Personal Adaptations to Remote Working in the Post-Pandemic City and Its Potential Impact on Residential Relocations: The Case of Istanbul	Transportation Research Record	Online survey and correlation analysis	Remote work impacts travel, energy use, and home choice.	Proximity to family, housing affordability, and proximity to essential amenities facilitate remote working and relocation processes.	Istanbul, Türkiye
Zhao and Said [105]	2023	The Effect of the Digital Economy on the Employment Structure in China	Economies	Panel data analysis	The digital economy profoundly influences employment structures, leading to shifts in commuting patterns due to the changing work nature.	Potentially decentralising urban cores and flattening land-use intensity gradients.	China
Alanazi & Alenezi [124]	2024	Driving the future: Leveraging digital transformation for sustainable transportation	Journal of Infrastructure, Policy and Development	Literature review	Digital transformation boosts environmental sustainability. Digital transformation risks: privacy, security, and ethics.	Urban quality of life improvements boosts area value.	Middle East
Gulc & Budna [112]	2024	Classification of Smart and Sustainable Urban Mobility	Energies	Literature review and case studies	SSUM: electromobility, collective transport 2.0 and low mobility societies.	Promoting compactness, low-mobility societies, and flexible land use patterns.	EU
Tartaglia & Petrozziello [117]	2024	Measuring the impact of institutional and territorial drivers for an efficient and smooth Mobility as a Service (MaaS) implementation: a global analysis	European Transport\Trasporti Europei	Composite set of indicators	The ultimate shift that MaaS needs is a cultural one, from ownership to usership.	Institutional factors key to smooth maas implementation.	Europe

in Appendix A.

3.4. Outcomes and Variables

The primary outcomes sought in this review were disruptions to urban systems caused by the digital economy and their subsequent impacts on land use patterns and land value. Specifically,

Table 1. Outcome domains and extracted data.

Outcome	Extracted Data
Primary Outcomes	Urban activity disruptions (changes in retail patterns, office space demand, public space usage) Behavioural disruptions (shifts in consumption patterns, work arrangements, social interactions) Mobility disruptions (changes in commuting patterns, transport mode choices, travel demand) Land use transformations (rezoning needs, repurposing of spaces, new spatial typologies) Land value impacts (valuation shifts, price dynamics, location premium changes)
Secondary Variables	Geographic context (country, city type, urban vs. suburban) Digital technology type (e-commerce, platforms, remote work tools, mobility apps) Stakeholders affected (residents, businesses, tourists, workers) Temporal aspects (immediate vs. long-term impacts, COVID-19 related changes) Policy implications (planning recommendations, regulatory needs) Equity considerations (digital divide, spatial inequality, displacement risks)

shows the extracted data on the outcome domains.

For each outcome domain, all relevant findings reported in the studies were collected, regardless of whether they were primary or secondary outcomes in the original research. Where studies reported multiple impacts or time-bound effects, all were extracted to ensure comprehensive coverage. Missing or unclear information was noted, and where critical data were absent (e.g., geographic context), attempts were made to infer from the study context or were marked as “not specified” in the extraction forms.

3.5. Quality Assessment and Risk of Bias

Given the theoretical and exploratory nature of this systematic review, and the diverse range of study designs included (literature reviews, case studies, empirical analyses, and theoretical papers), traditional risk of bias assessment tools designed for intervention studies or quantitative meta-analyses were not applicable. Instead, a quality consideration approach was adopted, appropriate for synthesising heterogeneous evidence on emerging phenomena [43].

While formal quality scores were not assigned, studies with clear methodological limitations (e.g., very small sample sizes, lack of methodological detail, or purely speculative arguments without empirical or theoretical grounding) were noted during synthesis. These considerations informed the weight given to different findings during the thematic analysis, with preference given to studies demonstrating robust methodology and clear evidence chains. The predominance of recent literature (2019–2024) helped minimise concerns about temporal bias, ensuring the findings reflect current digital economy developments [44].

The diversity of methodological approaches was viewed as a strength rather than a limitation, as it allowed for triangulation of findings across different research paradigms and geographic contexts, providing a more comprehensive understanding of the digital economy’s multifaceted impacts on urban systems [45].

3.6. Data Analysis and Synthesis Methods

3.6.1. Bibliometric Analysis

To complement this review, we conducted a bibliometric analysis using VOSviewer version 1.6.20 [46] on the final 66 articles. This multi-method approach, termed Bibliometric-Systematic Literature Review (B-SLR) following Marzi et al. [47], provides both quantitative insights into research patterns and qualitative synthesis of findings. The bibliometric analysis examined: (a) keyword co-occurrence to identify the core conceptual structure and thematic clusters, and (b) term co-occurrence to complement the keyword analysis and uncover deeper semantic relationships within the literature.

The keyword co-occurrence analysis employed the following parameters in VOSviewer v1.6.20: minimum occurrence threshold of the 3 three full counting method, and association strength normalisation. The keywords were extracted from both author-supplied keywords and database indexing terms. The keyword list was manually cleaned to merge synonyms (e.g., ‘sharing economy’ and ‘collaborative economy’) and remove overly general terms (e.g., ‘article’ and ‘study’). The final network layout used the Fruchterman–Reingold algorithm with default attraction and repulsion parameters. Subsequently, the term co-occurrence analysis extracted noun phrases appearing at least 10 times across the corpus using VOSviewer’s text mining functionality. Relevance scoring was applied (60% threshold) to filter generic terms while retaining conceptually significant ones. The binary counting method was used to prevent single text-heavy documents from skewing results. Terms were cleaned to remove common academic phrases (e.g., ‘literature review’ and ‘research method’), while retaining substantive concepts.

3.6.2. Thematic Analysis

In Stage 3, the analysis employed a systematic categorisation method adapted from [48], utilising a four-step qualitative approach to identify and organise key themes aligned with the research questions. These themes were then re-evaluated, refined, and cross-referenced with the other literature and review studies. The criteria for the formation of the themes are presented in

Table 2. Criteria for category formulation.

Step	Selection Criteria	Process Description
1	Initial Issue Identification	Determine key issues relevant to digital economy impacts on urban land use and land value using the eye-balling technique across the literature
2	Disruption Detection	Detect disruptions to traditional urban activities due to the digital economy Identify behavioural shifts in the digital economy age Identify how the digital economy transform urban mobility
3	Category Formation	Group identified disruptions with similarities to form broader potential categories
4	Category Refinement	Narrow down categories and check consistency against the other literature Final review of the literature and analysis of the shortlisted categories
5	Finalisation	Verify, classify, and finalise the creation of the final categories Distribute the selected literature under most relevant categories

.

The analysis utilised descriptive qualitative techniques rather than statistical methods. Pattern matching was employed to identify common themes, trends, and differences across the selected literature using systematic eye-balling techniques deemed sufficient for assessing and organising the data. Explanation building was used to develop coherent narratives connecting identified patterns to the theoretical framework and research questions. Rather than quantitative effect sizes, the focus was on identifying patterns of disruption across multiple studies; convergent and divergent findings; and contextual factors influencing outcomes and emerging theoretical insights. Furthermore, the heterogeneity in study designs was addressed by grouping studies by disruption type rather than methodology, explicitly noting where findings were context-specific or contested. The results are presented through structured narrative summaries for each thematic area; comprehensive evidence tables mapping individual study contributions; and thematic synthesis, highlighting cross-cutting patterns and implications. No quantitative pooling or statistical measures of the effect were calculated due to the qualitative and theoretical nature of the evidence base.

This analytical process resulted in the distribution of the 66 selected articles across three primary thematic categories: How Digital Economy Disrupts Urban Activities (n = 22), How Digital Economy Disrupts Urban Behaviour (n = 22), and How Digital Economy Disrupts Urban Mobility (n = 22). The final stage involved synthesising findings from the analysed articles into a comprehensive narrative that addresses each research question, presenting key findings within each thematic category, highlighting emerging trends, patterns, and implications, as well as highlighting theoretical implications for land use and land value, and an evidence-based framework for policy adaptation.

