Notes
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[1]
Space Situational Awareness technologies include a range of sensors, telescopes, and computational tools to track, monitor, and predict the movements of objects in Earth’s orbit.
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[2]
Space Traffic Management technologies refer to the planning, coordination, and regulation of the operations of spacecraft in Earth’s orbit.
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[3]
Commercial Orbital Transportation Services.
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[4]
A project led by the United States aimed at bringing humans back to the Moon by 2025, with the ultimate objective of extending space exploration to Mars and other celestial bodies.
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[5]
NASA pays the contractor for the actual cost of the work performed, plus an additional amount to cover the contract’s profit.
1 Society and civilization have witnessed four distinct waves of industrial revolution, as documented by the OECD (2017, 2019): the first wave, driven by steam power; the second, powered by electric energy; the third, characterized by automation; and the current wave, defined by digital connectivity. Concurrently, modern researchers have developed sundry approaches to understanding innovation trends. One of the most promising is Christensen’s theory of disruptive innovation, which effectively addresses the changing business environment and contributes values to academia and industry (Christensen et al., 2018, Nicholas, 2021).
2 This theory initially explains how established firms can be surpassed by new entrants who target a small new market segment with a less advanced technology, offering lower prices but lower performance (Christensen, Bower, 1996; Christensen, 1997; Danneels, 2004; Schmidt, Druehl, 2008). Incumbents often focus on improving existing technologies for their mainstream customers, creating an opportunity for new entrants to enhance the new technology and expand sales in the new market segment. If successful, the new technology replaces the existing one, causing the mainstream market segment to shrink. Incumbents struggle to catch up due to first-mover advantages. This phenomenon occurs when a specific new technology emerges, referred to as disruptive technology by Christensen (1997).
3 The theory of disruptive innovation has proven influential in explaining the failures of many incumbents who were unable to adapt their approach to innovation and competition, as observed in the cases of Kodak, Blockbuster, and Nokia (O’Reilly, Binns, 2019). This theory has also played a significant role in elucidating how an immature new technology can supplant dominant existing technology.
4 However, Christensen et al. (2018) recently suggested that a promising future direction for the theory of disruptive innovation is to engage in a systemic perspective. This expansion would enhance the theory’s applicability to non-technical disruptions, including market and policy disruptions, as well as to broader contexts beyond the level of individual organizations (Christensen, Raynor, 2003; Danneels, 2004; Christensen et al., 2018). Embracing this systemic perspective could significantly enhance our understanding of disruptive innovations comprising numerous sub-disruptions (as for renewable energy systems, electric vehicles, smartphones, and space technologies).
5 In this paper, we adopt the systemic perspective advocated by Christensen et al. (2018) by characterizing disruptive innovation itself, instead of concentrating on its impact within the ecosystem. To the best of our knowledge, this specific focus has not been extensively explored within disruptive innovation theory.
6 The objective of this research is to advance the theory of disruptive innovation by developing a model specifically applicable for studying the scope, the magnitude, and the interconnections of disruptions when considered as part of a larger system of various disruptions. This leads us to introduce the concept of ‘systemic disruption,’ which refers to a socio-technical disruption encompassing various simultaneous disruptions operating at multiple levels.
7 A bibliometric analysis approach is chosen to study systemic disruption, supported by the work of Kongthon (2004) and Jiang and Liu (2023). In addition, the selected case in this research focuses on the context of the space ecosystem due to its ongoing changes marked by various disruptions that are collectively known as New Space (Vernile, 2018; ESPI, 2019; Dos Santos Paulino, 2020). The scientific publications are retrieved from several databases (including Science Direct and Scopus). During the process of selecting and evaluating publications, a total of 1,428 English-written scientific publications were identified for the years 2005-2021.
8 Our analysis reveals that New Space can be regarded as a systemic disruption, involving six interconnected disruption clusters that develop concurrently: (1) new technology, (2) new policy, (3) new market, (4) new entrant, (5) new process, and (6) new funding approach. Each disruption cluster contains several disruption nodes, which represent sub-dimensions of the parent disruption. These disruptions encompass socio-technical aspects and span micro to macro levels. However, not all disruptions carry the same magnitude; among them, new technology, new policy, and new market exert the greatest influence. Additionally, specific interconnections between these disruption clusters offer valuable insights into a co-evolution mechanism that shapes the scope and magnitude of the systemic disruption during the period from 2005 and 2021.
9 The development of the concept of systemic disruption contributes to enlarging the applicability of disruptive innovation theory to systemic contexts characterized by multilevel socio-technical disruptions. Moreover, our research provides guidance to fellow researchers regarding the application of bibliometric analysis in the field of disruptive innovations. This paper can also help managers and policy-makers in gaining an understanding of the systemic nature of disruptions as they shape their innovation and strategy agendas.
Theoretical Background
Disruptive Innovation Theory
10 According to the background of disruptive innovation theory, this obtains some influence from the mechanism of creative destruction (Antonio, Kanbach, 2023). Schumpeter (1939, 1942) explained that entrepreneurs create innovation, serving as the driving force behind creative destruction, wherein new ideas, technologies, or processes disrupt existing ones. This process of creative destruction fuels economic development, leading to both positive and negative impacts on the relevant stakeholders. For instance, it can create new job opportunities while rendering others obsolete. Organizations that can adapt to change and embrace innovation are poised to sustained growth and survival in the market (Schumpeter, 1911).
11 Disruptive innovation theory, as introduced by Christensen (1997), delves into the mechanism of creative destruction at a micro level. It explains why big innovative incumbents selling mature technologies can fall behind small new entrants offering cutting-edge technologies. In the initial stages, these new entrants cater to customers in a small new market segment, selling immature new technology, generally at lower prices but with lower performance (Christensen, Bower, 1996; Danneels, 2004; Schmidt, Druehl, 2008).
12 Meanwhile, established incumbents often overlook these changes because the immature new technology typically falls short of meeting the performance demands of mainstream customers, and the small new market segment fails to meet the volume requirements of incumbents. Consequently, incumbent organizations prioritize enhancing their existing technologies to serve mainstream customers in the established market segment. This approach leaves an opportunity gap for new entrants to improve new technology and boost their sales within the small new market segment.
