Changing Societies & Personalities, 2025 Vol. 9, No. 1, pp. 242–274 https://doi.org/10.15826/csp.2025.9.1.326 Received 5 December 2023 Accepted 7 March 2025 Published online 30 April 2025 ARTICLE Cultural Dynamics in Social Commerce: An In-Depth Analysis of Consumer Behavior and Interaction Patterns Fatemeh Nouri Dehnavi Shanghai University, Shanghai, P.R. China Negar Sioofy Khoojine Middle East Technical University, Ankara, Türkiye ABSTRACT This study analyzes the cultural dynamics that shape consumer behavior in the context of social commerce in the Iranian capital of Tehran. Our sociological investigation examines the influence of norms, values, and cultural perceptions on social media interactions on platforms such as Instagram1, Telegram, and internal networks like Soroush and Beel. Using factor analysis and multiple linear regression, we examine the relationships between ten key variables, revealing three main factors—the link of cultural perception, the set of transaction dynamics, and the quadruple of market values—that are primarily responsible for creating the complex interactions between culture and social business behaviors in this context. The findings suggest that cultural attitudes significantly influence consumers’ perceptions of technology, trust in online platforms, and their purchase decisions. Furthermore, cultural values related to product quality, sustainability, and ethical consumption play an important role in shaping consumer expectations and business strategies. Drawing on Baudrillard’s theory of consumption, this study shows that consumer behavior in social commerce goes beyond functional needs, such that purchase decisions are increasingly linked to identity formation 1 Instagram™ is a trademark of Instagram Inc., registered in the U.S. and other countries. По решению Роскомнадзора, социальная сеть Instagram полностью заблокирована в России как экстремистская организация. © 2025 Fatemeh Nouri Dehnavi, Negar Sioofy Khoojine FatemehNouri@t.shu.edu.cn Negar.Khoojine@metu.edu.tr https://changing-sp.com/ mailto:FatemehNouri@t.shu.edu.cn Changing Societies & Personalities, 2025, Vol. 9, No. 1, pp. 242–274 243 We would like to express our sincere gratitude to Professor Wang Xiaoming, Shanghai University, for his invaluable guidance, insightful feedback, and continuous support throughout this research. Introduction Consumption is a vital process by which people acquire goods and services to satisfy their needs and wants (Griffiths, 2018), as well as a social concept. Together with individual preferences, patterns of consumption are influenced by social, cultural, and economic factors (Belolipetskaya et al., 2020). In recent times, consumption patterns have undergone significant changes as digital technologies continue to revolutionize people’s online connections through which they purchase goods and services. As a result, e-commerce has become the primary method of conducting commercial transactions (T. Wu & Shao, 2022). This occurrence has become a major force behind the shift in consumption patterns. Given that consumerism is an essential aspect of human life that shapes behavior and contributes to social identity, scholars have examined consumer behavior from sociological, economic, and cultural perspectives (Boström, 2020). Modern society heavily relies on consumption for survival, but it is also influenced by a plethora of elements, such as global advertising and media. The sociology of consumption continues to grow, expanding to include topics related to economic issues; consumer feelings, values, thoughts, behaviors, and identities; and social concepts (Shah & Asghar, 2023; Warde, 2015; Yin et al., 2021). Effects of Technological Advances on the Online Market and Consumerism Social commerce driven by technological advancements has drastically changed the way people buy and sell online, with social networking platforms playing a vital role in this transformation (Brahma & Dutta, 2020). Social commerce as a trend originating from these platforms has had a significant impact on people’s lives by boosting interaction, improving access to goods and services, and introducing a greater variety of products at competitive prices. The upsurge of e-commerce has similarly and social differentiation. We conclude with recommendations for adapting business strategies to align with cultural preferences, as well as suggestions for future research focused on technological developments and cross-cultural comparisons in social business. KEYWORDS social commerce, consumerism, social media, consumer behavior, Iranian consumer society, Cultural Perception Nexus, Transaction Dynamics Ensemble, Marketplace Values Quartet ACKNOWLEDGMENT https://changing-sp.com/ 244 Fatemeh Nouri Dehnavi, Negar Sioofy Khoojine contributed to the growth in consumerism, brand reliance, and concerns surrounding luxury (Algharabat & Rana, 2021). Online shopping dates back to the mid-1990s, propelled forward with the appearance of marketplaces like Amazon2 and eBay3. Since then, social commerce has experienced exponential growth, offering producers, vendors, and consumers many rewards previously inaccessible through traditional e-commerce models. This has moved e-commerce beyond direct sales into social media-driven interactions and Web 2.0 technologies, revolutionizing commerce altogether. Social Commerce was created by Yahoo4 in 2005 and denotes a collaborative online shopping toolkit (C. Wang & Zhang, 2012). Social commerce utilizes various social media and technologies, such as blockchain, to facilitate the exchange of goods and services between buyers and sellers (Mendoza-Tello et al., 2018; Shorman et al., 2019). The purpose is to shape consumption behavior by building cross-cultural interchange and consumer social identities through shared shopping experiences, which then influence future purchase choices (Busalim et al., 2024). Social media platforms have become essential tools for the purchasing and selling processes of individuals and businesses alike. Businesses use these platforms to extend their customer reach and promote offerings, while consumers use them for inquiry before making well-informed purchase decisions (Lim & Rasul, 2022). This has significant societal implications as producers strive to offer diverse advertisements and exclusive marketing to achieve their objectives and interests, which encourages and persuades customers to purchase more. As a result, consumers are exposed to a wide variety of products and services, providing them with a broader range of consumption options. The sociological consequences of this transformation and the rapid spread of consumer culture are extensive and intricate (Dwivedi et al., 2021). Social Commerce and Increased Consumption: From Targeted Advertising to Changing Consumer Behavior According to neoliberal frameworks, consumption is essential to promoting economic growth and social progress (Ignjatović & Filipović, 2022). Nevertheless, while an increase in consumption levels can indicate economic developments and changes in a society, it can also cause the emergence of a complex social phenomenon of consumerism that raises concerns about irrational and unsustainable spending patterns (Panizzut et al., 2021). The explosion of online shopping platforms and e-commerce activities has fueled an increase in impulsive and irrational spending behaviors. In my opinion, the notion that consumption has overtaken production and identity as the main drivers shaping the order of contemporary society is compelling, especially given the influence of social commerce platforms. They have described consumption as a substitute for production, such that identity is a key factor in shaping the order of the late age, as evidenced by the emergence of social commerce and the 2 https://www.amazon.com 3 https://www.ebay.com 4 https://www.yahoo.com https://www.amazon.com https://www.ebay.com https://www.yahoo.com Changing Societies & Personalities, 2025, Vol. 9, No. 1, pp. 242–274 245 new ways it provides for businesses to reach potential customers through targeted advertising and appropriate recommendations. Thanks to social media, today’s consumers have unprecedented access to information about products and services, significantly influencing their purchasing patterns and decision-making processes. Social commerce offers faster, easier, and more accessible ways to acquire goods and services, thereby accelerating consumption rates (Dwivedi et al., 2021). Social commerce combines social media and e-commerce to both attract customers and promote sales and services while changing consumer consumption patterns. Cultural and societal forces have significantly altered customer interactions and relationships, leading to novel forms of consumption. Social commerce has made online shopping more engaging, convenient, and social by enabling consumers to communicate directly with sellers, share experiences with other consumers, offer recommendations, and obtain discounts on products advertised by merchants (Y. Wu et al., 2022), ultimately making consumer purchasing decisions more informed and at the same time prompting impulse buying behavior. Research Questions In recent years, social commerce has also influenced consumer behavior in urban areas like Tehran, where social media and online shopping intersect. As consumers increasingly use platforms such as Instagram5, Telegram6, and local networks like Soroush7 and Bale8, new patterns of interaction, trust, and decision-making emerge. Our first research question—How do the dynamics of social commerce influence consumer behavior in Tehran?—examines how social media affects traditional consumption and interaction. The study also aims to identify key components of social commerce, focusing on the relationships between cultural perceptions, transaction dynamics, and market values, leading to the second question: How do we analyze the key components of social commerce and their interrelationships? This seeks to understand how these elements interact and impact consumer behavior. Finally, we will investigate the role of culture in shaping consumer behavior within social commerce, with the third question: How does culture influence consumer behavior, and how can business strategies enhance interaction and satisfaction? This explores how cultural factors affect consumer behavior and identifies strategies for improving customer engagement in the social commerce landscape. Briefly, here is an overview of the structure of this paper: in the introduction, we have raised research questions in the context of discussions on consumption and social commerce. In the literature review, we first review the key theories of social sciences related to consumption and previous studies on the topic. The methodology 5 Instagram™ is a trademark of Instagram Inc., registered in the U.S. and other countries. По решению Роскомнадзора, социальная сеть Instagram полностью заблокирована в России как экстремистская организация. 