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Military-Technical Transformation: Preparing an Index to Enable Comparative Research

Project

For three decades, military strategists have claimed that information superiority would increasingly minimize or even replace firepower through the application of advanced information technologies on the battlefield (sensors, computers, automation etc.) (Owens 2001; Arquilla/Ronfeldt 1997; Libicki  1996).

How this revolution affects the probability of international conflict or the effectiveness of peacebuilding is fiercely debated between political decision-makers and from within the scientific community alike. Critics point to moral dilemmas, the erosion of international law, the marginalization of democratic accountability mechanisms (for example with regard to drone strikes) and higher risks of unintended conflict escalation (Bergen/Rothenberg 2015; Sauer 2014; Kaag und Kreps 2014; Boyle 2013; Neuneck 2012; Schörnig 2011).

What is missing though is a comprehensive understanding of the driving factors of state investments in areas such as satellite sensors, drone technology or remotely-guided missiles. Given the large number of potential explanatory variables (see Mathers 2002; Terriff/Osinga 2010: 199-200; Giles 2014; Giles/Monaghan 2014; Laird/Mey 1999; Forster/Edmunds/Cottey 2002; Adams/Ben-Ari 2005; Farrell 2008; Gareis 2011; King 2014; Foley/Griffin/McCartney 2011; Thiele 2011) and, arguably, the confounding influence of more than a few other factors, there clearly is a need to supplement qualitatively gained knowledge through quantitative research designs.

Nevertheless, multicausal large-N studies cannot be conducted as long as we do not have a standardized measurement of the dependent variable, namely the timing and intensity of state investments in information technology-centric military equipment. The research project seeks to fill this critical gap.

To this purpose, data about unmanned aerial vehicles (UAVs), satellites and guided missiles have been aggregated into an index that enables a standardized ranking of the capabilities of each state (see table).

The data availabaility issues and conceptional criteria that guided the selection of the indicators are explained in the ‚Research Aims & Conceptional Foundation‘ section. A detailed look at our data and a set of download options are provided in the ‚Data‘ section.

Amongst other things, our data can be used to plausibilize two different logics of military-technological diffusion:

Structural-realist explanations of the military diffusion processes are based on the logic of systemic competition (Waltz 1979: 127) and a „technological imperative“ (Buzan/Herring 1998: 50-51; Resende-Santos 1996, 2007). Variances in military-technological capabilities result from the unequal resource bases (measurable in the gross domestic product) of different countries. Our data shows that, unsurprisingly, unequal resources clearly have some predictive power with regard to the military-technical capabilities. Yet other factors must play a role as well because the correlation is far from being perfect. A case in point are low MTTI-rankings of Latin American states with considerable economic resource bases (see „Data 2015“).

For illustrative purpose, see this comparison of the GDP and Index Value:

In contrast, liberal accounts of the ongoing military transformation, amongst other factors, point to the restraining influence of casualty-shy electorates on democratic security policy-making (Schörnig 2014; Sauer/Schörnig 2012: 371; Mandel 2004: 13-14). From this follow strong incentives to acquire precision-guided and automated military capabilities in order to minimize the death toll of military campaigns. Therefore, democratic regimes should be more eager to invest in satellite sensors, drone technology and guided missiles than their authoritarian counterparts.

Our index, however, only partially confirms this logic. While there are indeed plenty of democracies (as measured by their Polity IV index scores) within top-rank positions, other democracies (for example Japan and, again, Brazil and Argentine) noticeably lag behind authoritarian countries of comparable size. What is more, small Arab autocracies such as the United Arab Emirates combine low Polity IV scores with leading MTTI positions (see „Data 2015“). The following picture shows some leading democracies and autocratic regimes as well as outliers.