13 If the efforts made by new entrants to improve the new technology are successful, the performance of new technology will surpass that of the existing technology. In such a scenario, mainstream customers recognize the new technology as a substitute for the existing one, and it can be referred to as a disruptive technology. Consequently, the existing market segment of the incumbents shrinks, or even disappears, and incumbents are unable to catch up owing to the advantages of being first movers, including the learning curve. A notable example of creative destruction brought about by a disruptive technology is the introduction of the “Apple” personal computers in the late 1970s, which disrupted the computer market long dominated by “IBM” (Schmidt, Druehl, 2008).
Solving Research Gaps
14 The theory of disruptive innovation continues to grow, as noted by Nicholas (2021), who explained that the understanding of the phenomenon of disruptions has evolved among academic scholars and practitioners as the theory has developed. In addition, Christensen’s perspective embraces a theory-building approach that welcomes new findings to further refine the theory and enhance the generalizability (Christensen, 2006; Nicholas, 2021).
15 Echoing the current interest of research on networks, platforms, and ecosystems (Letaifa et al., 2016; Theodoraki, Messeghem, 2017; Palmié et al., 2020), Christensen et al. (2018) suggested that a promising future direction for disruptive innovation theory is to engage in a systemic perspective. Valuable findings could be obtained if researchers investigate disruptions in “systemic or network-based industries” (Christensen et al., 2018, p. 1062).
16 Considering that a disruption affects an entire ecosystem, not just incumbents (Ansari et al., 2016; Öberg, 2023; Silva, Grützmann, 2023), implies viewing disruptive innovation as a system of disruptions rather than merely an individual innovation, such as a specific new technology. For instance, adopting a systemic perspective prompts a re-evaluation of the late 1970s disruption that occurred in the computer market.
17 Personal computers disrupted the computer ecosystem dominated by IBM because they represented a system of disruptions, comprising new technologies (e.g. personal computers, killer applications), new processes (e.g. user-centered design), and new customers (e.g. individuals) (Schmid, Druehl, 2008).
18 In this paper, we engage in the systemic perspective advocated by Christensen et al. (2018) by studying disruptive innovation as a system of disruptions, rather than focusing on its impact within the ecosystem. To our knowledge, this particular focus has not been extensively explored in disruptive innovation theory. Furthermore, it provides valuable insights for managers and policy-makers when setting their innovation agendas (including R&D, innovation, and strategy roadmaps). Regarding disruptive innovations through a systemic perspective allows us to study the micro level, as initially done by Christensen’s theory, as well as the meso and macro levels in which disruptions also develop. Such a multilevel approach proved invaluable and desirable to comprehend various innovation trends that involve several levels (including renewable energy systems, electric vehicles, smartphones, and space technologies) (Crossan, Apaydin, 2010; Kim et al., 2020; Si, Chen, 2020).
19 In addition, a systemic perspective puts forward the idea of various disruptions interconnected within a system of disruptions (Iansiti, Levien, 2004; Teece, 2007; Peltoniemi, Vuori, 2008). Therefore, changes initiated by a specific disruption influence the other disruptions, which co-evolve and collectively impact the magnitude of the entire system of disruptions. Such an interconnection opens the door for a system where several disruptions can occur simultaneously during the same period of time (Pechman et al., 2015; Kilkki et al., 2018). All the interconnected disruptions forming this system share sufficient similarities to be regarded as a specific group of disruptions. For instance, they usually emerge in similar markets and build upon similar technologies. However, the scope of the system will continue to evolve due to the co-evolution process, influenced by factors such as complementarity and competition among disruptions, as well as the emergence of new disruptions (Meyer, Winebrake, 2009; Tripsas, 1997).
20 Applying a systemic perspective to disruptive innovation theory also leads to the recognition that disruptions are not solely technological, as initially proposed by Christensen (1997). For example, understanding meso and macro disruptions exclusively through a technological lens can be challenging. This observation is consistent with Schumpeter’s approach, which has been adopted in numerous studies recognizing several categories of innovations, including new products, new processes, and new markets (e.g. Oslo Manual [OECD/Eurostat, 2005]; Geels, 2011).
21 The generalization of disruptive innovation theory toward socio-technical disruptions has already been initiated by Christensen and Raynor (2003) when they replaced the term “disruptive technology” with “disruptive innovation”. Our aim is to further extend this initiative by regarding disruptive innovation as a system of disruptions that extends beyond a technology-centric viewpoint. Thus, in addition to the new technologies initially suggested by Christensen (1997), the systemic approach allows for consideration of all the relevant socio-technical disruptions observed in the context studied, ranging from new entrants (e.g. new producers and new customers) and new policy (e.g. new industrial policy), to new funding approaches (e.g. venture capital).
22 In essence, the systemic perspective we adopt in this research entails looking beyond individual micro-level technical disruptions and considering the interactions and dynamics of multilevel socio-technical disruptions that collectively shape the entire system of disruptions.
Model
23 To comprehensively study the scope, magnitude, and interconnections of a system of multilevel socio-technical disruptions, this paper develops a model and subsequently uses bibliometric analysis for this purpose.
The model
The model
24 The model in Figure 1 shows “systemic disruption”, which is a multilevel socio-technical disruption. We develop this concept not to examine the impact of the disruptions on the ecosystem, but to study the scope, magnitude, and interactions of the systemic disruption itself.
25 The socio-technical dimensions of the systemic disruption, referred to as “disruption clusters”, include the generic dimensions suggested by disruptive innovation theory, such as new technologies and new entrants, as well as context-specific dimensions related to the context studied, such as new policies, for example in a highly regulated environment.
26 Within each cluster, various nodes of disruptions interconnect with each other, forming the cluster and representing sub-dimensions of their parent dimension. For instance, within the technology cluster, these nodes may include technology 1, technology 2, and so forth. These clusters and nodes of disruptions can establish connections with each other at different levels, ranging from micro to meso to macro. Moreover, these nodes and clusters co-evolve during a specific time period. At the beginning of this period, disruptions are still immature, but their capacity to deliver expected values can ultimately shape the scope and the magnitude of the systemic disruption.