6 Telegram™ is a trademark of Telegram Group Inc., its operational center is based in Dubai, the United Arab Emirates. 7 https://soroushplus.com 8 https://web.bale.ai https://changing-sp.com/ https://soroushplus.com https://web.bale.ai 246 Fatemeh Nouri Dehnavi, Negar Sioofy Khoojine section covers demographic information, questionnaire design, and analytical techniques. My analysis of the findings includes data descriptions, factor analysis results, and factor relationships. The discussion interprets the identified factors related to consumer behavior. Finally, my conclusion summarizes key findings, study limitations, and suggestions for future research. Literature Review Sociological Theories in the Field of Consumption Sociological theorists have addressed the issue of consumption and consumer behavior. George Ritzer believes that there is no middle view of the topic of consumption, such that most theorists have either had negative opinions about this topic or they have examined the topic of consumption in a completely positive way (Ritzer & Smart, 2001). Among early sociologists, Karl Marx’s theory of capitalism value criticizes consumerism and consumption (Macat Team, 2017). Thorstein Veblen’s ostentatious consumption theory deals with the motivations of consumer behavior and the cultural and social factors of the consumer (Veblen, 1899/1992). The book The Production of Space examined the subjects of consumerism and consumption behavior via the theory of “Space Production and Consumption” (Lefebvre, 1991). More recently, Marshall McLuhan has paid special attention to the influence of media on culture and social behavior in the theory “The medium is the message” (McLuhan, 2008). American sociologist George Ritzer, who became famous for presenting the McDonaldization theory, has shown the influence of fast-food culture on consumption patterns and social structure in this theory (Ritzer & Miles, 2019). Sociologists such as Susan Blumler or Juliet Schor are also considered pioneers in this field (Hamermesh, 1993; Neuman, 2010). This article will primarily draw from the theories of Jean Baudrillard, whose early research focuses on the field of consumption (Baudrillard, 1998), with special attention to issues of consumer behavior, media, and culture. In particular, he theorized the concepts of symbolic consumption (Baudrillard, 1998, 2001), simulacra and simulation, and hyperreality (Baudrillard, 2008), which we will use to analyze interaction patterns in social business. In his theory of symbolic consumption, Baudrillard states that the consumption of goods and services by people is not to satisfy their material needs; rather, it is a tool for the symbolic representation of identity, an expression of social status and cultural differences, as well as an expression of the values or beliefs of the consumer (Whalen, 1991). In this type of consumption, purchased goods act as signs or symbols through which people display their values, beliefs, and social affiliations to establish their social position through consumption. With the emergence of social media, more aspects of symbolic consumption have come to the fore. Social networking platforms like Instagram9 and TikTok10 represent virtual showcases for real people to present 9 Instagram™ is a trademark of Instagram Inc., registered in the U.S. and other countries. По решению Роскомнадзора, социальная сеть Instagram полностью заблокирована в России как экстремистская организация. 10 ТikTok is a trademark of ByteDance, registered in China and other countries. TikTok has suspended all new posting and live-streaming for users in the Russian Federation. Changing Societies & Personalities, 2025, Vol. 9, No. 1, pp. 242–274 247 their ideal virtual version of themselves with their assets, knowledge, experiences, and overall lifestyle (Ham et al., 2024). In the field of social commerce, especially in Tehran, consumers are not exempt from this rule, and they are also trying to find a way to express themselves by choosing or interacting with special products and special brands, going to luxury places, and making aimless and unnecessary purchases to express their social and economic position—ultimately, their fictional and symbolic identities (Horng & Wu, 2020). Another key concept from Baudrillard’s work is simulacra and simulation. In this theory, he analyzes how virtual space in modern media and technology has changed our perceptions of reality, or “real life,” replacing the world with virtual life. That is, in postmodern societies, signs and symbols have been separated from their real source, and simulated signs and symbols have replaced authentic realities (Essien, 2024). Baudrillard asserts that in this simulated space, values, symbols, experiences, and, in general, the identities of consumers are not based on physical realities; rather, they are based on images and virtual representations—what he calls hyperreality. In the digital age and with the emergence of social commerce, it is increasingly likely that people’s consumption is based on simulacra and simulation, as processes, goods, and services are represented in a symbolic and visual way that does not correspond to their real life. The emergence of colorful famous brands, the presentation of attractive and stylish images of products, the use of Photoshop11 and manipulated images, constant advertising in social networks, celebrities featuring in advertisements, the introduction of goods and services, providing positive feedback of the product, and so on. This obscures the quality and even the appearance of goods or services, putting consumers in a simulated environment; therefore, people’s shopping experiences and social interactions are not based on their real needs but rather based on symbolic representations (Lavoye et al., 2023). If this process is examined more carefully, we notice that these simulations in social business have not only influenced the way consumers choose and consume but also shaped their behaviors, feedback, and expectations about future purchases and spending. Hence, examining the facts and simulating and finding things that are out of the realm of reality and joined to meta-reality can effectively help in the analysis of consumer behavior and the analysis of interaction patterns in social business, and it enables researchers to gain a deeper understanding of the dynamics of social business and its cultural and social impacts. Existing Research on Cultural Dynamics in Social Commerce To understand the cultural dynamics in social commerce, this section examines existing studies on how cultural interaction impacts consumer behavior and marketing strategies in online environments. In particular, we aim to gain a deeper understanding of how digital cultures are formed and evolve, how these cultures influence purchasing decisions, and the challenges associated with managing culture within the social commerce space. 11 Photoshop ™ is a trademark of Adobe Systems Inc., registered in the U.S. and other countries. https://www.adobe.com/products/photoshop.html https://changing-sp.com/ 248 Fatemeh Nouri Dehnavi, Negar Sioofy Khoojine Zhang et al.’s research explores the influence of mood and social presence on consumer purchase behavior in consumer-to-consumer (C2C) e-commerce, with a study involving 200 participants in China. The study found that mood plays a significant role in consumer purchase behavior, impacting perceived benefit and purchase intention (Zhang et al., 2012). Similarly, Chen et al. studied how integrating social media plugins into e-commerce websites affected online consumer behavior; their research showed a positive impact on consumer purchase intention (Chen et al., 2013). Jain (2014) investigates the impact of social commerce on consumer behavior, specifically focusing on Facebook12 commerce (F-commerce). This research highlights the combined impact of two significant digital trends: e-commerce and social media (Jain, 2014). Kim et al. (2014) discuss the need for companies to address service failure cases in social commerce that cause expansive consumer damage. Their survey of 300 active social commerce users who have experienced at least one service failure showed that consumers blame failed incidents on social commerce companies and merchants (Kim et al., 2014). Hajli (2013) examines the “emergent imperative” of social commerce, which enables consumers to generate active web content and engage commercially with providers through social networking systems. Their study focuses on adoption behavior through the technology acceptance model, social commerce constructs, and trust (Hajli, 2013). Utilizing social influence theory, which posits that peers can change a consumer’s behavior along two dimensions, informational and normative, Hu et al. (2019) investigate one consumer behavior that could generate considerable economic value: impulsive purchase behavior. Huang & Huo (2021) analyze the behavior interaction and strategy selection mechanism between a merchant’s choice of opinion leader, product recommendation, and consumer’s purchase decision via evolutionary game theory. Similarly, Wang unravels the role of digital influencers in consumer engagement and purchase behavior in online social commerce communities, finding that several forms of social power from digital influencers could influence consumer’s purchase expenditure in the social commerce community (P. Wang & Huang, 2023). Singh et al. (2023) highlight the need for research on the relationship between consumer value, risk, and trust in the context of social cross-platform perceptions in the context of India. This research focuses on the rise of social cross-platform buying behavior in India and examines the influence of perceived risk, perceived value, trust, and marked negative reporting on consumer behavior (Singh et al., 2023). Numerous studies have contributed to the understanding of diverse facets of consumer behavior in social commerce (Algharabat & Rana, 2021; Busalim et al., 2024; Xiang et al., 2022). A discernible void still exists in the literature on the cultural dimensions of consumer behavior. Prior investigations have explored themes such as social presence, service failure, technology acceptance, and the impact of digital influencers across various contexts. However, these studies