A Conceptual Model for the Development of Transmodern Innovations

Aleksandr Borzov

SUSTAINABLE DEVELOPMENT AND ENGINEERING ECONOMICS 2, 2024

Research article

DOI: https://doi.org/10.48554/SDEE.2024.2.5

A Conceptual Model for the Development of Transmodern Innovations

Aleksandr Borzov*

St. Petersburg Restoration and Construction Institute, St. Petersburg, Russian Federation

*

Corresponding author: [email protected]

Abstract

I

nnovation processes are strongly influenced by changes in economic, political, technological and

other external factors. For instance, economic instability and political uncertainty can both stimulate

and limit innovative activity in organisations. Transmodern innovation is a concept that involves

scientific and technological advancements that may remain unutilised until favourable changes occur

in technological or economic conditions. The purpose of this study is to develop a conceptual model

for transmodern innovation that takes into account the dynamics of innovation, including the intensity,

economic prerequisites, external changes and degree of innovation adaptation. This model will help

organisations to better understand and respond to the complexities of the innovation process. The

resulting model is a comprehensive tool for analysing changes in innovation activity and the external

environment over different time phases, including the initial state (t0), the transition to new conditions

(t1) and the final state (tx). In this model, the ‘Final stage of tx’ block represents the final stage, which

allows us to draw conclusions about the success of adaptation and innovation development. This is the

basis for formulating strategic conclusions and recommendations for future development.

Keywords: transmodern innovations, conceptual model, innovative activity, adaptation, time series

Citation: Borzov, A., 2024. A Conceptual Model for the Development of Transmodern Innovations. Sustainable

Development and Engineering Economics 2, 5. https://doi.org/10.48554/SDEE.2024.2.5

This work is licensed under a CC BY-NC 4.0

80

Management of knowledge and innovation for sustainable development

SUSTAINABLE DEVELOPMENT AND ENGINEERING ECONOMICS 2, 2024

Научная статья

УДК 338.1

DOI: https://doi.org/10.48554/SDEE.2024.2.5

Концептуальная Модель Развития Трансвременных Инноваций

Александр Борзов*

Санкт-Петербургский реставрационно-строительный институт, Санкт-Петербург, Россия

*

Автор, ответственный за переписку: [email protected]

И

Аннотация

нновационные процессы сильно зависят от изменений в экономических условиях,

политической сфере, технологических новшествах и других аспектах внешней среды.

Экономическая нестабильность, политическая неопределенность, а также технологические

и социокультурные изменения могут как стимулировать, так и ограничивать инновационную

активность организаций. Трансвременные инновации представляют собой концепцию,

включающую научные и технологические достижения, которые могут оставаться неактуальными

до тех пор, пока не наступят благоприятные изменения в технологических или экономических

условиях. Целью данного исследования является создание концептуальной модели развития

трансвременных инноваций с учетом различных аспектов динамики инновационных технологий,

таких как интенсивность инноваций, экономические предпосылки, изменения внешней среды и

степень адаптации инноваций. Полученная модель представляет собой комплексный инструмент

для анализа изменений в инновационной активности и внешней среде на различных временных

фазах, включая начальное состояние (t0), переход к новым условиям (t1) и конечное состояние

(tx). В полученной модели блок «Конечное состояние tx» представляет собой завершающую фазу,

которая позволяет сделать выводы об успешности адаптации и развитии инноваций, что является

основой для формулирования стратегических выводов и рекомендаций для будущего развития.

Ключевые слова: трансвременные инновации, концептуальная модель, инновационная активность,

адаптация, временные ряды

Цитирование: Борзов, А., 2024. Концептуальная Модель Развития Трансвременных Инноваций.

Sustainable Development and Engineering Economics 2, 5. https://doi.org/10.48554/SDEE.2024.2.5

Эта работа распространяется под лицензией CC BY-NC 4.0

Управление знаниями и инновациями в интересах устойчивого развития

81

A conceptual model for the development of transmodern innovations

1. Introduction

Adaptation to changing environmental conditions, particularly during economic crises or legislative changes, is essential for the survival and long-term success of organisations. In a rapidly changing

environment, where innovation is key to maintaining competitiveness and promoting sustainable growth,

understanding the factors that influence adaptation and innovation has become increasingly important.

