the influencing factors of enterprise digital

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THE INFLUENCING FACTORS OF ENTERPRISE DIGITAL TRANSFORMATION ON THE PERSPECTIVE OF INNOVATION

—— AN EMPIRICAL STUDY OF CHINESE PHARMACEUTICAL ENTERPRISES

XIAOWEN LUO

A Dissertation Submitted in Partial

Fulfillment of the Requirements for the Degree of Doctor of Philosophy (Management)

International College,

National Institute of Development Administration

2022

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THE INFLUENCING FACTORS OF ENTERPRISE DIGITAL TRANSFORMATION ON THE PERSPECTIVE OF INNOVATION

—— AN EMPIRICAL STUDY OF CHINESE PHARMACEUTICAL ENTERPRISES

XIAOWEN LUO International College,

Major Advisor ( Shun-Chi Yu, Ph.D.)

The Examining Committee Approved This Dissertation Submitted in Partial Fulfillment of Requirements for the Degree of Doctor of Philosophy (Management).

Committee Chairperson (Associate Professor Jiafu Su, Ph.D.)

Committee (Assistant Professor Renliang Li, Ph.D.)

Committee (Associate Professor Yu-Hsiu Lee, Ph.D.)

Committee ( Chih - Hung Chen, Ph.D.)

Committee ( Shun-Chi Yu, Ph.D.)

Dean (Assistant Professor Sid Suntrayuth, Ph.D.)

_____/_____/_____

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ABST RACT

ABSTRACT

Title of Dissertation THE INFLUENCING FACTORS OF ENTERPRISE DIGITAL TRANSFORMATION ON THE

PERSPECTIVE OF INNOVATION —— AN EMPIRICAL STUDY OF CHINESE

PHARMACEUTICAL ENTERPRISES

Author Mrs. XIAOWEN LUO

Degree Doctor of Philosophy (Management)

Year 2022

Digital revolution has altered the business models of a number of industries.

China’s pharmaceutical industry will be developed mostly via the digital transformation (DT) of pharmaceutical enterprises. Nevertheless, the current study on the digitization of Chinese pharmaceutical enterprises is deficient and trailing. Consequently, determining which key factors can influence the DT of pharmaceutical enterprises can support the government and enterprises in taking correct and effective steps to implement DT. The models of enterprise DT offered by previous scholars are imperfect and might be improved on the perspective of innovation. Formulating a solution for the DT of pharmaceutical enterprises requires determining the relationship between the influencing factors of DT and how to influence DT. Currently, Chinese pharmaceutical enterprises lack a set of effective solutions and guide ideas for its DT, which is an essential issue that must be addressed.

The objective of this study has four components. Identifying the key factors influencing the DT of Chinese pharmaceutical enterprises is the first step. Secondly, improving the theoretical model of the factors influencing the DT of Chinese pharmaceutical enterprises on the perspective of innovation and the TOE model.

Thirdly, empirically demonstrating the impact and relationship between the factors influencing the DT of pharmaceutical enterprises. Fourthly, providing suggestions and effective solutions for relevant institutions (e.g. government departments and enterprises) in order to promote the development of Chinese pharmaceutical enterprises’ DT.

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This study used the quantitative analysis method to conduct empirical research.

The questionnaire was developed using the Likert scale. Online questionnaire, purposive sampling and snowball sampling were utilized to acquire data. For factor analysis (FA), reliability testing, regression analysis, and structural equation modeling (SEM) analysis, SPSS 25.0 and AMOS 23.0 were utilized.

This study’s empirical analysis yields four aspects for its findings. The external environment (e.g. customer needs, market competition, government policy, digital technology), the internal conditions (e.g. digital strategy, organization capability, leadership), digital innovation, company size, staff position, age, region, ownership type of enterprise, and situation of enterprise’s DT were identified as factors influencing the DT of pharmaceutical enterprises. Secondly, this study enhanced the theoretical model of the factors influencing the DT of pharmaceutical enterprises on the perspective of innovation and the TOE model. Thirdly, this study demonstrated the relationship between the influencing factors and their impacts on the DT of pharmaceutical enterprises. Particularly, digital innovation and internal conditions can mediate the impact of the external environment on DT, and company size can moderate the impact of the external environment on DT. Fourthly, this study proposed effective suggestions and paths for the Chinese government and pharmaceutical enterprises to promote the development of Chinese pharmaceutical enterprises’ DT.

This study enriched the research on the DT of Chinese pharmaceutical enterprises, and its findings can serve as a reference not only for the DT practice of Chinese pharmaceutical enterprises, but also for the DT practice of foreign pharmaceutical industries and other pharmaceutical enterprises. Therefore, it has significant theoretical and practical significance for the implementation of DT in pharmaceutical enterprises.

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ACKNOWLEDGEMENT S

ACKNOWLEDGEMENTS

Studying for a doctorate degree for three years was a long and arduous process, but the time flew by in a flash. There are too many emotions to express and too many thanks to send when recalling this time. My husband, family, teachers, friends, and classmates, I appreciate your support, assistance, and encouragement.

Thanks for my husband-Xueliang Zi, in 2018, I quit my job in Yunnan Baiyao Group Co., Ltd. and chose to start a new career in Yunnan Minzu University. In the face of tight income, I didn’t give up my dream. It was his financial and spiritual support that made me bravely choose to study abroad; It is his love and encouragement that keep me moving forward when I can’t persist in my studies. Thanks for his love, tolerance and understanding. He is my bravest backing. Thanks to my child-You Zi. Wanting to be his good example is the motivation I have been working hard. Thanks to my grandfather, he still thinks about my studies when he is ill; Thanks to my grandmother, who has been urging and supporting me to study; Thank my parents for taking care of me in life, so that I can work and study easily; Thanks to my aunt, who has been giving me direction in life and study, giving me the courage to move forward, and encouraging and supporting me when I am depressed.