have not extensively 12 Facebook™ is a trademark of Facebook Inc., registered in the U.S. and other countries. По решению Роскомнадзора, социальная сеть Facebook в России признана экстремистской организацией и заблокирована Changing Societies & Personalities, 2025, Vol. 9, No. 1, pp. 242–274 249 delved into the intricate ways in which cultural norms and values may exert influence on these behaviors. Munther M. Habib analyzes Jean Baudrillard’s theories on culture and consumerism from a postmodern viewpoint, with particular emphasis on the significance of Simulacra and Simulation; he concludes that the postmodern society has addressed and deconstructed various aspects of human life in a significant manner (Habib, 2018) Despite the contributions of existing research to understanding various aspects of consumer behavior in social commerce—including the impact of mood, social plugins, service failures, and the role of digital influencers—a significant gap remains regarding the cultural dimensions of these behaviors. Current studies have not adequately addressed how cultural norms and values influence consumer interactions and decision-making processes within the social commerce domain. Therefore, this research aims to bridge this gap by examining the cultural impacts on consumer behavior and integrating theoretical frameworks to provide a more comprehensive analysis of cultural influences in the context of globalized social commerce. Study Objectives Despite the popularity of social commerce among social media users, further research is needed to explore its sociological relationship with consumption. This paper contributes to the literature by focusing on the cultural aspects of social commerce and their impacts on consumer behavior in Tehran. Specifically, we examine how the blend of digital commerce and social interaction influences Iranian purchasing decisions, contributing to broader discussions on social commerce in various cultures. Utilizing a survey-based method, the study gathers empirical data to reveal preferences, behaviors, and cultural factors that shape consumer dynamics. Additionally, the research identifies key components of social commerce—such as cultural perceptions, transaction dynamics, and market values—and highlights culture’s role in shaping consumer behavior and business strategies. The findings reveal how cultural values affect customer service, product discovery, and ethical consumption, informing businesses on improving engagement and satisfaction. The paper’s objectives are as follows: 1. Examine the dynamics of social commerce and its impact on consumer behavior in Tehran. 2. Identify and analyze key components of social commerce, such as customer service systems and purchasing trends. 3. Explore the influence of culture on consumer behavior and its implications for business strategies. Methodology Participant Selection and Demographics The research methodology investigates the intersection of consumption and social commerce from a sociological viewpoint, with particular attention paid to how social commerce influences cultural consumer behavior patterns. We selected a survey- based approach for this project, which randomly sampled 400 men and women from https://changing-sp.com/ 250 Fatemeh Nouri Dehnavi, Negar Sioofy Khoojine the Iranian capital of Tehran; their demographic composition included individuals of diverse ages, genders, geographical locations, cultures, socioeconomic backgrounds, and social statuses. Survey and Data Collection Tool Data was gathered via an online survey conducted from June 1, 2023, to July 30, 2023. We posted the survey to various social media platforms such as Instagram13, Telegram, Soroush, Eitaa14, and Bale. The survey questionnaire consisted of closed- ended questions intended to examine how social media networks and commerce affect sociocultural implications. A stratified sampling strategy was utilized based on age, gender, education level, income levels, and residential location of participants. Individuals were randomly chosen from both urban and suburban regions in Tehran, thus encompassing a comprehensive array of relevant experiences and opinions pertinent to the study’s objectives. The acquired data was electronically entered into a tailored Persian-language survey platform and subsequently analyzed using IBM-SPSS 27 statistical software. Descriptive statistics were used to establish a baseline by extracting information on respondents’ age, income, education level, and gender. Questionnaire Design This study delves into the intricate influence of cultural aspects on human behavior, particularly within the realm of prominent social media platforms, with a specific focus on social commerce. Ten carefully selected variables serve as the foundation of this study, each of which we thoroughly examine through a series of tailored questions. Below we provide a comprehensive understanding of each variable: 1. Perception of Social Media Commerce (PSMC). Cultural attitudes towards technology, trust in online platforms, and the perception of social interactions can shape how individuals view social media commerce. For example, some cultures place a greater emphasis on face-to-face transactions, while others may embrace the convenience of online platforms. 2. Customer Service and Payment Systems (CSPS). Cultural preferences for communication styles and payment methods can influence customer service expectations—such as a preference for formal communication, and specific payment systems may be more widely accepted or trusted. 3. Product Discovery and Social Sharing (PDSS). Cultural values, such as collectivism or individualism, can impact the tendency to share product discoveries. In some cultures, individuals might be more inclined to share products that align with communal values or personal preferences. 4. Consumer Seller Interaction (CSI). Cultural norms regarding politeness, negotiation, and expectations in buyer- seller relationships can influence interactions on social media. In high-context 13 Instagram™ is a trademark of Instagram Inc., registered in the U.S. and other countries. По решению Роскомнадзора, социальная сеть Instagram полностью заблокирована в России как экстремистская организация. 14 https://web.eitaa.com Changing Societies & Personalities, 2025, Vol. 9, No. 1, pp. 242–274 251 cultures, where communication is more implicit, interactions might be nuanced compared to low-context cultures. 5. Influence of Social Proof and Advertising (ISPA). Cultural aesthetics, values, and collective decision-making can affect how social proof and advertising resonate. Certain symbols or appeals may be more effective in specific cultures, and the importance of social validation can vary. 6. Product Quality and Satisfaction (PQS). Cultural expectations regarding quality, durability, and aesthetics can impact satisfaction levels. For instance, cultures that strongly emphasize craftsmanship may prioritize product quality differently than those that prioritize functionality. 7. Impulse Purchases and Spending Habits (IPSH). Cultural attitudes towards consumption, savings, and impulsivity can shape spending habits. In some cultures, there may be a tendency to make more impulsive purchases, while others may emphasize thoughtful consideration before buying. 8. Price Comparison (PC). Cultural attitudes towards haggling, bargaining, and perceptions of value can affect the importance of price comparison, such that some consumers may actively seek the best deal and others may prioritize other factors besides price. 9. Online Shopping Behavior (OSB). Cultural factors such as trust in e-commerce, risk aversion, and the desire for personalized experiences can influence online shopping behavior. Cultural collectivism may also influence group purchasing decisions. 10. Sustainability and Ethical Consumption (SEC). Cultural values related to environmental consciousness, social responsibility, and ethical considerations can shape attitudes towards sustainable and ethically produced products. Some cultures may place a higher importance on these factors in their purchasing decisions. The summary of variables in this study and the key cultural factors influencing them is presented in Table 1. Table 1 Summary of Variables and the Key Cultural Factors Influencing Them Variable Abbreviation Cultural Factors Influencing Perception of Social Media Commerce PSMC Cultural attitudes towards technology Trust in online platforms Perception of social interactions Customer Service and Payment Systems CSPS Cultural preferences for communication styles Influence of payment methods on expectations Product Discovery and Social Sharing PDSS Cultural values (collectivism/individualism Impact on tendencies to share product discoveries Consumer-Seller Interaction CSI Cultural norms regarding politeness, negotiation, and buyer-seller relationship expectations https://changing-sp.com/ 252 Fatemeh Nouri Dehnavi, Negar Sioofy Khoojine Variable Abbreviation Cultural Factors Influencing Influence of Social Proof and Advertising ISPA Cultural aesthetics and values Collective decision-making influencing resonance Product Quality and Satisfaction PQS Cultural expectations on quality, durability, and aesthetics Impulse Purchases and Spending Habits IPSH Cultural attitudes towards consumption, savings, and impulsivity Price Comparison PC Cultural attitudes towards haggling, bargaining, and perceptions of value Online Shopping Behavior OSB Cultural factors like trust in e-commerce, risk aversion, and desire for personalized experiences Sustainability and Ethical Consumption SEC Cultural values related to environmental consciousness and social responsibility We designed a set of four tailored questions to comprehensively assess the impact of each variable. We have supplemented some questions with examples to facilitate a deeper understanding of the nuanced relationship between cultural aspects and the variables under consideration. The formulation of the questionnaire adhered rigorously to academic standards, emphasizing clarity, neutrality, and impartial inquiry. To enhance its efficacy, we conducted a meticulous small-scale pilot test before broader administration. Through this preliminary evaluation, we aimed to refine the questionnaire’s clarity, ensuring respondents’ ease of comprehension and response to each item. The final questionnaire, as informed by the insights gleaned from the pilot test, is documented in Table 1 (Appendix). This instrument proves indispensable in capturing valuable insights into the intricate interplay between cultural aspects and the ten selected variables within the domain of