Institutional Structure of Narratives in the Economy: A Sociological Approach to Modeling Socio-Economic Systems

Tanova Anna Geraklitovna ORCID: 0000-0002-8921-3883 PhD in Sociology Associate Professor; Graduate School of Media Communications and Public Relations; Peter the Great St. Petersburg Polytechnic University 195220, Russia, Saint Petersburg, Grazhdansky ave., 28 tanova_ag@spbstu.ru Rodionov Dmitry Grigoryevich ORCID: 0000-0002-1254-0464 Doctor of Economics Professor; Director at the Graduate School of Industrial Economics; Peter the Great St. Petersburg Polytechnic University 194021, Russia, Saint Petersburg, Novorossiysk str., 50 drodionov@spbstu.ru

Dmitriev Nikolai Dmitrievich ORCID: 0000-0003-0282-1163 PhD in Economics Associate Professor at the Graduate School of Industrial Economics; Peter the Great St. Petersburg Polytechnic University Head of the Laboratory 'Modeling and Digitalization of Socio-Economic Systems'; Peter the Great St. Petersburg Polytechnic University 194021, Russia, Saint Petersburg, Novorossiysk str., 50 dmitriev_nd@spbstu.ru

introduction

Socio-economic systems have a complex structure that includes institutional norms, cultural attitudes and interrelated narratives. Institutional economics actively explores narratives as a mechanism for the formation and transformation of social institutions. The article examines the key aspects of the institutional structure of narratives in economics and their impact on the modeling of socio-economic systems through the application of a sociological approach.

Economic sociology analyzes the relationship between social and economic processes, emphasizing the social nature of economic activity, institutions and norms governing the behavior of agents. An important element of the analysis is institutional narratives as collective interpretations and social constructions that shape the perception of economic processes, influencing decision-making and the formation of long-term economic trends ^{[1; 2]}.

Socio-economic systems are characterized by high complexity and dynamics, which is associated with the influence of many factors, among which institutional narratives occupy a significant place. These narratives, being collective interpretations, shape the perception of economic processes and the behavior of agents. Robert Schiller, a Nobel Prize winner, argues that "viral popular narratives that motivate people to make economic decisions require careful study, and their life cycle should be the subject of analysis" ^[3].

Considering the concept of narrative economics, R. Shiller ^[4] identifies social constructions as tools for influencing economic behavior through ideas and interpretations. Within the framework of economic sociology, the emphasis is on institutional mechanisms that consolidate and reproduce narratives in the economic environment. For example, institutional narratives create agents' expectations, legitimize economic practices and form stable models of interaction in the social system ^[5].

The integration of the sociological approach into the modeling of socio-economic systems provides an opportunity to explore them not as a set of rational solutions, but as complex structures formed under the influence of social norms, collective representations and cultural contexts ^[6]. The importance of this approach increases in the context of digitalization, accelerating the spread of narratives and changing the landscape of economic interactions ^{[7; 8]}.

The purpose of the article is to study the institutional structure of narratives from the perspective of economic sociology and to form approaches to their modeling. Tasks include: analyzing the role of narratives in institutional dynamics, their influence on agent behavior, and integrating methodological and instrumental approaches into modeling complex systems.

Based on an in-depth study of the role of institutional narratives in the formation of socio-economic structures and mechanisms of their functioning, the scientific novelty of the work has been formed, which consists in applying a sociological approach to modeling economic systems.

LITERATURE REVIEW

1. Institutional narratives in economic sociology

Economic sociology focuses on the study of institutional mechanisms that determine economic behavior and the dynamics of social processes. One of the key works in this direction is the study by P. Berger and T. Lukman, where institutional structures are described as the result of collective construction through linguistic and narrative practices ^[5]. Such constructions consolidate behavioral norms, form expectations and guide the actions of economic agents.

The analysis of institutional narratives is becoming a central topic in economic sociology. The concept of "embeddedness", proposed by M. Granovetter, emphasizes that economic activity is rooted in social ties and relationships. This makes the study of institutional narratives important for analyzing the social nature of economic behavior ^[2].

