Sociology Assignment: Public Management For Innovation Technology

Question

Task: Please answer the three questions below in this sociology assignment. Each answer should be roughly 750 to 800 words long.
Please provide examples and references to strengthen your arguments.

Questions:
1. Innovation as a process
Describe innovation as a process. Why is it important to see innovation in this way? What are the main parts of the innovation process? How does this knowledge inform innovation management/governance strategies? How can public policymakers know if they are successful or not?

2. Modes of knowledge production
What is knowledge production and how is it connected to innovation processes? How has our understanding of knowledge production changed over time? What are the main frameworks that appeared in response to this change? Choose TWO of the main consequences of changing modes of knowledge production for public policy and elaborate on them using real-world examples.

3. Rationales for Public Policy Intervention
How have rationales for policy intervention transformed over the last century? What are the factors that have led to the change in rationales (for policy intervention)? What is the modern take on the intervention rationales? What is the spectrum of systemic problems? Provide some examples.

Answer

1. Innovation as a process
Discuss “Innovation as a process” in the sociology assignment.
Modelling of innovation including innovation processes had already evolved as a result of the growth of innovation principles. A wide variety of models exist for innovation processes. Models like these all have a similar notion that innovation activities may be modelled via the use of process models. New products and services are being introduced all the time. Thus, process innovation has increased in importance as a means of improving new product development's efficacy and efficiency. The innovation process is a series of activities which not only manages the invention but also helps define and shape the results such that the outcome is acceptable (Dossou-Yovo& Keen, 2021).

Components of Innovation
• Generation and Implementation of Ideas
Successful idea generation requires the right mix of competition and exploration. Thereafter, the new concept enters the mobilisation stage, when it is transferred to a new site. It is not uncommon for a fresh concept to require assistance from something other than the person who first came up with it. This stage is critical to the development of a new concept, and ignoring it can derail or even undermine the processes of inventing.

• Screening and Advocacy
Screening and advocacy must take place at some point in order to filter out ideas which lack promise without allowing participants to reject proposals impulsively because of their novelty. Researchers discovered that firms performed better when the assessment process was open and consistent because employees perceived more at ease when they knew how their concepts would be evaluated (O’Connor, 2012).

• Experimentation
At this point, it's critical to figure out who the consumer is and where the innovation would be used for. To put it another way: Even while a brilliant idea may exist, it may not be a good fit for a certain market.

• Commercialization
During the commercialisation stage, the business should first verify that the invention genuinely answers its consumers' concerns and then evaluate the costs and advantages of implementing the innovation. To be deemed an innovation, inventions must be made available to the general public. Commercialization, like lobbying, needs the involvement of the proper individuals in order to move the idea forwards (O’Connor, 2012).

• Implementation and Dissemination
There are two stages in the process of implementing an innovation: dissemination and adoption. At IBM workers are involved in the idea-generation process early on and are invited to participate in so-called "innovation jams," in that they are joined by clients, partners, and perhaps even employees' relatives. From the outset, IBM gives everybody an ownership in the concept, which helps it spread more widely.

Importance
Our knowledge of innovation as well as the benefits it brings to society has evolved significantly over the previous few decades. The deployment of a new or considerably enhanced commodity (good or service), technique, novel marketing approach, or new organisational method in company operations, workplace organisation, or external interactions is widely defined as innovation. Modern innovation practise demonstrates that the term "innovation" is intrinsically value-free and encompasses a wide range of activities, first from development of new information through its first practical implementation. The purpose of every innovation project is to find new ways to meet the needs and objectives of the intended audience, and this means that there will always be some element of risk as well as uncertainty involved.

