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ISSN : 1598-7248 (Print)
ISSN : 2234-6473 (Online)
Industrial Engineering & Management Systems Vol.19 No.3 pp.576-588

Model of Consumer Behavior during the Digital Transformation of the Economy

Natalya A. Yegina*, Elena S. Zemskova, Natalya V. Anikina, Vladimir A. Gorin
Department of Economics, Ogarev Mordovia State University, Saransk, Russian Federation
*Corresponding Author, E-mail:
June 1, 2020 June 22, 2020 June 29, 2020


This article explores the factors that influence consumer behavior under the conditions of technological changes and the accompanying social and economic externalities. The research goals were to develop a theory of consumer behavior and, based on such a theory, to consider a conceptual model of a digital consumer behavior during digital transformation. The authors systematized the theoretical approaches to understanding the models of consumer behavior and proposed to supplement the existing groups of models with incremental factors, which are caused by the impact of digitalization on society. Within this approach, network interaction algorithms can accurately predict the needs of each individual and suggest the most optimal way of meeting them. The authors developed a conceptual model of consumer behavior. In this model, on the one hand, the digital consumers are at the center of their own digital ecosystems tailored to their specific needs. On the other hand, using certain elements of the digital environment, they create digital footprints that are useful for other participants in the socioeconomic system. Considering this phenomenon allowed the authors to formulate and describe the social and economic externalities generated by the digitalization of consumption and include these in the proposed conceptual model of consumer behavior. Moreover, the authors studied the relationship between the use of digital technology and the socioeconomic development of countries. These countries were divided into clusters with different relationships between particular social parameters and varying levels of digital consumption. Having examined the dynamics of consumer price indices for certain groups of goods in the Russian Federation, the authors propose the hypothesis about the specifics of the digital consumption culture, which reduce both the transactional and direct costs for the consumer.



    Digital technologies and the network effects they generate have become deeply rooted in our political, economic, social, and cultural lives, exerting influence on the actors of the world economy and determining social progress.

    Digital transformation implies changes in the economies of countries and regions. Thus, the labor market is undergoing modification with the emergence of new jobs and the increase of consumers’ effective demand for goods and services (Markina and Riashchenko, 2014;Abdullaev et al., 2019). In addition, markets are expanding, and the competition among industries and countries is intensifying. All this can be both a source of growth and development of national economies and a significant challenge for them.

    The social paradigm of people’s lives is changing. Digitalization provides unique opportunities for selfdevelopment, acquisition of new skills and competencies, and professional growth. In other words, new social elevators are emerging as a result of this phenomenon. Individuals and companies involved in the digitalization—as its organic components—develop new models of behavior, enjoying various socioeconomic benefits and incentives.

    Undoubtedly, the digital revolution has led to profound structural changes in the whole production process, including consumption. As a traditional and the most important area of social life, consumption is undergoing farreaching structural changes driven by the digital economy.

    Considering all these, the current work’s research hypothesis was based on the assumption that a new model of consumer behavior and a system of values and preferences are currently being formed under the influence of the determinants of the digital economy. As a result, the target function of consumption has become more complex and has acquired new attitudes.

    Consumer behavior theory is a highly debatable issue in economics as it has been influenced by changes in the scientific views at different stages of the historical development of society. In the situation of rapidly changing lifestyles and social activities, the global scientific community has to find a new paradigm of scientific research. This requires an integrated approach to the systematization of existing knowledge and theories and new approaches to the study of consumption, which represent alternative points of view and complement each other (Danilcheko, 2013;Fedorenko et al., 2016). This methodology should reflect all scientific advances and global trends in digitalization and societal transformation.


    Considering the specifics of the research theme, the authors used the theoretical and methodological principles of interdisciplinary and multidisciplinary approaches, including the analysis of philosophical, historical, economic, social, cultural, and behavioral prerequisites underlying the formation of a consumer behavior model in specific conditions.

    The system and integration approach enabled us to present a logical and comprehensive consideration of various interrelated theories and institutions. This combination of tools allowed us to identify the key problems at the following stages of research:

    • 1) Substantiation of a theory, which states that the rapid development of digital technology and technological changes in the beginning of the twenty first century led to global social transformation in human values, needs, and motives, among others;

    • 2) Critical analysis of the approaches to modeling consumer behavior during different periods in history;

    • 3) Theoretical justification of the conceptual model of consumer behavior in the context of digital transformation, thus enriching and developing the theory of consumer behavior.

    The methods of applied statistics were used to assess the influence of digital technologies on the structure and dynamics of consumption in the Russian Federation. Having performed the cluster analysis of large data arrays, we determined the characteristic features of consumer behavior in different countries. This study allowed us to give the socioeconomic description of the digital consumer in the context of global digital changes.

    In this study, we used the data from official statistical sources (Rosstat, Eurostat, Knoema, and OECD. Stat platforms) and the analytical materials from the United Nations, the World Bank Group, and the McKinsey Global Institute.


