臺灣博碩士論文加值系統

近年來,台灣產業歷經許多挑戰,其中食品產業與生技產業備受市場關注,尤其,這兩類產業都具有一定程度之國際化經驗且對於資本市場更具有影響性,因此,這些特質引發本論文以有趣的觀點加以剖析產業之產業風險變化,以及捕捉企業營運特徵,試圖從產業未來發展之利基,提出對於企業之管理意涵。
企業之營運績效是大多數企業主關心重要指標,影響營運績效的因素很多,但是,存在於個別產業的經營課題或是面臨營運特徵的確不同,在經營課題方面,例如近年來,食品產業的經營紛擾甚多,食品安全問題不曾間斷,社會大會對於食品產業的信心崩壞。然而,食品產業在台灣資本市場具有一定影響力,甚至經營國際化市場的經驗豐富,不禁令人心虛。當然,食品產業也存在很多經營優質的企業,但是當整體食品產業共同面臨產業風險劇增的情況,似乎已經不是個別食品公司能夠置身事外,甚至可能因為產業風險的不確定性,進而侵蝕到個別食品公司之營運績效。
在營運特徵方面,近年來,台灣媒體大幅報導生物技術產業之研發能量以及投資潛力性,於是資本市場更鎖定生物技術產業作為重要投資標的,投資人更是大量投資於生物技術產業,實際上,媒體資訊或是投資人是否真正認知生物技術產業,的確令人存疑。因此,本文更進一步分析生物技術產業的真實樣貌,從生物技術產業之營運特徵,尤其規模效果的影響性,討論生物技術產業之研發創新等因素,對於營運績效之衝擊。永續經營是任何產業發展的重要使命,當產業發展在不斷前進的過程中,產業更需要以勇氣面對其為人詬病的經營暗處,以及很務實展現發展能力。因此,本文透過對於食品產業經營課題的重新檢討,以及觀察生物技術產業的營運特徵,希冀透過實證方法,發現這些產業實際的樣貌,並提供更多政策建議給予產業、主管機關以及投資人作為參考。
在過去幾年發生一系列令人震驚的國內食品安全醜聞之後,食品產業風險成為公眾注目焦點。本文採用使用2010 - 2016年台灣食品產業為例,分析公司價值,產業風險與總體經濟之間的關係。縱橫平滑移轉迴歸模型研究結果顯示,產業風險和痛苦指數與企業價值呈負向關係,而客戶資本與公司價值之間存在正向關係。然而,在高產業風險下,客戶資本和公司價值呈負向關係,這意味著公司的營銷推廣將無效。在經濟波動衝擊之下,產業風險變化與企業營運特徵是社會大眾所關切的議題,從整體產業風險面而言,產業風險程度可能影響到企業價值,尤其當產業風險形成,企業可能投入再多資源都是無益的,喚醒企業必須重新思考經營應有的態度。本文建議食品產業建立社會和消費者的高度信任,並且致力於對質量要求之積極態度。
在企業營運特徵面而言,該如何創造高經營績效是企業戰戰兢兢所追求的,著手大量投入研發創新與生產力,是否等同於獲得高經營績效,可能存在營運特徵之盲點,基此,本文以台灣生物技術產業在2008-2017年期間為例,分析企業生產力對企業績效的不同規模門檻結構,而規模擴張與績效呈現倒U型關係,結果表明當企業規模逐步擴張時,應留意對於經營績效持續保持提升之動能。我們發現企業之生產力具有不同的影響,其中我們觀察到大多數小型企業和大型企業間之績效,生產率和創新的影響具異質性,並表明大型公司的生產力和創新能力低於小型企業。在管理政策方面,我們建議大型企業加強對生產力和創新能力的管理,積極提高生產力績效,增強創新貢獻。
最後,經由本論文發現,食品產業與生技產業之間,存在彼此之間可以相互學習之處,例如食品產業過去重視客戶資本,但是忽略研發創新之重要性,未來確實是食品產業應該投入更有研發創新,方能夠產生更多食品產業之長期競爭力。再者,從世界潮流趨勢,重視E(環境),S(社會),G(治理)之永續發展,食品產業會比其他產業具有更重大之社會責任,讓消費大眾得以信賴食品產業之品質可靠性,建立食品產業與消費大眾之食安共識。
另外,生技產業具有強韌之研發創新技術,的確是生技產業之重要優勢,然而,本論文發現,當生技產業邁向大規模成長之際,似乎其研發創新對於經營績效之效益產生遞減效果,顯示邁向大規模之生技公司,應該更注意研發創新之效果,方能維持公司之長期競爭力。

