19-PM1-06: ST10.2 - Emerging Technologies and New Innovation Practices
R&D and innovation are often based on generic concepts and frameworks that are agnostic to the particular technologies involved. By contrast, this track explores how R&D and associated innovation processes are closely coupled to particular technologies. With their own characteristics and internal logics, individual technologies set the context for innovation and influence many dimensions of the innovation process, for example: timescales, research methods, skills requirements, financing requirements, risks, international topologies and information flows.
A particular focus will be with emerging ‘deep tech’ or ‘frontier technologies’ such as: machine learning, AI, big data, nanotechnology, additive manufacturing and the Internet of Things. These new technologies – with their specific characteristics – are expected to impact both how innovation is organised and how it is executed: ‘innovation in innovation’.
Papers are encouraged that concentrate on one or more specific technologies, identified at a sufficient level of granularity that their distinct characteristics can be appreciated. In this respect, it may be necessary to go beyond some of the commonly used categories such as ‘nanotechnology’ to more finely grained categories such as ‘nanomachines’.
For example, the branch of AI known as ‘deep learning’ is based on the use of multi-layer neural networks, which in turn need to be trained on a large data set. Such data sets have to be either generated from scratch or obtained from existing sources. The technology developers may not have in-house access to such data. The need for training data therefore fundamentally drives the innovation relationships or collaborations necessary for the technology to be developed. However, not all AI approaches are so dependent on training data. Looking at the technology only at the aggregated level of AI could miss insights that are important to theory, policy and practice.
As well as currently emerging new technologies, the track is open to papers that explore past examples of new technologies that have shaped innovation practices.
Finally, the track will also welcome papers that conceptualise or take an overview of the relationship between new technologies, R&D and innovation.
Emerging technologies – preserving and growing value over multiple innovation timelines
Institute for Manufacturing Cambridge, United Kingdom, And Technology Research Ltd.
Investment in emerging technologies is useful to R&D managers. Technology emerging at the right time may result in a market winner. But what if the time is not right? Does this mean that work undertaken has no value? Unlikely, but what is that value?
Fast changing industries breed new technologies and disruption in a market place will occur when the market and the technology come together. To survive disruptions companies can invest; but in what and when requires strategy. Different approaches, for example, investment in portfolios of technology which hedge outcomes are taken. Managers can develop strategies to support balancing portfolios and assist investment choices made. But, despite best efforts, ongoing R&D work can present outputs that do not match market conditions particularly as markets also change. Value may not therefore be captured when generated[1,3,4, 6]. Instances arise where value is captured during subsequent innovation activity[2,4], but, in the meantime, decisions on what is valuable may be misguided [4,6]. Of particular concern is implicit value associated with intangible assets such as software and data. These components of emerging technologies are difficult to identify and quantify and can be discarded as waste and lost.
Whilst descriptions of methods to identify explicit value emanating from work in emerging technologies (i.e. patents, licences, widgets) exist, there is little that covers implicit value. In addition how the value of implicit assets can be managed to enable capture during follow-on investment programs has attracted little attention.
Is it practical to identify and assess both the implicit and explicit value created or captured during R&D work ?
If it is, would it enable methods for managing and growing value across multiple investment programs to be developed and implemented in practice?
Data collection has been undertaken through interview and workshops using both qualitative and quantitative methods. Companies have been asked to describe value of work they undertake. Results have then be analysed against a framework of value types, The value types and categories of value within these types were developed following literature review. The value types and categories have been refined as a result of the research and then used to develop a process for value identification and capture.
Data has been collected through semi-structured interview and through workshop discussion. The data has been collected over an 18 month period which has allowed time for companies to baseline their practices. Results following on from the subsequent adoption of new process and language has been collected. Comparison has been made and the results of the comparison collected. Data input has been taken from 12 companies. Workshops conducted with four companies is reported on.
The methods used by companies to identify and report the value of the work undertaken in R&D and NPD are reported. The process developed during the research and trialled by the companies form the basis of the results. Three sets of results are presented.