Overall, these rudimentary plausibility probes lend support to the argument that we need to consider the influence of multiple factors and their interplay in contributing to top-ranking or low-ranking positions. One way to move forward is represented by the multivariate large-N studies, testing and assessing the relative explanatory power of a range of factors. Alternatively, a fuzzy-set qualitative comparative analysis (QCA) would offer a way to identify specific combinations of factors that could each constitute a path to transformation leadership or low-ranking positions respectively. In the latter case, the numerical values of the index should be used to demarcate the categories of leaders, followers, laggers-behind etc.

 

 

 

 

Military-Technical Transformation: Preparing an Index to Enable Comparative Research

Research aims & Conceptional Foundation

While there is a popular narrative juxtaposing commercial entrepreneurship to change-resistant militaries and emphasizing spin-offs from civil information-technology to military systems only, in reality there seems to be a much more complex interplay of civil and military agency with regard to technological transformation and diffusion (Weiss 2014). Preliminary evidence also calls into question the simple idea of a „technological imperative“ (Buzan/Herring 1998: 50-51) that forces states to spend as much as possible on militarily effective and efficient technologies. In short, the causes of military investments are far from beeing self-evident and „politics matters“. Yet the causes of the recent military technical transformation are still underresearched as compared to the effects of some applications such as, for example, drone technology.

Against this backdrop, the research project aims at a better understanding of the driving factors of military investments in information-technology equipment. Different competing explanations – ranging from the regime type to security threats ((see Mathers 2002; Terriff/Osinga 2010: 199-200; Giles 2014; Giles/Monaghan 2014; Laird/Mey 1999; Forster/Edmunds/Cottey 2002; Adams/Ben-Ari 2005; Farrell 2008; Gareis 2011; King 2014; Foley/Griffin/McCartney 2011; Thiele 2011) – have so far been tested almost exclusively through a few qualitative case study designs. Methodologically, these studies focus on only a few, predominantly Western, countries. Furthermore, they do not necessarily clarify their case selection criteria. Our knowledge of the dynamics behind the military adaption and diffusion of information technologies is therefore not only limited but probably also biased towards relatively well-documented Western cases. A quantitative comparative analysis that includes cases from a non-Western context is needed in oder to alleviate these shortcomings.

source: istockphoto, Alexei Cruglicov

A necessary first step to fill this critical research gap is to generate and provide a standardized measurement of relevant military capacities. To that purpose, we have aggregated data about unmanned aerial vehicles (UAVs), satellites and guided missiles into an index that enables a standardized ranking of the capabilities of each state. Besides issues of data availability and quality (see ‚What we did and what we didn’t), this selection of technical indicators is based on the assumption that the disruptive potential of ongoing military-technical transformations is best captured by the concept of the OODA-loop (observe-orient-decide-act) (see Fadok 1997: 366). In particular, we argue that in military-strategic terms what is aimed for is both information superiority (radical improvement of information quantity and quality during the observe-orient phase) and shrinking time-lags between military decision-making and actions (the two latter phases of the OODA-loop). Theres is arguably a trade-off between these two goals as the quantity of technical intelligence can overwhelm human decision-making capacities and, thus, slow down or even paralyze military actions (Drew 2010). Militaries nevertheless tend so pursue both goals at once and the technological capabilities we selected are key to both strategies (for more details see the section on methods).

A first downloadable version of our index contains data from 2015 (see data). Later versions will succinctly be created for 2010, 2005, 2000 and 1995. Once finished, the military-technical transformation index as well as the three composite indices can be used for quantitative hypothesis testing as a supplement to qualitative research designs. Some rudimentary plausibility probes of the predictive power of regime-type and resource-based variables are illustrated in the introductory section. Our ranking will also indirectly benefit qualitative research by broadening the base from which to find theoretically relevant empirical cases („crucial cases“). Moreover, clusters of states (transformation leaders, followers etc.) could be identified and then used in a fuzzy-set qualitative content analysis. Thus, we hope to serve multiple methodological pathways and thereby contribute to a more comprehensive research agenda on the causes and drivers of IT-based military transformations.

