From 4Ps to 4Es: Drivers of Phygital Purchase Intention in Generations Y and Z

Abstract

At the start of 2024, Indonesia’s highly connected digital landscape provided the setting for examining how the marketing mix evolves from 4Ps to 4Cs and 4Es and how these pathways relate to phygital purchase intention among Generations Y and Z. Data from 372 respondents were collected through accidental sampling and analyzed with PLS-SEM. The sequential evolution from 4Ps through 4Cs to 4Es was supported for both cohorts. Generation Y was identified as “Pragmatic Converters,” driven by the Place–Convenience–Everyplace pathway, whereas Generation Z was identified as “Sceptical Advocates,” driven by the Product–Customer–Experience pathway.

Keywords: marketing mix; digital natives; pragmatic converters; sceptical advocates.

Introduction

Nowadays, technology connects billions worldwide, transforming social behaviour and human interactions (Nagajayanthi, 2022). According to Kemp (2024) in Digital 2024: Indonesia by DataReportal, the total number of internet users in Indonesia reached 185 million in January 2024, representing an online penetration rate of 66.5 percent. Concurrently, the number of active social media user identities reached 139 million, or 49.9 percent of the total population (Kemp, 2024). It is important to note that these figures represent user identities and may not reflect unique individuals. Additionally, Kemp (2024) indicates that there were 127 million social media users aged 18 and above in Indonesia at the start of 2024, which is equivalent to 64.8 percent of the total population within that age range. Unlike traditional marketing, social media has become a primary societal need, necessitating a re-evaluation of traditional marketing strategies, influencing brand research, and serving as a platform for content sharing and product promotion (Arpaci, 2020). According to Casado-Aranda et al. (2022), the proliferation of technology has encouraged companies to compete in triggering customer value, rewards, and interest to market products and adopt efficient approaches to reach targets. Social media has transformed engagement and revolutionized marketing practices by facilitating content Introduction: At the start of 2024, Indonesia’s 185 million internet users and 139 million social media users formed a highly connected landscape where this research explores how the marketing mix’s evolution (from 4Ps to 4Cs to 4Es) associates with purchase intentions across Generation Y and Z in a phygital environment.

Methods

: Utilizing a quantitative approach, data from 372 valid Indonesian respondents were gathered via non-probability accidental sampling using a 4-point Likert scale. PLS-SEM was employed to analyse direct and total effects within the conceptual model. Results: The structural path analysis confirms that the marketing mix successfully evolves from the 4Ps, through the 4Cs, to the 4Es for both cohorts, identifying two distinct behavioural archetypes based on total effects. Generation Y operates as "Pragmatic Converters," whose purchase intent is significantly associated with the Place–Convenience–Everyplace pathway (Original Sample = 0.16, T Statistic = 3.32, and P Values = 0.00), prioritizing immediate accessibility and seamless utility. Conversely, Generation Z acts as "Sceptical Advocates," whose purchase intent is strongly tied to the Product– Customer–Experience pathway (Original Sample = 0.12, T Statistic = 2.32, and P Values = 0.02), requiring deep product validation and high-value, shareable experiences to overcome baseline marketing scepticism. Conclusion: Generation Y values frictionless utility, whereas Generation Z demands transparency and social currency. Consequently, businesses need cohort-specific strategies, maximizing convenience for Generation Y while delivering experience-driven content for Generation Z. The Pragmatic Converter and Skeptical Advocate archetypes provide a strategic roadmap for localized, experience-centric marketing. sharing, interactivity, customer service, and feedback, thereby enhancing brand interaction and customer experience (Hallock et al., 2019; Miah et al., 2022; Moon & Iacobucci, 2022). While customer engagement involves complex interactions driven by motivations such as sharing experiences and recommendations (Hallock et al., 2019). In contrast to traditional marketing, social media enables multi- way interactions alike to face-to-face communication, enhances content richness, improves customer experiences, and allows engagement and information sharing without constraints of cost, distance, or time, helping customers access diverse sources (Arpaci, 2020; Cao et al., 2021; Shahbaznezhad et al., 2021). An online customer experience framework emphasizes customer experience as an internal, subjective state (Vazquez et al., 2020). The concept has evolved through marketing mix theories, starting with the 4Ps, a product-centric model proposed by McCarthy (1968) and transitioning to the 4Cs, introduced by Lauterborn (1990) as a customer-centric alternative, ultimately culminating in the 4Es by Fetherstonhaugh (2009). The evolution from the 4Ps to the 4Cs and finally to the 4Es reveals a significant shift in marketing focus, where Experience replaces Product and Customer, emphasizing that today's customers prioritize memorable experiences in their journey rather than product features (Addis, M. et al., 2022). This shift also underscores the importance of establishing long-term relationships with customers through engaging and exclusive platforms (Allcott et al., 2020). Exchange, which shifts from traditional understanding of Price and Cost, emphasizes value creation and the co-creation process, where customers' time, attention, and participation in customization enhance the perceived value of offerings (Lauterborn, 1990; McCarthy, 1968). Moreover, Everyplace replaces Place and Convenience, highlighting customers' ability to shop anytime and anywhere. This necessitates that marketers engage with customer at opportune moments rather than pushing messages when they are inconveniently (Fetherstonhaugh, 2009), enabling brands to capture customer attention across various touchpoints in customers' ubiquitous digital landscape (Janschitz et al., 2020; Konhäusner et al., 2021). Lastly, Evangelism redefines Promotion and Communication as an evolved form of word-of-mouth marketing, where loyal customers advocate for brands by sharing their positive experiences, thereby helping to engage potential customers and drive sales (Konhäusner et al., 2021). While the theoretical foundation of this journey has historically evolved through successive marketing mix paradigms, originating from McCarthy’s (1968) product- centric 4Ps and transitioning to Lauterborn’s (1990) customer-centric 4Cs, these legacy frameworks prove increasingly insufficient within modern phygital environments. The limitation of both the 4Ps and 4Cs lies in their assumption of a static, linear marketplace. The 4Ps model relies on distinct, firm-controlled variables, while the 4Cs model focuses on optimizing customer value through linear channels of communication and convenience (Konhäusner et al., 2021). However, in a phygital landscape where digital and physical realities blur, product features are commoditized in mere minutes, and corporate communication is fragmented into millions of unstructured, peer-to-peer conversations (Fetherstonhaugh, 2009). Crucially, while emerging literature has begun exploring the 4Es paradigm (Y. H. Chen et al., 2020; Gerlich, 2023; Konhäusner et al., 2021), prior studies post-Fetherstonhaugh (2009) treat these models as isolated frameworks, leaving a critical theoretical gap. Extant literature has failed to empirically test the sequential evolutionary chain showing how the 4Ps structurally flow through the 4Cs into the 4Es, nor has it provided a granular generational comparison between the distinct behaviours of Generation Y and Generation Z. Furthermore, prior work lacks empirical testing within the hyper-connected Indonesian phygital ecosystem and fails to operationalize these dynamics into empirical behavioural typologies like the "Pragmatic Converter" and "Sceptical Advocate" archetypes. By addressing these unresolved empirical and theoretical tensions, this study advances the literature from a descriptive overview of marketing evolution to a rigorous, context-specific structural framework. Numerous research has highlighted that customer experience is an internal and subjective state shaped by individual perceptions and strongly influences purchase intentions (Vazquez et al., 2020). Especially in social e- commerce, where brands aim to communicate effectively, build connections with customers, and enable direct interaction and feedback, which are essential to understanding customer preferences and behaviour (Y. H. Chen et al., 2020; Li et al., 2021). In addition, companies continue to face growing challenges in translating their social media investments into meaningful customer engagement (Hallock et al., 2019; Shahbaznezhad et al., 2021). To encourage trust, companies must ensure that their social media content is credible and engaging while protecting customers from misinformation. The evolution of customer experience has also influenced the traditional marketing mix, shifting the focus from a product- centric 4Ps model to a customer-centric 4Es model, Experience, Exchange, Everyplace, and Evangelism. This shift reflects the fact that customers increasingly engage with brands through social media anytime and anywhere across global market (Fetherstonhaugh, 2009; McCarthy, 1968). Moreover, the framework promotes the concept of customer evangelism, an evolution of marketing mix that represents a more advanced form of word-of-mouth and viral marketing (Konhäusner et al., 2021; Nasir et al., 2021; Terziyska, 2024). It also highlights the importance of enabling customers to purchase products or services by affecting potential purchasing behaviour include experiences, attention attraction, creation of interest, and conduct thorough information searches (Grewal et al., 2019). While existing literature recognizes that changing technology and generational shifts influence consumer behaviour generations (Agárdi & Alt, 2022; Olsson et al., 2023), a critical theoretical gap remains: these distinct generational consumer profiles are frequently treated as descriptive empirical patterns rather than deriving them from marketing- mix frameworks. This research bridges this gap by theoretically deriving the "Pragmatic Converter" and "Sceptical Advocate" typologies from the structural intersection of Prensky’s (2001) digital native theory and Fetherstonhaugh’s (2009) 4Es evolution. "Pragmatic Converters" are conceptually rooted in Generation Y’s transitional digital upbringing, where their tech- savviness manifests as utility optimization, meaning their purchase intentions are structurally triggered when legacy Place and Convenience infrastructure successfully converts into the frictionless access of Everyplace (Allcott et al., 2020; Tran & Bui Thanh Khoa, 2025). Conversely, "Sceptical Advocates" are theoretically derived from Generation Z's lived experience in a hyper-saturated, peer-to-peer digital environment (Munsch, 2021); their inherent marketing scepticism requires rigorous Product validation and Customer centricity before they can step into the emotional resonance of the 4Es framework. Grounding these profiles in structural pathways rather than observed data provides a predictive, theory-driven framework for phygital purchase intentions. This research aims to explore how the marketing mix has evolved from a product-centric approach (4Ps) - as independent variable to the 4Cs and finally to the 4Es – as mediating variables and its impact on the purchase intention – as dependent variable, across digital generational cohorts, specifically between Generations Y and Z. It emphasizes the importance of understanding these effects across different digital generations and examining the total effects. the sum of direct and indirect effects. Methods

