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Article

An Anticipatory Practice for the Future of Science Parks: Understanding the Indices and Mechanisms on Different Spatial Scales of Regional Innovation Systems

by
Ssu-Chi Pan
1,
Peilei Fan
2,
Tai-Shan Hu
1,*,
Han-Yu Li
1 and
Wen-Shin Liu
1
1
Department of Urban Planning, National Cheng Kung University, Tainan 701, Taiwan
2
Department of Urban and Environmental Planning and Policy, Tufts University, Medford, MA 02155, USA
*
Author to whom correspondence should be addressed.
Sustainability 2024, 16(11), 4600; https://doi.org/10.3390/su16114600
Submission received: 27 March 2024 / Revised: 22 May 2024 / Accepted: 25 May 2024 / Published: 29 May 2024
(This article belongs to the Section Environmental Sustainability and Applications)
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Abstract

:
To construct a diverse anticipatory practice for the future of science parks, this work gives a systematic understanding of the effect of the regional background on the benefit of science parks, and of the synergy of the elements of the innovation system, which contains a space dimension and regional differences, and represents the unique characteristics of the regional environment at various geographic scales. This work examines the function and effect of different geographic scales on the conditions required for the evolution of science parks based on regional innovation systems. The research analyzes the implications of the development of science parks through different spatial scales from the perspective of the regional innovation system. The function of innovation in the Hsinchu and Southern Taiwan Science Parks is examined by comparing the two parks, confirming the effect of different regional backgrounds on the benefit of the science parks.

1. Introduction

Innovation and knowledge-oriented ability have become the most critical factors in sustainable competitiveness and society’s sustainability, including resource and energy problems and climate change [1]. The development of science parks is the most prevalent policy to encourage innovation [2,3], but it might not be able to promote industrial upgrades or technology rooting when facing innovation and globalization by high-tech industries. Innovation systems provide a valuable framework for evaluating policy related to the economy across extensive innovation regions [4]. The theory of the innovation system takes the innovation process as a whole and incorporates decision factors, origins, start-ups, social capital, and policies for further discussion [5]. The interactions between these factors are crucial because they promote innovation in innovation systems [6]. Regional innovation systems offer a channel of connection between the regional economy and innovation interaction [7]. Regional innovation systems consider innovation as a process of interaction among participants, including companies, universities and research institutes, regulatory institutes, intermediaries, policymakers, and financial institutions [8]. Such interactions enhance understanding of conditions for innovation benefits of science parks [9].
Scholars formerly believed that the evolution of science parks, as well as the innovation system, were affected by a multidimensional set of factors [10,11,12]. Nevertheless, from the perspective of the regional innovation system, most studies disregarded a synergistic effect of the innovation system across different dimensions and scales of interaction, which represented the unique features of the environment on geographic scales. These features contribute to the future development of science parks and even act as a potential for the redevelopment or transformation of science parks [12].
Consequently, this study examines the conditions of innovation necessary for developing science parks based on the theory of the regional innovation system. After establishing the indices and screening analytic hierarchy process (AHP) surveys, this study compares the evolution of Hsinchu Science Park and Southern Taiwan Science Park and further elucidates the role of innovation in the two parks. Additionally, an empirical study is carried out to identify the effect of the different backgrounds of the two parks on the benefit of the parks, and proposes anticipatory practices for future development and improvement of the science parks accordingly (Figure 1). Details of the research are summarized as follows.
  • Examine the functions and impacts of the conditions required for the evolution of science parks at different geographic scales from the perspective of the regional innovation system.
  • Explore the current development status of the science parks and propose improvement plans as well as anticipatory practices for the future development of science parks.

2. Literature Analysis

2.1. The Regional Backgrounds and Innovation Theory for the Development of Science Parks

A science park is generally described as a research-oriented cluster that gathers companies in one physical location. Based on the support of infrastructure, science parks improve knowledge exchange between enterprises or between enterprises and universities through innovation and further promote regional economic development [2]. Innovation originates from the interactions between universities depending on the regional background and government policy [2,11]. According to Poonjan and Tanner [2], the importance of science parks varies with region and time when evaluating the parks by outcomes such as patents and startups. Similarly, fundamental changes in the evolution of science and technology, economic, innovation and socio-ecological systems call for the building of a tool to cope with nonlinear, complex systems developing in rapidly changing environments [12].
Our analysis of the benefit of science parks that incorporates the regional background is inspired by the literature associated with territorial innovation models (TIMs). A common feature of TIMs is the consideration of regional development as a regional endogenous procedure that combines economy, culture, and politics and treating regions as a competitive advantage [3]. Previous works on economic geography focusing on TIM endeavored to identify the regional driving force of innovation. In one of the TIMs examined by Moulaert and Sekia U [3], the regional innovation system (RIS) framework dealt with the connection between the regional economy and the ability to innovate [7]. The investigation clarified the factors that influence the benefit of science parks and their functioning mechanism.
The discussion on the impact of science parks from different perspectives has resulted in several theories. The investigation of the development of science parks can be categorized into the triple helix model, industrial cluster, and regional innovation systems. Etzkowitz and Leydesdorff [13] proposed the triple helix model, which focuses on dynamic analysis of the relationship between the government, industries, and academic institutes. However, the triple helix model does not investigate the authority and knowledge gaps, which are the critical factors in innovation, or the structural hole. Summarizing the concepts proposed by Luger [14], Giuliani [15], Muhammad, Ghafoor, and Naseer [16], an industrial cluster is a group of enterprises or institutes in a specified area, which is geographically adjacent or interconnected, with a supportive and collaborative but competitive relationship. The industrial cluster theory highlights the investigation of the reason that a specific industry gathers in a defined area. Namely, the unique phenomenon of a spatial cluster of industries is explained in terms of the process of building an industrial cluster in an area and the condition of the area. In RIS, which is the reference for innovation networks in some areas, the regional environment is a base or background to accomplish the generation or interaction of innovative institutes [17]. Namely, RIS considers the interacting and learning process among economic actors to help establish industrial innovation networks. In RIS, innovation is considered as an interactive procedure among participants, such as enterprises, universities and academic institutes, management organizations, science parks, policymakers, and financial institutions [8]. In addition to the core functions, RIS also strengthens technological innovation and completes infrastructure.
Based on a comprehensive understanding of the literature on the discussion of science parks, a summary of the references indicates the possible involvement of different resource allocations in the innovation process. Innovation is influenced by several factors, namely, the characteristics of enterprises (scale, technology, knowledge adsorption capacity, and learning ability), member structure (relevant enterprises and universities and academic institutes), interactions between organizations (culture, authority, and trust), spatial properties (cities, rural areas, and old industrial areas) and types of knowledge (tacit and explicit) [18]. Experts have recently begun to focus on the influence of external factors on the regional development of science parks [10,11,19]. However, few references have discussed the relationship between the benefits and the regional background of science parks [20]. Considering the processes over space and time is neither new nor unique [21], this investigation concludes that both the external connection to a region and the internal factors inside a science park contribute to the changes in the benefit and dynamics of science parks.

