Next Article in Journal
Relationship Between Visual Marketing Elements and Consumer Satisfaction
Previous Article in Journal
Digital Transformation for Smart and Resilient Cities: Assessing Platform Maturity and ISO 37123 Compliance
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Platforms as Proximity Enablers for Regional Development

School of Spatial Planning and Development, Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece
Platforms 2025, 3(1), 4; https://doi.org/10.3390/platforms3010004
Submission received: 19 December 2024 / Revised: 13 February 2025 / Accepted: 28 February 2025 / Published: 5 March 2025

Abstract

:
This study offers a theoretical contribution exploring the interplay between platforms, proximity, and regional development and highlighting platforms’ crucial role in transforming routines and enhancing regional capabilities. It argues that routines, defining regional organization and adaptability, exhibit high transformative potential through platforms. Additionally, the study outlines a five-phase platform integration process in the regional context—sensing, patterns, categories, relations, and sequences—emphasizing the progression from vague platform comprehension to nuanced perception. This symbiotic relationship between platform utilization and routine development reinforces regional adaptability, innovation, and success in a connected landscape, shaping new opportunities for proximity-driven development.

1. Introduction

Development has been described as an uneven process across European NUTS2 regions, hereafter referred to as ‘regions’ [1,2]. Local attributes such as accessibility, the ability to attract skilled individuals, trust, and institutional strength are frequently emphasized as pivotal elements in fostering a region’s potential for development [3,4]. Metropolitan areas have been linked to higher levels of development, while regions with sparse populations, limited human resources, and poor accessibility tend to exhibit lower levels, indicating a positive correlation between spatial concentration and development [2,5].
Proximity plays a pivotal role in such agglomeration processes, stimulating productivity and paving the way for new paths of development [6]. Proximity allows regions to effectively combine their existing resources, fostering networks and the exchange of knowledge among stakeholders, thereby boosting knowledge production and spillover effects to neighboring areas [7]. In agglomeration economies developed in large metropolitan areas, increased concentration of resources can generate significant proximity-related benefits, facilitating the desired outcomes, while its absence hinders the emergence of effective proximity effects [8,9]. Consequently, regional disparities can be seen as an issue of unbalanced capability in producing the proximity-related benefits required for creating the necessary conditions for development.
Meanwhile, the evolving landscape of productivity and innovation has been significantly influenced by the emergence of digital platforms—hereafter referred to as platforms—introducing a novel framework connecting agents and data through digital processes [10,11]. Platforms have progressively become an integral element in value creation, establishing processes that complement or operate independently from traditional spatial structures, while fostering interactions, information flows, and network effects [5]. Hence, platforms can strengthen regional capabilities in relation to productivity and innovation by augmenting their ability in proximity creation [12,13].
The study investigates the power of platforms from a proximity-centered viewpoint, adding to previous research focusing on market-oriented approaches regarding the role of platforms [14,15]. It argues that platforms have the capacity to bridge prevailing proximity disparities, balancing regional differences among productivity, innovation potential, and opportunities within the labor market. To do so, it examines and analyses how platforms, via digital means, have significantly disrupted the organization of space at the regional level by complementing and facilitating existing dynamic processes that are crucial for the emergence of proximity. It investigates the digital factors that serve as connectors among platform agents, encompassing individuals, organizations, institutions, regions, and knowledge domains, establishing the dynamic perspectives of platforms. It also examines the fundamental components contributing to the emergence of proximity within platforms using the concept of routines as a cornerstone and linking them to productivity and innovation processes. Its theoretical contribution lies in the fact that it presents a five-phase platform integration process in the regional context—sensing, patterns, categories, relations, and sequences—emphasizing the progression from vague platform comprehension to nuanced perception. Thus, this study aims to provide a concrete theoretical link between the traditional notion of proximity and its digital equivalents.
The core argument of this study is that platforms, and the digital space they create, should be approached as an additional spatial dimension that works complementary to existing physical, organizational, institutional, social, and cognitive spaces. Embedding platforms into existing structures and creating connected spaces will result in increased regional capabilities and the emergence of intelligence. This is an essential step towards identifying the new challenges and opportunities introduced by platforms for regional development, focusing on productivity growth, resilience, sustainability, and inclusion, as well as the ways they could be integrated in existing policy frameworks.
This paper is structured as follows. Section 2 reviews key dynamic processes that shape regional capabilities and explores the role of platforms in facilitating and complementing these processes. Section 3 provides a detailed analysis of existing digital connectors that are embedded in platforms linking their various structural elements and agents. Section 4 explores routine transformation and enhancement through digital platforms, while Section 5 discusses the platform integration phases in a regional context. Finally, Section 6 presents concluding remarks along with a broader discussion on how future research can build upon the proposed approach to further explore the power of platforms in relation to proximity emergence and regional development.