    Modern economics is anticipating a new digital paradigm that will examine consumer behavior theory, among other issues. Despite the lack of research on consumer behavior in the context of digital transformation, some of its aspects have already been explored by several researchers, including Akerlof (1970), Tversky and Kahneman (1992), Castells and Himanen (2002), Machlup (1966), Masuda (1981), Tapscott (1999), Thaler (1985), Antipina (2014), Dolgin (2010), and Dyatlov (2017).

    For instance, Tapscott (1999) regards the transformation of the consumer-producer interaction system as the most important prerequisite for the emergence of the digital society: “the boundaries between production and consumption are being erased, and mass production is being replaced by customized production”. The consumer is becoming the key player in the market, digital technologies simplify the interaction between the consumer and the producer, while the conditions are created for “shifting consumer interests from long-term to short-term, which leads to the intensification of consumption” (Najmulmunir, 2020;Piriyawatthana et al., 2020).

    Value attitudes, as well as moral and ethical standards, are undergoing profound changes. Production ethics, as an informal institution, is losing its relevance and is becoming a thing of the past. In turn, consumption is expanded through economic socialization and stratification, while consumption culture is evolving rapidly (Ovrutsky, 2010).

    Machlup (1966), proposed theories about the information society, in which they described the new social reality that is being formed. Various aspects of the latter were considered in detail by Masuda (1981), who noted that “standards of living, forms of work and leisure organization, education system, and consumption are clearly influenced by the progress in information and knowledge”.

    This allowed us to draw a very important conclusion that the revolutionary transformation of modern society under the influence of massive use of digital technologies leads to changes in reproduction, including consumption. New patterns of consumer behavior are being formed as stable patterns, and they bear the characteristic features of the digital economic reality.

    Over one and a half centuries of research on the theory of consumption, scientists have proposed various theoretical and applied models. Let us analyze the evolution of consumer behavior models within the framework of the above hypothesis about the role of digital technologies in modern society.

    The first group of models, the so-called theoretical models (Table 1), was formed according to the traditional premises of neoclassical economic theory about the wish of consumers to maximize their utility in the context of budgetary constraints and the prevailing market prices.

    From our perspective, the practical implementation of these approaches is limited and has some disadvantages. For instance, the above models do not reflect the qualitative side of income structure related to consumption and savings, focusing only on the quantitative aspect of this problem. In addition, their mathematical abstraction is extremely high, which makes it impossible to develop real models of consumer behavior in conditions of uncertainty and risk. The patterns of consumption identified in these models occur only in static conditions.

    The second group includes macroeconometric models of consumer behavior based on the microeconomic justification of dynamic macro models of the goods market. Consumer behavior is modeled and forecasted on the basis of the following principles: their subjects are heterogeneous agents (consumers have certain parametric indicators, for example, assets, income, education, skills, age, gender, information, and networks); researchers use a method of dynamic programming based on variation methods and the analysis of limit values; the research is based on the model of general equilibrium. This group of consumption models supplements the theories considered above with new premises and limitations within the framework of general equilibrium of exogenous and endogenous incomplete markets.

    Considering this theoretical approach, we would like to highlight the model of overlapping generations of Diamond (1965), which shows the change in consumer behavior as people are getting older and justifies policies aimed at expanding consumption through fair social insurance and credit system. The following macroeconometric models have also become very popular in recent decades: the Aiyagari self-insurance model based on the uncertainty and risks of individuals (Aiyagari, 1994); the Kiyotaki-Moore model drawing on the fact that different time preferences of the subjects lead to the emergence of the financial market, while loans influence the distribution of their income (Kiyotaki and Moore, 1997); the Krusell-Smith model – one of the stochastic models of economic growth which allows insuring the risks of entities in the conditions of uncertainty and risk (Krusell and Smit, 1998).

    At present some researchers note the paradox of a formalized approach to the modeling of economic processes and phenomena: combining “formal sophistication ... with elementary methodology, which prevents making meaningful generalizations.” In this regard, we would like to mention the criticism of the practical significance of ma-croeconometric models expressed by O. Blanchard, S. Fisher, and Yu. Avtonomov. These authors point out the fragmentation and eclecticism of these models and claim that it is impossible to use them in applied macro analysis and forecasting, since these models cannot objectively describe all accumulated experimental data. However, these models allow forecasting certain patterns of individuals behavior: “the existence of incomplete contracts, the relationship of consumers and sellers, the construction of optimal motivation schemes, the structure of the rationing and income redistribution mechanism, and the inherent rational unselfish behavior (altruism)” (Blanchard and Fisher, 1989;Avtonomov, 2006).

    Obviously, if modern economic science does not consider irrational factors, it cannot be fully objective, moreover, it is misleading. We have faced the situation when abstract formalization and theoretical analysis based on macroeconomic models cannot be performed in the countries with on-going social transformations, military conflicts, economic crises, transformation processes, or economies in transition, experiencing the impact of globalization, digitalization, etc. Under these conditions, it seems viable to form a third group of models based on a multidisciplinary approach to the study of consumer behavior (Table 2).