4. Analysis and Results

This section presents the empirical findings from our scoping review, beginning with study characteristics, followed by bibliometric patterns, and concluding with a thematic synthesis of disruptions.

4.1. Study Characteristics

The increasing number of publications focusing on the digital economy’s impact on urban environments demonstrates a growing interest among researchers. As illustrated in Figure 2, the temporal distribution of publications reveals a dramatic 400% increase from 2019 to 2024, with European research maintaining consistent dominance throughout this period (48.5% of total publications), while Asian contributions have steadily grown from 25% in 2019 to 30% by 2024. The number of articles published reflects this trend, with 2 articles in 2017, 4 in 2018, four in 2019, 12 in 2020, 12 in 2021, 10 in 2022, and 22 between 2023 and 2024. Notably, the surge in 2023–2024 publications (32 articles, representing 48% of the total corpus) suggests that the COVID-19 pandemic catalysed research interest in digital transformations of urban spaces. The post-pandemic surge in publications particularly highlights how all three dimensions—activities (remote work), behaviours (digital consumption), and mobility (reduced commuting)—became simultaneously visible and measurable during this period of forced digital acceleration.

A significant number of leading authors are affiliated with academic institutions in Europe (n = 32) and Asia (n = 20), reflecting the widespread adoption of the digital economy in these regions. Figure 3 provides a visual representation of this geographic concentration, revealing stark disparities in research coverage. The choropleth map demonstrates that while Europe and East Asia constitute research hotspots (accounting for nearly 80% of studies), vast regions, including Africa (1.5%), Latin America (4.5%), and South Asia, remain significantly underrepresented. This geographic bias has profound implications for the generalisability of findings, as digital economy impacts likely manifest differently across varied urban contexts, governance systems, and levels of digital infrastructure development [49,50,51]. Interest is also evident in Australia (n = 5), South America (n = 4), and the Middle East (n = 4), with fewer studies originating from North America (n = 1).

The extensive and multifaceted impact of the digital economy on urban environments is reflected in the diverse range of journals and proceedings from which articles were selected for this research review. Approximately half of the articles are distributed across journals and proceedings focusing on Geography, Planning and Development (n = 8), Economics (n = 8), Business and Finance (n = 8), and Social Science (n = 8). The remaining half are primarily found in publications centred on Urban Studies (n = 6), Transport (n = 5), Environmental Science (n = 5), Engineering and Technology (n = 5), and Tourism (n = 5). A smaller proportion of papers originates from other various fields.

Regarding the research method, literature reviews represent the most prevalent type of paper addressing the impact of the digital economy (n = 24). The academic discourse on the digital economy and its effects on urban areas is often scattered across various disciplines, including management, information systems, economics, and urban planning. A literature review can bridge these disciplinary divides by synthesising diverse perspectives and bringing together insights from different fields [52]. While a literature review provides a broad overview of a topic, it may lack the depth and detail necessary to fully understand the complexities of the digital economy and its urban impacts. They are not always consistent, and different studies may reach conflicting conclusions [53].

An additional common research method employed is quantitative analysis, with 17 papers utilising approaches such as surveys, questionnaires, panel data, and regression models. Figure 4 reveals a significant methodological evolution over the study period that reflects the field’s maturation. The declining reliance on literature reviews (from 40% in 2019 to 20% in 2024), coupled with the rise in empirical studies (from 20% to 40%), indicates a shift from conceptual foundation-building to evidence-based research. This transition is particularly pronounced after 2021, suggesting that the pandemic provided both the impetus and the natural experiment conditions for the empirical investigation of digital transformations [54]. The steady increase in mixed-methods approaches (doubling from 10% to 20%) signals growing recognition that understanding digital economy impacts requires both quantitative measurement and qualitative interpretation of complex urban phenomena [55,56,57].

Conversely, a dozen papers adopted a qualitative approach, incorporating interviews, ethnographic studies, comparative analyses, and workshops. Qualitative methods prioritise the exploration of subjective experiences and meanings. Qualitative methods enable researchers to explore how urban residents perceive, interpret, and make meaning of the transformations induced by the digital economy. While qualitative approaches are inherently interpretive and subject to researcher bias, they offer valuable insights into the lived experiences and contextual understandings that may be overlooked by purely quantitative analyses [56].

Other methodological approaches used are case study (n = 10) and mixed method (n = 4). The case study approach is flexible and adaptable, allowing researchers to adjust their research questions and methods as new information emerges. This is particularly useful in the rapidly evolving digital economy, where new technologies and business models are constantly emerging. While case studies are often used for exploratory research, they can also contribute to theory building by generating new concepts, frameworks, and hypotheses.

Nonetheless, the evidence base reveals several critical limitations that should inform the interpretation of findings. Empirical gaps are evident in the scarcity of longitudinal studies tracking actual land value changes over time, with most research offering cross-sectional snapshots rather than dynamic analyses. Geographic bias is pronounced, with African cities (n = 1) and Latin American cities (n = 4) severely underrepresented, raising concerns about the generalizability of findings beyond European and Asian contexts. Measurement challenges persist across studies, with inconsistent definitions and metrics for assessing both “disruption” intensity and “land value impact,” preventing meaningful quantitative comparisons. The temporal overlap with COVID-19 further complicates interpretation, as many recent studies conflate pandemic-driven changes with longer-term digital economy trends, making it difficult to isolate specific causal mechanisms [57,58]. Finally, scale variations, with studies ranging from neighbourhood-level analyses to metropolitan-wide assessments, introduce additional complexity when attempting to synthesise findings or derive universal principles for urban planning practice.

During the screening process, several categories of studies were excluded despite initial relevance to the digital economy and urban contexts. Notable exclusions included the following:

• Technology-focused studies (n = 89): Papers examining smart city technologies, IoT implementations, or digital infrastructure without explicit analysis of land use or land value implications;
• Macro-economic analyses (n = 34): Studies investigating digital economy impacts at national or global scales without urban-specific insights;
• Purely technical papers (n = 28): Research on digital platform architectures, algorithms, or software development lacking a connection to urban spatial dynamics;
• Single-sector studies (n = 22): Investigations limited to one industry (e.g., fintech, edtech) without broader urban implications;
• Policy documents and grey literature (n = 15): Government reports and white papers that did not meet peer-review criteria.

Additionally, 11 articles that appeared highly relevant based on abstracts were excluded upon full-text review due to discussing digital transformation in rural rather than urban contexts (n = 4); focusing on digital governance without spatial implications (n = 3); addressing environmental monitoring systems without land use connections (n = 2); and examining digital divide issues without geographic specificity (n = 2).

Prior to examining each disruption category in detail,

Table 3. Quantitative summary of digital economy disruptions.

Disruption Category	No. of Studies	Research Methods	Geographic Coverage	Key Metrics Identified
Urban Activities	22 (33.3%)	Literature review (8) Case study (6) Mixed methods (4) Interviews (4)	Europe (10) Asia (7) Americas (3) Middle East (2)	Land value appreciation in digital hubs 20–40% retail space reduction 3× increase in logistics facilities Platform governance adoption
Human Behaviour	22 (33.3%)	Literature review (9) Survey (7) Mixed methods (4) Case study (2)	Europe (11) Asia (8) Americas (2) Middle East (1)	60% increase in gig work 45% shift to online shopping Digital payment adoption rates Remote work prevalence (30–50%)
Urban Mobility	22 (33.3%)	Literature review Case study (5) Survey (4) Multiple case (6)	Europe (11) Asia (5) Americas (3) Middle East (3)	25% reduction in commuting Shared mobility adoption (15–30%) Parking demand decrease (20%) Last-mile delivery growth (300%)

provides a quantitative synthesis of how digital economy disruptions manifest across our sample. The equal distribution of studies across the three categories (22 each) reflects the systematic nature of digital transformation—it simultaneously reshapes what happens in cities (activities), how people behave (behaviours), and how they move (mobility).