2. Dynamic Processes Shaping Regional Space and the Role of Platforms

Regional space refers to a collection of various forms of space (e.g., physical, social, organizational, institutional, and cognitive) that interact at the regional (sub-national) level of analysis. Within this context, dynamic processes include economic development, demographic shifts, policy interventions, technological advancements, and environmental changes. These processes shape the spatial structure of regions, influencing patterns of land use, infrastructure development, social cohesion, and governance. The interactions within regional space contribute to its continuous evolution, affecting competitiveness, resilience, and sustainability in an increasingly interdependent world.
Proximity arises from interconnected dynamic processes shaping the various forms of space involving interactions among agents, network formation, and resource flows. Consequently, a region’s capacity for proximity emergence, a pivotal factor for development, heavily relies on these processes and their manifestations within the regional context. Recently, the integration of different interconnected types of technological advancements resulted in the creation of new and the enhancement of existing forms of intelligence, such as artificial and collective intelligence, facilitating processes of production, diffusion, and accumulation of knowledge [16]. In this context, this study argues that the power of platforms as proximity enablers derives from their ability to create connected digital spaces where different actors co-exist and work together, thus enhancing interactions, network formation, and information flows.
The following paragraphs build on this idea by approaching and analyzing the notion of platforms as collaboration spaces, ecosystems, and information channels, which can effectively reinforce and optimize existing proximity forms while bypassing physical space barriers, such as limited accessibility and isolation.
Interactions among agents—individuals, businesses, organizations, and/or institutions—tend to increase the co-location of activities and environments, resulting in the formation of centripetal forces that are key driving elements for the creation of agglomeration economies, such as cities and innovation ecosystems [17,18]. At the same time, the effectiveness of numerous human activities relies on our capacity to live and work together within organized groups and societies [19]. Hence, collaboration is a key element that needs to be empowered when trying to maximize the benefits of agglomeration forces in physical space.
Collaborative intelligence emerges from shared efforts and synergies among individuals working towards a common goal [16]. In terms of innovation, partnerships, and coordination, collaborative intelligence can be effectively cultivated through network-based relationships [20]. Advancements in technology have created novel spaces where both actors and artifacts interact, communicate, and share knowledge and abilities, fostering the development of cyber–physical systems and collaborative innovation [21,22]. For instance, digital technologies and open data enhance participatory governance and public discourse in urban settings, promoting outcomes of collaborative intelligence in evidence-based decision-making [23,24].
Platforms provide the capacity to facilitate team collaboration, thereby unlocking the benefits of collective intelligence supported by a large variety of practices, such as open-source software, big data analysis, citizen science initiatives, and social mapping [25,26]. All these elements are essential for triggering interactions among agents in the digital space and generating agglomeration effects [18]. In this way, platforms can enhance the emergence of cyber–physical systems by efficiently merging advantages offered by user engagement and crowdsourcing together with technology, e-tools, datasets, and analytics [16]. This results in transforming the links between regional capabilities, knowledge, and human capital with global knowledge flows, fostering glocalized collaboration spaces shaped by intricate, non-linear, and dynamic processes of knowledge creation, diffusion, and utilization.
Increased interaction density, especially when integrated with established organizational and institutional frameworks, amplifies the emerging connections among diverse stakeholders across different areas. This integration unlocks their inherent potential for forming networks and nurturing developmental benefits [27]. Within this framework, innovative organizational structures like collaborative production and the utilization of open spaces seek to boost regions’ capacity to generate synergies and foster interactions among their stakeholders, ultimately aiming for more effective network formation processes.
Platforms play a pivotal role in fostering substantial synergies among their participants, leading to heightened interconnectedness and the establishment of ecosystems. These platform ecosystems offer a fresh organizational perspective, nurturing the emergence of collaborative and innovative business models through technology. Within platform structures, digital components promote synergies and collaboration among a multitude of participants who serve as both producers and consumers, actively generating and exchanging value [28]. This dynamic serves as a catalyst for the shift from traditional centrally organized production to decentralized production models and innovative processes, facilitating the seamless exchange of knowledge among collaborating peers [29].
These technological advancements create an ideal environment for establishing decentralized production, capitalizing on advantageous network effects, reducing transaction costs, and enabling wider market access [30]. These boundaryless ecosystems act as pivotal launchpads for other organizations, enabling regions to cultivate complementary products, technologies, or services [18,31]. Consequently, regions derive significant benefits from platform ecosystems, leveraging them to strengthen their capabilities in resource-sharing, knowledge dissemination, and market access.
At the same time, resource flows taking place within the local system stand as a dynamic element closely associated with proximity emergence, which is often interconnected with the existence of networks [32]. These flows significantly impact regional disparities by shaping a region’s ability to produce proximity externalities. For example, spatial disparities between the skills of individuals and available job opportunities lead to greater movements of resources, aiming to bridge the gaps in productivity and income [33]. These resource movements both influence and are shaped by spatial characteristics, demonstrating a tendency toward concentration that drives patterns of uneven regional development and territorial divergence [34]. This trend is notably observable in newly industrialized economies, where urban centers have increasingly become focal points for the development of their regions by attracting and concentrating human capital [35]. The growing concentration of job opportunities in urban areas has led to an imbalanced developmental process, leaving less-populated regions struggling to maintain adequate levels of skilled workers. This imbalance has resulted in a downward spiral affecting productivity, innovation potential, and overall developmental prospects [2].
Platforms have recently reshaped the movement of resources by introducing new avenues for accessing remote job markets. Trends like remote work and the rise of digital nomadism have seen continuous growth, especially in the wake of the COVID-19 pandemic, signaling a profound redefinition of the traditional concept of a ‘workplace’. Technological advancements have served as a catalyst for disassociating job opportunities from physical locations. This shift has been facilitated through the development of remote work applications, aiming to expand the capacity to work from multiple locations. Consequently, this transformation has altered mobility patterns, impacting not just urban or metropolitan areas, but also inter-regional dynamics. Suburban and peripheral areas have started to become increasingly attractive for both living and working, even for highly skilled individuals who previously preferred metropolitan areas due to a stronger alignment between their expertise and local labor market opportunities [36,37]. Within this context, digital infrastructures, notably broadband connectivity, have emerged as pivotal factors in redefining regional attractiveness. This underscores the significant influence platforms wield over the distribution of resources, and especially human capital, across different spaces, consequently shaping developmental opportunities.

3. Platforms Empowering Connectivity

Platforms serve as key drivers of dynamic processes, fostering interactions among diverse agents, enabling network development, and orchestrating resource distribution. These functions collectively enhance regional capacities, shaping their economic, social, and institutional landscapes. Yet, to gain a comprehensive understanding of the mechanisms steering these processes, it becomes crucial to explore the factors connecting agents and the digital components of platforms. When we speak of agents, we refer to all assets that compose regional capabilities, spanning individuals, organizations, institutions, regions, and the various domains of knowledge available within a region. Therefore, emphasis should be placed on exploring the diverse connectivity types that emerge amongst them relating to the multifaceted aspects of proximity (e.g., social, organizational, institutional, cognitive), and how platforms have impacted them.
In general, connectivity takes various forms based on the type of proximity it refers to [12]. For example, physical networks, such as transport infrastructure, constitute a significant connector in the case of geographical proximity strengthening the links between physical space. Similarly, social networks, such as cultural and ethnic communities, are the ones responsible for creating links between actors, boosting social proximity. Moreover, connectivity between organizations arises as an outcome of common protocols, processes, and working culture, increasing the compatibility between their processes, while institutional connectivity is achieved through the governance systems, encompassing laws, rules, and policies, setting the framework for designing and developing relevant solutions. Finally, in the case of cognitive proximity, multidisciplinary research and publications are key elements for boosting connectivity between different knowledge fields.
Platforms have introduced new channels of communication affecting connectivity within the regional space, either by creating new links or by enhancing existing ones. Consequently, platforms are influential in generating market disparities or shortcomings, leading to externalities that influence both production and consumption. Understanding how digital connectors integrated into platforms stimulate proximity necessitates drawing parallels between established connectors in various spatial forms and their digital counterparts. This correlation enables the association of these connectors with distinct types of proximity to further elaborate on how platforms facilitate connections among stakeholders to bolster regional capabilities.
Typically, platforms themselves represent digital renditions of physical infrastructures, serving as hubs that aggregate assets by gathering information, goods, and services from diverse agents. This consolidation forms a shared and intricately interconnected economy, creating network effects between users [38]. Hence, platforms offer digital spaces for creating and/or empowering agglomeration effects, generating value to users through the presence of others on the platform [31]. This type of connectivity boosts proximity in a similar way to geographically concentrated systems, such as cities and innovation ecosystems. However, platform connectivity is not without limitations, as issues like network dependency, latency, server downtime, and interoperability challenges can hinder seamless interactions. Additionally, security risks, bandwidth constraints, and regional restrictions may impact user access and engagement. In this context, platform sustainability is a crucial factor in establishing stronger networking and self-sustained ecosystem dynamics [31].
When transitioning to tools embedded within platforms, a diverse range of applications can function as connectors covering organizational, institutional, social, and cognitive aspects of proximity. Starting with the organizational perspective, digital management systems, including enterprise resource planning, product life-cycle management systems, and cloud computing infrastructures, aim at improving the performance of agents in relation to tasks or activities. This is achieved by normalizing information within organizations linked to multiple processes and workflows across different departments [39], as well as by consolidating information and process management across globalized supply chains [40]. Organizational proximity, in this case, is strengthened by establishing accessible channels that forge robust connections either between organizations or within them, fostering a shared base for disseminating knowledge.
At the same time, institutional connectivity is enhanced by the introduction of new digital governance models fostering institutional transparency and flexibility [6]. Open repositories, blockchain technologies, automated feedback systems, and intellectual property rights constitute some integral parts for achieving a shared institutional culture. Moreover, digital commons, such as online forums, enhance the ability to introduce decentralized and bottom-up decision-making structures, making institutions more flexible in terms of dealing with uncertainties and complexities in policy making [41,42]. Hence, platforms can effectively promote openness alongside wide participation and meaningful engagement, which are essential for empowering institutional proximity through transparency and flexibility.
Furthermore, social media platforms constitute key channels for enhancing social connectivity through networks and digital living labs. Their integrated digital tools facilitate the development and the establishment of socially embedded relations, which can act as boosters of trust between various agents [43]. This increases participation and brings additional benefits related to information sharing and higher network utility [44]. The growing positive correlation between network size and social externalities indicates that platforms function as extended online communities, encouraging active engagement and communication among their participants [18]. This process is facilitated by participatory experimentation and co-creation activities, which play a crucial role in enhancing social proximity by fostering flexible personal connections and reducing entry barriers for newcomers [45]. Therefore, social connectivity is boosted through the emergence of wide collaboration networks characterized by solid social structures and interpersonal relationships.
Regarding cognitive proximity, platforms serve as catalysts that drive collaborative knowledge production by inspiring users to contribute to particular or related cognitive domains, thereby generating beneficial external effects [46]. The use of open knowledge repositories for content generation and sharing with low temporal and spatial constraints is an important factor in releasing the power of platforms in this field. Open knowledge repositories support both the interconnectedness of expertise and communal knowledge, encompassing the utilization of individual skills via direct interaction and the collective knowledge that arises from shared information among group members [47]. Meanwhile, platforms can facilitate the management of knowledge generated by diverse actors by enabling them to create, collaborate, edit, and share content in a structured manner, while their co-creation tools empower learning processes and virtual collaboration, stimulating innovative ideas [48]. Thus, platforms enhance the capacity of individuals to learn from one another and facilitate swift knowledge dissemination without relying on the geographical proximity of participants, increasing new opportunities for less connected regions.