A deeper understanding of the reasons why states invest in IT-centric military capabilities would enable us to identity new possibilities (for example ‚issue-linkages‘, changes in the architecture of arms control regimes, regional partnerships) that would stabilize preventive arms control efforts alongside improved technical procedures. For example, causal analysis might reveal that effective governance mechanisms necessitate the participation of crucial regional powers or regional organizations. Strengthening parliamentary control might be a further necessity in order to avoid conflictive international dynamics while leading to the success of conflict governance mechanisms.

 

Military-Technical Transformation: Preparing an Index to Enable Comparative Research

What we did & didn’t

Measuring military technical transformation poses wide-ranging challenges. This section is about these difficulties and the way we have tried to overcome them. We explain our selection of indicators, which data we used and why, as well as the procedures of data aggregation. In short, we inform about what we did and what we didn’t. Please do not hesitate to contact us, if questions remain.

Our index is altogether a composite of three technological indicators. Conceptual assumptions as a basis of the selection criteria as well as the criteria themselves are respectively explained below. In its final version, the index measures the quantity and diversity of satellites and UAVs, respectively. In addition, cruise missiles are considered an indicator of military technical transformation if they are able to receive GPS signals or enable remote targeting via datalinks. Our measurement considers only operable systems and not research & development because our focus is on usable military capabilities only. The only exceptions are technological demonstration satellite systems because in this case it is hard to make a clear division between R&D and application.

 

Criteria that let us to Satellites, UAVs and CM

Which criteria guided the selection of technological capabilities as composites of the Military-Technical Transformation Index (MTTI)?

A basic assumption of our research design is that the concept of an OODA-Loop (Observe-orient-decide-act) (see Fadok 1997: 366) offers the best way to capture of essence of the ongoing IT-based military transformation. Thus, transformation-leading militaries pursue the dual goal of information superiority and a radical compression of time between decision-making and battlefield action. Whereas technical intelligence and an automated data analysis serves the first goal – improving the observe- and orient-phase – rapidly employable weapons systems that offer precision-strike options – exploiting information advantages – and flexible reprogramming serve the second, almost closing the decide-act gap. As a result of our conceptualization, we focused on the technological capabilities that play an integral part in either gaining information superiority or in the immediate exploitation of superior knowledge or both. Unmanned aerial vehicles, satellite systems and guided missiles fulfill these criteria sufficiently to become building blocks of our index creation.

Satellite communication forms the backbone of networked military operations and must therefore be regarded as a crucial factor in distributing sensor data and commanding military units over large distances. What is more, satellite sensors provide ears and eyes to the military and the signals from navigation satellite systems are almost indispensable for coordinating dispersed military units and for targeting weapons systems. Satellite systems are therefore an integral part of the efforts to achieve information superiority throughout the military and of minimizing the reaction time of individual units and platforms. Unmanned aerial vehicles, in turn, because of their ability to stay above the battlefield for hours, dramatically increase the ability to monitor ongoing situations. If weaponized they furthermore offer rapid intervention options. Thus, they are instrumental both to weaving a web of technical sensors (achieving information superiority) and to delivering military results on short notice (acceleration).  Finally, guided cruise missiles already contributed to a “shock-and-awe” strategy that neutralized conventional forces in the 1991 Gulf War in a very short time-period. They combine vast speeds with flexible targeting via the insertion of sensor data from other platforms. As a result, they have become a preferred choice for translating information advantages into swift military action. Although there is competition from unmanned aerial vehicles now, guided cruise missiles will likely be around for a considerable time not the least because it is much more difficult to defend against them.

Technologies we didn't choose

There are technological capabilities that met our criteria but were nevertheless not included.

Many would argue that the military-technical transformation is less about new technologies and platforms and more about a “system-of-system” approach and the paradigm of network-centric warfare (NCW). Unfortunately, it is hard to find a standardized measure of the degree of networking among military platforms and/or units. Even though one might be able to plausibly assess differences of networking between transformation-leading militaries and those who rely primarily on man-power and the deterrent effect of defensive legacy systems via detailed case studies, this is no viable strategy when it comes to the creation of large data sets. Even without data gaps, data acquisition would require far more resources than those available within a small research team.