Recent research has focused on the role of narratives in the transformation and reproduction of economic institutions. For example, V.V. Volchik emphasizes that narratives are an important source of knowledge about the mechanisms of functioning of institutions and their impact on the reproduction of social order ^{[9; 10]}. The analysis of institutional narratives makes it possible to detail the processes of formation of various models of interaction in society, taking into account social and economic conditions. Research also demonstrates that narratives serve as a structuring mechanism for repetitive social practices. The works focus on the interrelation of ideas, institutions and narratives, emphasizing their importance in the processes of institutional reproduction and adaptation to changing social and economic conditions.

2. Narrative economy and its development

The concept of narrative economics has become the object of intensive scientific research thanks to the works of R. Shiller, who highlights the influence of "viral" narratives on decision-making processes, the formation of collective expectations and behavioral models of economic agents ^[3]. The importance of this approach increases in the era of digitalization, when the acceleration of information dissemination increases the impact of narratives on the socio-economic environment.

An important contribution to the development of narrative economics was the work of A. Akerlof and R. Cranton, who explore the relationship between narratives and identity. Their works demonstrate how narratives influence the self-perception of economic agents and their participation in economic activity, including issues of formation of social capital and integration into economic systems ^[11].

Research over the past decade has also drawn attention to the importance of narratives for economic development. The article ^[12] focuses on the role of ideological constructions and symbolic elements in the transformation of national economic systems. Approaches to the integration of innovative ideas that contribute to the modernization of the economic environment are considered. The study suggests promising directions for the formation of a sustainable model of economic growth based on the effective use of narrative strategies.

3. Methods of analyzing narratives in sociological and economic research

Narrative research methods in economic sociology and narrative economics continue to develop actively, demonstrating high potential for studying complex social and economic processes. P. Bourdieu made a significant contribution to the study of narratives, highlighting the importance of symbolic capital in the formation of social fields and structures ^[6]. His approach emphasizes the role of narratives in legitimizing and reproducing economic actions, offering perspectives on their analysis through the prism of power and symbolic dominance.

Among the modern trends, the integration of digital technologies into the analysis of narratives stands out. For example, V. L. Tambovtsev and his colleagues in the article ^[13] demonstrate the compatibility of narrative analysis with quantitative tools. This approach reflects the tendency to integrate social factors into the study of decision-making processes at both micro and macro levels. The increasing use of big data and computing tools has contributed to the emergence of large-scale textual sources as an empirical base for sociological research. A. Makanovich's work ^[14] emphasizes that methods of semantic and network analysis, dictionary models, and machine learning algorithms make it possible to identify, interpret, and evaluate the impact of narratives on economic systems. These tools are used in management analytics.

A number of publications focus on the development of hybrid models for modeling socio-economic and sociotechnical systems ^[15]. Such models combine different approaches to simulation modeling, providing a multidimensional view of the phenomena under study. Their use has been observed in healthcare, marketing, environmental research, industry, and production system management, emphasizing the versatility and adaptability of this approach. In addition, research in the field of economic stability ^[16] offers two methods of analysis: equilibrium and ecosystem. Economic stability is interpreted as the ability of a system to recover from various shocks due to its internal adaptive characteristics. The method of decomposition of macroeconomic indicators allows us to identify predefined and adaptive factors that affect the stability of the economic system.

4. Modeling of socio-economic systems

Modeling of socio-economic systems is a methodological approach to studying the dynamics of complex social and economic processes. It is used to predict development, analyze structural changes, and develop resource management strategies.

The study ^[17] describes methods for modeling the development of socio-economic systems. The tasks of creating adaptive planning tools focused on the search for strategic directions of regional development are indicated. In an unstable socio-political situation and high differentiation of the quality of life, modeling is designed to provide new approaches to managing regional resources using cloud computing, artificial intelligence and big data analysis. The study ^[18] is devoted to the analysis of the impact of information capital on socio-economic indicators such as employment, poverty, migration, education and GRP. The obtained conceptual models are based on regression dependencies, allowing us to identify the links between information capital and the parameters of economic development.