2.2. The Relationship between Science Parks and Regional Innovation Systems

An RIS is generally rooted in the regional environment and contains local features. It exhibits regional differences in the composition of innovative components and activities through participation in innovation activities offered by private or public organizations, e.g., companies, research institutes, tech-transfer offices, educational and training organizations, workplace mediation organizations, and funders. Ideally, various relationships exist in different RISs, enhancing knowledge exchange and floẉ, and promoting innovation in the systems and interactive learning [22].
The development of high-tech industry is strongly dependent on the properties of the RIS, including industrial diversity, the quality of knowledge and infrastructure, financial availability, technical talents, intensive communication networks, policies and acts, and regional institutes [23,24,25,26]. Science parks are regarded as hotbeds for technologies, as they incubate and develop high-tech startups and promote technology transfer from universities to companies [9]. Additionally, science parks help establish and institutionalize industrial clusters, integrating production, science, technology, education, and organizations on top of the existing regions. The function of regional innovation systems is to complete infrastructure, optimize an innovative environment, and further encourage the formation of industrial clusters, which helps in industrial development and innovation. Wasim [27] explored science parks in developed and developing economies to identify factors that could influence the planning of science parks and their growth, governance, and sustainability (Figure 2).
Most previous studies on science parks disregarded the dynamic connection between regional characteristics and demands when assessing the performance of science parks. Poonjan and Tanner [2] analyzed the performance of science parks combined with combined RISs, and presented five regional factors, namely, universities and research institutes, industrial structure, the environment of organizations, funding support, and urbanization. The research demonstrated the influence of these factors on the performance of science parks and proposed increasing the accomplishment of science parks while considering regional features and demands. A comprehensive understanding of the dynamic connection between these regions can improve the design of science parks and enhance their development and performance. Tsamis [28] discussed support systems associated with tech-transfer collaboration and entrepreneurship as a background factor that strongly influences science parks. The factor provides local resources to attract regular tenants and offers local markets to startups. Comins and Rowe [29] concluded that the most successful science parks are generally located in urbanized, diversified, and mature developed economies due to the strong research background, company culture, active entrepreneurial spirit, and participation of universities and research institutes. Science parks offer various infrastructural supports for innovation and further consolidate the knowledge flow between enterprises, or between enterprises and universities, enhancing regional economic development [2].
From the perspective of the RIS, the anticipation is for science parks to innovate new technology and its applications through interactive networks spatially connected by industrial clusters. Even though scholars believed that complex factors influence the development of a science park, previous studies rarely addressed the background integration of science parks from the concept of spatial fields. Most studies neglected the synergy of the elements in innovation systems with the spatial dimension and regional differences. The variety of geographic scales that contain unique influences might support the future development of science parks, or even give potential for redevelopment and transformation. Nevertheless, the space planning and management of science parks is normally disconnected from the development of the surrounding areas. Previous studies scarcely considered different environmental fields when evaluating the indices that affect the development of science parks. The viewpoint of environmental fields must be considered in order to assist city administrators, planners, and designers in planning and making strategies for future urban development.

2.3. The Functions of the Elements of Innovation Systems in Each Space Dimension

In the era of the knowledge economy, scholars need to explore the characteristics of a city at different geographic scales and establish a conceptual framework for multidimensional and multiscale urban quality to attract and retain knowledge-intensive talents and industries [30,31,32]. Categorizing quality indicators, such as region, city, and cluster scales, and examining how these measures are correlated at different geographic scales as well as how they influence an urban area’s operation are also critical (Figure 3). Environment, economy, society, and individual were considered at different levels. First, the competitiveness of the capital system was emphasized at regional levels from the perspective of regional development. This competitiveness integrates environment, knowledge, financial institutes, society, culture, human resources, and identity capital, and thus, represents intangible assets and the power of a region to attract talents and investment in the knowledge economy. Additionally, regarding the city-level indicators, better life quality of a city attracts knowledge-intensive talents and is a marketing tool for industry, including the natural environment, economy, society, and welfare. The urban space unit between regions and clusters, in response to city operation and policy planning, must meet the requirement of the economy with a diversity of talents and industries, society, and culture, and balance the developmental quality for the regions and clusters. The cluster level is the connection between enterprises and individuals. This indicator focuses on the individuals and local places, including tangible and intangible factors, and reveals gaps from the evolution of spatial features [33]. Moreover, clusters offer a competitive and collaborative environment among knowledge-intensive industries by gathering high-tech enterprises, bringing competitive advantage to a city or region. Consequently, the cluster-level factors are mostly about providing or establishing innovation spaces to stimulate knowledge-intensive employees.
Based on the literature review, this study examined the differences in environmental elements at various geographic scales [34]. This study believes that the framework helps promote multidimensional and multiscale thoughts about innovative vibes, and assists in understanding the regional demands of science parks at different geographic scales. This study integrated regional backgrounds of science parks and examined the industrial environment from the cluster viewpoint. This study presents three categories from different spatial scales, based on regional innovation theory at regional, city, and science park levels. Initially, the regional level creates a competitive environment. The city level then provides an attractive environment. Finally, the science park level consolidates the interactions between enterprises and talents. The indicators corresponding to these spatial levels are summarized in Figure 4. Previous studies have found the proposed spatial levels generate gaps in the development of science parks. The synergy among these indices is the main factor for the operation of innovation systems. This work identifies the gaps in geographic scales, discusses the depth and level of industrial integration from three different categories (region, city, and science park), and addresses an empirical study with differences in the development of science parks.