This process involves a thorough examination of the external factors that may impact the integration and

implementation of innovative solutions across various sectors.

The purpose of this study is to develop a conceptual model that will allow us to evaluate and predict the dynamics of transmodern innovation through the analysis of interactions between economic,

political, technological and socio-cultural factors. We aim to understand how innovations can adapt and

evolve over time, considering both current and future economic, political and socio-cultural circumstances.

The focus of the research is on assessing innovative systems’ ability to respond to external challenges through a time-series analysis. Developing a transmodern model would allow us not only to

evaluate the current state and effectiveness of innovation activities but also to provide strategic recommendations for companies striving to enhance their competitiveness and market presence.

2. Literature Review

Trans-temporal innovation (TTI) is a category of innovative solutions, of various forms, formed

in the period t0, which remain in the stage of delayed relevance until the period tx, characterised by the

anamorphosis of environmental factors that form the economic prerequisites for their development (Urbinati, 2022).

TTI properties:

Deferred Relevance (τ) – the period of time between the formation of an innovative solution Ii and

its actualisation in the period tx:

τ ( I i ) =t x − t0 , ≤ t x

(1)

Environmental Readiness (At) – the ability of the external environment for a period of time tx to

create the economic conditions for the implementation of an innovative solution Ii:

At ( I i , t ) > At ( I i , t0 ) , t ≥ t x

(2)

The Power of Diffusion (Θ) – a measure of the speed and degree to which an innovative solution

Ii is distributed in the relevant research and applied field:

Θ ( I i , t ) > Θ ( I i , t0 ) , t ≥ t x

(3)

Market Awakening (Ma) – the growth of market demand and the level of potential economic feasibility of an innovative solution Ii:

M a ( Ii ,t ) ∝ V ( Ii ,t ) , t ≥ tx

(4)

Environmental Provocateur (Pt) – an event or sequence of events that stimulate the actualisation

of TTI:

Pt → ( At ( I i , t ) ∧ Θ ( I i , t ) ∧ M a ( I i , t ) ) , t ≈ t x

(5)

iНе можете найти то, что вам нужно? Попробуйте сервис подбора литературы.

So, we can conclude that transmodern innovations are formed within the framework of scientific

research and innovative experiments, but their value and benefits are not realised until the onset of the tx

Sustain. Dev. Eng. Econ. 2024, 2, 5. https://doi.org/10.48554/SDEE.2024.2.5

82

Borzov, A.

period, when changes in technological processes, accompanying scientific discoveries or the evolution

of market and economic conditions allow these innovative solutions to achieve the economic feasibility

of potential applications (Palfreyman, 2022; Marion, 2021; Koloskova, 2020).

A clear illustration of the transmodern nature of innovation is the neural network. Neural networks

were developed in the last century but were limited by insufficient computer performance and insufficient amounts of data for their training. With the development of computing power, increased availability of large amounts of data and improved algorithms, neural networks have found wide application in

areas such as machine learning, natural language processing and computer vision. In the modern technological order, neural networks are a powerful tool for solving complex problems and are one of the

key technologies in the field of artificial intelligence and machine learning (MacMahon, 2019; Milling,

2002; Meissner, 2015).

Electric vehicles can also be considered as a good example of this. The initial prototypes and

ideas were proposed by Thomas Davenport and Robert Davidson about 200 years ago. However, a lot

of time passed before their mass production and popularisation, as the development faced technological

limitations, such as capacity, battery performance and weak infrastructure of charging stations. At the

moment, the electric vehicle market is growing and developing rapidly, especially in countries with high

fuel prices (Žižlavský, 2013; Siguaw, 2006; Schoen, 2005).

Another example of a transmodern innovation is genomic sequencing. Initial genomic sequencing

technologies were developed with the long-term goal of understanding the genetic information of organisms, but limitations in performance, cost and speed of analysis limited their use. With the development of technologies in bioinformatics, biochemistry, computing and DNA analysis methods, genomic

sequencing has become faster, more accurate, affordable and scalable. This has allowed scientists and

physicians to expand the scope of this innovation in practice, using it for the diagnoses of diseases, the

study of genetic mechanisms, plant and animal breeding and other applied tasks (Elzinga, 2023; Giannopoulou, 2011).

