The identification of the key factors affecting the DT of Chinese pharmaceutical companies is the first step. Second, improving the theoretical model of the factors affecting the DT of Chinese pharmaceutical companies from the perspective of innovation and TOE model.
INTRODUCTION
- Background of the Study
- Statement of the Problems
- Research Objectives
- Significance of the Study
- Academic Significance
- Practical Significance
Therefore, it is essential to investigate the factors that influence the DT of pharmaceutical companies. However, their research on the factors that influence pharmaceutical companies' DT is insufficient.
LITERATURE REVIEW AND THEORETICAL FRAMEWORK
Theoretical Background
- Innovation Perspective
- Collaborative Innovation Theory
- Synergetics
- Summary
The government and businesses are also aggressively exploring the growth of collaborative innovation in the DT. For example, central enterprises in the Dawan district form the Digital Collaborative Innovation Alliance of central enterprises.
Related Concepts
- Definition of Digitalization
- Definition of Digital Innovation
- Definition of DT
- The Relationship between Digitalization, Digital Innovation and DT
- Definition of Pharmaceutical Enterprises and DT of Pharmaceutical
Third, digitalization and digital innovation can change the company's business model and result in the DT of organizations or the entire sector (Osmundsen et al., 2018). Digital innovation can strengthen customer-oriented and employee-oriented processes, optimize existing products and develop new business models.
Literature Review of Pharmaceutical Enterprise DT
- Background of Chinese Pharmaceutical Enterprise DT
- Problems in Digitalization of Chinese Pharmaceutical Enterprises
- Scenarios of Pharmaceutical Enterprises’ DT
- Influencing Factors of Enterprises’ DT
CRM is the key to the development of pharmaceutical companies and directly affects the future competitiveness of pharmaceutical companies. The digital development of pharmaceutical companies is not only manifested in the ability to use digital technology and tools, but also in the ability to transform traditional pharmaceutical companies into digital pharmaceutical companies.
Theoretical Framework
The position of the staff and the age of the enterprise can affect the DT of enterprises (J. Zhang, Long, & von Schaewen, 2021). Song (2020) thought that the current situation of the enterprise's DT can affect the implementation of the enterprise's DT in the next step. 2018), this section draws key arguments from relevant literature and forms a theoretical framework before building the conceptual framework.
Conceptual Framework and Research Hypotheses
- Conceptual Framework
- Research Hypotheses
H5: Internal conditions can significantly influence DT. H5a: Digital strategy can significantly influence DT. H5b: Organizational ability can significantly influence DT. H5c: Leadership can significantly influence DT. 6) Relationship between digital innovation (DI) and DT of companies. H6: DI can significantly affect DT. 7) The relationship between company size and DT of companies The size of the company, measured by the number of employees, can also influence whether DT is implemented or not. H11: Firm size can significantly moderate the relationship between the external environment and DT through DI.
H12: Company size can significantly moderate the relationship between the internal conditions and DT through DI. H14: The internal conditions and DI can significantly mediate the relationship between the external environment and DT.
Operationalization of Variables
- Independent Variables
- Dependent Variables
- Mediating Variables
- Moderating Variables
- Control Variables
Internal conditions are the main driving force for promoting entrepreneurial DT (Wolf et al., 2018). Improving customer satisfaction is one of the drivers of DT (Demirkan et al., 2016). Digital innovation has an intermediate impact on the relationship between the external environment, internal conditions and DT of the company.
Sufficient capital investment of the R&D contributes to the implementation of enterprise DT (Kontic & Vidicki, 2018). Staff position and firm ages have been proposed as the control variables of firm DT (J. Zhang et al., 2021).
RESEARCH METHODOLOGY
Research Methods
Structural equation modeling (SEM) is a statistical analysis tool that extensively uses multiple regression analysis, path analysis, and other methods to handle the causality model (Burnette & Williams, 2005). This study mainly used SEM to test the measurement scale and factor model of the influencing factors of DT of pharmaceutical companies and to verify the above research hypotheses.
