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Article

Using the Evolution of a River Technology System to Compare Classification-Based and Citation-Based Technology Networks

by
Lin Gan
1,
Yongping Wei
1 and
Shuanglei Wu
1,2,*,†
1
School of the Environment, The University of Queensland, Brisbane, QLD 4072, Australia
2
School of Public Policy and Management, Guangxi University, Nanning 530004, China
*
Author to whom correspondence should be addressed.
†
Permanent address: 100 Da Xue Dong Road, Xi Xiang Tang District, Nanning 530003, China.
Water 2024, 16(19), 2856; https://doi.org/10.3390/w16192856 (registering DOI)
Submission received: 9 August 2024 / Revised: 19 September 2024 / Accepted: 27 September 2024 / Published: 8 October 2024
(This article belongs to the Section Hydrology)
Browse Figures
Versions Notes

Abstract

:
With the increasing complexity of societal and environmental problems in the Anthropocene, the use of both classification-based approaches, which provide in-depth understanding within disciplinary boundaries, and citation-based approaches, which provide interdisciplinary research, has been encouraged. However, there are limited comparisons of the knowledge networks produced between these two approaches, which compromises our capacity to manage technological development. This paper aims to investigate the similarities and differences of river technology networks produced using classification-based and citation-based approaches. The World Intellectual Property Organization (WIPO) database from 1863 to 2020 was used as the data source. River technology systems contained three interactive subsystems: water demand, water supply, and water management, and the structure was measured using network-based metrics. It was found that river technology systems constructed using the classification-based and the citation-based approaches developed similarly in terms of their temporal, spatial, and compositional features. The structural differences were attributed to the addition of an external system that draws upon interdisciplinary knowledge beyond water resources. Both approaches can be used for guiding technology management, with the classification-based approach being more effective for understanding the content of innovations and the citation-based approach being more effective in gathering information beyond the water resource discipline. Technologies from more diverse disciplines should be encouraged to address increasingly complex water challenges.

1. Introduction

For a long time, human knowledge has been organised through classifications [1,2]. Information can be categorized according to disciplines (e.g., hydraulic engineering, chemical engineering, information engineering, etc.) or according to industry sectors (e.g., agriculture, transportation, and energy). “One technology–one industry” has been commonly used to characterize different eras of our society [3,4]. On the other hand, the classification-based knowledge system has contributed to the in-depth specialization of knowledge within the boundaries of intellectual communities [5].
However, with the increasing complexity of societal and environmental problems in the Anthropocene, the use of interdisciplinary research has been encouraged and has become more popular because it provides solutions or innovations that combine knowledge from various disciplines [6,7]. In the context of technological innovation, interdisciplinarity refers to the integration or fusion of knowledge from diverse technical fields to develop new technologies, goods, or procedures [4]. Some authors argue that the majority of advanced technologies tend to emerge from several technological domains rather than within a single area [8]. To align with the interdisciplinary trend of knowledge development, the citation-based approach has been developed to investigate the content and structural properties of knowledge from different domains [9,10,11,12]. Literature citations are often used in academic research, and patent citations are applied in technological innovation and transfer. If one patent cites another patent as a reference, they are considered technologically related [13,14]. This technical link between two patents has become the basis of patent citation analysis [4]. However, there is a limited understanding of the similarities and differences of the knowledge networks produced between these two approaches, which compromises our capacity to manage and direct knowledge and/or technological development [15].
Water is a precious resource for human life and society. However, water scarcity has been increasing due to the increasing pressure from climate change, rapid population growth, urbanization, and economic growth [16,17]. By 2050, four billion people might live in places with limited water supply. The imbalances between water supply and water demand are considered a major challenge for many countries [18]. River technology plays a critical role in coping with natural and societal challenges through, for example, water desalination to provide new water resources, wastewater treatment to improve water quality, drip irrigation to decrease water consumption, and dams to manage water resources [19,20,21,22,23,24]. River technology is also constantly advancing. For example, with the use of new technologies, we have moved from the dominant use of large-scale infrastructure (e.g., dams and canals) which conveys water over longer distances to diversified water use, such as the improved monitoring of water resources and reverse osmosis, which recycles water. However, technological innovation has yet to resolve the conflict between water demand and water supply [25,26]. Patent data have been widely used to analyse the dynamics and trends of water-related technologies, although studies have tended to focus on a single technological domain, such as wastewater treatment [27,28].
This paper aims to provide insight into the similarities and differences between the classification-based and citation-based knowledge networks established for the same river technology system, represented by patent data. The findings from this study will assist, on one hand, in managing and directing future technological development, and, on the other hand, in identifying technological innovation gaps to address future global water issues.

2. Methods

2.1. Data Source and Data Collection

We collected data from the World Intellectual Property Organization (WIPO) database, which is considered a patent database with low potential national bias and high-quality patents [29]. A keyword-based search was conducted with ‘river’ as the keyword, and the study period spanned from the earliest available data in 1863 to 2020. This resulted in a total of 40304 patents collected. We further extracted 4497 patents (11%) with citations, with the first appearing in 1979. Finally, the study period ranged from 1979 to 2020. These patents were used for further analysis. We collected the patent title, application number, publication date, country or patent office, International Patent Classification (IPC) code, patent citations, and the IPC of patent citations for each patent.
The study period was then divided into three stages, which were based on the growth rate of total patents in the river technology systems registered per year. Each stage showed a tenfold increase in growth rate. For spatial development, the number of cited patents developed in different countries as well as the number of cited patents in all study periods were collected.

