INTRODUCTION:

Currently, the remote retail sale of over-the-counter (OTC) medicines occupies a major share of the global e-pharmacy market and is a legal and generally accepted practice in most countries^1-4. The compound annual growth rate (CAGR 2024-2029) is expected to be 9.63%, as a result of which the projected volume of this market by 2029 will be $ 130.50 billion⁵.

The advantages of online purchases of medicines are saving time and money, favorable prices, the convenience of searching and comparing products, a large assortment (selection) of goods, the ability to find the right products and compare prices, offers, and discounts, the ability to shop anytime and anywhere, completeness of information and the ability to make the right choice, door to door delivery, and lack of personal communication with people in difficult epidemic situations^3,6-9. A study by the analytical company RNC Pharma well-known in the field of marketing information in the Russian pharmaceutical market, showed that the total volume of online sales in the first quarter of 2024 amounted to 103.1 billion rubles, which is 28.6% more than the same period last year, and exceeded the increase in sales in the pharmaceutical retail market (19.8%, including parapharmaceutical products)¹⁰.Although the popularity of remote purchases of medicines is steadily growing, consumers are faced with a new online payment environment, huge amounts of information, and problems with online access to trained specialists, with higher risks that may be exacerbated by the presence of illegal websites, substandard and falsified medicines, difficulties in managing personal information, and other circumstances^1,11-14. This is reflected in their trust in these purchases, which is currently a key condition for the further development of e-retailing of OTC medicines^1,11,13. The need to study trust is also explained:

1) By an increase in transaction costs with a low level of trust and irrational use of resources¹⁵,

2) By the many benefits for online buyers (consumers of OTC medicines) and sellers (pharmacy organizations): increasing the level of consumer satisfaction, their trust in the security of personal data¹⁶, and the perceived level of safety of purchasing OTC medicines by consumers^1,15, a more positive perception of medicine manufacturers¹⁷, etc.,

3) By the possibility of increasing the overall level of trust in society^18,19,

4) By the direct impact on the adoption of new technologies²⁰ and the development of the digital economy²¹.

There are various approaches to building consumer trust. In our opinion, the well-established unified theory of acceptance and use of technology (UTAUT) and its extended UTAUT2 model, which reveal behavioral aspects of consumer trust, including electronic retail of goods, are more suitable for this purpose concerning the online purchase of OTC medicines. However, this theory does not consider the influence of government policy in the field of consumer protection on the development of trust, the role of information quality in online medicine purchases, the quality of service, the possibility of transforming pharmacy into digital form and acquiring special importance of digital trust factors, and the urgent demand of OTC medicine consumers for online consultations. Therefore, it is of particular relevance:

1) To establish the possibility of using the behavioral factors UTAUT and UTAUT2 to form trust in the online purchase of OTC medicines,

2) To introduce other trust factors positively correlating with the formation of the trust under study,

3) To perform a marketing analysis of the combined formative factors of the trust under study.

This will optimize pharmaceutical activities in remote retail sales of medicines and shift the vector of the studied consumer trust to increase the perceived benefit of the purchase and reduce the perceived risk and uncertainty.

The work aims to identify factors that have a positive impact on the formation of consumer trust in the remote purchase of OTC medicines and to conduct marketing research in a group of target consumers in Russia.

MATERIALS AND METHODS:

The methodological basis for establishing the factors that form consumer trust in the online purchase of OTC medicines was based on the conceptual provisions and principles of the methodology of marketing research, the UTAUT and its extended model (UTAUT2), information quality theory, the theory of trust transfer, the theory of digital trust, and the quality of service model (SERVQUAL) adapted to electronic services.

The objects of the marketing study were 32 established formative factors. A survey of target consumers of OTC medicines sold remotely from 18 regions of the European part of Russia was conducted. The criteria for inclusion in the study were real and potential online users of OTC medicines over the age of 18 who agreed to participate in the survey. Participation was anonymous and voluntary, and the respondents were fully aware of the survey's purpose, nature, potential benefits, and risks. The study was based on the principles stipulated by the Helsinki Declaration and the International Chamber of Commerce (ICC)/European Society for Opinion and Marketing Research (ESOMAR) International Code on Market issues, public opinion, social research, and data analysis. The sampling was carried out by a random simple method. The representativeness of the sample was ensured by a sufficient number of respondents (confidence level: 95%, tolerable error: ±5%) and the correspondence of their ratio to the consumer structure of the online pharmaceutical market in Russia^{9, 13}.