Research Methodology
Bibliometric Analysis
27 Taking into account our model as presented in Figure 1, we propose using bibliometric analysis as a key element for the research methodology in order to navigate disruptions arising in the space ecosystem. This choice aligns with the suggestion made by Christensen et al. (2018, p. 1069), who noted that “by exploring novel metrics, researchers stand to contribute to disruptive innovation theory and to help managers charged with setting the innovation agenda for their companies”.
28 Bibliometric analysis is based on the measurement of an organic collection of measures related to various types of documents (Otlet, 1934). Pritchard (1969, p. 348) defines bibliometrics as “the application of mathematical and statistical methods to books and other media communication”.
29 Initially, bibliometric analysis focuses on material aspects, such as counting books, press articles, scientific publications, and citations, as statistically significant manifestations of recorded information. Recent advancements, particularly with new computational tools, have simplified the bibliometric analysis process for various purposes. In brief, bibliometric analysis aims to answer five principal questions: Who (authors), What (keywords), Where (location), When (year of publication), and with whom (professional network) (Borner, Polley, 2014).
30 The Oslo Manual (OECD/Eurostat, 2005) suggests that statistics on scientific publications can be used to measure innovation and some research has already attempted to apply established bibliometric-based analyses to study the scope, magnitude, and interconnections of disruptions in various contexts. For example, Moro et al. (2018) analyzed photovoltaic technologies, Dos Santos Paulino and Pulsiri (2022) explored sustainable space, and Jiang and Liu (2023) investigated energy security. These studies offer a bibliometric overview of research trends within specific contexts, including number of publications, top keywords, and keywords co-occurrences.
31 Previous studies based on bibliometric analysis have revealed specific disruptive innovations and clusters through keyword analysis. These results suggest that bibliometric analysis is a promising approach for measuring multilevel socio-technical disruptions.
Case
32 To navigate the disruptions from a systemic perspective, the space ecosystem is chosen as the context for this study because it is currently undergoing a transition process with numerous simultaneous disruptions, collectively known as the New Space phenomenon (Dos Santos Paulino, 2020; ESPI, 2019; Vernile, 2018). In addition, the space ecosystem refers to the complex network that includes organizations, countries, businesses, and technologies involved in space-related activities on a global scale. Since the mid-2000s, a growing number of mulitilevel socio-technical disruptions have accelerated the commercialization of space (Barbaroux, 2016; Dos Santos Paulino, Gudmundsson, 2021).
33 Examples of these disruptions include the entry of successful entrepreneurs who have designed new types of launch vehicles due to policy disruptions in NASA’s procurement. Notable entrepreneurs leading this phenomenon include Elon Musk and Jeff Bezos, who head SpaceX and Blue Origin respectively. Small satellites (e.g. CubeSats), internet by satellite (e.g. Starlink), and space tourism represent other disruptions that have recently received attention. We believe that effectively navigating these many disruptions that form the New Space phenomenon requires adopting a systemic perspective.
Methods
34 The research aims to study the scope, magnitude, and interconnections of multilevel socio-technical disruptions collectively known as the New Space phenomenon (Dos Santos Paulino, 2020). The selected approach for this study involves employing bibliometric analysis with the computational software tool VOSviewer (Van Eck, Waltman, 2022). This software has been applied to study disruptions in various contexts, as demonstrated in the works of Dos Santos Paulino and Pulsiri (2022), or Jiang and Liu (2023).
35 To delve into VOSviewer in detail, it is essential to grasp that it is a sophisticated software tool grounded in the principle of the analysis process (Van Eck, Waltman, 2022). Bibliometrics, as its core, involves the analysis and measurement of scholarly publications, their content, and their relationship, which can uncover patterns, trends, and connections in a specific field (Kongthon, 2004). Therefore, VOSviewer plays an essential role in this process as one of the well-known tools that equips researchers with a powerful means to visualize the complex web of relationships among keywords, authors, documents, and entities. In addition, VOSviewer software can generate network visualization with the formation of clusters for cluster analysis.
36 By comparing the bibliometric-based analysis processes used in previous innovation studies (Moro et al., 2018; Dos Santos Paulino, Pulsiri, 2022; Jiang, Liu, 2023), we can conclude that measuring disruptive innovations involves five main steps adapted from Fosso-Wamba et al. (2013), Touzard et al. (2015) and Escobar et al. (2021): 1) setting the scope of the research and plan for the bibliometric process, 2) selecting databases, defining the search string and extracting publications, 3) screening publications, 4) selecting publications for inclusion, and 5) analyzing and reporting the results (see Figure 2).
37 These steps, illustrated in Figure 2, are detailed below to provide guidance for applying this method:
Step 1: Setting the scope and plan for the bibliometric process
38 The study employs a bibliometric-based analysis approach, with the combination of some bibliometric analysis techniques to address the research objectives: specifically, to study the scope, magnitude, and interconnections within a multilevel socio-technical system. In addition, the model, presented in Figure 1, is developed to use for the case of space ecosystem.
Step 2: Database selection, defining search string and extracting publications
39 Keyword searches are performed in a series of five databases, which are Business Source Complete, Science Direct, Econlit, JSTOR, and Scopus. These databases are relevant for extracting scientific publications. The publications must be English-written journal articles published between 2005 and 2021. The search terms in the categories of new space, commercial space, private space, and disruptive space, as shown in Table 1, are used for extracting a preliminary selection of 23,026 publications. These search terms are used to retrieve relevant publications from databases, enabling the characterization of the current disruptions within the case of space ecosystem (Vernile, 2018; ESPI, 2019; Benaroya, Dos Santos Paulino, 2023).
Publication retrieval by databases
| Database/ Keyword | New Space | Commercial Space | Private Space | Disruptive Space | Total |
|---|---|---|---|---|---|
| Business Source Complete | 1,228 | 1,640 | 601 | 468 | 3,937 |
| Science Direct | 6,158 | 4,051 | 2,811 | 1,461 | 14,481 |
| Econlit | 29 | 47 | 11 | 13 | 100 |
| JSTOR | 136 | 78 | 29 | 6 | 249 |
| Scopus | 2,558 | 1,022 | 525 | 154 | 4,259 |
| Total | 10,109 | 6,838 | 3,977 | 2,102 | 23,026 |
Publication retrieval by databases
Step 3: Screening publications by title and abstract
40 In the initial screening process, the publications extracted from the five selected databases will undergo filtration by checking their titles and abstracts. Redundant publications will be excluded from the record. In addition, two experts will check the abstracts and remove irrelevant ones from the scope of New Space, resulting in 4,752 publications.