The purpose of this study is to develop a conceptual model for the development of transmodern

innovation, which will be used to analyse various aspects of the dynamics of the development of innovative technologies.

3. Materials and Methods

The methodology relies on general scientific methods, including analysis and synthesis, induction

and deduction and the abstraction and systematisation of information. The study examines the process

of the development of transmodern innovations through two time periods: the initial period t0, in which

innovations are formed, and the future period tx, in which they find their relevance and development due

to changes in the external environment.

The process of innovation transformation can be represented in the form of successive steps, each

of which is described by a system of nonlinear equations that reflect the relationship between innovations and the conditions of their development.

As parameters for modelling the transformation process of transmodern innovations, one can distinguish the intensity of innovation, which is an It parameter that can be interpreted as a measure of the

activity and effectiveness of innovation implementation at a certain point in time t. Many researchers

have described this characteristic of the innovation process. Peter Drucker’s works, in particular, emphasise the importance of a systematic search for innovative development opportunities and the generation of new solutions within the framework of enterprise competitiveness management, which largely

correlates with an understanding of the intensity of innovation (Mohr, 2009). Everett Rogers’s research

includes tools for analysing the speed and mechanisms with which innovative solutions are integrated

into public practice, which is mainly applicable to the concept of innovation intensity (Dibra, 2015).

Thus, the intensity of innovation can be viewed from several points of view, such as the speed of creation

Sustain. Dev. Eng. Econ. 2024, 2, 5. https://doi.org/10.48554/SDEE.2024.2.5

83

A conceptual model for the development of transmodern innovations

and implementation of innovations, their impact on the economic and social environment as well as the

willingness and ability of the system to accept and adapt to these changes.

The state of economic prerequisites Et in the context of modelling the process of transmodern

innovation refers to a set of conditions of the economic environment that affect the possibility and

effectiveness of the development and implementation of innovations at a certain point in time t. This

parameter can include a variety of factors, such as the level of economic development, the availability of

financial resources, tax policy, inflation, interest rates, public investment in research and development as

well as the general state and dynamics of the market. Robert Solow, in his model of economic growth,

postulated the thesis that productivity gains and economic growth are more driven by technological

innovations than by an increase in the number of production factors, which emphasises the importance

of economic conditions that intensify the economic process and the contribution of innovative results to

economic development. Paul Romer, in turn, argued that economic growth can be supported by investments in human capital and innovations aimed at increasing production efficiency and opening up new

opportunities for growth. Thus, economic prerequisites play a significant role in the innovation process,

since they not only determine the readiness and ability of the economy to generate and implement innovations, but also create conditions for their further development and commercialisation. In the context

of transmodern innovation, changing these conditions over time provides information about the optimal

time intervals for launching and promoting innovative solutions, and makes it possible to model potential difficulties or growth points associated with this process (Travassos, 2024).

The changing environmental conditions of St reflect the dynamics and intensity of changes in how

environmental specifics evolve and influence the development and implementation of innovations. This

parameter has been indirectly investigated in the works of many scientists. Michael Porter analysed the

economic structure of the industry through the prism of the ‘five forces’, which can be considered the

key elements of environmental change in the context of economic and strategic perspectives (Porter,

1995). John Cotter, within the framework of the ‘eight steps’ model of change management, defined the

key role of the external environment in initiating and maintaining change processes in organisations. Ulrich Beck, in his concept of ‘risk societies’, argued the thesis that modern societies are characterised by

increasing uncertainty and that the associated risks, as part of a changing external environment, require

societies and organisations to develop innovative approaches and strategies for their reification (Prieger,

2007). Thus, changes in the external environment have deep significance within the framework of the

transformation process of transmodern innovations, since they can both stimulate and restrain innovative

activity, influencing the time frame and conditions under which innovations are actualised in science and

practice (Dahlander, 2021).