2.2. Classification of Patents in River Technology Systems

We adopted the definition of a river technology system based on the water resource discipline as we developed in [19], which classified technologies into three subsystems: water demand, water supply, and water management subsystems (Figure 1). Water demand technologies accomplished one or more of the following five components to fulfil certain societal functions: “(1) reduce the quantity or quality of water required to accomplish a specific task; (2) adjust the nature of the task or the way it is undertaken so that it can be accomplished with less water or with lower quality water; (3) reduce the loss in quantity or quality of water as it flows from source through use to disposal; (4) shift the timing of use from peak to off-peak periods; (5) increase the ability of the water system to continue to serve society during times when water is in short supply” [30]. For example, drip irrigation technologies for agricultural water or water taps for domestic water can be used to reduce the quantity of water required to accomplish a specific task. Water supply technologies referred to the technologies adopted in water supply infrastructure networks designed to collect, transport, and distribute water, as well as to treat and reuse drainage [31,32]. For example, these include plumbing installations for freshwater or wastewater, physical, chemical, and biological water treatment technologies, and pipeline system technologies. Water management technologies refer to river regulations that assist in the operations of river systems and ensure the availability of water for both water supply and direct in-stream usage. Hydraulic engineering is a common water management technology. In addition to the hydraulic engineering techniques used for managing the detailed water flow processes, the water management technologies also include some modern smart electronics for data collection and other monitoring techniques, like data transmission, geographical data systems, and lasers for both laboratory and field measurements [33]. Each patent only belongs to a single subsystem according to its primary purpose to minimise ambiguity and maintain consistency, even though some patents may have crossover among three subsystems.
Additionally, an external system was defined to document the interdisciplinary technologies that were not directly related to water resources, which were great supplements to promote technological innovation [34] (refer to Appendix A Table A1 for classifications with detailed IPC codes).

2.3. Measuring the River Technology Network

Two different approaches were used to measure the river technology network. Individual patents were represented as “nodes” and their interactions as “ties”. For the classification-based approach, we classified the patents into the three subsystems as defined above based on their IPC codes. Connections between patents were established following the patent co-occurrence principle: two patents were connected if they were developed within the same country at the same time. All the connections were conducted within the water resource discipline. For the citation-based approach, patents and their cited patents were classified according to the same principles above, but the connections between patents were established based on the citations explicitly listed by the inventors in the patent documents [35], which included self-nominated connections beyond the water resource discipline.
The connections in both networks were then transferred into square matrix tables. For the classification-based network, the connections among the three subsystems were established by adding up the total number of connections in each country at three stages. An example of a matrix of water demand and water supply subsystem at Stage 2, together with the intensity values, can be found in the Supplementary Excel Tables S1–S3 document. For the citation-based network, the connections among the three subsystems and external system were determined by summing the number of connections of each patent and its citations at three stages. An example of the matrix at Stage 2 and the corresponding intensity values is presented in the Supplementary Excel Tables S4–S6.
The key features and characteristics of interactions between three subsystems in both river technology networks were then measured by three metrics: intensity, brokerage, and efficiency (Table 1), which have also been widely used to examine the structural properties of networks [36,37]. The intensity metric measured the total number of connections between a technology and other technologies, and a high-intensity technology interacts significantly with other technologies and has a great influence on other technical advancements [38]. The brokerage metric evaluated the number of connections of a technology that bridge between the otherwise independent technologies, and a high-brokerage technology has a strong bridging capacity that can facilitate knowledge transfer across disciplines [39,40]. The efficiency metric was determined by computing the inverse of the sum of the shortest distances between one technology to others, and a high-efficiency technology can facilitate more effective knowledge and information transfer since it only requires a small number of connections to interact with any other technologies [12,41].
A well-balanced structure among subsystems is necessary for the optimal river technology system [42]. A technology system with imbalanced intensity, brokerage, and efficiency indicated a structural failure [43,44,45]. For example, technological development may have been heavily influenced by “path dependency” due to an excessive number of connections in a high-intensity system [46]. The high brokerage in a technology system may create “bottle-neck” effects and raise the possibility of system failure or collapse due to insufficient alternative connections between otherwise disconnected technologies [12,47]. High efficiency in a technology system may have negative influences on the development and the spread of knowledge, which is the result of the lack of incentives for the development of complementary or distinct technologies.
The differences in structures were compared by the intensity, brokerage, and efficiency metrics as described in Table 1 for the classification-based and citation-based approaches using the network analysis software UCINET [48].