The research on institutional rent conducted in ^[19] suggests approaches to classifying rental relations as a socio-economic category. They focus on the institutional component of rent, which makes it possible to analyze its role in the allocation of resources and the formation of economic systems. Thus, the work ^[20] explores the institutional potential as a factor of socio-economic development. The authors consider the impact of the institutional environment on the development and adaptation of economic systems to external challenges.

The theory of narrative economics focuses on the influence of "contagious stories" on economic decision-making. Narratives form collective expectations and behavioral models, which allows us to consider them as a tool for managing economic systems ^[21]. In particular, it is possible to use text analysis in the modeling process. The article ^[22] proposes a method of computational text analysis for the study of narrative economics. Such tools are based on quantifying the popularity of narratives (for example, the frequency of keywords) in order to assess their impact on economic processes.

The paper ^[23] explores the interaction of narratives with market dynamics through an agent-oriented platform. Using adaptive investor strategies and models of nonlinear opinion dynamics, the authors analyzed the impact of narratives on the behavior of market participants. The results showed that even neutral narratives can change the overall market dynamics. The method demonstrates the promise of an agent-based approach for modeling the impact of narratives on financial markets. The article ^[24] examines the semantic analysis of uncertainty in narrative economics. The authors focused on measuring uncertainty through thematic analysis and semantic structures of texts. The proposed uncertainty indices correlated with key events in the global economy and allowed us to identify risk factors that correspond to discussions about the nature of uncertainty in macroeconomics. The methodology confirms the advantages of semantic analysis in comparison with probabilistic methods

The study ^[25] presents a human capital management algorithm integrating the methods of principal component analysis (PCA), cluster analysis (K-means) and linear discriminant analysis (LDA). The proposed approach highlights the structural characteristics of human capital, improving their use in management decisions. The use of such algorithms will make it possible to structure socio-economic indicators characterizing the state of human capital in order to support managerial decision-making in the field of impact on social groups.

Algorithms for modeling regional socio-economic systems, taking into account the actions of social groups, allow us to form modeling tools aimed at studying the development of regional socio-economic systems, taking into account system interconnections and dynamic variability over time, which was reflected in the work ^[26]. This approach is focused on strategic management and decision-making in the context of digitalization. The emphasis is placed on the need to take into account the interactions between the elements of the system in order to achieve management goals. It should be borne in mind that within the framework of the strategy of advanced development of the national economy, it is possible to lay down the concepts of transition from stability-oriented strategies to accelerated development strategies, which is reflected in the study ^[27]. To do this, special attention should be paid to the structural modernization and adaptation of socio-economic systems to the challenges of global dynamics.

The research review confirms the prospects of modeling socio-economic systems using narrative analysis, which contributes to an in-depth study of the mechanisms of their functioning. This approach allows us to take into account the cultural and historical features of economic activity, which leads to more accurate forecasts and improved management efficiency.

RESEARCH METHODS

The study used a comprehensive methodological and instrumental approach, including mathematical modeling, quantitative and qualitative analysis to study the institutional structure of narratives in socio-economic systems. The approach was based on the adaptation of epidemiological models, such as SIR (Susceptible-Infected-Recovered), to describe the processes of formation, spread and extinction of institutional narratives, which made it possible to integrate social, economic and political factors into a single analytical system. The model took into account the stages of the life cycle of narratives (origin, spread, saturation, extinction), allowing to formalize the key processes of their interaction with the institutional environment.

1. The mathematical basis of the analysis

A modified version of the SIRV model, represented by a system of differential equations, was used to quantify the dynamics of the distribution of narratives:

where S(t) is the proportion of those susceptible to the narrative; I(t) is the proportion of those involved; R(t) is the proportion of those who have recovered (lost interest); V(t) is the proportion of those who are immunized (immune). The parameters β(t), γ(t), and v describe, respectively, the coefficients of narrative transmission, recovery (loss of interest), and immunization. The use of time dependence parameters β(t), γ(t)) made it possible to take into account the impact of institutional changes, political instability and social movements.