Besides quantitative and qualitative networking characteristics, the degrees of automatization would principally be another relevant criterion for categorizing individual platforms or, in a second step, for identifying an average level of automatization throughout a set of military capabilities. The automatization relies on computer algorithms that cannot be analyzed from the outside however. Unmanned aerial vehicles (UAVs), are – as most systems – black boxes in this regard. This is no basis for large n-studies.


DATA

… WE USED …

Satellite
UCS – (Union of Concerned Scientists) Satellite Database, available at http://www.ucsusa.org/nuclear-weapons/space-weapons/satellite-database. This database is the most detailed with respect to satellite platforms and sensors. It lists users and purpose as well as many technical specifics and has a transparent data policy as one can easily track all the sources of all information. The data available online only reflect the status quo but older versions are available on demand.
UAVs
Military Balance 2016, available in most university libraries on a digital basis or in print version, was an essential source for counting UAVs in general.

New America Foundation, World of Drones overview on combat drones, available only at http://web.archive.org/web/20170519151619/http://securitydata.newamerica.net/world-drones.html. We included NAF information on combat UAVs in our index because it was the only exhaustive overview we could find. It is updated regularly, so we had to check if drones were integrated after 2015 and should therefore not be included in our 2015 dataset.

CMs
Janes Weapons Strategic, 2015-2016, available in some libraries in print version. This publication discusses technical developments in different fields, including cruise missiles. It was an essential source for our analysis because it indicates CMs with GPS navigation and targeting datalink features.

Military Balance 2016, available in most university libraries on a digital basis or in print version. It was necessary to check the possessor states of CMs that had been found in Janes Defense. The combination of both sources came along with some problems that are discussed below.

… WE DIDN’T USE
General

Heather Roff: Global Security – Autonomous Weapons System. The project provides information on a variety of military capabilities that include some degree of automatization. Yet it does not aim at a comprehensive assessment of the automatization of all existing systems in a given category as, for example, unmanned aerial vehicles. Item selection has been primarily on the basis of arms export volumes and therefore systematically excludes indigenously developed technologies and weapons systems. Bearing in mind that these systems are just as relevant to our index as purchased systems, the database offers a useful additional resource but does not qualify as a primary data source.

SIPRI Arms Trade Database: SIPRI is well-known for its comprehensive and reliable data on the global arms trade. Yet our research interest goes beyond the market-based diffusion of technologies and systems. Missing data on indigenously developed systems that are not exported therefore constitutes a crucial data gap within the context of the Military-Technical Transformation (MTTI) index. That’s why we didn’t rely on SIPRI arms trade data as primary source although we used it to check the reliability of other sources.

Satellites

Three available datasets, although they provide useful information on satellite systems, could not meet our specific research needs:

United Nations Office for Outer Space Affairs: http://www.unoosa.org/oosa/osoindex/index.jspx?lf_id= The UNOOSA database lists all orbiting satellites and is highly user-friendly by offering advanced search options. However, it does not indicate orbiting satellites in a given year in the past. As our index presents data in five-year intervals (2015, 2010, 2005, 2000), continuous databases without differentiation between years do not meet our specific research needs.

Jonathan McDowell’s Homepage: http://www.planet4589.org/space/. This database has been created as a private project by astrophysicist Jonathan McDowell. It probably offers more details on space objects than any other database. Most relevant with respect to our research purposes, Jonathan gives estimates on the end-of-operation of all satellites. Thereby, we have been able to identify orbiting satellites on a yearly basis. We also very much appreciate that Jonathan provided even more detailed data, differentiating between military and non-military payloads, via direct communication. However, the data did not allow us to differentiate the civil and commercial purposes of satellite systems. Therefore, we eventually decided to use other primary sources.