    The advantage of a multidisciplinary approach is the ability to study the subject applying various theories within general economics. In turn, the principle of multidisciplinarity allows us to combine the methodological approaches of the sciences that explore consumption. Both principles enrich the theory of consumption and can be implemented within the system integrative approach that analyzes not only social and economic factors of consumer behavior, but also cultural, philosophical, historical, and psychological ones.

    New approaches attempt to explain the specifics of people’s behavior, including that of consumers, without employing traditional theoretical methods and concepts.

    Therefore, at present moment, due to the law of increasing human needs, there is further quantitative growth and qualitative development of needs, which leads to the adjustment of the target function of consumption, its enrichment by various social, cultural, economic, and other parameters under the influence of digital transformation. The criteria for assessing the usefulness of goods are changing, and their structure is expanded with new components which are transformed into internal motives of consumer behavior under the influence of exogenous factors. The target function of consumption acts not so much as the desired result, but as a criterion for the effectiveness of the selection process.

    4. RESULTS

    4.1 Justification of the Conceptual Model of Consumer Behavior in the Digital Economy

    Having performed the retrospective analysis and systematization of different views on the evolution of the theory of consumer behavior, we defined it as an integral element of economic development. Under the conditions of total informatization and digitalization one cannot eliminate the influence of technological progress (the use of smart phones, applications, the Internet, social networks, or electronic media) on consumer decisions (Yegina, 2019). Accordingly, the problem of modeling consumer behavior under the influence of digitalization factors is particularly relevant for economic entities when forecasting and taking managerial decisions, or developing a state social and economic policy adequate to new challenges.

    We proposed a novel conceptual model of consumer behavior in the new conditions driven by the digital transformation in all social spheres (Figure 1)

    As long as we perceive the digital economy as a new social reality, we should consider its versatility and the radical transformations that the digital revolution has introduced in all aspects of public life.

    For instance, digital technologies and informatization processes have initiated a profound social transformation: changes in gender identity and values typical of the representatives of different generations, a greater need for sharing resources, and an awareness of social responsibility for lean consumption, aggravation of social inequality, increased labor mobility and the labor market transformation, reforms in the education and health care systems, aggravation of financial, environmental, and social crises.

    We studied the impact of particular determinants of the digital economy on consumer behavior in conjunction with social factors in different countries. The analysis was performed with the multidimensional statistical method – cluster analysis, which involved splitting the set of studied objects and features into groups (clusters) that were homogeneous according to certain characteristics. An advantage of this approach is the ability to operate a significantly larger number of subjects (observations), as well as to classify them not according to one, but several parameters.

    The clustering of 75 countries with different levels of development was based on two features: the ICT Development Index and GDP per capita. The first principle was selected in line with the research goal: to develop the conceptual model of the digital consumer behavior in the context of digital transformation. However, the nature of consumer behavior is also determined by such an important factor as income since budget is the most important limiting factor. This determined the choice of the second classification feature.

    Having analyzed the results, we identified four clusters of countries according to their socioeconomic development and ICT penetration (Table 3).

    The countries included in the first and second clusters demonstrate a low level of socioeconomic and ICT development. These countries obviously lack the economic, intellectual, and institutional potential required for the fast formation of the digital society, and, consequently, their digital consumption is in its infancy.

    The countries in the third (emerging economies) and the fourth clusters (developed countries) are of particular interest due to the high penetration of digital technologies in society. In these clusters, let us consider the relationship between certain social factors and indicators of the digital economy and their impact on the digital behavior of consumers (the use of digital technologies and the Internet to purchase main goods and services (Y)). For this purpose, we performed correlation analysis (the values of the correlation coefficient presented in Table 4 are reliable according to the Student criterion with a probability of 95% (tcr = 2.0195)).

    The results of the analysis show that in the third and fourth clusters consumers actively use digital services and mobile means of communication to buy main goods and services. There is a strong relationship between the studied parameters, which also indicates a high level of ICT infrastructure development in these countries.

    We should also note that these countries have a high level of urbanization and a significant share of people with higher education. The promotion of digital services begins in large cities, and the most active users of these services are educated people.

    In this regard, we would like to point out the most important contradictions and threats to the sustainable development of modern society due to the mass adoption of digital technologies: growing social injustice, aggravation of the digital divide, increasing social exclusion, and the violation of the principles of collective bargaining.

    These conditions lead to the emergence of a new type of consumers – the digital consumer (Figure 1). Their behavior is determined both by the digital environ-ment and the factors of social transformation. A digital consumption ecosystem is being formed around this person, surrounding the user with automated personal consultants (digital platforms and services, social networks, and smart spaces). Electronic devices and network interaction technologies study and predict the needs of the consumers, and help them make and implement their choices (Yegina, 2019;Tosida et al., 2020;Yakhneeva et al., 2020). In addition, consumers often need not only a consultant, but also a guarantor of the transaction.