The degree of adaptation of an innovation At reflects the ability and readiness of an innovative process or product to change or modify to meet fundamentally new or changing environmental conditions

during time t. This parameter is important for understanding the labour intensity involved in adapting an

innovative solution to new market requirements, technological standards, socio-cultural norms or environmental constraints. Everett Rogers, within the framework of the theory of diffusion of innovations,

studied the processes by which innovations spread between participants in the social system, addressing

the issue of adaptation as one of the factors influencing the success of innovation (Globe, 1973). Rogers

also discussed how social, cultural and individual characteristics influence the acceptance and adaptation

of innovations by society. Michael Tushman and Philip Anderson, within the framework of the concept

of ‘technological shifts’, investigated how companies adapt to radical technological changes, focusing

on the need to adapt management practices and organisational structures for the effective integration of

new technologies (Sivarajah, 2024; Hekkert, 2007). Clyden Christensen, within the framework of the

theory of ‘disruptive innovation’, described how new technologies that are initially created in niche markets can eventually radically change industries, displacing established companies (Damanpour, 2012).

In Christensen’s concept, adaptation to new conditions is a key element of the survival and sustainable

development of companies (Chursin, 2016). Understanding and analysing the degree of adaptation of innovation is critical to assessing the viability and potential for the long-term development of innovations.

84

Sustain. Dev. Eng. Econ. 2024, 2, 5. https://doi.org/10.48554/SDEE.2024.2.5

Borzov, A.

In the context of modelling transmodern innovations, At emphasises the need for a flexible approach to

the development and implementation of innovative ideas (Seebode, 2012).

4. Results

tions:

The relationship of the proposed parameters can be described by the following system of equa-

dI

= f1 ( E ( t ) , A ( t ) )

dt

(6)

dE

= g ( S (t ))

iНе можете найти то, что вам нужно? Попробуйте сервис подбора литературы.

dt

(7)

dS

= h (t, S (t ))

dt

(8)

dA

= k ( I (t ) , S (t ))

dt

(9)

Function f1 describes how changing economic prerequisites and the degree of adaptation of innovation affect its development. The deterioration of economic conditions may imply a number of scenarios – from macroeconomic instability to local financial crises – that can have a significant impact on

the operation of enterprises, the investment climate, consumer sentiment and overall economic activity.

These changes in the economic and political landscape can be caused by a variety of reasons. These

include, for example, economic downturns, which lead to a decrease in total output and the number of

jobs. Inflation also plays a role, increasing the price level and thereby reducing consumer opportunities.

An increase in interest rates can complicate the process of obtaining loans for both individual consumers and corporations, which makes investment activity more difficult. Instability in the political arena

can increase business risks and reduce investor confidence. Finally, global financial crises involving

multiple countries can lead to consistent economic disruptions in different regions. The deterioration of

economic conditions has a direct impact on innovation processes. In times of economic uncertainty, both

companies and investors may show restraint in investing in new projects and developments, which leads

to a reduction in investment in innovation activities. This fact changes consumer preferences, leading

consumers to favour products and services that either satisfy basic needs or offer a relatively high value

per unit cost. In response, companies are forced to adjust the supply structure, optimise operating costs

and rethink innovative strategies to maintain competitiveness and, as a result, profitability. However,

these uncertain conditions can also stimulate the innovation process, as enterprises are forced to look for

alternative ways to survive and develop. In some cases, the crisis may additionally motivate companies

to develop new products or optimise processes in order to achieve long-term development and increase

sustainability.

The g-function mathematises how the dynamics of changes in the external environment interact

with economic fundamentals, emphasising the complex impact of various factors on the economic state,

which, in turn, directs the development of innovations. These factors cover global economic trends,

including the growth or decline in gross domestic product (GDP) of the world’s leading economies,

which can expand or narrow international markets; political stability and changes in legislation that

ensure the predictive ability of business; rapid changes in technologies that redefine industry standards;

and socio-cultural changes affecting consumer preferences and behaviour. Environmental changes are

also critically important, forcing companies to rethink production processes and market approaches. The

logical and meaningful nature of the g-function allows us to form a deep understanding of how these

changes shape the economic atmosphere by indirectly stimulating or constraining innovation activity.

These variables can play a role in expanding new markets, accelerating investment activity, stimulating

entrepreneurship and technological development, as well as in shaping new industrial dynamics.