Gunter Krebs: http://space.skyrocket.de/. This database offers information on satellite systems on a country-basis. However, it does not indicate orbiting satellites in a given year in the past. As our index presents data in five-year intervals (2015, 2010, 2005, 2000), continuous databases without differentiation between the years do not meet our specific research needs.

Cruise Missiles

Heather Roff: Global Security – Autonomous Weapons System. The project provides information on a variety of military capabilities that include some degree of automatization. Yet it does not aim at a comprehensive assessment of the automatization of all existing systems in a given category. Item selection has been primarily conducted on the basis of arms export volumes and therefore systematically excludes indigenously developed technologies and weapons systems. Bearing in mind that these systems are just as relevant to our index as  the purchased systems, the database offers a useful additional resource but does not qualify as a primary data source.

SIPRI Arms Trade Database: SIPRI is well-known for its comprehensive and reliable data on the global arms trade. Yet our research interest goes beyond the market-based diffusion of technologies and systems. Missing data on indigenously developed systems that are not exported therefore constitutes a crucial data gap within the context of the Military-Technical Transformation (MTTI) index. For this reason, we did not rely on the SIPRI arms trade data as a primary source although we used it to check the reliability of other sources.

Although we used the yearly Military Balance (MB) of the International Strategic Studies Institute (IISS), the data was checked against and sometimes corrected by information within the IHS Janes Weapons Strategic. The MB was not our only primary source for two reasons:  First, we have found that crucial abbreviations such as LACM (Land-Attack-Cruise-Missile) or ASCM (Anti-Ship-Cruise-Missile) are not always used consistently when comparing several country profiles or volumes. Furthermore, the MB does not usually provide details on the navigation and targeting features of missile systems. Although it is unquestionably a very valuable source, we therefore decided to complement the MB data with data from the HIS Janes Weapons Strategic.

UAVs

Heather Roff: Global Security – Autonomous Weapons System. The project provides information on a variety of military capabilities that include some degree of automatization. Yet it does not aim at a comprehensive assessment of the automatization of all existing systems in a given category. This also applies to Unmanned Aerial Vehicles. Item selection has been primarily conducted on the basis of arms export volumes and therefore systematically excludes indigenously developed technologies and weapons systems. Bearing in mind that these systems are just as relevant to our index as the purchased systems, the database offers a useful additional resource but does not qualify as a primary data source.

SIPRI Arms Trade Database: SIPRI is well-known for its comprehensive and reliable data on the global arms trade. Yet our research interest goes beyond the market-based diffusion of technologies and systems. Missing data on indigenously developed systems that are not exported therefore constitutes a crucial data gap within the context of the Military-Technical Transformation (MTTI) index. Thus, we did not rely on SIPRI arms trade data as a primary source although we used it to check the reliability of other sources.

Matthew Fuhrmann/Michael Horowitz: Both well-known experts in drone proliferation, they have created a dataset on operational drone systems in 2014 and tested several explanations (threat environment, regime type, industrial base) of drone technology diffusion in their International Organization article (see https://www.cambridge.org/core/journals/international-organization/article/droning-on-explaining-the-proliferation-of-unmanned-aerial-vehicles/8982612535696D00F6D040DB56C741AF). The data also differentiates between tactical and advanced as well as the armed types of UAV capabilities. However, it is not yet shown in a time-series format and therefore cannot be used to create values in five-year intervals.


WHAT WE DID IN DETAIL:

Satellites

source: istockphoto, mechanick

Our measurement relates to the quantity and diversity of national satellite systems. Both governmental and military satellites are included, although their values have been weighted asymmetrically. Commercial satellite systems were excluded from our analysis. The inclusion of civil-governmental satellites is due to the dual use potential of space assets. The data gathered by civil-governmental satellites can be used for military purposes. Weather satellites or satellite navigation systems offer good examples. Furthermore, the labelling of satellites reflects political choices – many Chinese space programs are categorized as civil-governmental despite offering military applications – and therefore the line between non-military and military use is further blurred. While it is true that militaries rely on commercial satellite services as well, for example the UK forces on Skynet, these customer-client relationships need to be differentiated from the cases of state ownership. Only state-owned satellites count as technological capabilities. Commercial satellite systems have therefore been excluded from out data set.