Step 4: Selecting publications for inclusion
41 After screening scientific publications by checking their titles and abstracts, the remaining publications will proceed to a relevancy check. Therefore, 3,324 irrelevant publications that are not related to disruptions within the space ecosystem will be excluded from the record, resulting in 1,428 publications.
Step 5: Analysis and Reporting
42 The selected publications that have passed all previous steps will go through analysis by using the bibliometric approach. This last step is divided into two parts:
- Content analysis and frequency counting. In this part, all selected publications are organized within Mendeley, a reference management software. As a result, a minimum of two qualified experts will read and analyze abstracts stored in Mendeley. They will identify the disruption clusters and nodes of disruptions by tagging them based on publications (Kongthon, 2004; Chae 2022). Additionally, following the recommendation of Gueguen (2022), the analysis effectively involves reading abstracts to assess content. The finding from this stage will be summarized in alignment with the model (Figure 1) to elucidate the scope of the systemic disruption formed by particular disruptions. Simultaneously, the tagging of each disruptive cluster (from 2005-2021) will be counted annually to measure its magnitude and evolution.
- Cluster analysis in the context of co-word analysis and network visualization. After gaining insights from the previous part, we will apply cluster analysis, using co-word analysis and network visualization with the bibliometric software VOSviewer (Van Eck, Waltman, 2022). This process begins with downloading a csv file containing details of selected publications that have passed the screening process. Following this, the VOSviewer software will compute and generate a list of keywords. Subsequently, data cleaning is required to select only keywords representing nodes of disruptions and group them into their respective disruption cluster within the framework of the proposed model in Figure 1. Meanwhile, irrelevant keywords will be excluded during this process. After that, the co-word analysis and network visualization function will present the disruption clusters within a network. The disruption clusters that closely relate to each other will exhibit a strong connection, indicating significant interconnections (Dos Santos Paulino, Pulsiri, 2022).
The five steps of the bibliometric analysis
The five steps of the bibliometric analysis
Results
The Scope of the Systemic Disruption
44 Analysis of the 1,428 selected scientific publications is used to characterize the scope of New Space systemic disruption, which we regard as a system of multilevel socio-technical disruptions.
45 After completing the bibliometric process, our analysis, as shown in Figure 3, reveals that New Space represents a systemic disruption, comprised of six main disruption clusters: (1) new technology, (2) new policy, (3) new market, (4) new entrant, (5) new process, (6) new funding. Furthermore, our results indicate that, within each cluster, there are several disruption nodes representing sub-dimensions of their parent clusters. To enhance clarity in Figure 3, we have grouped similar nodes within the same box. These clusters and nodes encompass macro, meso and micro socio-technical disruptions.
46 In Figure 3, the new technology cluster (TC) features the technological disruptions in new spacecraft technology, referring to disruption nodes in reusable launch vehicles, interplanetary spacecraft, space robotics, and nuclear technology. These disruption nodes revolutionize the engineering design for space vehicle development to use in outer space, which also results in increasing valuable economic activities; whereas the small satellites disruption node refers to the miniaturization of satellites causing the transition from costly large traditional satellites to cost-effective small modernized satellites. This disruption node is the backbone for the formation of mega-constellations that offers more valuable services such as the Internet from space. However, the rapid increase in the small satellite population is currently provoking some challenging issues, in particular space debris. By the way, there are disruption nodes in green space technologies that appeared to secure the environment of Earth and space, including SSA tech [1], and STM tech [2].
47 The new policy cluster (POC) represents policy disruptions in the space ecosystem through commercial space policy and law (Figure 3). The disruption nodes in this cluster include innovative policy, procurement policy, export control relaxation, and international partnerships. The NASA COTS [3] initiative in 2006 and the Artemis Accord [4], signed in 2020, are central disruption nodes that impact commercial space partnerships. The increasing concerns about space debris and the ecological impact of space activities have led to the development of new policies to address these issues, including space debris governance, space sustainability, and planetary protection. Space organizations are progressively adjusting their activities to minimize space debris and ecological impact.
The scope of the New Space systemic disruption
The scope of the New Space systemic disruption
48 In the new market cluster (MC), market disruptions are generated by creating new commercial spaceflight and space habitat markets (Figure 3). These refer to disruption nodes in space tourism and hotels, orbital/sub-orbital space flights, commercial ISS, and moon base. These disruption nodes also include the space medicine and pharmacy market, which aims to save the lives of astronauts and people on Earth. Simultaneously, there is market disruption in commercial space mining, including disruption nodes that aim to extract natural resources from outer space to create commercialized values, such as asteroid mining and moon mining. Space mining activities could emerge as a pivotal solution to address the depletion of Earth’s resources (including minerals and metals). Finally, there is the initiation of commercial satellite services to engage with organizations to consider new markets related to satellite infrastructure. This includes disruption nodes such as the Internet from space (e.g. Starlink), SSA, STM, OOS (On Orbit Servicing) and ADR (Active Debris Removal).
49 In the new entrant cluster (EC), we consider new entrants as disruptors that can bring new opportunities and threats in the space ecosystem (Figure 3). These new entrants encompass both supply and demand roles, such as firms run by entrepreneurs from existing spacefaring countries (e.g. O3b Networks, OneWeb, SpaceX, and Team Indus). Our results also show the entry of firms (e.g. ICEYE, Zero 2 Infinity) and space agencies from new spacefaring countries, such as Mexico, Portugal, South Africa, and United Arab Emirates (e.g. AEM, PTSPACE, SANSA, UAESA, respectively).
50 Furthermore, in the new process cluster (PRC), there are process disruptions we grouped in: nodes referring to vertical integration, including the modularity process and 3D printing, and nodes referring to value creation networks, including open innovation and digital transformation.
51 Finally, in the new funding cluster (FC), there are new funding approaches that disrupt the way funding support is provided in the space ecosystem, originally funded by public money. The rise of private funding includes commercial space ventures, PPP (Public-Private Partnerships), and SPAC (Special-Purpose Acquisition Companies).