Research Type

This research employs quantitative methods to test theoretical frameworks, establish empirical facts, examine correlations between variables, and predict outcomes. During the research phase, a questionnaire was developed to assess the impact of marketing mix evolution affects purchasing intention, as identified in the literature. To ensure the quality of the research, academics reviewed the questions, and a pilot test was conducted with a small sample of social media users. The final questionnaire was modified and divided into two parts: the first part collected socio-demographic information (gender, age, used social media frequently, and online purchase frequency), while the second part included statements on evolution of marketing mix and purchase intention, representing the thirteen variables studied with thirty-nine indicators. The measurement were adapted from established literature, McCarthy (1968) and Konhäusner et al. (2021) for the traditional 4Ps: Product, Price, Place, Promotion (4 variables with 12 indicators); Lauterborn (1990) and Agárdi and Alt (2022) for the transitional 4Cs: Customer, Cost, Convenience, Communication (4 variables with 12 indicators); Fetherstonhaugh (2009) and Gerlich (2023) for the experiential 4Es: Experience, Everyplace, Exchange, Evangelism (4 variables with 12 indicators); and Munsch (2021) for Purchase Intention (1 variable with 3 indicators).

Population and Sample/Informants

The sample size for a population of 127 million social media users aged 18 and above in in January 2024 in Indonesia (Kemp, 2024) was determined using Cochran’s formula, resulting in a required sample size of approximately 271 respondents at a 90 percent confidence level and a 5 percent margin of error.

Research Location

The survey targeted Generations Y and Z, using a questionnaire administered to social media users across these cohorts, as defined by the Indonesian Central Bureau of Statistics / BPS (2024).

Instrumentation or Tools

Respondents indicated the evolution of marketing mix from the 4Ps to the 4Cs and finally to the 4Es and the impact to Purchase Intention variables using a 4-point Likert scale, structured as: "Strongly Disagree" (1), "Disagree" (2), "Agree" (3), and "Strongly Agree" (4). This a priori decision to omit a neutral midpoint was intentionally implemented to eliminate central tendency bias and "fence-sitting," an approach established by Garland (1991) to encourage definitive, high- variance responses. By removing the midpoint prior to data collection, the instrument systematically compels respondents to choose a directional stance, generating more precise indicators for structural equation modeling (Adelson & Mccoach, 2010). This forced-choice format is further validated by research, which confirm that eliminating the neutral option produces cleaner, actionable structural path data within Indonesian populations (Adila Kasni Astiena et al., 2026).

Data Collection Procedures

A non-probability accidental sampling method was used to gather data from social media users in Indonesia via online questionnaires distributed across Indonesian social media groups, professional networks, and consumer forums. Strict screening criteria embedded in the instrument restricted eligibility to individuals matching the age range at the time of the 2024 survey period: 28–43 years old for Generation Y (born 1981–1996) or 18–27 years old for Generation Z (born 1997– 2006), who demonstrated active social media usage and regular online purchasing frequency. Concluding in January 2024, the three-month data collection process yielded 372 valid responses (Generation Y: 176, 47.3 percent; Generation Z: 196, 52.7 percent), mirroring the macro-digital proportions of the 2024 Indonesian Internet Service Providers Association (APJII) survey. Crucially, given the inherent limitations of a non- probability accidental sampling method regarding population representativeness, these findings cannot be generalized to the entire Indonesian Generation Y and Z macro-populations, but instead explicitly reflect the structural path behaviours of the surveyed digital-native respondents.

Data Analysis

To systematically evaluate the collected data of structural pathways of marketing-mix evolution across generation for Generations Y and Z and validate the theoretical archetypes, to investigate differences across these digital generations, highlighting the similarities and differences. The reliance on self-reported data collected via a single instrument introduces susceptibility to common-method bias, while the forced-choice 4-point Likert scale lacks a neutral midpoint, potentially omitting nuanced neutral sentiments (Adelson & Mccoach, 2010). Two types of analyses were conducted: descriptive and inferential. The descriptive analysis outlines the socio- demographic characteristics of the respondents and presents the minimum, maximum, and mean values for each variable and indicator within the research model. The inferential analysis utilized PLS-SEM to test the hypotheses, proceeded through a two-stage framework: a measurement model assessment to confirm indicator reliability and discriminant validity, followed by a structural model evaluation (Aguirre- Urreta & Rönkkö, 2018). This structural phase utilized multi- group analysis (PLS-MGA) to compare the direct, indirect, and total effects between Generation Y (n = 176) and Generation Z (n = 196), considered for total effects, representing the combined direct and indirect effects within the path model (Hair et al., 2021).

Ethical Approval

This research prioritized ethical principles by protecting participants' anonymity, respecting their rights, and ensuring no harm was caused. The research followed established ethical standards to maintain the dignity and well-being of everyone involved. As no additional data were generated beyond the survey responses collected, individual responses cannot be shared due to ethical and privacy concerns.

