Generation Z has emerged as a pivotal consumer segment with substantial purchasing power and increasing market influence, projected to become the largest consumer group in the near future. The impact of service innovation on Generation Z customers’ repurchase intention is examined in the study, with value co-creation as a mediating factor.
Data were collected through an official questionnaire, yielding 1,393 valid responses from Generation Z participants in Vietnam with diverse locations, gender and educational backgrounds. The analysis was conducted using partial least squares structural equation modeling (PLS-SEM) SmartPLS 4 software.
The results confirm that value co-creation mediates the relationship between service innovation and repurchase intention, highlighting its critical role in enhancing the effect of service innovation on Generation Z consumer loyalty.
This study addresses a gap in the literature by exploring how service innovation can be leveraged to foster repurchase intention among Generation Z consumers. It provides theoretical and practical insights into promoting loyalty through supportive service innovation and value co-creation in the context of an emerging economy.
1. Introduction
Generation Z, born between 1995 and 2010, comprises more than 2 billion individuals globally, representing over 30% of the world's population and about 27% of the workforce (Koop, 2021). This demographic exhibits distinctive consumption behaviors across cultures, prioritizing authentic experiences, digital engagement and participatory brand relationships (Francis and Hoefel, 2018; Priporas et al., 2017). In Vietnam, this global trend is evident, with forecasts indicating that Generation Z will constitute one-third of the working-age population by 2025, totaling nearly 15 million individuals (GSO, 2019). As a result, Generation Z has emerged as a critical group with significant purchasing power and influence on the market in the future and is expected to be the largest consumer group (Do et al., 2023; Huyen, 2021).
The unique consumption style and habits of Generation Z pose challenges for companies, as this group prioritizes experiences and holds high expectations for products of interest while showing limited commitment to repurchase intention or brand loyalty (Ismail et al., 2021; Williams and Page, 2011). To meet these expectations, companies must address resource constraints, as satisfying customer demands can be costly (Edvardsson and Tronvoll, 2013). It is suggested by research that retaining existing customers is a cost-effective strategy for achieving high efficiency compared to focusing solely on acquiring new customers.
At the same time, the existing literature demonstrates that service innovation significantly influences consumer behavior, particularly regarding repurchase intention and brand loyalty (YuSheng and Ibrahim, 2020). However, the Vietnamese market context presents unique characteristics that warrant specific investigation. Vietnamese market research reveals that logistics service innovations directly influence Generation Z repurchase behavior, with backend service capabilities proving particularly crucial in emerging economy contexts (Vu and Nguyen, 2025). Furthermore, Vietnamese firms often demonstrate limited understanding of innovation implementation, constraining their ability to fully capitalize on service innovation opportunities (Phan, 2014). This limitation becomes especially critical as Vietnam transitions toward an innovation-driven service economy, where understanding consumer response mechanisms to service innovation represents both a business imperative and a strategic national priority.
Furthermore, service innovation is defined as the creation of new value propositions through developing existing practices and resources, creating entirely new ones or integrating existing practices and resources in novel ways (Skålén et al., 2015). The positive effects of service innovation on customer repurchase intention will increase when businesses demonstrate respect and satisfy customer demand by facilitating customer participation. When creating the products, customers act as co-creators of value and are active creators instead of passive value recipients, and companies act as facilitators rather than value creators (Chen and Wang, 2016). The active involvement of customers in the value co-creation process significantly influences their satisfaction with the service (Vega-Vazquez et al., 2013). Therefore, successful service innovation not only boosts customers' repurchase intentions but also creates a long-term competitive advantage for companies in today's competitive business landscape.
Despite growing recognition of service innovation’s importance and value co-creation as a strategic imperative, empirical investigations into these relationships among Generation Z consumers remain limited. The mechanisms through which service innovation influences repurchase intention, particularly the mediating role of value co-creation, remain underexplored in emerging economies like Vietnam. The present study addresses these research gaps by examining the interplay between service innovation and its influence on repurchase intention among Vietnam’s Generation Z consumers through value co-creation. This investigation is guided by two critical research questions:
To what extent do supportive service innovation and interactive service innovation influence Generation Z customers' repurchase intention through value co-creation?