2.3.1. Region

Science parks are located worldwide in regions with great diversity and different regional environments. Some scholars believe that science parks contribute to new undeveloped systems [35,36,37], although others disagree with the evolution process [38]. Moreover, some studies assume that the size of a region is correlated with the contribution of a science park [39]. Finally, most cases demonstrate that public policies help develop science parks [40].
The reviewed literature suggests that government support and capital investment are indispensable for developing science parks [5,40,41]. Meanwhile, excessive public intervention with bureaucracy and strict controls inhibit the development of the parks, limiting the flexibility and innovative activities of science parks. Restated, policymakers need to attract high-quality human resources and financial capital when making policies. Such policies not only enhance the development of science parks but also trigger the economic evolution of a region [42].

2.3.2. City

Science parks help develop a city during a recession [19]. According to the literature, the location of a science park is vital for its successful development [43,44]. Regarding the locational conditions, life quality, livable and affordable residential areas, good educational environment, well-functioning transportation system, and cultural vibes attract companies and talents to science parks [45,46,47,48,49,50]. Consequently, many people consider cities or metropolitan areas as good locations for science parks [51]. This also explain why cities urge the development of science parks [47]. However, some believe to the contrary that science parks located in non-urban areas are also beneficial [39,47]. In conclusion, developers must consider the gaps between local policies and science parks and further evaluate the opportunities and restrictions in the future when developing science parks [52,53].

2.3.3. Science Parks

Overall, many studies have examined the features and properties of science parks. For instance, some experts indicated that more private-sector organizations participating in the ownership and governance of science parks was favorable for innovative activities [54,55]. Conversely, science parks led by the government would result in a well-functioning innovation system [55].
The different development periods and scales of science parks significantly influence the development of companies located in them [56,57]. Enterprises located in newer or older science parks have better development efficiency than those settled in middle-aged parks. Companies located in large science parks outperform those in small ones [37,58].
As for the management of science parks, the scale of the management team is positively correlated with the innovation efficiency of the companies [37]. In other words, the innovative actions of enterprises are crucial to the development of the parks [59,60]. Another series of investigations discovered that the financial, business, and innovative supports provided by science parks and the services and facilities offered by the networks are favorable for the innovation efficiency of the firms [61,62,63,64]. Organizations and companies consider the reputation of a science park as one of the main factors to consider [47,58]. Firms seek to benefit from the positive and remarkable reputation of science parks [65]. Even though no direct evidence shows any advantage brought by the positive reputation of science parks [66,67], relevant studies indicate the importance of the image of science parks to companies [47,68]. Recent related studies demonstrate that science parks enhance the well-being of employees by providing open spaces (green spaces) and encouraging employees to rest outdoors. This demarcation enables employees to psychologically distinguish working areas from leisure areas, thereby increasing creativity and innovation [69,70].

3. Materials and Methods

By analyzing relevant references about regional innovation systems and science parks, this study identified the impact of different geographic scales on the requirement for developing science parks. Based on the results of the literature review, this study identified the problems of interest. The factors and mechanisms required for developing science parks were significantly correlated with spatial levels and regions, in addition to regional backgrounds. Accordingly, this study evaluated the development of science parks from the perspective of the region, city, and science park (Appendix A). Moreover, a two-step questionnaire was dispatched to experts to evaluate the indicators for science park development. The Fuzzy Delphi Method was incorporated to screen the importance of each index in the first step. This step reviewed the adequacy of overall indicators and appropriately categorized indices into region, city, or science park. In the second stage, the weight of each item was estimated by the fuzzy AHP. In the last stage, the RISs of northern Taiwan (Hsinchu Science Park) and Southern Taiwan Science Park were compared and analyzed based on the evaluation system for the development of science parks established from the study and the weight of each index. The comparison and analysis displayed the regional backgrounds and the operation mechanisms that influenced the development efficiencies of the two science parks. The following describes the methods selected for the investigation.

3.1. Questionnaire for Experts

To build an evaluation system for indices that influence the development of science parks, this study first established an indicator framework on top of the literature. Experts in different positions and with various professional backgrounds might have different perspectives and emphases regarding the development planning for science parks. Hence, the study selected experts with professional backgrounds, relevant experience or research, and publications as the research subjects. Questionnaires were issued to a selection of 15 experts, composed of academic and research institutes (5 persons), public sector (2 persons), management unit of science parks (2 persons), companies from the Taiwan Science Park Association of Science and Industry (3 persons) and relevant advocacy groups (3 persons). Decisions and summaries were made based on the two-step questionnaire with expert participation from industry, government, academia, and different advocacy groups. This questionnaire is exempt from ethical review approval under the Human Subjects Research Act in Taiwan.
In the first stage, the Fuzzy Delphi Method was adopted to screen and establish indices. The design of the questionnaire enabled experts to evaluate every item by filling in acceptable minimum, optimal, and acceptable maximum values. Statistical analysis was undertaken for these values to establish the triangular fuzzy numbers. A gray zone test was further undertaken to review whether the experts reached a consensus. Meanwhile, revisions and amendments were made based on the suggestions proposed by the experts.
Continuing with the selected research subjects and following the first-step questionnaire, the FAHP was utilized to estimate the weight of each indicator in the second step. In the investigation, an interval from 1:7 to 7:1 was selected as the weight range for the comparison of each pair of factors. Experts had to score three values from the interval, namely, the optimal ratio and acceptable maximum and minimum values for the relative importance of every pair of indices. The triangular fuzzy numbers were defined according to the compared result of each pair. Last, the weight of each item was ranked by the results accumulated from the questionnaire, followed by analysis and discussion.

3.2. Empirical Analysis

After establishing an index system for indicators that influenced the development of science parks, a two-step survey was performed to assess and discuss the weights of the indices from the perspectives of regions, cities, and science parks. Based on the ranking of the weight of each indicator, the selected research subjects, the RISs of Hsinchu Science Park and Southern Taiwan Science Park, were compared using available data and references to validate the effect of regional backgrounds on the efficiency of the parks. Finally, some proposals were devised for the future development of science parks by analyzing the differences between the two innovation systems in northern (Hsinchu Science Park) and southern (Southern Taiwan Science Park) Taiwan.

4. Results

4.1. Empirical Analysis of the Questionnaires

This section discusses the regional, city, and science park levels in depth based on the results of the two-step questionnaire from 15 representatives, in response to the index framework established in this study to promote the innovation efficiency of science parks. A comprehensive analysis and comparison of the regional innovation systems of Hsinchu Science Park in northern Taiwan and Southern Taiwan Science Park in southern Taiwan were performed to verify the impact of each indicator on the parks. The transformation, upgrade, and future planning of science parks in Taiwan were proposed accordingly, based on the different developmental backgrounds of the two parks.