I would like to thank Luming Yang Professor, my first enlightening tutor, for guiding my master’s thesis for more than 14 times, which made me curious and awed about scientific research. His patience, preciseness, responsibility and scholarly attitude gave me the idea of becoming an excellent teacher. He was willing to accept me and gave me scientific research guidance and training according to the requirements of doctoral students. Although I had experienced things that I couldn’t write, I wanted to give up the task he arranged, experienced the pain of rushing through the subject all night, and had the joy of being recognized for my scientific research achievements. But when I was confused, he always gave me encouragement and support, and thanked him for his teachings and guidance.

I would like to thank Dr. Shun-Chi Yu, my doctoral thesis tutor, who was willing to accept me and had become his first student at Nida. When I met him, he let me see the hope of graduation. When I met him, I had fewer bumps on my way to my doctoral degree.

When I met him, I firmly believed that as long as I do myself well. When I met him, I

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learned to be more rigorous in academic work. When I met him, I became bigger. It was also a very happy thing to help others. Thanks for meeting him in my most difficult time.

Thank my friends and classmates. Having never been abroad, I went to Bangkok with my classmates from all over the world for the first time in 2019. We go to school together, ride the wind and waves on the boat every day, eat together, complete course assignments together, celebrate the Spring Festival together, take exams together, and apply for visas together. Although we have only less than 90 days of experience, I can feel the friendship of our classmates. Thank my roommate Siyu Yang for guiding and urging me to study English for TOEFL in July 2019; Thank Yunqing Zhang and Hui Chen for enlightening and helping me when I was confused; Thank Jianxian Wang and Zibing Pang for their guidance and suggestions when I prepared for the QE exam; Thanks to Di Wu for helping us find suitable apartments and giving me academic guidance; Thank Fei Yu and Qian Zhang for their help and assistance in my work; Thank Wenjing Ke, Dingfan Liang, Yaping Wu, Fei Su, Bing Zou, Yongjun Liang, Mengchen Cai and Anran Zhang for their help and support. We are classmates, teammates, friends, thank you for meeting you.

Studying is a lonely and painful process, because I met you and met more beautiful. The end of my doctoral career is just the end of a stage. Learning will be my lifelong pursuit.

XIAOWEN LUO October 2022

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LIST OF TABLES

Page

Table 2.1 Operationalization of Independent Variables ... 59

Table 2.2 Operationalization of Dependent Variable ... 62

Table 2.3 Operationalization of Internal Conditions Variables ... 64

Table 2.4 Operationalization of Digital Innovation ... 66

Table 2.5 Operationalization of Company Size ... 67

Table 2.6 Operationalization of Control Variables ... 69

Table 3.1 External Environmental Items Affecting Enterprise DT ... 75

Table 3.2 Internal Conditions Items Affecting Enterprise DT ... 77

Table 3.3 Digital Innovation Items Affecting Enterprise DT ... 79

Table 3.4 DT Items ... 80

Table 3.5 Descriptive Statistical Results of Samples ... 82

Table 3.6 Descriptive Statistical Analysis of Variables ... 83

Table 3.7 Reliability Test Results of External Environment Variables ... 86

Table 3.8 Reliability Test Results of Internal Conditions Variables ... 87

Table 3.9 Reliability Test Results of Digital Innovation Variable ... 88

Table 3.10 Reliability Test Results of DT Variable ... 89

Table 3.11 Measurement Standard of KMO ... 90

Table 3.12 Statistics of Variables Validity Test ... 90

Table 3.13 FA Results of External Environment Variables ... 91

Table 3.14 FA Results of Internal Conditions Variables ... 92

Table 3.15 FA Results of Digital Innovation Variable ... 93

Table 3.16 FA Results of DT Variable ... 93

Table 4.1 Descriptive Statistical Results of Samples ... 97

Table 4.2 Descriptive Statistical Analysis of Variables ... 99

Table 4.3 Reliability Test Results of External Environment Variables ... 101

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Table 4.4 Reliability Test Results of Internal Conditions Variables ... 103

Table 4.5 Reliability Test Results of Digital Innovation Variable ... 104

Table 4.6 Reliability Test Results of DT Variable ... 105

Table 4.7 Standardized Factor Loadings, CR, AVE of Latent Variables ... 106

Table 4.8 Optimal Fitness Index and Recommended Value ... 108

Table 4.9 The CFA Results of External Environment Variables... 111

Table 4.10 The CFA Results of Internal Conditions Variables ... 113

Table 4.11 Discriminant Validity Analysis of the Scale... 115

Table 4.12 The Descriptive Statistics of Employees in Different Positions on DT ... 117

Table 4.13 Comparative Analysis of Variance of Employees in Different Positions on DT ... 117

Table 4.14 Descriptive Statistics of Enterprises in Different Regions on DT ... 118

Table 4.15 Comparative Analysis of Variance of Enterprises in Different Regions on DT ... 119

Table 4.16 Descriptive Statistics of Enterprises in Different Ages on DT ... 119

Table 4.17 Comparative Analysis of Variance of Enterprises in Different Ages on DT ... 120

Table 4.18 Descriptive Statistics of Enterprises in Different Situation on DT ... 120

Table 4.19 Comparative Analysis of Variance of Enterprises in Different Situation on DT ... 121

Table 4.20 Descriptive Statistics of Company Size on DT ... 122

Table 4.21 Comparative Analysis of Variance of Company Size on DT ... 122

Table 4.22 Independent-Sample T-Test of Ownership Type ... 123

Table 4.23 Correlation Analysis of Variables... 128

Table 4.24 The Results of Common Method Biases Test ... 129

Table 4.25 Collinearity Diagnosis of the Impact of the External Environment on DT ... 131

Table 4.26 Collinearity Diagnosis of the Impact of the Internal Conditions on DT ... 132

Table 4.27 Collinearity Diagnosis of the Impact of the External Environment on DI ... 133

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Table 4.28 Collinearity Diagnosis of the Impact of the Internal Conditions on DI .. 134 Table 4.29 Fitting Indexes of the Influencing Factors Model of Pharmaceutical