2. Consideration of institutional factors

To analyze the impact of institutional changes on the spread of narratives, the institutional transformation coefficient θ(t) was introduced, defined as:

where , , are the parameters reflecting the basic level, amplitude and rate of attenuation of institutional changes; ω is the frequency of reforms; ξ is the intensity of their influence. This coefficient is integrated into the system to adjust β(t) and γ(t), which made it possible to model the impact of political reforms and economic crises.

3. The competition of narratives

To describe the interaction of competing narratives, an additional variable σ was introduced, reflecting the effect of suppression of one narrative by another:

where and is involvement in two competing narratives; σ is the coefficient of interaction between narratives, which made it possible to describe the dynamics of changing information agendas and the influence of counter–narratives.

4. Qualitative analysis and interpretation

The qualitative analysis was based on the application of methods of text analysis and content analysis of narratives, which made it possible to identify key topics and categories. In particular, natural language processing (NLP) algorithms were used for semantic analysis of text data. The use of the SIRV model in conjunction with the results of text analysis made it possible to determine the stability of narratives and their key growth points.

5. Integration of results

The obtained results were visualized using graphs of the life cycle of narratives and heat maps to display the influence of factors on various stages of their distribution. The revealed dependencies between the model parameters and external factors (political, social, economic) confirmed the hypothesis of the key role of the institutional environment in the formation and transformation of narratives. Forecasting models based on SIRV equations made it possible to assess the resilience of socio-economic systems to changes in the narrative environment.

THE RESULTS OF THE STUDY

1. Stages of the life cycle of institutional narratives

The study covers the analysis of the life cycle stages of institutional narratives, including their structural and dynamic characteristics. As part of the work, a SIRV model adapted for socio-economic analysis was applied. A detailed factor analysis of the interaction of narratives with the institutional system has been carried out.

To build the life cycle of a narrative, data was used, including statistics of media activity (frequency of mentions in social networks and news publications), text arrays from media and blogs, analytical reports from international organizations (OECD and the World Bank), as well as historical data describing similar narratives. As examples, popular narratives of 2008-2015 were selected, such as "offshore production", "the era of hyperurbanization", "the outsourcing revolution", "complete decarbonization", "carbon tax", "green urbanization", etc. These narratives were analyzed through natural language processing algorithms (NLP), which allowed to identify the stages of their life cycle (generation, propagation, saturation and extinction), as well as to evaluate the dynamics parameters.

1.1. Stages of the life cycle of narratives

1. The nascent phase. The formation of a narrative is influenced by key historical events, economic crises or social changes. At this stage, the role of media and social networks contributing to the formation of the initial information field is critical.

2. The distribution phase. The narrative coverage is actively enhanced through media, social networks and political support. The use of the SIRV model makes it possible to analyze propagation through the transmission coefficient, which reflects the effectiveness of communication.

3. Saturation phase. It is characterized by reaching the maximum level of audience engagement. At the same time, the rate of involvement slows down, and the system enters an equilibrium state, where agents are classified as involved or immunized.

4. The phase of extinction. A decrease in interest in the narrative is associated with the competition of new ideas, a decrease in audience engagement and an increase in counter-narratives. This stage is modeled through the recovery coefficients γ and immunization v.

The interpretation of the life cycle of narratives based on the analysis reveals the relationship between the stages of their evolution and the main external factors of influence (Table 1), including media, political processes and social changes.

Table 1. Stages of the narrative life cycle: Description and key factors

The graph shown in Figure 1 visualizes the dynamics of the narrative's life cycle, which demonstrates the stages of its development and mechanisms of interaction with external social and institutional factors. The interaction of media and political processes forms the basis for the transition between the stages, while social changes play the role of a catalyst in the initial and final phases. The process of extinction of one narrative is often accompanied by the emergence of a new one, which helps to maintain a constant information field. This model is applicable to predict the duration of the narrative's existence, as well as to highlight strategically significant moments of its maintenance or weakening.