4. Routine Transformation and Enhancement Through Platforms

Routines, as defined by Feldman and Pentland [49], encompass sets of interconnected actions performed by various agents, impacting regional organization through a combination of inertia and adaptability. These dual facets encompass both the structural, abstract nature and the specific, actionable character [50]. In essence, routines serve as organizational learning mechanisms, fostering endogenous growth within an evolutionary framework and embedding knowledge and capabilities crucial for organizational adaptation in the face of innovations [51,52,53]. Carrincazeaux et al. [54] note that higher technological complexity requires more frequent routine transformations, while standardized production relies on more rigid, less adaptable routines.
The effectiveness of routines is heavily influenced by the context in which they function [55]. Crucial to this effectiveness are shared social, cognitive, and organizational structures, facilitating the seamless development of action patterns among multiple agents, ultimately enhancing routine efficiency. This interplay creates a reinforcing cycle, fostering organizational, social, and cognitive proximity [56]. Therefore, the connectivity facilitated by common platform structures can be transformed into proximity when viewed within the framework of routines.
More specifically, platforms present a significant opportunity to replicate or even improve routines due to their repetitive nature. Procedures that were traditionally performed manually or physically can now be executed by digital tools and applications, potentially streamlining and enhancing these routines. However, not all types of routines are suitable for replication and enhancement by platforms. Based on their transferability potential, we can identify four different types of routines: fully transferable, semi-transferable, non-transferable, and new routines [12].
Fully transferable routines refer to processes that can be entirely moved from the physical to the digital space. These routines can be easily replicated by digital tools taking advantage of the automation, efficiency, and scalability that platforms can offer throughout their seamless implementation. Some indicative examples for fully transferable routines are data entry, document management, and basic calculations, which can be very easily optimized when performed on platforms, reducing error risks and accelerating process management, especially in complex tasks. Semi-transferable routines can be partially transposed onto platforms, often comprising a blend of tasks that can be automated by digital tools alongside those necessitating human intervention or physical presence. For instance, customer support can be considered as a semi-transferable routine encompassing an initial automated screening process to handle common inquiries and identify user requests, followed by personalized assistance for addressing more intricate issues. While digital tools proficiently handle the initial phase, they fall short in effectively managing the latter, which requires a human touch and cannot be entirely automated. Hence, a hybrid approach becomes essential in this scenario, where platforms serve as facilitators, optimizing processes, and enriching the customer experience. Non-transferable routines include processes that cannot be reproduced by platforms. Tasks falling into this category are closely tied to physical presence and human judgment, necessitating empathy, creativity, or intricate decision-making, which cannot be replicated by algorithmic systems. Examples like creative tasks and therapy epitomize non-transferable routines, demanding a significant amount of human expertise, intuition, and emotional understanding, which are not technologically reproducible. Finally, platforms have the capacity to introduce new routines, prompting shifts in work dynamics, interactions, and broader lifestyle aspects that were previously inaccessible. The advent of artificial intelligence, automation, and smart technologies plays a pivotal role in this paradigm. Virtual assistants and recommender systems, for instance, serve as essential components in this emerging landscape, optimizing scheduling and predicting consumer preferences. This reformulates everyday processes, impacting both production and consumption facets.
Figure 1 schematically presents the identified routine types, based on their potential to be transferred onto platforms. As can be seen, the first case refers to non-transferable routines whose implementation is not affected by platforms. The following two cases refer to existing routines, which can be either partially or fully delivered through platform-based technologies. Finally, the fourth case represents the case of a new routine emergence, where existing physical and digital elements co-exist with new digitally enabled tasks. This is the most interesting but also the most difficult case to find, as it embeds an innovative character for the developmental potential of a region.
The channels mentioned earlier, through which platforms empower routines, can lead to a general rise in connectivity among agents, paving the way for new opportunities in proximity. To better understand the relevance of this in regional development, it is crucial to delve into particular routines integral to regional processes, such as product innovation and smart specialization strategy. Unveiling the transformative influence of platforms on these routines requires dissecting them into smaller tasks (sub-routines), each capable of being replicated or enhanced through digital tools. The following paragraphs explore this aspect by decomposing these two processes into their constituent actions, highlighting how platforms play a role in their implementation or enhancement.
Starting with product innovation processes, the literature has highlighted the importance of technology for new product development, as it is inherently related to innovation [57]. Four sub-routines can be identified in this case—customer insight, ideation, development, and launch—each one of which can be facilitated by platform-based tools [58]. Tools such as big data analytics, visual simulation, customer profiling, and discussion platforms closely align with the customer insight sub-routine. Concurrently, digital tools like rapid prototyping, simulation tools, co-design platforms, and vision narratives are indicative of their relevance during the ideation phase. The product development sub-routine, crucial for streamlined processes and enhanced collaboration, can be fortified through the utilization of project management tools, collaborative environments, and computer-aided design. Lastly, when deconstructing the product launching sub-routine, digital elements such as enterprise resource planning, product sales simulation tools, advanced product life-cycle management systems, and social media dashboards emerge as critical components. These digital tools play an instrumental role in linking cross-functional activities, expanding outreach to a broader audience, and monitoring engagement throughout the product launch process [58].
From the above, it becomes clear that platforms can both transform and enhance product innovation routines. However, these newly introduced platform-based tasks also confront various challenges. Optimizing organizational and development processes at the regional level stands as a critical barrier, demanding streamlined workflows and agile methodologies to adapt swiftly to evolving demands. Effective collaboration and joint design between producers and consumers pose another challenge, necessitating robust platforms facilitating seamless interaction and feedback loops for a symbiotic relationship. Empowering information sharing and knowledge diffusion among regional actors is paramount, requiring innovative digital tools that facilitate swift and effective communication, thereby fostering a culture of continuous learning and ideation. Furthermore, maintaining regional competitiveness requires constant effort to harness and amplify its unique competitive advantages, demanding strategies that align with evolving market needs and trends, bolstered by agile innovation processes and responsive adaptation to industry shifts.
Moving on to smart specialization strategy routine, it is possible to decompose it into six discrete sub-routines, each one of which integrates various methodologies, some of which indicate high complexity creating difficulties in their understanding and implementation by the regional actors [24,59]. Platforms in this case introduce digital tools that facilitate the application of the required methodologies expanding administrative capabilities of regional institutions [60]. Interoperability, logical connections, and information links constitute the key features that are being introduced and empowered by the corresponding digital elements. For example, platform-based tools facilitating and enhancing regional context analysis sub-routine include evidence-based regional asset and research infrastructure mapping, science and technology profiling, and specialization index calculations. These tools use data mining and analysis techniques for performing complex comparisons between regions revealing composite relationships that may exist within the regional innovation and knowledge production system. Visualization tools are also essential in this case as they enable more efficient knowledge diffusion and learning processes between users participating in these sub-routines.
The platform-based design and implementation of a smart specialization strategy confronts a series of challenges crucial for its success. First among these is the optimization of data integration from diverse sources, necessitating robust systems capable of harmonizing disparate datasets to derive meaningful insights. Expanding data processing within complex methodological frameworks poses another hurdle, demanding sophisticated analytical tools to navigate and extract valuable information from intricate data structures. Effective information sharing and collaboration among actors from diverse backgrounds stand as a pivotal challenge, requiring platforms that facilitate seamless interaction and knowledge exchange to align diverse expertise towards common goals. Moreover, building holistic monitoring and evaluation processes is essential for assessing the effectiveness of regional policies, requiring sophisticated tracking mechanisms and evaluative tools to gauge the impact and efficiency of implemented strategies, ensuring they align with the region’s overarching goals and objectives.

