¶ … administered to 50 respondents. The data obtained from these participants was credible for analysis since there were no substantive missing values. The questions were based on a Likert Scale that made it easier for participants to provide their responses and enhance reliability. Data obtained from this instrument was analyzed using descriptive statistics and measures. In this case, the researcher utilized Cross Tabulation analysis and Chi-Square analysis.
Participants' Demographics
This study had 50 respondents working in German and Swiss labor markets though the research was not restricted to participants from German or Swiss origins. Actually, the respondents were from different nationalities though they were working in German or Swiss labor markets as shown in the table below.
Table 1: Nationality of Respondents
Nationality
Number of Respondents
Percentage
German
14
28%
Swiss
6
12%
Italian
7
14%
Lebanese
2
4%
Indian
7
14%
English
2
4%
Spanish
3
6%
Polish
3
6%
Danish
2
4%
Georgian
2
4%
Salvadorean
1
2%
Lithuanian
1
2%
Source: Own Elaboration
The study respondents included C-level executives (CEOs, COOs, HR Managers, HR Advisors, Directors, Co-directors, Consultants, and Assistant Directors) who have worked in their respective companies for a period of between less than a year to more than five years. 72% of the respondents were males whereas 28% were females. On the other hand, 58% worked in German labor markets whereas 42% worked in Swiss labor markets.
Study Results in Relation to Research Objectives
The research objectives listed in the previous chapter were the basis for conducting this study and analyzing data collected from the respondents/participants. In this case, the researcher utilized the objectives as the premise for analytical comprehension of data obtained from the questionnaire that was administered to the 50 participants. Consequently, the research findings/results were grouped as follows:
Most Suitable Innovation Models
The research question that guided this study was the determination of the most suitable innovation model (closed or open) that helps in achievement of an organization's innovation goals and how they can be successfully implemented. As previously indicated, this research issue informed the study on the premise that there are complexities in understanding the most suitable model that is customized based on an organization's innovation goals (Sviokla & Wasden, 2010). In this case, the respondents in this study were working in companies or organizations that had implemented different innovation models for the business goals. 56% of the respondents are working in companies with closed innovation model whereas 44% were utilizing open innovation models as shown in Table 2 below.
Table 2: Innovation Models Adopted by the Companies
Innovation Model
Number of Companies
Percentage
Open Innovation Models
28
56%
Closed Innovation Models
22
44%
Source: Own Elaboration
On the question of which innovation models would be suitable for the organization's operations, success and sustainable growth, the responses were as shown in Table 3 below.
Table 3: Most Suitable Innovation Model
Recommended Innovation Models
Number of Respondents
Percentage
Open Innovation
33
66%
Closed Innovation
7
14%
Both
5
10%
Unsure (or Not Applicable)
5
10%
Source: Own Elaboration
As shown in Table 3 above, 66% of the respondents strongly believe that open innovation is a more suitable innovation model towards helping an organization achieve its innovation goals. This is followed by closed innovation model and a mixture of both closed and open innovation models and at 14% and 10% respectively. This implies that organizations should mostly consider adopting open innovation models across all business operations. If open innovation would be an unsuitable single innovation model for a company, a mixture of both closed and open innovation should first be considered before closed innovation.
The researcher examined whether these recommendations of the most suitable innovation model for organizational operations, success and sustainable growth are attributable to the respondents location. Using Cross Tabulation and Chi-Square analyses, an evaluation was carried out to determine the existence of any link between the country of operation and the suggested innovation model for organizational operations, success and sustainable growth. In essence, the researcher sought to determine whether the respondents' choice or suggestion of a suitable innovation model. This analysis would help in determining the generalization of the suggested innovation model for organizational operations, success, and sustainable growth. The use of Cross Tabulation and Chi-Square analyses in this process helps in testing the relationship between these variables. Additionally, these statistical analyses measures helps in enhancing the credibility and reliability of the recommended innovation models by this group of respondents. The results of the analysis were as shown in the tables below.
Table 4: Cross-tabulation for Link between Country of Operation and Innovation Model
Cross Tabulation Frequency Percent
Is closed or open innovation suitable for the organization's operations, success, and sustainable growth?
Closed Innovation
Open Innovation
Both
Unsure/Not Applicable
Row Totals
What country do you work in?
