The effect of prior knowledge, cognitive styles and social network on opportunity recognition: the role of absorptive capacity
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2021
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2564
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eng
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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Fan, Jing (2021). The effect of prior knowledge, cognitive styles and social network on opportunity recognition: the role of absorptive capacity. Retrieved from: https://repository.nida.ac.th/handle/662723737/6857.
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The effect of prior knowledge, cognitive styles and social network on opportunity recognition: the role of absorptive capacity
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Abstract
The objective of this study is to make better sense of individual-level factors in
opportunity recognition in the context of China's IT industry. This study seeks to
analyze theoretically and empirically how prior knowledge (i.e., customer need
knowledge, technological knowledge depth, and technological knowledge breadth),
social network (i.e., social network size and social network strength), cognitive styles
(i.e., knowing style, planning style, and creating style) and absorptive capacity are
related to opportunity recognition. To date, limited research has empirically examined
the direct and indirect effects of the above-mentioned variables on opportunity
recognition in the context of China's IT industry.
Drawing on human capital theory, social network theory and the view of
cognitive psychology, a conceptual model that shows the relationships between these
variables is developed. To examine the conceptual model, this study conducts a
survey to employees of IT firms located in Beijing, Guangdong, and Jiangsu. With the
aid of software SPSS 24.0 and AMOS 24.0, preliminary analysis is conducted to
make sure that the proposed measurement model is satisfactory. Bootstrap procedure
is used to examine the proposed hypotheses.
The results of this study reveal the positive direct effects of technological
knowledge breadth, knowing style, and creating style on opportunity recognition. The positive effect of absorptive capacity on opportunity recognition is also established.
This study identifies three mediating mechanisms through which knowing style,
planning style, and creating style develop their effects on opportunity recognition.
Additionally, the results of this study show that customer need knowledge,
technological knowledge depth, social network size, and social network strength do
not play important roles in opportunity recognition.
By showing the different effects of the above-mentioned variables on
opportunity recognition, this study provides a more fine-grained understanding of
individual-level factors in opportunity recognition. The findings of this study shed
new light on what individual-level factors are helpful in recognizing opportunities in
the context of China's IT industry. This study makes several contributions to the
theory of opportunity recognition and provides useful implications for
entrepreneurship practice. Finally, this study concludes with its limitations and
directions for further research.
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Thesis (Ph.D. (Management))--National Institute of Development Administration, 2021