Most research outcomes offer a "mental jump" from knowledge to technology (for instance product innovation). This is because knowledge is an intangible asset and technology (eg. product) is a tangible asset. Do we really have an approach to combine knowledge and technology? I appreciate if you can provide me any idea or recommendation of journal articles/papers on this topic.
Yes, indeed! Presumably it takes knowledge to develop and build technology? The knowledge is, in effect, made tangible in the tangibility of the product.
Christopher NOCK
Dear Gezahegn Tesfaye Dadi , it is really a wonderful issue. I have tried to look around and tried to share the information that I got in the following ways.
Dear Gezahegn, more important than the knowledge and skills themselves is how they are utilized. The often esoteric protocols of the scientific method actually have a pedestrian benefit – they minimize the risk of making costly decisions. While it’s not productive to get bogged down in geeky minutia, some technical details can have big business consequences. Here are some of the points on how to tie knowledge, skills, tools and data together by using core business skills, scientific thinking and a dash of common sense.
Frame the issue: Make sure you understand the key business issues, what decisions must be made, how they will be made and by whom. How you frame the issue drives research design. When planning research, think about the deliverables and the end users first and work backwards. Be careful about the assumptions you make and always be on the lookout for confirmation bias – searching for, interpreting or recalling information in a way that confirms your beliefs. A great deal of time can be wasted correcting mistakes made in the early stages of a research project. These often occur because we haven’t thought things through or have made off-the-cuff assumptions that turned out to be wrong. If advanced analytics will be used it’s best to design them into the research whenever possible. Establish realistic timelines – haste does make waste.
Construct a path diagram: Path diagrams similar to those used in path analysis and structural equation modeling can help you visualize plausible ways variables may be interrelated.
Exploit the researcher’s toolbox: Often more than one research method or statistical technique will get the job done and frequently several are used in conjunction. Steer clear of a cookie-cutter approach to analytics. Time and budget are obviously things to think about and may rule out the approach you feel is ideally suited for a project, so you need to be flexible (without cutting corners).
That fascinating result may be wrong: Even supposedly clean data can have serious errors. Your data may turn out to be quite unrepresentative of your target population. If some pattern seems weird or, on the other hand, looks like a finding that will dazzle your client…it could mean there is a problem with your data. Many bad decisions have also resulted from data dredging. When done by professionals, multivariate analysis is less risky and more informative than looking through reams of cross tabulations.
Keep to the facts: Distinguish between facts, hypotheses, and speculation. Avoid being seduced by sexy interpretations and recommendations that are actually based speculation or pseudoscience. Let’s not forget that intellect and technology are not substitutes for integrity.
Never stop learning: Many excellent books have been written about decision-making, such as Thinking, Fast and Slow (Kahneman), Simple Heuristics That Make Us Smart (Gigerenzer et al.), Risk Assessment and Decision Analysis (Fenton and Neil) and Experimental and Quasi-Experimental Designs (Shadish et al.).
Though science is often mystified in the news and entertainment media, the essence of the scientific method does not require advanced mathematics or technical skills of any kind. It does require critical thinking but this can be acquired in a multitude of ways. Other kinds of knowledge and skills are important too but scientific thinking is fundamental to sound research and can act as a bridge among researchers who are specialists in very dissimilar areas.
You can't have technology without knowledge in any field were technology is developed.
I think, knowledge pushes you to ask objective questions / remarks ... and the technology comes after to answer / confirm ....
Investing in technological knowledge and skills sounds a good combination.
- Vocational training
-Etc
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Knowledge guides technology towards doing well. Between knowledge and technology a reversible relationship. because technology corrects some ideas.
Technology gives tangibility to knowledge although knowledge is the bedrock technological innovation. When you see technology you have seen knowledge in display.
Both help each other. With knowledge the technology can be improved and by technology we can enhance the knowledge for example to study human tissues and organs 3D printing is helpful to fabricate identical body parts. With our knowledge in mechatronics we can improve the 3D printing machines and so on.
Actually, we are talking about two opposite faces of one coin, but to strengthen relations, it is important to depend on the practical applications.
Regards,
Emad
With good knowledges we can do a wanderful technology. Because technology become from a good ideas that nesseciate a minimum of a knowldges
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