Innovation as a complex adaptive system

Engler, Joseph

doi:10.17077/etd.bnphvn4x

Cited by 3 publications

(4 citation statements)

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“…Keeping in mind that there are analogies between projects and complex adaptive systems (CAS) [12], innovation and CAS [13], and energy systems and CAS [11], the idea of this paper is to encompass all these similarities in energy innovation projects as a whole. The analogy between EIPs and CAS is reflected in several important points (adapted according to Reference [14]):…”

Section: Energy Innovation Projects As Complex Adaptive Systems (Cas)mentioning

confidence: 99%

Reducing Risks in Energy Innovation Projects: Complexity Theory Perspective

Mihić

Dodevska²,

Todorović

et al. 2018

Sustainability

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The aim of this paper is to contribute to existing work on project risk management, and energy innovation projects, using the lens of complexity theory. By regarding energy innovation projects as complex adaptive systems, and linking complexity theory elements to the possibilities for reducing risks of energy innovation projects, the authors conducted empirical research on a representative sample of 100 subjects. The authors used a questionnaire that was formed on the basis of a previously designed research model, which unifies several different management fields, and a large number of phenomena previously studied independently. Therefore, it has a holistic approach to the topic. The results of this research suggest that considering the elements of complexity theory had a positive impact on reducing risks in energy innovation projects, in all analyzed aspects including specific, operational, and especially regarding social and behavioral aspects. This paper strives to support and encourage better results in energy innovation projects by reducing their risks, and hopes to bring additional value by introducing a new risk philosophy, based on complexity theory. Lessons learnt regarding each issue of this research are points of concern for project managers.

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Section: Energy Innovation Projects As Complex Adaptive Systems (Cas)mentioning

confidence: 99%

Reducing Risks in Energy Innovation Projects: Complexity Theory Perspective

Mihić

Dodevska²,

Todorović

et al. 2018

Sustainability

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“…Several specialised papers are focused on modelling innovation and describing the adjacent processes in the public sector or SMEs: Engler (2009), Tilebein (2006), Yilmaz (2008). Engler (2009) approaches innovation as "a complex adaptive system". The historical perspectives on innovation modelling development highlights linear models and pull models, as well as systemic models (feedback or strategic models, networked model).…”

Section: Innovation: Models and Systemsmentioning

confidence: 99%

“…The approach of the problem concerning the unicriterial optimality of the innovation strategies could be associated to classical problems of linear programming in integers or with a problem of ordination (Boldur et al, 1982: 204-207). Rephrasing one of the examples presented in the mentioned paper, we shall consider an innovation strategy S = {I , I } where I = {a , a , a }, and I = {a , a , a } represent sequences of operations , = 1,6 , using scarce resources ( = 1, = 1,3 ), , = 1,3 according to Table 1 Maintaining only the achievable sequences, we shall obtain the programmes of ordination: S1 = (a2, a4, a6, a1, a3, a5), S2 = (a1, a2, a3, a4, a5, a6), S3 = (a1, a2, a3, a5, a4, a6), S4 = (a1, a3, a2, a4, a5, a6), S5 = (a1, a3, a5, a2, a4, a6), (12) V1 = (0,2, 7, 11, 12, 17), V2 = (0, 0, 2, 2, 7, 7), V3 = (0, 0, 2, 7, 9, 14), V4 = (0, 1, 6, 8, 13, 13 According to the criterion of optimality, it results that S2 will be the optimal innovation strategy, holding the smallest length of accomplishment.…”

Section: B) Examplementioning

confidence: 99%

Optimal Innovation Strategies in the Public Sector

Matei¹,

Săvulescu²,

Antonovici³

et al. 2018

Preprint

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For the time being, public sector innovation gains new and complex forms of expression: managerial, institutional, technological or communication. This fact is also due to national and international important bodies’ interest for using innovation as resource and tool for public sector development. Characterised by complexity and adaptation, the innovative processes in the public sector embrace the form of medium and long term innovation strategies, holding high key socio-economic impact on the social utility of public sector innovation. The optimality of innovation strategies becomes a tool for improved decisions in public sector management, providing the methodology for their evaluation related to the objectives of development in the public sector.