Sampling Methods
For the sake of ensuring the representativeness and popularization of the samples, purposive sampling and snowball sampling were used to study the DT of Chinese pharmaceutical enterprises in this study.
Sample Objects and Sample Size
- Sample Objects
- Sample Size
Research Instruments
Measurement
Do you consider the impact of competitive market pressure in the same sector on corporate DT? Do you believe that the rapid development of DT of competitors in the same industry can significantly affect the DT of enterprises? Do you believe that the impact of government financial support and incentives on corporate DT is significant?
Do you consider the application perspective of NGIT (e.g. 5G, cloud computing, big data, AI, IoT, blockchain) can significantly impact enterprise DT. Do you think it is important for employees to have the ability to work with information to influence the enterprise DT.
Data Collection, Data Processing Tools and Analysis
- Data Collection
- Data Processing Tools and Analysis
Pre-test
- Descriptive Statistical Analysis of Pre-test
- Reliability Analysis of Pre-test
- Validity Analysis of Pre-test
By observing the CITC between the observed variables and their latent variables, it was found that the CITC value of CN1 does not meet the general standard of 0.5, and the overall reliability can be increased to 0.890 after deleting this item, indicating that the placement of this item does not it was good, so it should be deleted;. By observing the CITC between the observed variables and their latent variables, it was found that the CITC value of GP3 did not meet the general standard of 0.5, and the overall reliability could be increased to 0.904 after deleting this item, indicating that the placement of this item did not it was good, so it should be deleted;. It can be seen that the questionnaire scale used in this study had good reliability.
By observing the CITC between the observed variables and their latent variables, it was found that the CITC value of LS2 does not meet the general standard of 0.5, and the whole reliability can be increased to 0.918 after deleting this item, which indicates that the setting of this item was not good, so it should be deleted. Through the reliability and validity test of the pre-test, it was found that the questionnaire had good reliability and validity.
RESULTS AND DISCUSSION
Descriptive Analysis
- Descriptive Statistical Analysis of Samples
- Descriptive Statistical Analysis of Variables
Regarding the region to which the companies belong, there were 67 subjects in the West, corresponding to 16.14%. Measured by the types of companies, the number of state-owned companies was 160, corresponding to 38.55%. Regarding the situation of the company's DT, the number of companies that had not performed DT and had no intention and plan for DT was 28, corresponding to 6.75%.
The number of enterprises that had no DT and had the intention and plan of DT was 73, accounting for 17.59%; The number of enterprises that underwent DT and whose DT projects are in the initial phase of construction was 123, accounting for 29.64%; The number of enterprises that underwent DT and achieved certain results in DT projects was 191, accounting for 46.02%. According to the data in Table 4.2, the data of the survey items in the questionnaire of this study obeyed the positive distribution.
Reliability and Validity Analysis
- Reliability Analysis
- Validity Analysis
- Aggregate Validity
- Model Fitness
- Discriminant Validity
After deleting this item, the overall reliability increased to 0.916, indicating that the setting of this question was not good. After deleting this item, the overall reliability increased to 0.912, indicating that the setting of this question was not good. After deleting this item, the overall reliability increased to 0.877, indicating that the setting of this question was not good.
After deleting this item, the overall reliability was raised to 0.874, indicating that the setting of the question was not good. It showed that the three dimensions of internal variables (digital strategy, organizational ability and leadership) can be combined into an overall variable for subsequent analysis of path conditions. 4) CFA for DT variables.
The Impacts of Demographic Variables on DT
- Staff Position
- Region
- Age
- The Situation of DT
- Company Size
- Ownership Type
According to the descriptive data of enterprises in different regions in DT, as shown in table 4.14, the West region scored the lowest in DT. According to the descriptive data of enterprises of different ages in DT, as shown in table 4.16, enterprises older than 10 years scored the highest points in DT. According to the descriptive data of enterprises in different situations for DT as shown in table 4.18, the situation "No and there is no purpose and plan for DT".