Germany
5
17
3
4
29
Row Percent
17.24%
58.62%
10.35%
13.79%
58%
Switzerland
2
16
2
1
21
Row Percent
9.52%
76.20%
9.52%
4.76%
42%
Column Totals
7
33
5
5
50
Column Percent
14%
66%
10%
10%
Row Percent = (Observed Value/Row Totals)*100
Row Percent for Row Totals = (Row Total/Column Totals)*100
Source: Own Elaboration
Table 5: Chi-Square Analysis for Link between Country...
This result is not significant at p < 0.05, which implies that the
null hypothesis is rejected. Consequently, the country of operation was found to have no impact on the recommended innovation model for organizational operations, success and sustainable growth. The respondents recommendations of open innovation model as the most suitable followed by closed innovation model was not determined on the basis of where their organizations were located. Additionally, their recommendations were not necessarily based on the kind of innovation model adopted by their respective companies or organizations.
Key Success Factors for Adoption of Innovation Models
An analysis of the key success factors adopted by the organization in relation to innovation models was also conducted. This analysis was conducted based on two research objectives i.e. determining necessary success factors for effective implementation of innovation models and determine the concept and
learning process of closed and open innovation. In this case, several factors were identified and included in the questionnaires administered to the 50 respondents. These factors include incorporating innovation in business strategy and operations, review of innovation models/processes towards continued success, and ensuring employees understand and implement innovation models. The other factors are establishing a corporate culture that promotes and enhances continued innovation and consideration of organizational processes/factors when choosing innovation models.
To determine whether these factors play a crucial role in the successful/effective implementation of innovation models, the researcher considered the respondents Likert Scale scores. A score of between 3 and 5 was considered high whereas a score of 1-2 was considered low in each of these factors. If the number of respondents with high scores was significantly high, the factor was considered crucial in
adoption or implementation of innovation models and vice versa as shown in Figure 1 below.
Figure 1: Respondents' Scores in Key Success Factors
As shown in the Figure 1, there were high scores in each of the key success factors for implementation of innovation models. Consideration of organizational factor when choosing an innovation model, incorporating innovation in business, and implementing innovation throughout the organization had a high score of 86%, 82% and 82% respectively. Establishing a corporate culture that promotes innovation, ensuring employees understand and implement innovation, review and/or changing innovation models/processes, and ensuring innovation is at the frontline of operations had a high score of 78%, 72%, 76% and 74% respectively.
The responses on the Likert Scale for these factors are utilized to determine the link between these factors and successful implementation of innovation models in an organization, especially in relation to organizational operations, success, and sustainable growth. In this case, cross tabulation analysis is carried out on each of these factors based on respondents' high scores i.e. between 3 and 5. The results of the cross tabulation is in turn utilized in chi-square analysis or test, which helps in establishing the link between the two variables based on the level of significance of 0.05 as shown in the tables below.
Table 6: Cross Tabulation on the Link between Factors and Successful Implementation
Cross Tabulation Frequency Percent
Link between Key Factors and Successful Implementation of Innovation Models
Slightly (3)
Much (4)
Very Much (5)
Row Totals
Key Factors in Implementing Innovation Models
Innovation in Business Strategy
7
22
12
41
Row Percent
17.07%
53.66%
29.27%
14.91%
Innovation in the whole organization
16
18
7
41
Row Percent
39.03%
43.90%
17.07%
14.91%
Innovation at the Frontline
8
21
8
37
Row Percent
21.62%
56.76%
21.62%
13.45%
Review of Innovation Models
15
16
7
38
Row Percent
39.47%
42.11%
18.42%
13.82%
Employees Understand Innovation
11
20
5
36
Row Percent
30.56%
55.56%
13.88%
13.09%
Corporate Culture to Promote Innovation
8
19
12
39
Row Percent
20.51%
48.72%
30.77%
14.18%
Considering Organizational Processes
16
23
4
43
Row Percent
37.21%
53.49%
9.30%
15.64%
Column Totals
81
55
Column Percent
29.45%
50.45%
20%
Row Percent = (Observed Value/Row Totals)*100
Row Percent for Row Totals = (Row Total/Column Totals)*100
Source: Own Elaboration
The results of this cross tabulation are used in chi-square analysis in Table 7. The level of significance is 0.05, which is the normal level. To determine the cumulative probability value (P), the researcher utilizes a Chi-square calculator to calculate the Chi-square score and degree of
freedom based on a significance level of 0.05. As shown in Table 7, the researcher determined the overall Chi-square score through adding the chi-square score for all items or factors analyzed in the cross tabulation analysis. The overall chi-square score is then used to calculate the cumulative probability value.
Table 7: Chi-Square…