Figure 1. The life cycle of the narrative

1.2. Systemic interactions in the process of formation and dissemination of narratives

Institutional changes, including legislative reforms and policy initiatives, become the starting point for creating narratives that shape changes in social norms and rules. The emergence of cultural and political narratives is initiated under the influence of factors such as reforms and crisis phenomena, which contributes to their dissemination through media and social networks. These channels act as a link between the sources of narrative and the agents of perception, which include households, businesses and individuals.

Perception agents, interpreting and adapting narratives, make decisions that determine investment strategies, consumer preferences and other forms of economic activity. The emerging economic dynamics have the opposite effect on social and economic structures, consolidating the influence of the narrative.

Globalization and localization contribute to changing economic behavior, generating effects at various levels — from microeconomic to macroeconomic processes. These effects include the adaptation of local economies and the transformation of social norms in the face of global change. The impact of such trends strengthens the relationship between local and global processes.

Figure 2 shows a diagram of interactions between institutional changes, media, perception agents and their impact on economic behavior. The scheme also reflects the roles of globalization and localization, as well as the relationship between social structures and narrative dynamics.

Figure 2. The relationship of factors and agents

The graphical representation shown in the figure systematizes the complex relationships between the elements of the socio-economic system, demonstrating the following aspects:

1. Integration of narratives into the institutional environment. Narratives act as mediators between institutional changes and economic behavior of subjects. Their dissemination through media formats contributes to legitimization and adaptation in the social environment, forming new behavioral models.

2. The influence of media and social networks. Media platforms play an important role in translating institutional changes at the micro level. They ensure the wide dissemination of narratives among households and individual agents, which enhances their perception in the mass consciousness.

3. Globalization and local transformations. The processes of globalization stimulate the adaptation of narratives in a local context. Institutional changes that have arisen at the national level become part of global processes, which leads to a modification of the social structure and transformation of economic practices.

4. Forecasting decisions and behavior. The proposed structure helps to identify the causal mechanisms that determine decision-making by subjects, which opens up prospects for analyzing economic activity in conditions of instability and crisis phenomena.

5. Reforms as initiators of changes. At the macro level, institutional reforms form the basis for the transformation of the social structure, defining long-term economic trends and ensuring interaction between institutional and economic components.

1.3. The complex structure of institutional narratives

Institutional narratives are formed under the influence of historical events and economic crises, which set the primary impetus for their development. The media, social networks and the expert community play a key role in spreading ideas. They adapt the content of narratives taking into account the specifics of target audiences, accelerating their integration into the socio-economic space.

Institutional narratives function within a multi-level system that includes the following levels:

• Macro level (state). It influences the regulatory framework, generates political support and sets guidelines for institutional transformations.

• Meso-level (companies, industries). It acts as a platform for introducing innovations and adapting narratives to the specifics of industry markets.

• Micro-level (households, individuals). It is characterized by a change in behavioral patterns, the formation of new consumer preferences and social activity

Figure 3 shows a system model reflecting the relationships between sources, distribution channels, and multi-level agents. It demonstrates the mechanism of the impact of narratives on long-term social and economic processes, as well as their adaptation to innovative challenges.

Figure 3. Multilevel structure of narratives

Narratives influence economic behavior and social change by setting long-term trends. This is confirmed by the adaptation of agents to change through innovation and revision of perception. Political, economic and sociological factors regulate the degree and speed of influence of narratives on the audience.

The analysis confirmed the influence of narratives on the behavior of economic agents and social changes:

• Political, economic and sociological factors regulate the intensity of impact and the rate of dissemination of narratives.

Narratives serve as a mediator between institutional norms and economic behavior, which is consistent with the theories of P. Bourdieu and M. Granovetter.

The main conclusions of the analysis:

1. Legitimization through institutional support. Political and social institutions contribute to the consolidation of narratives in public perception, strengthening their adaptation.