Result and Discussion

Descriptive Analysis

Inference Analysis

Table 1. Measurement Model Analysis

Structural Model and Hypothesis Testing

Total Effect Analysis

Conclusion

: Generation Y values frictionless utility, whereas Generation Z demands transparency and social currency. Consequently, businesses need cohort-specific strategies, maximizing convenience for Generation Y while delivering experience-driven content for Generation Z. The Pragmatic Converter and Skeptical Advocate archetypes provide a strategic roadmap for localized, experience-centric marketing.

sharing, interactivity, customer service, and feedback, thereby enhancing brand interaction and customer experience (Hallock et al., 2019; Miah et al., 2022; Moon & Iacobucci, 2022). While customer engagement involves complex interactions driven by motivations such as sharing experiences and recommendations (Hallock et al., 2019). In contrast to traditional marketing, social media enables multi- way interactions alike to face-to-face communication, enhances content richness, improves customer experiences, and allows engagement and information sharing without constraints of cost, distance, or time, helping customers access diverse sources (Arpaci, 2020; Cao et al., 2021; Shahbaznezhad et al., 2021). An online customer experience framework emphasizes customer experience as an internal, subjective state (Vazquez et al., 2020). The concept has evolved through marketing mix theories, starting with the 4Ps, a product-centric model proposed by McCarthy (1968) and transitioning to the 4Cs, introduced by Lauterborn (1990) as a customer-centric alternative, ultimately culminating in the 4Es by Fetherstonhaugh (2009). The evolution from the 4Ps to the 4Cs and finally to the 4Es reveals a significant shift in marketing focus, where Experience replaces Product and Customer, emphasizing that today's customers prioritize memorable experiences in their journey rather than product features (Addis, M. et al., 2022). This shift also underscores the importance of establishing long-term relationships with customers through engaging and exclusive platforms (Allcott et al., 2020). Exchange, which shifts from traditional understanding of Price and Cost, emphasizes value creation and the co-creation process, where customers' time, attention, and participation in customization enhance the perceived value of offerings (Lauterborn, 1990; McCarthy, 1968). Moreover, Everyplace replaces Place and Convenience, highlighting customers' ability to shop anytime and anywhere. This necessitates that marketers engage with customer at opportune moments rather than pushing messages when they are inconveniently (Fetherstonhaugh, 2009), enabling brands to capture customer attention across various touchpoints in customers' ubiquitous digital landscape (Janschitz et al., 2020; Konhäusner et al., 2021). Lastly, Evangelism redefines Promotion and Communication as an evolved form of word-of-mouth marketing, where loyal customers advocate for brands by sharing their positive experiences, thereby helping to engage potential customers and drive sales (Konhäusner et al., 2021). While the theoretical foundation of this journey has historically evolved through successive marketing mix paradigms, originating from McCarthy’s (1968) product- centric 4Ps and transitioning to Lauterborn’s (1990) customer-centric 4Cs, these legacy frameworks prove increasingly insufficient within modern phygital environments. The limitation of both the 4Ps and 4Cs lies in their assumption of a static, linear marketplace. The 4Ps model relies on distinct, firm-controlled variables, while the 4Cs model focuses on optimizing customer value through linear channels of communication and convenience (Konhäusner et al., 2021). However, in a phygital landscape where digital and physical realities blur, product features are commoditized in mere minutes, and corporate communication is fragmented into millions of unstructured, peer-to-peer conversations (Fetherstonhaugh, 2009). Crucially, while emerging literature has begun exploring the 4Es paradigm (Y. H. Chen et al., 2020; Gerlich, 2023; Konhäusner et al., 2021), prior studies post-Fetherstonhaugh (2009) treat these models as isolated frameworks, leaving a critical theoretical gap. Extant literature has failed to empirically test the sequential evolutionary chain showing how the 4Ps structurally flow through the 4Cs into the 4Es, nor has it provided a granular generational comparison between the distinct behaviours of Generation Y and Generation Z. Furthermore, prior work lacks empirical testing within the hyper-connected Indonesian phygital ecosystem and fails to operationalize these dynamics into empirical behavioural typologies like the "Pragmatic Converter" and "Sceptical Advocate" archetypes. By addressing these unresolved empirical and theoretical tensions, this study advances the literature from a descriptive overview of marketing evolution to a rigorous, context-specific structural framework. Numerous research has highlighted that customer experience is an internal and subjective state shaped by individual perceptions and strongly influences purchase intentions (Vazquez et al., 2020). Especially in social e- commerce, where brands aim to communicate effectively, build connections with customers, and enable direct interaction and feedback, which are essential to understanding customer preferences and behaviour (Y. H. Chen et al., 2020; Li et al., 2021). In addition, companies continue to face growing challenges in translating their social media investments into meaningful customer engagement (Hallock et al., 2019; Shahbaznezhad et al., 2021). To encourage trust, companies must ensure that their social media content is credible and engaging while protecting customers from misinformation. The evolution of customer experience has also influenced the traditional marketing mix, shifting the focus from a product- centric 4Ps model to a customer-centric 4Es model, Experience, Exchange, Everyplace, and Evangelism. This shift reflects the fact that customers increasingly engage with brands through social media anytime and anywhere across global market (Fetherstonhaugh, 2009; McCarthy, 1968). Moreover, the framework promotes the concept of customer evangelism, an evolution of marketing mix that represents a more advanced form of word-of-mouth and viral marketing (Konhäusner et al., 2021; Nasir et al., 2021; Terziyska, 2024). It also highlights the importance of enabling customers to purchase products or services by affecting potential purchasing behaviour include experiences, attention attraction, creation of interest, and conduct thorough information searches (Grewal et al., 2019). While existing literature recognizes that changing technology and generational shifts influence consumer behaviour generations (Agárdi & Alt, 2022; Olsson et al., 2023), a critical theoretical gap remains: these distinct generational consumer profiles are frequently treated as descriptive empirical patterns rather than deriving them from marketing- mix frameworks. This research bridges this gap by theoretically deriving the "Pragmatic Converter" and "Sceptical Advocate" typologies from the structural intersection of Prensky’s (2001) digital native theory and Fetherstonhaugh’s (2009) 4Es evolution. "Pragmatic Converters" are conceptually rooted in Generation Y’s transitional digital upbringing, where their tech- savviness manifests as utility optimization, meaning their purchase intentions are structurally triggered when legacy Place and Convenience infrastructure successfully converts into the frictionless access of Everyplace (Allcott et al., 2020; Tran & Bui Thanh Khoa, 2025). Conversely, "Sceptical Advocates" are theoretically derived from Generation Z's lived experience in a hyper-saturated, peer-to-peer digital environment (Munsch, 2021); their inherent marketing scepticism requires rigorous Product validation and Customer centricity before they can step into the emotional resonance of the 4Es framework. Grounding these profiles in structural pathways rather than observed data provides a predictive, theory-driven framework for phygital purchase intentions. This research aims to explore how the marketing mix has evolved from a product-centric approach (4Ps) - as independent variable to the 4Cs and finally to the 4Es – as mediating variables and its impact on the purchase intention – as dependent variable, across digital generational cohorts, specifically between Generations Y and Z. It emphasizes the

importance of understanding these effects across different digital generations and examining the total effects. the sum of direct and indirect effects.

Methods Research Type This research employs quantitative methods to test theoretical frameworks, establish empirical facts, examine correlations between variables, and predict outcomes. During the research phase, a questionnaire was developed to assess the impact of marketing mix evolution affects purchasing intention, as identified in the literature. To ensure the quality of the research, academics reviewed the questions, and a pilot test was conducted with a small sample of social media users. The final questionnaire was modified and divided into two parts: the first part collected socio-demographic information (gender, age, used social media frequently, and online purchase frequency), while the second part included statements on evolution of marketing mix and purchase intention, representing the thirteen variables studied with thirty-nine indicators. The measurement were adapted from established literature, McCarthy (1968) and Konhäusner et al. (2021) for the traditional 4Ps: Product, Price, Place, Promotion (4 variables with 12 indicators); Lauterborn (1990) and Agárdi and Alt (2022) for the transitional 4Cs: Customer, Cost, Convenience, Communication (4 variables with 12 indicators); Fetherstonhaugh (2009) and Gerlich (2023) for the experiential 4Es: Experience, Everyplace, Exchange, Evangelism (4 variables with 12 indicators); and Munsch (2021) for Purchase Intention (1 variable with 3 indicators).

