A Study on the Mechanism of Digital Technology’s Impact on the Green Transformation of Enterprises: Based on the Theory of Planned Behavior Approach
Abstract
:1. Introduction
2. Literature Review
2.1. The Meaning and Impact of DT
2.2. Research on GT
3. Research Model and Hypotheses
3.1. Theory of Planned Behavior
3.2. DT
3.3. Attitude (Digitalization Drives GT)
3.4. Subjective Norm for GT
3.5. Perceived Behavioral Control for GT
3.6. Intention to Pursue GT
3.7. The Mediating Role
3.8. Theoretical Model
4. Research Design
4.1. Variable Measurement
4.1.1. DT
4.1.2. Attitude (Digitalization Drives GT)
4.1.3. Subjective Norm for GT
4.1.4. Perceived Behavioral Control for GT
4.1.5. Intention to Pursue GT
4.1.6. GT
4.2. Questionnaire Design and Data Collection
4.3. Structural Equation Modeling
5. Results
5.1. Reliability and Validity of the Measurement Model
5.2. Model Fit and Path Coefficients
5.3. Mediating Effect
6. Discussion
7. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Item | Sample Characteristics | Number of Samples | Percentage (%) |
---|---|---|---|
Enterprise types | Traditional manufacturing enterprises | 134 | 33.0 |
High-tech manufacturing enterprises | 213 | 52.5 | |
Others | 59 | 14.5 | |
Enterprise nature | State-owned enterprises | 181 | 44.6 |
Private enterprise | 174 | 42.9 | |
Foreign-funded enterprises | 26 | 6.4 | |
Others | 25 | 6.2 | |
Enterprise size (persons) | <100 | 28 | 6.9 |
100–500 | 173 | 42.6 | |
500–1000 | 184 | 45.3 | |
>1000 | 21 | 5.2 | |
Enterprise age (year) | <2 | 28 | 6.9 |
2–5 | 170 | 41.9 | |
5–10 | 173 | 42.6 | |
>10 | 35 | 8.6 |
Latent Variables | Dimensions | Label | Items |
---|---|---|---|
Digital Technology(DT) | Operation | DT1 | The company is performing digital-technology-based business processes. |
Integration | DT2 | The company is integrating digital technologies to transform our business processes. | |
Transition | DT3 | The company is shifting its operational management towards the use of digital technologies. | |
Diffusion | DT4 | The company is willing to put effort into promoting and publicizing digital skills and management knowledge. | |
Attitude (digitalization drives GT) (ATT) | Production side | ATT1 | Digitalization of enterprises can help companies achieve green production. |
ATT2 | Digitalization of the enterprise can provide data to support decisions on green behavior in the company. | ||
ATT3 | Digitalization of an enterprise can effectively capture the environmental impact of a company’s production. | ||
Service side | ATT4 | The company can use its digital platform to collect the environmental needs of consumers. | |
ATT5 | The company can enhance its green image through digital services. | ||
Subjective Norm for GT(SN) | Personal norm | SN1 | The company has a clear and specific environmental policy. |
Exemplary norm | SN2 | Awareness of energy conservation and emission reduction has generally increased in the same industry. | |
SN3 | Carrying out green and low-carbon production and operation has become the norm in the industry. | ||
Directive norm | SN4 | National energy-saving standards, relevant policies, and regulations have prompted the company to develop environmentally friendly projects. | |
SN5 | Consumer demand for green products has led to the development of environmentally friendly projects. | ||