How does value co-creation mediate the relationship between service innovation and Generation Z customers' repurchase intention?
This study comprises seven parts: introduction, literature review, hypothesis development and research model, methodology, results, discussion and conclusion with implications and limitations.
2. Literature review
2.1 Theoretical background
In today's competitive world and rapidly shifting business environment, the power of retailers and the level of customer demand are increasing daily. Producers must maintain long-term customer relationships to survive in such a competitive environment. This literature review assesses key concepts including service innovation, value co-creation and repurchase intention to establish the study's framework.
In this context, the Service-Dominant Logic (SDL) proposed by Vargo and Lusch (2008) represents a paradigm shift from goods-dominant logic to service-centric value creation, positioning service as the fundamental basis of exchange. Unlike traditional goods-dominant logic that focuses on separation and control of actors to optimize tangible outcomes, SDL emphasizes collaborative value creation through resource integration between service providers and customers. This framework is particularly relevant for Generation Z consumers, who actively seek participatory and experiential consumption rather than passive receipt of pre-defined offerings.
2.2 Service innovation and value co-creation
The concept of service innovation has been interpreted diversely in research from 1979 to 2014, with three main perspectives: assimilation, differentiation and synthesis. The synthesis perspective is considered the most promising research direction (Miles, 2010). Service innovation is considered a driving force for social innovation and provides a necessary catalyst for developing the service industry and general economic growth (Gustafsson et al., 2020). Furthermore, the increasingly important role of service innovation is evident in numerous studies, such as its role in the companies' performance (Lusch et al., 2007) and competitive advantage (Chen and Wang, 2016).
Value co-creation encompasses behaviors, interactions and experiences driven by collaborative value creation, where consumers assume active roles and create value together with firms (Kohler, 2016) through direct and indirect collaboration across production and consumption stages (Ranjan and Read, 2016). Ranjan and Read (2016) identified two primary dimensions: co-production and value-in-use. Co-production refers to activities undertaken by economic actors in society, facilitated through collaboration and dialogue, integrating common resources to create value and evaluated based on knowledge, equity and interaction. Value-in-use evaluates the customer’s experience and suggests improvements to the product or service beyond its inherent attributes, aligning with their motivations, competencies, actions, processes and performance.
Due to its significance, there is a growing emphasis on the relationship between service innovation and value co-creation, as evidenced by numerous studies. For example, early research by Mele et al. (2010) involved a case study of an innovative Italian firm, which revealed successful innovation where customers and other stakeholders act as true co-innovators, exchanging and integrating resources to co-create value. Additionally, Gustafsson et al. (2020) examined customer co-creation based on four communication aspects: frequency, direction, method and content to understand the value of customer co-creation in service innovation and its impact on product success and whether this impact is contingent on the level of innovation. The findings indicate that three out of four customer co-creations positively influence product success factors in the presence of innovation.
Research on repurchase intention by Hellier et al. (2003) suggests that it is influenced by customer satisfaction, as evidenced in service industry research. Repurchase intention implies a customer’s inclination to maintain a relationship with a specific service provider for future purchases. In marketing, repurchase intention is the subjective probability of a consumer revisiting a store based on their current circumstances (Sullivan and Kim, 2018). Customers tend to consider alternative purchase locations, even if current options offer better prices (Shah et al., 2020). Skepticism toward the seller makes it difficult to convince buyers to return to purchase. Therefore, effective mechanisms in the transaction process are essential for building customer trust and encouraging repurchase behavior.
2.3 Generation Z consumer behavior
Generation Z consumer behavior demonstrates remarkable cross-cultural consistency, challenging traditional assumptions about localized consumption patterns (Anh Do et al., 2023). Empirical research across diverse markets validates convergent behavioral characteristics that transcend geographical boundaries (Francis and Hoefel, 2018). Their digital-native generation's extensive social media utilization creates shared consumption vocabularies and behavioral norms that operate independently of traditional cultural boundaries (Ngo et al., 2024).
