The Use of Innovation Management Processes in Managing Innovation-Driven Projects

Abstract—This paper looks at the use of Innovation Management process in the Project Management domain, it first introduces technique; how it works and how to use it. Two papers are reviewed that use innovation management processes in managing innovation driven projects. The first paper, “The role of business model innovation in the hospitality industry during the COVID-19 crisis” by Matthias Breier, Andreas Kallmuenzer, Thomas Clauss, Johanna Gast, Sascha Kraus, and Victor Tiberius (2020), looks at the use of innovation management processes in the context of Business Model Innovation in the hospitality industry during the Covid-19 crisis.

The second paper, “Dynamic Innovation Strategy Model in Practice of Innovation Leaders and Followers in CEE Countries—A Prerequisite for Building Innovative Ecosystems” by Michaela Kotkova Striteska and Viktor Prokop in 2020 considers innovation management processes in the context of Dynamic Innovation Strategy Model (DISM) as a Prerequisite for Building Innovative Ecosystems. Following these papers a case study is being presented by the author which explain the context in which it was used, how it was used, what results were achieved, and some reflections on the process.

Index Terms— Innovation Management, Project Management, Technique, Innovation, Business Model Innovation, Dynamic Innovation Strategy Model

Introduction

THIS paper looks at innovation management that focuses on innovation processes while suggesting the likelihood of innovation process management in business. The proposed model will be critical as a control tool during the assessment of performance of innovation processes in a business organization. To answer the question, various methods will be considered based on their relevance and matching the character of the respective components of the model. As such, the researcher explores document analysis for the current and conventional data regarding the topic.

Other Researchers Use of Technique

In this section we’ll review two papers where researchers have used innovation management processes in their work, and look at how they have used it and the outcomes of its use. The two papers are “The role of business model innovation in the hospitality industry during the COVID-19 crisis” by Matthias Breier, Andreas Kallmuenzer, Thomas Clauss, Johanna Gast, Sascha Kraus, and Victor Tiberius in 2020 and “Dynamic Innovation Strategy Model in Practice of Innovation Leaders and Followers in CEE Countries—A Prerequisite for Building Innovative Ecosystems” by Michaela Kotkova Striteska and Viktor Prokop in 2020.

First Paper

In the first paper, the researchers’ explored how businesses in the hospitality industry used the Business Innovation Model to recover from the effects of Covid-19 pandemic and also how they successfully adapted to the contemporary situation (Matthias et al., 2020). The researchers conducted a multiple case study involving six hospitality firms in Austria. The researchers relied on data obtained during the interviews with the managers alongside one of their primary stammgasts in every case that they further triangulated with secondary data to expound data analysis.

Matthias et al. (2020) established that customers demand better services in order to enhance their situations and have the liberty to give feedback after enjoying the services. However, the rigid lockdown has altered the context. Simultaneously, lockdown measures have restricted movements making it difficult to exchange information. Accordingly, open innovation remains a reasonably distant knowledge in the hospitality sector despite its pillars and processes gaining momentum in the industry (Iglesias-Sanchez et al., 2020; Yan et al., 2018).

As such, this study unveils a unique and potentially important function of the stammgasts in the presence of a crisis, such as their psychological support, particularly in preparation and implementation of a BMI and also where they aided the firms to navigate the first shock and urged the decision-makers to be creative. The outcomes indicated that Business Management Innovation (BMI) is effective during and after the crisis to generate new sources of revenue and secure a higher liquidity level with instrumental role of stammgasts.

Crisis - BMI relationship model under the influencing factors of the hospitality industry

Second Paper

In the second paper, the researcher’s approach was to recognize innovation determinants in Dynamic Strategic Model (DISM). The researchers also established how such determinants drive creation and sustenance of innovation leaders’ competitive advantage in sampled European nations under the group of moderate innovators. Additionally, the authors defined a combination of factors that will be introduced in the company strategy to encourage a substantial impact on the innovative aspects of the company. Other studies suggest that innovative features determine a company’s innovative ecosystems (Kotkova & Prokop, 2020; Shakeel et al., 2020). Furthermore, the researchers used data obtained from Eurostat concerning the innovators and subscribers of nine European Union nations and also their regression models to establish the fundamental success determinants of the innovation leaders and followers.