    The interaction in the subsystem “digital consumer – consumption ecosystem” creates a multiplicative accelerating effect that manifests itself in the formation of trust capital (a specific form of social or cultural capital). The value of trust capital in consumption should not be underestimated since it implies lower costs of searching information for consumers, as well as enables the coordination of joint activities, optimizes economic choice, replacing formal rules and procedures with the relationships of trust, and ensures better communication. In addition, the trust formed by consumers and the existing system of values have a significant impact on the digital consumer culture.

    Undoubtedly, the emerging new model of consumer behavior greatly influences the social and economic development of countries and regions (Figure 1). Let us consider in detail its social effects.

    Digital technologies influence consumer behavior and provide the opportunity for moving upward certain social layers, thus creating social elevators. As a rule, a social elevator is represented by certain actions or situations that give access to significant resources in a given society. For a long time, social mobility was limited by a number of insurmountable institutional reasons (belonging to a certain family, estate, caste, financial situation, access to power, or education).

    Studying the access to education, we can clearly see how the possibilities in this field have changed due to digital technologies. Obtaining a formal education in the pre-digital era was associated with significant costs while preparing for admission to an educational institution, moving to a place of study, and paying for accommodation and the training itself. Considering the costs related to finding information about the desired educational institution and alternative areas of training, potential applicants were guided by the proverb “there is no place like home,” which reduced the chances of upward social mobility.

    The advent of digital technology and broadband Internet access significantly reduce the costs of finding alternatives and information about the desired educational institution for today’s applicants. Moreover, there are numerous both paid and free educational services that allow one to prepare for enrollment at university. That is, distance, tight budget, and lack of information that used to limit access to educational services (social elevators) nowadays hinder social mobility to a much lesser extent.

    The digital economy is bridging the gap between potential participants in an employer-employee relationship, which also acts as a factor in upward social mobility. A person with a certain level of competence can find work outside their current place of residence. As a rule, large cities offer higher salaries for a similar level of competence due to greater housing and rent costs and a higher cost of living in general. The development of remote work allows one to get a more competitive salary without giving up the benefits of living in a small city.

    On the one hand, digital economy promotes necessary competencies with relatively lower costs, compared to traditional economy. On the other hand, the possibilities for mastering these competencies are not the same (the phenomenon of digital exclusion demonstrates that the adaptation to modern services varies significantly for different generations).

    The studies of the UN and the World Bank reveal that modern development is associated with increasing social inequality within countries. However, its intensity varies in different regions of the world (for example, inequality in the US and the Middle East is growing faster than in Western Europe). The financial crisis of 2008 led to a global decrease in the share of middle class property (World Economic and Social Survey 2014; World Inequality Report 2018). Social stratification remains a major challenge both for national economies and globally. However, the social elevators mentioned above alleviate this problem (however, one should bear in mind that this is possible only if the subject is ready for changes).

    In addition, nowadays we can witness the emergence of a unique digital culture of consumer behavior. Digital technology helps a person to find “friends” by joining various special interest groups. These communities reveal the talents of a particular person and, accordingly, contribute to their progress in this field.

    The involvement of consumers in different sharing platforms, social networks, certain groups in social networks form the history of their interaction, and allow companies to evaluate the services provided or the goods sold. Ratings and popularity on social networks and sharing platforms are an element of digital culture that can be monetized and act as a social elevator. Social networks are becoming both a personal diary and a source of income. Successful bloggers today are opinion leaders that determine not only consumer, but also political behavior of people (Zemskova, 2019).

    A specific feature of modern digital culture is reputation that can be broadcast to the entire global market. The reputation formed in the digital environment is a currency that cannot be faked and is an important parameter of selfregulation, more significant than government regulation.

    In other words, digital culture significantly reduces depends on the goods we intend to consume – search, experience, or credence ones. We can find out the quali-ty of credence and experience goods only after we con-sume them. That is, ten years ago to learn whether we would like a book or a movie, we had to read or watch it. Currently, recommendation engines reveal the prefer-ences of a particular individual and compare them with the preferences of the people who have chosen similar goods (clothes, films, books, or interiors) and were satis-fied with this choice (it is important that data from dif-ferent platforms and devices of this individual can be consolidated). Next, the recommendation service uses certain algorithms to provide accurate targeted advice that significantly reduces the cost of finding infor-mation and examining goods. The level of trust in the source of information is directly proportional to the ac-curacy of the assessments of the goods that the person had already consumed earlier, according to the recom-mendation of this source.

    Accordingly, the more evaluations are given to the same good by different groups of users (reviewers), the more accurate the recommendations will be. Due to the network effect, digital culture becomes more efficient with a larger number of people involved in the network.

    Another obvious social effect of digitalization is improved living conditions. For instance, digital e-government systems make it possible to receive a wide range of services provided by the state without leaving home: to pay fines or taxes, to obtain certificates, to submit documents, to register a business, to make an appointment with a doctor, etc. Electronic banking and online shopping not only help save time required for planning a purchase and the purchase itself, but also allow one to save money.