Several patterns emerge from this quantitative overview. First, the methodological approaches vary by disruption type: studies on urban activities rely heavily on literature reviews and case studies, while behavioural disruptions are more likely to employ surveys and empirical methods. This methodological diversity reflects the different epistemological challenges in studying tangible spatial changes versus intangible behavioural shifts [59]. Second, the geographic coverage reveals that European researchers dominate studies on activities and mobility, while Asian scholars contribute proportionally more to behavioural research, possibly reflecting different cultural attitudes toward digital adoption. Third, the key metrics identified demonstrate that digital disruptions produce quantifiable impacts: a 20–40% reduction in retail space, 60% increase in gig work participation, and 25% decrease in commuting—magnitudes that demand urgent policy responses.

4.2. Bibliometric Analysis

4.2.1. Keyword Co-Occurrence Analysis

Figure 5 presents the keyword co-occurrence network derived from the 66 selected articles, revealing the intellectual landscape of this emerging field. The network visualisation identifies distinct thematic clusters that align with and validate systematic categorisation. At the centre of the network, ‘smart cities’ emerge as the dominant node, serving as a conceptual bridge connecting various research streams. This central positioning reflects how smart city initiatives have become the primary lens through which researchers examine digital transformations of urban space [60,61]. The strong connections between ‘smart cities’ and both ‘digital economy’ and ‘platform urbanism’ (shown by thick connecting lines) indicate that these concepts are frequently studied together, suggesting an emerging theoretical framework that links technological infrastructure, economic transformation, and new forms of urban governance. The network reveals five distinct thematic clusters.

Cluster 1 (Red—Governance and Economic Processes): This cluster, anchored by ‘governance’ and ‘economic processes,’ represents research examining how digital technologies reshape urban administration and economic structures. The proximity of these terms to ‘platform urbanism’ suggests that scholars are increasingly recognising platforms as new governing institutions that mediate urban economic activities.

Cluster 2 (Green—Environmental and Sustainability): The green cluster links ‘smart cities’ with ‘forecasting’ and ‘climate change,’ indicating a research stream focused on how digital technologies can support sustainable urban development. The presence of ‘black and queer code studies’ in this cluster suggests emerging critical perspectives on inclusive and equitable smart city development.

Cluster 3 (Blue—Data and Platform Infrastructure): The blue cluster, featuring ‘data’ and ‘platform urbanism,’ represents technical and infrastructural research. This cluster’s separation from others indicates that platform studies often remain siloed from broader urban transformation research—a gap our review seeks to bridge.

Cluster 4 (Purple—Digital Economy and Cultural Transformation): The purple cluster connects ‘digital economy’ with ‘cultural economy,’ revealing how researchers examine digital transformation not merely as technological change but as cultural shift affecting urban life patterns and values.

Cluster 5 (Light Blue—Geographic Focus): The appearance of ‘China’ and ‘spatial spillover’ as connected nodes reflects the geographic concentration of empirical studies and the recognition that digital economy impacts extend beyond administrative boundaries.

The temporal evolution of research keywords illustrates a dynamic shift in the scholarly focus within the field. Between 2019 and 2020, the discourse was primarily centred on technological constructs, such as “smart cities” and “digital platforms,” reflecting an initial emphasis on digital infrastructure and urban innovation. In the subsequent period of 2021 to 2022, attention expanded to include terms like “platform urbanism” and “governance,” indicating a growing interest in the organisational and regulatory dimensions of digital urbanism. By 2023 to 2024, the emergence of “cultural economy” and “spatial spillover” as prominent keywords signals a further intellectual progression toward examining the socio-spatial implications and cultural dynamics engendered by digital transformation. This temporal trajectory suggests a maturation of the research agenda, moving from a technology-centric orientation toward more integrated analyses of urban digitalisation’s broader societal and spatial consequences.

4.2.2. Term Co-Occurrence Analysis

To complement the keyword analysis and uncover deeper semantic relationships within the literature, a term co-occurrence analysis was conducted, extracting frequently used terms from the full texts of the 66 articles. Figure 6 presents the term co-occurrence network, which reveals more nuanced conceptual relationships than keyword analysis alone, as it captures terms used throughout the manuscripts rather than just author-designated keywords [62].

The term network presents a striking bifurcation between behavioural–social dimensions (left side) and economic–spatial dimensions (right side), with ‘digital economy’ serving as the dominant bridging concept. This structural pattern provides crucial insights into how the four distinct conceptual domains emerge from the term analysis.

Domain 1 (Red—Behavioural Change Cluster): The red cluster centres on ‘consumer behaviour’ and ‘change,’ revealing extensive attention to how digital technologies alter urban consumption patterns. The strong connections between ‘consumer behaviour,’ ‘digital entrepreneurship,’ and ‘article’ (indicating empirical studies) suggest this research stream relies heavily on empirical investigation of behavioural shifts. Notably, the prominence of ‘COVID’ in this cluster confirms that the pandemic served as a critical catalyst for studying behavioural transformations.

Domain 2 (Blue—Digital Economy and Employment): The blue cluster, dominated by the large ‘digital economy’ node, connects strongly with ‘employment,’ ‘China,’ and ‘urban tourism development.’ This configuration reveals two key insights: first, employment transformations represent a primary lens through which researchers examine digital economy impacts. Second, the prominence of ‘China’ as a term (not just a keyword) indicates that Chinese urban experiences significantly shape theoretical understanding in this field.

Domain 3 (Green—Smart Urbanism and Practice): The green cluster links ‘smart urbanism’ with ‘practice’ and ‘COVID,’ suggesting research focuses on practical implementations of smart city initiatives, particularly in pandemic contexts. The separation of this cluster from the main digital economy node indicates that smart city research often proceeds independently from broader digital economy studies—a problematic silo our review aims to bridge.

Domain 4 (Purple—Data, Value, and Regulation): The purple cluster connecting ‘data,’ ‘value,’ ‘regulation,’ and ‘use’ represents emerging research on data governance and value creation in digital cities. This cluster’s central position between other domains suggests its potential as an integrative framework, yet its relatively small node sizes indicate this remains an underdeveloped research area.

An analysis of term frequency across temporal intervals reveals a clear evolution in research priorities within the field. Prior to 2020, scholarly discourse was primarily dominated by the concepts of “smart urbanism” and “practice,” reflecting a focus on the application of digital technologies in urban contexts. The onset of the COVID-19 pandemic in 2020–2021 triggered a marked surge in terms such as “COVID,” “change,” and “consumer behaviour,” indicating a rapid pivot toward examining societal responses and behavioural adaptations in times of crisis. In the more recent period of 2022–2024, the prominence of terms like “regulation,” “data,” and “value” suggests a shift toward critical investigations on governance, data governance frameworks, and the valuation of digital systems in urban environments. This temporal progression underscores a transition from a technology-driven narrative to one increasingly centred on behavioural dynamics and, ultimately, governance mechanisms, highlighting the field’s growing complexity and interdisciplinarity.

4.3. Thematic Synthesis

4.3.1. Urban Activity Transformations

This section discusses some digital economy impacts on urban activity disruption. Based on the reviewed literature, the following outcomes were identified: (a) spatial segregation; (b) privatisation of public space; (c) corporatisation of urban governance; (d) revaluation of urban centres and suburban areas; and (e) tourism disruption (Table A1).

First, digital economies have shifted urban governance towards a smart city model, integrating high-tech investments and knowledge-intensive industries [63]. Municipalities are now active participants in shaping digital infrastructure, forming public–private partnerships and data-driven policies. This involves designing cities to support digital entrepreneurship through “smart precincts” and innovation hubs, leading to specialised districts catering to knowledge economies [64].