Their outcome showed that the determinants include: marketing and design, cooperation with partners, and in-house Research and Development (R&D) activities. The results also revealed that among the innovative leaders, the primary determinants have positive effects on produced innovations for the followers, while the similar group indicate a negative impact.

Dynamic Innovation Strategy Model
Fig. 2. 1. Dynamic Innovation Strategy Model; Source: own processing.

Case Study

Technology and Innovation Management in Higher Education—Cases from Latin America and Europe- Using Model of Learning in Technology and Innovation Management to solve the typical bottlenecks in the innovation and development process often referred to as the European Paradox. The researchers introduce various experiences of education. Theoretically, the model focuses on behaviors, skills, tools, and competences.

Models are essential tools that enhance the understanding of learning processes at the organization level and are also useful to underscore and build an innovation ecosystem. At a glance, they provide an overview of the issues linked with innovation and technology management and may likely provide further questions to be solved in the next stage (Arciénaga Morales et al., 2018). Thus, the Model of Learning in Technology and Innovation Management helps understand a reasonable practice of managing innovation and technology to bridge the gaps and limitations in educational schemes. According to Arciénaga Morales et al. (2018), this approach is the missing link that compares innovation and technology management with curricular design in higher learning institutions (Albors-Garrigos et al., 2018; Laeeque et al., 2017). Learning solves the gaps alongside the limitations in management whose solutions have a lot of value for Latin America and Europe.

The Dynamic Strategic Model facilitates understanding at different learning stages because it gives a visual expression of the various learning approaches. It is also instrumental in shaping and guiding learning strategies and the subsequent tools to be adopted. The outer circles exhibit crucial elements that influence the learning process entirely (Arciénaga et al., 2018; Naranjo-Valencia et al., 2018). On the other hand, the inner layer denotes the internal organizational factors that intensely impact the learning process. It also entails the isolation of suitable competencies, tools, behaviors in innovation, technology management, and their involvement in a uniform model. Notably, empirical evidence posits that organizational learning and innovation influence business performance (Arciénaga et al., 2018; Kotkova & Prokop, 2020).

This model is unique due to its cooperative innovation pattern connected to the sustainability and circular economies, e-services, and simulation that aid learning, education-action approach, and emerging learning practices in Higher Education.

In the first component, experiences suggest that solutions are embedded in collaborative innovation and categorize product, service opportunities, and processes emanating from a broader context. Moreover, the know-how to share the entrepreneurship training, the skills to change ideas into the strategic project, the knowledge to finance the new opportunities, and the various engagements to solve concerns are significant components of this model (Kotkova & Prokop, 2020; Shakeel et al., 2020).

This case study also clarifies that learning strategies entail capacity building on environmental issues, risk-taking, and knowledge valorization. An interdisciplinary system is critical to earning value from the innovation processes when examining R&D valorization and knowledge production (Kotkova & Prokop, 2020). The fact that innovative processes interact implies that there is a need to address various stakeholders’ perceptions at different stages.

One of the crucial missing aspects in the innovation gap solution comprises the learning model for reliable practices and tool design in technology and innovation management. Studies show that the learning model is crucial at the organizational level to solve dynamically, or partially at the start, one’s limitations of innovation’s requisite knowledge (Melane-Lavado & Álvarez-Herranz, 2018; Naranjo-Valencia et al., 2018). The learning models help address the role of technology management in the implementation of technological solutions, suitable curriculum design, and the teaching of such management issues.

While most of the studies pay enough attention to R&D, innovation process, general training competencies, technology transfer, and technology management, they are often limited in terms of specific competencies alongside the tools that mitigate the context issues, including learning rate globalization, complexity, and uncertainty (Melane-Lavado & Álvarez-Herranz, 2018). Such factors in many ways impact the capacity to control multifaceted disciplines like innovation and technology management. Due to the changing nature of innovation management and technology, the concern has always been the competencies, architecture of concepts, tools, and strategies to organizations and the society meets the thresholds to transform knowledge into utility (Melane-Lavado & Álvarez-Herranz, 2018).