52 In summary, New Space systemic disruption represents a system of many socio-technical multilevel disruptions that occurred between 2005 and 2021. We navigate this systemic disruption by delineating its scope, which is comprised of six disruption clusters and associated nodes. This is the preliminary step toward measuring the magnitude and interconnections of New Space systemic disruption.
Magnitude
53 The magnitude measurement of the New Space systemic disruption was conducted through an extensive analysis of the 1,428 selected publications for this research. In accordance with the outlined bibliometric process in Figure 2, every publication passed through a rigorous check, during which it was meticulously categorized and labeled with its respective disruption clusters.
54 Table 2 displays the magnitude of disruptions between 2005 and 2021. The results indicate that over half of the systemic disruption pertains to the new technology cluster (TC = 52.2%). The new policy cluster ranks second (POC = 23.1%), while the new market cluster ranks third (MC = 13.2%). The new entrant (EC = 5.3%), new process (PRC = 4.7%), and new funding approach (FC = 1.2%) clusters follow in descending order of magnitude. The top three disruption clusters, namely new technology, new policy, and new market, account for 88.5% of systemic disruption, and thus they play a critical role in shaping New Space phenomenon.
Magnitude of disruptions during 2005-2021
| Disruption | Systemic disruption | Tech (TC) | Policy (POC) | Market (MC) | Entrant (EC) | Process (PRC) | Funding (FC) |
|---|---|---|---|---|---|---|---|
| Publications | 1428 | 746 | 330 | 189 | 75 | 67 | 21 |
| Note: Tech = New technology, Policy = New policy, Market = New market, Entrant = New entrant, Process = New process, Funding = New funding approach | |||||||
Magnitude of disruptions during 2005-2021
55 When examining the magnitude of New Space systemic disruption from a dynamic perspective, Figure 4 demonstrates a global trend of growth from 2005 to 2021. Between 2005 and 2012, an emerging stage is evident, indicating a slow and disorderly evolution of systemic disruption. Furthermore, the troughs in 2007, 2009, and 2012 suggest that systemic disruption during this stage was fragile and immature. However, from 2012 to 2021, a marked takeoff is observed, and the troughs no longer jeopardize the survival of systemic disruption, indicating that the maturity of the disruption is rapidly increasing. During this second stage, systemic disruption becomes a major phenomenon that managers and policy makers in the realm of space ecosystem need to seriously consider when setting their innovation agendas (including R&D, innovation, and strategy roadmaps).
Disruption evolution
Disruption evolution
56 Analyzing the evolution of disruption clusters individually offers a complementary understanding to navigate the New Space systemic disruption. Figure 4 depicts substantial takeoffs among the new technology (TC), new policy (POC), and new market (MC) disruptions, whereas the new entrant (EC), new process (PRC), and new funding (FC) disruptions display sluggish trends. The innovation agendas of managers and policy makers must be in the need of paying more attention to these driving disruptions.
Cluster Interconnections
57 After gaining insights from the previous results regarding the scope of systemic disruption and the magnitude of each disruption cluster, we complement these findings by clarifying the interconnections among the six disruption clusters characterizing New Space systemic disruption. A cluster analysis in the context of co-word analysis and network visualization was conducted by using VOSviewer software (Jiang, Liu, 2023), with the six main defined disruption clusters as illustrated in Figure 3. Consequently, the software grouped the keywords into each disruption cluster (new tech, new policy, new market, new entrant, new process, and new funding) and analyzed their interconnections over the 2005-2021 timeframe.
58 Figure 5 provides a visualization that reveals the interconnections between the disruption clusters. The size of each dot reflects the extent of keyword co-occurrences related to the nodes of disruptions within its respective clusters, indicating cluster significance (Van Eck, Waltman, 2022). Additionally, the thickness of the line, or the link strength, signifies the strength of relationships between two disruption clusters (Van Eck, Waltman, 2022). The sum of all link strengths is referred to as the total link strength, which can indicate the degree of interconnectedness of a cluster relative to others.
The disruption cluster’s interconnection in systemic disruption (2005-2021)
The disruption cluster’s interconnection in systemic disruption (2005-2021)
59 The results presented in Figure 5 demonstrate that the disruption clusters are connected within the green and red groupings. In the green group, new technology emerges as the most interconnected disruption cluster (TC: 140 co-occurrences, 343 total link strength), followed by new market (MC: 103, 207), and new process (PRC: 18, 71).
60 On the other hand, the red group highlights new policy as the most interconnected disruption cluster (POC: 133 co-occurrences, 299 total link strength, followed by new entrant (EC: 39, 116), and new funding approach (FC: 13, 45)).
61 Thereafter, the new technology cluster (TC) is located in the center of the network visualization and is strongly connected to new market (MC) and new policy (POC) clusters, signifying the significant influence of technological disruption on systemic disruption. In conclusion, the six disruption clusters are closely linked, suggesting co-evolution among the multilevel socio-technical disruptions forming the New Space systemic disruption.
Co-evolution of Disruptions
62 Examining the co-evolution mechanism helps us to comprehend how New Space systemic disruption is shaped through time. We achieve this by dynamically analyzing the magnitude, scope, and interconnections of the systemic disruption depicted in Figures 3, 4, and 5.
63 New Space systemic disruption is first shaped by the new technology disruption cluster (TC). The cost of space technologies decreased significantly in the mid-2000s due to the growing trend of satellite miniaturization, supported by small satellites such as the first CubeSat, launched into outer space in 2006. The miniaturization trend stimulated the development of the first constellations of small satellites (TC) from new commercial entrants among spacefaring countries, such as O3b Networks, RapidEye, and WorldView in the late 2000s (EC). These new entrants built their development on new funding approaches (FC) in which commercial funding (e.g. venture capital) became more important at the expense of public funding.
64 The new technology (TC) and the new market (MC) clusters belong to the red group of clusters in Figure 5, which denotes a tight co-evolution of technology and market disruptions shaping the evolution of New Space systemic disruption. For example, in the mid-2000s the miniaturization of satellites pushed new opportunities in markets such as the Internet from space and Earth observation, and at the same time, the growth of demand for internet access on white zones (e.g. rural areas, flights) and Earth imagery (e.g. navigation, natural resources management) pulled in new space technologies. We notice that the co-evolution within systemic disruption is shaped by technology push and market pull forces that progressively extended the scope and the magnitude of the New Space.