Knowledge Management and Governance Strategies
A Chief Knowledge Officer (CKO) or perhaps a separate department may be in charge of implementing a KM strategy inside a business (Bitkowska, 2017). Modern and extensive research integrating governance principles alongside strategies to gather and produce information, organise, share and use it at the right time in the right location is lacking. Therefore, KM governance processes as well as principles are those procedures and concepts that serve as a basis for the evaluation of, regulation, oversight, and amendment of the KM process itself. In order to achieve the aforementioned goals, KM governance should focus on helping the company develop and implement a comprehensive knowledge management strategy that is in line with the company's value proposition and strategy, as well as regularly reviewing, approving, and monitoring KM investments in the firm's infrastructure as well as in human sharing knowledge methods (Lee, 2016).

Policy Makers success criteria
Policymakers may assess the success of their innovation deployment using ten different measures. In order for a firm to be a success, it must have a cross-functional division, devoted team leader, organisational structure, thereafter organisational strategy as well as effective management in place (Liyanage&Netswera, 2021).

2. Modes of knowledge production
Knowledge production
Modern sociology of science uses the phrase "knowledge production modes" to describe the ways wherein (scientific) information is constructed. There are now three types of production modes. Mode 1 is defined by theory development and testing of a profession towards to the principle of universal knowledge, whereas Mode 2 is characterised by knowledge that may be put to use in a specific context. In Mode 1,the given knowledge is general law and mostly cognitive, whereas Mode 2 information is specific and temporal. Mode 1, knowledge in data would be context free, whilst Mode 2 knowledge is temporally entrenched. Mode 1 the given knowledge would bemainly cognitive. Logic as well as measurement, while also regularity of planning and prevention, are used to validate knowledge in Mode 1, whereas experiential, interdisciplinary, and transdisciplinary procedures are used to validate knowledge in Mode 2. As an observer in Mode 1, the author's responsibility is to remain detached and objective; in Mode 2, the current researcher would be a socially responsible, integrated, and reflexive participant or change agent. "Mode 3" is defined by Carayannis and Campbell as a method of knowledge that focuses on the coexistence as well as co-development of several information and knowledge modes somewhere at the micro-individual, macro-organizational, and macro-societal levels (Liyanage&Netswera, 2021). This book discusses the interconnectedness of knowledge at the nano, micro, and meso - level, including the "democracy of knowledge" (knowledge being in a democratic system), "free market capitalism," as well as "entrepreneurial universities".

Knowledge production and connection with innovation
A company's ability to innovate is a result of its ability to generate and use new information. It's also about how these newer technologies may be transformed into services and goods that have monetary value in the marketplace. Innovators need to have a thorough understanding of the markets they're working with if they want to succeed. Inside an increasingly competitive marketplace, a company's ability to innovate and grow will be defined by the constant exchange of technical and market information (Meifort, 2015).

Knowledge Production evolution over time
Mode I
• University or Academic based research is the primary source of new knowledge.
• Research topics created within a single scientific area are often mono-disciplinary in character. They are only held
accountable towards their scientific colleagues if they get public financing.

Mode 2
• A rising number of colleges are participating in the programme.
• Not least since it deals with research problems addressed outside of a particular field instead of those posed inside it, it is frequently transdisciplinary in nature.
• Those who are financed by the government are held to a higher standard by the scientific community as a whole.

Contemporary
• Research would be neither "purely" fundamental nor applied, but rather combines the two to provide both new insight and valuable information.
• Science and technology are getting increasingly intertwined.
• The research and innovation system is made up of a more complex web of interconnected institutions.
• In a wide range of institutions and circumstances, new scientific knowledge is generated.
• Universities, governments, and businesses all work together through a variety of hybrid organisations, such as research centres, networks, and collaborations.
• In today’s modern "advanced science" and "frontier research," a variety of established scientific fields are combined to produce ground-breaking results.

Two Frameworks
• In scientific research, Pasteur's quadrant is a way to categorise undertakings that aim to get a deeper grasp of scientific issues while simultaneously providing direct benefit to society. There are many examples of this style of study, and Louis Pasteur's work is often regarded as an example of it (Kleinman, 1999).
• In a knowledge - based economy, the relationships between universities, industry, administration, and the general public are described by the quadrupled and quintuple invention helix frameworks. For example, Henry Etzkowitz and LoetLeydesdorff created an innovation helix framework theory that uses circles (helix) to symbolise each sector plus overlapping circles to indicate relationships between sectors (Pan & Guo, 2021).