3. Results

3.1. The Temporal and Spatial Development of River Technology Systems

Overall, river technology systems were characterized by slow accumulation (Stage 1), rapid expansion (Stage 2), and stagnation (Stage 3). Fewer than five patents were registered on average each year at Stage 1 (1979–1993), most of which were water demand patents with an average of two patents per year (Figure 2b). These technologies mainly focused on machines or engines for liquids (IPC code: F03B, the same thereafter), especially on machines or engines for power stations, as well as those related to ships or other waterborne vessels (B63B). There was also a noticeable peak in water management patents in 1985, indicative of surging engineering work to better control or use rivers, streams, other marine sites, barrages, or weirs.
Stage 2 (1994–2013) was characterized by an exponential expansion of river technologies for all subsystems (R2 = 0.87) with an average of over 145 patents per year (Figure 2c). Water management patents became the fastest growing and most dominant, with more than 48 patents per year. Hydraulic engineering remained the most significant technology, including the measurement of river conditions, such as chemical or physical properties (G01N), and the measurement of river volume and liquid levels (G01F). However, its proportion decreased over time and it was replaced by river measuring and monitoring technology (G06Q). Following this was the water supply subsystem, with 41 patents per year. The focus was on water treatment with physical and chemical processes like sorption and the biological treatment of water with aerobic processes, as well as the construction of embankments and underwater structures (E02D), bridges (E01D), and sewers and cesspools (E03F).
Stage 3 (2014–2020) marked the stabilization of river technologies in all three subsystems at 218 patents per year, with no significant change trend (R2 = 0.0019) (Figure 2d). The relative proportions of patents in each subsystem were similar and were as follows: water management (42%), water supply (34%), and water demand (24%). There was increasing diversity in water supply patents, with an increasing number of biological water treatment techniques and patents on water supply construction. While the water demand subsystem was most dominant at Stage 1, its development lagged behind the other subsystems from Stage 2 to Stage 3 (with an average of 28 patents per year). This subsystem also had a noticeable shift towards animal husbandry, pisciculture, and fishing (A01K, A01G).
The external system had 168 unique IPC groups in total, and most of the patents were related to electrography, electrophotography, magnetography (G03G), surgery using medical and biological material (A61B), and medical devices (A61M).
There were 18,744 citations between three river subsystems and the external system from 1979 to 2020 (Figure 3a). The development of citations was in line with the three stages for patent development. Stage 1 (1979–1993) was characterized by the slow accumulation of citations with over 25 per year on average and no statistically significant trend (Figure 3b). Most of the citations occurred within the river technology systems, and there were only two citations regarding the external system. Among the three subsystems, the greatest number of citations appeared between water supply and water management (11%), signified by connections among surface or ground construction related to rivers (E01C), hydraulic engineering (E02B), and dredging (E02F).
Stage 2 (1994–2013) was characterized by an exponential expansion of the total patent citations in river technology systems (R2 = 0.86) with over 582 citations on average each year (Figure 3c). Most of the river patents were cited within water management (26%), within water supply (26%), and within water demand (21%). Only about 20% of the connections were between water supply and water management (9%), water demand and water supply (7%), and water demand and water management (6%), and only about 3% were with the external system.
At Stage 3 (2014–2020), the citations between river patents were characterized by stabilisation, with no statistically significant trend (965 connections on average each year) (Figure 3d). The citations within and between the respective subsystems remained largely unchanged from Stage 2, and less than 1% of patents from the three subsystems cited the external system. Additionally, the actual number of citations was reduced, in particular, the citations for water supply decreased from 5065 to 2642. This indicates that while the citations were increasingly concentrated between patents within the same subsystem, there was declining interest in cross-boundary citations.
To sum up, the temporal development of river technology systems from both classification-based and citation-based approaches was similar, with slow accumulation in Stage 1 (1979–1993), an exponential growth rate in Stage 2 (1994–2013), and stabilisation in Stage 3 (2014–2020). The water management subsystems grew fastest, and most of the river patents were also cited within the water management subsystem. It was noticed that there were low values of the R2 coefficient in the regression results in both Stage 1 and Stage 3, and this may be because these two stages were in the phase of slow accumulation and stabilization. Therefore, there were fluctuations in the river patents each year and an unpredictable developmental trend.
From the spatial perspective, a total of 19,776 unique river-related patents and their cited patents were registered in 25 countries (Figure 4), with 1601 patents directly registered by four regional and global patent offices (Appendix A Table A2). Among the 25 countries, Japan has registered the most patents (9176), followed by the Republic of Korea (4807), the United States (4198), China (486), and the United Kingdom (330). It is noticed that the top three countries registered approximately 92% of the total river patents and cited patents across three river subsystems and the external system. Most of the patents in the water supply subsystem, water management subsystem, and external system were registered in Japan, whereas the United States registered the most patents on water demand.
Moreover, the Republic of Korea has registered the most patents for water management subsystems, whereas China has registered the most patents for water supply and the United Kingdom has registered the most patents for water demand. Some countries with a lower number of total patent registrations focused on specific subsystems. For example, Australia focused on water management and Canada, Switzerland, Germany, France, and the Netherlands focused on water demand. In addition, 16 European countries were involved in river patent registration, whereas only five Asian countries and less than two countries in North America, South America, and Oceania were involved.

