創業意圖及行動關鍵因素之研究

Abstract

創業家對國家的經濟成長和社會發展帶來技術創新及提供工作機會的正向貢獻，提升創業和自我雇用對處理年輕人的就業議題是一個有效的策略，而研究影響創業意圖與實際採取創業行動的關鍵因素，將有助於了解如何提升人們成為創業家的意圖及行動。目前有關創業意圖及創業行動的研究，都將兩者獨立分開討論，但許多變數同時出現在創業意圖及創業行動中，這些變數是先影響創業意圖再影響創業行動，抑或直接影響創業行動，目前沒有相關的研究。本研究以影響創業意圖的主要模型Ajzen的計畫行為理論(theory of planned behavior, TPB)(Ajzen, 1991)(Ajzen, 2002)及Shapero and Sokol的創業事件模型(the entrepreneurial event model, EEM)(Shapero and Sokol, 1982)為基礎，將影響創業意圖與創業行動的變數，包括:人格特質五個向度(Big Five personality traits)、控制信念(locus of control)、創業支持與創業阻礙，同時列入模型成為系列中介變數，以這些序列中介變數建構創業意圖到創業行動的概括創業模型，藉以事前了解及預測影響人們創業意圖及實際創業行動的關鍵變數及其影響機制。研究方法採用結構方程模型(structural equation modelling, SEM)的確定性因素分析(confirmatory factors analysis, CFA)建構測量模型，並以測量模型潛在變數分別建構創業意圖及創業行動結構模型，並將獨立的創業意圖模型及創業行動模型加以連結成概括創業模型，同時，以SPSS巨集程式PROCESS分析概括創業模型各路徑的直接效果與間接效果，藉此說明模型內中介變數及干擾變數的影響。研究最後，以類神經網路Artificial Neural Network, ANN）及決策樹的CART演算法(Classification and Regression Tree)進行分類，決定創業意圖及創業行動每一條路徑錯誤率最低的決策法則，提供決策者快速判斷人們的創業意圖及創業行動傾向，同時，了解如何提供必要的支援以提高創業意圖及行動。由概括創業意圖的研究結果顯示:人格特質五個向度僅有經驗開放性及外向對創業意圖有直接影響，且可透過TPB-EEM模型中的主觀規範及創業需要對創業意圖產生間接影響，而創業支持及控制信念則對創業意圖沒有直接及間接效果。研究也發現:創業意圖對創業行動的直接效果最明顯，但也可透過創業支持、控制信念及創業阻礙對創業行動產生間接效果。

Studies have discussed numerous key variables and their influences on entrepreneurial intentions and actions. However, many of these variables appear simultaneously in the models of entrepreneurial intentions and actions. The influence mechanism of these variables has not been investigated. Therefore, this study investigated widely used variables that represent entrepreneurial intentions and actions, as well as serial mediators, to construct models of entrepreneurial intentions, entrepreneurial actions, and generalized entrepreneurship. Participants in entrepreneurial activities and entrepreneurial courses, and practical entrepreneurs in Taiwan, were interviewed through questionnaires (N = 276). Models were constructed to understand the influence mechanisms of key variables and pathways on people's entrepreneurial intentions and actions. Moreover, the direct and indirect effects of the pathways in the models were explored. Finally, the artificial neural network was used to classify the groups and the decision tree algorithm Classification and Regression Tree was used to build decision rules to briefly judge and predict the tendencies of entrepreneurial intentions and actions. The results showed that the Big Five personality traits directly affect entrepreneurial intentions and exert indirect influence on entrepreneurial intentions through subjective norms and entrepreneurial desirability. Entrepreneurial actions were influenced by entrepreneurial intentions through serial mediators, including the external locus of control, entrepreneurial support, and entrepreneurial obstacles. We briefly judged the likelihood of entrepreneurial intentions and actions according to the numerical values of the variables in the decision rules. Changing the scope of these variables to promote people's entrepreneurial intentions and actions was also discussed.