The increasing importance of digital connectivity and data accessibility is shifting the economic value of land [65]. High-tech districts and smart city hubs are experiencing land value appreciation, while traditional commercial zones are becoming less relevant [66]. This dynamic leads to increased value in digitally connected districts, potentially causing gentrification and displacement. As an example, smart city projects can attract private investment, which increases real estate prices and displaces low-income residents. Furthermore, algorithmic urban exclusion, digital mapping, and AI-driven urban services often prioritise privileged groups while excluding marginalised communities [67]. For example, routing algorithms in ride-hailing apps avoid low-income neighbourhoods, reinforcing spatial segregation and unequal access to services.

Secondly, municipal governments are increasingly collaborating with tech firms, leading to the privatisation of public services and spaces, potentially catering primarily to those who can afford them [68]. This collaboration blurs the boundaries between public and private spaces, transforming public areas into commercialised zones, as seen in smart city projects that maximise data collection and monetisation [69]. Cities are being designed with interactive urban environments, integrating technologies like AR, smart sensors, and AI-driven public services, and shifting urban services such as transport and accommodation to private digital platforms, which affects affordability [70]. This shift highlights the digital divide and socio-spatial inequality, as not all residents benefit equally from these digital transformations [66], leading to the exclusion of marginalised communities from digital economic benefits.

Third, digital urbanism is evolving from smart, data-driven city management to platform urbanism, where digital platforms increasingly mediate urban services and interactions. These platforms, exemplified by transportation services like Uber and short-term rentals like Airbnb, act as intermediaries that reshape traditional urban economies [71,72]. This shift can lead to cities becoming reliant on specific corporate platforms, creating issues of “lock-in” and potentially “lock-out” from alternative solutions, influencing city governance and service delivery [68]. The rise of these platforms also fosters informalisation and deregulation, creating tensions with existing municipal policies, and potentially leading to corporate-controlled governance models where private firms dictate urban management strategies, as seen in projects where private firms experiment with urban governance models [73].

Fourth, the increasing prevalence of remote work, e-commerce, and home delivery platforms is reshaping urban landscapes by diminishing physical movement within cities [74]. This shift leads to a decline in traditional office and retail districts as digital alternatives reduce foot traffic, prompting the conversion of retail spaces and the adaptation of residential areas with co-working spaces and smart home technologies [75]. While suburban and exurban areas gain value due to increased digital connectivity, allowing work from diverse locations, demand rises for logistics hubs and data centres, yet urban centres maintain their appeal due to proximity to customers, skilled workers, and innovation ecosystems [76]. Despite Industry 4.0’s ability to decentralise production, companies still cluster in knowledge-intensive urban environments.

Digital platforms are transforming urban employment patterns by reshaping labour markets, leading to both the decline in traditional jobs and the creation of new, digitally based opportunities [77]. This shift fosters informal employment, particularly in gig-based mobility services, creating a new category of workers as independent contractors and expanding flexible employment opportunities that alter commuting patterns and demand for commercial spaces [78]. The digital economy also reduces information asymmetry between enterprises and consumers through online platforms, enabling cross-regional economic transactions and making financial services more inclusive, while the reduced need for physical proximity disperses economic activities beyond traditional urban cores.

The final outcome relates to tourism disruption. Digital technologies are reshaping urban economies reliant on tourism by enhancing efficiency, reducing business costs, and offering personalised services [79]. This encourages tourism specialisation in non-traditional tourist destinations, shifting their economic focus. As digital platforms boost tourism, land values in certain urban areas may increase due to higher visitor demand [80]. Digital storytelling and mobile apps are redefining tourist experiences at urban heritage sites [81], while the value of urban land is now based on digital enhancements and engagement metrics, with digital tools creating new interactions between residents, tourists, and city infrastructure [82]. However, areas with digital upgrades may experience increased land values, potentially displacing residents and businesses, indicating that urban land value is increasingly tied to digital infrastructure and tourism potential [83]. Moreover, Box 1 represents the summary of how urban activities are disrupted along with their policy implications.

Box 1. Urban activity disruption.

Key Insights on Urban Activity Disruption: Evidence Base: 22 studies across five continents; Geographic Hotspots: Europe (36%), Asia (32%), and Americas (18%); Dominant Methods: Literature reviews (24%) and case studies (23%).

Critical Findings: Smart city projects create digital enclaves excluding marginalised communities; Platform urbanism shifts governance from public to corporate control; E-commerce drives conversion of retail to logistics spaces; Digital tourism displaces residents in historic centres; Remote work devalues CBD properties by 15–30%.

Policy Implications: Mandate affordable housing in smart city developments; Regulate platform monopolies in urban service delivery; Rezone commercial districts for mixed-use development; Implement short-term rental caps to protect housing stock.

4.3.2. Behavioural Shifts in Digital Cities

This section discusses how the digital economy disrupts urban behaviour. This disruption can be seen in: (a) gig work and digital nomadism; (b) consumption patterns; (c) the shift from ownership to access-based consumption; and (d) the power of digital engagement (Table A2).

The first disrupted urban behaviour is related to working behaviour. The digital economy is reshaping urban work and consumption patterns by diminishing reliance on centralised office districts and physical retail spaces [84]. This shift is driven by the rise of digital businesses that operate without fixed locations and the growth of remote work, digital nomadism, and flexible workspaces [85]. As businesses migrate to digital platforms, traditional retail and office spaces lose value, potentially leading to the repurposing of shopping malls and business districts into mixed-use developments or logistics hubs. This transformation leads to new job opportunities in logistics, digital marketing, and information technology, while simultaneously disrupting traditional retail employment, requiring cities to adapt their workforce and education systems to meet Industry 4.0 requirements [86,87]. The platform economy, encompassing gig work and remote jobs, further redistributes urban wealth and employment, leading to uneven economic transformations that necessitate a rethinking of labour policies and workforce training [88], highlighting the need for cities to address digital inequality to ensure e-inclusion and social equity.

The second disruption affects consumption patterns. The digital economy is reshaping urban consumption patterns, with consumers increasingly favouring online and hybrid shopping experiences, which reduces foot traffic in physical retail spaces [89]. Businesses are adapting from product-centric to customer-centric models that emphasise personalised digital interactions, which alter traditional commercial zones [90]. This retail transformation favours experience-based spaces like interactive showrooms and pop-up stores [91], necessitating adjustments in commercial zoning policies, while the adoption of e-wallets further reduces reliance on physical cash, impacting how people engage with urban commercial spaces [92]. Digital payment systems also support the development of smart and cashless cities [93], where urban spaces integrate seamless digital services, potentially leading to a redesign of urban centres that facilitates digital transactions and reduces the need for ATMs and physical banking spaces.

The shift towards digital consumption is reshaping urban spaces as traditional retail diminishes and e-commerce expands. This leads to the repurposing of vacant department stores into mixed-use developments or logistics hubs, while the growth of home delivery services increases the demand for urban logistics centres [94]. Developed urban centres experience faster digital consumption growth, potentially creating regional imbalances, and technological innovation in the digital economy impacts income distribution and urban investment [95]. Furthermore, digital commerce adoption is higher among younger and wealthier urban consumers, which may exacerbate economic polarisation between digitally connected and disconnected communities.

The third disruption has been identified in how the digital economy fosters on-demand access to services, shifting consumer behaviour toward instant and flexible consumption models. This has led to collaborative consumption, where individuals share assets like cars and homes, facilitated by digital platforms that prioritise renting, lending, and sharing over ownership, exemplified by services like Airbnb and Uber [96]. This transition has contributed to a decline in demand for property investment. Similarly, the rise in shared mobility platforms is increasingly disrupting conventional models of private vehicle ownership in dense urban environments, although ownership levels remain relatively high in many regions. This shift is particularly evident in cities characterised by well-developed public transportation systems and elevated parking costs, where urban planning practices are beginning to reflect these changes, such as the conversion of parking areas into green spaces and the redesign of public transit infrastructure to include designated zones for on-demand pick-up and drop-off. Moreover, public transportation systems may need to evolve toward more flexible, demand-responsive models, moving beyond traditional fixed-route services to better accommodate emerging mobility patterns.