3.2. Comparing the Compositions of River Technology Systems Formed by Classification-Based and Citation-Based Approaches

We examined the patents classified within the water supply, water demand, and water management subsystems in detail to compare the differences in the compositions of the river technology systems formed by the classification-based and citation-based approaches. Figure 5 illustrated the compositions of the patents classified in the water demand (top), water supply (left), and water management (right) subsystems using the citation-based approach. Patents that belonged to the same subsystem indicated the alignment of their compositions with the classification-based approach, whereas patents from the other subsystems indicated differences in their compositions between the citation-based and classification-based approaches.
At Stage 1, water demand (161) had a greater number of patent citations than water management (116) and water supply (80) (Figure 5a). Among the patent citations in the water demand subsystem, most citations (76%) aligned with the classification-based system (i.e., they remained within the water demand subsystem), which mainly focused on energy and transportation (for example, ships or other waterborne vessels (B63B), hydroelectric power (F03B), steam turbines (F01D), launching vessels, equipment for underwater work (B63C), the design of courts or rinks on rivers (A63C), and heat pumps (F24D)). About 12% of the citations regarded the water supply subsystem, mainly focusing on mining, water treatment, and construction (for example, earth or rock drilling and obtaining water from wells (E21B)). For the citations regarding the water management subsystem (11%), the focus was on hydraulic engineering and river channel measurement (e.g., E02B and G01C). Among patent citations in the water management subsystem, 66% of the connections remained within the water management subsystem, dominated by hydraulic engineering (E02B, 90%). In addition, monitoring and measuring rivers using electricity technology (G01F) and river pollutant properties (G01N) were also the focus. The percentage of citations outside the water management subsystem increased to 30%, with water supply (19%) patents focusing on water supply infrastructure, construction, and water treatment, and water demand (13%) patents focusing on the textile industry, agriculture, and transportation. Among the patent citations in the water supply subsystem, connections with water supply accounted for the largest proportion (59%), which was mainly related to water treatment and water supply infrastructure for drainage pavement and embankments (e.g., C02F and E01C). The citations regarding the water management subsystem (24%) mainly focused on hydraulic engineering and river monitoring (e.g., E02B and G06F), and those regarding the water demand subsystem (15%) focused on ships and other transportation modes (e.g., B65B and B63B). Only about 2% of the citations regarded subjects other than river technology systems, such as water demand related to hinges or suspension devices for doors or windows (E05D); water management with cigarettes (A24D) and biochemistry (C12K); and water supply with burners (F23D).
At Stage 2, water management (4458) had a larger number of patent citation connections than water supply (3991) and water demand (3183) (Figure 5b). The patent citations within the water management subsystem (68%) had largely unchanged compositions compared to Stage 1. Newly developed technologies focused on improved river flooding predictions (G06F). This was similar for those regarding water supply (16%), with new developments in technologies such as sewers and cesspools (E03F) and methods for obtaining, collecting, or distributing water (E03B). Citations regarding water demand (11%) were dominated by the culture of aquatic animals (A01K) and hydroelectric energy (F03B). Among the patent citations within the water supply subsystem (75%), the composition was largely unchanged. Citations regarding water demand (12%) were mainly related to horticulture (A01G), cement (C04B), hydroelectric energy (F03B), and the culture of aquatic animals (A01K); meanwhile, for citations regarding water management (9%), the compositions remained largely unchanged from Stage 1. The citations within the water demand subsystem (78%) remained dominated by hydroelectric power (F03B). Technologies related to the culture of aquatic animals (A01K) and horticulture (A01G) emerged in the top five most cited patents. The compositions of citations regarding water supply (11%) and water management (8%) were largely unchanged. For the external system, the composition of this subsystem totally changed and accounted for 4–5% of the total citations. All the subsystems acquired knowledge from the external technologies related to information storage (G11B and G03G), diagnosis and surgery (A61B), optics (G02F), typewriters (B41J), loudspeakers or microphones (H04R), electric discharge tubes or discharge lamps (H01J), and domestic washing or cleaning (A47L).
At Stage 3, the number of citations was reduced for all the subsystems compared to Stage 2, with water management (2765) having a larger number of patent citation connections than water supply (2029) and water demand (1961) (Figure 5c). Among the patent citations in the water management subsystem, the only technique that changed the composition for water management (74%) compared to Stage 2 was signalling or calling systems (G08B). It was noted that more technologies for river modelling and computing were developed than technologies for simple measurements of river conditions. The composition of water supply (16%) was the same in Stage 2, and the water demand (8%) composition was largely unchanged with only one technique emerging (semiconductor devices (H01L)). For the external system (2%), three technologies emerged: loudspeakers or microphones (H04R), the use of inorganic or non-macromolecular organic substances as compounding ingredients (C08K), and controlling combustion engines (F02D). While the compositions remained largely unchanged for citations within the water supply subsystem, there was a great increase in the number of techniques for sewers and cesspools (E03F) compared to others at Stage 3. This was similar for the citations regarding the water demand (11%) and water management (11%) subsystems. However, the technologies in the external subsystem completely changed again (2%). These included technologies related to devices for introducing media into, or onto, the body (A61M), chemical features in the manufacture of man-made filaments, threads, or fibres (D01F), fusion reactors (G21B), tables, desks, or office furniture (A47B), and punching metal (B21D). Similarly, the composition within the water demand (78%) subsystem and those within the water supply (9%) and water management (10%) systems were largely unchanged. Two new technologies appeared in the external system (2%): technologies related to diagnosis and surgery (A61B) and domestic washing or cleaning (A47L) emerged.