2 Consequences of Changing Modes and it’s examples
Access to higher education has been made more widely available as a result of the growth of Mode 2 research, as well as modifications in HET institutions' structure and operation. For instance, in South Africa, Universities and colleges have seen a significant increase in their programme offerings that go well beyond the supply of disciplinary degree qualifications as a result of the simultaneous expansion of access and the development of new skill requirements resulting from the information economy.

The growth and diversification of programme delivery has also been a result. A highly educated and well-trained workforce is needed in the information economy, which has resulted in an explosion of paraprofessional as well as professional recurring and continuous education opportunities. In the end, it led in the formation of more diverse and open professional programmes. For instance, in South Africa, overwhelming majority of part-time, repetitive, and ongoing education takes place in "open learning" systems, which are residential or contact-time mixed with distant education techniques, and in certain cases with the support of information technology,

3. Rationales for Public Policy Intervention

Arguments for a new approach to policy intervention
Researchers are the only source of new ideas for neo-classical academics (and invention). Is it possible to turn the outcomes of research into goods or procedures that can be employed in the economy(Rosenberg 1982, 1994). There are no surprises in the neo-classical theory, which states that the process of invention follows a predetermined series of stages. When it came to large-scale scientific and technical projects, defence investigation, and energy, the neo-classical analysis gives authorities with compelling arguments to continue investing in these areas because of the high public rate of return, this same barriers for entry were substantial, and the considerations were also suspected large. Researchers are the only source of new ideas for neo-classical academics (and invention).

Further, the overall policy ramifications of the frameworks of innovation perspective diverge from the typical economy-based methodology of the neo-classical researcher. Continue reading. Despite the fact that the SI method has its foundation in evolutionary theory, the two approaches are nevertheless very distinct.. Whilst information asymmetries have been regarded a market failure throughout the neo-classical method, asymmetric information is important to give innovation and diversity underneath evolutionary theory as well as the SI approach. According to evolutionary theory, creativity is fueled by the processes of variety production and selection (e.g., competition). Furthermore, it emphasises the need of a well-defined innovation route. As one of its starting points, the SI method takes evolutionary theory as a starting point and focuses on how innovations develop and spread. Companies do not innovation in isolation, but rather via continual interactions within the system. This is emphasised by the SI method.

Factors that have lead to a change in rationales are as follows:
(1) First and foremost, the goals set by capitalist enterprises and the market process must be unattainable. There must be a problem if private individuals and market forces cannot fix it on their own. We've referred to this as a systemic issue. Alternatively, it might be referred to as a policy potential. (2) The state (national, regional, or municipal) and its government entities should also have or be successful in establishing the capability to address or reduce the problem. This might be referred to as a person's policy expertise).

Modern take on Intervention rationales
Sweden's government launched VINNOVA as an example of a new approach to intervention rationales.

The overall goal can be broken down its component parts: Serving as an innovation policy advisor to the administration in-house research on innovation relevant threads commissioned and conducted Assist and encourage innovation through developing (national, regional, and industry) policy programmes (Puech & Durand, 2017).

According to VINNOVA, "effective innovation systems are promoted at a nationwide, sectoral, and provincial scale. The interplay between these several levels is critical to the establishment of strong, long-term growth. Sweden's Triple helix must cooperate together to prioritise and create new projects in the country's most critical development sectors to ensure that innovation systems are efficient and successful.

Systemic Problems
This includes both physical infrastructure (such as transportation) and scientific infrastructure (such as high-quality universities and other research laboratories) as well as telecommunications infrastructure (Telecome and IT etc)

Transition problems: Firms and other players might experience challenges if they confront technology issues or if the present technological paradigm shifts are too much for them to handle. If new paradigms, radical new ubiquitous technologies, or big market shifts necessitate new technology solutions, companies may not be able to predict them.