4.1.1. Regional Perspective

Regarding the Fuzzy Delphi Method applied in the first stage of the questionnaire, the expert consensus range (Hi) for the natural environment (5.48) type and physical environment (5.82) and spatial conditions (5.52) indices in the regional perspective did not achieve the threshold of the criteria, which was set to 6. The Hi < 6 reflected that experts disagreed with the hypothesis that environmental resources and natural landscapes affected the innovation development of science parks. Considering the geographic scope and relatively small territory of Taiwan, the different regions of Taiwan do not exhibit many differences in the external physical environment. Consequently, the regional perspective as an indicator to evaluate innovation development in science parks was not applicable.
According to the result from the second stage of the questionnaire, the FAHP, the weights for region and city perspectives among the indices that influenced the development of science parks were 0.3817 and 0.3791, respectively. Both exceeded the perspective of science parks, which was 0.2329. The results indicate that the formation and energy of innovation for science parks depended heavily on the resources of the surrounding areas and the production environment. Experts also agreed with the significance of the two indices, industrial environment (0.4761) and institutional environment (0.3103), in terms of the regional perspective. The results reveal that the management factors affecting company operation, decision, and efficiency are critical to the innovation development of the science parks. Moreover, participants in different RISs interact differently and contained regional characteristics when creating interfering measures or policies. Hence, to meet the requirements of science parks, this study proposes to consider regional differences when resource raising and making policies.

4.1.2. City Perspective

Regarding the city perspective, the results of the Fuzzy Delphi Method applied in the first step of the questionnaire indicate that the expert consensus range (Hi) did not reach the acceptance criteria of 6, for “land use” (5.65) and the corresponding indicator, “functional replacement of industrial zone” (5.32). According to the definition of land use in the study, urban land use and spatial morphology focused on the mixed development of functions, emphasized the compactness of innovative space and geographic proximity, and even supported the adjustment of land use for the industry. It reduced production costs, urged knowledge exchange, and promoted technical and industrial transformation. However, the experts reported relatively low results for the functional replacement of the industrial zone, suggesting that they considered it to be unimportant, because the different industrial districts, including science parks, were managed by various authorities and followed different laws and regulations in Taiwan. Some experts might answer the questionnaire directly and intuitively based on the limit of the knowledge field, causing them to underestimate the importance of the indicator. The next section describes the empirical demonstration of the two case studies Hsinchu and Southern Taiwan Science Parks.
According to the result of the FAHP in the second stage of the questionnaire, experts reached a consensus on the importance of the facility index (0.5864) and cultural environment index (0.2274) from the city perspective. The weight of the indices included infrastructure, medical and educational institutes, professional network facilities, transportation, and public spaces. The indices were significantly correlated with the features of knowledge-intensive talents and lifestyles, and thus, revealed the socioeconomics of all levels in a city. The indicators reflected whether the physical spaces of infrastructure and culture functioned and benefited the city. Therefore, the properties of spaces adopted for knowledge transfer and innovative activities were critical from the viewpoint of urban spatial scale.

4.1.3. Science Park Perspective

As for the perspective of science parks, the first-step result of the questionnaire carried out by the Fuzzy Delphi Method for the index of residential development (5.77) in the “land use” (6.60) type did not reach the expert consensus range (Hi) of 6. The result was based on the definition of residential development in the study that provided various types of housing compatible with other purposes in science parks. The accommodation in science parks reduced the distance from home to the workplace and offered more innovations and job opportunities. Nevertheless, the importance of the indicator was reported by the experts to be relatively low. Due to the changes in the industrial type and residential requirements, the rental demand for housing or dormitories in science parks was reduced. The innovation efficiency of science parks benefited little from housing areas with the primary function of being lived in and used by employees. Consequently, timely adjustment of residential areas in science parks could enhance land-use flexibility and would be more in line with future needs.
Different from the previous two perspectives which focused on the influence of science parks on the regional environment, the result of the second-stage questionnaire applied by the FAHP showed the emphasis on factors inside the science parks in terms of the perspective of science parks. Experts were consistent on the significance of the indicators facility in science parks (0.2115) and service and management (0.1836). The function of science parks in cultivating startups and promoting technology transfer was favorable for increasing the efficacy of the RIS. Accordingly, science parks acted critically in promoting industrial upgrades, stimulating innovations, and developing processes. The areas, industrial equipment, research outcomes (technology and product), and the services provided by science parks encouraged innovative transformation and benefited the value and reputation of science parks. Along with the evolution and transformation of global industry and environment, science parks must make dynamic adjustments for continuously competitive development, so that the management teams of science parks can continue to focus on developing the positioning, locational requirements, laws and regulations, space functions, operation and management and changes in innovation transformations (e.g., financial, business, innovative, startups, and network services). The services provided by the management teams were crucial to the development of science parks.
The results and discussions of the two-step questionnaire indicate that experts from different professional fields had different beliefs and rankings for the significance of the region, city, and science park aspects regarding the development of regional innovation and requirements in science parks. In general, experts with academic backgrounds believed the regional aspect and its relevant indicators to be the most essential factors when considering the innovative conditions required for developing science parks. Conversely, management teams and firms in science parks were mainly concerned about the perspective of science parks and the related indices, followed by the city aspect and the factors. Because experts with different backgrounds and at different positions had various degrees of involvement in the planning of science, they had diverse viewpoints and perceptions about the development of the parks. Consequently, effective communication and collaboration among different levels of participants, such as city managers, planners, and designers, are critical for the future development and planning of science parks, in addition to the consideration of various geographic scales. A plan based on adequate discussion and collaboration by all levels of participants is vital for future spatial planning.

4.2. Analysis for Innovation Systems

Previous investigations have revealed the significance of the specialized cluster effect for the high-tech industry in some areas of Taiwan. Science parks act crucially in RISs. This study analyzes science parks from three different spatial scales, namely, region, city, and science park. The impact and function of each indicator were further verified based on the ranking of the weights of the indices. Southern Taiwan and Hsinchu Science Parks were selected for the case study. The analytical results of the empirical study were then compared and discussed along with relevant publications and information to consolidate the analysis and systematic explanation of innovation systems established by the study. The research and analysis were incorporated for the planning of the future development of science parks and innovation systems. The analysis of the investigation is summarized in Figure 10 and described in the following points.