3.3. Comparing the Structures of the River Technology Systems Formed by Classification-Based and Citation-Based Approaches

From the intensity perspective (Figure 6a), water management patents had the greatest values for both the classification-based (average degree = 130, 48%) and citation-based connections (average degree = 21, 39%) at Stage 1. Both were driven mainly by patents pertaining to hydraulic engineering (E02B). The values for water demand and water supply patents were the same (average degree = 69, 26%) for the classification-based connections, whereas the water demand subsystem (mainly related to water treatments such as the magnetic or electrostatic separation of solid materials from water (B03C)) had a greater intensity value (average degree = 19, 36%) than the water supply subsystem for the citation-based connections. From Stage 2 to Stage 3 (Figure 6b,c), the water management subsystem continued to increase in relative proportions and had the greatest intensity values for both classification-based (average degree = 9292, over 40%) and citation-based connections (average degree = 68, about 50%). Meanwhile, the water demand subsystem (mainly related to agriculture and transportation, e.g., patents related to planting, sowing, and fertilising (A01C)) increased rapidly for the classification-based approach but decreased in relative proportions for the citation-based approach.
From the brokerage perspective (Figure 6d), the classification-based brokerage was significantly greater among the subsystems (average betweenness = 16, 94%) at Stage 1, mainly focusing on hydraulic engineering (E02B) and the measurement of river conditions (G01N), river volume, and liquid level (G01F). The bridging effect for water demand and water supply patents was the same (average betweenness = 0.5, 3%). On the other hand, the water demand subsystems dominated in citation-based connections (average betweenness = 117, 51%), by transportation and water treatment (e.g., launching vessels, equipment for underwater work (B63C), and the magnetic or electrostatic separation of solid materials from water (B03C)). Similar brokerage values were identified for the external (average betweenness = 26, 11%) and water supply (average betweenness = 24, 10%) subsystems. At Stage 2 (Figure 6e), the water management subsystem decreased in relative proportions for the classification-based approach (average betweenness = 37, 54%), but slightly increased for the citation-based approach (56%). There was an increasing level of brokerage for the water demand subsystem (average betweenness = 22, 32%), focusing on technologies related to agriculture, animal husbandry, pisciculture, and fishing (A01) and ships or other waterborne vessels (B63). In contrast, for the citation-based connections, it was the water supply subsystem that had an increasing brokerage value, focusing on the treatment of water (C02F) and water separation (B01D). At Stage 3 (Figure 6f), the water supply subsystem overtook the water management subsystem, with the greatest proportion (average betweenness = 16, 38%) for the classification-based approach, including water separation (B01D), dissolving, emulsifying, or dispersing (B01F), chemical or physical processes for water treatment (B01J and B01L), and the disposal of solid waste from rivers (B09B). Conversely, the brokerage values for the subsystems among the citation-based connections remained largely unchanged from Stage 2, and there were even slight decreases in the brokerage values for the water supply and external subsystems.
The efficiency values were similar among the water demand, water supply, and water management subsystems and almost did not change at all during the three stages (average closeness = 0.76, 33%) for the classification-based connections (Figure 6g–i). Technologies in the water management subsystem had consistently higher values. This was similar for the citation-based connections, with efficiency value similarly distributed among the water demand, water supply, water management, and external subsystems. It was observed that technologies with high efficiency values were largely unchanged compared to those with high brokerage values.