Lock-in Problems: Out from inertia of society and technology, lock-in difficulties may impede the spread of more improved technology. 4 out of 5. There is a risk that businesses and other organisations may be unable to switch to newer technologies (as well as technology systems).

Hard and soft institutional problems: These problems are connected to both official and informal norms (laws, regulations) (Both cultural and social for example). Institutions have an important role in systems of innovation, according to the system of approach to innovation.
Problems related to informal as well as formal laws (laws, regulations) and are significantly more informal and implicit ones are both hard and soft institutional issues (social and political culture for instance). Institutions have an important role in systems of innovation, according to the system of innovation approach (COLETTI & RADAELLI, 2013).
Network problems: Some of them are the result of the model of innovation having too few or too many weak or strong links (blindness towards what occurs just outside of the network). However, even if the system may be suffering from network issues that may necessitate government intervention, it is impossible to accurately estimate the system's linking strength (Philipson, 2019).
Capability and learning problems: Deficiencies in human, organisational, and technological skills may restrict the ability of organisations to learn, adopt, or generate new technologies somewhere on the future.
Unbalanced exploration-exploitation mechanisms: Some systems are capable of producing diversity, but lack the procedures necessary to make appropriate selections. Other systems may have extremely sophisticated processes for making selects, but lack the potential to produce diversity.
Complementarity problems: They could not complement one other or those who may have not been linked so that the favourable advantages of complimentary qualities are not completely used (Pan & Guo, 2021).

References
Bitkowska, A. (2017). Knowledge management in production enterprises. Production Engineering Archives, 15, 23–26. https://doi.org/10.30657/pea.2017.15.06
COLETTI, P., & RADAELLI, C. M. (2013). ECONOMIC RATIONALES, LEARNING, AND REGULATORY POLICY INSTRUMENTS. Public Administration, 91(4), 1056–1070. https://doi.org/10.1111/padm.12006
Dossou-Yovo, A., & Keen, C. (2021). SMEs and the Innovation Management Process: A multi-level process conceptual framework. Technology Innovation Management Review, 11(1), 22–33. https://doi.org/10.22215/timreview/1414
Kleinman, D. L. (1999). Pasteur’s Quadrant: Basic Science and Technological Innovation. Donald E. Stokes. Isis, 90(4), 834–835. https://doi.org/10.1086/384572
Lee, M. C. (2016). Knowledge management and innovation management: best practices in knowledge sharing and knowledge value chain. International Journal of Innovation and Learning, 19(2), 206. https://doi.org/10.1504/ijil.2016.074475
Liyanage, S. I. H., &Netswera, F. G. (2021). Greening Universities with Mode 3 and Quintuple Helix Model of Innovation–Production of Knowledge and Innovation in Knowledge-Based Economy, Botswana. Sociology assignmentJournal of the Knowledge Economy. https://doi.org/10.1007/s13132-021-00769-y
Meifort, A. (2015). Innovation Portfolio Management: A Synthesis and Research Agenda. Creativity and Innovation Management, 25(2), 251–269. https://doi.org/10.1111/caim.12109
O’Connor, G. C. (2012). Innovation: From Process to Function. Journal of Product Innovation Management, 29(3), 361–363. https://doi.org/10.1111/j.1540-5885.2012.00909.x
Pan, J., & Guo, J. (2021). Innovative Collaboration and Acceleration: an Integrated Framework Based on Knowledge Transfer and Triple Helix. Journal of the Knowledge Economy. https://doi.org/10.1007/s13132-021-00852-4
Philipson, S. (2019). Sources of innovation: Consequences for knowledge production and transfer. Journal of Innovation & Knowledge. https://doi.org/10.1016/j.jik.2019.01.002
Puech, L., & Durand, T. (2017). Classification of time spent in the intrapreneurial process. Creativity and Innovation Management, 26(2), 142–151. https://doi.org/10.1111/caim.12214