[논문]The Effect of Creative Potential on Innovation Behavior: focusing on Design Thinking

KIM, Taehyung

doi:10.15722/jds.18.8.202008.65

The Effect of Creative Potential on Innovation Behavior: focusing on Design Thinking 원문보기

유통과학연구 = Journal of distribution science, v.18 no.8, 2020년, pp.65 - 74

KIM, Taehyung (Department of Data Knowledge Service Engineering, Graduate School, Dankook University)

Abstract ▼ AI-Helper

Purpose: The purpose of study is to examine the effects of design thinking-based programs on creative potential, creativity and innovation behavior, as well as the mediating effect of creative potential and creativity. Research design, data and methodology: The study was conducted through a four-step process. First, the previous studies were investigated. Second, a total of three experts were reviewed to improve and supplement the program. Third, a workshop-based design thinking program was conducted four times. Fourth, the effectiveness of the program was reviewed through data analysis. Results: The design thinking-based program was found to have a statistically positive effect on creative potential, creativity, and innovation behavior. As another hypothesis of this study, by applying the design thinking-based program, it was statistically confirmed that creative potential has a direct, indirect effect, and a mediating effect on innovation behavior. Conclusions: These results provide usability for design thinking in terms of direction for creativity-based creative problem solving and innovation. Finally, design thinking can be used to develop and utilize new services and discover new ideas, especially improve the competitiveness of the company. In addition, it means that the level of innovation action can vary depending on the level of the individual's creative potential.

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표/그림 (9)

그림 Figure 1 : Research Model
표 Table1 : General characteristics of the subject
그림 Figure 2 : Research procedure
표 Table 3 : Final designed design thinking program
그림 Figure 4 : Change in creative potential before and after the program
표 Table 4 : Difference between Creative Potential, Creativity, and Innovation Before and After the Program
그림 Figure 5 : Creativity change before and after the program
그림 Figure 6 : Change in innovation before and after the program
표 Table 6 : Correlation between Creative Potential, Creativity, and Innovation

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문제 정의

This study sought to identify the effects of design thinking-based programs on creative potential, creativity, and innovative behavior and to examine the mediating effects of creative potential and creativity on the relationship with innovative behavior. The following findings and implications related to these research objectives are presented.

제안 방법

This may require measurement items from different perspectives by sector and organization. Although this study was limited to creative potential, creativity, and innovative behavior as variables that represent effectiveness through design thinking, it is hoped that design thinking will be used to derive more diverse innovation outcomes through studies that extract, examine, apply, and analyze various factors.
Based on such prior studies, this study aims to identify the effects of design thinking on each variable and determine how they relate to the variables, from the 'creative potential' inherent in the person from the perspective of own creativity to the 'creative potential' of the individual and the creation of new ideas and the 'innovative behavior' of the individual from the perspective of implementing the idea.
A summary of the statistical analysis methods undertaken for this study is as follows. First, frequency analysis was conducted to identify the general characteristics of the research subjects. Second, Cronbach's α was calculated to determine the reliability of the measuring tool.
To this end, a self-entry survey was conducted on participants in the program and 62 people, excluding unfaithful respondents, were selected as subjects of the study. Frequency analysis was performed to identify the general characteristics of the subjects.
To verify this, this study designed and applied a design thinking-based program on the basis of expert review. Further, detailed factors were selected for each variable, including eight items for creative potential, 11 items for creativity, and five items for innovative behavior, and their feasibility was secured through frequency analysis and reliability analysis. The response sample t-test confirmed that the study hypothesis was statistically significant.
This study was conducted through a total of four stages. In order to design the design thinking program in the first stage, the relevant theory and prior research were investigated, and the structure of the entire program was derived by benchmarking the relevant program and implementation process. In order to verify the effectiveness of the program designed in the second stage, the improvement and supplementation process of the program was carried out through review by a total of three experts.
In order to ensure the validity of the program, the program was modified and supplemented through several consultation meetings and reviews by three experts with at least five years of experience in IT, education, and management, including researchers who participated in the program development for about two months from June to August 2018.
This design thinking aims to create a concept for new products, services, or digital applications to promote innovation and develop solutions to so-called evil problems. Rather than focusing on quantifying solutions and starting the problem, it has a clear distinction in that it discovers as many diverse ideas as possible during the problem solving process and then rapidly prototypes and tests.
The basic design of the entire program utilized the five-step process of design thinking presented by Stanford University's d.school, and detailed programs were organized in consideration of future strategy methods and commercialization strategies in the direction of proactively responding to rapid changes in the future and enhancing practicability in the field.
school, and detailed programs were organized in consideration of future strategy methods and commercialization strategies in the direction of proactively responding to rapid changes in the future and enhancing practicability in the field. This program has completed the first draft after a review, revision, and improvement process including four researchers in the fields of data science, management, and education.
First, application of design-thinking-based programs has been shown to have statistically positive effects on creative potential, creativity, and innovative behavior. To verify this, this study designed and applied a design thinking-based program on the basis of expert review. Further, detailed factors were selected for each variable, including eight items for creative potential, 11 items for creativity, and five items for innovative behavior, and their feasibility was secured through frequency analysis and reliability analysis.
While existing studies mainly focus on verification of reliability and validity through measurement, the results of this study contribute to clarifying the relevance of the creative potential, creativity, and innovative behavior of the participants, along with the validity of the design thinking program. Therefore, it suggests the need to improve design thinking and creative potential in the direction of solving problems based on creativity and achieving innovative results in the future, and it is believed that it can help derive approaches for developing design thinking-based programs in various fields and achieving better results.