Enterprises’ DT ... 135 Table 4.30 Estimation of Latent Variable Parameters of the Influencing Factors

Model of Pharmaceutical Enterprises’ DT ... 136 Table 4.31 The Moderating Effect Test of Company Size on the Relationship

between the External Environment and DT ... 141 Table 4.32 The Moderating Effect Test of Company Size on the Relationship

between the External Environment and DI ... 145 Table 4.33 The Moderating Effect Test of Company Size on the Relationship

between the Internal Conditions and DT ... 148 Table 4.34 The Moderating Effect Test of Company Size on the Relationship

between the Internal Conditions and DI ... 151 Table 4.35 Path Coefficient of the Mediating Effect Model ... 153 Table 4.36 Regression Analysis Results of Each Dimension of the External

Environment on Each Dimension of the Internal Conditions ... 157 Table 4.37 Verification Results of Research Hypotheses ... 159

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LIST OF FIGURES

Page

Figure 1.1 2020 China’s Digital Economy Development Index... 3

Figure 1.2 The Integration Level of Informatization and Industrialization in China by 2020... 4

Figure 1.3 2012-2020 China’s Pharmaceutical Market Scale ... 5

Figure 2.1 The Theoretical Framework of TOE ... 19

Figure 2.2 The Theoretical Framework for Enterprise DT ... 50

Figure 2.3 The Conceptual Framework for Enterprise DT ... 52

Figure 4.1 The overall CFA Model... 109

Figure 4.2 The CFA Model of External Environment Variables ... 110

Figure 4.3 The CFA Model of Internal Conditions Variables ... 112

Figure 4.4 The CFA Model of Digital Transformation Variable ... 114

Figure 4.5 The SEM Model of Influencing Factors of Pharmaceutical Enterprises’ DT ... 124

Figure 4.6 The SEM Model of the Influencing Factors of Pharmaceutical Enterprises’ DT (standardized)... 137

Figure 4.7 The SEM Model of the Influencing Factors of Pharmaceutical Enterprises’ DT (unstandardized)... 153

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CHAPTER 1 INTRODUCTION

1.1 Background of the Study

New digital technologies have increased in significance for enterprises, consumers, and governments. The digital economy can both improve the quality of economic growth and promote economic expansion (Mardonakulovich &

Bulturbayevich, 2020). As digital technologies become increasingly integrated into the real economy, traditional industrial digital and intelligent levels continue to increase, hence accelerating the development of the new economy and the paradigm of government governance. Today, countries have placed a high priority on the digital economy, and the DT of the global economy is also advancing (Kolesnikov, Zernova, Degtyareva, Panko, & Sigidov, 2020). The United States was the first country to implement the DT programs. It established the “Intelligent Manufacturing Revitalization Plan” and the “American Leading Advanced Manufacturing Strategy”

and suggested accelerating the growth of technology-intensive advanced manufacturing by utilizing the new generation of information technology (NGIT) (E. B. Reynolds &

Uygun, 2018). In 2017, the British government announced the “UK Digital Strategy,”

which included methods to support the nation in launching and promoting digital businesses (Ullah et al., 2021). In 2018, Russia signed the “National Goals and Strategic Tasks for the Development of the Russian Federation in 2024” presidential decree, which outlined the implementation of NGIT and platform solutions in the public services, health care, education, and industry sectors (Pleslov & Lukashenko, 2020). In addition, the Chinese government has formulated pertinent policies to make significant arrangements for the digital economy, promote the integration of information technology and urban development strategy, support the optimization and upgrading of traditional industries, and construct a modern digital economy system. In 2015, the

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Chinese government developed “Made in China 2025” (L. Li, 2018). In 2016, “the 13th Five-Year National Informatization Plan” advocated “Integration of information technology into economic and social growth”, the digital divide was substantially reduced, and the digital dividend was fully realized (Hong, 2017). The Chinese government recommended in April 2018 to forcefully develop the digital economy, accelerate digital industrialization, and continuously encourage the new industries, forms, and business models powered by information technology innovation (X. Zhu, 2019). In March 2021, “the 14th Five-Year Plan of China” and “the Long Term Goal Outline for 2035” advocated explicitly to develop new digital economic advantages and to advance digital industrialization and industrial digitization (Quan & Zhao, 2020).

Therefore, the digital economy has been an integral part of the national agenda.

Nowadays, the industrial digitalization is the distinctive and strategic choice for developing the digital economy.

The expansion of the global economy has been sluggish in recent years, but the integration of the global digital economy has advanced rapidly. In 2020, the digital economy has accounted for 43.7% of global gross domestic product (GDP), and its role in the national economy has steadily improved (The China Academy of Information and Communications Technology (CAICT), 2021). Integration of the global digital economy is intensifying. In 2020, global industrial digitization had been the driving force behind the development of the global digital economy (CAICT, 2021). Aside from that, governments are accelerating the development of major concerns, such as new infrastructures, DT, cross-border data flow, digital taxation, digital trade, and digital currency, and competition and collaboration are rising in key sectors.

China views the development of the digital economy as the foundation for economic growth. The industrial digitization is extremely crucial for businesses, industries, and the whole economy. The digital reformation of industry has given new quality and efficiency advantages to enterprises. From this point of view, industrial digitization has transformed the new pattern of industrial cooperation and division of labor. The majority of industries have hastened the transition from traditional growth drivers to new engines from a macro perspective. Enterprise digitization is the linchpin of industrial digitization progress and will play a crucial role in industrial digitization.

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According to the report titled “The Process of Chinese Enterprises’ Digital Transformation in 2020,” the contribution of Chinese enterprises to the nation’s GDP has increased annually. In 2020, the added value of Chinese enterprises’ DT contributed for 13.31% of the contribution of enterprises, an increase of 2.23 % from 2018 (NIISDRC, 2021). The research on the “2020 China Digital Economy Development Index (DEDI)” investigated the state of the digital economy in 31 Chinese provinces from three aspects: foundation, industry, and integration.