In emerging economies like Vietnam, Generation Z consumers demonstrate “global citizen” identities that prioritize international standards for corporate responsibility and social equality, while maintaining consistent expectations for co-creative experiences and participatory value creation. Research on sustainable consumption reveals that Generation Z's demand for ethical brand behavior and participatory service design manifests consistently across cultures, suggesting that their values-driven approach to consumption transcends national boundaries. These consumers also display unique cultural adaptations, blending traditional collectivist values with individualistic digital consumption behaviors, as evidenced by their strong family and peer influences in ethical consumption decisions (Le et al., 2022). These findings collectively suggest that while Generation Z exhibits consistent expectations for participatory and innovative service experiences across cultures, the specific service innovation dimensions that drive repurchase intention may vary based on market maturity and infrastructure development.
This study addresses the research gap regarding value co-creation's mediating role between service innovation and Gen Z repurchase intention, providing comprehensive insights into enhancing customer loyalty through strategic innovation.
3. Hypothesis development
3.1 Supportive and interactive service innovation
Salunke et al. (2013) categorized service innovation into two dimensions: interactive and supportive service innovation, highlighting a close relationship between them. Interactive service innovation involves introducing value-creating changes to the service concept to elicit customers' cognitive, affective and behavioral responses. On the other hand, supportive service innovation involves indirect value-creating changes at the backend to support the new value proposition.
Consequently, a disconnect between interactive and supportive processes creates problems and can negatively impact a company's sales. Despite many critical activities supporting a service being intangible to customers, comprehending how those activities align with customer needs is crucial for ensuring a compelling value proposition. Parasuraman et al. (1985) also emphasize the importance of establishing a connection between the interactive and supportive aspects of service innovation. Similarly, research conducted by Ta and Yang (2018) classified service innovation into interactive and supportive categories in the Vietnamese market, which also implied the impact of support on interactive service innovation.
Therefore, due to the primary objective of this study being to target consumers in Vietnam, the following hypothesis is proposed:
Supportive service innovation positively influences interactive service innovation.
3.2 Service innovation and value co-creation
As service innovation is a value-creating activity, it is evident that innovative products establish a competitive edge for companies, enabling them to meet current and future customer needs and enhance perceived value (Kandampully and Duddy, 1999). Tether et al. (2001) observed that service improvements transform customer perceptions, influencing their view on the services' value, as echoed in other research.
Additionally, an exemplary implementation of the value co-creation process will lead to breakthrough service innovation and provide more effective business solutions (Sheth, 2020). Customers develop ideas for new services or improved service quality during the co-creation process that can meet the basic customer requirements that the service provider has not met or upgraded the services (Banu et al., 2019). Therefore, the ideas obtained from value co-creation are a reflection of customer needs, and the development of innovative services should depend on the understanding of customer needs.
Consequently, when service innovation is viewed as a value-creating activity, its significance is focused on the strong connection between service innovation and customer value co-creation.
Therefore, two hypotheses are proposed to evaluate the impact of service innovation and value co-creation.
Interactive service innovation positively influences value co-creation.
Supportive service innovation positively influences value co-creation.
3.3 Service innovation and repurchase intention
Zeithaml et al. (2010) contend that while service innovation is similar to product innovation, service quality evaluation differs from product quality. Gilkeson and Reynolds (2003) argue that feedback from sellers and buyers, such as store reputation and consumer shopping experience, are crucial resources for prospective consumers in gauging service innovation, reliability, satisfaction and product quality. As a result, when consumers contemplate purchasing services, they reflect on their previous shopping experience and other consumers' reviews of service innovation and product quality at the store. This dual assessment aids in evaluating the product's value and plays a pivotal role in their decision-making process regarding whether to proceed with the purchase. Therefore, consumer perception of service innovation fluctuations directly impacts their intention to repurchase.
Reichheld and Schefter (2000) assert that targeting the right audience is crucial for profitability, as initial consumers have the opportunity to become loyal patrons, making repeat purchases and providing free advertising for sellers.
To examine their influence, two hypotheses are proposed:
Interactive service innovation positively influences repurchase intention.
Supportive service innovation positively influences repurchase intention.