    Regarding humanization of labor, we would like to mention the works of alarmists (Autor and Salomons, 2017) that consider economy digitalization a global challenge for the labor market and, in general, preserva-tion of humans as a biological species. On the one hand, labor is a process of self-expression and self-affirmation of a person, the application of gained skills, the realiza-tion of their abilities and creativity, and digital technolo-gies give new opportunities for the comprehensive de-velopment of the individual. The boundaries between working time and free time are shifting, while new forms of employment (non-traditional and self-employment) are becoming more popular. On the other hand, some dangerous and routine activities can now be delegated to digital technologies and robots, which improves the quality of working life.

    Considering the economic effects, we would like to note (Figure 1) that the sphere of consumption remains the most important area of social life, being the basis of economic growth and development. Digital transfor-mation contributes to the increase in solvent demand of consumers (due to the effects of income and substitu-tion), which initiates the growth in the quality and standard of living. Digital technologies lead to the ex-pansion of consumer demand for economic goods, and the dynamics of the structure of consumer spending is changing (Figure 2).

    We studied the dynamics of prices for the main groups of consumer goods and services in the period from 2010 to 2019, dividing them into two groups. Group A included goods and services, the consumption of which implies the application of digital technologies (according to the Association of Internet Commerce Companies, the goods that Russians most often purchase online are household appliances, electronics, and clothes). Also, we included the services of banks that apply digital technologies in their work, as well as services for renting apartments in this group. Group B covered mainly services that are directly connected with people who provide them, and these services are consumed offline.

    The analysis revealed that consumer price indices for the goods in group A grew slower than those for the goods in group B. This indicates the positive influence of digital technologies on the expansion of consumption.

    The ideology of a consumer society used in Keynesian models of economic growth eventually led to such externalities as environmental pollution, total extinction of some plant and animal species, and degradation of ecosystems. Humanity has reached the resource limit that digital technologies can remove as they will engage the resources already put into circulation in a more productive and rational way, both from the economic and environmental perspective (Ivlev et al., 2016).

    In previous publications, we focused on the positive external effects produced by carpooling services: traffic congestion and air emissions are reduced when fellow travelers make a journey in the same car. Selling or exchanging unnecessary clothes, sports equipment, and other things on C2C sites reduces overproduction by providing access to goods that are not fully used (Zemskova, 2019).

    Modern culture shifts the focus from mass consumption to lean consumption, whose main value is not the demonstration of status, but a real responsibility to future generations. It is the values of lean consumption that made us think about the appropriateness of owning a car (which 80% of the time is not used by its owners), buying new clothes every season (the production of clothes requires a large amount of fresh water, and the use of disposable tableware (made of non-degradable plastic).

    Network effects, amplified by digital platforms, can significantly increase the efficiency of using goods that are already in circulation due to the synchronous interaction of many participants redistributing goods and benefits. This organization of modern society allows implementing the values of lean consumption.

    There is no doubt that digital technologies and the consumption mediated by them will become a powerful driver of countries’ economic growth and increase their competitiveness. For instance, according to the estimates of the McKinsey Global Institute, by 2025 the Chinese economy is expected to grow by 22% due to the active use of digital technologies. In the US the added value created by Internet technologies can reach USD 1.6-2.2 trillion, and in Russia, 19-34% of the expected GDP growth will be generated by the digital economy.

    The competition that manufacturers face under the conditions of increasing globalization and online sales due to the wider use of digital technologies strengthens their competitive advantages and helps them focus not on local, but on global markets. Understanding this can help manufacturers open new markets and increase their profits.

    4.2 Digital Consumer: Unique Features and Consumption Specifics

    Considering all the above, the question naturally arises: what is the digital consumer like? What are the unique features of their behavior in the digital economy?

    Undoubtedly, in the digital economy, consumption is undergoing qualitative systemic transformations, and consumer behavior acquires unique characteristics (Figure 3).

    Firstly, digital technologies and wide access to information make consumption more rational, creating a variety of choices, which allows the consumer to maximize their usefulness, while needs are satisfied more efficiently.

    Secondly, modern consumers attribute special importance to the goods whose utility is influenced by external effects (the so-called effects of demonstrative behavior). H. Leibenstein commented on the goods with subjective utility: “... the utility extracted from a given product increases or decreases depending on whether others buy this product, or because this product has a higher price compared to other products” (Leibenstein, 1993). The consumer is often not so much interested in the good itself or its consumer functions, but in its symbol, which often has zero or even negative value, not only for the subject, but also for society as a whole. As Dolgin (2010) rightly notes, “products are more and more frequently used not just as objects with useful properties, but as signs, symbols, and cultural codes, in other words, as signals and messages”.

    The special importance of the symbolic value of goods underlies another characteristic feature of consumer behavior – the so-called integrated consumer behavior or, as A. Dolgin names it, “club consumption”. Club consumption, which is undoubtedly a phenomenon of the digital economy, helps to structure society, which enables to minimize transaction costs since it is easier for individuals to filter out information about club mates according to a set of criteria. In addition, belonging to one club allows accessing the necessary information about how and what to consume, thanks to the systematization of data on the preferences of their club mates (Dolgin, 2010). Here, social networks play a special role, acting as the “circulatory system” in the interaction of the participants in special interest groups (Yegina, 2019).