Perceived Behavioral Control for GT(PBC) | External control belief | PBC1 | Energy efficiency and emission reduction technologies are now relatively mature and easy to master. |
PBC2 | Adopting a green transformation is not significantly more costly than a non-green transformation. | ||
Internal control belief | PBC3 | The company has greater access to financial services information and financial products. | |
PBC4 | The company can quickly identify its environmental problems and find solutions. | ||
PBC5 | The company has sufficient resources and manpower to undertake the green transformation. | ||
PBC6 | Overall, the company has the financial strength and technical requirements to make the green transformation. | ||
Intention to Pursue GT (INT) | Formation of motivation | INT1 | The company is willing to carry out pollution control in our production operations. |
INT2 | The company is willing to adopt technologies and equipment related to green transformation. | ||
Formation of plans | INT3 | We will provide a plan to validate the green transformation concept. | |
INT4 | The company will organize the exchange of green transformation ideas across all departments. | ||
Green Transformation (GT) | Green strategy | GT1 | The company actively monitors pollution emissions and carries out pollution prevention. |
GT2 | The company minimizes the potential harm to the environment during the production of our products. | ||
GT3 | The company actively introduces clean technologies. | ||
Green innovation | GT4 | The company invests more in research and development of green technologies. | |
GT5 | The company actively develops green products. | ||
GT6 | The company uses greener raw materials as much as possible. |
Constructs | Label | Unstd. | S.E. | t-Value | p | Std. | SMC | CR | AVE | Cronbach’s Alpha |
---|---|---|---|---|---|---|---|---|---|---|
DT | DT1 | 1.000 | 0.753 | 0.567 | 0.820 | 0.542 | 0.809 | |||
DT2 | 1.763 | 0.112 | 15.808 | *** | 0.940 | 0.884 | ||||
DT3 | 1.168 | 0.097 | 12.056 | *** | 0.606 | 0.367 | ||||
DT4 | 1.103 | 0.094 | 11.727 | *** | 0.591 | 0.349 | ||||
ATT | ATT1 | 1.000 | 0.870 | 0.757 | 0.855 | 0.543 | 0.853 | |||
ATT2 | 0.657 | 0.044 | 14.824 | *** | 0.691 | 0.477 | ||||
ATT3 | 0.661 | 0.043 | 15.352 | *** | 0.710 | 0.504 | ||||
ATT4 | 0.680 | 0.043 | 15.752 | *** | 0.725 | 0.526 | ||||
ATT5 | 0.637 | 0.045 | 14.263 | *** | 0.670 | 0.449 | ||||
SN | SN1 | 1.000 | 0.884 | 0.781 | 0.876 | 0.586 | 0.874 | |||
SN2 | 0.642 | 0.040 | 16.151 | *** | 0.712 | 0.507 | ||||
SN3 | 0.650 | 0.040 | 16.442 | *** | 0.721 | 0.520 | ||||
SN4 | 0.696 | 0.041 | 16.983 | *** | 0.738 | 0.545 | ||||
SN5 | 0.726 | 0.041 | 17.711 | *** | 0.760 | 0.578 | ||||
PBC | PBC1 | 1.000 | 0.918 | 0.843 | 0.894 | 0.588 | 0.893 | |||
PBC2 | 0.593 | 0.036 | 16.676 | *** | 0.695 | 0.483 | ||||
PBC3 | 0.664 | 0.034 | 19.255 | *** | 0.760 | 0.578 | ||||
PBC4 | 0.679 | 0.037 | 18.557 | *** | 0.743 | 0.552 | ||||
PBC5 | 0.661 | 0.035 | 18.855 | *** | 0.750 | 0.563 | ||||
PBC6 | 0.634 | 0.037 | 17.308 | *** | 0.712 | 0.507 | ||||
INT | INT1 | 1.000 | 0.917 | 0.841 | 0.806 | 0.518 | 0.801 | |||
INT2 | 0.495 | 0.042 | 11.689 | *** | 0.596 | 0.355 | ||||
INT3 | 0.554 | 0.045 | 12.370 | *** | 0.630 | 0.397 | ||||