3.4 Value co-creation and repurchase intention
Dong et al. (2008) explored the relationship between co-creation intent and customer repurchase intention and found a positive correlation among the variables. Similarly, Park and Ha (2016) analyzed the positive relationship between co-created value and customer repurchase intention in their research. Dissatisfied customers, or those with low satisfaction levels, exhibit minimal acquisition behavior. However, in such instances, co-creation through active customer engagement, interaction and personalization can significantly impact satisfaction and trust and foster solid relationships between parties, influencing customer loyalty (Bitner et al., 1997).
Thus, a practical method to enhance consumer confidence is facilitating and enhancing their participation in the co-value creation process (See-To and Ho, 2014). Consumer involvement in value co-creation cultivates a high level of trust with the customer, leading to their intention to repurchase. Consequently, the following hypothesis is proposed:
“Value co-creation positively influences customer repurchase intention.”
3.5 The mediating role of value co-creation
Fatima et al.’s (2021) research in telecommunications services has revealed the mediating role of value co-creation in the correlation between interactive and support service innovation and customer repurchase intention. The results of this study have suggested that service innovation will be more effective in retaining customers and increasing their repurchase intention if the activity is aimed at new services with the participation of customers and increases value for stakeholders. Thus, two hypotheses are proposed:
Value co-creation mediates the impact of interactive service innovation on repurchase intention.
Value co-creation mediates the impact of supportive service innovation on repurchase intention.
Figure 1 illustrates the proposed research model in this study.
The model begins with two text boxes on the left. The top text box is labeled “Interactive Service Innovation,” and the bottom text box is labeled “Supportive Service Innovation”. An upward arrow labeled “H 1” connects “Supportive Service Innovation” to “Interactive Service Innovation”. From “Interactive Service Innovation,” a diagonal rightward arrow labeled “H 2 a” connects to the text box in the center labeled “Value Co-creation”. From “Supportive Service Innovation,” another diagonal rightward arrow labeled “H 2 b” also connects to “Value Co-creation”. From “Value Co-creation,” a rightward arrow labeled “H 4” connects to the text box on the far right labeled “Repurchase Intention”. A direct rightward arrow labeled “H 3 a” connects “Interactive Service Innovation” to “Repurchase Intention,” and another direct rightward arrow labeled “H 3 b” connects “Supportive Service Innovation” to “Repurchase Intention”.Research model. Source: Developed by authors
The model begins with two text boxes on the left. The top text box is labeled “Interactive Service Innovation,” and the bottom text box is labeled “Supportive Service Innovation”. An upward arrow labeled “H 1” connects “Supportive Service Innovation” to “Interactive Service Innovation”. From “Interactive Service Innovation,” a diagonal rightward arrow labeled “H 2 a” connects to the text box in the center labeled “Value Co-creation”. From “Supportive Service Innovation,” another diagonal rightward arrow labeled “H 2 b” also connects to “Value Co-creation”. From “Value Co-creation,” a rightward arrow labeled “H 4” connects to the text box on the far right labeled “Repurchase Intention”. A direct rightward arrow labeled “H 3 a” connects “Interactive Service Innovation” to “Repurchase Intention,” and another direct rightward arrow labeled “H 3 b” connects “Supportive Service Innovation” to “Repurchase Intention”.Research model. Source: Developed by authors
4. Methodology
The study was approved by ethics committee of the Research Management Department, National Economics University, Vietnam. The study followed ethical procedures, which involved acquiring introductory letter from the ethics committee and securing permission to gather data. Involved participants were provided with a verbal consent that clearly outlined the research's primary objectives and underscored the significance of their voluntary participation in contributing to the study's success. The verbal consent form explicitly stated participants’ autonomy to withdraw from the study at any point, ensuring their involvement remained voluntary.
4.1 Process research
In the study, qualitative and quantitative methods were used to develop the research scale and assess the results. Qualitative approaches are utilized to explore further, enhance the original scale and modify it to better suit survey participants. During the qualitative research phase, the authors utilized the in-depth interview method, which offers several advantages of semi-structured interviews. The authors conducted in-depth interviews with 15 Generation Z customers who had utilized the service, encompassing individuals from the North, Central and South regions with diverse gender and educational backgrounds. The primary objective was to evaluate the comprehensiveness and scale of the proposed research model. Quantitative methods were employed to finalize and evaluate the preliminary scale. Upon refining the research scale to its completed form, a pilot survey was conducted involving 50 customers to make adjustments if the questionnaire's content and meaning required clarification due to overlapping interpretations with the preferences of the majority of Generation Z customers.