The mean of both satellite quantity and diversity indices values constitutes the overall satellite index.


UAVs

source: istockphoto, Alexei Cruglicov

We analyze the quantity and diversity of national UAVs. Only military UAVs are included. UAVs are obviously used not solely within military campaigns but also for other security tasks such as border control or environmental protection, for example against poaching in the context of wildlife protection. What is more, they also serve non-security missions as for example agricultural management and in the not too distant future they might play a leading role in customized logistics. In other words: UAVs are multipurpose systems and this begs the question why we did not include civil UAVs in our measurement. The reason is threefold: First, existing databases within peace and security studies do not include civil UAVs. Given the proliferation rate especially of widely available small UAVs, data acquisition would be an almost insurmountable task. Second, there are good reasons to ignore small commercial UAVs because their performance is hardly comparable to military systems r- in terms of speed, endurance, payload etc. Second, counting all state-owned and advanced UAVs poses methodological challenges beyond data acquisition. That is because the competences of state border control and other security agencies and their relationship to military forces vary enormously from case to case. It is therefore almost impossible to calculate any plausible military side-value for state-owned UAVs in general.  We therefore opted to ignore non-military UAVs, acknowledging the risk that we eventually underreport some states capacities. Both weaponized and reconnaissance UAVs are included. The data basis for our 2015 index was the Military Balance 2016 plus the data from the New America foundation. The Military Balance is the only source of information on all national military UAV capacities on a global scale. Other sources did only partially meet our research criteria (see above, why). The New America Foundation dataset was the only one offering data about different types of weaponized UAVs within national militaries weapons arsenals.

The MB uses military technical terms (squadron or units) without quantifying the number of component weapon systems or soldiers. Given that there is no universally consistent definition of a squadron or unit, we counted UAVs in entities and single UAVs separately and constructed a mixed index.

The mean of the quantity UAV index and diversity UCAV index is used to construct the UAV index.

CMs

source: istockphoto, AlexZabusik

Guided missiles with satellite navigation and/or datalink targeting technology qualify for our index. Cruise missiles differ in many ways whether it is payloads, possible warheads, fly range, propellant, navigation technology, the targeting system or the seeker. Few components could unambiguously be attributed to the information technology revolution. What is more, qualitative differences are difficult to assess without classified information. There are two exceptions: satellite navigation and datalink targeting. Both technologies enable more precise flight and firing and rely heavily on data infusion. Additionally, both features are well documented by publicly available databases. On average, missiles that receive and are able to process satellite navigation signals operate more precisely than those with only inertial navigation. They also fly more autonomously than those being controlled by the launcher via datalinks. Datalinks differ with respect to navigation or targeting: Most datalinks serve only navigation purposes. If also used to exchange targeting data, the missile stays under control of the launcher until a very late point in time during the flight. This is only possible because of complex data management within the missile and on the launcher. Datalink targeting requires therefore a high degree of digitalization. On the other hand, the missile acts arguably less autonomously than the one without such a link. While the purpose of data transmittance makes for a good analytical starting point, the widely used label ‘fire and forget‘  is less useful because it offers a limited number of clues to specific technical features and is inconsistently applied to very different systems for marketing purposes. Unfortunately, there is no alternative convincing categorization of the degrees of autonomy. What is more, missiles are black boxes when it comes to the algorithms that enable autonomous operations. These fall under classified information policies. As a result, the limits of data acquisition alongside conceptual issues prevented us from adding degrees of autonomy to our indexing criteria.

Every state, that has at least one type of missile that occurs on our list, receives one point. In case a state has got both satellite navigation and datalink technology among its missiles, it receives two points. The scales start with – 0 – representing zero missiles with either data link or satellite navigation features. The end of the scale is set at  – 1 – representing the maximum possible value attributed to a state: 2. All state values based on simply counting are then converted into the index value.