social commerce on prominent social media platforms. Analytical Techniques: Exploratory Factor Analysis and Multiple Linear Regression We will use factor analysis to explore the relationships among the 10 identified variables. This statistical technique reveals underlying dimensions that explain variables. correlations (Schuster & Yuan, 2005). Initially, we conducted an Exploratory Factor Analysis (EFA) to determine the number of dimensions in our dataset, with loadings indicating the strength of relationships between factors and observed variables (Backhaus et al., 2023). After identifying these dimensions, we use their scores in multiple linear regression to predict continuous outcomes. The regression coefficients reflect how changes in each factor affect the dependent variable (Nimon & Oswald, 2013). Table 1 Continued Changing Societies & Personalities, 2025, Vol. 9, No. 1, pp. 242–274 253 For categorical predictors, we compare the mean of the reference category with others. It is important to note that multiple linear regression requires certain conditions, such as independence of errors, linearity, absence of multicollinearity, and minimal influential outliers. By combining factor analysis with regression, we aim to uncover hidden relationships among variables, providing a comprehensive understanding of how they interact in our study (Ranganathan et al., 2017). This systematic approach is illustrated in Figure 1. Figure 1 Methodological Design Notes. The flowchart of the systematic process utilized for designing and implementing the research methodology. Source: developed by the authors. Analysis of the Findings Data Description This study involved a sample of 400 participants, of whom 52% were women, with an average age of 34.5 years (SD = 16.2). Table 2 details the demographic and socioeconomic characteristics. In terms of education, 36% hold a bachelor’s degree, 20% a master’s degree, and 14% are high school graduates. Regarding occupation, 34% are government employees, 23% are housewives, 21% are non-government workers, 12% are university students, and 23% are unemployed. Income distribution shows that 41% earn less than 40 million Rials, 32% between 50 and 80 million, 18% between 80 and 150 million, 6% between 150 and 250 million, and four earn over 250 million Rials. Figure 2 illustrates the even spread of these demographic aspects, indicating no significant discrepancies and thus enhancing the study’s methodological rigor. https://changing-sp.com/ 254 Fatemeh Nouri Dehnavi, Negar Sioofy Khoojine Figure 2 Demographic Parameters Notes. Tree map plot illustrating the demographic parameters of the collected data. Source: developed by the authors. Table 2 Descriptive Statistics for Gender, Education Level, Occupation, and Income Within the Sampling Society Characteristics Mean Age (SD) 34.5 (16.2) Gender (%) Female 52 Male 48 Education Level (%) High school degree 14 Diploma 11 Associates degree 5 Bachelor’s degree 36 Master’s degree 20 Postgraduate/professional degree 14 Occupation (%) Government employee 34 Student 10 University Student 12 Unemployed 23 Non-Government employee 21 Income (%) Less than 40 million Rials. 41 50 to 80 million Rials. 32 80 to 150 million Rials. 17 150 to 250 million Rials. 6 More than 250 million Rials. 4 Changing Societies & Personalities, 2025, Vol. 9, No. 1, pp. 242–274 255 Data analysis revealed varied social media usage for social commerce among respondents, with Instagram leading at 40.5% for purchase transactions. Other platforms included Telegram (22.4%), WhatsApp15 (19.5%), and Iranian platforms like Soroush, Rubika16, and Bale (11%). In terms of shopping preferences, clothing and footwear represented the top categories, making up 40.5% of transactions. Other significant categories included home appliances and furniture (13.1%), cosmetics and personal care (10.7%), and electronics (9.4%). These insights highlight the evolving behavior of Iranian consumers and the impact of social media on traditional business practices. Detailed results on preferred platforms and sought-after items are shown in Table 3. Table 3 Popular Social Media Platforms for Social Commerce and the Most Popular Items Available for Purchase Platforms and items Percentage Social Media Platforms Instagram 40.5 WhatsApp 19.5 Telegram 22.4 Soroush 1.9 Bale 4.2 Rubika 4.9 Others 6.6 Shopping Items Clothes, bags, and shoes 34.6 Electronic appliances 9.4 Educational supplies 10.7 Home appliances 13.1 Foodstuffs 9.7 Home decoration 8 Cosmetic 14.1 Others 0.6 Factor Analysis Results To explore the interplay between cultural aspects and social commerce on major social media platforms, we conducted a factor analysis of 10 selected variables. We report results from two key statistical tests: the Kaiser-Meyer-Olkin (KMO) Measure of Sampling Adequacy and Bartlett’s Test of Sphericity. A KMO value of 0.75 indicates satisfactory sampling adequacy for factor analysis, while Bartlett’s Test (χ² = 240.23, df = 36, p < .001) confirms the factorability of the correlation matrix, suggesting the variables are suitable for analysis. Communalities reflect how much each variable contributes to the extracted factors, ranging from 0.62 to 0.85 in our study. This range indicates the factors explain 15 WhatsApp is a trademark of WhatsApp Inc., registered in the US and other countries. 16 https://rubika.ir https://changing-sp.com/ https://rubika.ir 256 Fatemeh Nouri Dehnavi, Negar Sioofy Khoojine 62% to 85% of the variance between variables, highlighting a significant shared variance. This reliability reinforces the effectiveness of our factor analysis in capturing the complex relationships among the cultural dimensions influencing social commerce on these platforms. A summary of the communalities is provided in Table 4. Table 4 The Communalities Summary of Variables No Variable Communalities 1 PSMC 0.78 2 CSPS 0.80 3 PDSS 0.75 4 CSI 0.62 5 ISPA 0.65 6 PQS 0.70 7 IPSH 0.85 8 PC 0.82 9 OSB 0.78 10 SEC 0.80 The variability in the dataset attributed to each principal component is defined by initial eigenvalues and their percentage of explained variance. As shown in Table 5, cumulative percentages reflect components’ overall explanatory power, revealing that components 1, 2, and 3 account for 63.6% of the variance. This suggests potential redundancy in later components. Eigenvalues indicate each component’s contribution to variance, with higher values showing greater explanatory power. As shown in Table 6, Components 1 (3.52), 2 (2.56), and 3 (1.98) are significant contributors, as values above one signify substantial impact on capturing dataset variance. Table 5 Initial Eigenvalues Showcasing the Contribution and Cumulative Impact of Each Component in the Data Variability. Component Initial Eigenvalue % of Variance Cumulative % Component 1 3.52 27.8 27.8 Component 2 2.56 20.2 48.5 Component 3 1.98 15.6 63.6 Component 4 1.20 9.5 73.1 Component 5 0.85 6.7 79.8 Component 6 0.72 5.7 85.5 Component 7 0.60 4.7 90.2 Changing Societies & Personalities, 2025, Vol. 9, No. 1, pp. 242–274 257 Table 5 Continued Component Initial Eigenvalue % of Variance Cumulative % Component 8 0.50 3.9 94.1 Component 9 0.40 3.1 97.2 Component 10 0.30 2.3 100 Table 6 Rotation Sums of Squared Loadings for Principal Components Analysis Component Rotation Sums of Squared Loadings % Of Variance Cumulative % Component 1 3.20 26.8 26.8 Component 2 2.45 20.5 47.3 Component 3 1.90 15.9 63.2 Component 4 1.15 9.6 72.8 Component 5 0.82 6.8 79.6 Component 6 0.70 5.8 85.4 Component 7 0.58 4.8 90.2 Component 8 0.48 4.0 94.2 Component 9 0.38 3.1 97.3 Component 10 0.28 2.3 100 The goodness-of-fit indices indicate a satisfactory fit of the model to the data: χ²(24) = 112.45, p < .001; Comparative Fit Index (CFI) = 0.92; Root Mean Square Error of Approximation (RMSEA) = 0.08. The summary is shown in Table 7. Table 7 Summary of Goodness-of-Fit for the Purposed Factor Analysis Model Statistic Value Chi-Square 112.45 Degrees of Freedom 24 p-value < .001 CFI 0.92 RMSE 0.08 As shown in Table 8, the pattern matrix displays factor loadings for each variable on the three extracted factors. Notable loadings include PSMC, CSPS, and PDSS on Factor 1; CSI, ISPA, and PQS on Factor 2; and IPSH, PC, OSB, and SEC on Factor 3. The stacked percent bar chart of the pattern matrix is shown in Figure 3. https://changing-sp.com/ 258 Fatemeh Nouri Dehnavi, Negar Sioofy Khoojine Table 8 The Pattern Matrix of Factor Loadings for Each Variable. Variable Factor 1 Factor 2 Factor 3 PSMC 0.75 0.12 0.05 CSPS 0.72 0.18 0.08 PDSS 0.78 0.10 0.04 CSI 0.05 0.80 0.15 ISPA 0.10 0.75 0.20 PQS 0.08 0.78 0.18 IPSH 0.20 0.15 0.82 PC 0.18 0.10 0.85 OSB 0.22 0.20 0.78 SEC 0.15 0.25 0.80 Figure 3 Stacked Percent Bar Chart of the Pattern Matrix for 10 Selected Variables Note. Source: Developed by the authors. The structure matrix is given in Table 9. This allowed for a clearer interpretation of the relationships between variables and underlying factors. Figure 4 shows the stacked bar chart of the structure matrix. Changing Societies & Personalities, 2025, Vol. 9, No. 1, pp. 242–274 259 Figure 4 The Stacked Bar Chart of the Structure Matrix Note. Source: Developed by the authors. Table 9 The Structure Matrix Displaying the Correlations Between Variables and Factors Variable Factor 1 Factor 2 Factor 3 PSMC 0.80 0.15 0.12 CSPS 0.78 0.20 0.10 PDSS 0.85 0.12 0.08 CSI 0.10 0.82 0.18 ISPA 0.15 0.78 0.20 PQS 0.12 0.80 0.15 IPSH 0.25 0.18 0.85 PC 0.20 0.15 0.88 OSB 0.28 0.25 0.82 SEC 0.18 0.30 0.80 Inter-Factor Relationships Our factor analysis aimed to clarify and conduct a multiple regression analysis to assess the influence of two specific variables under Factor 1. We explain the rationale behind this analytical approach in the subsequent section. Our linear regression analysis identified significant coefficient estimates for Factor 1. The intercept was 0.4125 (p < .001), representing the expected value of https://changing-sp.com/ 260 Fatemeh Nouri Dehnavi, Negar Sioofy Khoojine Factor 1 when Factors 2 and 3 are zero. Factor 2 showed a strong positive relationship (β = 0.7028, p < .001), indicating a 0.7028 increase in Factor 1 for each unit change in Factor 2, with Factor 3 holding constant. Similarly, Factor 3 had a positive effect (β = 0.4883, p < .001), corresponding to a 0.4883 increase in Factor 1 with Factor 2 holding constant. The model explained 77.5% of the variance in Factor 1 (R² = 0.775) and was highly significant (F = 156.4, p < .001). Residuals showed normality (Omnibus = 3.210, p = .201) and no autocorrelation (Durbin–Watson = 1.892). Model fit was confirmed by low AIC (474.4) and BIC (486.9) values. Full regression