4.2.1. The Level of Linkage for the Elements of Innovation Systems across the Regions

The concept of RISs is concerned with the industrial structure, knowledge-based infrastructure, policies and supporting organizations, and institutional structure prevalent in specific geographic zones [26]. Furthermore, RISs emphasize a learning system based on the perception of interactive innovation and knowledge transfer [17]. Along with the complexity and difficulty in innovation, governance of technological innovation and environmental construction carried out by a single local government has gradually expanded and switched to cross-regional collaboration among several governments, and between public and private sectors. Satisfactory cross-regional collaboration among organizations and institutional structures is a benefit for the addition of roles and functions to a regional innovation system and the enhancement of industrial innovation in the system.
A distinct cluster effect for the high-tech industry in northern Taiwan was observed from the resources and industrial environment in the surrounding areas of Hsinchu Science Park. This cluster effect includes investment in research and development, technology transfer, talents and enterprises, and production and interaction. From the perspective of the industrial environment, clusters of innovative companies in the Hsinchu area generate cross-region connections as the industrial environment matures. Firms in northern Taiwan interact frequently and smoothly for technology transfer (Figure 5), contract relationships, and production and transaction networks (Figure 6). The headquarters of most enterprises are located in northern Taiwan. Consequently, a high ratio of enterprises in northern Taiwan collaborate and innovate with clients and competitors and are involved in international collaborations.
Concerning the proximity to Taipei and Taoyuan City, talents who participated in the innovative activities of innovation systems in northern Taiwan were relatively young with high levels of internationalization. This is due to specific linkages and interactions in addition to knowledge transmission and application led by research institutes and large enterprises, especially many higher education institutions and research institutes located in the Hsinchu area. Moreover, the completeness of transportation systems in the metropolitan areas of Taipei, New Taipei, and Taoyuan Cities make cross-city interactions connectable and accessible. Northern Taiwan has collected many resources. For example, local and regional finance and resources for research and development are mostly concentrated in areas north of Hsinchu. Under specific social characteristics, policies and incentives or mechanisms provided by enterprises have motivated members to absorb, apply, and advertise innovative activities and systems on the regional scale of the innovation systems.
Southern Taiwan Science Park has less complete industrial planning, based on the cluster scale, the number of similar enterprises in the park, and cross-regional connection, than Hsinchu Science Park, due to its later establishment. Considering the innovative behaviors or origins, the spatial proximity to research institutes, and the level of industrial clusters, the industrial innovation clusters in Southern Taiwan Science Park are mainly connected with Kaohsiung City for interactions, such as technology transfer, contract relationships, and production and transaction networks. Although spatial proximity is essential to some types of knowledge exchange, knowledge transmission of innovation systems also requires cross-regional transfer and interaction. In response to the research of Hsieh, Chen, Wang, and Hu [71], knowledge exchange in a geographic innovation system consists of diversity and cross-regional and long-distance virtual interactions, creating additional collaborative chances for the knowledge-intensive service industry in Hsinchu.

4.2.2. The Differences between Regional Innovative Activities and Knowledge Exchange

This investigation observed differences in industrial conditions, labor markets, industries, and mechanisms of enterprises between the regional innovation system of northern Taiwan, revolving around Hsinchu Science Park, and that of southern Taiwan, centered around Southern Taiwan Science Park. The two innovation systems are very dissimilar in innovative activities and knowledge exchange, demonstrating regional distinctions for RISs [72]. RISs are generally rooted in the regional environment, encouraging knowledge flow, innovation for the system, and interactive learning through connections and contributions of innovative private and public institutions [22].
In terms of industrial conditions, enterprises in the Hsinchu area collaborate and innovate with clients and competitors to a greater extent than companies located in other areas. Enterprises in science parks collaborate and partner with firms outside of science parks by participating in their disciplines and specialized fields. For instance, a complete industrial chain in the semiconductor and optoelectronics industry comprises small and medium-sized enterprises (SMEs) and large enterprises, collaborating from upstream to downstream supply chains. The interaction and communication between technical information from upstream and market information from downstream, while tightly connecting with the global value chain, enables the enterprises to respond to the impact of globalization. The intense gathering of SMEs and large enterprises triggers innovations under collaborative and competitive partnerships. The industry of southern Taiwan mainly consists of traditional industries and SMEs, which perform research and development independently and mostly without collaboration with external institutes or organizations (see Table 1 for the top five sectors based on the number of firms in the northern and southern regions in Taiwan). The establishment of Southern Taiwan Science Park has diversified the industrial structures of southern Taiwan, but even so, most SMEs still rely on local knowledge, restricting the capital, learning mode, market analysis and forecasting, and the ability of cross-field integration. The method of knowledge exchange and differences in its spatial characteristics in northern and southern Taiwan correspond to those observed by Hsieh, Chen, Wang, and Hu [71]. The knowledge-intensive service industry in Tainan City is relatively dependent on local and domestic knowledge, whereas that in Hsinchu and metropolitan northern Taiwan obtains and acquires knowledge both domestically and internationally.
In terms of the labor market, the Hsinchu area contains many higher education institutions and research institutes. The technical talents gather in the Hsinchu area (Figure 7). The high level of internationalization and relative youth of talents have led to a condensed and closed spatial characteristic in the Hsinchu area. Tainan, adjacent to Kaohsiung, is abundant in academic resources, human resources, and well-educated and technical talents, but has less globalization than the Hsinchu area.
In terms of industries and mechanisms of enterprises, the development resources in Taiwan are mostly concentrated in northern areas. Most venture capital firms are located in northern Taiwan. The huge investment in research and development, along with the policies, incubation centers in research institutes or universities, financial institutions, venture capital, and operation of capital markets, have created distinct mechanisms and different policy operations in northern Taiwan compared to southern Taiwan (Figure 8). Such attractions and incentives have accordingly encouraged industrial investment in northern Taiwan. Conversely, the academia–industry collaborations in southern Taiwan are missing from the survey of industrial needs executed by the intermediary agencies and the plan for matching operation mechanisms. Moreover, most companies in southern Taiwan lack industrial guidance from the government and the ability to execute research projects. Therefore, the firms are incapable of applying the industrial guidance effectively. In response to the different regional characteristics of northern and southern Taiwan, providing customized and differentiated industrial policies and measures is crucial for the transformation and innovation of SMEs in southern Taiwan.