According to Figure 1.1, the Chinese digital economy development index can average 29.6 in 2020. Tibet, Hainan, Jilin, Ningxia, and Qingh ai lag far behind the top five provinces of Guangdong, Beijing, Jiangsu, and Zhejiang.

Consequently, the development of China’s provinces’ digital economies is uneven (China Center for Information Industry Development: CCID, 2020 ).

Figure 1.1 2020 China’s Digital Economy Development Index

Source: China Center for Information Industry Development: CCID (2020).

65.3

5552.251.5 45.542.8

38.635.6 3532.5

29.429.429.328.828.5

26.326.224.924.723.5

21.321.120.519.318.918.117.817.417.1 13.8

8

0 10 20 30 40 50 60 70 80 90 100

Guangdong Beijing Jiangsu Zhejiang Shanghai Shandong Fujian Sichuan Henan Hubei Hebei Hunan Anhui Chongqing Jiangxi Shaanxi Guangxi Tianjin Guizhou Liaoning Yunnan Shanxi Heilongjiang Gansu Neimeng Xinjiang Hainan Jilin Ningxia Qinghai Tibet

China's digital economy development index in 2020

digital economy development index National average

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From 2005 to 2019, the proportion of China’s digital economy devoted to industrial digitalization expanded from 49.1% to 80.2 (Changsha News, 2021a). The intensive promotion of industrial digitization has injected continuous energy into the development of the digital economy, and the proportion will increase in 2020. As shown in Figure 1.2, the average value of China’s industry and information integration in 2020 is 56, with Hainan, Qinghai, Xinjiang, Gansu, and Tibet far below the average value, which is far below the top five in Jiangsu, Shandong, Zhejiang, Shanghai, and Beijing.

Figure 1.2 The Integration Level of Informatization and Industrialization in China by 2020

Source: NIISDRC (2021).

From 2012 to 2020, the Chinese pharmaceutical market size has expanded from 955.5 billion yuan to 2.15 trillion yuan, at a compound annual growth rate of 10.7%, as shown in Figure 1.3, which depicts the evolution of the pharmaceutical market ( E R I , 2 0 2 0 ) . The pharmaceutical market in China has maintained a rapid growth rate, although its total degree of digitization l ags behind that of other pillar industries. The traditional pharmaceutical paradigm

63.262.4 62 61.561.260.559.258.558.457

53.553.553.2 53 52.750.750.349.849.248.6

47.747.6 47 46.946.646.5 45 44.1 44 43.542.8

0 10 20 30 40 50 60 70 80 90 100

Jiangsu Shandong Zhejiang Shanghai Beijing Guangdong Chongqing Tianjin Fujian Sichuan Liaoning Hubei Henan Hebei Anhui Hunan Neimeng Shanxi Shaanxi Jiangxi Guizhou Jilin Ningxia Heilongjiang Yunnan Guangxi Hainan Qinghai Xinjiang Gansu Tibet

Integration of Informatization and Industrialization in China by 2020

Integration level of informatization and Industrialization National average

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continues to dominate the present market. Under the pressure and encouragement of new medical policies such as batch procurement, conformity evaluation of imitation medicine, and the development of the digital industry, the traditional pharmaceutical industry will rapidly move closer to digitization, thereby promoting the advancement of medicine.

Figure 1.3 2012-2020 China’s Pharmaceutical Market Scale Source: ERI (2020).

DT has revolutionized the business models of several industries. However, pharmaceutical industry adoption of digital services is extremely slow (Finelli &

Narasimhan, 2020). Pharmaceutical enterprises are required to undertake DT projects in order to avoid exiting competitors and meet client demands in a competitive environment (Asad Amraji, Mohammadian, Rajab Zadeh Ghatari, & Shoar, 2020).

Participating actively in DT, achieving the goal of “Medical Internet +,” reforming traditional medicine enterprises through network thinking, innovating new chain modes for the pharmaceutical industry, and realizing the integration of traditional manufacturing and the Internet are the objectives of the pharmaceutical industry. Even if building innovation capability is a deficiency, the pharmaceutical sector has ample

9555

10985

12457

13829 14975 16118 17131

19067

21500

0 5000 10000 15000 20000 25000

2012 2013 2014 2015 2016 2017 2018 2019 2020

2012-2020China's pharmaceutical Market Scale (100 million RMB)

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room to adapt to and tackle the innovative environment (Qiu, 2020). DT refers to the process of redesigning a company’s vision and strategy, organization structures, business processes, organization capabilities, and corporate culture in order to adapt to a changing environment (Gurbaxani & Dunkle, 2019). The pharmaceutical industry’s DT is rethinking how drugs are developed and how people are employed. The primary factors that foster the growth of enterprises are leadership support, teamwork, entrepreneurialism, and product thinking (Finelli & Narasimhan, 2020). To meet the needs of a fluctuating market, pharmaceutical enterprises should enhance their organization capabilities. One of the enterprise’s strategies is DT (Okano, dos Santos, Ursini, Honorato, & Ribeiro, 2021). To be more competitive on the global market, the pharmaceutical industry need cutting-edge digital technologies. The pharmaceutical enterprises are investing more in digitizing its operations. Digitalization can help pharmaceutical enterprises in overcoming numerous obstacles. Particularly in digital marketing, pharmaceutical enterprises continue to adapt and transform their marketing strategies in response to COVID-19 (Bin Sawad & Turkistani, 2021). The DT of pharmaceutical enterprises is an effective way of accelerating the pharmaceutical industry’s transition to innovative technologies and boosting its competitiveness.