In the past ten years, Taiwan's industries have experienced many challenges. Among them, the food industry and the biotech industry have attracted much attention from the market. In particular, these two types of industries have a certain degree of internationalization experience and are more influential to the capital market. Therefore, these characteristics trigger this thesis to analyze the industrial risk changes of the industry with interesting points of view, and capture the characteristics of business operations, try to take the niche of the future development of the industry, and propose the management implications for business owners.
Under the impact of economic fluctuations, the changes in industrial risks and corporate operations' characteristics have become issues of great concern to the general public in recent years. In fact, the degree of overall industrial risk may affect firms’ value, especially when such risks appear.
Due to a series of shocking domestic food safety issues in Taiwan in the past few years, society has paid great attention to the food industry. Therefore, this research uses the panel data model of Taiwan's food industry to analyze the relationship between firm performance, customer capital, R&D innovation, structural capital, firm size, industry risk, and macroeconomics.
The survey results show that customer capital is negatively correlated with firm performance under high industrial risks, which means that the firm's marketing and promotion become ineffective. The industrial risk and misery index has a negative impact on the firm's performance, and there is a significant positive relationship between customer capital and the firm's performance. Therefore, this article suggests that the food industry needs to establish a high degree of trust between society and consumers. For the food industry, it is also important to show a positive attitude towards quality requirements.
Besides, this research analyzes Taiwan's biotechnology industry and analyzes the different scale threshold structures of firm productivity to business performance. Scale expansion has an inverted U-shaped relationship with performance, but the results show that scale expansion is detrimental to business performance. We find that the productivity of biotech firms has different effects on business performance.
This study further observed that biotech firms are heterogeneous under the influence of their performance, productivity, and innovation, especially small and large-scale firms, and found that large-scale firms' productivity and innovation capabilities are lower than that of small firms. Investing large amounts of capital in R&D innovation and productivity is equivalent to obtaining high operational performance, but the firm’s operational characteristics may have blind spots. In terms of management policies, we recommend that large-scale firms strengthen the management of productivity and innovation capabilities and actively improve product performance. In terms of firm operating characteristics, creating high operating performance is the firm's goal.
Finally, through this paper, it is found that the food industry and the biotech industry can learn from each other. For example, the food industry used to value customer capital, but ignored the importance of R&D and innovation. In the future, the food industry should invest more only with R&D innovation can produce more long-term competitiveness of the food industry. Furthermore, from the trend of the world, attaching importance to the sustainable development of E (environment), S (society), and G (governance), the food industry will have greater social responsibility than other industries, allowing consumers to trust the quality of the food industry Reliability, to establish a consensus on food safety between the food industry and consumers.
In addition, the biotech industry has strong R&D and innovation technologies, which is indeed an important advantage of the biotech industry. However, this paper found that when the biotech industry is moving towards large-scale growth, it seems that its R&D innovation has a beneficial effect on business performance. The diminishing effect shows that biotech firm moving towards large-scale should pay more attention to the effects of R&D and innovation in order to maintain the firm's long-term competitiveness.

Table of Content
ABSTRACT IV
LIST OF TABLES IX
LIST OF FIGURES X
CHAPTER 1 INTRODUCTION 1
1.1 MOTIVATION 1
1.2 OBJECTIVES 6
1.3 THE FLOW CHART 10
CHAPTER 2 LITERATURE REVIEW 11
2.1 INDUSTRIAL RISK 13
2.2 SPECIFIC CHARACTERISTICS 14
2.3 SCALE FACTOR 20
2.4 NON-LINEAR THRESHOLD EFFECT 20
CHAPTER 3 METHODOLOGY 22
3.1 DATA RESOURCE 22
3.2 PANEL REGRESSION MODEL 22
3.3 PANEL UNIT ROOT 23
3.4 PANEL THRESHOLD MODEL 25
CHAPTER 4 EMPIRICAL RESULTS AND ANALYSIS 33
4.1 INDUSTRIAL RISK 33
4.2 SPECIFIC CHARACTERISTICS 38
4.3 SCALE FACTOR 46
CHAPTER 5 CONCLUSION AND REMARKS 61
5.1 INDUSTRIAL RISK 62
5.2 SPECIFIC CHARACTERISTICS 62
5.3 SCALE FACTOR 63
REFERENCES 66

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