Population and Sample/Informants The sample size for a population of 127 million social media users aged 18 and above in in January 2024 in Indonesia (Kemp, 2024) was determined using Cochran’s formula, resulting in a required sample size of approximately 271 respondents at a 90 percent confidence level and a 5 percent margin of error.

Research Location The survey targeted Generations Y and Z, using a questionnaire administered to social media users across these cohorts, as defined by the Indonesian Central Bureau of Statistics / BPS (2024).

Instrumentation or Tools Respondents indicated the evolution of marketing mix from the 4Ps to the 4Cs and finally to the 4Es and the impact to Purchase Intention variables using a 4-point Likert scale, structured as: "Strongly Disagree" (1), "Disagree" (2), "Agree" (3), and "Strongly Agree" (4). This a priori decision to omit a neutral midpoint was intentionally implemented to eliminate central tendency bias and "fence-sitting," an approach established by Garland (1991) to encourage definitive, high- variance responses. By removing the midpoint prior to data collection, the instrument systematically compels respondents to choose a directional stance, generating more precise indicators for structural equation modeling (Adelson & Mccoach, 2010). This forced-choice format is further validated by research, which confirm that eliminating the neutral option produces cleaner, actionable structural path data within Indonesian populations (Adila Kasni Astiena et al., 2026).

Data Collection Procedures A non-probability accidental sampling method was used to gather data from social media users in Indonesia via online questionnaires distributed across Indonesian social media groups, professional networks, and consumer forums. Strict screening criteria embedded in the instrument restricted eligibility to individuals matching the age range at the time of the 2024 survey period: 28–43 years old for Generation Y (born 1981–1996) or 18–27 years old for Generation Z (born 1997– 2006), who demonstrated active social media usage and regular online purchasing frequency. Concluding in January 2024, the three-month data collection process yielded 372 valid responses (Generation Y: 176, 47.3 percent; Generation Z: 196, 52.7 percent), mirroring the macro-digital proportions of the 2024 Indonesian Internet Service Providers Association (APJII) survey. Crucially, given the inherent limitations of a non- probability accidental sampling method regarding population representativeness, these findings cannot be generalized to the entire Indonesian Generation Y and Z macro-populations, but instead explicitly reflect the structural path behaviours of the surveyed digital-native respondents.

Data Analysis To systematically evaluate the collected data of structural pathways of marketing-mix evolution across generation for Generations Y and Z and validate the theoretical archetypes, to investigate differences across these digital generations, highlighting the similarities and differences. The reliance on self-reported data collected via a single instrument introduces susceptibility to common-method bias, while the forced-choice 4-point Likert scale lacks a neutral midpoint, potentially omitting nuanced neutral sentiments (Adelson & Mccoach, 2010). Two types of analyses were conducted: descriptive and inferential. The descriptive analysis outlines the socio- demographic characteristics of the respondents and presents the minimum, maximum, and mean values for each variable and indicator within the research model. The inferential analysis utilized PLS-SEM to test the hypotheses, proceeded through a two-stage framework: a measurement model assessment to confirm indicator reliability and discriminant validity, followed by a structural model evaluation (Aguirre- Urreta & Rönkkö, 2018). This structural phase utilized multi- group analysis (PLS-MGA) to compare the direct, indirect, and total effects between Generation Y (n = 176) and Generation Z (n = 196), considered for total effects, representing the combined direct and indirect effects within the path model (Hair et al., 2021).

Ethical Approval This research prioritized ethical principles by protecting participants' anonymity, respecting their rights, and ensuring no harm was caused. The research followed established ethical standards to maintain the dignity and well-being of everyone involved. As no additional data were generated beyond the survey responses collected, individual responses cannot be shared due to ethical and privacy concerns. Result and Discussion The socio-demographic profile of the 372 respondents in the first part of the questionnaire revealed that 49 percent were male and 51 percent were female (Figure 1). Regarding generational classification, 47 percent identified as Generation Y, while 53 percent were Generation Z, indicating a predominantly younger and tech-savvy (Manyanga et al., 2024; Mertala et al., 2024). Social media usage patterns showed that 91 percent of respondents used social media frequently, while online purchase frequency was mainly categorized as "Sometimes" (44 percent) and "Rarely" (31 percent). Social media has transformed engagement and revolutionized

Figure 1. Respondent Characteristic (N:372 respondents)

Figure 2. Descriptive Data Analysis (Mean values)

marketing practices by facilitating content sharing, interactivity, customer service and feedback, thereby enhancing brand interaction and customer experience (Hallock et al., 2019; Miah et al., 2022; Moon & Iacobucci, 2022). When information aligns with their needs, customers are more motivated to search for products and services (Ebrahimi et al., 2022). Tham et al. (2020) empirically demonstrated that high social media engagement is crucial in decision-making processes.

Descriptive analysis This research employs descriptive analysis from the second part of the questionnaire to address the first question: Does social media impact on customer experience (4Ps, 4Cs, and 4Es) and purchase intention across different generations? The analysis provided the mean values for 4Ps, 4Cs, 4Es, and purchase intention variables within the research model between Generations Y and Z (Figure 2). The variable with the lowest mean value in the research model is "Place" from 4Ps similar for both generational cohorts reporting similar means. According to Haniff (2021), the place is a primary driver of perceived value in physical distribution. Place as the function of providing products where and when they are required to create time, place, and ownership utilities (Baig et al., 2020). This uniform dissatisfaction suggests that the digital distribution are less likely to engage, leading to lower overall satisfaction (Haniff, 2021). Conversely, the highest mean values differed by generational cohort. For Generation Y, the highest mean was observed for the "Customer" from 4Cs variable (mean: 3.35). Generation Y may struggle to adapt to rapid changes, intention to engage with social media is significantly influenced by their personality traits and openness to new experiences (Agárdi & Alt, 2022). For Generation Z, the highest mean was found in "Purchase Intention " variable (mean: 3.32). As a younger and more tech-savvy, Generation Z is more influenced by social media, and stronger need for stimulation, which is an important driver of satisfaction despite the complexity of two-way communication to be stimulating (Kirk et al., 2015; Rajagopal, 2009). The highest mean value is similar for "Everyplace" from 4Es variable. Customer experience and everyplace drives active interaction and facilitates the deep communication required for strong brand relationships (Wongkitrungrueng & Assarut, 2020). However, the 4Ps and 4Cs variables varied significantly between generational cohorts. The highest mean value for Generation Y in the "Product” from 4Ps variable and "Customer” from 4Cs variable, reflects a preference for traditional marketing focus on a one to-one relationships, whereas social media operates on a many-to-many basis, often resulting in a more passive audience (Allcott et al., 2020). However, they may struggle to adapt to rapid changes, as their openness to experience and personality traits significantly influence their intention to engage with social media (Agárdi & Alt, 2022). In contrast, highest mean value for Generation Z in the "Promotion” from 4Ps variable and "Communication” from 4Cs variable, describe the evaluation of traditional marketing and a more advanced form of word of-mouth (WOM) communication and viral marketing (Konhäusner et al., 2021; Nasir et al., 2021; Terziyska, 2024).