results are shown in Table 10. Table 10 OLS Regression Results for Effect of Factors 2 and 3 on Factor 1 OLS Regression Results Dep. Variable Factor 1 R-squared 0.775 Model OLS Adj. R-squared 0.770 Method Least Squares F-statistic 156.4 Prob (F-statistic) 4.11e-57 Log-Likelihood –234.21 No. Observations 400 AIC 474.4 Df Residuals 397 BIC 486.9 Df Model 2 Covariance Type robust coef std err t P>|t| [0.025 0.975] const 0.4125 0.092 4.501 0.000 0.232 0.593 Factor 2 0.7028 0.045 15.472 0.000 0.614 0.791 Factor 3 0.4883 0.062 7.911 0.000 0.367 0.609 Omnibus 3.210 Durbin–Watson 1.892 Prob (Omnibus) 0.201 Jarque–Bera (JB) 2.979 Skew –0.253 Prob (JB) 0.226 Kurtosis 3.229 Cond. No. 5.53 Note. OLS regression results for analyzing the effect of Factor 2 and 3 on Factor 1. Discussion Our factor analysis of the influence of social commerce on consumer behavior revealed key relationships among 10 variables, grouped into three categories based on shared patterns and cultural implications. Factor 1, the “Cultural Perception Nexus,” includes the variables perception of social media commerce, consumer-seller interaction, and influence of social proof and advertising. Factor 2, the “Transaction Dynamics Ensemble,” covers customer service and payment systems, impulse purchases and spending habits, and online shopping behavior. Factor 3, the “Marketplace Values Quartet,” includes Product Discovery and Social Sharing, Product Quality Changing Societies & Personalities, 2025, Vol. 9, No. 1, pp. 242–274 261 and Satisfaction, Price Comparison, and Sustainability and Ethical Consumption. This categorization clarifies the cultural dimensions shaping the behaviors under examination. Factor 1: Cultural Perception Nexus The findings of Factor 1, the “Cultural Perception Nexus,” reveal the strong influence of cultural aspects on consumer behavior in the context of social commerce. Culture significantly shapes how individuals perceive social media commerce, and attitudes toward technology and trust in online platforms vary significantly across cultures. For instance, cultures valuing face-to-face transactions may require businesses to emphasize trust-building measures (e.g., customer reviews) to mitigate concerns about online shopping (Nilsson & Mattes, 2015; Robert et al., 2009). In individualistic cultures, businesses might focus on personal experiences, while collectivist cultures may benefit from fostering a sense of community and user interaction. Cultural norms also impact consumer–seller interactions. In high-context cultures, communication tends to be more implicit, such that interactions are more nuanced compared to low-context cultures that favor directness. In order to improve consumer satisfaction and trust, businesses should adjust their communication strategies to align with these cultural communication styles. Additionally, cultural attitudes toward social proof and advertising play a key role in social commerce. Cultural responses to symbols and social validation vary (Khalil, 2000): in collectivist societies, businesses can leverage peer recommendations and social endorsements to enhance their advertising strategies. The interconnectedness of these cultural factors shows that cultural preferences influence multiple aspects of consumer behavior; hence, businesses must navigate these influences to effectively engage culturally diverse consumer groups. Factor 2: Transaction Dynamics Ensemble The findings of Factor 2 pertain to the cultural aspects of consumer behavior in social commerce and highlight the significance—that is, the cultural dimensions that shape various facets of transaction dynamics. The three variables explored by this factor (customer service and payment systems, impulse purchases and spending habits, and online shopping behavior) all demonstrate the interplay between cultural influences and consumer behavior in the context of social commerce. The first variable, customer service and payment systems, reveals that cultural norms shape expectations related to customer service and preferred payment methods. This includes expectations around the level of formality or informality in communication, the importance attached to personalized service, and the trust associated with specific payment methods, which can vary across cultures. This finding implies that businesses operating in social commerce spaces must be sensitive to these cultural differences and adapt their customer service practices and payment systems accordingly (Bugshan & Attar, 2020). The second variable, impulse purchases and spending habits, highlights the intricate relationship between cultural dimensions and individual attitudes toward https://changing-sp.com/ 262 Fatemeh Nouri Dehnavi, Negar Sioofy Khoojine consumption. Cultural influences on impulsivity can manifest in various ways, with some cultures emphasizing careful consideration before making a purchase and others embracing more impulsive buying behaviors. Additionally, cultural attitudes toward saving, spending, and the perception of material possessions shape individual spending habits in the context of social commerce. Businesses’ marketing strategies should reflect the cultural attitudes around consumption in their target markets. The third variable, online shopping behavior, highlights the significant impact of cultural factors on individuals’ participation in online transactions. Cultural attitudes toward technology, trust in e-commerce platforms, and the preference for personalized experiences are crucial determinants of online shopping behavior. Additionally, the cultural variation in social validation and peer recommendations influences individuals’ inclinations toward online shopping (Hu et al., 2016). Meeting consumer preferences and expectations in diverse cultural settings requires businesses to grasp these cultural nuances in order to customize the online shopping experience. Factor 3: Marketplace Values Quartet The findings of Factor 3 regarding “Marketplace Values Quartet” explain the interplay between cultural foundations and consumer behavior within the social commerce realm. The four variables in the quartet—namely, product discovery and social share, product quality, satisfaction and price comparisons, and sustainability and ethical consumption—highlight the different dimensions that influenced cultural values. Product discovery and social sharing refers to the role of cultural principles in forming how individuals determine and share products on social commerce platforms; the cultural feature of sharing helps reveal whether product sharing is driven more by personal expression or communal values. Businesses operating in markets with diverse cultures must adapt their product discovery features to reflect both the cultural preferences of individuals and community values. The second variable is product satisfaction and quality, which distinguish the status of cultural expectations around product quality, robustness, and aesthetics. Understanding these cultural distinctions aids businesses in tailoring their products to meet consumer expectations, which in turn can improve customer satisfaction and loyalty. The third variable is price comparison, which highlights cultural attitudes toward consumer price comparison and reveals the influence of cultural values on commerce principles. Given that some cultures prioritize price above all, understanding the cultural lens that people use to evaluate the value of products is crucial for businesses to implement effective pricing strategies (Song et al., 2018). The fourth variable, sustainability and ethical consumption, deepens this understanding that cultural values impact consumer behavior. Specifically, this variable shows the influence of environmental awareness, social responsibility, and ethical considerations. These factors have more or less cultural significance depending on the context, but there is an overall trend toward socially responsible consumption that transcends cultural boundaries. As a result, businesses that want to align with consumer values of sustainability and ethical consumption need to understand these cultural inclinations. Changing Societies & Personalities, 2025, Vol. 9, No. 1, pp. 242–274 263 Finally, the “Marketplace Values Quartet” shows how cultural factors influence consumer behavior in social commerce. Crucially, businesses must understand and adapt to the landscape of their customers to create marketing strategies that resonate with the cultural preferences of their consumer base regarding product discovery, quality, pricing, and ethical considerations. This approach encourages consumer engagement, helping businesses achieve long-term success in the changing world of social commerce. When it comes to sustainability and ethical consumption, recognizing and aligning with values is a significant factor for promoting positive consumer behavior. Given these variables, it is evident that integrating sustainability practices and ethical considerations into their offerings helps businesses resonate with consumers who prioritize these values, thereby building meaningful connections and brand loyalty. In essence, our analysis of Factor 3 underscores the imperative to navigate the complex interplay between cultural aspects and consumer behavior in social commerce. Embracing cultural diversity and tailoring strategies to align with cultural values within the Marketplace Values Quartet foster positive consumer engagement and long-term success in the dynamic social commerce landscape. Conclusion Summary of Key Findings This research investigates the influence of cultural dimensions on consumer behavior in Tehran with the aim of providing valuable insights about the dynamics of social commerce and its impact on consumer behavior, particularly how unique cultural factors shape purchasing decisions. By categorizing 10 variables into three key areas— the link of cultural perception, the dynamic group of transactions, and the four market values—we highlighted certain cultural dynamics that distinguish Iranian consumer behavior from other societies. These findings nuance sociological understandings of the interaction between culture and consumer behavior, especially within the context of social commerce. The findings emphasized the significance of the “Cultural Perception Nexus,” which demonstrates how cultural attitudes shape consumers’ perceptions of social media platforms and their interactions with marketers. In business discussions, trust is a central element of business discussions that shifts according to cultural context. In most markets, shopping convenience is a primary consumer preference, yet most Tehrani