5. Platform Integration Phases at the Regional Context

To date, it has been argued that platforms represent a novel avenue for fostering proximity and empowerment, complementing established connectivity structures such as physical, organizational, institutional, cognitive, and social networks. Nevertheless, the efficacy of harnessing their potential hinges on the degree to which regions can adeptly integrate them into their developmental processes, thereby enhancing their knowledge base and capabilities. This section presents a process with five distinct learning phases that regions must traverse to effectively harness the transformative influence of platforms (Figure 2).
Considering that routines play a pivotal role in the conversion of platforms into proximity generators, the outlined learning process should prioritize a comprehensive grasp of the effective integration of platforms and routines. In the initial stages, regions not yet immersed in the realm of platforms face challenges in distinctly identifying the individual components. Thus, Phase 1 marks the shift from a vague comprehension of platforms to a more nuanced perception, empowering regions to discern specific functions and crucial elements associated with them. During this phase, regions begin to recognize the emergence of something novel and become increasingly attuned to new experiences stemming from these aspects. For example, a region transitioning through Phase 1 may initially perceive social media platforms as mere communication tools. However, as the phase unfolds, they start recognizing the platform’s potential for community building, information dissemination, and public engagement. Previous studies have highlighted the role of social media platforms as enablers for community building and development [61]. Over time, these platforms contribute to the gradual accumulation of social capital within a region, fostering stronger social connections and collective engagement [62]. This heightened awareness allows the region to adapt and explore new possibilities, laying the groundwork for a more informed and purposeful utilization of platforms in subsequent phases.
In Phase 2, regions progress to identify and differentiate recurring patterns among platform elements. This advancement allows them to discern which elements within the platform exhibit similar functionalities and can be applied for specific purposes. Recognizing that not all platform elements serve identical functions is crucial for gaining a comprehensive understanding of its diverse components and their respective applications. Consequently, regions transition from relying on automatic reflexes when interacting with platforms to a more conscious utilization, strategically employing them for specific purposes. For example, a region that has reached Phase 2 may recognize that certain platform elements, such as data analytics tools and communication features, consistently appear together in successful initiatives, such as MinStad, BlockByblock, CityLab010, VisitTheMayor, and NextCampus, facilitating active citizen participation. Evidence suggests that the co-creation process not only enhances citizen engagement but also fosters the development of more sustainable solutions to local challenges [63,64]. Understanding these recurring patterns enables the region to strategically leverage these elements for data-driven decision-making and effective communication strategies. Instead of approaching platforms with a broad, automatic usage, the region can now consciously tailor its platform utilization to optimize outcomes. This conscious approach might involve integrating data analytics tools for informed decision-making and utilizing communication features to engage stakeholders, thereby enhancing the region’s ability to achieve targeted objectives with precision and efficiency.
Advancing into Phase 3 takes the comprehension of platforms to a higher level, empowering regions to realize that the diverse platform elements can be categorized into distinct groups, each exhibiting shared characteristics among its elements. Consequently, regions gain the ability to select from a range of platform-based tools when contemplating the execution of specific actions, with a focus on optimizing potential outcomes. For example, at this stage, a region may categorize platform elements into groups such as data analytics, communication tools, and collaborative platforms. This categorization allows the region to tailor its approach based on its specific objectives. If the goal is to enhance public engagement, the region might choose communication tools, such as social media platforms, that citizens tend to engage quite easily but without a structured way [65], whereas if the focus lies more on data-driven decision-making, the use of collaborative platforms is encouraged given their structured approach that captures more motivated individuals and in-depth insights [66]. The ability to strategically select and combine platform-based tools based on shared characteristics enhances the region’s agility and effectiveness in addressing diverse challenges and objectives [67].
The foundational aspects of the regional learning process set in the first three phases described above involve the identification, recognition, and grouping of platform-based elements, serving as the milestone for effectively enhancing the density of platform-related actions. This, in turn, acts as a multiplier for interactions and information flows among actors within the region, which are empowered through the following phases, increasing regional capabilities.
Phase 4 denotes the comprehension of the connections among different platform elements and the increasing gap between them. Following this phase, a region can grasp the interrelationships among diverse platform elements and discern their potential interactions. Previous studies highlight the importance of combining diverse types of platforms to maximize their impact on regional decision-making and value creation [68,69,70]. For instance, online discussion forums alone can serve to gather information on regional stakeholder perspectives regarding a proposed action. However, when integrated with visualization tools, additional latent information can be extracted, signaling a close connection between these platform elements [69].
Finally, Phase 5 pertains to the acquisition of skills necessary to perceive an entire sequence of actions as a unified entity. This skill is particularly demanding, requiring a comprehensive understanding of the various levels of functioning not only within a specific platform but also across different platforms. Understanding the complexities of how these platforms interact and influence each other becomes crucial at this stage, marking a sophisticated level of proficiency in navigating the intricate landscape of interconnected digital systems. This holistic comprehension allows regions to optimize their use of diverse platforms, leveraging them synergistically to achieve overarching goals and outcomes. Examples related to Phase 5 might include the development and integration of a holistic framework for implementing life cycle sustainability assessment of regional bioeconomy [71], the design and implementation of smart specialization strategies [60,72], and the implementation of smart city services [73,74]. This holistic approach involves perceiving the entire sequence—from gathering information to decision-making and implementation—as a cohesive and interconnected process. By understanding the synergies between these different platforms, the region can effectively navigate the complexities of diverse digital systems, maximizing the impact of their actions and fostering a more streamlined and efficient decision-making processes.
A specific example of how platforms integrate throughout the regional learning process is illustrated in Figure 3. Six distinct platforms have been selected to demonstrate how they combine and interact within the overall framework for identifying new regional developmental paths. Initially, regions learn to recognize relevant platforms that offer essential information for uncovering potential new directions. Next, they categorize these platforms based on their specific functions (e.g., regional context analysis, data provision, and ecosystem development). By leveraging the links and sequences between them, regions can better understand and benefit from the information flows that emerge throughout the process.
When examining our example in detail, the process of identifying the broader regional context begins with the integration of the S3 Observatory (S3O) and Knowledge4Policy (K4P) platforms. These platforms are instrumental in mapping out existing regional priorities by aggregating key knowledge produced by previous studies and projects, thus providing a comprehensive foundation for understanding the region’s historical and current developmental landscape. Building on this foundation, the framework is further enriched with specific datasets from the ARDECO and KOHESIO platforms. These data sources offer targeted insights that not only validate initial findings but also highlight potential developmental opportunities through a more granular analysis of regional trends and needs. Finally, the S3 Thematic Platforms (S3TP) and RIS3 One Stop Liaison Office (OLSO) facilitate the creation of targeted regional ecosystems by establishing synergies among a diverse array of actors and stakeholders. By connecting government bodies, industry leaders, research institutions, and community groups, these platforms help to foster collaborative networks that are essential for driving sustainable innovation and growth throughout the region.
Continuous feedback mechanisms play a crucial role in ensuring the effectiveness of this integration. Regions must assess the efficiency of platform interactions by monitoring engagement levels, tracking data flows, and evaluating the impact of decisions informed by these platforms. This iterative process allows for adjustments and refinements, ensuring that platforms remain relevant and responsive to regional needs over time. However, several challenges may arise in this process. Differences in data formats and interoperability between platforms can complicate integration, requiring technical solutions to streamline information exchange. Additionally, varying levels of digital maturity among regional stakeholders may create barriers to the effective adoption and utilization of these tools. Aligning multiple actors with diverse interests also presents a challenge, necessitating well-structured governance mechanisms to facilitate collaboration. Despite these challenges, successful implementation of platform integration can yield significant benefits. Case studies from EU initiatives highlight instances where data-driven decision-making and collaborative ecosystems have accelerated regional development, showcasing the transformative potential of platform-based regional learning processes [22,75,76].