The avenues to address learning challenges, decision processes, and other innovation bottlenecks are critical to underscore how to implement collaborative innovation, evolve knowledge and teaching practices, and nurture systematic competencies for a dynamic, complex discipline (Grimpe et al., 2017; Sossa et al., 2019 ). It can be deduced that in the context of technology and innovation management, there is an entire chain of tools and competencies that are linked with the logical decision-making processes (Grigorescu et al., 2020). Some of the essential aspects of this approach include the following:

  • Strategic solutions that point to the opportunities or problems as goals to achieve. At this level, the organization must be involved in extensive new product development, technological collaboration, introducing reliable external linkages, and innovation and technology strategy (Laeeque et al., 2017).
  • Concrete decisions to earn such solutions as new product development, intellectual property protection, commercialization, project management, technology-based entrepreneurship, R&D management, input management, internal processes management, and technological innovation.
  • Financial innovation, which constitutes the financing of all the activities listed above.

This model also stresses the need for a creative environment in an organization by adopting four components, which are:

  • Reliable communication processes and cohesive relations among the organization’s members
  • Recognition and rewarding of the members’ contributions
  • Knowledge sharing networks and circuits
  • A culture that nurtures and emulates identity and purpose.

Management has a critical role in an organization because it can create a conducive environment or obstruct the free flow of information and ideas. As such, this model proposes a need to create a management practice that embraces a nonhierarchical system when handling new ideas and proposals. Also, a creative environment entails more than the employees’ liberties to navigate probabilities to earn results (Rauter et al., 2019). Creativity, like other fundamental processes, needs a reliable framework to function effectively. Organizations should reduce protocols to allow a seamless flow of information and ideas at all times.

Innovation management challenges

One of the challenges facing innovative ideas is that most of them cannot be translated into the intended new product. In other words, most of the projects cannot be technically feasible products. Even in cases where they are achievable, sometimes they fail to get market recognition. That, in many ways, has seen innovation success rates in organizations very low (Naranjo-Valencia et al., 2018; Prokop & Stejskal, 2019). For example, in drug development, typically, one of three thousand innovative ideas becomes commercially successful. In most cases, such discoveries take close to twelve years and sometimes more to move from the discovery stage to listing of the new drug and subsequently costing hundreds of million dollars.

As such, the innovation process has sometimes been seen as a funnel because, despite several new ideas that have the potential at the start, only a few samples become successful. According to Schatzmayr, (2018), there is a need to have downstream activities of the innovation process such as commercialization and marketing. Ideally, they argue that firms should adopt innovation as a significant component of firms’ innovation strategy (Prokop & Stejskal, 2019). Similarly, organizations should also involve consumers to suggest the possible ways the innovation would serve them best.

Learning Model for Technology and Innovation Management.
Fig. 3. Learning Model for Technology and Innovation Management.

Reflections

The goal of this paper was to review of the Use of Innovation Management Processes in Managing Innovation Driven Projects. To this end innovation management was first explained, then two papers that use it were discussed, as well as my own experiment using this techniques.

One of the primary reflections that constitute this paper is that decision-making is critical to any innovation process and management success. It means that complex and unplanned situations characterize decision-making in risky and uncertain environments as it is in many cases to formulate decisions in technology and innovation management (Rauter et al., 2019). Decision problems entail processing and converting such understanding and information into critical knowledge to control the innovation process and technologies, including design, planning, strategies, organization, and marketing of new products. Previous studies have not conclusively argued the relationship between superior decision-making and cognitive abilities, especially in uncertain and risky situations (Rauter et al., 2019). However, it is essential to underscore such relations and the value of such stages for acknowledging innovation and technology management.

Nonetheless, such stages are often not linear in their steps; instead, they are a chain with interconnections due to the interactive models of complex and innovative decision-making processes. Today, with the application of management decisions in organizations, new aspects of technology and innovation management theories have emerged (Annavarapu, 2016; Wollmann and Steiner 2017). As such significant reflections in technology and management and complex decision-making models can be argued as:

  1. Awareness tools and competencies provide a framework through which work is done in an organizations. The process involves search tools to educate entrepreneurs on setting priorities by availing enough information (Leković & Marić, 2016). Such awareness competencies affirm that the full view of sources isolate and solve, in a practical way, the firm’s information needs and knowledge related to the decision-making process in the organization.
  2. The diagnostic tools enable the organization to recognize and focus on the same challenges or available opportunities. The diagnostic elements are linked with the decision-making and the advancement of the organizational intelligence process because they define the organization’s present position and the need to change (Leković & Marić, 2016). Diagnostics are also instrumental in controlling multifaceted issues, mainly where uncertainty unfolds by linking fact-finding with identifying concerns and opportunities progressively.
  3. Taking action is essential in an organization because it aids the determination of what the organization needsto do and how it should achieve the desired changes. As part of the action-related activities, it improves the organizational learning processes (Leković & Marić, 2016; Naranjo-Valencia et al., 2018). As such, one of the essential competence is project alongside problem-solving critical for corporate learning.
  4. Also, the financing tools and competencies for the innovation and technology projects are critical aspects of innovation and technology management, particularly for the SMEs to close the competency circles, skills, aptitudes, tools, and attitudes.

References

Albors-Garrigos, J., Igartua, J. I., & Peiro, A. (2018). Innovation management techniques and tools: Its impact on firm innovation performance. International Journal of Innovation Management, 22(06), 1850051.

Arciénaga Morales, A. A., Nielsen, J., Bacarini, H. A., Martinelli, S. I., Kofuji, S. T., & García Díaz, J. F. (2018). Technology and innovation management in higher education—Cases from Latin America and Europe. Administrative Sciences, 8(2), 11.

Grigorescu, A., Maer-Matei, M. M., Mocanu, C., & Zamfir, A. M. (2020). Key drivers and skills needed for innovative companies focused on sustainability. Sustainability, 12(1), 102.

Grimpe, C., Sofka, W., Bhargava, M., & Chatterjee, R. (2017). R&D, marketing innovation, and new product performance: a mixed methods study. Journal of Product Innovation Management, 34(3), 360-383.

Iglesias-Sánchez, P. P., López-Delgado, P., Correia, M. B., & Jambrino-Maldonado, C. (2020). How do external openness and R&D activity influence open innovation management and the potential contribution of social media in the tourism and hospitality industry? Information Technology & Tourism, 22(2), 297-323.

Kotkova Striteska, M., & Prokop, V. (2020). Dynamic Innovation Strategy Model in practice of innovation leaders and followers in CEE countries—A prerequisite for building innovative ecosystems. Sustainability, 12(9), 3918.

Laeeque, S. H., Babar, S. F., & Ahmad, H. M. (2017). The integrative determinants of innovation performance: The role of learning organization and knowledge creation. Pakistan Journal of Commerce and Social Sciences (PJCSS), 11(1), 167-184.

Leković, B., & Marić, S. (2016). Innovativeness as a source of competitive advantage for entrepreneurial ventures and small business. Strategic Management, 21(3), 3-12.

Melane-Lavado, A., & Álvarez-Herranz, A. (2018). Different ways to access knowledge for sustainability-oriented innovation. The effect of foreign direct investment. Sustainability, 10(11), 4206.

Naranjo-Valencia, J. C., Naranjo-Herrera, C. G., Serna-Gómez, H. M., & Calderón-Hernández, G. (2018). The relationship between training and innovation in companies. International Journal of Innovation Management, 22(02), 1850012.

Prokop, V., & Stejskal, J. (2019). Determinants of innovation activities and SME absorption–Case study of Germany. Scientific papers of the University of Pardubice. Series D, Faculty of Economics and Administration. 46/2019. Web.

Rauter, R., Globocnik, D., Perl-Vorbach, E., & Baumgartner, R. J. (2019). Open innovation and its effects on economic and sustainability innovation performance. Journal of Innovation & Knowledge, 4(4), 226-233.

Schatzmayr, G. M. (2018). The influence of top management, innovation-culture and organization on open innovation, its impact on innovation success and cross sectoral learnings from benchmarking of an Austrian Biotech firm against a group of German companies (Doctoral dissertation, Wien).

Shakeel, J., Mardani, A., Chofreh, A. G., Goni, F. A., & Klemeš, J. J. (2020). Anatomy of sustainable business model innovation. Journal of Cleaner Production, 261, 121201.

Yan, M. R., Chien, K. M., Hong, L. Y., & Yang, T. N. (2018). Evaluating the collaborative ecosystem for an innovation driven economy: A systems analysis and case study of science parks. Sustainability, 10(3), 887. Web.

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