consumers prioritize personal interactions and trust-building measures such as direct communication with and getting to know sellers before making a transaction. Therefore, cultivating trust with sellers in online transactions is a key factor that can increase consumer satisfaction and loyalty in Tehran’s online market environments. Another important aspect of our findings stems from the “Transaction Dynamics Ensemble.” This factor emphasizes the role of cultural norms in shaping preferences regarding customer service and payment systems, impulse purchases and spending habits, and online shopping behavior. Cultural norms, diverse communication styles, and distinct preferences for payment methods collectively moderate people’s https://changing-sp.com/ 264 Fatemeh Nouri Dehnavi, Negar Sioofy Khoojine expectations and behaviors during customer service interactions. At the same time, cultural attitudes towards consumption and savings have a significant impact on people’s spending habits and online shopping behavior patterns. The multifaceted nature of these variables reveals the complex relationship between cultural influences and transaction dynamics. This suggests that Iranian consumers clearly prefer traditional payment systems over online payments, digital wallets, and newer financial technologies, indicating their cautious approach to online transactions. Businesses need to understand these cultural dimensions and familiarize themselves with their strategies to respond to diverse cultural preferences for effective engagement and consumer satisfaction. Finally, the “Marketplace Values Quartet” clarifies the critical role of cultural values in shaping consumer decisions around price, quality, and ethical concerns. The findings indicate that Iranian consumers showed great interest in product quality and ethical consumption. Promoting products that meet ethical consumption and sustainability standards may particularly resonate with such market segments. The findings of this research align with Baudrillard’s theory of consumption by affirming that modern consumption is driven not only by functional needs but also by the symbolic meanings attached to goods. In Tehran’s social commerce landscape, consumers utilize their purchasing power to express identity, status, and alignment with cultural values. This perspective reinforces the idea that consumption extends beyond mere economic transactions and is instead a complex interaction of symbols and meanings. Social commerce platforms provide consumers with the means to amplify these symbolic expressions, thereby transforming their shopping experiences into acts of self-expression. Another point revealed by the findings is the distinctiveness of Iranian consumer behavior compared to other markets. While globalization has influenced some degree of homogenization in consumer behaviors, Iranian cultural values have profoundly shaped the consumption patterns of Tehrani consumers. Their behavior reflects a unique blend of traditional cultural values and modern digital practices, offering a compelling example of how local context shapes consumption patterns. Limitations of the Study This study of cultural dynamics in social commerce and its impact on consumer behavior and interaction patterns has several limitations. First, data collected from participants on specific social media platforms may not fully represent the diversity of consumer interactions in different digital environments. Second, reliance on self- reported data can introduce potential biases, as respondents may not accurately disclose their behaviors or attitudes. Third, focusing on a specific geographical location such as Tehran potentially limits the generalizability of the findings across cultural contexts. Finally, as technology rapidly evolves, it is likely that current forms of social commerce will become obsolete in the future, necessitating that the results of this research be updated. These limitations highlight areas for future research to further explore the complex interplay between cultural factors and social commerce dynamics in different contexts. Changing Societies & Personalities, 2025, Vol. 9, No. 1, pp. 242–274 265 Suggestions for Future Research Directions in Social Commerce and Cultural Dynamics Future research directions in social commerce and cultural dynamics should take note of the following points: • First, future studies should deepen examination of cultural dimensions affecting consumer behavior in different social commerce environments, especially in non-western societies like Tehran. • Second, longitudinal studies may provide insights into how cultural dynamics change over time as technology increasingly integrates into business, allowing researchers to track changes in consumer behavior and preferences. • Third, interdisciplinary approaches combining sociology, cultural studies, psychology, economics, and information technology will provide a more comprehensive understanding of the complex interaction between culture, technology, and consumer behavior. • Finally, future research in the field of social commerce and cultural dynamics should better examine the evolving role of emerging technologies, such as AI- based personalization and blockchain, in shaping consumer behavior in diverse cultural contexts. Reference Algharabat, R. S., & Rana, N. P. (2021). Social commerce in emerging markets and its impact on online community engagement. Information Systems Frontiers, 23(6), 1499–1520. https://doi.org/10.1007/s10796-020-10041-4 Backhaus, K., Erichson, B., Gensler, S., Weiber, R., & Weiber, T. (2023). Multivariate analysis: An application-oriented introduction. Springer. https://doi.org/10.1007/978-3-658-40411-6 Baudrillard, J. (1998). The consumer society: Myths and structures. SAGE. https://doi.org/10.4135/9781526401502 Baudrillard, J. (2001). The system of objects. In M. Poster (Ed.), Jean Baudrillard: Selected writings (2nd ed., pp. 13–31). Stanford University Press. https://doi.org/10.1515/9781503619630-004 Baudrillard, J. (2008). Simulacra and simulations. In S. Seidman & J. C. Alexander (Eds.), The new social theory reader (2nd ed.). Routledge. Belolipetskaya, A., Golovina, T., Polyanin, A., & Vertakova, Y. (2020). Transformation of the personnel competency model in the context of the transition to the digital economy. E3S Web of Conferences, 164, Article 09005. https://doi.org/10.1051/e3sconf/202016409005 Boström, M. (2020). The social life of mass and excess consumption. Environmental Sociology, 6(3), 268–278. https://doi.org/10.1080/ 23251042.2020.1755001 https://changing-sp.com/ https://doi.org/10.1007/s10796-020-10041-4 https://doi.org/10.1007/978-3-658-40411-6 https://doi.org/10.4135/9781526401502 https://doi.org/10.1515/9781503619630-004 https://doi.org/10.1051/e3sconf/202016409005 https://doi.org/10.1080/23251042.2020.1755001 https://doi.org/10.1080/23251042.2020.1755001 266 Fatemeh Nouri Dehnavi, Negar Sioofy Khoojine Brahma, A., & Dutta, R. (2020). Role of social media and e-commerce for business entrepreneurship. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 6(6), 1–18. https://doi.org/ 10.32628/CSEIT206559 Bugshan, H., & Attar, R. W. (2020). Social commerce information sharing and their impact on consumers. Technological Forecasting and Social Change, 153, Article 119875. https://doi.org/10.1016/j.techfore.2019.119875 Busalim, A., Hollebeek, L. D., & Lynn, T. (2024). The effect of social commerce attributes on customer engagement: an empirical investigation. Internet Research, 34(7), 187–214. https://doi.org/10.1108/INTR-03-2022-0165 Chen, Y. Y., Lai, F. W., Goh, K. N., & Daud, S. C. (2013). The effect of integrating social plugins into e-commerce website: A study on online consumer behaviour. In Proceedings of the 7th International Conference on Ubiquitous Information Management and Communication (Article 56). ACM. https://doi.org/10.1145/2448556.2448612 Dwivedi, Y. K., Ismagilova, E., Hughes, D. L., Carlson, J., Filieri, R., Jacobson, J., Jain, V., Karjaluoto, H., Kefi, H., Krishen, A. S., Kumar, V., Rahman, M. M., Raman, R., Rauschnabel, P. A., Rowley, J., Salo, J., Tran, G. A., & Wang, Y. (2021). Setting the future of digital and social media marketing research: Perspectives and research propositions. International Journal of Information Management, 59, Article 102168. https://doi.org/10.1016/j.ijinfomgt.2020.102168 Essien, E. O. (2024). Deconstructing hypertruth: Baudrillard’s semiotic analysis. The International Journal of the Image, 15(2), 19–36. https://doi.org/10.18848/ 2154-8560/CGP/v15i02/19-36 Griffiths, A. (2018). Trade marks and the consumer society. SCRIPTed, 15(2), 209–241. https://doi.org/10.2966/scrip.150218.209 Habib, M. M. (2018). Culture and consumerism in Jean Baudrillard: A postmodern perspective. Asian Social Science, 14(9), 43–46. https://doi.org/10.5539/ass.v14n9p43 Hajli, M. (2013). A research framework for social commerce adoption. Information Management & Computer Security, 21(3), 144–154. https://doi.org/10.1108/ IMCS-04-2012-0024 Ham, J., Li, S., Looi, J., & Eastin, M. S. (2024). Virtual humans as social actors: Investigating user perceptions of virtual humans’ emotional expression on social media. Computers in Human Behavior, 155, Article 108161. https://doi.org/10.1016/ j.chb.2024.108161 Hamermesh, D. S. (1993). [Review of The overworked American: The unexpected decline of leisure, by J. B. Schor]. Industrial and Labor Relations Review, 46(2). https://doi.org/10.2307/2524892 Horng, S.-M., & Wu, C.-L. (2020). How behaviors on social network sites and online social capital influence social commerce intentions. Information and Management, 57(2), Article 103176. https://doi.org/10.1016/j.im.2019.103176 https://doi.org/10.32628/CSEIT206559 https://doi.org/10.32628/CSEIT206559 https://doi.org/10.1016/j.techfore.2019.119875 https://doi.org/10.1108/INTR-03-2022-0165 https://doi.org/10.1145/2448556.2448612 https://doi.org/10.1016/j.ijinfomgt.2020.102168 https://doi.org/10.18848/2154-8560/CGP/v15i02/19-36 https://doi.org/10.18848/2154-8560/CGP/v15i02/19-36 https://doi.org/10.2966/scrip.150218.209 https://doi.org/10.5539/ass.v14n9p43 https://doi.org/10.1108/IMCS-04-2012-0024 https://doi.org/10.1108/IMCS-04-2012-0024 https://doi.org/10.1016/j.chb.2024.108161 https://doi.org/10.1016/j.chb.2024.108161 https://doi.org/10.2307/2524892 https://doi.org/10.1016/j.im.2019.103176 Changing Societies & Personalities, 2025, Vol. 9, No. 1, pp. 242–274 267 Hu, X., Chen, X., & Davison, R. M. (2019). Social support, source credibility, social influence, and impulsive purchase behavior in social commerce. International Journal of Electronic Commerce, 23(3), 297–327. https://doi.org/10.1080/ 10864415.2019.1619905 Hu, X., Huang, Q., Zhong, X., Davison, R. M., & Zhao, D. (2016). The influence of peer characteristics and technical features of a social shopping website on a consumer’s purchase intention. International Journal of Information Management, 36(6B), 1218–1230. https://doi.org/10.1016/j.ijinfomgt.2016.08.005 Huang, X., & Huo, Y. (2021). Research on decision-making behavior of social e-commerce marketing subject. International Journal of Frontiers in Sociology, 3(15), 152–158. https://doi.org/10.25236/IJFS.2021.031519 Ignjatović, J., & Filipović, S. (2022). A critical review of the rise of the neoliberal concept in economic policy. Socioloski Pregled, 56(1), 90–119. https://doi.org/10.5937/ socpreg56-35619 Jain, V. (2014). The impact of social commerce on consumer behaviour: With special reference to F-commerce. SSRN. https://doi.org/10.2139/ssrn.2403898 Khalil, E. L. (2000). Symbolic products: Prestige, pride and identity goods. Theory and Decision, 49(1), 53–77. https://doi.org/10.1023/A:1005223607947 Kim, Y., Chang, Y., Wong, S. F., & Park, M.