대상 데이터

This study was conducted based on data obtained from the results of the design thinking program at A University in Gyeonggi-do in August 2018.
To this end, a self-entry survey was conducted on participants in the program and 62 people, excluding unfaithful respondents, were selected as subjects of the study. Frequency analysis was performed to identify the general characteristics of the subjects.

데이터처리

A response sample t-test was conducted to verify changes in the level of creative potential, creativity, and innovative behavior after the program was implemented.
Fourth, Pearson's correlation was conducted to determine the correlation between creative potential, creativity, and innovative behavior. Fifth, hierarchical regression analysis was conducted to verify the relationship between creative potential, creativity, and innovative behavior. Sixth, the bootstrap verification proposed by Hayes was conducted to derive indirect, direct, and total effects of creative potential on innovative behavior by mediating creativity.
Fourth, Pearson's correlation was conducted to determine the correlation between creative potential, creativity, and innovative behavior.
Second, as one of the hypotheses of this study, it was statistically confirmed that the application of a design-thinking-based program has creative potential as well as direct, indirect, and overall mediated effects on innovative actions in addition to the enhancement of creativity. In this study, the correlation and influence relationship between variables was identified through Pearson correlation and hierarchical regression analysis, and the statistical interfactor mediating effect was confirmed through bootstrap verification. This means that the level of innovative behavior may vary depending on the level of individual creative potential, and it can be interpreted that it is helpful to increase not only individual creativity but also creative potential in order to increase innovative behavior.
Pearson's correlation was performed to determine the correlation between creative potential, creativity, and innovative behavior.
Second, Cronbach's α was calculated to determine the reliability of the measuring tool. Third, a response sample t-test was conducted to verify the statistical significance of changes in creative potential, creativity, and innovative behavior before and after the program was implemented. Fourth, Pearson's correlation was conducted to determine the correlation between creative potential, creativity, and innovative behavior.

성능/효과

First of all, the verification of the impact relationship between variables before the program was conducted showed that creative potential had a significant positive effect on creativity (B=.737, p<).001).
Fourth, the direct and creative potential before and after the design thinking program is implemented is mediated with the direct and creative effects on innovative behaviors, and the total effects of combining the direct and indirect effects on innovative behaviors are compared.
Second, as one of the hypotheses of this study, it was statistically confirmed that the application of a design-thinking-based program has creative potential as well as direct, indirect, and overall mediated effects on innovative actions in addition to the enhancement of creativity. In this study, the correlation and influence relationship between variables was identified through Pearson correlation and hierarchical regression analysis, and the statistical interfactor mediating effect was confirmed through bootstrap verification.
The creative potential of controlling the effects of creativity did not significantly affect innovative behavior, and creativity was shown to have a significant positive effect on innovative behavior (B=.530, p<).01).

후속연구

Another limitation of this study is the failure to take into account demographic variables of participants such as the type of work, age, number of years of service, etc. In the future, we hope that studies will be conducted to develop and utilize design thinking programs applicable by stage and level by securing more diverse samples depending on the target and context and deriving various improvement directions by type through hierarchical regression or cluster analysis. It is also a limitation that the sample size of this study was 62.
For diversity of research, sample should be collected through various groups. In the next study, the sample size needs to be further expanded.

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