Sustain. Dev. Eng. Econ. 2024, 2, 5. https://doi.org/10.48554/SDEE.2024.2.5

85

A conceptual model for the development of transmodern innovations

The h-function provides a critical analysis of how variations in the external environment, including economic fluctuations, political instability and technological innovations, affect different systems

over time. This function is characterised by potential nonlinearity, emphasising that even minor changes

in bifurcation conditions can lead to significant and not always predictively significant effects within the

system. The inclusion of time dynamics in the analysis allows one to track how changes affect the system

over time, providing an understanding of both short-term and long-term consequences. Modelling these

changes is critically important for organisations focused on strategic planning and risk management, as

it allows them to prepare more effectively for future scenarios and optimally respond to emerging challenges, minimising the potential negative consequences of external destabilisation factors.

The k-function mathematically approximates the relationship between the intensity of innovation

activity, including the development of new technologies, product improvement and innovative business

practices, and changes in the external environment. These changes can range from economic fluctuations to socio-cultural trends, technological innovations as well as changes in policy and legislation.

The interaction of these two elements impacts how effectively innovations can adapt to new external

conditions. For example, a favourable external environment equipped with supportive legislation and

technological advances can facilitate the application and dissemination of innovations. However, in the

context of legislative barriers or an economic recession, even active innovation can face obstacles, which

require innovators and companies to adapt more deeply and develop innovative strategies to overcome

these obstacles.

Figure 1 shows a conceptual model for the development of transmodern innovation.

Figure 1. Conceptual model of the development of transmodern innovation.

86

Sustain. Dev. Eng. Econ. 2024, 2, 5. https://doi.org/10.48554/SDEE.2024.2.5

Borzov, A.

The ‘Initial state t0’ block is the basis of the entire flowchart, which sets the initial parameters

for the subsequent modelling of the properties of transmodern innovation and changes in the external

environment. Within this block, the basic levels of innovation activity are established, which reflect the

beginning of innovative processes, products or technologies. Also, the characteristics of the external

environment at time t0 are determined, and the data are supplemented by taking into account political,

economic and technological factors that approximate the context that can influence the further development and adaptation of innovative results. These initial parameters play a critical role in modelling the

initial state and provide reference points for monitoring the dynamics of changes throughout the time

period under consideration.

In the flowchart, the ‘Transition to t1’ block represents the initial stage of changes, within which

there is an active interaction between innovations that have the property of duration in time and the

changing external environment. This section focuses on two main aspects: the first comprises changes

directly in the external environment, covering all the key economic, political, technological and social

shifts that occurred earlier; the second is the adaptation of innovations, which may include processes

such as the introduction of new technologies, the recycling of existing products or a change in strategic

direction in response to new conditions and challenges of the time. This section illustrates how innovations begin to adapt to new external conditions, marking the initial stages of this transition process. In

fact, this block is a significant analytical point for assessing how effectively the innovation system is able

to respond to external challenges and adapt at the initial stage of this interaction.

The block ‘Process of change from to to tx’ plays a key role in the structure of the flowchart, covering the constant process of adaptation and transformation of transmodern innovations and environmental

changes during the analysed time period. In this block, each time point is considered individually, which

makes it possible to monitor recurring changes in the external environment and adaptation processes

within the framework of innovation activities. Changes in the environment and how innovations respond

to them are documented in each individual time interval. These adaptation processes may include the introduction of relevant technologies, strategic business reorientation or other forms of innovative activity

aimed at increasing competitiveness and realising new opportunities. Each time period also includes an

analysis of the impact of key political, economic and technological factors of development, which contributes to a deep understanding of how they form the context in which major changes occur. Thus, the

block describes in detail the complex interaction between changing conditions and innovation activities,

demonstrating the evolution and adaptation of business processes and approaches in a rapidly changing

world and forming a pool of effective long-term development strategies.

The ‘Final state of tx’ block in the flowchart visualises the final phase of modelling, within which

a summary of all transformations and adaptations that took place during the analysed time is presented.

This block displays the final state of transmodern innovation and the external environment, allowing one

to assess the impact of events that have occurred. It reflects the current state and nature of innovation

activity, which demonstrates how successful the adaptation and development of the innovations have

been. The analysis of the current state of the external environment is also carried out, which includes

economic, political, socio-cultural and technological changes. Understanding the impact of significant

events in the fields of politics, economics and technology allows us to determine their significance in the

formed results of innovation activity and environmental conditions. This block is critically important for

iНе можете найти то, что вам нужно? Попробуйте сервис подбора литературы.

synthesising the results of the entire process, highlighting achievements and shortcomings in innovation

management and allowing one to formulate strategic conclusions and recommendations for future development.