65 Figures 4 and 5 also indicate that the co-evolution mechanism characterizing New Space systemic disruption heavily relies on the influence of a new policy cluster (POC). In 2006, NASA experimented with a new procurement policy, referred to as COTS, to encourage the development of new commercial spacecraft (TC) by private US companies. NASA shifted from traditional cost-plus contracts [5] in which the final cost is not predetermined, to fixed-cost contracts. This experiment in space procurement stimulated the emergence of New Space systemic disruption and extended its scope to new entrant commercial companies run by entrepreneurs (EC) who competed with new, immature technologies (TC) (i.e. SpaceX and Virgin Galactic run by Elon Musk and Richard Branson, respectively). In the early 2010s, competing incumbent firms in the US and Europe argued that many new technologies in this cluster, such as reusable launchers, were a dead end and that New Space systemic disruption in general would not last long. However, the successes of SpaceX proved the capacity of new entrants (EC) to deliver the expected value. This aftermath reinforced the new fixed-cost contract practices (POC), as well as many of the new technologies (TC) and processes (PRC, including open innovation and vertical integration) introduced by new entrants (EC). All of these interconnected disruptions supported cost reduction, which in return amplified the magnitude of systemic disruption and extended its scope. For example, we observe the development of new markets (MC), and the entry of firms and space agencies from non-spacefaring countries (e.g. AEM, UAESA, Zero 2 Infinity) (EC).
66 After 2012, the takeoff of New Space systemic disruption visible in Figure 4 revealed a noticeable surge in the magnitude of disruptions simultaneously pushed and pulled by the technology (TC), market (MC), and policy (POC) disruption clusters. This corresponds to new disruptions that developed particular interconnections extending the scope of New Space systemic disruption. For example, in 2013, the United States relaxed the export control regulation (POC) to open up international market opportunities (MC) for domestic new space technologies (TC). This brought in the entry of new customers (EC) to buy US space technologies. In 2017, President Trump passed the initiative for a program aiming to return to the Moon and travel to Mars, referred to as the Artemis Accord, the twin sister of the 1960s Apollo program (POC). The result of the Artemis Accord is that many spacefaring and non-spacefaring countries can join the program (EC) and benefit from mainstream research in space exploration. In 2018, FCC granted SpaceX approval for the initial 4,425 satellites of its future mega-constellation Starlink (TC), and in 2020, NASA initiated the asteroid mining contracts (MC) with new commercial companies (EC). These more ambitious socio-technical disruptions brought in new funding approaches (FC), such as PPP and SPAC, in which individuals and private organizations support higher risks.
67 After 2012, the rapid growth of New Space systemic disruption also led to new challenges that stimulated new disruptions. This ultimately shaped the interconnections and the scope of systemic disruption toward more sustainability. For example, the development of mega-constellations (TC, e.g. Starlink) and space tourism (MC) raised the issues of space debris and ecological impact from space activities that generated a threat for the development of New Space systemic disruption itself. To mitigate this risk we observe the renewal of space governance (SSA, STM) and planetary protection (POC), as well as the launch in 2020 of the first Earth’s Active Debris Removal (ADR) program to clean up space (TC, MC).
Discussion and Conclusion
68 Christensen is credited with pioneering the theory of disruptive technology, which is based on Schumpeter’s concept of creative destruction. This theory suggests that innovative incumbents can be disrupted by new entrants who serve customers with a nascent technology that eventually becomes a substitute due to successful efforts to improve its performance.
69 However, Christensen himself acknowledged that his theory should engage in a systemic perspective and not only focus on technological disruptions (Christensen, Raynor, 2003; Christensen et al., 2018). Therefore, this research provides novel findings to help solve the limitation that restricts the applicability of the theory to such broad contexts.
70 The aim of this research is to expand the applicability of disruptive innovation theory by studying the scope, magnitude, and interconnections of multilevel socio-technical disruptions, referred to as systemic disruption (Figure 1). Instead of examining the impact of the disruptions on the ecosystem, our approach is to thoroughly characterize the disruptions themselves.
71 We chose to study the space ecosystem between 2005 and 2021 because it is currently experiencing many multilevel socio-technical disruptions, known as the New Space phenomenon (Vernile, 2018; ESPI, 2019; Dos Santos Paulino, 2020). We employed a bibliometric analysis approach due to its applicability to navigating those disruptions (Pulsiri, Vatananan-Thesenvitz, 2020).
72 As a result, our research identified the scope of New Space systemic disruption, which is characterized by several disruption nodes grouped in six disruption clusters: new technology (TC), new policy (POC), new market (MC), new entrant (EC), new process (PRC), and new funding approach (FC) (Figure 3). All these disruptions come together, with new technology, new policy, and new market forming the most influential clusters within the systemic disruption owing to the highest magnitude (Figure 4).
73 The cluster analysis in the context of co-word analysis and network visualization also reveals the interconnections among the six disruption clusters (Figure 5), providing insights for co-evolution, and thus suggesting that systemic disruption is pushed and pulled by the most influential disruptions. Consequently, it can conclude that new technology, new policy, and new market disruption clusters shape the magnitude and scope of New Space systemic disruption between 2005 and 2021.
74 The development of the concept of systemic disruption contributes to bringing some advances from systemic perspective into the theory of disruptive innovation. By considering disruptions as a system, we enlarge the applicability of the theory to systemic contexts in which the disruption cannot be studied as an individual new technology but involves several socio-technical disruptions embedded at different levels (Hang et al., 2011; Dos Santos Paulino, Le Hir, 2016; Dos Santos Paulino, Pulsiri, 2022). This is the case in many current disruptions such electric cars and artificial intelligence. More generally, this research echoes the current interest of the research community in networks, platforms, and ecosystems (Christensen et al., 2018; Theodoraki, Messeghem, 2017).