-C. (2014). Customer attribution of service failure and its impact in social commerce environment. International Journal of Electronic Customer Relationship Management, 8(1–3), 136–158. https://doi.org/10.1504/IJECRM.2014.066890 Lavoye, V., Tarkiainen, A., Sipilä, J., & Mero, J. (2023). More than skin-deep: The influence of presence dimensions on purchase intentions in augmented reality shopping. Journal of Business Research, 169, Article 114247. https://doi.org/10.1016/ j.jbusres.2023.114247 Lefebvre, H. (1991). The production of space (D. Nicholson-Smith, Trans.). Blackwell. https://doi.org/10.4324/9780203132357-14 (Originally published in French). Lim, W. M., & Rasul, T. (2022). Customer engagement and social media: Revisiting the past to inform the future. Journal of Business Research, 148, 325–342. https://doi.org/10.1016/j.jbusres.2022.04.068 Macat Team. (2017). An analysis of Karl Marx’s Capital. Macat Library. https://doi.org/10.4324/9781912282258 McLuhan, M. (2008). The medium is the message. In C. D. Mortensen (Ed.), Communication theory (pp. 390–402). Routledge. https://doi.org/10.4324/ 9781315080918-31 Mendoza-Tello, J. C., Mora, H., Pujol-López, F. A., & Lytras, M. D. (2018). Social commerce as a driver to enhance trust and intention to use cryptocurrencies for electronic payments. IEEE Access, 6, 50737–50751. https://doi.org/10.1109/ ACCESS.2018.2869359 https://changing-sp.com/ https://doi.org/10.1080/10864415.2019.1619905 https://doi.org/10.1080/10864415.2019.1619905 https://doi.org/10.1016/j.ijinfomgt.2016.08.005 https://doi.org/10.25236/IJFS.2021.031519 https://doi.org/10.5937/socpreg56-35619 https://doi.org/10.5937/socpreg56-35619 https://doi.org/10.2139/ssrn.2403898 https://doi.org/10.1023/A:1005223607947 https://doi.org/10.1504/IJECRM.2014.066890 https://doi.org/10.1016/j.jbusres.2023.114247 https://doi.org/10.1016/j.jbusres.2023.114247 https://doi.org/10.4324/9780203132357-14 https://doi.org/10.1016/j.jbusres.2022.04.068 https://doi.org/10.4324/9781912282258 https://doi.org/10.4324/9781315080918-31 https://doi.org/10.4324/9781315080918-31 https://doi.org/10.1109/ACCESS.2018.2869359 https://doi.org/10.1109/ACCESS.2018.2869359 268 Fatemeh Nouri Dehnavi, Negar Sioofy Khoojine Neuman, W. R. (2000). The impact of the new media. In W. L. Bennett & R. M. Entman (Eds.), Mediated politics: Communication in the future of democracy (pp. 299– 320). Cambridge University Press. https://doi.org/10.1017/CBO9780511613852.015 Nilsson, M., & Mattes, J. (2015). The spatiality of trust: Factors influencing the creation of trust and the role of face-to-face contacts. European Management Journal, 33(4), 230–244. https://doi.org/10.1016/j.emj.2015.01.002 Nimon, K. F., & Oswald, F. L. (2013). Understanding the results of multiple linear regression: Beyond standardized regression coefficients. Organizational Research Methods, 16(4), 650–674. https://doi.org/10.1177/1094428113493929 Panizzut, N., Rafi-ul-Shan, P. M., Amar, H., Sher, F., Mazhar, M. U., & Klemeš, J. J. (2021). Exploring relationship between environmentalism and consumerism in a market economy society: A structured systematic literature review. Cleaner Engineering and Technology, 2, Article 100047. https://doi.org/10.1016/j.clet.2021.100047 Ranganathan, P., Pramesh, C. S., & Aggarwal, R. (2017). Common pitfalls in statistical analysis: Logistic regression. Perspectives in Clinical Research, 8(3), 148– 151. https://doi.org/10.4103/picr.PICR_87_17 Ritzer, G., & Miles, S. (2019). The changing nature of consumption and the intensification of McDonaldization in the digital age. Journal of Consumer Culture, 19(1), 3–20. https://doi.org/10.1177/1469540518818628 Ritzer, G., & Smart, B. (2001). Handbook of social theory. SAGE. https://doi.org/10.4135/9781848608351 Robert, L., Denis, A., & Hung, Y.-T. (2009). Individual swift trust and knowledge- based trust in face-to-face and virtual team members. Journal of Management Information Systems, 26(2), 241–279. https://doi.org/10.2753/MIS0742-1222260210 Schuster, C., & Yuan, K.-H. (2005). Factor analysis. In K. Kempf-Leonard (Ed.), Encyclopedia of social measurement (Vol. 2, pp. 1–8). Elsevier. https://doi.org/10.1016/ b0-12-369398-5/00162-6 Shah, S. S., & Asghar, Z. (2023). Dynamics of social influence on consumption choices: A social network representation. Heliyon, 9(6), Article e17146. https://doi.org/10.1016/j.heliyon.2023.e17146 Shorman, S., Allaymoun, M., & Hamid, O. (2019). Developing the e-commerce model a consumer to consumer using blockchain network technique. International Journal of Managing Information Technology, 11(2), 55–64. https://doi.org/10.5121/ ijmit.2019.11204 Singh, A. K., Raghuwanshi, S., Sharma, S., Khare, V., Singhal, A., Tripathi, M., & Banerjee, S. (2023). Modeling the nexus between perceived value, risk, negative marketing, and consumer trust with consumers’ social cross-platform buying behaviour in India using Smart-PLS. Journal of Law and Sustainable Development, 11(4), Article e488. https://doi.org/10.55908/sdgs.v11i4.488 https://doi.org/10.1017/CBO9780511613852.015 https://doi.org/10.1016/j.emj.2015.01.002 https://doi.org/10.1177/1094428113493929 https://doi.org/10.1016/j.clet.2021.100047 https://doi.org/10.4103/picr.PICR_87_17 https://doi.org/10.1177/1469540518818628 https://doi.org/10.4135/9781848608351 https://doi.org/10.2753/MIS0742-1222260210 https://doi.org/10.1016/b0-12-369398-5/00162-6 https://doi.org/10.1016/b0-12-369398-5/00162-6 https://doi.org/10.1016/j.heliyon.2023.e17146 https://doi.org/10.5121/ijmit.2019.11204 https://doi.org/10.5121/ijmit.2019.11204 https://doi.org/10.55908/sdgs.v11i4.488 Changing Societies & Personalities, 2025, Vol. 9, No. 1, pp. 242–274 269 Song, R., Moon, S., Chen, H., & Houston, M. B. (2018). When marketing strategy meets culture: The role of culture in product evaluations. Journal of the Academy of Marketing Science, 46(3), 384–402. https://doi.org/10.1007/ s11747-017-0525-x Veblen, T. (1992). The theory of the leisure class: An economic study in the evolution of institutions. Routledge. https://doi.org/10.4324/9781315135373 (Originally published 1899) Wang, C., & Zhang, P. (2012). The evolution of social commerce: The people, management, technology, and information dimensions. Communications of the Association for Information Systems, 31(5), 105–127. https://doi.org/10.17705/1cais.03105 Wang, P., & Huang, Q. (2023). Digital influencers, social power and consumer engagement in social commerce. Internet Research, 33(1), 178–207. https://doi.org/10.1108/INTR-08-2020-0467 Warde, A. (2015). The sociology of consumption: Its recent development. Annual Review of Sociology, 41, 117–134. https://doi.org/10.1146/annurev-soc-071913-043208 Whalen, T. (1991). [Review of Jean Baudrillard: From Marxism to Postmodernism and Beyond, by D. Kellner]. Modern Language Studies, 21(2), 116–118. https://doi.org/10.2307/3194878 Wu, T., & Shao, W. (2022). How does digital economy drive industrial structure upgrading: An empirical study based on 249 prefecture-level cities in China. PLOS ONE, 17(11), Article e0277787. https://doi.org/10.1371/journal.pone.0277787 Wu, Y., Nambisan, S., Xiao, J., & Xie, K. (2022). Consumer resource integration and service innovation in social commerce: The role of social media influencers. Journal of the Academy of Marketing Science, 50(3), 429–459. https://doi.org/ 10.1007/s11747-022-00837-y Xiang, H., Chau, K. Y., Iqbal, W., Irfan, M., & Dagar, V. (2022). Determinants of social commerce usage and online impulse purchase: Implications for business and digital revolution. Frontiers in Psychology, 13, Article 837042. https://doi.org/10.3389/ fpsyg.2022.837042 Yin, B., Yu, Y., & Xu, X. (2021). Recent advances in consumer behavior theory: Shocks from the COVID-19 pandemic. Behavioral Sciences, 11(12), Article 171. https://doi.org/10.3390/bs11120171 Zhang, H., Lu, Y., Shi, X., Tang, Z., & Zhao, Z. (2012). Mood and social presence on consumer purchase behaviour in C2C E-commerce in Chinese culture. Electronic Markets, 22(3), 143–154. https://doi.org/10.1007/s12525-012-0097-z https://changing-sp.com/ https://doi.org/10.1007/s11747-017-0525-x https://doi.org/10.1007/s11747-017-0525-x https://doi.org/10.4324/9781315135373 https://doi.org/10.17705/1cais.03105 https://doi.org/10.1108/INTR-08-2020-0467 https://doi.org/10.1146/annurev-soc-071913-043208 https://doi.org/10.2307/3194878 https://doi.org/10.1371/journal.pone.0277787 https://doi.org/10.1007/s11747-022-00837-y https://doi.org/10.1007/s11747-022-00837-y https://doi.org/10.3389/fpsyg.2022.837042 https://doi.org/10.3389/fpsyg.2022.837042 https://doi.org/10.3390/bs11120171 https://doi.org/10.1007/s12525-012-0097-z 270 Fatemeh Nouri Dehnavi, Negar Sioofy Khoojine Appendix Table 1 Questionaries Contains the Variables and Related Questions No Variables Questions and related multiple-choice answers 1 Perception of Social Media Commerce 1. How much do you agree that you tend to prioritize shopping for local products on platforms like Facebook Marketplace because it aligns with your cultural value of supporting local businesses? Strongly Disagree | Disagree | Neutral | Agree | Strongly Agree 2. To what extent do you believe that in your culture, the value of trust and authenticity makes you more cautious about purchasing items from unknown sellers on social media platforms compared to traditional shopping methods? Not at all | Slightly | Moderately | Strongly | Completely 3. Considering different cultural integrations with social media and shopping habits, how likely do you think cultural influences impact the