4. Discussion

This paper developed insights into the similarities and differences of the river knowledge networks produced between classification-based and citation-based approaches. River technology systems were defined as three interactive subsystems: water demand, water supply, and water management. An external system was added when the technology network was established using the citation-based approach. Three network-based metrics (intensity, brokerage, and efficiency) were used to examine the river technology structures. The World Intellectual Property Organization (WIPO) database from the earliest available date, 1863, to 2020 was used as the data source. The key findings from this study are summarised as follows:
There were 40,304 patents related to ‘rivers’ during 1863–2020, in which a total of 4497 patents had citations (11%), with the first patent appearing in 1979.
River technology development was characterised by slow accumulation in Stage 1 (1979–1993), exponential growth in Stage 2 (1994–2013), and stabilisation in Stage 3 (2014–2020).
Twenty-five countries were involved in river technology development with the top five being Japan, the Republic of Korea, the United States, China, and the United Kingdom. The top five countries had the most patent registrations accounting for over 90% of the total, and each country focused on specific subsystems.
The composition of the water supply subsystem remained mostly unchanged: more diverse water treatment techniques were patented with an increasing number on water supply infrastructure construction. The water demand subsystem had an increasing number of patents in agriculture, and the water management subsystem was dominated by hydraulic engineering with an increasing number of patents in river monitoring.
Among all the patents under the water demand, water supply, and water management subsystems, over 90% of the patents from the citation-based approach align with the classification-based approach. Less than 5% of the citations were from the external system, with changing compositions over time.
The river technology systems demonstrated balanced efficiencies among all the subsystems for both the classification-based and citation-based approaches. The water management subsystem had decreasing brokerage values by the classification-based approach but increasing values by the citation-based approach, whereas the water demand subsystem had increasing intensity values by the classification-based approach and decreasing values by the citation-based approach.
The findings from this study will assist in managing and directing future knowledge and /technological development. It was found that the technology networks produced with both the classification-based and citation-based approaches showed very similar temporal and spatial patterns, showed connections with similar compositions, and had similarly balanced structural efficiency metrics. However, the classification-based connections indicated decreasing brokerage values for the water management subsystem and increasing intensity values for the water demand subsystem, and vice versa for the citation-based approach. This was mainly due to the additional consideration of connections with the external system in the citation-based approach. We held that both the classification-based and the citation-based approach could be used to analyse river technology systems, but their usage should be dependent on one’s context and aim. Patents with citations were inadequately developed, with only a very small proportion of patents (11%) having citations, and patents from some countries such as China and Russia did not include citations. Thus, the classification-based approach is preferred to understand the general trends and compositions of technological development. When it comes to measuring the structure of river technology systems to identify the compositional and structural failure of technological innovations, the two approaches should be used jointly to closely examine specific river governance challenges about the supply, demand, and management of water, especially given their capacity to gather information beyond the water resource discipline. Our approaches also enable comparisons of technological innovations in different sectors.
The findings from this study also assist in identifying the gaps in river technological innovation to address future global water issues. First, the whole river technological system and its three subsystems presented stabilization and even a slight decrease at Stage 3, despite the ongoing increase in research and development expenditure [49]. The water management subsystem was the fastest development in river technology systems, and this was the result of the shift from the traditional water supply to the integrated water management approaches [50]. However, even with the growth of the fastest subsystem, water innovation was much slower than modern technologies such as gene technology and nanotechnology, which often have an exponential growth pattern [51,52].
Second, there was great spatial inequality in river technology development globally: only 25 countries had river technology patents and citations, and there were huge differences in terms of the number of patents among these countries. In particular, Asian countries like Japan, Korea, and China have registered a sizable number of patents and were among the top five countries for river technology development. Multiple reasons exist, including: the significant investment in research and development, severe water scarcity challenges caused by large populations and rapid urbanization, and the supportive science, technology, and innovation policies of their governments, and patents serving as an indicator for research and knowledge development evaluations in these countries [53,54,55,56].
Third, the evolution of the composition of the three subsystems of river technology tended to be homogeneous with limited diversification over the past 160 years. Only a few patents were found in support of river-related environmental sustainability, community livelihood, and climate adaptions. It was expected that the citation-based approach could reveal more interdisciplinary and inter-sector connections [57], but the inconvenient truth was that connections with the external system only accounted for an average of 2% of the total citations.
Finally, the structure of river technology systems had increasingly skewed development, especially in terms of the intensity and brokerage metrics from Stage 1 to Stage 3, which may have negative influences on the innovation or knowledge transfer within and beyond the water resource discipline. Therefore, we are concerned that present river technology systems have a very limited capacity for innovations addressing global water challenges under increasing pressure from climate change, rapid population growth, urbanization, water quality deterioration, and economic growth. The recommendation from our study is that more, faster, and more diverse river innovations should be encouraged, particularly in developing countries where water issues represent major threats to sustainable development.
This study has some limitations. First, we recognize that socioeconomic contexts, such as education levels, economic investments, wealth distribution, and government policies [58,59], have great impacts on the development and adaptation of technology. While the focus of this study is the comparison of the classification-based and citation-based approaches used to measure river technology networks, we assume that the same socioeconomic contexts can be applied simultaneously in both approaches and that this will not affect our key findings. Second, patents are only one primary source of technology and not all river technologies are patentable. Third, not all river patents can be applied and diffused in reality. Finally, to demonstrate the innovativeness of pending patents, applicants are unwilling to quote other patents as inspiration because of their potential competitive relationship, and therefore, this may limit the number and accuracy of the citations analysed [60].

5. Conclusions

We developed an understanding of the similarities and differences of the river technology system networks established by the classification-based and citation-based approaches. We found that the temporal, spatial, and compositional development for the two approaches was similar, but their structural characteristics differed in terms of intensity and brokerage. Current river technology systems have limited capacity for innovations to address global water challenges, and more river innovations need to be promoted, especially in developing nations where water-related problems pose serious challenges to sustainable development.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/w16192856/s1, Table S1: The IPC codes of water demand and water supply patents and their actual number in three sub-systems in each country at Stage 2; Table S2: The final matrix table that adds up the values of all the water demand and water supply patents in each country at Stage 2; Table S3: The intensity values of each IPC codes between the connections of water demand and water supply patents at Stage 2; Table S4: The IPC codes and its actual number of patents and its citation in three sub-systems and external system at Stage 2; Table S5: The final matrix table at Stage 2; Table S6: The intensity values of each IPC codes among the connection in three subsystem patents at Stage 2.