Inference Analysis This research uses inference analysis from the second part of the questionnaire to address the second question: What is the relevant impact of social media on the marketing mix Table 1. Results of Measurement model analysis

AVE: Average Variance Extracted CR: Composite Reliability CA: Cronbach's Alpha Descriptive Data Analysis (Mean values) Descriptive Data Analysis (Mean values) AVE CR CA Loading Factor Result AVE CR CA Loading Factor Result Product-centric (4Ps) - Product (P1) 0,67 0,86 0,75

Reliable - Product Packaging 4Ps-P1.1

0,78 Valid - Product Quality 4Ps-P1.2

0,84 Valid - Product Recommendation 4Ps-P1.3

0,76 Valid Product-centric (4Ps) - Price (P2) 0,79 0,92 0,87

Reliable - Price Fairness 4PS-P2.1

0,89 Valid - Value for Money 4PS-P2.2

0,93 Valid - Competitive Pricing 4PS-P2.3

0,72 Valid Product-centric (4Ps) - Place (P3) 0,79 0,92 0,87

Reliable - Product Availability 4PS-P3.1

0,83 Valid - Purchase Timing 4PS-P3.2

0,86 Valid - Payment Method 4PS-P3.3

0,90 Valid Product-centric (4Ps) - Promotion (P4) 0,86 0,95 0,92

Reliable - Promotional Creativity 4PS-P4.1

0,90 Valid - Direct Promotion 4PS-P4.2

0,88 Valid - Online Promotion 4PS-P4.3

0,88 Valid Customer-centric (4Cs) - Customer (C1) 0,72 0,89 0,80

Reliable - Product Assortment 4CS-C1.1

0,77 Valid - Perceived Quality 4CS-C1.2

0,82 Valid - Need Fulfilment 4CS-C1.3

0,86 Valid Customer-centric (4Cs) - Cost (C2) 0,70 0,88 0,79

Reliable - Product Assortment 4CS-C1.1

0,88 Valid - Perceived Quality 4CS-C1.2

0,87 Valid - Need Fulfilment 4CS-C1.3

0,83 Valid Customer-centric (4Cs) - Convenient (C3) 0,76 0,91 0,84

Reliable - Location Accessibility 4CS-C3.1

0,84 Valid - Service Flexibility 4CS-C3.2

0,92 Valid - Service Comfort 4CS-C3.3

0,84 Valid Customer-centric (4Cs) - Communication (C4) 0,75 0,90 0,84

Reliable - Informative Advertising 4CS-C4.1

0,85 Valid - Targeted Promotion 4CS-C4.2

0,90 Valid - Information Updates 4CS-C4.3

0,80 Valid Customer-focused (4Es) - Experience (E1) 0,69 0,87 0,78

0,87 Valid - Enjoyment 4ES-E1.2

0,83 Valid - Involvement 4ES-E1.3

0,83 Valid Customer-focused (4Es) - Exchange (E2) 0,75 0,90 0,84

Reliable - Information 4ES-E2.1

0,87 Valid - Promotion 4ES-E2.2

0,87 Valid - Engagement 4ES-E2.3

0,83 Valid Customer-focused (4Es) - Everyplace (E3) 0,77 0,91 0,85

Reliable - Product information 4ES-E3.1

0,87 Valid - Product readiness 4ES-E3.2

0,83 Valid - Product purchase 4ES-E3.3

0,83 Valid Customer-focused (4Es) - Evangelism (E4) 0,72 0,88 0,81

Reliable - Customer satisfaction 4ES-E4.1

0,82 Valid - Promotion program 4ES-E4.2

0,92 Valid - Involving 4ES-E4.3

0,91 Valid Purchase intention (PI) 0,67 0,86 0,75

Reliable - Information of products PI-1

0,87 Valid - Selection of products PI-2

0,73 Valid - Purchase of products PI-3

Table 2. Results of Discriminant Validity – Generation Y

Construct 4C-1 4C-2 4C-3 4C-4 4E-1 4E-2 4E-3 4E-4 4P-1 4P-2 4P-3 4-P4 Purchase Intention Customer Cost Convenient Communi cation Experience Exchange Everyplace Evangelism Product Price Place Promotion 4C-1 Customer 0.849 4C-2 Cost 0.762 0.839 4C-3 Convenient 0.681 0.688 0.872 4C-4 Communica tion 0.753 0.741 0.782 0.868 4E-1 Experience 0.728 0.626 0.728 0.750 0.833 4E-2 Exchange 0.631 0.691 0.685 0.727 0.765 0.869 4E-3 Everyplace 0.739 0.768 0.724 0.809 0.715 0.777 0.875 4E-4 Evangelism 0.626 0.714 0.673 0.722 0.710 0.789 0.786 0.848 4P-1 Product 0.620 0.586 0.596 0.629 0.651 0.578 0.619 0.492 0.816 4P-2 Price 0.630 0.713 0.577 0.676 0.562 0.575 0.714 0.527 0.723 0.889 4P-3 Place 0.303 0.364 0.395 0.341 0.478 0.515 0.336 0.469 0.530 0.319 0.891 4P-4 Promotion 0.519 0.511 0.614 0.587 0.657 0.560 0.520 0.645 0.521 0.418 0.522 0.929 Purchase Intention 0,535 0.535 0.473 0.553 0.465 0.491 0.615 0.498 0.392 0.484 0.201 0.373 0.817

Table 3. Results of Discriminant Validity – Generation Z Construct 4C-1 4C-2 4C-3 4C-4 4E-1 4E-2 4E-3 4E-4 4P-1 4P-2 4P-3 4-P4 Purchase Intention Customer Cost Convenient Communi cation Experience Exchange Everyplace Evangelism Product Price Place Promotion 4C-1 Customer 0.818 4C-2 Cost 0.787 0.862 4C-3 Convenient 0.746 0.744 0.868 4C-4 Communica tion 0.703 0.741 0.827 0.851 4E-1 Experience 0.672 0.651 0.691 0.727 0.843 4E-2 Exchange 0.655 0.600 0.674 0.705 0.815 0.860 4E-3 Everyplace 0.679 0.638 0.678 0.705 0.760 0.809 0.873 4E-4 Evangelism 0.527 0.547 0.602 0.662 0.725 0.715 0.651 0.883 4P-1 Product 0.628 0.616 0.552 0.585 0.610 0.543 0.529 0.559 0.794 4P-2 Price 0.641 0.645 0.550 0.573 0.547 0.526 0.502 0.540 0.791 0.849 4P-3 Place 0.476 0.446 0.508 0.456 0.505 0.535 0.381 0.524 0.569 0.648 0.862 4P-4 Promotion 0.547 0.551 0.591 0.587 0.626 0.582 0.535 0.611 0.646 0.611 0.660 0.887 Purchase Intention 0,535 0.307 0.327 0.366 0.431 0.479 0.419 0.439 0.431 0.461 0.412 0.413 0.461

evolution from the 4Ps to the 4Cs and finally to the 4Es between Generations Y and Z? And the third question: What is the relevant impact of marketing mix from the 4Es on the purchase intention between Generations Y and Z? The PLS- SEM model analysis follows two steps: first, a measurement model analysis to evaluate the relationships between indicators and variables; and second, a structural model evaluation to examine the predictive capability and connections between variables. The measurement model analysis (Table 1) shows that all indicators for both generational groups, are valid, with factor loadings above 0.70. Both Cronbach’s Alpha (CA) and Composite Reliability (CR) values exceeded 0.70, indicating strong internal consistency (Hair et al., 2019). Furthermore, the Average Variance Extracted (AVE) values for all variables were above 0.50, confirming the reliability of the thirteen variables across both generations. Discriminant Validity (Fornell-Larcker Criterion) assessment for Generation Y (Table 2) and Generation Z (Table 3) explained by each latent construct within its own indicators is greater than the variance shared with other constructs, confirms that the thirteen variables are empirically distinct and ready for structural model path analysis. Collectively, these results demonstrate that all thirteen variables (4Ps, 4Cs, 4Es, and Purchase Intention) maintain distinct empirical boundaries within both the Generation Y and Generation Z cohorts. Consequently, discriminant validity is robustly established for the two sub-groups, validating the data for subsequent multi-group structural equation modelling. After establishing the validity, reliability of the measurement model and Discriminant Validity assessment, the structural model analysis was performed using Smart-PLS version 3.0 with bootstrapping of 5.000 samples. This analysis relationships between variables were evaluated using t- statistics, with values above 1.646 indicating significance for one-tailed tests and P-values to confirm hypotheses, with significance set at less than 0.05 (Hair et al., 2019). A one- tailed testing framework was deliberately employed because Table 4. Results of Structural model analysis