Subsequently, consumer spending habits are influenced by economic crises and conflicts, leading to increased price sensitivity and a focus on product availability, delivery efficiency, and affordability [97]. This shift is further amplified by the digital economy, where younger, tech-savvy generations like Millennials and Gen Z are more inclined to participate in the sharing economy, driven by social and environmental motivations, and enabled by the reduced barriers to access provided by digital platforms [96]. Moreover, higher technological proficiency and openness to innovation among these younger populations drive greater adoption of digital payment methods, influencing urban economic activities and potentially redesigning urban centres to facilitate digital transactions [92]. The COVID-19 pandemic has also accelerated the transition of businesses to new conditions of functioning, further solidifying the importance of digital solutions in meeting consumer demands.

The power of digital engagement is the final impact of urban behaviour disruption. Consumers are increasingly utilising self-service technologies and digital platforms, which are reshaping their engagement with businesses and altering urban spaces. This shift is evident in the rising expectation for digital interfaces in hospitality and other urban services by tourists and shoppers, which is impacting the demand for traditional service spaces [98,99]. As restaurants integrate self-service technologies, the demand for large seating areas and physical interactions may decline, potentially leading to the repurposing of commercial spaces. The rise in travel applications and online booking platforms empowers tourists to plan independently, leading to a preference for unorganised tourism and more diverse tourist routes that extend to lesser-known urban areas [100,101]. This dispersion of tourists can challenge local infrastructure, potentially leading to the repurposing of commercial spaces.

The increasing reliance on digital platforms and social networks is shifting decision-making from local interactions to global digital spaces [102]. People engage with urban environments through digital interfaces, and increasingly rely on online information and peer reviews, leading to a preference for self-guided tourism and diverse routes [100]. Metropolitan residents engage in more digital transactions and use online information sources (e.g., reviews, comparison sites) more frequently than rural residents [103]. While the gig economy allows residents to monetise assets through ride-sharing and local tours, historic city centres experience higher rental prices and displacement of local communities due to increased short-term rental activity, leading to short-term rental booms in tourist-heavy areas. This affects housing availability and affordability for local residents. Increased demand for temporary lodging changes zoning regulations and urban planning priorities. Box 2 shows how urban behaviour disruptions require policy adaptations.

Box 2. Urban behaviour disruption.

Key Insights on Urban Behaviour Disruption: Evidence Base: 22 studies focusing on consumption and work; Population Focus: Millennials/Gen Z (68%) and general public (32%); Key Technologies: E-commerce, sharing platforms, and digital payments.

Critical Findings: Gig economy workers comprise 15–30% of urban workforce; Online shopping reduces physical retail trips by 40–60%; Sharing economy shifts from ownership to access (cars -25%); Digital payments accelerate cashless society transition; Social media drives 70% of consumption decisions.

Policy Implications: Develop labour protections for gig workers; Support digital literacy programs for excluded populations; Adapt zoning for home-based businesses; Create frameworks for sharing economy regulation.

4.3.3. Mobility System Reconfigurations

This section discusses what kind of urban mobility is affected by digital economy development. These disruptions are evident in: (a) commuting mobility; (b) logistic and last-mile delivery; (c) supporting 15-min city implementation; and (d) car ownership vs. on-demand mobility (Table A3).

First, the digital economy is reshaping urban commuting patterns by shifting employment from manufacturing and construction to service-based jobs [104], leading to a decreased demand for industrial zones and an increased need for co-working spaces and digital hubs [105]. This shift is further amplified by the rise in remote work, which has significantly reduced daily commutes [106] and reliance on public transport and private vehicles [107]. Consequently, suburban areas are becoming more attractive due to the reduced need for commuting, leading to a shift in housing preferences towards larger homes with workspaces and potentially driving demand for decentralised mobility solutions in previously car-dependent peripheral urban areas [108].

Secondly, the rise in online shopping is substituting physical trips, which has led to a decline in shopping-related travel and has affected public transport ridership and road congestion [109]. This shift requires updating traditional travel demand models to reflect how digital platforms influence when, where, and how people travel for shopping [110]. As people manage social and commercial activities through digital platforms, public spaces see a decline in casual movement, while increased home deliveries have shifted urban mobility patterns, necessitating new models of urban freight distribution and potentially causing congestion with the rise of same-day delivery and e-commerce logistics hubs [111]. The increased demand for logistics and last-mile delivery hubs is also shifting land use patterns from retail-centric to warehousing, prompting cities to rezone areas for micro-fulfillment centres and distribution hubs to support rapid delivery services. With more people working remotely and using shared transport, parking lots and car-dependent infrastructure may become obsolete. Urban planners might convert underutilised parking spaces into green spaces, pedestrian-friendly zones, or mixed-use developments [112].

Thirdly, as commuting decreases, people compensate with more local, non-work-related travel [113], leading to increased neighbourhood-level mobility and demand for high-quality public spaces. This shift supports the rise of 15 min cities and self-sustaining, mixed-use districts, where daily needs are met within short distances [114]. Enhanced by digital economies, these urban clusters promote localised living and reduce the need for cross-city travel [115], with mobility dominated by autonomous buses, personal mobility devices, cycling, and walking [116]. As a result, urban policies are increasingly focused on reducing car dependency, enhancing walkability, and reallocating road space for green and functional urban areas.

Finally, digital platforms are transforming travel behaviour by promoting convenience and efficiency over car ownership, with users favouring pay-per-use models enabled by app-based services [117,118]. Millennials, as tech-savvy digital natives, drive demand for flexible, technology-driven transport options like Uber and Lyft, reducing reliance on private vehicles and disrupting traditional transportation systems [110,119]. Features like voice search and AI recommendations further shape travel choices [120,121]. While women often prefer these digital solutions for safety and time control, access remains unequal, with financial barriers potentially widening mobility gaps [122].

Mobility-as-a-Service (MaaS) supports compact, mixed-use urban development by reducing reliance on private cars and enhancing access to jobs and services through integrated, multimodal transport hubs [123]. These hubs connect public transit, shared mobility, and micromobility options, prompting cities to redesign infrastructure and zoning policies—such as exclusive parking for shared vehicles—to support seamless travel [124]. Cities like Zurich, Basel, Paris, and San Francisco are leading these efforts. MaaS platforms also use demand-based pricing, influencing travel behaviour and land use, while offering potential solutions for declining public transport in rural and suburban areas through shared mobility alternatives [125]. Box 3 sums up how the digital economy drives the new mobility system configuration.

Box 3. Urban mobility disruption.

Key Insights on Urban Mobility Disruption: Evidence Base: 22 studies on transport transformation; Key Trends: Remote work, MaaS, and last-mile delivery; Geographic Leaders: Singapore, Europe, and China.

Critical Findings: Remote work reduces commuting by 30–50% post-pandemic; Last-mile delivery increases urban freight by 25%; Ride-hailing reduces parking demand by 15–20%; 15 min cities gain traction in 40% of studied areas; Suburban areas see 20% increase in desirability.

Policy Implications: Convert parking to green/community spaces; Establish urban consolidation centres for deliveries; Integrate MaaS into public transport planning; Redesign streets for micromobility and walkability.

4.4. Understanding Digital Disruption Pathways and Impacts

It is essential to understand the complex pathways through which digital technologies transform urban systems. Figure 7 presents a Sankey diagram that visualises the flow from five key digital technologies to their urban outcomes through three disruption channels. The diagram reveals that e-commerce (15 studies) and platform economy technologies (18 studies) represent the most studied digital drivers, with platform economy showing the most diverse impact pathways across all three disruption categories.

This visualisation highlights several critical patterns: first, certain technologies cluster around specific disruption types—remote work predominantly affects mobility patterns, while smart city technologies primarily reshape urban activities and governance. Second, the thickness of the flows indicates that behavioural disruptions often manifest in multiple urban outcomes, suggesting cascading effects that traditional land use models fail to capture. Third, the convergence of multiple technologies on outcomes like ‘suburban growth’ and ‘logistics hub expansion’ indicates that these transformations result from synergistic rather than isolated technological impacts.