Among the 629 respondents, there were 392 women (62.3%) and 237 men (37.7%). Their average age equaled 44.2±10.5 years (median 44, interquartile range (IQR): 34-54). The survey participants were classified into age groups: the participants aged 18-35 were considered young (32.3%); the participants aged 35-55 years – middle-aged (42.6%), and the participants aged 55 and older – elderly (25.1%). According to social status, most respondents were employed (66.5%), and pensioners made up only 11.3%. Most online consumers of OTC medicines had higher professional education (66.6%). The share of respondents with secondary professional education was 20.7%, and the share of the participants without professional education equaled 12.7%. In terms of the average monthly income per family member, most survey participants had an average (58.2%) and low (25.1%) income level.

The field stage of the study was conducted in April-July 2024 using a personal oral survey (21.5%) and a web survey (78.5%) using a structured questionnaire. The questions of the first part of the questionnaire concerned the characteristics of the survey participants, the second part involved the factors that have a positive impact on the formation of respondents' trust in the remote purchase of OTC medicines. All questionnaires were encoded for tracking purposes, and the codes were securely stored.

For marketing analysis of the positive significance (importance) of factors, the Likert scale was used (extremely important, very important, moderately important, slightly important, not at all important). The frequency analysis of the evaluation results was carried out for each factor. The group of positive ratings included the ratings "extremely important" and "very important" according to the Likert scale, the group of neutral ratings included "moderately important", and the group of negative ratings included "slightly important" and "not at all important". The assessment of the level of positive effect from the influence of the studied factors on the respondents was carried out by the method of individual point estimates (according to a 5-point scale), followed by the calculation of integral indicators.

Statistical data processing was performed using the IBM SPSS Statistics 29.0.1 software. The average frequency of occurrence of positively significant assessments (E_av) and the average assessment of the effectiveness of the impact of factors (_Aiav) are presented as M±σ (M is the arithmetic mean, σ is the standard quadratic deviation). The critical level of significance in testing statistical hypotheses in the study was assumed to be 0.05.

RESULTS:

Formulation of hypotheses and establishment of factors (derived hypotheses)

To identify the factors that have a positive impact on the formation of consumer trust in the online purchase of OTC medicines, hypotheses were formulated based on the UTAUT and its extended model (UTAUT2), information quality theory, trust transfer theory, digital trust theory, and service quality model (SERVQUAL) adapted to electronic services (Table 1).

Table 1. Factors that have a positive impact on the formation of consumer trust in the remote purchase of OTC medicines