Hypothesis Generation Y (n=176) Generation Z (n=196) Original Sample T Statistic P Values Result Original Sample T Statistic P Values Result H1: Product-centric (4Ps) has a positive relationship with Customer-centric (4Cs) H1a Product (P1) > Customer (C1) 0.62 12.43 0.00 Accepted 0.63 12.15 0.00 Accepted H1b Price (P2) > Cost (C2) 0.71 16.94 0.00 Accepted 0.64 13.28 0.00 Accepted H1c Place (P3) > Convenient (C3) 0.39 4.23 0.00 Accepted 0.51 8.16 0.00 Accepted H1d Promotion (P4) >Communication (C4) 0.59 11.42 0.00 Accepted 0.59 11.67 0.00 Accepted H2: Customer-centric (4Cs) has a positive relationship with Customer-focused (4Es) H2a Customer (C1) > Experience (E1) 0.73 17.85 0.00 Accepted 0.67 13.76 0.00 Accepted H2b Cost (C2) > Exchange (E2) 0.69 15.10 0.00 Accepted 0.60 11.59 0.00 Accepted H2c Convenient (C3) > Everyplace (E3) 0.72 18.02 0.00 Accepted 0.68 12.42 0.00 Accepted H2d Communication (C4)> Evangelism (E4) 0.72 16.86 0.00 Accepted 0.66 13.40 0.00 Accepted H3: Customer-focused (4Es) has a positive relationship with Purchase intention (PI) H3a Experience (E1) > Purchase Intention 0.05 0.46 0.65 Rejected 0.29 2.52 0.00 Accepted H3b Exchange (E2) > Purchase Intention 0.00 0.02 0.99 Rejected -0.07 0.60 0.54 Rejected H3c Everyplace (E3) > Purchase Intention 0.57 5.26 0.00 Accepted 0.17 1.59 0.11 Rejected H3d Evangelism (E4) > Purchase Intention 0.02 0.17 0.87 Rejected 0.16 1.53 0.16 Rejected

every hypothesized path in the proposed model is strictly directional, grounded in established marketing-mix evolution theories where advancements from the 4Ps to 4Cs and 4Es are structurally posited to exert a positive, monotonic influence on purchase intention variables. H1: Product-centric (4Ps) has a positive relationship with Customer-centric (4Cs). Based on the results of the inference analysis presented in Table 4, the first hypothesis (H1) examined the relationship between the Product-centric (4Ps) and Customer-centric (4Cs) result consistently across both Generations Y and Z was accepted, with t-statistics values >1.646 and P-values <0.05 for both groups (Hair et al., 2019). As Lauterborn (1990) suggests, this evolution redefines strategy as a response to customer needs only valuable when translated into customer-centric (4Cs) benefits, where "Product" becomes a customer solution, and "Price" is re- evaluated as the total Cost of ownership, including time and psychological effort (McCarthy, 1968). This alignment ensures that company-led strategies are grounded in the target market’s desires rather than just internal capabilities (Haniff, 2021). H2: Customer-centric (4Cs) has a positive relationship with Customer-focused (4Es). The second hypothesis (H2) examined the relationship between Customer-centric (4Cs) and Customer-focused (4Es) result consistently across both Generations was accepted. This result provides empirical weight to the arguments of Batat (2022) and Fetherstonhaugh (2009), who suggest that we have entered an era where physical and digital experiences merge into a "phygital" setting. This reveals that for customers, especially within the digital landscape, functional utility (4Cs) is no longer sufficient, it must culminate in a subjective, internal state of engagement (Vazquez et al., 2020). H3: Customer-focused (4Es) has a positive relationship with Purchase intention (PI). The third hypothesis (H3) examined the relationship between Customer-focused (4Es) and Purchase intention (PI) highlighting differences between generations. Based on the results presented in Table 2 for Generation Y, is that H3c, which states that Everyplace (E3) has a positive relationship with Purchase Intention is accepted, while the other three out of four hypotheses (H3a, H3b, and H3d) are rejected. Difference for Generation Z, only H3a is accepted, which states that the Experience (E1) has a positive relationship with Purchase intention, while other three out of four hypotheses (H3b, H3c, and H3d) are rejected. The ubiquitous nature of digital access grants customers the ability to shop anytime and anywhere, requiring brands to capture attention across all "phygital" touchpoints (Addis, M. et al., 2022; Fetherstonhaugh, 2009). For Generation Y, the Everyplace reflects a shift from traditional one-to-one marketing relationships to social media’s many-to-many operational basis, which can often result in a more passive audience (Allcott et al., 2020). As digital natives, Generation Y grew up utilizing product reviews and social tools to gather opinions before committing to a purchase (Munsch, 2021). However, they may struggle in adapting to the Experience, Exchange, and Evangelism, as their openness to experience and personality traits significantly influence their purchase (Agárdi & Alt, 2022). Furthermore, the online customer experience framework emphasizes that customer experience is an internal, subjective state (Vazquez et al., 2020). For Generation Z, the Experience reflects a necessity to cross-verify social media content with their own experience to derive meaning from the stimuli to which they are exposed (Aju et al., 2022; González-Serrano et al., 2024). According to Arpaci (2020), social media has become a societal necessity that influence transactions while serving as a platform for content sharing and product promotion. As Generation Z comes of age, they are expected to drive significant increases in spending as well as overall buying power (Munsch, 2021).

Total Effect Analysis. An Analysis of the structural model results reveals that the meaningfulness of path coefficients is enhanced by examining total effects. These are defined as the sum of direct and indirect effects of the marketing mix evolution from the 4Ps to 4Es, and the relevant impact of marketing mix on the purchase intention as endogenous variable (Hair et al., 2021). A direct effect refers to the relationship between two variables linked by a single arrow, while indirect effects involve one or more intervening variables in the causal path. As detailed in Table 5, the total effect for Generation Y was confirms marketing mix that has successfully evolves from a product-centric 4Ps model, through the customer-centric 4Cs to an experiential 4Es framework. The path coefficient (Original Table 5. Results of Structural model analysis for Total Effect – Generation Y

4Ps to 4Es (via 4Cs) Original Sample T Statistic P Values Result 4Ps to Purchase Intention (via 4Cs and 4Es) Original Sample T Statistic P Value s Result Product (P1) > Customer (C1) > Experience (E1) 0.45 0,18 0.00 Accepted Product (P1) > Customer (C1) > Experience (E1) > Purchase Intention 0.02 0.44 0.66 Rejected Price (P2) > Cost (C2) > Exchange (E2) 0.49 9.49 0.00 Accepted Price (P2)

> Cost (C2) > Exchange (E2) > Purchase Intention 0.00 0.02 0.99 Rejected Place (P3) > Convenient (C3) > Everyplace (E3) 0.29 4.11 0.00 Accepted Place (P3) > Convenient (C3) > Everyplace (E3) > Purchase Intention 0.16 3.32 0.00 Accepted Promotion (P4) > Communication (C4) > Evangelism (E4) 0.42 8.14 0.00 Accepted Promotion (P4) > Communication (C4) > Evangelism (E4) > Purchase Intention 0.01 0.17 0.87 Rejected

Table 6. Results of Structural model analysis for Total Effect – Generation Z 4Ps to 4Es (via 4Cs) Original Sample T Statistic P Values Result 4Ps to Purchase Intention (via 4Cs and 4Es) Original Sample T Statistic P Values Result Product (P1) > Customer (C1) > Experience (E1) 0.42 8.64 0.00 Accepted Product (P1) > Customer (C1) > Experience (E1) > Purchase Intention 0.12 2.32 0.02 Accepted Price (P2) > Cost (C2) > Exchange (E2) 0.39 7.75 0.00 Accepted Price (P2)