The results showed that the condition "No, and there is no goal and plan for DT" had the greatest impact on DT of enterprises. According to the descriptive data of company size in DT as shown in Table 4.20, company size of "more than 2000 people" scored the highest in DT.
Construction of the SEM Model
Hypotheses Test
- Dummy Variable Processing
- Correlation Analysis of Variables, Common Method Biases Test and
- Correlation Analysis of Variables
- Common Method Biases Test
- Multicollinearity Test
- The Results of Main Effect Test
- The Results of Moderating Effect Test
- Steps of Moderating Effect Test
- The Moderating Effect Test of Company Size on the Relationship
- The Moderating Effect Test of Company Size on the Relationship
- The Moderating Effect Test of Company Size on the Relationship
- The Results of Mediating Effect Test
- The Results of Sub-hypotheses Test
- Testing the Impacts of Various Dimensions of External
- Testing the Impacts of Various Dimensions of External
- Testing the Impacts of Various Dimensions of the Internal
- Testing the Impacts of Various Dimensions of Internal Conditions
- Testing the Impacts of Each Dimension of the External
- The Results Summary of Research Hypotheses Verification
The standardized path coefficient of the external environment on the internal conditions was 0.52 (T=6.47, P<0.001), indicating that the external environment had a significant effect on the internal conditions, so the hypothesis H3 was valid;. The standardized path coefficient of the internal conditions on DT was 0.49 (T=6.05, P < 0.001), indicating that the internal conditions had a significant effect on DT, so the hypothesis H5 was valid;. The regression coefficient of the multiplicative term is significant, and R2 is significantly improved, and the model interpretability is improved.
Therefore, it was proved that the moderating variable Size strengthened the influence of the independent variable EE on the dependent variable DT through the mediator variable DI, so hypothesis H11 was valid. Therefore, it was proved that the moderating variable Size strengthened the influence of the independent variable IC on the dependent variable DT through the mediator variable DI, so hypothesis H12 was valid.
Discussion of the Research Findings
- Discussion on the Demographic Results
- Discussion on the Main Effect
- The Impact of the External Environment on the DT of Enterprises
- The Impact of the External Environment on the DI of
- The Impact of the External Environment on the Internal
- The Impact of the Internal Conditions on the DI of Enterprises 168
- The Impact of DI on the DT of Enterprises
- Discussion on the Moderating Effect
- The Moderating Role of Company Size in the Relationship
- The Moderating Role of Company Size in the Relationship
- The Moderating Role of Company Size in the Relationship
- The Moderating Role of Company Size in the Relationship
- The Moderating Role of Company Size in the Relationship
- The Moderating Role of Company Size in the Relationship
- Discussion on the Mediating Effect
- The Mediating Role of DI in the Relationship between the
- The Chain Mediating Role of the Internal Conditions and DI in the
- The Mediating Role of the Internal Conditions in the relationship
This also showed that the external environment was one of the key factors influencing the companies' DT. This also showed that the internal conditions were the key factor influencing the companies' DT. Therefore, it was proved that the size of the company played a positive role in the influence of the external environment on the companies' DT.
Therefore, it can demonstrate that firm size positively moderated the relationship between the external environment and firms' DT through DI. Therefore, it can demonstrate that firm size positively moderated the relationship between internal conditions and firms' DT through DI.
CONCLUSION
- Summary
- Academic Contribution
- Practical Implication
- Suggestions for Improving the External Environment
- Suggestions for Improving the Internal Conditions
- Suggestions for Improving the Digital Innovation Level
- Suggestions for the Paths of Pharmaceutical Enterprises’ DT
- Research Limitations
There were currently no effective recommendations or solutions to guide pharmaceutical companies' DT. First, this study can enrich the previous research on pharmaceutical companies' DT. First, it is necessary to clarify the objectives of pharmaceutical companies to formulate the DT strategy.
For the level of specification, the DT routes of pharmaceutical companies can be used as follows. For the scenario level stage, the pharmaceutical companies' DT routes can be used as follows.