Theoretical background	Hypothesis	Factor (a derivative of the hypothesis), F
According to the UTAUT, the level of behavioral trust of online shoppers is influenced, among other things, by expected performance, expected effort, social influence, and facilitating conditions	Expected efficiency (performance) positively correlates with trust in the purchase	F1. The expected improvement or preservation of health when using OTC medicines purchased remotely
	The expected effort positively correlates with trust in the purchase	F2. The expected ease in making online purchases of OTC medicines
		F3. Expected availability when making online purchases of OTC medicines
		F4. The expected convenience when making online purchases of OTC medicines
	Social influence positively correlates with trust in the purchase	F5. Positive recommendations from family members on online purchase of OTC medicines
		F6. Positive recommendations from colleagues and friends on online purchase of OTC medicines
	Facilitating conditions positively correlate with trust in the purchase	F7. Having the necessary knowledge to make online purchases of OTC medicines
		F8. Availability of necessary resources for online purchase of OTC medicines
		F9. Availability of the necessary support for the online purchase of OTC medicines
According to the extended model of the UTAUT (UTAUT2), the level of behavioral trust of online buyers in addition to UTAUT is influenced by habit, hedonistic motivation, and value	The habit positively correlates with trust in the purchase	F10.Frequent online purchases of other goods (not medicines)
	Hedonistic motivation positively correlates with trust in the purchase	F11. The pleasure derived from satisfying the need for OTC medicines
	Value positively correlates with trust in the purchase	F12. The predominance of the supposed advantages (benefits) from the online purchase of OTC medicines over their monetary cost
	Value positively correlates with trust in the purchase	F13. Estimated lower prices for OTC medicines when buying online
Government policy in the field of consumer protection affects the level of their trust	Ensuring compliance with consumers' rights to access safe goods positively correlates to trust in their purchase	F14. Ensuring compliance with consumers' rights to access safe OTC medicines when buying online
	Protecting the interests of consumers while providing them with equal access to goods positively correlates with trust in their purchase	F15. Protecting the interests of consumers who make online purchases and ensuring equal access to OTC medicines
According to the theory of information quality, the level of trust of online buyers is influenced by the usefulness, sufficiency, and reliability of information about goods	The usefulness of information about goods positively correlates with trust in their purchase	F16. The usefulness of the information provided on the website by the pharmacy organization for online purchase of OTC medicines
	The sufficiency of information about goods positively correlates with the trust in their purchase	F17. Sufficiency of the information provided on the website by the pharmacy organization for online purchase of OTC medicines
	The reliability of information about goods positively correlates with the trust in their purchase	F18. The reliability of the information provided on the website by the pharmacy organization for online purchase of OTC medicines
According to the theory of information quality, the level of trust of online buyers is influenced by the feedback mechanism, which allows one to obtain relevant, relevant, accurate, and comprehensive information	The presence of a feedback mechanism that provides relevant information positively correlates with trust in the online purchase	F19. Availability of a feedback mechanism that allows one to obtain relevant information for online purchase of OTC medicines
	The availability of a feedback mechanism that provides up-to-date information positively correlates with trust in the online purchase	F20. Availability of a feedback mechanism that allows one to get up-to-date information for online purchase of OTC medicines
	The availability of a feedback mechanism that provides accurate information positively correlates with trust in the online purchase	F21. Availability of a feedback mechanism that allows one to get accurate information for online purchase of OTC medicines
	The availability of a feedback mechanism that provides comprehensive information positively correlates with trust in the online purchase	F22. Availability of a feedback mechanism that allows one to obtain comprehensive information for online purchase of OTC medicines
According to the recommendations on interpersonal communication, the level of trust of online consumers is influenced by online consultations with specialists as more reliable sources of information compared to other sources	Interpersonal recommendations positively correlate with trust in the purchase	F23. Online consultations (recommendations) with a doctor before buying OTC medicines
		F24. Online consultations (recommendations) with a pharmaceutical worker before buying OTC medicines
According to the theory of trust transfer, the cross-channel transfer of trust in various contexts affects the level of trust of online buyers	The transfer of positive trust from offline purchases of goods to online purchases positively correlates with trust in the online purchase	F25. Transferring positive trust from offline purchases in certain pharmacy organizations to online purchases
		F26. Transferring positive trust from offline purchases of certain medicines to their online purchases
According to the theory of digital trust, the level of trust of online consumers is influenced, among other things, by safety and reliability	The presence of a mechanism that ensures the safety of consumers positively correlates with trust in their online purchase	F27. The availability of a mechanism that provides online guarantees for security and confidentiality and includes warning information and reliable security signals
	The presence of a mechanism that ensures the reliability of the online service positively correlates with the trust in their online purchase	F28. The availability of a mechanism that ensures the technical and technological reliability of the online service when purchasing OTC medicines
According to the service quality model (SERVPERF) adapted to electronic services, the level of trust of online buyers is influenced, among other things, by material values, reliability, responsiveness, confidence	Perceived material values leading to satisfaction of the need for the product positively correlate with trust in the online purchase	F29. Perceived good quality of the pharmacy organization's website (attractive design, easy navigation, high-quality content, technical reliability, ease of use, accessibility to search engines)
	Perceived reliability in service positively correlates with trust in the online purchase	F30. Perceived reliability in the timely and accurate delivery of OTC medicines, in the absence of errors and inaccuracies in orders
	Perceived responsiveness positively correlates with trust in the online purchase	F31. Perceived responsiveness of pharmacy staff, quick response to requests related to online purchase of OTC medicines
	Perceived trust in good quality of service positively correlates with trust in the online purchase	F32. Perceived confidence in the correspondence of the actual quality of service received for the online purchase of OTC medicines to the expected one, or receiving better service than expected

Based on sources^22-29

Table 2. Results of the assessment of the level of positive effect from the impact of factors forming consumer trust in the remote purchase of OTC medicines in Russia

Factor	Rank *(R_i)¹**	Rank value *(C)²**	Factor weight *(W_i)³**	Factor assessment *(A_iср)*	Parametric index *(P_i)⁴**	Summary parametric index *(P_n)⁵**
F1	32	0.0019	0.061	4.72±0.48	0.29	4.3
F2	7		0.013	4.35±0.63	0.06
F3	22		0.042	4.56±0.55	0.20
F4	18		0.034	4.52±0.70	0.15
F5	12		0.023	4.26±0.76	0.10
F6	5		0.009	4.05±0.60	0.04
F7	13		0.025	4.25±0.52	0.11
F8	29		0.055	4.23±0.60	0.23
F9	20		0.038	4.03±0.52	0.15
F10	8		0.015	4.40±0.46	0.07
F11	19		0.036	4.05±0.76	0.15
F12	26		0.050	4.35±0.48	0.22
F13	10		0.019	3.90±0.66	0.07
F14	31		0.059	4.20±0.74	0.25
F15	30		0.057	4.18±0.65	0.24
F16	15		0.028	4.62±0.50	0.13
F17	14		0.027	4.25±0.66	0.12
F18	17		0.032	4.55±0.74	0.15
F19	11		0.021	4.40±0.55	0.09
F20	3		0.006	4.25±0.63	0.03
F21	2		0.004	4.05±0.74	0.02
F22	1		0.002	3.95±0.70	0.01
F23	28		0.053	3.86±0.55	0.21
F24	27		0.051	3.30±0.68	0.17
F25	4		0.008	3.85±0.55	0.03
F26	23		0.044	4.85±0.46	0.21
F27	24		0.046	4.12±0.70	0.19
F28	16		0.030	4.25±0.68	0.13
F29	6		0.011	4.35±0.55	0.05
F30	21		0.040	4.30±0.74	0.17
F31	9		0.017	4.18±0.74	0.07
F32	25		0.047	4.30±0.55	0.20

*¹ Direct ranking method. *² С=1/∑R_i. *³ W_i=R_i • C. *⁴ P_i=A_i • W_i. *⁵ Р_n=ΣP_i.