> Cost (C2) > Exchange (E2) > Purchase Intention -0.03 0.58 0.56 Rejected Place (P3) > Convenient (C3) > Everyplace (E3) 0.34 6.29 0.00 Accepted Place (P3) > Convenient (C3) > Everyplace (E3) > Purchase Intention 0.06 1.48 0.14 Rejected Promotion (P4) > Communication (C4) > Evangelism (E4) 0.39 7.18 0.00 Accepted Promotion (P4) > Communication (C4) > Evangelism (E4) > Purchase Intention 0.06 1.46 0.14 Rejected

Sample) showed the significant total effect comes from Price (P2) to Exchange (E2) via Cost (C2) and Product (P1) to Experience (E1) via Customer (C1), but it not driving to purchase intention directly, with only one significant total effect comes from Place (P3), Convenience (C2) and Everyplace (E3) path, to Purchase intention. The total effect for marketing-mix evolution theories where advancements from the 4Ps to 4Cs and 4Es for Generation Y (Table 5) are statistically significant for all paths, but the next paths of total effect to purchase intention, highlighting differences, only Place, Convenience and Everyplace path to Purchase intention (Original Sample = 0.16, T Statistic = 3.32, and P Values = 0.00) are statistically significant, identifies Generation Y as a “Pragmatic Converters,” they focus on an easy to access, availability,traditional one to-one relationships as the primary drivers of their intent to purchase, whereas social media operates on a many-to-many basis, often results in a more passive audience for this generation (Allcott et al., 2020; Tran & Bui Thanh Khoa, 2025). While traditional approaches and active interaction continue to influence purchase intentions, companies must address the distinct preferences and concerns of each digital generation to strengthen trust and drive sustained, meaningful customer behaviour which can often result in a more passive audience platforms (Allcott et al., 2020). For Generation Z, the total effect for marketing-mix evolution theories where advancements from the 4Ps to 4Cs and 4Es for Generation Y (Table 6) have successfully evolved for all paths. In contrast, for the next paths of total effect to purchase intention, only the path coefficient from Product (P1) to Experience (E1) via Customer (C1), and it driving to purchase intention directly (Original Sample = 0.12, T Statistic = 2.32, and P Values = 0.02), showed the strongest total effect. The primary significant driver is the Product, Customer and Experience path, more influenced by specific features, quality, or value proposition of the product compared to the other marketing mix elements. Social media has transformed engagement and revolutionized marketing practices by facilitating content sharing, interactivity, customer service, and feedback, thereby enhancing brand interaction and customer experience (Hallock et al., 2019; Miah et al., 2022; Moon & Iacobucci, 2022). The significant total effect from Product, Customer and Experience path to Purchase intention identifies Generation Z as a “Sceptical Advocates,” they seek experiential depth and high-value information as a form of shareable social currency to navigate baseline consumer scepticism (Allcott et al., 2020; Kozłowski, 2024; Tran & Bui Thanh Khoa, 2025). This pattern

Generation Y (n=176) Generation Z (n=196)

Figure 3. Results of Structural model analysis for Hypothesis: Marketing Mix Evolution from the 4Ps to the 4Cs and finally to the 4Es (H1 and H2). Generation Y (n=176) Generation Z (n=196)

Figure 4. Results of Structural model analysis for Hypothesis: Marketing Mix 4Es positively affects Purchasing Intention (H3).

suggests that, for Generation Z, foundational product utilities strongly associate with customer-centric perceptions, which in turn connect with experiential engagement to ultimately relate to purchase intentions. Generation Z as a Sceptical Advocates, a behavioural archetype defined by deep-seated doubt toward marketing effectiveness and a demand for high- value product experiences (Kozłowski, 2024). Importantly, these relationships reflect static, non-causal correlations rather than a definitive timeline of behavioural transformation. This generational segment appears to navigate a baseline of consumer scepticism by aligning their purchase intent with experiential depth and creative, efficient brand delivery. Companies must create value for customers and spark their interest in products by being more creative and efficient in reaching their target (Casado-Aranda et al., 2022). Ultimately, companies must focus on creating engaging social media while simultaneously building brand trust and experiential depth. Interpretation of Key Findings The accepted relationship between these frameworks demonstrates a linear evolutionary chain. The 4Ps provide the infrastructure, the 4Cs provide the relevance, and the 4Es provide the emotional resonance (Figure 3). Within this framework, Experience replaces Product and Customer, today's customers prioritize memorable interactions over mere functional features (Addis, M. et al., 2022). Exchange replaces Price and Cost, value is no longer a one-way transaction but a co-creation process where the customer’s time and participation enhance perceived value (Konhäusner et al., 2021). Everyplace replaces Place and Convenience, the ubiquitous nature of digital access grants customers the right to shop anytime and anywhere, this requires brands to capture attention across all physical and digital or "Phygital" touchpoints (Addis, M. et al., 2022; Fetherstonhaugh, 2009). Finally, Evangelism replaces Promotion and Communication, redefine promotion as an evolved form of word-of-mouth, where loyal advocates drive the brand narrative through social validation (Konhäusner et al., 2021). While literature often interprets this progression as a transition toward a mature "experiential marketing mix" (Addis, M. et al., 2022), these patterns should be viewed as interconnected strategic dimensions rather than a universal or absolute pinnacle of marketing maturity. However, rather than establishing a universal pinnacle of marketing maturity, these frameworks represent interconnected strategic variables bounded by distinct methodological limitations. Because these findings rely on a cross-sectional research design, the documented pathways reflect static statistical correlations captured at a single point in time rather than definitive chronological transformations over time. The evolution and spread of digital technologies have structurally shifted customer experiences from offline to online environments, led to the rise of new consumer interactions that combines the characteristics of physical and digital ("phygital") settings (Addis, M. et al., 2022). This paradigm shift refocuses the marketing mix onto customer experience, everyplace, exchange, and evangelism, highlighting an essential transition from a traditional product-centric approach to a comprehensive, experience marketing. The results of this research indicate that the evolution of the marketing mix from the 4Ps to the 4Es exerts a significant positive influence on consumer behavioural intentions, allowing for a highly granular, multi-generational comparison between Generation Y and Z within the rapidly changing Indonesian phygital context (Silalahi & Heryjanto, 2023). This perspective recognizes the critical role of customer experience in influencing consumer behaviour, brand loyalty, and post-purchase satisfaction (N. Chen & Yang, 2023; Gerlich, 2023). However, since customers have evolved, companies must consider designing experiences instead of products because we have entered a new era in digital experiences, shift from the functional and economic benefit toward a more experiential approach (Addis, M. et al., 2022). 4Ps 4Cs 4Es H1a H2a H3a H3b 4Cs H1b H2b H1c H2c H3c H3d H1d H2d Product Price Place Promotion Customer Cost Convenience Communication Experience Exchange Everywhere Evangelism Purchase Intention 4Ps 4Cs 4Es H1a H2a H3a H3b 4Cs H1b H2b H1c H2c H3c H3d H1d H2d Product Price Place Promotion Customer Cost Convenience Communication Experience Exchange Everywhere Evangelism Purchase Intention 4Ps 4Cs 4Es H1a H2a H3a H3b 4Cs H1b H2b H1c H2c H3c H3d H1d H2d Product Price Place Promotion Customer Cost Convenience Communication Experience Exchange Everywhere Evangelism Purchase Intention 4Ps 4Cs 4Es H1a H2a H3a H3b 4Cs H1b H2b H1c H2c H3c H3d H1d H2d Product Price Place Promotion Customer Cost Convenience Communication Experience Exchange Everywhere Evangelism Purchase Intention