The first set relates to the categorisation of value used by companies to identify value. Categories fit within two main types, explicit and implicit. A value matrix is used to help identify the difference between the two types. Further categorisation according to the context relevant to the company and the lens they employ is also reported. Two guiding questions 'Value of what' and 'Value for whom' and used during the analysis. .
The second set covers results of analysis to identify when and where value is created. From this assets which can be measured are identified alongside measures that can be used for quantification. Storylines that provide evidence and justification for the values are also presented.
The third set includes reports on the types of visualisations used to communicate the value identified. Graphs, box plots, bar charts and pie charts are examples of
graphics used to communicate value created.
Contribution to Scholarship
This research adds to literature that analyses and describes the value of technology. In addition it adds to literature relevant to communications, management, NPD and R&D. Value not reported through business case development is addressed as well as re-usable technology and the building of assets. Detail in respect of process, method and language are provided in the literature developed. Types and categories of value are presented in the literature alongside quantitative analysis of how companies use the categories for communicating implicit or intrinsic values which can be difficult to identify. The impact of such communication on issues such as portfolio management and investment decisions is addressed.
Contribution to Practice
This research identifies process, methods and language that can be used in practice to identify value created during work in R&D and NPD. Companies face difficulties in communicating the value of such work, in particular when the work relates to emerging or early stage technologies. This work supports managers when describing value created through R&D. Such information is important in practice when judging outcomes from R&D and when making on-going investment decisions.
This research addresses a gap between research and industry, that of how to value the outputs of innovation. Companies invest in R&D for NPD and such investment often involves emerging technology. The research looks at value resulting from such work.
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 V. Lynch (2013) An investigation into the value of embedded software (2013). University of Cambridge PhD Thesis. Feb. 2013.
 R.Mitchell, R. Phaal, N.Athanassopoulou (2018) Scoring methods for evaluating and selecting early stage technology and innovation projects. Centre for Technology Management working paper series ISSN 2058-8887, No. 2 March 2018
 I. Chandrasekar. (Nov. 2018) DRIVING DISRUPTION:Catching the Next Wave of Growth in Electric Vehicles. https://www.christenseninstitute.org/publications/driving-disruption. Last accessed 17/02/2019.
R&D management across a technology transition: the case of additive manufacturing
1Technologia Ltd; 2RADMA
We are claimed to be in a transition to additive manufacturing - radically different from traditional (subtractive) manufacturing, and involving new technologies. Through a case study, the paper explores whether the transition in manufacturing technologies is leading to an equivalent transition in the respective practices of R&D management.
Despite the management of R&D being as close to the technology as one can get, much of the academic literature on R&D management, and many of the techniques employed by practitioners, are generic (e.g. Cetindamar et al, 2010). The evolution of innovation management techniques is rarely discussed, though Hidalgo and Albors (2008) identified the growth of the knowledge economy as an influence. Bauer and Schimpf (2018) propose a historical analysis related to the changing industrial role of R&D but recognise that methods and tools are a minor topic.
Management literature has paid more attention to technology specifics at times in the past, for example through contingency theory (Woodward, 1965) and the history of technology literature generally pays much attention to such details.
Niaki and Nonio (2016) undertook a bibliometric review and classification of the additive manufacturing literature but the topic of R&D management was absent.
The paper seeks to address three gaps. Firstly, to explore the R&D management practices for additive manufacturing, as opposed to the technologies themselves. Secondly, the evolution of R&D management practices in the face of technology transitions. Thirdly, the role of technology specifics in R&D management.
1.Given the difference between subtractive and additive manufacturing, how different are the respective R&D management practices? 2. At what level of granularity can distinct practices associated with additive manufacturing be identified? 3.Are they chosen from the pool of generic practices, or devised for particular deposition techniques, materials, or application areas?
The research uses a case study of a UK manufacturing SME in which the author was a practitioner and participant observer. The author’s participatory involvement was initially in conceiving the disruptive additive manufacturing concept, designing the overall plan, and securing grant funding. The author’s observations are supplemented by in-depth interviews with members of both the (new) additive manufacturing project team and members of the (pre-existing) engineering team. The interviews cover how the R&D challenges were understood and overcome, and how the additive manufacturing project challenged pre-existing R&D norms within the firm.