DISCUSSION:

The choice of UTAUT and its extended model (UTAUT2) showed that the hypotheses formulated on their basis and the established factors (F1-F9 and F1-F13, respectively) had a fairly high significance (E_av=84.4±9.2% and E_av=83.7±8.8%, respectively). The addition of UTAUT theory with UTAUT2 factors (F10-F13) did not significantly reduce the overall average significance of the factors (E_av=82.2±8.9%, p>0.05). Therefore, it is advisable to use the factors of the extended UTAUT2 model to build consumer trust in the remote purchase of OTC medicines. This is consistent with the literature data on using UTAUT2 factors in healthcare^31-35. However, in recent years, works have appeared in the literature indicating the controversial nature of certain UTAUT2 trust factors (F2-F4, F7-F9, F12) concerning medical services^36-39. These statements make it necessary to conduct further research to understand the mechanism of behavioral intention underlying the formation of consumer trust concerning the online purchase of OTC medicines.

The permissibility of using other trust factors was justified by their essential importance for target consumers. This applied to factors related to the government policy (F14-F15): E_av=96.7±5.0, factors based on information quality theory (F16-F22): E_av=76.5±6.7, factors conditioned by interpersonal recommendations (F23-F24): E_av=94.2±2.8, factors based on the theory of trust transfer (F25-F26): E_av=80.9±13.8, and the theory of digital trust (F27-F28): E_av=87.2±5.9, factors based on the SERVPERF adapted to electronic services (F29-F32): E_av=81.9±9.6. The results obtained for most of these factors (F14, F16-F20, F24, F28-F30) corresponded to the information in the literature concerning pharmacy^{3, 11, 17, 40-44}, medicine^{26, 45-50}, electronic commerce^{14, 51}, but for some of them (F23, F24, F27, F31) there were some discrepancies^{1, 3, 39, 50}. This confirmed the need for further study of the mechanism of formation of consumer trust in the remote purchase of OTC medicines.

A marketing analysis of the positive effect of the impact of factors forming consumer trust showed that only 18.8% of the factors had a high effect (A_iav> 4.5). On the other hand, only 15.6% of the factors had a low positive effect (A_iav< 4.0). The average overall positive effect from the impact of factors on the survey participants (P_n=4.3) indicated the need for an in-depth analysis of the mechanism of practical manifestation of trust factors depending on the demographic characteristics of consumers, the general level of the government legislative framework in the field of circulation of medicines, including the possibility of their remote sale, technical and technological capabilities, the degree of uncertainty and risks for consumers when buying OTC medicines online, as indicated by the authors of some research articles^{37, 41, 46, 47}. In this study, only a reliable influence of the demographic parameter, the age group, on the positive effectiveness of certain factors of respondents' trust was established ^52-54.

CONCLUSIONS:

1. Based on the UTAUT2 model, the SERVQUAL service quality model adapted to electronic services, the theory of digital trust, the theory of trust transfer, the theory of information quality, and following the government policy in the field of consumer protection and recommendations on interpersonal communication, 24 hypotheses were formulated and 32 factors were identified that had a positive effect on the formation of consumer trust in the remote purchase of OTC medicines.

2. The marketing analysis showed a fairly high significance (importance) of the studied trust factors among the survey participants. The significant predominance of positive ratings in the overall frequency ratio (83.3±9.2%) and their prevalence in minimally important factors (F21 and F22, about 70%) confirmed the correctness of the developed hypotheses concerning the positive nature of the factors and the possibility of using these factors to build consumer trust in the online purchase of OTC medicines.

3. The presence of an average level of positive effect from the practical impact of the proposed factors on Russian consumers was empirically proven (P_n=4.3). A reliable dependence of the formation of some trust factors (F10, F13, F31) on the age group of respondents was established.

The results showed the need for further research to understand the mechanism of behavioral intention underlying the formation of consumer trust concerning the remote purchase of OTC medicines.

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Received on 17.10.2024 Revised on 13.02.2025

Accepted on 15.04.2025 Published on 02.05.2025

Available online from May 07, 2025

Research J. Pharmacy and Technology. 2025;18(5):2363-2370.

DOI: 10.52711/0974-360X.2025.00338

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