Social media has transformed engagement and revolutionized marketing practices by facilitating content sharing, interactivity, customer service, and feedback, thereby enhancing brand interaction and overall customer experience (Hallock et al., 2019; Miah et al., 2022; Moon & Iacobucci, 2022). According to Casado-Aranda et al. (2022), such technology has encouraged companies to compete in triggering customer value, rewards, and interest to market products and efficient approaches to reach targets. Although they may find the complexity in large amounts of similar and repetitive information, posing a challenge to the credibility of the information (Djohan Gunawan & Prihanto, 2026). Consequently, companies should implement customized strategies to engage both Generations Y and Z within evolution of marketing mix framework from the 4Ps to the 4Cs and ultimately to the 4Es to influence purchase intention (Figure 4). Generations Y's purchase intention is anchored in frictionless utility, as evidenced by the significant Place to Convenience and to Everyplace pathway. Generation Y as Pragmatic Converters approaches digital spaces with transactional logic, they utilize traditional, structured one-to- one digital relationships to minimize purchase friction (Allcott et al., 2020; Tran & Bui Thanh Khoa, 2025). Business must prioritize structural and logistical optimization by implementing a frictionless transactional architecture (e.g., seamless checkout, one-click purchasing), guaranteeing omnichannel availability and delivery reliability via synchronized live inventory systems, and maximizing payment convenience through integrated mobile wallets and localized digital gateways. Generations Z operate as "Sceptical Advocates" because their Product to Customer to Experience pathway demands empirical validation. They heavily scrutinize core product features before engaging. However, once this scepticism is disarmed through creative, efficient, and transparent brand interactions (Casado-Aranda et al., 2022). For Generations Z, the experiential journey is a form of shareable social currency (Allcott et al., 2020; Kozłowski, 2024). Brands must deploy trust-building, experiential strategies. This involves provisioning searchable product evidence and transparent, unedited customer reviews to satisfy their demand for empirical verification, collaborating on authentic creator content that showcases real-world product utility over polished corporate ads, and designing shareable digital experiences (e.g., immersive AR trials or gamified challenges) that provide inherent social currency and incentivize organic advocacy. To capture both markets effectively, companies need to address the distinct preferences and concerns of each generation to strengthen trust and encourage sustained, meaningful customer behaviour in personal and subjective, shaped by individual perceptions and a range of emotions arising during pre-purchase and post-purchase interactions (Purnamaningsih & Rizkalla, 2020; Vazquez et al., 2020). These emotional responses affect how customers perceive brands, form preferences, and make decisions, ultimately shaping their overall experience (Hamid et al., 2023).

Limitations and recommendations for Future Research While this research offers valuable insights into marketing-mix transitions across digital generations, its findings are bounded by several explicit methodological limitations that direct clear pathways for future inquiry. The empirical model relies on non-probability accidental sampling within a single-country context (Indonesia), which restricts universal generalizability, alongside a cross-sectional design that captures static statistical associations rather than definitive causal transformations over time. Furthermore, the data collection was also constrained by a forced-choice 4- point Likert scale, which lacks a neutral midpoint and potentially omitted nuanced neutral sentiments. To address these specific boundaries, future research should employ probability sampling methods across multi-country contexts, adopt longitudinal designs to track temporal behavioural shifts, and utilize 5-point or 7-point Likert scales alongside multi-wave data collection to capture neutral sentiments and further minimize common-method variance. Finally, future frameworks should integrate specific stages of the customer journey as control variables—such as the AIDA or AISAS models—to map how the behavioural tracks of "Pragmatic Converters" and "Sceptical Advocates" unfold dynamically across physical and digital touchpoints. Conclusion This research aims to compare the impact of social media on the evolution of the marketing mix from the 4Ps to the 4Cs and finally to the 4Es, highlights the need of understanding the similarities and differences in how the 4Es impacts the purchase intention between generations Y and Z, offering strategic insights for designing marketing strategies that effectively engages both digital cohorts. First, social media significantly impacts both the marketing evolution and purchase intention by shifting the focus from traditional 4Ps (product-centric) to the emotional marketing of the 4Es (customer-focused) perspective of Generations Y and Z. The data demonstrate that the traditional 4Ps function as an operational infrastructure that significantly associates with the customer-centric 4Cs, which in turn relates to the experiential outcomes within the 4Es framework across both cohorts. However, instead of showing that social media definitively or universally alters the entire consumer journey, the structural models uncover critical path-specific differences between the two groups. For Generation Y, identified as "Pragmatic Converters," purchase intention is significantly associated with the Place to Convenience to Everyplace pathway, indicating that their buying intent is anchored in direct accessibility and utility, even though they remain a relatively passive audience within decentralized, many-to-many social media networks. In contrast, Generation Z, operating as "Sceptical Advocates," exhibits an intentional pattern where the Product to Customer to Experience path is highly significant; their purchase intent is strongly tied to initial product validation and high-value, shareable experiences that serve as digital social currency to overcome inherent marketing scepticism. Consequently, companies cannot assume a universal evolutionary shift; instead, they must implement cohort-specific strategies that maximize functional accessibility and seamless convenience to engage Generation Y pragmatists, while delivering transparent, deeply experiential content to satisfy the specific trust and engagement criteria of Generation Z sceptics. Second, the research concludes that marketing has entered a period of experiential marketing, characterized by a linear evolutionary chain of marketing mix from 4Ps, to 4Cs and ultimately culminating in the 4Es. Rather than establishing a universal market condition, the results of this cross-sectional survey suggest that "experiential maturity" is best understood as a conceptual interpretation within the sampled Indonesian Generation Y and Z cohorts. The empirical data demonstrate a significant structural alignment along the 4Ps, 4Cs and 4Es path sequence for both groups, indicating that traditional operational infrastructures are strongly associated with customer-centric relevance, which in turn relates to experiential dimensions. For these specific Indonesian digital-native segments, this interconnectedness reflects a localized strategic transition where memorable interactions, co-created value, and phygital ubiquity are highly correlated with the overall framework. For these specific Indonesian digital-native segments, this interconnectedness reflects a localized

strategic transition where memorable interactions, co-created value, and phygital ubiquity are highly correlated with the overall framework. However, the final link to behaviour is strictly path-specific rather than universally holistic: the tested results reveal that this experiential maturity heavily relates to purchase intention only for Generation Z via the statistically significant Experience to Purchase Intention path, whereas it is statistically rejected for Generation Y, who instead prioritize the utility, driven Everyplace pathway. Consequently, within the rapidly changing Indonesian phygital landscape, marketing strategies should not treat experiential marketing as a uniform evolutionary law, but rather as a contextualized framework where localized social validation and brand evangelism must be selectively deployed to match the distinct, statistically supported behavioural tracks of each cohort. Third, the research concludes that this evolution necessitates a dual-strategy approach to address the distinct behavioural archetypes of digital natives. Generation Y as Pragmatic Converters, purchase intent is primarily triggered by "Everyplace" accessibility and seamless convenience, and Generation Z as Sceptical Advocates, prioritizes rigorous information-seeking and high-value product experiences as shareable social currency. As a result, marketing strategies must focus on leveraging social media to foster interactivity and co-created value while navigating the challenges of information credibility, brands can address the unique emotional responses and subjective perceptions of each generation to drive sustained trust and meaningful customer behaviour between Generation Y and Z within the rapidly changing Indonesian phygital context.

Author contributions The authors declare that no additional data was generated in this work beyond the survey responses collected. Individual responses cannot be shared due to ethical and privacy concerns, in accordance with our commitment to protecting participant confidentiality. All authors have read and agreed to the published version of the research output. The contributions of the authors are grouped into two functions: lead and supporting roles. The first author contributed as a lead in the overall process, including conceptualization, resource provision, supervision, and the primary drafting the paper. The second and third authors served in supporting roles provided essential support through data collection, technical analysis, results interpretation, and the critical reviewing and editing of the paper

Acknowledgements We sincerely thank Universitas Multimedia Nusantara for their generous support throughout this research project. Their assistance provided essential resources and research tools, enabling us to conduct the study effectively. We appreciate the university's commitment to advancing research and fostering an environment conducive to academic inquiry and collaboration.

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