5. Discussion

The importance of the resulting model lies in its ability to provide insight into the nature of innovations over time and their potential application in various industries.

The conceptual model examines the evolution of innovation, paying attention to the interaction

Sustain. Dev. Eng. Econ. 2024, 2, 5. https://doi.org/10.48554/SDEE.2024.2.5

87

A conceptual model for the development of transmodern innovations

of innovation processes with economic, political, technological and other changes in the environment.

Changes in economic stability, the political environment, technological progress and socio-cultural aspects can both stimulate and inhibit the innovative activity of an organisation. This means that even

active innovation can face obstacles, such as legislative barriers or economic downturns. Overcoming

these obstacles requires deeper adaptation and innovative strategies.

In the context of studying the development of transmodern innovations, this model can be applied

to track the progress of technological advances in different time periods, allowing researchers and practitioners to identify key points of innovation, technological shifts and their consequences. Moreover, it

can become the basis for forecasting future technological trends and achievements, thereby supporting

strategic decision-making in various industries.

Thus, the transmodern innovation development model is an important tool for evaluating and

predicting the dynamics of innovative technologies to formulate strategic conclusions and recommendations for future development.

6. Conclusion

In this study, a conceptual model of the development of transmodern innovation was obtained,

which can be applied to track the dynamics of technological innovations at different points in time, in

particular, from t0 to tx. It can serve as a basis for understanding how innovations evolve and transform

from t0 to tx, potentially shedding light on patterns, breakthroughs and disruptions in technological development. The mathematical functions f1, g, h and k represent a complex interaction of economic, political,

technological and socio-cultural factors and allow us to analyse how changes in economic prerequisites,

the external environment as well as political and technological innovations affect innovation processes

at various time stages.

References

Chursin,

A.,

Makarov, Y.,

2016.

Innovation

as

a

Basis

for

Competitiveness:

Theory

and

Practice.

https://doi.org/10.1007/978-3-319-40600-8/COVER

Dahlander, L., Gann, D.M., Wallin, M.W., 2021. How open is innovation? A retrospective and ideas forward. Research Policy. 50, 104218.

https://doi.org/10.1016/J.RESPOL.2021.104218

Damanpour, F., Aravind, D., 2012. Managerial innovation: Conceptions, processes, and antecedents. Management and Organization Review. 8, 423–454. https://doi.org/10.1111/J.1740-8784.2011.00233.X

Dibra, M., 2015. Rogers’ theory on diffusion of innovation – the most appropriate theoretical model in the study of factors influencing the integration of sustainability in tourism businesses. Procedia – Social and Behavioral Sciences. 195, 1453–1462.

https://doi.org/10.1016/J.SBSPRO.2015.06.443

Elzinga, R., Janssen, M.J., Wesseling, J., Negro, S.O., Hekkert, M.P., 2023. Assessing mission-specific innovation systems: Towards an

analytical framework. Environmental Innovation and Societal Transitions. 48. https://doi.org/10.1016/j.eist.2023.100745

Giannopoulou, E., Gryszkiewicz, L., Barlatier, P.J., 2011. A conceptual model for the development of service innovation capabilities in research and technology organisations. International Journal of Knowledge Management Studies. 4.

https://doi.org/10.1504/IJKMS.2011.048441

Globe, S., Levy, G.W., Schwartz, C.M., 1973. Key factors and events in the innovation process. Res. Manage. 16, 8–15. https://doi.org/10.108

0/00345334.1973.11756189/ASSET//CMS/ASSET/3F1F4654-86E6-4BA4-AAB6-E1B4098866DD/00345334.1973.11756189.