6. Conclusions

This study highlights the multifaceted role of platforms in shaping regional development through proximity emergence. It emphasizes the interconnected dynamic processes influencing various spatial forms and the crucial role of regional capacity for proximity emergence. Technological integration, including artificial and collective intelligence, is identified as a key driver, enhancing knowledge production, diffusion, and accumulation. In this framework, platforms are positioned as crucial proximity enablers, creating connected digital spaces that enhance interactions and information flows among diverse actors.
The pivotal role of platforms in shaping regional capabilities is also highlighted through their ability to enhance connectivity among diverse agents, emphasizing the need to explore factors connecting agents and digital components within platforms to gain a comprehensive understanding of the mechanisms driving regional processes. Various forms of connectivity are discussed, including physical, social, organizational, institutional, and cognitive proximity, with platforms impacting them by creating new links or enhancing existing ones. In this context, platforms are portrayed as digital renditions of physical infrastructures, acting as hubs that aggregate assets, creating interconnected economies and generating network effects.
The paper also discusses the intersection of routines and platforms, emphasizing how routines, defined as interconnected actions performed by various agents, play a crucial role in regional organization and adaptation. Routines serve as organizational learning mechanisms, embedding knowledge and capabilities essential for adapting to innovations. The effectiveness of routines is influenced by shared social, cognitive, institutional, and organizational structures, fostering proximity. Platforms, with their repetitive nature, provide an opportunity to replicate or enhance routines, transforming them digitally.
The transferability potential of routines onto platforms is classified into four types: fully transferable, semi-transferable, non-transferable, and new routines. Platforms, acting as digital renditions of physical infrastructures, influence routine types, leading to new opportunities in proximity. The connection between platforms and routines is further explored by dissecting processes like product innovation and smart specialization strategy into sub-routines. Platforms, through digital tools, transform and enhance these routines, introducing challenges related to organizational optimization, co-design, collaboration, information sharing, and knowledge diffusion.
Given that platforms emerge as transformative elements influencing routine types and enhancing regional capabilities, this study argues that there are five discrete phases for effectively integrating platforms into the regional context. The outlined phases represent a developmental trajectory that equips regions with the skills and insights necessary to harness the power of platforms effectively towards enhancing their capabilities for proximity emergence. The progression from a basic understanding in Phase 1 to a sophisticated comprehension in Phase 5 is transformative. As regions evolve through these phases, they gain the ability to identify patterns, categorize elements, and understand the intricate relationships across various platforms. This heightened awareness empowers regions to strategically utilize platform-based tools for specific purposes, optimizing outcomes and fostering a more conscious approach to decision-making. The regional ability to produce proximity effects through platforms lies in the adept navigation and integration of these digital tools, creating a synergistic environment where interactions, links, and information flows among actors are boosted with data-driven insights, enhancing overall regional development. By intertwining this platform proficiency with the development of routines, regions establish a dynamic framework for consistently generating proximity effects, transforming platforms into key drivers that shape regional habits, practices, and collaborative endeavors. This symbiotic relationship between platform utilization and routine development reinforces the regional capacity to adapt, innovate, and thrive in an increasingly connected landscape.
Despite the progressive phases outlined in understanding and utilizing platforms, several potential barriers can impede the seamless integration of these tools into regional processes, particularly in underdeveloped areas where growth is nonlinear. One notable challenge is the resistance to change, where individuals or regions may be reluctant to adopt new technologies and adjust established routines. Additionally, there could be disparities in digital literacy and technological infrastructure across regions, hindering equal access and utilization, limiting the benefits of platform-based development. The complexity of platform interactions further complicates adoption, especially in advanced stages where coordinating actions across multiple platforms requires specialized knowledge. Privacy concerns and cybersecurity issues also pose significant challenges, with the need to balance openness and transparency against the protection of sensitive information. Environmental challenges must also be considered. The widespread adoption of digital platforms relies on hardware that depends on critical resource minerals (CRMs), which are often extracted through environmentally damaging processes. For underdeveloped regions, this raises concerns about long-term sustainability, as reliance on imported technology can create dependencies while also exacerbating environmental harm. Effective platform integration requires addressing these barriers, acknowledging diverse levels of technological readiness, and implementing strategies to ensure inclusivity, security, and the environmental impact of technology expansion.
Future research in this domain could delve into the development of advanced algorithms and artificial intelligence systems to automate the identification of recurring patterns and relationships among platform elements, easing the burden on regions during Phase 2 and Phase 3. Exploring strategies to enhance digital literacy and bridge technological disparities among regions would be crucial to ensure equitable participation in platform-based processes. Investigating the ethical dimensions of platform utilization, including privacy preservation and data security, could provide valuable insights into the responsible deployment of these technologies. Furthermore, understanding the dynamics of cross-platform interactions in Phase 5 and developing frameworks for seamless integration could be a promising avenue for research. Additionally, exploring the long-term impacts of regional platform adoption on governance structures, community dynamics, and decision-making processes would contribute to a more comprehensive understanding of the implications and outcomes associated with the increasing reliance on digital platforms.