This review also reveals that digital economy impacts vary significantly in their intensity and urgency across different urban dimensions.

Table 4. Impact intensity heat map.

Disruption Impacts	Land Use Change	Land Value Impact	Policy Urgency
Spatial Segregation	1		4
Platform Governance
Tourism Disruption		2
Gig Economy		3
Remote Work
Shared Mobility
E-commerce
Digital Divide

¹ Low, ² Medium, ³ High-Medium, ⁴ High.

presents a heat map that synthesises expert assessments and empirical evidence on impact intensity across eight key disruption areas. This visualisation reveals three critical insights:

First, spatial segregation and platform governance emerge as ‘red zones’ requiring immediate policy intervention, scoring high on all three dimensions—land use change, land value impact, and policy urgency. These areas represent where the digital economy most fundamentally challenges existing urban planning paradigms. Second, the heat map reveals an inverse relationship between land use change and land value impact in some areas: while the gig economy produces moderate physical changes to urban space, its impact on land values remains low, suggesting that not all digital disruptions translate directly into real estate market effects. Third, the ‘policy urgency’ column identifies a mismatch between impact intensity and regulatory preparedness—areas like the digital divide show low physical impact but critical policy urgency, highlighting how digital transformations can exacerbate existing inequalities even without visible spatial changes.

5. Discussion

Building on the empirical evidence, this section develops theoretical frameworks, identifies insights from bibliometrics, emerging patterns, and discusses implications for urban planning theory and practice.

5.1. Bibliometric Insights

The keyword network analysis yields several critical insights into the current state of scholarship. First, the relative isolation of specific clusters highlights enduring disciplinary fragmentation. Notably, the weak linkages between the governance cluster (red) and the data and platform cluster (blue) suggest a lack of substantive engagement between policy-oriented and technically focused research. This conceptual divide may impede the development of integrated frameworks that fully capture the dual role of digital platforms as both technical infrastructures and instruments of governance [126,127].

Second, the conspicuous absence or marginal presence of key urban planning terms—such as land value, gentrification, housing, and mobility—is particularly revealing. Despite their foundational relevance to urban planning discourse, these terms are either peripheral or absent from the main network. This suggests that the intersection between digital transformation and core urban planning concerns remains insufficiently explored in the current literature, underscoring a critical gap that this review seeks to address.

Third, the structural configuration of the network reinforces the tripartite categorisation of digital disruptions. The emergent clustering pattern corresponds closely with the three domains identified in this review: urban activities (reflected in the governance and economic processes cluster), human behaviour (cultural economy cluster), and mobility (which remains notably underrepresented, thereby corroborating the identification of this area as a key research gap).

The term co-occurrence analysis reveals several pivotal conceptual dynamics within the existing literature. First, the network reveals a fundamental conceptual divide in the literature. The spatial separation between behavioural research (left) and economic research (right) suggests limited integration between scholars studying how people adapt to digital technologies and those examining economic-spatial transformations. This divide may explain why comprehensive frameworks for digital urban transformation remain elusive.

Second, the analysis exposes significant conceptual gaps. Traditional urban planning terms such as ‘zoning,’ ‘land use,’ ‘density,’ or ‘infrastructure’ appear minimally or not at all in the main network structure. The term ‘value’ appears but remains weakly connected to other concepts, suggesting researchers have yet to systematically link digital transformations to land value implications. These absences validate this review’s focus on connecting digital economy research with core urban planning concerns.

Third, the centrality of ‘digital economy’ as a bridging term highlights both an opportunity and a challenge. While this term connects diverse research streams, its broad usage may obscure more specific mechanisms through which digital technologies transform urban systems. The systematic categorisation into activities, behaviours, and mobility provides the conceptual precision needed to advance beyond this general framing.

5.2. Emerging Trends and Patterns

The emerging trends identified through our analysis validate the utility of our tripartite framework, while revealing its dynamic nature. Each trend, digital decoupling, platform governance, hybridisation, and uneven impact manifests differently across our three lenses but ultimately requires integrated analysis to fully understand.

5.2.1. Digital Decoupling of Land Value from Proximity

The most transformative finding emerging from our analysis is the progressive decoupling of land value from physical proximity to employment centres, services, and amenities, a phenomenon we term “digital decoupling.” This manifests through multiple interconnected mechanisms that collectively challenge fundamental urban economic principles.

Remote work capabilities have inverted traditional value gradients, with suburban properties possessing high-speed internet connectivity now commanding premiums historically reserved for central locations, with documented increases of 20–30% in digitally connected peripheral areas. Simultaneously, virtual service access diminishes the value premium of physical proximity to education, healthcare, and retail facilities, as digital platforms enable service consumption independent of location [128]. Most significantly, network effects create new value determinants, where land value increasingly correlates with digital infrastructure quality—fibre optic access, 5G coverage, and data centre proximity—rather than distance to urban centres.

This decoupling phenomenon challenges foundational theories in urban economics, from von Thünen’s agricultural land use model to Alonso’s bid-rent theory, necessitating theoretical frameworks that position digital connectivity as a primary spatial organising principle equivalent to, or potentially superseding, physical accessibility.

5.2.2. Platform-Mediated Urban Governance

The emergence of platform urbanism represents a paradigmatic shift in urban governance structures and processes. Our analysis reveals that platforms now mediate 15–40% of urban mobility and accommodation services in major cities, fundamentally altering the relationship between citizens, services, and governance institutions [129]. This intermediation extends beyond simple service provision to encompass algorithmic management of urban systems, where private companies’ proprietary algorithms determine traffic flows [130], resource allocation [131], and service accessibility [132].

The concentration of urban data within platform ecosystems creates unprecedented power asymmetries, as companies like Google, through services such as Maps and Traffic, possess more comprehensive real-time urban movement data than municipal governments [133,134]. This raises critical questions about democratic accountability and sovereignty, as unelected technology companies gain increasing influence over de facto urban policy through algorithmic decision-making.

The platform governance model operates through three distinct layers: infrastructure (platforms as essential urban utilities), service (platforms as primary service providers), and governance (platforms as regulatory actors through algorithmic rule-setting). This multi-layered intermediation challenges traditional notions of public service provision and urban governance, requiring new regulatory frameworks that balance innovation with democratic oversight and public accountability.

5.2.3. Hybridization of Physical-Digital Spaces

Rather than digital technologies simply replacing physical infrastructure, our analysis reveals sophisticated hybridisation processes creating “phygital” urban environments. This hybridisation manifests across multiple urban domains, fundamentally altering how spaces function and generate value. In retail environments, 60% of purchases now involve both digital and physical touchpoints [135], with stores evolving into experiential showrooms linked to online fulfilment systems [136], creating new spatial typologies that defy traditional commercial classifications. The workplace undergoes a similar transformation through the emergence of “third places”, cafes, libraries, and coworking spaces, that accommodate the growing remote workforce [137], with these spaces requiring new infrastructural provisions, including enhanced connectivity, privacy accommodations, and flexible furniture arrangements [138]. Public spaces increasingly incorporate digital augmentation through sensor networks, interactive displays, and AR overlays, creating multi-layered environments that simultaneously serve physical and virtual functions.

The hybridisation of phygital space necessitates planning approaches that conceptualise urban spaces as possessing dual existence, physical and digital, each with distinct but interrelated functions, values, and user groups [139,140]. The challenge for urban planners lies in creating regulatory frameworks flexible enough to accommodate rapid technological change while ensuring that hybrid spaces remain inclusive and accessible to all urban inhabitants, regardless of their digital capabilities.

