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Starting from intention–behaviour models and building upon the growing evidence that aggregated internet search query data represent a good proxy of human interests and intentions. The purpose of this study is to demonstrate that the internet search traffic information related to the selected key terms associated with establishing new businesses, reflects well the dynamics of entrepreneurial activity in a country and can be used for predicting entrepreneurial activity at the national level.

Theoretical framework is based on intention–behaviour models and supported by the knowledge spillover theory of entrepreneurship. Monthly data on new business registration from 2018 to 2021 is derived from the open database of the Russian Federal Tax Service. Terms of internet search interest are identified through interviews with the recent founders of new businesses, whereas the internet search query statistics on the identified terms are obtained from Google Trends and Yandex Wordstat.

The results suggest that aggregated data about web searches related to opening a new business in a country is positively correlated with the dynamics of entrepreneurial activity in the country and, as such, may be useful for predicting the level of that activity.

The results may serve as a starting point for a new approach to measure, monitor and predict entrepreneurial activities in a country and can help in better addressing policymaking issues related to entrepreneurship.

To the best of the authors’ knowledge, this study is original in its approach and results. Building on intention–behaviour models, this study outlines, to the best of the authors’ knowledge, the first usage of big data for analysing the intention–behaviour relationship in entrepreneurship. This study also contributes to the ongoing debate about the value of big data for entrepreneurship research by proposing and demonstrating the credibility of internet search query data as a novel source of quality data in analysing and predicting a country’s entrepreneurial activity.

The purpose of this paper is to study the spectral sensitivity characteristics of new pyroelectric sensor based on tetraaminodiphenyl film within the wavelength range of 0.4-10 µm and 300-3,000 µm.

Mylar film with the thickness of about 70 µm was used as the input window. The MDR-41 monochromator-based spectrometric complex and the quasi-optical spectrometer with the set of backward-wave oscillators were used for measurements of the pyrodetector spectral characteristics within the 0.4-10 µm and 300-3,000 µm ranges, respectively.

Mylar was found to have absorption lines within the range of 0.4-10 µm, which must be taken into account when broadband detectors developing. The noise equivalent power in the visible and infrared ranges was less than 6 × 10^–10 W/Hz^1/2, which is about five times lower than for analogue ones. In the sub-THz range, the pyrodetector sensitivity is 2-8 times higher than the Golay cell. The sensitivity of such pyrodetector weakly depends on the wavelength in the total measured range.

The pyroelectric sensor has good prospects for use in super wide spectral range, from ultraviolet to millimeter radiation, in spectrometers for scientific research, in industry for the operational control of THz radiation sources, as well as in security THz-systems.

The spectral sensitivity characteristics of the pyroelectric photosensor based on TADPh in the visible, infrared and terahertz ranges were measured. The prospects for the use of such sensors were determined.