China’s pharmaceutical industry is a substantial contributor to the nation’s economy and the well-being of its citizens. Digital technology will foster innovation and influence the pharmaceutical industry’s ecosystem. Government of China is expanding funding for digital medicine. The execution of the “Healthy China 2030”

strategy, “Internet + Medical and Health,” and the medical big data management standard will establish the framework for a digital medical and healthy ecosystem (Tan, Liu, & Shao, 2017). The development of digitization has advanced dramatically, and DT has transformed into an urgent and essential research topic for pharmaceutical enterprises. In the post-epidemic period, pharmaceutical enterprises must also raise their investment in and rate of digitization. This is due to two reasons. Initially, digital capability can reduce enterprises’ reliance on physical resources and decrease production costs and other concerns. Secondly, they can get voluminous data in the future, so enhancing their competitiveness. With the standardization of drug collection and medical insurance negotiation policies, cost control and structural adjustment have become the industry development trend in China’s pharmaceutical industry.

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Pharmaceutical enterprises must enhance the research and development (R&D) success rate and shorten the R&D cycle.

In the manufacturing and distribution process, it must control costs more precisely, cut expenses, and increase operational efficiency. Regarding sales and services, it should closely align with the trend of medical and health reform, improve participation more directly and effectively, and create a new customer-centric medical and health ecosystem. Therefore, the DT of pharmaceutical enterprises is not limited to a specific segment or technology, but rather should integrate and invent diverse technologies throughout the entire industrial chain and businesses. In addition, there is still much space for Chinese pharmaceutical enterprises to expand their digital and intelligent capabilities. Statistics indicate that more than half of China’s pharmaceutical manufacturing enterprises are in a state of single point informatization and digital coverage, with little system integration. Moreover, 26% of pharmaceutical manufacturing enterprises are still in the early stages of DT (NIISDRC, 2018). The majority of pharmaceutical enterprises lag below the industry average in digital maturity (Vermeer & Thomas, 2020). Insufficient research has been conducted on the factors influencing the digitalization of pharmaceutical enterprises. The pharmaceutical industry has not maintained the efficient operation mode necessary for the implementation of the digitalization agenda (Fox, Paley, Prevost, & Subramanian, 2020). The following are the causes for the slow response of large pharmaceutical enterprises to the environment and the lag in digitization: senior executives lack knowledge of digitalization; The organization lacks a digital section with distinct responsibilities; The organization does not manage its digital budget and return on investment; The organization lacks professional management to advance DT (Fox et al., 2020). If digital plans do not align with enterprise strategy, there is a high risk of DT failure. There are four prerequisites for pharmaceutical enterprises to implement digital health: a digital vision and comprehensive digital strategy, the provision of value to consumers, and the application of innovative techniques (Kaltenbach, 2014).

The pharmaceutical industry’s DT has been caused by macroeconomic factors including technical innovation, new laws, rising drug production costs, and new demand (Dierks, Bruyère, Reginster, & Richy, 2016). This study investigates the factors that influence the adoption of cloud computing by pharmaceutical enterprises,

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including complexity, compatibility, comparative advantage, executive support, company size, technology readiness, competitive pressure, and trade partner pressure (Al-Shura, Zabadi, Abughazaleh, & Alhadi, 2018). The internal and external factors influencing the DT of small and medium-sized enterprises (SMEs) are included among the factors influencing the DT (Tarutė, Duobienė, Klovienė, Vitkauskaitė, & Varaniūtė, 2018). There are environmental factors that influence enterprise DT, such as the external environment of enterprises, including policies, the economy, technology, and customer needs, among others (Tarutė et al., 2018). The internal factors that influence enterprise DT include strategy, corporate culture, leadership, dynamic capability, organization traits, and innovation (Peter, Kraft, & Lindeque, 2020). If the key influencing factors can be identified, targeted steps will be implemented to accelerate the DT of pharmaceutical enterprises. Therefore, it is essential to investigate the factors that influence the DT of pharmaceutical enterprises.

According to the Baidu Aiqicha search tool, there are 30149 Chinese pharmaceutical enterprises that have been operational for more than three years as of January 20, 2022. The development of China’s pharmaceutical industry relies heavily on the DT of pharmaceutical enterprises. The pharmaceutical industry’s digitization requires the cooperation of every link in the supply chain (e.g. procurement, R&D, manufacture, pharmaceutical circulation, etc.). The primary objective of pharmaceutical industry digitalization, from a value perspective, is to actualize efficient R&D, optimize business operations, and improve customer experience. The implementation of digitization solutions can achieve not only the acceleration of new drug R&D, the improvement of production efficiency, the reduction of marketing expenses, and the optimization of the customer experience, but also the revitalization of the pharmaceutical industry as a whole. This study concentrates primarily on the linkages between the external environment, internal conditions, digital innovation, and the DT of Chinese pharmaceutical enterprises. The research on the DT of Chinese pharmaceutical enterprises has far-reaching implications for advancing the “Healthy China 2030” plan and the building of “Digital China”.

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1.2 Statement of the Problems

Internet, digital revolution, communication, and the increase in international information mobility lead to an information explosion, which influences and transforms the global economy. In addition, the pharmaceutical industry is facing a number of new challenges and opportunities (Epstein, 2007).By searching the topic of DT and pharmaceutical enterprises on CNKI, Google Scholar, and Web of Science, it was found that there is a great deal of literature review, but few research on Chinese pharmaceutical enterprises and their DT-influencing aspects. Therefore, the study on the DT of Chinese pharmaceutical enterprises is inadequate.

Through a review of literature, it determined that there are numerous factors influencing the DT of enterprises, but the research on the DT of pharmaceutical enterprises primarily focused on the applications of digital technologies (e.g. artificial intelligence (AI), Internet of things (IoT), blockchain, and cloud computing, etc.) (Châlons & Dufft, 2017; Fox et al., 2020; Hu et al., 2019), trends (Beloborodova, Antonchenko, Pavlova, Hajrullina, & Soldatov, 2020) and performance of DT (Amelia et al., 2020). Although some have researched the DT of pharmaceutical enterprises from the perspective of macro factors, and others have investigated the DT of pharmaceutical enterprises from the perspective of technology, organization, and environment, many have not (Al-Shura et al., 2018). However, their research on the factors that influence the DT of pharmaceutical enterprises is insufficient. For the purpose of promoting the DT of pharmaceutical enterprises, it is crucial to determine the key factors influencing DT. Therefore, “What are the key factors influencing DT in pharmaceutical enterprises?” is the first question to be addressed in this study.