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“…This forewarns us against defining innovation at singular scales (local or global), and therefore, conceptualizing innovation more generally as 'the development of a solution to a problem' enables cross-linking its independent definitions agnostic of their scale dependencies. For instance, Engler (2009) and Engler andKusiak (2010, 2011) define innovation by extending its scope across the system components (agents, actors and artifacts), thereby accounting for the cross-scale impact of innovation and connecting well to process, practice, product manifestations and even to organizational IJIS 13,3 design (Sheth and Sinfield, 2019a). Further, it allows us to link the product conceptualization of innovation to the marketplace (Draper, 2017)a complex system in itself.…”

Section: Introductionmentioning

confidence: 99%

Systematic problem-specification in innovation science using language

Sheth

Sinfield

2021

IJIS

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Purpose Problem specification is a key front-end step in the innovation process. This paper aims to introduce ‘purpose-context’ – a conceptual framework to systematically explore problem-specification across mapped contexts. The framework’s logic is operationalized by the inherent structure of language – its syntax/grammar, which enables the systematic exploration of problem-specification. The method showcases two approaches to structurally explore the vast textual databases available to us today for problem-specification in innovation science, thereby furthering the pursuit of innovation through its foundational elements. Design/methodology/approach The conceptualization of the purpose-context framework was guided by logic and the scholarship of integration applied to bodies of work including innovation, design and linguistics. Further, the key elements of the conceptual framework were unpacked and structured using the syntax of language. Two approaches to operationalize the method were developed to illustrate the systematicity of the process. The construct was then validated by using it to systematically specify problems in the technical context of Raman spectroscopy and in the socio-technical context of international development. Overall, this paper is a work of relational scholarship of integration that bridges academic-practitioner gaps. Findings The purpose-context framework is well-suited for application in the innovation process with applicability across several abstraction levels. One key contribution is the recognition that a broader problem-specification exercise covering one-one, one-many, many-one, many-many problem-context mappings expands the range of potential solutions (innovations) to address the problem-space. Additionally, the work finds that it is possible to provide structure to the cognitive elements of the innovation process by drawing inspiration from the structure inherent in other cognitive processes such as language (e.g., parts-of-speech, phrase composition). Drawing from language is particularly appropriate as language mediates communication in any collective pursuit of the innovation process and furthermore because a large amount of information exists in textual form. Finally, this paper finds that there is merit in approaching innovation science from its foundational elements – i.e. data, information and knowledge. Research limitations/implications While the purpose-context framework is broadly applicable, the methodical approach to provide structure to the front-end cognitive process is ‘one’ fruitful approach. We suspect other approaches exist. Practical implications The purpose-context framework is simple in its framing yet provides innovators, scholars and thought leaders, the ability to specify the problem space with greater coverage and precision. Further, in the solution-space, it provides them the ability to choose the breadth of solution scope (e.g. targeted solution addressing a single problem, targeted solution addressing a set of problems, the combination of solutions addressing a single problem and combination of solutions addressing a combination of problems). In addition, by pairing the creative front-end innovation process with machine power, this study provides a formal method to scale-up the coverage of creativity (and potentially that of solutions to those problems) and reduces the chances of missed/blind-spots in problem-specification. Finally, evaluating purpose-contexts leads to ‘capability-contexts’ – a capability-oriented viewpoint informing capability development decisions such as the focus of R&D programs and related resource allocation decisions. Originality/value The paper uses logic to connect multiple bodies of research with a goal to provide systematicity to problem-specification – problem-specification, which is an under-addressed part of the innovation process. The use of data to systematically explore problem-space lends it systematicity (repeatability and measurability) and is therefore, valuable to innovation science. The proof-of-concept demonstrates the conversion of concept into a method for practical application.

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Innovation as a complex adaptive system

Cited by 3 publications

References 60 publications

Reducing Risks in Energy Innovation Projects: Complexity Theory Perspective

Reducing Risks in Energy Innovation Projects: Complexity Theory Perspective

Optimal Innovation Strategies in the Public Sector

Systematic problem-specification in innovation science using language

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