75 This study also contributes to demonstrating that bibliometric analysis is a promising measurement approach in the field of innovation, as suggested by the Oslo Manual (OECD/Eurostat, 2005), and subsequently implemented by scholars (Moro et al., 2018; Jiang, Liu, 2023). We show that scientific publications can serve as an indicator to study disruptive innovations. Publications offer new options for data collection and analysis complementing traditional innovation indicators, such as R&D expenditure, patents, and new product launches. This research also provides guidance to other researchers in applying bibliometric analysis to study disruptive innovations. We suggested five main steps for analyzing the scope, magnitude, and interconnections of disruptive innovations, which are detailed in the paper (Figure 2). This contributes to the transferability of bibliometric methods to other studies in the domain of innovation.
76 The implications of our findings for the actors of the ecosystem, including managers and policy makers, are not limited to the space ecosystem. In many ecosystems these actors must be able to understand the systemic nature of disruptions for setting a multilevel socio-technical innovation agenda (including R&D, innovation and strategy roadmaps). For example, our research provides guidance for incumbent organizations not to overlook the influence of new policies and the different types of new entrants when evaluating the magnitude and the scope of disruptions in their roadmaps.
77 Finally, the theory of disruptive innovation, especially when linked to the systemic perspective, possesses the potential for continuous development and provides greater value for the benefit of society. This was Christensen’s intention, as he always welcomed new findings to expand upon his theory, stating that “Cumulative effort has produced a rich and useful theory, but many opportunities for further research remain unexplored” (Christensen et al., 2018, p. 1052).
References
- ANTONIO, J. L., KANBACH, D. K. (2023), Contextual Factors of Disruptive Innovation: A Systematic Review and Framework, Technological Forecasting and Social Change, 188, 122274.
- ANSARI, S., GARUD, R., KUMARASWAMY, A. (2016), The Disruptor’s Dilemma: TiVo and the U.S. Television Ecosystem, Strategic Management Journal, 37(9), 1829-1853.
- BARBAROUX, P. (2016), The Metamorphosis of the World Space Economy: Investigating Global Trends and National Differences among Major Space Nations’ Market Structure, Journal of Innovation Economics & Management, 20(2), 9-35.
- BENAROYA, C., DOS SANTOS PAULINO, V. (2023), Le New Space: Ruptures et transformations de l’écosystème spatial, Technologie et innovation, Forthcoming.
- BÖRNER, K., POLLEY, D. E. (2014), Visual Insight: A Practical Guide To Making Sense Of Data, Cambridge, The MIT Press.
- CHAE, B. (2022), Mapping the Evolution of Digital Business Research: A Bibliometric Review, Sustainability, 14(2), 6990.
- CHRISTENSEN, C. M., BOWER, J. (1996), Customer Power, Strategic Investment, and the Failure of Leading Firms, Strategic Management Journal, 17(3), 197-218.
- CHRISTENSEN, C. M. (1997), The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail, Boston, Harvard Business School Press.
- CHRISTENSEN, C. M., RAYNOR, M. (2003), The Innovator’s Solution: Creating and Sustaining Successful Growth, Boston, Harvard Business Review Press.
- CHRISTENSEN, C. M. (2006), The Ongoing Process of Building A Theory of Disruption, Journal of Product Innovation Management, 23(1), 39-55.
- CHRISTENSEN, C. M., MCDONALD, R., ALTAMN, E. J., PALMER, J. E. (2018), Disruptive Innovation: An Intellectual History and Directions for Future Research, Journal of Management Studies, 55(7), 1043-1078.
- CROSSAN, M., APAYDIN, M. (2010), A Multi-dimensional Framework of Organizational Innovation: A Systematic Review of the Literature, Journal of Management Studies, 47(6), 1154-1191.
- DANNEELS, E. (2004), Disruptive Technology Reconsidered: A Critique and Research Agenda, Journal of Product Innovation Management, 21(4), 246-258.
- DOS SANTOS PAULINO, V., LE HIR, G. (2016), Industry Structure and Disruptive Innovations: The Satellite Industry, Journal of Innovation Economics and Management, 20(2), 37-60.
- DOS SANTOS PAULINO, V. (2020), Innovation Trends in the Space Industry, London, John Wiley & Sons.
- DOS SANTOS PAULINO, V., GUDMUNDSSON, S. (2021), Market Diffusion of Industrial Products and Regulatory Barriers to Adoption: The Case of Satellites, Journal of Innovation Economics & Management, 36, 117-138.
- DOS SANTOS PAULINO, V., PULSIRI, N. (2022), Safeguarding Earth and Space’s Environment: Issues and Trends towards Sustainable Development, International Journal of Technology Management and Sustainable Development, 21(3), 353-376.
- ESCOBAR, O. R., LEONE, L., MALAFRONTE, P., MELE, S. (2021), The Effect of Telemedicine on Patients’ Wellbeing: A Systematic Review, Journal of Innovation Economics & Management, 35, 9-31.
- ESPI, (2019), Evolution of the role of space agencies. Retrieved from https://www.espi.or.at/wp-content/uploads/2022/06/ESPI-Public-Report-70-Evolution-of-the-Role-of-Space-Agencies-Full-Report.pdf
- FOSSO-WAMBA, S., ANAND, A., CARTER, L. (2013), A Literature Review of RFID-Enabled Healthcare Applications and Issues, International Journal of Information Management, 33(5), 875-891.
- GEELS, F. W. (2011), The Multi-level Perspective on Sustainability Transitions: Responses to Seven Criticisms, Environmental Innovation and Societal Transitions, 1(1), 24-40.
- GUEGUEN, G. (2022), PME et entrepreneuriat: Une analyse lexicométrique et structurelle des travaux publiés dans la revue internationale PME (1988-2020), Revue internationale PME, 35(2), 23-48.
- HANG, C. C., CHEN, J., YU, D. (2011), An Assessment Framework for Disruptive Innovation, Foresight, 13(5), 4-13.
- IANSITI, M., LEVIEN, R. (2004), Strategy as Ecology, Harvard Business Review, 82(3), 68-78.
- JIANG, Y., LIU, X. (2023), A Bibliometric Analysis and Disruptive Innovation Evaluation for the Field of Energy Security, Sustainability, 15(2), 969.
- KILKKI, K., MÄNTYLÄ, M., KARHU, K., HÄMMÄINEN, H., AILISTO, H. (2018), A Disruption Framework, Technological Forecasting and Social Change, 129, 275-284.