Author Contributions

L.G. contributed to conceptualization, methodology, data curation, data analysis, writing the original draft, and reviewing and editing the manuscript. S.W. contributed to conceptualization, methodology, data validation, and reviewing and editing the manuscript. Y.W. contributed to conceptualization, methodology, data validation, and reviewing and editing the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

The research is funded by a Research Training Program scholarship from the University of Queensland Graduate School. This study is supported by the Australian Research Council Special Research Initiative (SR200200186).

Data Availability Statement

The data that support the findings of this study are available from the World Intellectual Property Organization (WIPO) at https://www.wipo.int/patentscope/en/ (accessed on 25 February 2022).

Conflicts of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix A

All the patents and their cited patents were categorized into three subsystems or the external system based on their IPC codes, which were automatically assigned to each patent by the Patent Offices. The following the principles below were followed to categorise the IPC codes into three subsystems and the external system (Appendix A Table A1):
  • The water demand subsystem included patents addressing the use of water for domestic and recreational purposes, agriculture, and industry;
  • The water supply subsystem included patents associated with water collection; water treatment (water quality); water pollution and wastewater; and the supply of water for industrial or domestic use;
  • The water management subsystem included patents associated with hydraulic engineering and river condition measurements and monitoring;
  • All patents that fell outside the scope of water demand, water supply, and water management technologies but that were cited in the patents of these technologies were classified into the external system beyond the water resource disciplinary boundary.
Table A1. The classification of patents (detailed description of each IPC can be found at https://www.wipo.int/classifications/ipc/en/ (accessed on 16 May 2023)).
Table A1. The classification of patents (detailed description of each IPC can be found at https://www.wipo.int/classifications/ipc/en/ (accessed on 16 May 2023)).
Technology SubsystemsIPC Code
Water demandA01B, A01C, A01D, A01G, A01K, A01M, A01N, A22B, A22C, A23B, A23K, A23N, A43B, A45B, A45C, A45F, A47C, A47K, A61H, A61K, A62B, A62C, A63B, A63C, A63F, A63G, A63H, A63J, B03B, B03C, B03D, B04B, B04C, B05B, B07B, B23B, B23K, B23P, B24B, B24C, B25B, B27K, B28C, B44C, B60B, B60F, B60G, B60J, B60L, B60M, B60P, B60R, B60S, B60V, B60W, B61B, B61L, B62B, B62D, B63B, B63C, B63G, B63H, B63J, B64B, B65B, B65G, B66C, B66D, B66F, B67D, C04B, C05F, C05G, C08G, C09K, C10G, C10J, C10L, C10M, C12Q, C22B, C25B, C25C, D02G, D03D, D04B, D06B, D06F, D06M, D06P, E03D, E05F, E06B, E06C, E21C, E21D, F01B, F01D, F01K, F01P, F02B, F02C, F02G, F02M, F02N, F03B, F03C, F03D, F03G, F04B, F04C, F04F, F16B, F16C, F16D, F16H, F16K, F16N, F17C, F21K, F21L, F21S, F21V, F24D, F24F, F24H, F24T, F25B, F25C, F25D, F26B, F28B, F28C, F28D, F28F, F28G, F42B, F42D, G02B, G06M, G08G, G09F, G21C, G21D, H01B, H01L, H01M, H01Q, H01R, H02K, H02N, H02P, H02S, H04B, H05B
Water supplyA23L, A47J, A61C, A61G, A61L, A62D, B01D, B01F, B01J, B01L, B02C, B06B, B08B, B09B, B09C, B21F, B25H, B25J, B28B, B28D, B29B, B29C, B30B, B32B, B64C, B64D, B65D, B65F, B65H, B66B, C01B, C01C, C01D, C01F, C01G, C02F, C03B, C03C, C07C, C07D, C07F, C08F, C08J, C08L, C09D, C10B, C10C, C11D, C12F, C12M, C12N, C12P, C14C, C22C, C23C, C23F, C23G, C25D, C30B, D04H, D07B, E01C, E01D, E01F, E01H, E02C, E02D, E02F, E03B, E03C, E03F, E04B, E04C, E04D, E04F, E04G, E04H, E21B, E21F, F04D, F15B, F16F, F16L, F16M, F17D, F22D, F23G, F23J, F24S, F24V, F27D
Water managementE02B, F15C, F15D, F22B, G01B, G01C, G01D, G01F, G01G, G01H, G01J, G01K, G01L, G01M, G01N, G01P, G01R, G01S, G01T, G01V, G01W, G05B, G05D, G06F, G06G, G06K, G06N, G06Q, G06T, G07C, G08B, G08C, G09B, G10L, G16C, G16Z, G21F, H01F, H01H, H01T, H02B, H02G, H02J, H03B, H03F, H03K, H04H, H04L, H04M, H04N, H04Q, H04W, H05F, H05K
IPC classifications
A: Human Necessities
B: Performing operations; Transporting separating; Mixing
C: Chemistry; Metallurgy
D: Textiles; Paper
E: Fixed constructions
F: Mechanical engineering; Lighting; Heating; Weapons; Blasting
G: Physics
H: Electricity
Table A2. The patents which are not shown in Figure 4.
Table A2. The patents which are not shown in Figure 4.
CountryTotal
Eurasian Patent Organization5
European Patent Office419
Soviet Union54
World Intellectual Property Organization1123