In the TOE model, Drazin, Tornatzky, and Fleischer (1991) proposed that technology, organization, and environmental factors influence innovation, which in turn influences enterprise transformation. Al-Shura et al. (2018) considered that the technological, organizational, and environmental factors can influence the DT of pharmaceutical enterprises. Tarutė et al. (2018) thought that both internal and external factors influence DT. Osmundsen, Iden, and Bygstad (2018) put forward the model that digital innovation and digitalization can have an impact on the DT of enterprises.

In the IS success model proposed by Vogelsang, Liere-Netheler, Packmohr, and Hoppe

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(2018), organization, environment, and technology are the major factors that determine an enterprise’s DT. According to the findings of these scholars, the current research on the influencing factor model of pharmaceutical enterprises’ DT is not exhaustive and flawless. The second question to be addressed in this study is, thus, “How to improve the influencing factors model of pharmaceutical enterprises’ DT on the perspective of innovation and the TOE model?”

According to K. Zhu, Dong, Xu, and Kraemer (2006), external environmental factors (e.g. technical capability and competitive pressure) can influence DT. Nadeem (2018) thought that the external environment can promote digital innovation, and customer problems and customer needs can promote enterprise digital innovation.

Wolf, Semm, and Erfurth (2018) considered that the external environment can greatly influence the changes of internal conditions, and that internal conditions can facilitate the DT of enterprises. Nasiri, Saunila, Ukko, Rantala, and Rantanen (2020)considered that enterprises with favorable internal conditions can promote digital innovation.

Otherwise, enterprise DT’s research methods mainly consist of the literature research approach and the qualitative analysis method. The papers of “Digital transformation:

driving forces, success factors and Enlightenment” (Osmundsen et al., 2018) and

“identify the factors affecting the digital transformation of SMEs” (Tarutė et al., 2018) adopt the literature research method. The papers of “Identify success factors for digital transformation”(Morakanyane, O'Reilly, McAvoy, & Grace, 2020), “Success factors for promoting the digital transformation of manufacturing enterprises” (Vogelsang et al., 2018) and “Updating the framework of factors promoting digital transformation”

(Rueckel, Muehlburger, & Koch, 2020) adopt quantitative method. There are few quantitative methods in enterprise DT research, particularly empirical testing and the correction of the theoretical model. The relationship between external environment factors, internal conditions, digital innovation, and enterprise DT cannot be adequately captured by previous research. Consequently, “What is the relationship between the external environment, internal conditions, digital innovation, and the DT of pharmaceutical enterprises?” and “How do the external environment, internal conditions, and digital innovation influence the DT of pharmaceutical enterprises?”

are pressing issues that must be investigated in this study.

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There are currently a large number of pharmaceutical enterprises in China, and competition on the pharmaceuticals market is fierce. The digital level of pharmaceutical enterprises is generally poor, the R&D capacity of new drugs is inadequate, and there is a dearth of digital technology support mechanisms in the R&D phase (Tan et al., 2017). The majority of informatization and automation in the manufacturing stage of pharmaceutical enterprises are segregated, and data from the production process have not been collected in time for R&D, production process control, and management (NIISDRC, 2018). In general, pharmaceutical enterprises lack the capacity for drug marketing channel management, real-time tracking, and marketing data analysis (Q. Zhou, 2021).Chinese pharmaceutical enterprises are in urgent need of DT, but they lack a set of solutions and guiding recommendations for its effective implementation. It is essential to initiate relevant research on the DT of Chinese pharmaceutical enterprises, and research on the factors influencing DT will serve as the basis for the formulation of pertinent guidance recommendations. The practical significance of this study is thus “How do Chinese pharmaceutical enterprises implement DT?”.

1.3 Research Objectives

The following are the research objectives of this study in order to resolve the issues in section 1.2.

1) To identify the main factors affecting the DT of Chinese pharmaceutical enterprises;

2) To improve the theoretical model of the factors affecting the DT of Chinese pharmaceutical enterprises on the perspective of innovation and the TOE model;

3) To demonstrate the impact and the relationship between the influencing factors and pharmaceutical enterprises’ DT by using the quantitative method;

4) To provide suggestions and effective solutions for relevant institutions (e.g. government departments and enterprises) to promote the development of Chinese pharmaceutical enterprises’ DT.

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1.4 Significance of the Study

The objectives of this study are to determine the key factors influencing the DT of pharmaceutical enterprises, to establish the influencing factor model of DT, to analyze the impact and relationship of the various influencing factors on DT, and to provide the government department and pharmaceutical enterprises with suggestions and paths for DT implementation. This study will have important academic and practical significance.

1.4.1 Academic Significance

The academic significance of this study include:

1) Previous research concentrated mostly on the applications of digital technology in DT, the causes of DT, the trends of DT, and the performance of DT.

However, research on the factors influencing pharmaceutical enterprises’ DT is still limited and not exhaustive. This study will identify the key factors that influence the DT of pharmaceutical enterprises, as well as the impact and relationship of various factors on the DT of pharmaceutical enterprises, in order to provide effective suggestions and paths for the DT of pharmaceutical enterprises. Therefore, this study will contribute to the DT of pharmaceutical enterprises’ research.

2) In previous research, a few scholars proposed models of enterprise DT, but they were not exhaustive. Therefore, this study will improve the influencing factor model of pharmaceutical enterprises’ DT on the perspective of innovation and the TOE model.

1.4.2 Practical Significance

The practical significance of this study to enterprise development is profound and lasting, as follows:

1) This study will empower pharmaceutical enterprises rapidly identify the key influencing factors of DT, seize new market opportunities, explore new business models, and enhance their competitiveness.