- KIM, S., PARBOTEEAH, K., CULLEN, J., LIU, W. (2020), Disruptive Innovation and National Cultures: Enhancing Effects of Regulations in Emerging Markets, Journal of Engineering and Technology Management, 57, 101586.
- KONGTHON, A. (2004), A Text Mining Framework for Discovering Technological Intelligence to Support Science and Technology Management, PhD Thesis, Georgia Institute of Technology.
- LETAIFA, S. B., EDVARDSSON, B., TRONVOLL, B. (2016), The Role of Social Platforms in Transforming Service Ecosystems, Journal of Business Research, 69(5), 1933-1938.
- MEYER, P. E., WINEBRAKE, J. J. (2009), Modeling Technology Diffusion of Omplementary Goods: The Case of Hydrogen Vehicles and Refueling Infrastructure, Technovation, 29(2), 77-91.
- MORO, A., BOELMAN, E., JOANNY, G., GARCIA, J. L. (2018), A Bibliometric-Based Technique to Identify Emerging Photovoltaic Technologies in A Comparative Assessment with Expert Review, Renewable Energy, 123, 407-416.
- NICHOLAS, T. (2021), How History Shaped the Innovator’s Dilemma, Business History Review, 95(1), 121-148.
- ÖBERG, C. (2023), Disruption and the Ecosystem: The Changing Roles of Ecosystem Stakeholders in the Course of Disruption, Technological Forecasting and Social Change, 194, 122679.
- O’REILLY, C., BINNS, A. J. M. (2019), The Three Stages of Disruptive Innovation: Idea Generation, Incubation, and Scaling, California Management Review, 61(3), 49-71.
- OECD, EUROSTAT, (2005), Oslo Manual: Guidelines For Collecting And Interpreting Innovation Data, Paris, OECD Publishing.
- OECD, (2017), The Next Production Revolution, Paris, OECD Publishing.
- OECD, (2019), What Works in Innovation Policy? New Insights for Regions and Cities: Developing Strategies for Industrial Transition, Paris, OECD Publishing.
- OTLET, P. (1934), Traité de documentation : Le livre sur le livre, Bruxelles, Palais Mondial.
- PALMIÉ, M., WINCENT, J., PARIDA, V., CAGLAR, U. (2020), The Evolution of the Financial Technology Ecosystem: An Introduction and Agenda for Future Research on Disruptive Innovations in Ecosystems, Technological Forecasting and Social Change, 151, 119779.
- PECHMAN, F. V., MIDLER, C., MANIAK, R., CHARUE-DUBOC, F. (2015), Managing Systemic and Disruptive Innovation: Lessons from the Renault Zero Emission Initiative, Industrial and Corporate Change, 24(3), 677-695.
- PELTONIEMI, M., VUORI, E. (2008), Business Ecosystem as the New Approach to Complex Adaptive Business Environments, in Proceedings of eBusiness Research Forum (Vol. 2, No. 22), 267-281.
- PRITCHARD, J. (1969), Statistical Bibliography or Bibliometrics?, Journal of Documentation, 25(4), 348-349.
- PULSIRI, N., VATANANAN-THESENVITZ, R. (2020), Drones in Emergency Medical Services: A Systematic Literature Review with Bibliometric Analysis, International Journal of Innovation and Technology Management, 18(4), 2097001.
- SCHMIDT, G. M., DRUEHL, C. T. (2008), When is A Disruptive Innovation Disruptive?, Journal of Product Innovation Management, 25(4), 347-369.
- SCHUMPETER, J. A. (1911), The Theory of Economic Development: An Inquiry into Profits, Capital, Credit, Interest, and Business Cycle, Quebec, Transaction Publishers.
- SCHUMPETER, J. A. (1939), Business Cycles, New York, Mcgraw-Hill.
- SCHUMPETER, J. A. (1942), Capitalism, Socialism, and Democracy, London and New York, Routledge.
- SI, S., CHEN, H. (2020), A Literature Review of Disruptive Innovation: What It Is, How It Works and Where It Goes, Journal of Engineering and Technology Management, 56(8), 101568.
- SILVA, J. P. N., GRÜTZMANN, A. (2023), The Evolution of the Disruptive Ecosystem: A Framework Integrating Disruption, Ecosystems, and Business Models, European Journal of Innovation Management, 26(5), 1255-1270.
- TEECE, D. J. (2007), Explicating Dynamic Capabilities: The Nature and Microfoundations of (Sustainable) Enterprise Performance, Strategic Management Journal, 28(13), 1319-1350.
- THEODORAKI, C., MESSEGHEM, K. (2017), Exploring the Entrepreneurial Ecosystem in the Field of Entrepreneurial Support: A Multi-Level Approach, International Journal of Entrepreneurship and Small Business, 31(1), 47-66.
- TOUZARD, J.-M., TEMPLE, L., FAURE, G., TRIOMPHE, B. (2015), Innovation System and Knowledge Communities in the Agriculture and Agrifood Sector: A Literature Review, Journal of Innovation Economics & Management, 17, 117-142.
- TRIPSAS, M. (1997), Unraveling the Process of Creative Destruction: Complementary Assets and Incumbent Survival in the Typesetter Industry, Strategic Management Journal, 18(S1), 119-142.
- VAN ECK, N. J., WALTMAN, L. (2022), VOSviewer Manual (version 1.6.18), Leiden, Universitiet Leiden.
- VERNILE, A. (2018), The Rise of Private Actors in the Space Sector, Switzerland, Cham, Springer.
Notes
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[1]
Space Situational Awareness technologies include a range of sensors, telescopes, and computational tools to track, monitor, and predict the movements of objects in Earth’s orbit.
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[2]
Space Traffic Management technologies refer to the planning, coordination, and regulation of the operations of spacecraft in Earth’s orbit.
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[3]
Commercial Orbital Transportation Services.
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[4]
A project led by the United States aimed at bringing humans back to the Moon by 2025, with the ultimate objective of extending space exploration to Mars and other celestial bodies.
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[5]
NASA pays the contractor for the actual cost of the work performed, plus an additional amount to cover the contract’s profit.
