**5.1 Limitations of the study**

*Intellectual Property Rights - Patent*

users in the studied sample.

have a significant impact.

Thus, the technical feasibility, comparative advantage, and cost of electricity are the main factors for the growth in the number of distributed energy technology

**Table 6** shows the regression analysis results of the specific factors that have

All specific factors had a positive effect on the distributed generation technology adoption by companies with a probability of error *p* of no more than 0.05. The coefficient β with the variable "efficiency" was 0.324 (*p* < 0.01); for the factor "no energy transfer costs" was β = 0.378 (*p* < 0.05); and for the factor "absence of payment for technological connection to electric networks" was β = 0.321 (*p* < 0.05). At the same time, the factors "the existing price ratio for electric energy" (β = 0.016; *p* > 0.10) and "the possibility of changing the volumes of generated electric and thermal energy when economic situation changes" (β = 0.163; *p* > 0.10) did not

The results of testing hypotheses are the following. According to Hypothesis 1, which described the factors influencing the distributed energy technology perception by companies, it was partially confirmed for intraorganizational factors, (a) technical feasibility (β = 0.264; *p* < 0.05); (d) perceived benefits (β = 0.451; *p* < 0.01), and (e) electricity cost (β = 0.598; *p* < 0.05), and environmental factor, (i) the regulator's decision (β = 0.396; *p* < 0.05). The factors (f) costs of building and installing distributed generation sources (β = −0.387; *p* < 0.01) and (g) market pressure (β = −0.196; p < 0.01) have a negative impact on the distributed energy technology adoption. For factors (c) perceived risks (β = 0.166; *p* < 0.01) and (h) possibility of changing the volumes of generated electrical and thermal energy

According to Hypothesis 2, companies' perception of distributed energy technologies is influenced by specific factors. This hypothesis is partially confirmed for common factors: (b) the presence of by-products that can be used as fuel (β = 0.421; *p* < 0.01); (d) high efficiency (β = 0.324; *p* < 0.10); (e) no costs for energy transfer (β = 0.316; *p* < 0.01); and (h) lack of payment for technological connection to electric networks (β = 0.363; *p* < 0.01). The influence of factors (g) existing ratio of prices for electric energy and natural gas (β = 0.016; *p* < 0.01); (i) possibility of changing the volume of generated electrical and thermal energy (β = 0.163; *p* = 0.45); and (j) a reduction in need for energy transmission over considerable

Thus, the proposed model of analysis is successful, describing various factors of adoption of technologies of distributed energy by industrial companies. Standardized coefficients not only allow testing hypotheses but can also be used to compare the influence of various characteristics of distributed energy facilities on

Thus, according to the obtained results, when deciding on the company's own generation, the main factors are technical feasibility (β = 0.421), perceived advantages (β = 0.363), electricity cost (β = 0.324), and the decision of regulators (β = − 0.309). It can be concluded that for analyzed companies, technical feasibility, cost of electricity, and perceived benefits are critical factors in deciding on the use of distributed generation technologies. The risk factor turned out to be insignificant (β = 0.209), which, when conducting in-depth interviews, the companies explained by the fact that distributed generation systems reduce the occurrence of the listed adverse effects to a minimum. Obtaining cheap electric and thermal energy, a

influence on the distributed energy technology adoption.

(β = 0.153; *p* < 0.01), the hypothesis was not confirmed.

distances (β = 0.211; *p* < 0.01) has not been confirmed.

the likelihood of their acceptance by industrial companies.

**154**

**5. Conclusions**

It is necessary to note some of the limitations of this study. It was not possible for us to interview the entire totality of Russian companies due to limited data collection opportunities. However, our sample of companies covers a representative part by sector, sales revenue, and company size. In the future, researchers would be able to analyze the factors of distributed generation technology adoption in a larger sample of companies.

The results of a sample of 69 companies confirm the practicability of a comprehensive assessment of the distributed generation technology adoption factors. Within the framework of this study, the selected internal, external, and specific factors were measured empirically and used to analyze the distributed generation technology adoption by companies.

The qualitative stage of research allowed us to draw initial conclusions about the significance of certain aspects of distributed generation technology adoption. Thus, in accordance with the results of the theoretical base analysis, it was empirically confirmed that when companies adopted distributed generation, the cost of electricity and technical compatibility were of greatest importance. At the qualitative stage, the majority of respondents named these aspects of adoption as the most important.