    What is more, we can witness the formation of a special model of consumer behavior based on the collective use of economic goods. This refers to the so-called collaborative (lean) consumption. Collaborative consumption implies rethinking of not only what people purchase, but also how they consume it. The economy of collaborative consumption reflects the ongoing transformation of consumer values. Digital technologies, as well as the increasing popularity and growth of online interest communities, which have developed their own moderation and rules, have unprecedentedly increased trust between the participants.

    We can observe the growing importance and role of consumer networking. The new digital reality and network interaction give consumers the opportunity not only to communicate, purchase goods and services, but also to take active part in the production process; their life experience, skills and knowledge allow them to determine the technical parameters of goods and to transform them. Tapscott (1999) called this unique behavior feature prosumerism – a combination of producer and consumer. Indeed, nowadays consumers want not only to participate in the final consumption of goods and services, but also in their creation. Consumers no longer differentiate between production and consumption, and they are naturally involved in both processes, which become a meaning of life and a source of development and inspiration for them.

    In addition to this, a close relationship between the manufacturer and the consumer allows the customization of products in accordance with the needs of the consumer. The manufacturer personalizes the products to meet the individual needs of the consumer, maximizing its usefulness. E-commerce and mobile applications allow the consumer to receive a unique offer even before the sale itself (Yegina et al., 2019).

    In turn, this leads to personalization of demand. Due to the effect of price differentiation, manufacturers take into account different elasticities of demand for different categories of consumers. Moreover, consumer groups form really easily in the information space, i.e. regardless of their real connection with each other. Modern digital technologies enable fast accumulation and update of the information required for building individual demand functions.

    The greening of consumption – the increasing popularity of the ideas related to environmentally friendly consumption, environmental awareness, zero waste, and recycling – is one of the factors caused by the digital transformation. Consumers are ready to change the format and structure of consumption, abandon the principles of demonstrative consumption, and focus on saving resources, which can be achieved thanks to digital technologies.

    Another point is the digitalization of consumer behavior, which we understand as the mediation of goods consumption by digital technologies. On the one hand, consumption itself becomes virtual, and there are two independent ways of consumption: in real time in the network (online) and beyond it, but using digital technology (offline). There is no doubt that virtual space has its advantages as it removes all restrictions on consumers regarding the place and time of consumption, enables collaborative consumption, expands the possibilities of search for goods, and offers a wider range of payment methods. All this helps overcome the limitations of traditional consumption. A new global type of online consumption with its specific digital culture is being formed.

    On the other hand, new consumer goods – digital (network) goods – are emerging. The category “digital (network) goods” is a new one in economics and represents the product of the formed digital paradigm and is immediately connected with such concepts as “electronic good” or “information good”. The digital good is a good that can be represented in digital form (digitized) and transmitted over the Internet. For example, this refers to audio and video products, databases, software, and online services (government services, distance learning, or telemedicine). Copying digital goods leads to the emergence of their digital “doubles”. All of them have a number of common features: they are indestructibility, transmutability and reproducibility.

    Finally, a digital consumption culture is formed. Its manifestations include a new value, semantic, and symbolic space of consumption, new consumption practices, the code of consumer behavior in the digital environment, overcoming digital illiteracy, and legal regulation of the behavior of business entities in the new reality.


    In this article, we systematized the existing theoretical approaches explaining consumer behavior models. The first group included the models based on the assumptions of the neoclassical economic theory about maximizing utility from consumption according to current prices and budget constraints. The models of this group are characterized by high abstraction, which allows mathematical interpretation of factors influencing consumption, but does not reflect the qualitative characteristics of reality. The second group included macroeconometric models of consumer behavior based on the microeconomic justification of dynamic macro-models of the goods market. This group of consumption models supplements the theories considered above with new premises and limitations within the framework of a general equilibrium of exogenous and endogenous incomplete markets. However, this group of models has the same drawback as the previous one: it does not enable the formalization of real socio-economic processes, world crises, the experience of the countries with economies in transition, digitalization, and the impact of globalization.

    In the third group, the models of consumer behavior were less formal and more realistic and took into account the widest possible range of factors determining consumer behavior. The interpretation of the research results of this group was used as the basis when building the conceptual model of consumer behavior presented in this article.

    This research paper presents an attempt of putting together and systematization of the premises for analyzing consumer behavior during the digital transformation using an interdisciplinary, multidisciplinary, and system integration approaches. At the same time, we aimed to consider not only the factors that influence the consumer in objective reality (big data, artificial intelligence, virtual reality, and the Internet of things) but also the consumer’s influence on this reality (social and economic effects of digitalization). It should be noted that when describing the effects of digitalization, we discovered there was not enough empirical data that could have emphasized the advantages of a new digital culture based on horizontal trust. Paradoxically, in the Big Data era, national statistical agencies and influential international organizations do not have a set of tools for analyzing the consequences that can be brought about by the changes. Therefore, the conceptual model of consumer behavior proposed in this article under the conditions of digital transformation can be useful for determining the range of areas that require systematic empirical observations.


