1. What are the contributions in "Analysis of organizational factors affecting employee innovation" ?
This study aimed to holistically explore the organizational factors affecting employee innovation using principal component analysis ( PCA ) and condense the dimensionalities for a better focus of organizational development.. The study executed a survey questionnaire and collected useful data from one hundred and ninety-five ( 195 ) respondents of various Indian companies.. The study identified forty-six sub-factors and evolved into nine major organizational factors influencing employee innovation namely organization structure, organization culture and environment, corporate strategy, innovation process, employee, technology, resources, knowledge management and management and leadership.. The study recommended that any firm must focus on these factors to encourage employee innovation leading to overall organizational success.
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2. What are the future works mentioned in the paper "Analysis of organizational factors affecting employee innovation" ?
Any further research studies may consider a qualitative approach in gathering employees ’ viewpoints using thematic analysis, Delphi study, or focused group to list more appropriate organizational factors specific to industrywise.
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3. What are the key determinants of organizational success?
Previous research studies in HR management extensively stressed on employee innovation susceptibility, employee and operational competencies, managing organizational innovation and their related aspects, theories and models of work-life, socio-cultural issues as key determinants for organization success.
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4. What is the role of employees in the innovation process?
Employees act as a channel between organizational factors and the innovation process as they were found as a potential source to reinforce innovation.
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![Table 4 explains the summary of the rotated factor matrix of organizational factors using Principal Component Analysis with Varimax rotation under Kaiser Normalization [19]. The PCA method and rotation converged into 8 iterations. All the forty-six sub-factors were extracted into nine factors and accounted for 74.83 % of the total variance. Only those factor loading above 0.50 were considered to be significant [14].](/figures/table-4-explains-the-summary-of-the-rotated-factor-matrix-of-2iosrzyi.png)