4.2.3. The Quality and Quantity of Knowledge-Based Infrastructure and Constitution of Living Environment and Functions

Encouraged by industrial spatial policies in science parks and the development of a knowledge economy, enterprises and talents have begun to focus on spatial proximity and face-to-face interactions. Therefore, recent research implemented in-depth explorations of clusters from the viewpoint of spatial scale [73]. Spaces and infrastructure in communities are beneficial for official interactions and networking areas and infrastructure for informal communications has accelerated the generation and diversity of professional activities, resulting in knowledge spillovers and useful networks [74,75].
The regions where Hsinchu and Southern Taiwan Science Parks are located include a series of connections and interactions among relationships, production factors, and the physical environment. According to the results of this study, the two science parks have different levels of development in the infrastructure and transportation systems of the surrounding areas and communications between organizations in the professional network.
The aspect of the transportation system: In the questionnaire design of this study, transportation in the regional perspective refers to cross-regional connectivity; in the city perspective, it focuses on the commuting time of workers in the science park; in the science park perspective, it refers to the shared traffic facilities in the park. The results of expert questionnaires accumulated in this study indicate that the city perspective is the most important perspective in the aspect of the transportation system. Transportation in the surrounding areas of Hsinchu Science Park is flexible. The capacity, occupancy rate, and outbound transportation system enhance the accessibility of Hsinchu Science Park for the staff who work in the science park. The transportation that links Southern Taiwan Science Park with the surrounding areas is relatively dependent on national, provincial, and county highways.
The aspect of the professional networks: Many national research institutes have settled in Hsinchu. Hsinchu has good ability for company operations, solid networks, and high accessibility of technology exchange. Consequently, many national and international enterprises have located their headquarters or research centers in Hsinchu. Conversely, most research centers located in southern Taiwan are funded by foundations. SMEs in southern Taiwan are more independent in research and development and less collaborative with outer organizations than those in northern Taiwan.
The aspect of infrastructure: The aspect of infrastructure in the city perspective also received a high weight in the expert questionnaire results. Hsinchu City has many industrial and life requirements derived from Hsinchu Science Park. Leisure and business activities are active and vigorous. In contrast, the consumption and living activities in Tainan mainly occur in the downtown area, revealing that the communities and environment of the neighboring regions are still under growth and construction.
Overall, the spatial proximity of Hsinchu Science Park and the surrounding areas have stimulated the formation of industrial and production networks established by the industrial clusters. The spatial inseparability has encouraged the flow of technical talents. The facilities, spaces, and social culture provided by Hsinchu City and County, such as infrastructure, medical and educational institutions, professional network facilities, transportation, and public spaces, satisfy the need for knowledge-intensive talents (Figure 9). This situation is favorable for knowledge transmission, the generation of innovative activities, and the expansion of professional networks. Intra- and inter-system operations and knowledge exchange function well. Hence, Hsinchu Science Park has been able to continuously grow and innovate through collaboration with the surrounding areas and cities. In contrast, the spatial development and distribution for industries and the interactions of firms in Southern Taiwan Science Park are comparably loose. The exchange and interaction of knowledge, capital, talents, and products are not derived from spatial proximity. Additionally, the innovative and living environment of Tainan City is less appealing than Hsinchu to talents. Southern Taiwan Science Park and the neighboring region, which recently cooperated with projects of construction and establishment of the industrial base, are still investing in knowledge-based infrastructure, so are not yet able to achieve a synergy effect. However, this effect can be anticipated in Southern Taiwan Science Park in the future, and is likely to bring positive changes.

4.2.4. The Core and Spatial Proximity of Planning for Industrial Clusters in Science Parks

Durmaz [76] investigated regional attributes and spatial conditions of industrial and innovative industrial clusters in a city and indicated the most critical factors, namely, proximity, centrality, and accessibility. These key factors assist in promoting daily working processes, improving efficiency, and urging collaborations, and thus, provide personal inspiration. Hence, the regional features and spatial conditions of a science park and a city include proximity, centrality, and accessibility. A dense spatial distribution for organizations, institutes, industries, and facilities supports forming connections in a science park and acquiring technologies, and thus, may benefit from the infrastructure and business vibes.
Hsinchu County and City have several important research institutes, business service centers, and technology exchange centers. These institutes and centers, along with industrial parks, serve the parts required for the relevant industries, satisfy the tech-transfer needs of industry and business, and further shape a solid industrial network. As for the locational requirement, Hsinchu Science Park and the neighbors in the Industrial Technology Research Institute (ITRI), National Tsing Hua University, and National Yang Ming Chiao Tung University form a dense and cohesive spatial characteristic. The geographic proximity of academia and research institutes to Hsinchu Science Park provide quality human resources. Many engineers utilize the accessible resources and have created close collaborations between the university and industry. The industrial talents and enterprises cultivated by ITRI have triggered university–industry interactions and collaborations. Additionally, the establishment of business service and technology exchange centers, i.e., Taiwan Science Park Association of Science and Industry, Industrial Commercial Development and Investment Promotion Committee of Hsinchu County, and SME service centers of Hsinchu City, and the neighboring industrial parks, such as Hsinchu Industrial Park, located in Hukou Township of Hsinchu County, and Zhudong and Zhunan Industrial Parks, could serve components and parts to related industries in Hsinchu Science Park. The current urban scale and culture, in line with the infrastructure and facilities in surrounding areas of Hsinchu Science Park, including transportation systems and information networks, attract firms, provide relevant services and communications, satisfy the requirement of technology transfer, and offer various urban and technological activities. Such appealing locational requirements have built a robust and complete industrial network.
Southern Taiwan Science Park, located in Chiayi–Tainan Plain, has relatively flat and open terrain. Southern Taiwan Science Park has less tangible and intangible accessibility with its surrounding areas than Hsinchu Science Park, thus weakening the formation of industrial networks. Accordingly, Southern Taiwan Science Park relies more on introducing resources in the surrounding areas to make connections.
The connections of Southern Taiwan Science Park with the production networks in the surrounding areas depend on the import of resources, such as resource connections through the incubation center of Southern Taiwan Science Park or the Academia-Industry Consortium for Southern Taiwan Science Park, to enhance technology and talent exchange among universities, research institutes, and enterprises in the science park. Additionally, factories of Southern Taiwan Science Park are distributed in Shanhua, Xinshi, and Anding districts. Because of the early stage of development, the transportation system, industrial foundation, business services, and living environment in Tainan are comparably immature. The area also has only a few public facilities. The development of Southern Taiwan Science Park has triggered the land use planning of Tainan City, driving the animation of all urban functions. The continuous development of Southern Taiwan Science Park has recently encouraged investment from the semiconductor industry, including Taiwan Semiconductor Manufacturing Company (TSMC) and United Microelectronics Corporation (UMC) and appealed to the population moving in. Even though high-tech industrial clusters are still forming at the current stage, improvement of transportation and construction and promotion of Shalun Smart Green Energy Science City and the surrounding areas of Sinji, Tree Valley, and Yongkang industrial parks will aid the formation of better locational requirements for Southern Taiwan Science Park in the future.