    The paper systematizes the existing theoretical approaches and proposes its own conceptual model of consumer behavior during digital transformation, reflecting the factors that influence consumers in objective reality (big data, artificial intelligence, virtual reality, and the Internet of things), as well as consumers’ influence on reality.

    The measurable results of the study include the clustering of 75 countries on the basis of two criteria – the “ICT Development Index” and “GDP per capita.” This analysis revealed four clusters of countries that differ in the nature of the relationship between the studied parameters: the higher GDP per capita is, the more actively consumers use digital services to meet their needs. In turn, the analysis of Russian statistics showed that consumer price indices for goods that are often bought online grew more slowly (and even decreased in some categories) than price indices for goods and services more often purchased offline.

    Another significant point if that the conceptual model of consumer behavior proposed in the article under the conditions of digital transformation determines the range of areas in which national statistical agencies should aggregate data for making socio-economic forecasts and adapting the business community to the transformation of consumer demand in the digital economy.


    This article was written with the support of the Russian Foundation for Basic Research (RFBR), project No. 19-010-00142 A “Modeling of consumer behavior in the context of digital transformation”.



    The conceptual model of consumer behavior in the context of digital transformation.


    Consumer price indices for some goods and services in the Russian Federation in the period from 2010 to 2019 (2010 = 100)*.


    Digital consumer.


    Theoretical models of consumer behavior (Manakhova, 2014)

    Multidisciplinary approaches to the study of consumer behavior

    The results of the cluster analysis of countries according to their socioeconomic development and ICT penetration (2017-2018).

    <sup>*</sup> calculated by the authors using the data of Rosstat, Eurostat, Knoema and OECD.Stat platforms.

    The results of the correlation analysis*

    <sup>*</sup> – calculated by the authors using the open data of Knoema platform.