5.2.4. Uneven Spatial Impacts and Digital Divides

Digital transformation’s benefits distribute unevenly across urban space, exacerbating existing inequalities while generating novel forms of exclusion. Our analysis reveals that high-quality digital infrastructure concentrates disproportionately in affluent areas, with low-income neighbourhoods experiencing 40–60% lower connectivity speeds despite often paying comparable prices for internet services [141]. This infrastructural inequality compounds through skills gaps, where digital literacy emerges as a new barrier to urban participation [142], affecting 27% of elderly populations and disproportionately impacting women in developing countries, effectively excluding them from digitally mediated services and opportunities [143]. Platform economies introduce additional exclusion mechanisms, as gig economy platforms systematically exclude individuals lacking smartphones, bank accounts, or stable addresses—prerequisites that correlate strongly with socioeconomic disadvantage.

Geographic analysis reveals these divides operating across multiple scales simultaneously: between Global North and South, where infrastructure and regulatory differences create divergent digital transformation trajectories; between urban and rural areas, where infrastructure deployment economics favour dense urban cores; and within cities [144], where neighbourhood-level disparities in infrastructure, skills, and platform access create micro-geographies of digital inclusion and exclusion [145]. These patterns suggest that without deliberate intervention, digital transformation may increase rather than decrease urban inequality, creating “digital Bantustans” where geographic location determines access to the digital economy’s benefits.

5.3. Theoretical Contributions

5.3.1. The Digital Decoupling Framework

This systematic review advances urban theory through three fundamental contributions that reconceptualise how we understand cities in the digital age. First, the researchers introduce the “digital decoupling framework” (Figure 8) as a theoretical lens for understanding how digital technologies systematically sever traditional relationships between location, activity, and value. This framework identifies three dimensions of decoupling: spatial (activities no longer require specific locations), temporal (asynchronous interactions replace synchronised presence), and value (land value derives from connectivity potential rather than locational attributes). This framework provides theoretical coherence for understanding seemingly disparate phenomena—from remote work to e-commerce to virtual tourism—as manifestations of fundamental spatial restructuring rather than isolated technological disruptions.

5.3.2. Platform Urbanism Theory

Second, we develop a comprehensive platform urbanism theory that extends beyond existing platform studies to examine how digital platforms restructure urban systems. Our framework identifies four transformation mechanisms (

Table 5. Platform urbanism transformation mechanisms.

Four Transformation Mechanisms
1. Disintermediation	2. Datafication
Before: User → Middleman → Service After: User ←→ Service Taxi dispatch → Uber app Hotel booking → Airbnb Restaurant phone → Delivery	Physical World → Digital Traces Activities → Data → Insights → Control Movement patterns → Traffic prediction Purchase history → Demand forecasting Social graphs → Targeted advertising
3. Algorithmic Management	4. Network Effects
Human Decision → Algorithm Subjective → “Objective” Surge pricing algorithms Route optimisation Rating/ranking systems	Linear Growth → Exponential Growth Competition → Monopolisation More users → Better service → More users Data accumulation → Better predictions Ecosystem lock-in → Switching costs

): disintermediation (platforms eliminating traditional intermediaries), datafication (urban activities generating monetizable data), algorithmic management (automated decision-making replacing human judgment), and network effects (platform dominance creating lock-in and barriers). These mechanisms operate through three urban layers (Figure 9): infrastructure, service, and governance, creating a multi-dimensional transformation that challenges traditional urban governance models. This theoretical contribution provides analytical tools for understanding how platforms not merely provide services but fundamentally restructure urban power relations and governance processes.

5.3.3. Phygital Value Framework

Third, we propose a digital-physical value framework (

Table 6. Phygital value framework heat map.

Phygital Value Framework
Factor Category	Traditional Era	Digital Era	Change Trend
Traditional	High Importance	Low Importance
	3		−75%
CBD Distance			−80%
Transit Access			−50%
Walkability			−67%
Parking			−80%
Street Front	2		−70%
Digital	No Importance	High Importance
Fiber Speed	Not considered		New
5G Coverage	Not considered		New
Platform Density	Not considered		New
Digital Skills	Not considered		New
Cloud Access	Not considered		New
Hybrid	Partial Importance	High Importance
			200%
Flex Spaces			200%
Delivery Access	1		233%
Smart Ready	Not considered		New
Mixed Use			71%
Adaptability			100%

¹ No importance, ² Low importance, ³ High importance.

) that reconceptualises urban land valuation by incorporating digital attributes as primary, rather than secondary, factors. Traditional factors, such as distance to CBD, proximity to transport nodes, and physical accessibility, demonstrate declining importance, while digital factors, including broadband reliability, 5G coverage, platform service availability, and local digital skills, emerge as primary value determinants. Additionally, hybrid factors, such as adaptability for digital use, last-mile delivery accessibility, and AR/VR readiness, represent emerging value drivers that blur physical–digital boundaries. This framework suggests that urban economics must fundamentally reconceptualise value creation mechanisms in cities where digital connectivity rivals or exceeds physical accessibility in importance.

5.4. Recent Developments and Emerging Studies

While our systematic search protocol (conducted through January 2024) captured 66 studies meeting our inclusion criteria, we acknowledge several recent high-impact publications that provide additional insights into digital economy impacts on urban systems. These papers, published after our search cutoff or in journals outside our initial database parameters, offer important perspectives that both validate and extend our findings.

Guo et al. [146] provide crucial quantitative evidence for the digital economy’s impact on urban economic quality in their comprehensive analysis of Chinese cities. Using panel data from 2011–2019 and employing spatial econometric models, their findings reveal spatial spillover effects, where digital economy development in one city positively influences neighbouring cities’ economic quality. A phenomenon we identified in our term co-occurrence analysis (Figure 6), but lacked quantitative validation for. This study particularly strengthens our findings on the “revaluation of urban and suburban areas” by providing empirical evidence that digitally connected cities experience 15–20% higher economic growth quality compared to less connected peers. Moreover, their identification of threshold effects, where digital economy impacts accelerate after reaching certain infrastructure levels, helps explain the geographic disparities we observed between well-connected European and Asian cities and infrastructure-limited African contexts.

Xu et al. [147] address a critical dimension largely absent from our initial corpus: how digital economies enhance urban resilience. Their analysis of 284 Chinese cities from 2011 to 2021 demonstrates that digital economy development improves urban resilience through four pathways: enhancing information flow during crises, diversifying economic structures, improving resource allocation efficiency, and strengthening social networks. Their innovative use of text mining to analyse government work reports provides methodological insights for capturing policy responses to digital transformation.

Das and Kwek [148] offer a deep ethnographic examination of Singapore’s AI-driven urbanism, providing crucial insights into the intersection of artificial intelligence, data governance, and urban planning. Their 18-month fieldwork reveals how AI systems are reshaping urban governance through predictive analytics, automated decision-making, and citizen surveillance. This study significantly extends our findings on “corporatisation of urban governance” by showing how AI introduces a new layer of technological mediation between citizens and city services. Their concept of “data-driven spatial segregation”—where AI systems optimise urban services in ways that inadvertently concentrate resources in already-privileged areas—provides a mechanism for the spatial inequalities we identify.

The comprehensive policy paper by Jieutsa et al. [149], based on workshop discussions with 20 African urban researchers and practitioners, fills a critical gap in our geographic coverage. Their policy recommendations—prioritising inclusive digital infrastructure, protecting vulnerable sectors through regulation, and ensuring transparent governance—provide concrete pathways for addressing the inequalities our review identified.

5.5. Geographic Variations in Digital Economy Impacts

Chinese studies (n = 10) represent a distinct approach to digital economy research, characterised by state-led smart city initiatives and platform economy integration. The prominence of terms like “China,” “employment,” and “spatial spillover” in our bibliometric analysis (Figure 6) indicates that Chinese urban experiences significantly shape theoretical understanding in this field. Chinese research emphasises technology-driven solutions, quantitative economic metrics, and the spatial spillover effects of digital transformation, where digital economy benefits in one city positively influence neighbouring cities [79,150]. This reflects China’s unique model of digital urbanism, combining strong state planning with rapid platform economy growth [151,152].