5. Discussion and Conclusions

Owing to the requirements in production and R&D of high-tech industry, innovation and knowledge orientation have become critical to maintaining competitiveness. Science parks have institutionalized the governance and management of industrial clusters [2,3]. The integration of production, science, technology, education, and agency primarily established in a region promotes economic and technological development. Developing an environment that benefits the development of science parks in the future, while facing the new innovative face of high-tech industry and globalization, provides a driving force for industrial upgrades and establishments. Additionally, the investigation incorporates RISs to identify the regional backgrounds for developing science parks [3,7] (Figure 10). This study examines the factors and mechanisms affecting innovative efficiency in science parks based on a literature review, questionnaire, and empirical analysis and discussion. This study develops a conceptual and methodological approach to predict the important factors for the future science parks, theoretically drawing on the conclusions of the indices and mechanisms that influence innovative efficiency in RISs in order to respond to the competitive environment currently. The results of the study are summarized below.
  • This study utilizes the concept of RISs and explores the indices and mechanisms that influence innovative efficiency in science parks. The synergy effect of the elements of innovation systems occurs across regions, reflecting the unique feature of the local environment at various geographic scales and emphasizing the importance of governance of science park development at different spatial scales.
  • Among the development indices for encouraging the efficiency of science parks, this study considers the regional characteristics and needs and proposes three spatial scales, including regions, cities, and science parks. A questionnaire was distributed to experts and analyzed by the Fuzzy Delphi Method (FDM) and the FAHP to establish an indicator system that would help promote the efficiency of science parks. Based on the results of the two-step questionnaire, the regional background is crucial in improving the efficacy of science parks. Through this study, we attempted to address the research gap related to the contribution of different geographical scales to the practice of innovation policy, and propose anticipatory practices for the future of science parks [77].
  • From the questionnaire results in the second phase of this study, experts ranked the relative importance of each perspective as regional (0.3817), the city (0.3791), and science park (0.2392). The spatial heterogeneity of various RISs needs to be considered in terms of resource raising and making policies to meet the requirements of each science park. In other words, the establishment and regulation of science parks should not be separated from the background characteristics of the region and city where the science park is located. Policymakers must go beyond the scale of science parks, that is, construct science parks from a wider perspective (including regions and cities), to efficiently promote knowledge and information exchange among manufacturers in the science park.
  • The empirical analysis of Hsinchu and Southern Taiwan Science Parks also revealed significant differences. The level of linkage for the elements of innovation systems across the regions, the differences between regional innovative activities and knowledge exchanges, the quality and quantity of knowledge-based infrastructure and constitution of the living environment and functions are different between Hsinchu and Southern Taiwan Science Parks, due to the regional characteristics and needs and the three spatial scales proposed by this study.
  • The industrial and institutional environments are the most important indices at the regional level. Labor market (0.0658), enterprise condition (0.0650), and financial market (0.0518) have the highest weights in the industrial environment aspect. Policy integration and continuity (0.0383) and mechanism of industry and enterprise (0.0443) have a higher weight in the institutional environment aspect. Level of facilities is the most influential factor at the city level—infrastructure (0.0554), healthcare and educational institutes (0.0535), professional network/facility (0.0560) and transportation (0.0573) have a higher weight at this perspective. Finally, centrality2 (0.0510) is the most essential indicator in the location type of the science park.
  • The development of high-tech industry triggers a variety of characteristics, functions, and requirements in an innovation system. The space economy of production in science parks is beginning to disperse. Single-input or focused investment in science or industrial parks is no longer the dominant investment model as in the past. The future development of science parks should benefit from spatial proximity, linking the surrounding resources and innovative components with the core of science parks. Altering the interactive layout of science parks, regions, and urban industrial space encourages spontaneous and small-scale interactions in the industry, develops flexible collaborations, and further leads to the transformation and upgrade of science parks by solid innovation systems.
  • The analytical results also reveal significant differences in the opinions and cognition for the development of science parks among experts in different professional fields. Therefore, communication and collaboration among different levels of city managers, planners, and designers are important when planning for the future of science parks.

Author Contributions

S.-C.P.: data curation; formal analysis; methodology; project administration; software; supervision; validation; writing—original draft; writing—review and editing. P.F.: conceptualization; writing—review and editing. T.-S.H.—conceptualization; funding acquisition; methodology; project administration; resources; supervision; validation; writing—review and editing. H.-Y.L.—data curation; formal analysis; software; validation; writing—review and editing. W.-S.L.—data curation; formal analysis; investigation; methodology; software; writing—original draft. All authors have read and agreed to the published version of the manuscript.

Funding

Part of the context of the article was extracted and revised from the research project, MOST 109-2410-H-006-087, with funding supported by the National Science and Technology Council. We acknowledge the funding support by National Science and Technology Council.

Institutional Review Board Statement

According to Articles 4 and 5 of Taiwan’s “Human Research Act”, research related to human experiments must undergo ethical review approval. The complete content of the two aforementioned Articles are as follows: Article 4. Definitions: 1. Human subject research (hereinafter “research”): refers to research involving obtaining, investigating, analyzing, or using human specimens or an individual person’s biological behavior, physiological, psychological, genetic or medical information. 2. Human specimens: refer to human (including a fetus and corpse) organs, tissues, cells, body fluids, or any derivative biomaterial arising from experimentation therewith. 3. Delinkage: refers to the operation of permanently disabling encoded biological specimens, data, and information from being linked to or matching them with the subjects personal data or information. Article 5. Prior to conduct a research, the principal investigator shall submit the research protocol for review and approval by the Institutional Review Board (hereinafter “IRB”). However, the research protocol within the scope of exemption categories for IRB review, as announced by the competent authority, shall not apply. The review in the preceding Paragraph shall be conducted by the research entity’s IRB. Where an entity does not have an established IRB, the review may be conducted by IRB of other entity. Amendments of an approved research protocol shall be submitted for IRB approval prior to its implementation. For the full text, please see: https://law.moj.gov.tw/ENG/LawClass/LawAll.aspx?pcode=L0020176, accessed on 18 February 2024.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

All cited data in this study are available in a publicly accessible repository, and the relevant original data can be found on the website provided by the source of each figure.