Participant observation plus four to six depth interviews within the subject organisation.
The starting point for the results is a case study of how the additive manufacturing R&D was conducted in the SME against its background of traditional manufacturing R&D. This case study is then analysed to identify R&D management practices across the technology transition between subtractive and additive manufacturing. Both explicit/formal processes and tacit/informal processes are identified, together with the interviewees’ stated reasons for any choices. The case study will answer RQ1 regarding the difference between R&D management practices in subtractive and additive manufacturing.
This ethnographic account is then used to propose a conceptual framework that describes how the R&D management choices can be explained in terms of features of the technologies they seek to manage, particularly in respect of the technology transition. This addresses RQ2 concerning the level of granularity in the technologies of additive manufacturing.
Finally, the results are used to address wider questions on the ecology of R&D management practices, especially RQ3 concerning generic and technology-specific practices.
Contribution to Scholarship
Technology transitions are well understood but R&D management transitions are not. The intention of the paper is to use the case study of additive manufacturing to better understand a transition that is still in progress and to develop a model of how researchers choose (or devise) an appropriate practice. It is implicit in the literature that R&D management practices should be ‘appropriate’, but appropriateness is rarely discussed. The wider agenda of this paper is to better understand the relationship between R&D management practices and the technologies that are the subject of these processes.
Contribution to Practice
Though intended as a pilot study, the paper will be immediately relevant to practitioners and policy makers in the field of additive manufacturing. But there is a larger audience of practitioners who have to choose from among the many R&D management approaches that exist. The research will help practitioners think critically about the appropriateness of the tools and techniques on offer.
This is a practitioner paper seeking to bridge research and industry. The case study of this paper is at one level a very practical industrial story. The bridge to research is that this story raises and perhaps can start to answer some important academic questions for the R&D management field.
Bauer, W. & Schimpf, S. (2018). Understanding the history of industrial innovation: developments and milestones in key action fields of R&D management. R&D Management Conference 2018, Milan, Italy
Cetindamar, D., Phaal, R. & Probert, D. (2010). Technology Management Activities and Tools. Palgrave Macmillan
Hidalgo, A., & Albors, J. (2008). Innovation Management Techniques and Tools: A Review from Theory and Practice. R&D Management, 38, 113-127.
Niaki, M. K. & Nonino, F. (2016). Additive manufacturing management: a review and future research agenda. International Journal of Production Research, 55 (5) 1419-1439
Woodward, J (1965) Industrial Organisation Theory and Practice. OUP
From Venture Capital Ties to Social Capital Bonds: A Case Study on How a Venture Capital Investment Makes Supply Chain Networking Work
National Chengchi University, Taiwan
One challenging mission for nanotechnology startups is to acquire complementary resources for product commercialization. If it is located in an area where manufacturing capability is declined, the strong linkage with partners working in hardware fabrication become alienated and in the long run, will lose its ability to innovate.
Supply chain management is the attribute to be sources of sustained competitive advantage (Barney, 2012). It is particularly important to start-ups when the company requires to gain access to and leverages resource resided in the relevant supply chain. However, with limited social capital, it is a rather difficult process to them because knowledge transformation that allows new technologies to develop requires a certain level of person-to-person contact for gaining efficient information (Tassey, 2010).
Through inviting a strategic investor with strong social capital to invest in the startup is able to compensate for the vulnerability in social networking. At theoretical level, this paper will combine the concept of weak ties concept originally from Granovetter's micro-macro bridge (Granovetter, 1973) to Burt’s social network research (Burt, 1992) in sociological theory, and the notion of complementary asset (Teece, 1986) to address the relationship between a startup and its supply chain.
The field of research seems to lack of an empirical study on the social capital of a start-up with hard (technological) innovation and how the company boosts its technology via the relationship of two units in the node of networking links with asymmetric social capital resources in previous literature.
What is the critical success factors of radical hard innovation for a startup? How does a startup with hard innovation extend industrial networking through leveraging the partner’s social capital via investment relation, when the company locates in the region without the clusters of product design and manufacturing?