Funding

This research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Rodríguez-Pose, A. The Revenge of the Places That Don’t Matter (and What to Do about It). Camb. J. Reg. Econ. Soc. 2018, 11, 189–209. [Google Scholar] [CrossRef]
  2. Iammarino, S.; Rodriguez-Pose, A.; Storper, M. Regional Inequality in Europe: Evidence, Theory and Policy Implications. J. Econ. Geogr. 2019, 19, 273–298. [Google Scholar] [CrossRef]
  3. de la Roca, J.; Puga, D. Learning by Working in Big Cities. Rev. Econ. Stud. 2017, 84, 106–142. [Google Scholar] [CrossRef]
  4. Capello, R. Space, Growth and Development: A Historical Perspective and Recent Advances. A Historical Perspective and Recent Advances. In Handbook of Regional Growth and Development Theories: Revised and Extended Second Edition; Edward Elgar Publishing Ltd.: Cheltenham, UK, 2019; pp. 24–47. [Google Scholar] [CrossRef]
  5. Kemeny, T.; Storper, M. Superstar Cities and Left-Behind Places: Disruptive Innovation, Labor Demand, and Interregional Inequality; International Inequalities Institute, London School of Economics and Political Science: London, UK, 2020. [Google Scholar]
  6. Boschma, R.A. Proximity and Innovation: A Critical Assessment. Reg. Stud. 2005, 39, 61–74. [Google Scholar] [CrossRef]
  7. Balland, P.A.; Boschma, R.; Frenken, K. Proximity and Innovation: From Statics to Dynamics. Reg. Stud. 2015, 49, 907–920. [Google Scholar] [CrossRef]
  8. Fitjar, R.D.; Rodríguez-Pose, A. Innovating in the Periphery: Firms, Values and Innovation in Southwest Norway. Eur. Plan. Stud. 2011, 19, 555–574. [Google Scholar] [CrossRef]
  9. Radosevic, S.; Curaj, A.; Gheorghiu, R.; Andreescu, L.; Wade, I. Advances in the Theory of Smart Specialization; Academic Press: London, UK, 2017. [Google Scholar]
  10. Frenken, K.; Vaskelainen, T.; Fünfschilling, L.; Piscicelli, L. An Institutional Logics Perspective on the Gig Economy. Res. Sociol. Organ. 2020, 66, 83–105. [Google Scholar] [CrossRef]
  11. van Dijck, J.; Poell, T.; de Waal, M. The Platform Society; Oxford University Press: New York, NY, USA, 2018; Volume 1. [Google Scholar] [CrossRef]
  12. Panori, A. Digitally Disrupted Space: Proximity and New Development Opportunities for Regions and Cities; Elsevier: Amsterdam, The Netherlands, 2024. [Google Scholar]
  13. Panori, A.; Kakderi, C.; Komninos, N.; Fellnhofer, K.; Reid, A.; Mora, L. Smart Systems of Innovation for Smart Places: Challenges in Deploying Digital Platforms for Co-Creation and Data-Intelligence. Land Use Policy 2021, 111, 104631. [Google Scholar] [CrossRef]
  14. Kenney, M.; Zysman, J. The Platform Economy: Restructuring the Space of Capitalist Accumulation. Camb. J. Reg. Econ. Soc. 2020, 13, 55–76. [Google Scholar] [CrossRef]
  15. Feldman, M.; Guy, F.; Iammarino, S. Regional Income Disparities, Monopoly and Finance. Camb. J. Reg. Econ. Soc. 2021, 14, 25–49. [Google Scholar] [CrossRef]
  16. Komninos, N.; Panori, A. The Creation of City Smartness: Architectures of Intelligence in Smart Cities and Smart Ecosystems. In Smart Cities in the Post-Algorithmic Era: Integrating Technologies, Platforms and Governance; Edward Elgar Publishing Ltd.: Cheltenham, UK, 2019; pp. 101–127. [Google Scholar] [CrossRef]
  17. Capello, R. Indivisibilities, Synergy and Proximity: The Need for An Integrated Approach to Agglomeration Economies. Tijdschr. Econ. Soc. Geogr. 2009, 100, 145–159. [Google Scholar] [CrossRef]
  18. Panori, A. Platforms Enhancing Proximity in the Digital Era. Platforms 2024, 2, 1–14. [Google Scholar] [CrossRef]
  19. Humphrey, N. The Social Function of Intellect. In Growing Points in Ethology; Cambridge University Press: Cambridge, UK, 1976; pp. 303–317. [Google Scholar]
  20. Antonelli, G.; Cappiello, G. Smart Development in Smart Communities. In Smart Development in Smart Communities; Taylor & Francis: London, UK, 2016; pp. 1–324. [Google Scholar] [CrossRef]
  21. Giovannella, C. “Territorial Smartness” and Emergent Behaviors. In Proceedings of the 2013 2nd International Conference on Systems and Computer Science (ICSCS 2013), Villeneuve d’Ascq, France, 26–27 August 2013; pp. 170–176. [Google Scholar] [CrossRef]
  22. Panori, A. Fostering Regional Intelligence from the Ground up: A Selection of Case Studies from EU Projects. Discov. Sustain. 2024, 5, 407. [Google Scholar] [CrossRef]
  23. Komninos, N.; Musyck, B.; Reid, A.I. Smart Specialisation Strategies in South Europe during Crisis. Eur. J. Innov. Manag. 2014, 17, 448–471. [Google Scholar] [CrossRef]
  24. Capello, R.; Kroll, H. From Theory to Practice in Smart Specialization Strategy: Emerging Limits and Possible Future Trajectories. In Regional Innovation Strategies 3 (RIS3); Routledge: London, UK, 2018; pp. 1–14. [Google Scholar] [CrossRef]
  25. Qi, G.J.; Aggarwal, C.C.; Han, J.; Huang, T. Mining Collective Intelligence in Diverse Groups. In Proceedings of the WWW 2013—Proceedings of the 22nd International Conference on World Wide Web, Rio de Janeiro, Brazil, 13–17 May 2013; pp. 1041–1051. [Google Scholar] [CrossRef]
  26. Anttiroiko, A. City-as-a-Platform: The Rise of Participatory Innovation Platforms in Finnish Cities. Sustainability 2016, 8, 922. [Google Scholar] [CrossRef]
  27. Quatraro, F.; Usai, S. Knowledge Flows, Externalities and Innovation Networks. Reg. Stud. 2017, 51, 1133–1137. [Google Scholar] [CrossRef]
  28. Kakderi, C.; Komninos, N.; Panori, A.; Psaltoglou, A. Smart Specialisation 2.0: Driving Public Funds towards Platforms and Ecosystems. In New Metropolitan Perspectives; Smart Innovation, Systems and Technologies (SIST); Springer: Cham, Switzerland, 2020; Volume 177 SIST, pp. 68–79. [Google Scholar] [CrossRef]
  29. Dickel, S.; Ferdinand, J.-P.; Petschow, U. The Multiple Applications of 3D Printing: Between Maker Movements and the Future of Manufacturing. In The Decentralized and Networked Future of Value Creation; Springer: Cham, Switzerland, 2016; pp. 9–26. [Google Scholar] [CrossRef]
  30. Parker, G.G.; Van Alstyne, M.W.; Choudary, S.P. Platform Revolution: How Networked Markets Are Transforming the Economy—And How to Make Them Work for You; WW Norton & Company: New York, NY, USA, 2017; p. 336. [Google Scholar]