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2) This study will provide suggestions and effective solutions for relevant institutions (e.g. government departments and enterprises) to encourage the growth of the DT of Chinese pharmaceutical enterprises. Based on synergetics and collaborative innovation theory, this study will propose methods for promoting the DT of pharmaceutical enterprises, including: the government cooperating with enterprises in innovation; universities cooperating with enterprises in innovation; scientific research institutions cooperating with enterprises in innovation; and customers cooperating with enterprises in innovation.

3) Not only will the results of this study serve as a reference for the DT practices of Chinese pharmaceutical enterprises, but also for the DT practices of foreign pharmaceutical industry and other pharmaceutical enterprises.

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CHAPTER 2 LITERATURE REVIEW AND THEORETICAL FRAMEWORK

Brief Introduction of the Chapter

Innovation can drive enterprises’ DT, and collaborative innovation can contribute to enterprises’ DT. The synergy of government, enterprises and research institutions can promote the DT of enterprises. Therefore, this study will be based on the innovation perspective, the TOE model, collaborative innovation theory, and synergetics to explore Chinese pharmaceutical enterprises’ DT.

In this chapter, it combs the relevant literature of theory and pharmaceutical enterprises’ DT. The innovation perspective, collaborative innovation theory, and synergetics are taken as the basic of the research, and the influencing factors of pharmaceutical enterprises’ DT are further studied. The main parts are 1) Literature research on relevant theories; 2) Concepts related to DT; 3) Literature research on DT of pharmaceutical enterprises; 4) Theoretical framework; 5) Conceptual framework and research hypotheses.

2.1 Theoretical Background

2.1.1 Innovation Perspective 1) Overview of Innovation

In 1912, Schumpeter introduced innovation and distinguished it from invention; the distinction was significant at the time. Innovation was defined as the introduction of a new product or product quality, a new technique of manufacturing, the opening of a new market, and the conquering of a new source of raw materials (Schumpeter, 1934). In his book Business Cycle, he defined innovation as “doing things differently within the scope of economic life”, and furthered clearly pointed out five situation of innovations, including production innovation, technology innovation,

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market innovation, resource allocation and organization innovation (Schumpeter, 1939). Schumpeter (1951) considered that innovation is a business concept that occurs predominantly in enterprises. Generally, enterprises must combine multiple forms of information, capabilities, skills, and resources to achieve innovation. Innovation and technological development are evolving and being implemented at an unprecedented rate. Globally, entrepreneurs are implementing the commercialization process resulting from invention and technical transformation. In the past few decades, people’s conception of the innovation process has evolved from the “technology-driven” and

“demand-driven” mode to the “coupling” mode, and finally to the “comprehensive”

pattern that is prevalent today. As a result of the globalization of the Internet, communications, and electronics, innovation is becoming more rapid and decentralized, with organizations and individuals increasingly collaborating through networks (Abouzeedan, Busler, & Hedner, 2009). Entrepreneurs are essential for the development and implementation of innovation. Government and relevant agencies should also encourage innovation and entrepreneurial policies (Norrman & Klofsten, 2009). Therefore, innovation research will grow to dominate economics, business, and other fields.

2) The Content and significance of enterprise innovation

Utilizing and continuously optimizing the allocation of its own resources and social resources, and carrying out invention and innovation from the two levels of enterprise operation and management is enterprise innovation (Gronum, Verreynne, & Kastelle, 2012). Lendel and Varmus (2011) considered that enterprise innovation is a vital component of enterprise management and a crucial factor in determining the enterprise’s development direction, scale, and velocity. Enterprise innovation consists mostly on the following aspects.

Concept innovation is the premise of various innovation of enterprises.

In the development of enterprises, enterprises leaders should have new ideas, new breakthroughs and new measures in the aspects of management concept, business concept and production concept, so that the concept of enterprises can keep pace with the growth of the market (Tsichritzis, 1997).

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Institutional innovation refers to the introduction of new organization to take the place of the old organization to suit the new situation or new characteristics which enterprises are facing (S. Chen, Tao, & He, 2012). Advanced enterprise institution can manoeuver the work aggressiveness of diverse individuals and advance the management and technical innovation development (Hargrave & Van de Ven, 2006).

Management innovation is the cornerstone of enterprise innovation.

Innovation in management is exemplified by the widespread implementation of knowledge management, which makes management more scientific and methodical (Birkinshaw, Hamel, & Mol, 2008). Through management innovation, enterprises can integrate talents, capitals, technologies, and other resources, optimize various production factors and production conditions, and enhance their strength and competitiveness (Mol & Birkinshaw, 2009).

Product innovation is essential for company innovation. It enables enterprises to satisfy consumers’ demands for growing materials and maintain the sustainability of their development (Danneels, 2002).

Technological innovation is the core of enterprise innovation.

Technological innovation includes the invention of production technologies, the development of new technologies, and the application innovation of current technologies (Cantwell & Kosmopoulou, 2003). The competitiveness of enterprises is reliant on technologies, and the tendency toward enhancing technical innovation has become unavoidable. Independent R&D and innovation are crucial strategies for enterprises who are committed to enhancing the level of technical innovation, so that they can achieve competitive advantages in the fierce market competition (David J Teece, 2010).

Marketing innovation is a process of achieving breakthroughs or changes of marketing elements in certain aspects in combination with the resource conditions and business strength of enterprises for the sake of confronting the change of marketing environment (Yongmin Chen, 2006). Marketing innovation is committed to supplying customers with high-quality products and services, so enabling enterprises to keep and expand their market share and preserve their competitive advantage, thereby increasing their profitability (Tinoco, 2010).

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3) Innovation Related Research

Under the background of digital technology, digital technology innovation, process innovation, organization innovation, marketing innovation, and business model innovation are vitally critical parts of digital innovation (Hinings, Gegenhuber, & Greenwood, 2018). Digital technology, digital platforms, and digital infrastructures have altered the innovation process. It not only generates new chances for inventors and entrepreneurs, but also has far-reaching effects on the creation and acquisition of value (Nambisan, Wright, & Feldman, 2019). Digital tools can not only affect output and process efficiency, reshape the entire innovation process, and realize the new configuration of personnel, teams, and enterprises, but they can also help enterprises in innovating their business models and distribution channels, and delivering more value to their customers (Falco, Renzi, Orlando, & Cucari, 2017). The use of digital platform can enhance research productivity, hence enhancing the nation’s global innovation and economic standing (Lazarev, Varkulevich, & Andreev, 2021).