FP.PNG

Hekkert, M.P., Suurs, R.A.A., Negro, S.O., Kuhlmann, S., Smits, R.E.H.M., 2007. Functions of innovation systems: A new approach for analysing technological change. Technological Forecasting and Social Change. 74. https://doi.org/10.1016/j.techfore.2006.03.002

Koloskova, O.I., Somina, I.V., Radosavljevic, M., 2020. Efficiency Factors of the Innovative Activity in High-Tech Industries, in: Springer

Proceedings in Business and Economics, pp. 181–193. https://doi.org/10.1007/978-3-030-39859-0_16

Liu, W., Liu, Y., Liu, L., Peng, Q., 2024. A MBSE-based approach for architecting concepts for business model innovation of smart product

systems. Computer-Aided Design and Applications. 21, 155–170. https://doi.org/10.14733/cadaps.2024

MacMahon, M., Fellenz, M.R., 2019. Conceptualizing the team-level innovation process: Roles for exploration and exploitation. Academy

of Management Proceedings. 2019, 14438. https://doi.org/10.5465/ambpp.2019.14438abstract

Marion, T.J., Fixson, S.K., 2021. The transformation of the innovation process: How digital tools are changing work, collaboration, and organizations in new product development. Journal of Product Innovation Management. 38, 192–215. https://doi.org/10.1111/JPIM.12547

Meissner, D., Kotsemir, M., 2015. Conceptualizing the innovation process towards the ‘active innovation paradigm’—trends and outlook.

Journal of Innovation and Entrepreneurship. 5. https://doi.org/10.1186/s13731-016-0042-z

Milling, P.M., 2002. Understanding and managing innovation processes. System Dynamics Review. 18, 73–86. https://doi.org/10.1002/SDR.231

Mohr, J.J., Sarin, S., 2009. Drucker’s insights on market orientation and innovation: Implications for emerging areas in high-technology

marketing. Journal of the Academy of Marketing Science. 37, 85–96. https://doi.org/10.1007/S11747-008-0101-5/METRICS

Palfreyman, J., Morton, J., 2022. The benefits of agile digital transformation to innovation processes. Journal of Strategic Contracting and

Negotiation. 6. https://doi.org/10.1177/20555636221079943

88

Sustain. Dev. Eng. Econ. 2024, 2, 5. https://doi.org/10.48554/SDEE.2024.2.5

Borzov, A.

Porter, M.E., van der Linde, C., 1995. Toward a new conception of the environment-competitiveness relationship. Journal of Economic

Perspectives. 9, 97–118. https://doi.org/10.1257/JEP.9.4.97

Prieger, J.E., 2007. Regulatory delay and the timing of product innovation. International Journal of Industrial Organization. 25, 219–236.

https://doi.org/10.1016/J.IJINDORG.2006.05.001

Schoen, J., Mason, T.W., Kline, W.A., Bunch, R.M., 2005. The innovation cycle: A new model and case study for the invention to innovation process. EMJ – Engineering Management Journal. 17, 3–10. https://doi.org/10.1080/10429247.2005.11415292

Seebode, D., Jeanrenaud, S., Bessant, J., 2012. Managing innovation for sustainability. R and D Management. 42, 195–206.

https://doi.org/10.1111/J.1467-9310.2012.00678.X

Siguaw, J.A., Simpson, P.M., Enz, C.A., 2006. Conceptualizing innovation orientation: A framework for study and integration of innovation research. Journal of Product Innovation Management. 23. https://doi.org/10.1111/j.1540-5885.2006.00224.x

Sivarajah, U., Kumar, S., Kumar, V., Chatterjee, S., Li, J., 2024. A study on big data analytics and innovation: From technological and

business cycle perspectives. Technological Forecasting and Social Change. 202. https://doi.org/10.1016/j.techfore.2024.123328

Travassos, A., Raimundo, R., Travassos Rosário, A., 2024. Importance of competitive dynamics of strategic groups: Opportunities and

challenges. Administrative Sciences. 14, 147. https://doi.org/10.3390/ADMSCI14070147

Urbinati, A., Manelli, L., Frattini, F., Bogers, M.L.A.M., 2022. The digital transformation of the innovation process: Orchestration mechanisms

and future research directions. Innovation: Organization and Management. 24, 1. https://doi.org/10.1080/14479338.2021.1963736

Žižlavský, O., 2013. Past, present and future of the innovation process. International Journal of Engineering Business Management. 5.

https://doi.org/10.5772/56920

Список источников