European studies (n = 32), representing nearly half of our sample, demonstrate markedly different concerns. These studies prioritise governance implications, social equity, and citizen rights in digital transformation. The co-occurrence of terms like “governance,” “regulation,” and “data” in European research reflects the region’s emphasis on protecting citizens from potentially harmful digital practices [153,154]. European scholars are particularly concerned with platform urbanism’s impact on democratic accountability and public space privatisation [70,71]. This orientation aligns with the EU’s regulatory framework, including GDPR and emerging digital rights legislation.

Despite the limited representation of African contexts in the literature, emerging scholarship highlights critical divergences in how digital transformation unfolds across geographies. The recent policy paper by Jieutsa et al. [149], based on a multidisciplinary workshop involving 20 African scholars and practitioners, underscores the continent’s unique challenges that are largely absent from European and Asian discourse. Unlike cities in the Global North and parts of Asia, which are preoccupied with issues of platform governance and data regulation, many African cities continue to struggle with foundational infrastructure deficits. With an estimated 900 million people lacking internet access, the principal barrier is not the regulation of digital platforms but the establishment of inclusive and equitable digital infrastructure [155]. Furthermore, the digital divide disproportionately excludes vulnerable populations, including the elderly, women, refugees, illiterate individuals, and local-language speakers [156], revealing a digital transformation that risks reinforcing preexisting social inequities. The deployment of e-hailing platforms, such as Uber, has also produced distinct and often violent conflicts in cities like Casablanca, Cape Town, and Douala, where the absence of robust regulatory frameworks has led to clashes between platform drivers and traditional taxi operators [157].

The severe underrepresentation of Latin American (n = 4) and North American (n = 1) studies indicates significant knowledge gaps. Latin American cities, experiencing rapid urbanisation and informal economy dynamics similar to Africa, likely face unique digital transformation challenges not captured in our review. The absence of North American perspectives is particularly striking given Silicon Valley’s role in developing many platform technologies reshaping global cities.

The geographic concentration of the existing research, primarily centred on European and Asian contexts, presents significant limitations for both theory development and policy application in the study of the digital economy’s impact on urban land use. Theoretically, prevailing frameworks are largely informed by European governance models and Chinese state-led development paradigms, which may not adequately capture the dynamics of cities characterised by informal economies [158], limited institutional capacity [159], or infrastructural deficits [160]. This narrow lens constrains the generalisability and applicability of theoretical constructs to diverse urban realities.

From a policy perspective, the dominance of Global North and East Asian experiences introduces the risk of inappropriate policy transfer. Regulatory approaches developed in European contexts, for instance, often presuppose robust digital infrastructure and formal labour markets—assumptions that may not hold in African or Latin American cities, where informal economies and infrastructural precarity prevail. Furthermore, these biases risk overlooking innovation emerging from the Global South. Historical precedents, such as the pioneering of mobile money systems in Africa [161], which subsequently influenced global fintech models, suggest that similar urban innovations, born from resource-constrained environments [162], may be underrecognised. Addressing this geographic imbalance is, therefore, critical to developing inclusive, context-sensitive, and globally relevant urban digitalisation strategies.

5.6. Limitations

Publication and Language Bias: The restriction to English-language publications likely excluded relevant research published in other languages, particularly from non-Anglophone regions experiencing significant digital transformations (e.g., China, Brazil, and Indonesia). Additionally, the focus on peer-reviewed academic literature may have introduced publication bias toward studies with positive or significant findings, as null results or failed digital initiatives are less likely to be published [163]. The exclusion of grey literature also means that recent industry reports and government assessments of digital transformation impacts were not captured, potentially missing cutting-edge developments.

Synthesis Challenges: The heterogeneity of the included studies—spanning theoretical essays, empirical research, and case studies—presented significant synthesis challenges. The thematic analysis approach, while appropriate for diverse evidence, relies on reviewer interpretation and judgment, introducing potential subjectivity despite dual-reviewer processes [164,165]. The inability to conduct meta-analysis or systematic quality scoring due to methodological diversity means that all findings were weighted relatively equally, regardless of study robustness or sample size.

Reviewer and Resource Limitations: Although two reviewers independently conducted screening and extraction, both are affiliated with the same disciplinary backgrounds, potentially introducing shared biases in interpretation [164,165]. Resource constraints prevented the engagement of additional reviewers from different disciplinary backgrounds (e.g., economics or computer science) who might have offered alternative perspectives on the evidence. The lack of direct contact with study authors to clarify ambiguous findings or obtain additional data represents another limitation.

Scope Boundaries: The focus on land use and land value, while providing analytical clarity, may have artificially separated interconnected urban phenomena. For instance, social equity impacts were considered primarily through a spatial lens, potentially underemphasising important non-spatial dimensions of digital transformation [166,167]. The exclusion of rural–urban linkages and peri-urban areas also limits understanding of how digital economies reshape entire metropolitan regions rather than just urban cores [168,169,170].

6. Conclusions

This scoping review systematically examines 66 studies to understand how the digital economy disrupts urban land use and value through transformations in activities, behaviours, and mobility. Through our tripartite analytical framework, we reveal the fundamental reconfiguration of spatial–economic relationships that have governed cities since industrialisation. Five key findings emerge from this comprehensive analysis. First, digital technologies decouple land value from physical proximity, with connectivity replacing accessibility as the primary value determinant—connected districts command 15–30% premiums, while traditional CBDs experience systematic devaluation. Second, platform urbanism shifts urban governance from public to hybrid public–private models, with platforms mediating 15–40% of mobility and accommodation services in major cities. Third, behavioural transformations manifest in 20–40% reductions in physical retail trips and 30–50% of knowledge workers adopting remote work in digitally advanced cities. Fourth, mobility patterns are fragmenting into hyperlocal movements and last-mile delivery, with commuting declining by 25% and local delivery traffic increasing by 300%. Finally, significant geographic disparities persist, with European and Asian cities dominating research (78% of studies), while African and Latin American contexts remain critically underexamined.

This review makes three fundamental theoretical contributions to urban studies. Our digital decoupling framework demonstrates that urban economic theory must fundamentally reconceptualise value creation mechanisms, moving beyond distance–decay models to network–effect models where digital connectivity rivals or exceeds physical accessibility in importance. The platform urbanism theory reveals how digital intermediaries create new governance layers that challenge traditional municipal authority and democratic accountability, requiring new analytical tools to understand power dynamics in digitally mediated cities. Additionally, the phygital value framework provides mechanisms for valuing hybrid physical–digital spaces, where traditional metrics of footfall and proximity become insufficient for capturing value creation in spaces that exist simultaneously in physical and digital realms.

The transformative patterns identified demand immediate and fundamental changes in urban planning and policy. Cities must urgently revise zoning codes to accommodate hybrid live–work spaces and platform-mediated services that transcend traditional land use categories, recognising that rigid industrial-era classifications no longer reflect how urban space is actually used. Comprehensive platform regulation frameworks must be established that balance innovation with worker protection and democratic oversight, addressing the governance vacuum created by platform intermediation of urban services. Most critically, universal digital infrastructure deployment must be prioritised as a fundamental urban right equivalent to water or electricity access, particularly in underserved communities where market forces alone prove insufficient to ensure equitable access to the digital economy’s benefits.

Several critical research priorities emerge from this review’s findings. Longitudinal studies tracking actual land value changes over time, rather than cross-sectional snapshots, are essential, particularly in Global South contexts where digital transformation may follow different trajectories than those observed in Europe and Asia. The development of standardised metrics for measuring digital disruption intensity would enable comparative analysis across cities and identification of best practices for managing digital transformation. Furthermore, the investigation of feedback loops between digital transformation and climate adaptation strategies becomes increasingly urgent as cities simultaneously navigate technological and environmental transitions, with potential synergies and conflicts requiring systematic examination.

The digital transformation of cities represents not merely a technological overlay but fundamental spatial restructuring comparable to industrialisation’s impact. Cities that recognise and adapt to these transformations—through integrated planning approaches that address activities, behaviours, and mobility holistically—will thrive in the digital age, while those clinging to industrial-era frameworks risk obsolescence.