INT4 | 0.627 | 0.046 | 13.526 | *** | 0.691 | 0.477 | ||||
GT | GT1 | 1.000 | 0.895 | 0.801 | 0.902 | 0.607 | 0.879 | |||
GT2 | 0.686 | 0.035 | 19.399 | *** | 0.775 | 0.601 | ||||
GT3 | 0.629 | 0.035 | 17.758 | *** | 0.734 | 0.539 | ||||
GT4 | 0.693 | 0.037 | 18.867 | *** | 0.762 | 0.581 | ||||
GT5 | 0.641 | 0.036 | 17.922 | *** | 0.738 | 0.545 | ||||
GT6 | 0.640 | 0.034 | 18.715 | *** | 0.758 | 0.575 |
AVE | GT | BI | PBC | SN | ATT | DT | |
---|---|---|---|---|---|---|---|
GT | 0.607 | 0.779 | |||||
BI | 0.518 | 0.332 | 0.720 | ||||
PBC | 0.588 | 0.334 | 0.545 | 0.767 | |||
SN | 0.586 | 0.333 | 0.410 | 0.368 | 0.766 | ||
ATT | 0.543 | 0.312 | 0.512 | 0.359 | 0.338 | 0.737 | |
DT | 0.542 | 0.383 | 0.480 | 0.335 | 0.379 | 0.383 | 0.736 |
Fit Indices | χ2 | df | χ2/df | RMSEA | GFI | AGFI | NFI | TLI | CFI |
---|---|---|---|---|---|---|---|---|---|
Test value | 814.170 | 398 | 2.046 | 0.051 | 0.881 | 0.861 | 0.879 | 0.928 | 0.934 |
Recommended values | N/A | N/A | 1~3 | <0.08 | >0.8 | >0.8 | >0.9 | >0.9 | >0.9 |
Path | Parameter Significance Estimates | Standardized Path Coefficient | Hypothesis | Conclusion | |||
---|---|---|---|---|---|---|---|
Unstd. | S.E. | C.R. 1 | p 2 | ||||
DT→ATT | 0.805 | 0.112 | 7.223 | *** | 0.416 | H2 | Supported |
DT→SN | 0.831 | 0.115 | 7.212 | *** | 0.409 | H3 | Supported |
DT→PBC | 0.772 | 0.115 | 6.697 | *** | 0.372 | H4 | Supported |
ATT→INT | 0.326 | 0.048 | 6.775 | *** | 0.357 | H5 | Supported |
SN→INT | 0.179 | 0.044 | 4.096 | *** | 0.205 | H6 | Supported |
PBC→INT | 0.350 | 0.044 | 8.006 | *** | 0.411 | H7 | Supported |
INT→GT | 0.453 | 0.070 | 6.466 | *** | 0.367 | H8 | Supported |
Indirect Effect | Point Estimate | Product of Coefficients | Bootstrapping | ||||
---|---|---|---|---|---|---|---|
SE 1 | Z 2 | BC 3 95% CI 4 | Percentile 95% CI | ||||
Lower | Upper | Lower | Upper | ||||
DT→ATT→INT→GT | 0.119 | 0.034 | 3.500 | 0.065 | 0.201 | 0.063 | 0.196 |
DT→SN→INT→GT | 0.067 | 0.027 | 2.481 | 0.026 | 0.131 | 0.025 | 0.129 |
DT→PBC→INT→GT | 0.123 | 0.037 | 3.324 | 0.064 | 0.212 | 0.062 | 0.209 |
Total indirect effect | 0.309 | 0.076 | 4.066 | 0.177 | 0.474 | 0.181 | 0.478 |
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© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
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Gao, Y.; Tang, Y. A Study on the Mechanism of Digital Technology’s Impact on the Green Transformation of Enterprises: Based on the Theory of Planned Behavior Approach. Sustainability 2023, 15, 11854. https://doi.org/10.3390/su151511854
Gao Y, Tang Y. A Study on the Mechanism of Digital Technology’s Impact on the Green Transformation of Enterprises: Based on the Theory of Planned Behavior Approach. Sustainability. 2023; 15(15):11854. https://doi.org/10.3390/su151511854
Chicago/Turabian StyleGao, Yi, and Yinkai Tang. 2023. "A Study on the Mechanism of Digital Technology’s Impact on the Green Transformation of Enterprises: Based on the Theory of Planned Behavior Approach" Sustainability 15, no. 15: 11854. https://doi.org/10.3390/su151511854
APA StyleGao, Y., & Tang, Y. (2023). A Study on the Mechanism of Digital Technology’s Impact on the Green Transformation of Enterprises: Based on the Theory of Planned Behavior Approach. Sustainability, 15(15), 11854. https://doi.org/10.3390/su151511854