  31. Komninos, N. Smart Cities and Connected Intelligence: Platforms, Ecosystems and Network Effects. In Smart Cities and Connected Intelligence: Platforms, Ecosystems and Network Effects; Routledge: London, UK, 2019; pp. 1–280. [Google Scholar] [CrossRef]
  32. Gui, Q.; Liu, C.; Du, D. International Knowledge Flows and the Role of Proximity. Growth Change 2018, 49, 532–547. [Google Scholar] [CrossRef]
  33. Glaeser, E.L.; Hausman, N. The Spatial Mismatch between Innovation and Joblessness. Innov. Policy Econ. 2020, 20, 233–299. [Google Scholar] [CrossRef]
  34. Faggian, A.; Modrego, F.; Mccann, P. Human Capital and Regional Development. In Handbook of Regional Growth and Development Theories: Revised and Extended Second Edition; Edward Elgar Publishing Ltd.: Cheltenham, UK, 2019; pp. 149–171. [Google Scholar] [CrossRef]
  35. Venables, A.J. Shifts in Economic Geography and Their Causes; London School of Economics and Political Science, Centre for Economic Performance: London, UK, 2006. [Google Scholar]
  36. Gurrutxaga, M. Visualizing the Rural Population Growth in Spain during 2020 Triggered by the Covid-19 Pandemic. Reg. Stud. Reg. Sci. 2021, 8, 305–307. [Google Scholar] [CrossRef]
  37. Mariotti, I.; Marino, M.D.; Akhavan, M.; Capdevila, I. The Effects of COVID-19 on Coworking Spaces. In Handbook of Labor, Human Resources and Population Economics; Springer: Cham, Switzerland, 2022. [Google Scholar] [CrossRef]
  38. Srnicek, N. Platform Capatlism; John Wiley & Sons: Hoboken, NJ, USA, 2017; pp. 1–170. [Google Scholar]
  39. Pershina, R.; Soppe, B.; Thune, T.M. Bridging Analog and Digital Expertise: Cross-Domain Collaboration and Boundary-Spanning Tools in the Creation of Digital Innovation. Res. Policy 2019, 48, 103819. [Google Scholar] [CrossRef]
  40. Dallasega, P.; Rauch, E.; Linder, C. Industry 4.0 as an Enabler of Proximity for Construction Supply Chains: A Systematic Literature Review. Comput. Ind. 2018, 99, 205–225. [Google Scholar] [CrossRef]
  41. Janssen, M.; van der Voort, H. Adaptive Governance: Towards a Stable, Accountable and Responsive Government. Gov. Inf. Q. 2016, 33, 1–5. [Google Scholar] [CrossRef]
  42. Papadimitropoulos, E. Platform Capitalism, Platform Cooperativism, and the Commons. Rethink. Marx. 2021, 33, 246–262. [Google Scholar] [CrossRef]
  43. Komninos, N.; Kakderi, C.; Collado, A.; Papadaki, I.; Panori, A. Digital Transformation of City Ecosystems: Platforms Shaping Engagement and Externalities across Vertical Markets. In Sustainable Smart City Transitions; Routledge: London, UK, 2022; pp. 91–112. [Google Scholar] [CrossRef]
  44. Zhang, C.B.; Li, Y.N.; Wu, B.; Li, D.J. How WeChat Can Retain Users: Roles of Network Externalities, Social Interaction Ties, and Perceived Values in Building Continuance Intention. Comput. Hum. Behav. 2017, 69, 284–293. [Google Scholar] [CrossRef]
  45. Balland, P.A.; De Vaan, M.; Boschma, R. The Dynamics of Interfirm Networks along the Industry Life Cycle: The Case of the Global Video Game Industry, 1987–2007. J. Econ. Geogr. 2013, 13, 741–765. [Google Scholar] [CrossRef]
  46. Hinnosaar, M.; Hinnosaar, T.; Kummer, M.E.; Slivko, O. Externalities in Knowledge Production: Evidence from a Randomized Field Experiment. Exp. Econ. 2022, 25, 706–733. [Google Scholar] [CrossRef]
  47. Yuan, Y.C.; Fulk, J.; Monge, P.R. Access to Information in Connective and Communal Transactive Memory Systems. Commun. Res. 2007, 34, 131–155. [Google Scholar] [CrossRef]
  48. Zhang, S.; Chen, J.; Wen, Y.; Chen, H.; Gao, Q.; Wang, Q. Capturing Regulatory Patterns in Online Collaborative Learning: A Network Analytic Approach. Int. J. Comput.-Support. Collab. Learn. 2021, 16, 37–66. [Google Scholar] [CrossRef]
  49. Feldman, M.S.; Pentland, B.T. Reconceptualizing Organizational Routines as a Source of Flexibility and Change. Adm. Sci. Q. 2003, 48, 94. [Google Scholar] [CrossRef]
  50. Bourdieu, P. Outline of a Theory of Practice. In The New Social Theory Reader; Routledge: London, UK, 2020; pp. 80–86. [Google Scholar] [CrossRef]
  51. Nelson, R.; Winter, S. Organizational Capabilities and Behavior. In An Evolutionary Theory of Economic Change; Harvard University Press: Cambridge, MA, USA, 1982; pp. 96–135. [Google Scholar]
  52. Argote, L. Organizational Learning: Creating, Retaining and Transferring Knowledge. In Organizational Learning: Creating, Retaining and Transferring Knowledge; Springer: New York, NY, USA, 2013; pp. 1–217. [Google Scholar] [CrossRef]
  53. Becker, M.C.; Lazaric, N.; Nelson, R.R.; Winter, S.G. Applying Organizational Routines in Understanding Organizational Change. Ind. Corp. Change 2005, 14, 775–791. [Google Scholar] [CrossRef]
  54. Carrincazeaux, C.; Lung, Y.; Rallet, A. Proximity and Localisation of Corporate R&D Activities. Res. Policy 2001, 30, 777–789. [Google Scholar] [CrossRef]
  55. Dosi, G.; Faillo, M.; Marengo, L. Organizational Capabilities, Patterns of Knowledge Accumulation and Governance Structures in Business Firms: An Introduction; LEM Papers Series; Scuola Superiore Sant’Anna; Laboratory of Economics and Management (LEM): Pisa, Italy, 2003. [Google Scholar]
  56. Östbring, L.; Eriksson, R.; Lindgren, U. Labour Mobility and Organisational Proximity: Routines as Supporting Mechanisms for Variety, Skill Integration and Productivity. Ind. Innov. 2017, 24, 775–794. [Google Scholar] [CrossRef]
  57. Godoe, H. Innovation Regimes, R&D and Radical Innovations in Telecommunications. Res. Policy 2000, 29, 1033–1046. [Google Scholar] [CrossRef]
  58. Jaruzelski, B.; Loehr, J.; Holman, R. Navigating the Digital Future Booz & Company’s Annual Study of R&D Spending Reveals the Tools That Are Transforming Innovation-from Customer Insight to Product Launch; Booz & Company: Chicago, IL, USA, 2013. [Google Scholar]
  59. Panori, A.; Kakderi, C.; Dimitriadis, I. Combining Technological Relatedness and Sectoral Specialization for Improving Prioritization in Smart Specialisation. Reg. Stud. 2022, 56, 1454–1467. [Google Scholar] [CrossRef]