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Water 16 02856 g001
Figure 1. Defining and measuring a river technology system (triangle), and its interactions within the river technology system (arrows inside the triangle) and external system (arrows outside the triangle) (modified from [19]).
Figure 1. Defining and measuring a river technology system (triangle), and its interactions within the river technology system (arrows inside the triangle) and external system (arrows outside the triangle) (modified from [19]).
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Water 16 02856 g002
Figure 2. (a) The temporal development and regressions for the total river patents and in the water demand, water supply, and water management subsystems and the external system, and the temporal development of patents in (b) Stage 1 (1979–1993), (c) Stage 2 (1994–2013), and (d) Stage 3 (2014–2020).
Figure 2. (a) The temporal development and regressions for the total river patents and in the water demand, water supply, and water management subsystems and the external system, and the temporal development of patents in (b) Stage 1 (1979–1993), (c) Stage 2 (1994–2013), and (d) Stage 3 (2014–2020).
Water 16 02856 g002
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Figure 3. (a) The temporal development and regression for the total citations between river patents and their cited patents in the water demand (D), water supply (S), and water management (M) subsystems and the external system (E). The temporal development of citations in (b) Stage 1 (1979–1993), (c) Stage 2 (1994–2013), and (d) Stage 3 (2014–2020).
Figure 3. (a) The temporal development and regression for the total citations between river patents and their cited patents in the water demand (D), water supply (S), and water management (M) subsystems and the external system (E). The temporal development of citations in (b) Stage 1 (1979–1993), (c) Stage 2 (1994–2013), and (d) Stage 3 (2014–2020).
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Figure 4. The spatial distribution of river-related patents and their cited patents during 1979–2020.
Figure 4. The spatial distribution of river-related patents and their cited patents during 1979–2020.
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Figure 5. The evolution of the compositions of citation-based river technology systems compared with the classification-based water demand (top), water supply (left), and water management (right) subsystems at (a) Stage 1 (1979–1993), (b) Stage 2 (1994–2013), and (c) Stage 3 (2014–2020). Each pie chart illustrates the composition of water demand (green gradient), water supply (orange gradient), water management (blue gradient), and external system (grey gradient) patents under the three subsystems.
Figure 5. The evolution of the compositions of citation-based river technology systems compared with the classification-based water demand (top), water supply (left), and water management (right) subsystems at (a) Stage 1 (1979–1993), (b) Stage 2 (1994–2013), and (c) Stage 3 (2014–2020). Each pie chart illustrates the composition of water demand (green gradient), water supply (orange gradient), water management (blue gradient), and external system (grey gradient) patents under the three subsystems.
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Figure 6. Comparisons of structural indicators for the citation-based and classification-based river technology systems for intensity at (a) Stage 1 (1979–1993), (b) Stage 2 (1994–2013), and (c) Stage 3 (2014–2020); brokerage at (d) Stage 1, (e) Stage 2, and (f) Stage 3; and efficiency (g) Stage 1, (h) Stage 2, and (i) Stage 3.
Figure 6. Comparisons of structural indicators for the citation-based and classification-based river technology systems for intensity at (a) Stage 1 (1979–1993), (b) Stage 2 (1994–2013), and (c) Stage 3 (2014–2020); brokerage at (d) Stage 1, (e) Stage 2, and (f) Stage 3; and efficiency (g) Stage 1, (h) Stage 2, and (i) Stage 3.
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Table 1. Metrics to measure and assess the structure of a river technology system.
Table 1. Metrics to measure and assess the structure of a river technology system.
MetricsDefinitionAssessment
IntensityThe average degree of connections between two subsystems (average degree = sum of number of connections to a node/total number of nodes)The larger the degree, the more intensively connected two subsystems are.
BrokerageThe average betweenness of interactions between two subsystems (average betweenness = sum of number of a node bridging between two other nodes/total number of nodes)The greater the betweenness, the more connections bridging between two otherwise unconnected subsystems.
EfficiencyThe average closeness of interactions between two subsystems (average closeness = 1/(the shortest distance of a node to all nodes/total number of nodes))The greater the closeness, the more efficiently two subsystems are connected.
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Gan, L.; Wei, Y.; Wu, S. Using the Evolution of a River Technology System to Compare Classification-Based and Citation-Based Technology Networks. Water 2024, 16, 2856. https://doi.org/10.3390/w16192856

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Gan L, Wei Y, Wu S. Using the Evolution of a River Technology System to Compare Classification-Based and Citation-Based Technology Networks. Water. 2024; 16(19):2856. https://doi.org/10.3390/w16192856

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Gan, Lin, Yongping Wei, and Shuanglei Wu. 2024. "Using the Evolution of a River Technology System to Compare Classification-Based and Citation-Based Technology Networks" Water 16, no. 19: 2856. https://doi.org/10.3390/w16192856

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