The innovation of enterprises can be reflected in these aspects as follows.

(1) Innovation in enterprise operation management, such as the implementation of enterprise resource planning system (ERP), can serve as a platform for enterprise management innovation and assist enterprises in reducing costs, enhancing business efficiency, and optimizing capital operation (Kemp & Low, 2008).

(2) Innovation in product R&D, for instance, pharmaceutical enterprises use AI, big data, and other technologies in drugs R&D and clinical trials to reduce costs and the drugs R&D cycle (Q. Zhou, 2021).

(3) Innovation in production and manufacturing management, such as the applications of intelligent manufacturing, can effectively improve the existing manufacturing industry, shorten the product development cycle, reduce costs, and increase productivity, as well as promote the development of a new manufacturing mode and the internal needs of upgrading the manufacturing industry. Intelligent manufacturing’s effect on the manufacturing industry’s competitiveness is becoming increasingly important (J. Davis et al., 2015).

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(4) Innovation in customer management, as well as cooperative innovation with customers or end-users, is gaining significance for enterprises as they develop new services and products (Greer & Lei, 2012). For instance, the deployment of customer relationship management system (CRM) can realize the integrated operation of the market, sales, and after-sales support, significantly enhance labor productivity, cut operating expenses, and boost the order transaction rate of enterprises (Rigby & Ledingham, 2004). Digital marketing is an innovation in marketing. Internet, communication technology, and digital interactive media can be utilized to accomplish marketing objectives. In addition, enterprises can expand new markets and discover new consumers in the most efficient and cost-effective manner (Desai, 2019).

In addition, Tornatzky and Fleisher, in their research on the impact of innovation on corporate transformation, proposed the TOE theoretical framework, which takes into account not only the characteristics of technology but also organizational and external factors (Drazin et al., 1991). The theoretical framework of TOE is shown in Figure 2.1. This model has a transparent and adaptable structure, which provides a solid theoretical perspective for the research of innovation driving factors and their impacts, and is commonly utilized for the analysis of innovation influencing factors. Bin and Hui (2021) made use of the TOE to study the influencing factors of SMEs’ DT. Patil (2021) used the TOE to study the application of industry 4.0 by manufacturing enterprises. Additionally, the TOE was utilized to examine the success factors of promoting the DT of manufacturing enterprises (Vogelsang et al., 2018).

For the purpose of guaranteeing that pharmaceutical enterprises can meet customers’ needs and gain competitive advantages in the fierce market competition, the leading pharmaceutical enterprises have begun to investigate digital innovation and DT. Therefore, it is necessary to examine the DT of pharmaceutical enterprises on the innovation perspective, and digital innovation is also a significant factor influencing the DT of pharmaceutical enterprises.

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Figure 2.1 The Theoretical Framework of TOE Source: Drazin et al. (1991).

2.1.2 Collaborative Innovation Theory 1) Overview of Collaborative Innovation

David J. Teece (1986) first proposed that collaborative innovation is a combination of relevant capabilities required for inter enterprise innovation, such as joint venture, cooperative production, cross channel coordination and technology licensing, involving strategic management, public policy, international trade and investment, so as to achieve win-win innovation among relevant enterprises. Cebon (2006) thought that collaborative innovation is a group of researchers who form networks through network platforms to exchange ideas and technologies for the sake of achieving common goals. Persaud (2005) thought that collaborative innovation is about the collaborative process of multiple participants to enhance innovation performance based on R&D cooperation. Serrano and Fischer (2007) considered that collaborative innovation involved the intersection and integration of knowledge, technology, data, resources and other aspects. Ketchen Jr, Ireland, and Snow (2007) thought that collaborative innovation refers to the innovation across organizational boundaries, and the sharing of ideas, knowledge and expertise can help organizations achieve continuous innovation. Collaborative innovation advocates encouraging universities, research institutions and enterprises to deliver their capabilities, integrate resources,

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complement advantages, and accelerate the popularization, application and industrialization of technology under the guidance of national will and institutional arrangements (Soeparman, van Duivenboden, & Oosterbaan, 2009). J. P. Davis and Eisenhardt (2011) considered that collaborative innovation is an integrated innovation organization model and relationship with knowledge increment and innovation performance improvement as the core, which is the extension and application of synergetics in the field of innovation, and includes the integration and cooperation of knowledge across organizational boundaries, technology and resources.

2) The Characteristics of Collaborative Innovation

The main characteristics of collaborative innovation are as follows:

(1) Availability of innovation resources

Innovation resources are the numerous inputs required for technological innovation, primarily including talents, funding, technology, and knowledge, as well as other components. Collaborative innovation can make better use of external resources, effectively resolve the contradiction between the unpredictability of internal technological innovation, the scarcity of resources, and the limitation of technological innovation capacity, and boost the competitiveness and risk resistance of all innovation subjects (X. Wang, 2017).

(2) Ecology of innovation environment

The collaborative innovation environment’s ecosystem is an organic collection of innovation aspects based on open innovation and network innovation. It is a condition in which basic enterprise capabilities continue to expand.

The competition mechanism of a system for collaborative invention can maximize resource allocation. To ensure the efficient operation of the entire system, all actors of innovation constantly generate new innovation demands in their pursuit of maximum adaptation and compatibility.

(3) Sharing of innovative achievements

Collaborative innovation is a part of knowledge management’s collaborative development. It is the transmission, assimilation, digestion, sharing, incorporation, application, and re-creation of knowledge amongst cooperative groups.

Essentially, it is the transformation and promotion of tacit and explicit knowledge held by enterprises, universities, and scientific research institutions.