  60. Panori, A.; Angelidou, M.; Mora, L.; Reid, A.; Sefertzi, E. Online Platforms for Smart Specialisation Strategies and Smart Growth. 2018. Available online: https://napier-repository.worktribe.com/output/1253993 (accessed on 3 December 2024).
  61. Gruzd, A.; Haythornthwaite, C. Enabling Community through Social Media. J. Med. Internet. Res. 2013, 15, e2796. [Google Scholar] [CrossRef]
  62. Matthews, P. Social Media, Community Development and Social Capital. Community Dev. J. 2016, 51, 419–435. [Google Scholar] [CrossRef]
  63. Repette, P.; Sabatini-Marques, J.; Yigitcanlar, T.; Sell, D.; Costa, E. The Evolution of City-as-a-Platform: Smart Urban Development Governance with Collective Knowledge-Based Platform Urbanism. Land 2021, 10, 33. [Google Scholar] [CrossRef]
  64. Katmada, A.; Katsavounidou, G.; Kakderi, C. Platform Urbanism for Sustainability. In Distributed, Ambient and Pervasive Interactions; Lecture Notes in Computer Science; Springer: Cham, Switzerland, 2023; Volume 14037, pp. 35–52. [Google Scholar] [CrossRef]
  65. Porwol, L.; Ojo, A.; Breslin, J.G. Social Software Infrastructure for E-Participation. Gov. Inf. Q. 2018, 35, S88–S98. [Google Scholar] [CrossRef]
  66. Toots, M. Why E-Participation Systems Fail: The Case of Estonia’s Osale.Ee. Gov. Inf. Q. 2019, 36, 546–559. [Google Scholar] [CrossRef]
  67. Simonofski, A.; Fink, J.; Burnay, C. Supporting Policy-Making with Social Media and e-Participation Platforms Data: A Policy Analytics Framework. Gov. Inf. Q. 2021, 38, 101590. [Google Scholar] [CrossRef]
  68. Hagen, L. Content Analysis of E-Petitions with Topic Modeling: How to Train and Evaluate LDA Models? Inf. Process. Manag. 2018, 54, 1292–1307. [Google Scholar] [CrossRef]
  69. Hagen, L.; Keller, T.E.; Yerden, X.; Luna-Reyes, L.F. Open Data Visualizations and Analytics as Tools for Policy-Making. Gov. Inf. Q. 2019, 36, 101387. [Google Scholar] [CrossRef]
  70. Matheus, R.; Janssen, M.; Maheshwari, D. Data Science Empowering the Public: Data-Driven Dashboards for Transparent and Accountable Decision-Making in Smart Cities. Gov. Inf. Q. 2020, 37, 101284. [Google Scholar] [CrossRef]
  71. Zeug, W.; Bezama, A.; Thrän, D. A Framework for Implementing Holistic and Integrated Life Cycle Sustainability Assessment of Regional Bioeconomy. Int. J. Life Cycle Assess. 2021, 26, 1998–2023. [Google Scholar] [CrossRef]
  72. Cohen, C. Reflections Guiding Smart Specialisation Strategies Impact Assessment; JRC Research Reports; Publications Office of the European Union: Luxembourg, 2021. [Google Scholar]
  73. Larrinaga, F.; Pérez, A.; Aldalur, I.; Hernández, J.L.; Izkara, J.L.; de Viteri, P.S. A Holistic and Interoperable Approach towards the Implementation of Services for the Digital Transformation of Smart Cities: The Case of Vitoria-Gasteiz (Spain). Sensors 2021, 21, 8061. [Google Scholar] [CrossRef]
  74. Komninos, N.; Kakderi, C.; Mora, L.; Panori, A.; Sefertzi, E. Towards High Impact Smart Cities: A Universal Architecture Based on Connected Intelligence Spaces. J. Knowl. Econ. 2022, 13, 1169–1197. [Google Scholar] [CrossRef]
  75. Schaffers, H. Shaping Ecosystems for Collaborative Innovation towards Fostering Urban and Regional Development. In Smart Cities in the Post-Algorithmic Era: Integrating Technologies, Platforms and Governance; Edward Elgar Publishing Ltd.: Cheltenham, UK, 2019; pp. 70–100. [Google Scholar] [CrossRef]
  76. Liva, G.; Micheli, M.; Schade, S.; Kotsev, A.; Gori, M.; Codagnone, C. City Data Ecosystems between Theory and Practice: A Qualitative Exploratory Study in Seven European Cities. Data Policy 2023, 5, e17. [Google Scholar] [CrossRef]
Figure 1. Various routine types based on their transferability potential.
Figure 1. Various routine types based on their transferability potential.
Platforms 03 00004 g001
Figure 2. Regional learning process for embedding platforms in their developmental paths towards enhancing proximity.
Figure 2. Regional learning process for embedding platforms in their developmental paths towards enhancing proximity.
Platforms 03 00004 g002
Figure 3. Example of regional learning process based on EU platforms developed for enhancing innovation and productivity. Note: S3O—S3 Observatory (https://ec.europa.eu/regional_policy/assets/s3-observatory/index_en.html); K4P—Knowledge4Policy Platform (https://knowledge4policy.ec.europa.eu/home_en); ARDECO—ARDECO Dataset (https://urban.jrc.ec.europa.eu/ardeco/explorer?lng=en); KOHESIO—KOHESIO Dataset (https://kohesio.ec.europa.eu/en/); S3TP—S3 Thematic Platforms (https://ec.europa.eu/regional_policy/policy/communities-and-networks/s3-community-of-practice/thematic_platforms_en); OSLO—RIS3 One Stop Liaison Office for Region of Central Macedonia (https://www.ris3rcm.eu/en/).
Figure 3. Example of regional learning process based on EU platforms developed for enhancing innovation and productivity. Note: S3O—S3 Observatory (https://ec.europa.eu/regional_policy/assets/s3-observatory/index_en.html); K4P—Knowledge4Policy Platform (https://knowledge4policy.ec.europa.eu/home_en); ARDECO—ARDECO Dataset (https://urban.jrc.ec.europa.eu/ardeco/explorer?lng=en); KOHESIO—KOHESIO Dataset (https://kohesio.ec.europa.eu/en/); S3TP—S3 Thematic Platforms (https://ec.europa.eu/regional_policy/policy/communities-and-networks/s3-community-of-practice/thematic_platforms_en); OSLO—RIS3 One Stop Liaison Office for Region of Central Macedonia (https://www.ris3rcm.eu/en/).
Platforms 03 00004 g003
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Panori, A. Platforms as Proximity Enablers for Regional Development. Platforms 2025, 3, 4. https://doi.org/10.3390/platforms3010004

AMA Style

Panori A. Platforms as Proximity Enablers for Regional Development. Platforms. 2025; 3(1):4. https://doi.org/10.3390/platforms3010004

Chicago/Turabian Style

Panori, Anastasia. 2025. "Platforms as Proximity Enablers for Regional Development" Platforms 3, no. 1: 4. https://doi.org/10.3390/platforms3010004

APA Style

Panori, A. (2025). Platforms as Proximity Enablers for Regional Development. Platforms, 3(1), 4. https://doi.org/10.3390/platforms3010004

Article Metrics

Back to TopTop