2. The dynamics of narratives and sustainable behaviors. A direct link has been revealed between the development of narratives and changes in the long-term behavioral strategies of economic agents.

3. Positive impact. Constructive narratives activate investment processes and reduce economic anxiety.

4. Negative impact. Destructive narratives increase uncertainty and reduce the level of trust in the economic environment.

The obtained results emphasize the importance of analyzing the multilevel structure of narratives in order to understand their long-term impact on social and economic processes. This approach, based on the integration of institutional analysis and theories of social change, can be used to develop strategies for managing social processes and adapting narratives to changing conditions.

2. Institutional mechanisms and their impact on the adaptation and sustainability of narratives

The use of the SIRV model for the analysis of narratives has shown that the coefficients of transmission and recovery depend on external factors: institutional reforms, economic crises and the level of social density. Economic and social narratives (ideas, beliefs, concepts) spread in society like infections. Agents who are "receptive" to new ideas become "infected" with them, "recover" (lose interest) or become "immunized" (immune to new narratives). The SIRV model can be adapted to explore how narratives encompass society.:

• S (Suspicious) – agents who are not yet familiar with the narrative.

• I (Infected) – agents actively involved in the narrative (spreading it).

• R (Recovered) – agents who have ceased to be active carriers of the idea (disappointed or forgotten).

• V (Vaccinated) – agents who are initially skeptical of the idea or have already had similar experiences and are "immune".

Figure 4 illustrates the dynamics of engagement driven by the impact of institutional changes.

Figure 4. Modified SIRV model

Immunized agents (V) represent individuals who are resistant to new narratives due to previous experiences that have led to the development of critical thinking or have taken into account the consequences (negative or beneficial) of interactions with pre-existing narratives. Political, economic and cultural institutions influence society by forming resistance to certain narratives through the introduction of counterarguments, information campaigns and awareness raising.

The introduction of the category of immunized (V) into the SIRV model structures the influence of groups with a critical attitude to narratives, and also takes into account the resistance of the audience to new information influences. The change in the time coefficients β (transmission) and γ (restoration) reflects institutional and social changes affecting the dynamics of narratives:

• Transmission coefficient (β). Depending on the effectiveness of media, social networks, educational and cultural institutions, the coefficient characterizes the intensity of the spread of the narrative. Political reforms, economic crises and information campaigns are key factors influencing its temporary changes.

• Recovery coefficient (γ). This indicator takes into account the influence of social factors, such as saturation of the audience or fatigue from information noise, which leads to a decrease in engagement. Additionally, it reflects the competition between narratives, contributing to the loss of interest among the audience.

Simulation results:

• Graph A. The change in the proportions of susceptible (S), involved (I), recovered (R) and immunized (V) agents over time reflects the key stages of the narrative life cycle. The maximum engagement is observed in the initial phase, which corresponds to the hypothesis of saturation of the audience at a certain time interval.

• Graph B. The dynamics of the transmission coefficient (β) illustrates the impact of institutional transformations on the intensity of narrative dissemination.

• Graph B. The change in the recovery coefficient (γ) under the influence of social factors demonstrates a decrease in the rate of loss of interest in the narrative with the support of social movements.

• Graph G. The ratio of involved (I) and recovered (R) agents, including the prediction of future trajectories, confirms the possibility of prolonging the relevance of the narrative under certain institutional conditions, for example, political support.

The model is used to predict the dynamics of the impact of narratives, taking into account socio-economic and institutional factors. The SIRV methodology is a universal tool for assessing the long-term effects of narratives and developing strategies for managing their spread in socio-economic systems.

The use of graphical analysis and the SIRV model allowed:

• Identify the key phases of the narrative life cycle: origin, spread, saturation and extinction.

• To develop a conceptual model that takes into account the influence of multilevel factors on the adaptation of narratives to changes in the social and economic environment.

• Formulate approaches to forecasting and managing narratives in institutional systems.