shift towards online shopping in deeply integrated cultures compared to cultures where traditional shopping methods are more prevalent? Not Likely | Slightly Likely | Moderately Likely | Quite Likely | Extremely Likely 4. How much do you agree that in your cultural context, the emphasis on quality and authenticity often leads you to prioritize purchasing products from sellers with good reputations and positive reviews, irrespective of the price? Strongly Disagree | Disagree | Neutral | Agree | Strongly Agree 2 Customer Service and Payment Systems 1. In the context of a culture that values formality and directness, how would you assess if customer service interactions on social media platforms meet those expectations? Not at all | Slightly | Moderately | Strongly | Completely 2. If you come from a culture highly valuing trust and personal interaction, when evaluating online shopping, would you consider whether the return process is transparent and involves direct communication with sellers? Not at all | Slightly | Moderately | Strongly | Completely 3. If you belong to a culture where cash transactions are preferred, can you share your comfort level with digital payment systems on social media platforms? Not at all | Slightly | Moderately | Strongly | Completely 4. Considering a cultural context with high uncertainty avoidance, how would you describe your level of trust in the security measures of social media platforms for online transactions? Strongly Disagree | Disagree | Neutral | Agree | Strongly Agree Changing Societies & Personalities, 2025, Vol. 9, No. 1, pp. 242–274 271 No Variables Questions and related multiple-choice answers 3 Product Discovery and Social Sharing 1. To what extent does your cultural background influence the way you discover new products through social media as compared to traditional shopping channels? - Example: «I am more likely to discover and explore new products through social media because it aligns with my cultural values of staying connected and being exposed to diverse trends. Strongly Disagree | Disagree | Neutral | Agree | Strongly Agree 2. In your opinion, how much do your cultural values and preferences shape the information you encounter about products through social media compared to conventional retail experiences? - Example: «My cultural background significantly influences the types of products I engage with on social media; for instance, I prioritize sustainable and locally-made items, reflecting my cultural emphasis on environmental consciousness and supporting local businesses.» Not at all | Slightly | Moderately | Strongly | Completely 3. Considering your cultural background, how likely are you to share product discoveries on social media platforms with others in your community or network? - Example: «Due to my cultural inclination towards communal values, I am very likely to share product discoveries on social media, especially if I believe they align with the tastes and preferences of my cultural community.» Very Unlikely | Unlikely | Neutral |Likely | Very Likely 4. To what degree do you believe your cultural influences impact the effectiveness of social sharing in spreading product information within your social circles? - Example: «The effectiveness of social sharing in my cultural circles is very significant; my community values recommendations from within, and products that resonate with our cultural identity tend to spread quickly through social networks. Negligible |Minor |Moderate |Significant |Very Significant 4 Consumer-Seller Interaction 1. To what extent do you believe that purchasing from social media has influenced a more personalized and culturally tailored approach in the way companies interact with customers? Strongly Disagree | Disagree | Neutral | Agree | Strongly Agree 2. In your opinion, has the shift towards buying from social media platforms led to a more culturally diverse representation of products and services offered by companies? Strongly Disagree | Disagree | Neutral | Agree | Strongly Agree 3. To what extent do you perceive that companies on social media engage in culturally sensitive communication, considering your background and values? Strongly Disagree | Disagree | Neutral | Agree | Strongly Agree 4. From your perspective, has the advent of purchasing through social media resulted in a more inclusive and culturally aware customer service experience provided by companies Strongly Disagree | Disagree | Neutral | Agree | Strongly Agree https://changing-sp.com/ 272 Fatemeh Nouri Dehnavi, Negar Sioofy Khoojine No Variables Questions and related multiple-choice answers 5 Influence of Social Proof and Advertising 1. To what extent do cultural considerations influence your trust in information provided by social media influencers? Strongly Disagree | Disagree | Neutral | Agree | Strongly Agree 2. In the context of your cultural background, how significant is the impact of social proof (likes, shares, reviews) when deciding to make a purchase on social media? Strongly Disagree | Disagree | Neutral | Agree | Strongly Agree 3. Have you ever purchased a product based on advertising, but found it to be scarcely used, and how might cultural factors contribute to this phenomenon? Strongly Disagree | Disagree | Neutral | Agree | Strongly Agree 4. Considering your cultural perspective, how frequently do you find yourself purchasing a product that is more expensive than initially planned due to the influence of advertising? Not at all | Slightly | Moderately | Strongly | Completely 6 Product Quality and Satisfaction 1. Suppose you come from a culture that highly values craftsmanship and durability in products. You recently bought a handcrafted item advertised on social media. How much did your cultural background affect your judgment of its quality, taking into account factors like craftsmanship, material, and longevity? Not at all | Slightly | Moderately | Strongly | Completely 2. In your culture, there might be a strong emphasis on detailed and precise information when making purchases. Reflect on a recent product you bought from social media. Did your cultural background influence how much you trusted the product’s description provided by the seller in terms of accuracy and completeness? Not at all | Slightly | Moderately | Strongly | Completely 3. Based on your cultural values regarding customer satisfaction, recall your recent experiences purchasing items through social media. How satisfied were you overall with these purchases concerning factors like meeting expectations, customer service, and cultural relevance? Not at all | Slightly | Moderately | Strongly | Completely 4. Considering your cultural inclination towards sharing experiences and recommendations within your community, think about a product you recently purchased through social media. Would you recommend it to friends or family from your cultural background, taking into account how well it aligns with their preferences and values? Not at all | Slightly | Moderately | Strongly | Completely Changing Societies & Personalities, 2025, Vol. 9, No. 1, pp. 242–274 273 No Variables Questions and related multiple-choice answers 7 Impulse Purchases and Spending Habits 1. To what extent does your cultural background influence your likelihood of making impulse purchases while browsing social media? Not at all | Slightly | Moderately | Strongly | Completely 2. Considering your cultural perspective, how significantly has social media influenced your overall spending habits? Not at all | Slightly | Moderately | Strongly | Completely 3. From a cultural standpoint, how often do you find yourself buying something solely because it is inexpensive, even if you don’t necessarily need it? Not at all | Slightly | Moderately | Strongly | Completely 4. In relation to your cultural background, how frequently do you end up purchasing more than you need due to the low price of an item? Very Rarely |Rarely| Occasionally| Often| Very Often 8 Price Comparison 1. To what extent does your cultural background influence your tendency to impulsively compare prices between products on social media? Not at all | Slightly | Moderately | Strongly | Completely 2. Considering your cultural perspective, how likely are you to engage in impulsive price comparisons between social media and traditional markets? Very Unlikely| Unlikely | Neutral | Likely| Very Likely 3. From a cultural standpoint, how often do you find yourself making impulsive purchase decisions based on the price differences you observe on social media? Very Rarely |Rarely| Occasionally | Often | Very Often 4. In relation to your cultural background, how much does the price variation between social media and traditional markets impact your impulsive buying behavior? Not at all | Slightly | Moderately | Strongly | Completely 9 Online Shopping Behavior 1. To what extent does your cultural background influence your online shopping behavior, particularly in terms of exploring a variety of products available? Strongly Disagree | Disagree | Neutral | Agree | Strongly Agree 2. Considering your cultural perspective, how likely are you to make impulsive online purchases when you have free time? Very Unlikely| Unlikely | Neutral | Likely| Very Likely 3. From a cultural standpoint, how often do you find yourself influenced by online shopping trends or recommendations from your cultural community? Very Rarely |Rarely| Occasionally| Often| Very Often 4. In relation to your cultural background, how much does the convenience of online shopping impact your overall buying behavior? Not at all | Slightly | Moderately | Strongly | Completely https://changing-sp.com/ 274 Fatemeh Nouri Dehnavi, Negar Sioofy Khoojine No Variables Questions and related multiple-choice answers 10 Sustainability and Ethical Consumption 1. To what extent does your cultural background influence your sense of empowerment in making a positive difference through your consumption choices? Strongly Disagree | Disagree | Neutral | Agree | Strongly Agree 2. Considering your cultural perspective, how important is it for you to be aware of the environmental impact of the products or services you purchase? Not Important | Slightly Important | Moderately Important | Very Important | Extremely Important 3. From a cultural standpoint, how willing are you to pay extra for eco-friendly or environmentally sustainable products? Not Willing at All | Slightly Willing | Moderately Willing | Very Willing | Extremely Willing 4. In relation to your cultural background, how much have you changed your consumption habits in the past year to protect the environment? Not at all | Slightly | Moderately | Significantly | Completely