In this research, participant observation as a data collection method is the approach for the case study. The method is a widely used methodology typically used in qualitative research and ethnography. By participating-as-observer with the executive management team of the focal company over an extended research time period, the research is able to obtain more detailed and accurate information about the company under study. The observation in this study in the sense that the data is gathered when the events happen and provide real-time insights on the sequence of decision making and strategy forming processes.
The focal company in this study is a start-up company in North America spun-off a revolutionary, high conductive functional nanotechnology from a lab in a university with deep material science knowledge in small-molecule. It is in the pre-revenue stage and is looking for a new strategic investor based in Asia who is able to help the company to engage with its potential customers in manufacturing industries. The interaction with the focal company is a process to enhance mutual understanding and building partnership via capital investment.
During the field study, the author was acting as an investment manager on behalf of one of the potential new investors. The empirical material related to this study extracted from the process of conducting venture capital due diligence for making the final investment decision over 14 months. To gaining access to phenomena of interest, the method of covert observation and interaction provides empirical evidence through interviewing the existing investors, industrial partners, and the new investor in the same investment round of the focal company.
Most successful nanotechnology innovations in the market are either developed and incubated by larger size companies or developed by start-up companies but targeting to be acquired after the proof of concept. Even though the breakthrough of nanotechnology may have a significant impact on a wide variety of hi-tech areas, similar to other material science innovations, several bottlenecks need to be overcome before scaling-up the technology, including the verification of its functionality for various applications, the utilization of the materials, and customer engagements. One fundamental reason is that startups have relatively weak social networking, and it is a challenging mission for a startup to overcome the hurdles mentioned above.
Through the networking of the investment arm of the Industrial Technology Research Institute (ITRI), an independent research organization focusing on developing applied science technology, the focus company can access to the broad networking this research organization has built since 1973. This is an important social capital asset to the focus company because some of ITRI’s research directions are perfectly matched to the company. Through the channel, the company can access to the makers in Asian countries, the hub of OEM/ODM service providers.
Contribution to Scholarship
This exploratory study develops a framework to explain and conceptualize the relationship of two units with asymmetric social capital in the same field of social networking. The argument proposed in this research indicates that through the ties of a strategic partner with strong external social capital, the unit at a weaker node is empowered to entering into well-built networking to bond the resources for growth. It reduces the amount of redundant investment on time and effort to build networking which is essential and precious to the weaker side.
The insight from this research provides initial evidence to explore the mechanism on how to convert a tangible tie into an intangible bond to extend the networking from firm-to-firm level to much wider networking. Through the new proposed lens, it extends the interpretability of the social capital theory and provides the breeding ground in the field of entrepreneurship studies.
Contribution to Practice
This paper provides a practical contribution to identifying the keys to the success of a radical hard innovation from an academic research. The evidence in this paper indicates that a startup from university can fill the gap of social capital by leveraging its strategic investor’s social networking. It is crucial when it is facing asymmetric competitions from well-established competitors in the same sector, and geographical proximity is a challenge factor in the commercialization process. The conclusionhopes to create an example for other university spin-offs in the future.
One of the themes of this track expects to explore how associated innovation processes are closely coupled to frontier technologies, taker example, nanotechnology. The case study is a good fit for the attendees from academics and industries who are interested in the commercialization process of a university hard innovation.
Barney, J. B. (2012). Purchasing, supply chain management and sustained competitive advantage: The relevance of resource-based theory. Journal of Supply Chain Management, 48(2), 3-6.
Burt, R. S. (1992). Structural holes: the social structure of competition: Cambridge, Mass.: Harvard University Press.
Granovetter, M. S. (1973). The Strength of Weak Ties. American Journal of Sociology, 78(6), 1360-1380.
Tassey, G. (2010). Rationales and mechanisms for revitalizing US manufacturing R&D strategies. J Technol Transf, 35(3), 283-333.
Teece, D. J. (1986). Profiting from technological innovation: Implications for integration, collaboration, licensing and public policy. Research Policy, 15(6), 285-305.