    1. Abdullaev, F. O. , Khamraev, K. I. , Arzuova, S. A. , and Abdukayumov, A. N. (2019), Digital transformation of market institutions, Journal of Southwest Jiaotong University, 54(3), Available from:
    2. Aiyagari, S. R. (1994), Uninsured idiosyncratic risk and aggregate saving, Quarterly Journal of Economics, 109(3), 659-684.
    3. Akerlof, G. A. (1970), The market for “lemons”: Quality uncertainty and the market mechanism, Quarterly Journal of Economics, 84(3), 488-500.
    4. Antipina, O. N. (2014), Consumer behavior and market pricing in the information economy under the influence of debts, Moscow University Physics Bulletin. Series 6. Economics, 1, 19-36.
    5. Arieli, D. (2013), Behavioral Economics. Why Do People Behave Irrationally and How to Make Money on This, Translated from English by P. Mironov (ed.), Mann, Ivanov i Ferber, Moscow.
    6. Autor, D. and Salomons, A. (2017), Robocalypse now: Does productivity growth threaten employment? National Bureau of Economic Research, Available from:
    7. Avtonomov, Y. V. (2006), Modern approaches to economic modeling of a sense of justice, HSE Economic Journal, 4, 620-637.
    8. Baudrillard, J. (2006), Consumer Society: Myths and Structures, Translated from French, afterword and commentary by E. A. Samarskaya (ed.), Respublika: Kulturnaya Revolyutsiya, Moscow.
    9. Blackwell, R. D. , Miniard, P. W. , and Angel, J. F. (2002), Consumer Behavior, Peter Publishing House, St. Petersburg.
    10. Blanchard, O. and Fisher, S. (1989), Lectures on Macroeconomics, MIT Press, Cambridge.
    11. Bourdieu, P. (2002), Forms of capital, Economic Sociology, 3(5), 60-74.
    12. Castells, M. and Himanen, P. (2002), Information Society and Welfare State: The Finnish Model, Trans. From English by Kalinin, A. and Podoroga, Y. (eds.), Logos, Moscow.
    13. Danilcheko, V. (2013), Scientific basis of the assessment of the regional consumer market, Journal of Contemporary Economics Issues, 1,
    14. Diamond, P. (1965), National debt in a neoclassic growth model, American Economic Review, 55(5), 1126- 1150.
    15. Dolgin, A. (2010), Manifesto of the New Economy, The Second Invisible Hand of the Market, AST, Moscow.
    16. Doyle, P. (2003), Marketing Management and Strategy (3rd ed.), Peter, St. Petersburg.
    17. Dyatlov, S. (2017), E-neural-network Hyper-competitive economy, Publishing House of SPbGEU, St. Petersburg.
    18. Fedorenko, R. V. , Persteneva, N. P. , Konovalova, M. E. , and Tokarev, Y. A. (2016), Research of the regional service market in terms of international economic activity’s customs registration, International Journal of Economics and Financial Issues, 6(5), 136-144.
    19. Ivlev, V. Y. , Barkova, E. V. , Ivleva, M. I. , and Buzskaya, O. M. (2016), Environmental approach to the study of the modern stage of information society development: Research prospects, International Journal of Environmental and Science Education, 11(16), 9113- 9124.
    20. Jacobs, J. (1984), Cities and the Wealth of Nations, Random House, New York.
    21. Kiyotaki, N. and Moore, J. (1997), Credit cycles, Journal of Political Economy, 105(2), 211-248.
    22. Kotler, F. (1992), Fundamentals of marketing, Translated from English by V. B. Bobrov ed. E. Penkova. Novosibirsk: Nauka.
    23. Krusell, P. and Smith, A. (1998), Income and wealth heterogeneity in the macroeconomy, Journal of Political Economy, 106(5), 867-896.
    24. Leibenstein, H. (1993), The effect of joining the majority, the snob effect, and the Veblen effect in the theory of consumer demand. In: Milestones of Economic Thought, 1. The Theory of Consumer Behavior and Demand. Ed. V. M. Halperin. St. Petersburg: School of Economics, 304-325.
    25. Levitt, T. (1960), Marketing myopia, Harvard Business Review (July-August).
    26. Machlup, F. (1966), Production and Dissemination of Knowledge in the United States, Nauka, Moscow.
    27. Manakhova, I. (2014), Transformation of consumption in the conditions of the information economy: Dissertation, Ph.D. dissertation, Economic Sciences, Moscow.
    28. Markina, I. and Riashchenko, V. (2014), Functional aspects of consumer cooperation system, Journal of Contemporary Economics Issues, 2,
    29. Masuda, Y. (1981), The Information Society as Postindustrial Society, World futures Society, Bethesda MD.
    30. Najmulmunir, N. (2020), The role of pay, job security and sales force motivation in supply chain performance: A case of indonesian distribution companies, International Journal of Supply Chain Management (IJSCM), 9(1), 137-143.
    31. Ovrutsky, A. V. (2010), Social Philosophy of Consumption: Methodological and Theoretical Aspects, Rostov- on-Don: IPO PI SFU.
    32. Piriyawatthana, W. , Phumdara, T. , and Jermsittiparsert, K. (2020), Does the social capital matters in buyersupplier relationships? A Thai perspective, International Journal of Supply Chain Management (IJSCM), 9(1), 1-9.
    33. Salamat, A. and Didehkhani, H. (2017), Investigating the relationship between human resources management, measures and organizational justice of Alborz insurance employees in Golestan province, Uct Journal of Management and Accounting Studies, 5(4), 1-5.
    34. Sewell, C. and Brown, P. (2002), Customers for Life: How to Turn that Onetime Buyer into a Lifetime Customer, Jenson Books Inc, Fulfilled by Amazon New York.
    35. Tapscott, D. (1999), The Digital Economy: Promise and Peril in the Age of Networked Intelligence, Translated from English by Dubinsky, I. and Pisarev, S. (ed.), Kiev: ITN Press.
    36. Thaler, R. (1985), Mental accounting and consumer choice, Marketing Science, INFORMS, 4(3), 199-214.
    37. Tosida, E. T. , Wahyudin, I. , Andria, F. , Djatna, T. , Ningsih, W. K. , and Lestari, D. D. (2020), Business intelligence of Indonesian telematics human resource: optimization of customer and internal balanced scorecards, Journal of Southwest Jiaotong University, 55(2), Available from:
    38. Tversky, A. and Kahneman, D. (1974), Judgment under uncertainty: Heuristics and biases, Science, New Series, 185(4157), 1124-1131.
    39. Tversky, A. and Kahneman, D. (1992), Advances in prospect theory: Cumulative representation of uncertainty, Journal of Risk and Uncertainty, 5(4), 297-323.
    40. Werling, R. , Chintakrindi, S. , Clark, N. , Morris, G. , Perry, G. , and Randol, B. (2018), Citizen opinion survey: How a mid-sized california community perceives their police department, International Journal of Criminology and Sociology, 7, 239-249,
    41. Yakhneeva, I. V. , Agafonova, A. N. , Fedorenko, R. V. , Shvetsova, E. V. , and Filatova, D. V. (2020), On collaborations between software producer and customer: A kind of two-player strategic game, Advances in Intelligent Systems and Computing, 908, 570-580.
    42. Yegina, N. A. (2019), Transformation of consumer behavior models in the digital economy, Finance and Credit, 25(9), 1971-1986.
    43. Yegina, N. A. , Zemskova, E. S. , Gorin, V. A. , and Stepanova, D. I. (2019), Applying consumer behavior theory in the context of the digital transformation of the economy, International Journal of Supply Chain Management, 8(3), 341-347.
    44. Zemskova, E. S. (2019), Sharing as a reflection of consumer values in the digital economy, Scientific Journal NRU ITMO. Series: Economics and Environmental Management, 3, 17-27.