The final index is aggregated from the combined satellite index, UAVs index and missile index scores. On the left: our construction, on the right: the result.

 

Military-Technical Transformation: Preparing an Index to Enable Comparative Research

Data 2015, 2010, 2005

Our data is accessible on this page in two ways. You can either search within our tables or download the data you need. ‚MTTI_subindecies and Index 2005-2015‘ aggregates the results of our analysis.

The data you will find within ‚SAT‘ ‚UAV‘ and ‚CM‘ contains the sub-indices results, including evaluative comments and source information. If any questions about our methods remain, please do not hesitate to contact us.

MTTI overview 2005, 2010, 2015_table
MTTI 2005_table
MTTI 2010_table
MTTI 2015_table

 

Military-Technical Transformation: Preparing an Index to Enable Comparative Research

Literature

All references on this homepage are listed below plus additional titles we deem useful in the context of our research project. You can get our plaine citavi-file by contacting us.

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Military-Technical Transformation: Preparing an Index to Enable Comparative Research

Publications

Journal Articles:

Mischa Hansel and Simon Ruhnke (2017) A Revolution in Democratic Warfare? Assessing Regime Type and Capability-Based Explanations of Military Transformation Processes, in: International Journal, 72 (3), 356-379.

Mischa Hansel and Sara Nanni (2018) Quantitative Rüstungsanalysen im Zeichen von Digitalisierung und Automatisierung, in: Zeitschrift für Internationale Beziehungen, 25 (1), [Quantitative Armament Studies within the Context of Digitalization and Automation Processes].

 

Presentations:

Mischa Hansel and Simon Ruhnke: Military-Technical Transformation Index (MTTI): Assessing Competing Explanations and Conditions of Military Acquisitions, Colloqium Center for Security Studies, ETH Zürich, 2nd November 2017.

Mischa Hansel and Simon Ruhnke: Military-Technical Transformation Index (MTTI): Assessing Competing Explanations and Conditions of Military Acquisitions, 5. offene Sektionstagung der Sektion IB der DVPW, University of Bremen, 4th October 2017.

Mischa Hansel and Sara Nanni: Military-Technical Transformation Index (MTTI): Grundlagen für quantitativ-vergleichende Ursachenforschungen zur militärischen Transformation, Institut für Friedensforschung und Sicherheitspolitik an der Universität Hamburg (IFSH), 24th May 2017.

Mischa Hansel and Sara Nanni: Rüstungsdynamik beobachten? Herausforderungen für quantitativ-vergleichende empirische Forschungen zur militärischen Transformation [Observing Arms Dynamic? Challenges of Quantitative-comparative Empirical Research on Military Transformations], Tagung der DVPW-Sektion Internationale Beziehungen, Greifswald, 12th-13th January 2017.

Mischa Hansel and Simon Ruhnke: A Revolution of Democratic Warfare? Testing Liberal and Realist Explanations of Military Transformation Processes, 8th ECPR General Conference, Glasgow, 3rd-6th September 2014.

Mischa Hansel and Simon Ruhnke: A Revolution of Democratic Warfare? Introducing Fuzzy-Set Methodology to Discover the Driving Factors behind Military Transformations, International Studies Association Annual Convention, Toronto, 26th-29th March 2014.

 

Military-Technical Transformation: Preparing an Index to Enable Comparative Research

Mischa Hansel Sara Nanni Marina Uebachs

Military-Technical Transformation: Preparing an Index to Enable Comparative Research

Contact

Our project aims to fill a critical gap within studies on military transformation by providing a global database on military capabilities in advanced information technologies.We thus hope to facilitate more quantitative works on the causes and driving factors of military-technological diffusion processes. Comments and criticsm is therefore very much welcome.

Please direct all your inquiries to Dr. Mischa Hanselmischa.hansel@ipw.rwth-aachen.de