The SIRV model demonstrates the importance of individual and collective behavior for the dissemination of narratives, which is especially relevant for the analysis of socio-economic systems. The change in transmission coefficients (β) and recovery coefficients (γ) may be related to institutional transformations, changes in the media context, or the consequences of economic crises.

The competition of narratives in the real economy is a complex process involving the interaction, replacement and mutual reinforcement of various narratives. The expansion of the SIRV model to analyze several competing narratives opens up prospects for studying their interactions and effects on socio-economic systems.

Thus, the SIRV model formalizes the study of the influence of institutional and social factors on the spread of narratives, their adaptation and long-term dynamics in the socio-economic environment.

Parameterization of factors through time dependencies allows the use of time functions for modeling institutional and social impacts. The use of a logarithmic scale focuses on exponential trends characteristic of the processes of propagation, engagement and recovery, which allows us to analyze the early stages of dynamics and asymptotic behavior. Figure 5 presents a logarithmic interpretation of the dynamics of four categories of agents in a population. A modified SIRV model is used, taking into account institutional and social factors, as well as immunization processes. The results are presented in table 2.

Figure 5. Logarithmic dynamics of narratives in the SIRV model with immunization and institutional factors

The graph illustrates the patterns of narrative propagation within the SIRV model. Taking into account the influence of institutional factors, the model demonstrates: the effect of rapid saturation of engagement at the initial stages; gradual restoration of interest, accompanied by resistance to re-engagement; the potential of using the model to predict the behavior of social groups in the context of changes in the political and economic environment.

Table 2. Dynamics of agent categories and the influence of institutional and social factors

Institutional factors include actions by government, corporate, and regulatory agencies that have a direct impact on the dissemination, support, or extinction of the narrative. Social factors encompass cultural, societal, and communication aspects, including the role of media, social networks, traditions, and group behavior.

3. Institutional mechanisms of influence on the life cycle of narratives

The analysis revealed the distribution of the power of influence of social, economic, political and technological factors on the stages of the life cycle of narratives (origin, spread, saturation, extinction). The logic of the study:

1. Stages of the life cycle of narratives:

• The origin. At the stage of narrative formation, social and technological factors are of the greatest importance. Social networks, digital media and other communication platforms create the infrastructure for the emergence and initial dissemination of ideas.

• Distribution. At the stage of active audience involvement, social factors continue to prevail, while the political impact becomes critical. Institutional support (or suppression) through legislative initiatives, reforms, or censorship mechanisms significantly affects audience reach.

• Saturation. At the stage of maximum audience coverage, economic factors begin to play a key role. The resource base, including financing, infrastructure, and economic incentives, supports or limits the further spread of the narrative.

• Fading away. The final stage is characterized by the dominance of political and economic factors. Limited resources, a change in institutional priorities, or a decrease in political support lead to a gradual decrease in interest in the narrative and the end of its life cycle.

2. Dynamics of the distribution of factors:

• Social factors dominate the initial stages, supporting the formation and dissemination of the narrative. However, their importance is gradually decreasing towards the stage of extinction.

• Economic factors achieve the greatest impact at the saturation stage, when resources determine the possibility of continuing the narrative, and retain their impact at the extinction stage.

• Political factors have a stable influence at all stages, providing support or suppression of narratives through institutional mechanisms.

• Technological factors are most significant at the stage of origin, but by the stage of extinction their impact becomes minimal.

The presented model and heat map (Figure 6) make it possible to formalize institutional mechanisms for influencing narratives and identify points for strategic intervention. This approach is applicable for managing the dynamics of narratives in socio-economic systems and predicting their transformation under the influence of external factors.

Figure 6. Heat map of the influence of institutional factors on the stages of the life cycle of narratives

Environmental initiatives, such as the concept of a "green economy", demonstrate the described dynamics. Social movements and technological platforms form the basis for the emergence of a narrative. Political support in the form of the introduction of environmental standards stimulates its dissemination. At the saturation stage, economic resources, including subsidies and grants, determine the duration of the life cycle. The fading of the narrative may be due to a change in the political agenda or a reduction in funding.