Acknowledgments

We acknowledge H.-P. Lin for her assistance in project execution and article writing. In addition, we would like to thank each respondent for their generous assistance.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A

Table A1. Indices and their weights.
Table A1. Indices and their weights.
AspectTypeIndexWeight
ItemLocal Weight
NW		ItemLocal Weight
NW		Overall WeightItemLocal Weight
NW		NW × NW × NW
Region0.3817Physical Environment0.21360.0815Regional Structure0.30770.0254
City Image0.32050.0265
Transportation0.37180.0307
Industrial Environment0.47610.1817Labor Market0.36020.0658
Enterprise Condition0.35630.0650
Financial Market0.28350.0518
Institutional Environment0.31030.1185Policy Integration and Continuity0.31900.0383
Political Environment Stability0.31180.0375
Mechanism of Industry and Enterprise0.36920.0443
City0.3791Community Type0.18620.0706Spatial Structure0.25940.0183
Innovative Vibe0.23890.0169
Diversity and Level of Openness0.23890.0169
Service & Management0.26280.0186
Facility0.58640.2223Infrastructure0.24930.0554
Healthcare and Educational Institutes0.24080.0535
Professional Network/Facility0.25210.0560
Transportation0.25780.0573
Cultural Environment0.22740.0862Public Space0.34930.0301
Lifestyle0.31100.0268
Environmental Safety0.33970.0293
Science Park0.2392Location0.21330.0510Centrality10.0510
Environmental Design0.14120.0338Outer Space and Landscape0.52050.0176
Inner Space0.47950.0162
Facility0.21150.0506Advanced Level0.51590.0261
Shareability0.48410.0245
Service and Management0.18360.0439Transportation0.52630.0231
Software Service0.47370.0208
Land Use0.13090.0313Development Plan10.0313
Recognition0.11950.0286Brand Reputation10.0286

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Figure 1. The conceptual framework of this study.
Figure 1. The conceptual framework of this study.
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Figure 2. Factors of science park planning and the future trend. Source: modified from Wasim [27].
Figure 2. Factors of science park planning and the future trend. Source: modified from Wasim [27].
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Figure 3. The conceptual framework for evaluation of urban quality. Source: modified from Esmaeilpoorarabi and Yigitcanlar [30].
Figure 3. The conceptual framework for evaluation of urban quality. Source: modified from Esmaeilpoorarabi and Yigitcanlar [30].
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Figure 4. The conceptual framework of indices.
Figure 4. The conceptual framework of indices.
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Figure 5. Value of technology purchased and sold by Hsinchu and Southern Taiwan Science Parks. Source: Factory operation census of 2020, Department of Statistics, Taiwan.
Figure 5. Value of technology purchased and sold by Hsinchu and Southern Taiwan Science Parks. Source: Factory operation census of 2020, Department of Statistics, Taiwan.
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Figure 6. Total value of imports and exports of Hsinchu and Southern Taiwan Science Parks. Source: Statistical database of 2014–2023, the statistics of National Science and Technology Council, Taiwan.
Figure 6. Total value of imports and exports of Hsinchu and Southern Taiwan Science Parks. Source: Statistical database of 2014–2023, the statistics of National Science and Technology Council, Taiwan.
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Figure 7. Proportion of employees with different education level to total employees. Source: Statistical database of 2023, the statistics of National Science and Technology Council, Taiwan.
Figure 7. Proportion of employees with different education level to total employees. Source: Statistical database of 2023, the statistics of National Science and Technology Council, Taiwan.
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Figure 8. The ratio of R&D expenditure to revenue of Hsinchu and Southern Taiwan Science Parks. Source: Factory operation census of 2023, Department of Statistics, Taiwan.
Figure 8. The ratio of R&D expenditure to revenue of Hsinchu and Southern Taiwan Science Parks. Source: Factory operation census of 2023, Department of Statistics, Taiwan.
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Figure 9. The differences in quality and quantity of knowledge-based infrastructure and constitution of living environment and functions between Hsinchu and Southern Taiwan Science Parks.
Figure 9. The differences in quality and quantity of knowledge-based infrastructure and constitution of living environment and functions between Hsinchu and Southern Taiwan Science Parks.
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Figure 10. Scheme of interactive mode of the regional innovation system in Hsinchu and Southern Taiwan Science Parks.
Figure 10. Scheme of interactive mode of the regional innovation system in Hsinchu and Southern Taiwan Science Parks.
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Table 1. Top 5 sectors based on number of firms in northern and southern regions in Taiwan.
Table 1. Top 5 sectors based on number of firms in northern and southern regions in Taiwan.
RegionSectorsPercentage
entry 1Fabricated Metal Products Manufacturing19%
Electronic Parts and Components Manufacturing12%
Machinery and Equipment Manufacturing12%
Repair and Installation of Industrial Machinery and Equipment9%
Computers, Electronic, and Optical Products Manufacturing5%
entry 2Fabricated Metal Products Manufacturing37%
Plastic Products Manufacturing22%
Machinery and Equipment Manufacturing19%
Manufacturing Not Elsewhere Classified12%
Printing and Reproduction of Recorded Media10%
Source: Industry, Commerce and Service Census in 2016, Taiwan.
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Pan, S.-C.; Fan, P.; Hu, T.-S.; Li, H.-Y.; Liu, W.-S. An Anticipatory Practice for the Future of Science Parks: Understanding the Indices and Mechanisms on Different Spatial Scales of Regional Innovation Systems. Sustainability 2024, 16, 4600. https://doi.org/10.3390/su16114600

AMA Style

Pan S-C, Fan P, Hu T-S, Li H-Y, Liu W-S. An Anticipatory Practice for the Future of Science Parks: Understanding the Indices and Mechanisms on Different Spatial Scales of Regional Innovation Systems. Sustainability. 2024; 16(11):4600. https://doi.org/10.3390/su16114600

Chicago/Turabian Style

Pan, Ssu-Chi, Peilei Fan, Tai-Shan Hu, Han-Yu Li, and Wen-Shin Liu. 2024. "An Anticipatory Practice for the Future of Science Parks: Understanding the Indices and Mechanisms on Different Spatial Scales of Regional Innovation Systems" Sustainability 16, no. 11: 4600. https://doi.org/10.3390/su16114600

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