An example of the spread of narratives within the framework of the concept under consideration is the development of "mainstream" trends in economics that form dominant interpretations of economic processes and influence decision-making. Robert Shiller in ^[3] notes that popular narratives spread like viruses, exerting a significant influence on the behavior of economic agents, creating a basis for long-term economic trends.

One of these trends is the popularization of the ideas of sustainable development and environmental responsibility, which has transformed corporate strategies, public policy and consumer preferences. This narrative can be considered through four key stages of its life cycle proposed within the framework of the model ^{[28; 29; 30]}:

1. The stage of origin. The sustainable development narrative has been shaped by international initiatives such as the Paris Climate Agreement, as well as through the activities of non-governmental organizations. The main trigger was the goals to reduce the carbon footprint and increase environmental responsibility, which created the basis for the formation of a new global consensus.

2. The distribution stage. Increased attention to the environmental agenda was provided through international conferences (for example, COP28), media and social media activities. Corporations have begun to actively implement the ESG concept, including the promotion of environmental innovations, the development of sustainable technologies and corporate social responsibility strategies.

3. Saturation stage. The peak of the spread of the narrative occurred in 2018-2021, when "green" practices, such as the transition to renewable energy sources, the use of recycled materials and increased investment in environmental projects, became widespread. An example is the multibillion-dollar investments in renewable energy in the EU, the USA and China, as well as the development of national sustainable development strategies.

4. The stage of extinction. In recent years, interest in the sustainable development narrative has begun to decline, which is associated with increased counter-narratives focusing on the high costs of transition to a "green" economy, as well as global challenges such as the COVID-19 pandemic, geopolitical instability and economic crises. Under the current conditions, countries and corporations are focusing on issues of energy security, digitalization and adaptation to crisis conditions, which leads to a partial shift of attention from sustainable development.

The presented example highlights the relationship between the stages of the narrative's life cycle, institutional and social factors that determine its spread. The analysis suggests that the development of narratives is due to a combination of support at the institutional level and the perception of their value by society.

In addition, the analysis of the institutional stability of narratives corresponds to the conclusions of V.V. Volchik ^{[9; 12]}, who emphasizes the role of ideas and symbols in the reproduction of economic institutions. Also, the use of quantitative methods in the study of complex socio-economic systems to identify key stages of the life cycle correlates with the approaches proposed by V. Tambovtsev and colleagues ^[13].

conclusion

The study of the institutional structure of narratives has confirmed their importance in the formation and transformation of socio-economic systems. Narratives are integral elements that influence institutional norms, collective expectations, and the behavior of economic agents. The scientific novelty of the work lies in the elaboration of approaches to the integration of narrative factors into the modeling process, which creates the basis for forecasting and managing complex socio-economic systems in the context of digitalization and global transformations.

The use of the SIRV model has made it possible to formalize the life cycle of narratives, including their origin, spread, saturation and extinction, where political and economic determinants prevail. The analysis revealed that the dynamics of narratives is determined by the interaction of social, economic, political and technological factors that have a different impact at each stage. The use of modified epidemiological models has made it possible to describe the spread of narratives as a nonlinear process depending on the institutional environment and information mechanisms

The approach presented in the study ensures the integration of narrative factors into the management of social processes, including forecasting their impact on long-term economic and social trends. The developed methods and approaches can be used for strategic management of institutional transformations, the development of effective policies and increasing the adaptability of socio-economic systems to changes in the external environment.

The results obtained can be used in strategic management to predict the impact of institutional narratives on economic and social trends, as well as in policy and regulation, where they can contribute to the development of effective initiatives to manage public opinion and maintain key narratives to stabilize the institutional environment. In the field of corporate governance, the results will be applied in the development of communication strategies that take into account the influence of narratives on consumer behavior and market trends. In the scientific environment, the findings can become the basis for the formation of new analytical models that integrate social and economic aspects into the analysis of institutional changes.