4.2 Measurements
After evaluating the reliability and discrimination of the factors gathered during the pilot survey, the scale was completed, including: interactive service innovation, supportive service innovation, value co-creation and repurchase intention. The 5-point Likert scale was applied, corresponding to completely disagree to completely agree. Specifically, the process of building the scale is as follows:
For the service innovation factor, the independent factor of supportive service innovation only inherits 5/6 of the observed variables of the original by Salunke et al. (2013) because one observed variable did not warrant reliability standards while the scale of interactive innovation was retained. In terms of the value co-creation factor, in the initial study of Ranjan and Read (2016), the research team received feedback from survey participants about the existence of content neutrality between some questions combined with the results of preliminary survey analysis to check the reliability of Cronbach Alpha, did not meet the standard. Therefore, the author retained 10 observed variables represented by the first-order factor Co-production and retained 5/11 observed variables represented by the first-order variable value in use. Based on the research of Hellier et al. (2003), three factors were proposed to influence repurchase intention. Interviews with respondents and pilot surveys showed that Generation Z customers conducted preliminary quantitative analysis, inherited three factors and developed two factors. The results of the preliminary quantitative assessment showed that all five factors met the conditions for retention and formal quantitative analysis. All Cronbach's Alpha values exceeded 0.8, confirming good reliability, with measurement scales detailed in Table 1.
The current scale
| Factors | Item code | Items | Source |
|---|---|---|---|
| Interactive Service Innovation | ISI1 | The way the company interacts with customers | Salunke et al. (2013) |
| ISI2 | Areas of expertise that the company offers | ||
| ISI3 | How the services you provide are delivered | ||
| ISI4 | The speed at which the company provides the service | ||
| ISI5 | The image of the company | ||
| ISI6 | The degree of flexibility of the product or service | ||
| Supportive Service Innovation | SSI1 | The way the company evaluates service quality is innovative | |
| SSI2 | The nature of the technology the company uses to create the service | ||
| SSI3 | Cooperate with other organizations | ||
| SSI4 | Company complaint resolution process | ||
| SSI5 | The company's employee training process solves problems | ||
| Co-production (Value co-creation) | CP1 | Be willing to receive new ideas and suggestions to improve the current or work towards developing a new product | Ranjan and Read (2016) |
| CP2 | Provide complete information and illustrations | ||
| CP3 | Be willing to spend time and effort to share ideas and suggestions with others to help further improve products and processes | ||
| CP4 | Provide the right environment and opportunities to generate suggestions and ideas | ||
| CP5 | Easy access to necessary information | ||
| CP6 | Processes at the company are consistent with requirements | ||
| CP7 | Play an important role as the product owner in the process | ||
| CP8 | Share an equal role in final product decisions | ||
| CP9 | The party that enables full interaction with consumers in business processes (product development, marketing, support of other customers, etc.) | ||
| CP10 | To get maximum benefit from the process (or product), take a proactive role in the interaction | ||
| Value in use (Value co-creation) | VU1 | It was a memorable experience | |
| VU2 | Strive to serve the individual needs of each consumer | ||
| VU3 | Consumers can improve the process by experimenting and trying new things | ||
| VU4 | Provides a good overall experience, beyond “functional” benefits | ||
| VU5 | Relationship with party | ||
| Repurchase Intention | RI1 | Intent to continue to purchase | Hellier et al. (2003) |
| RI2 | The ability will actually purchase | ||
| RI3 | Chance of will continue to purchase | ||
| RI4 | Plan to continue doing business | Author’s compilation | |
| RI5 | Will recommend to other people |
4.3 Data collection and analysis
The qualitative research findings indicate a clear link between service innovation and the repurchase intent of Generation Z customers. The team conducted initial quantitative research involving 50 Generation Z customers in Hanoi to validate the qualitative results.
Given the complexity of the model and its inclusion of higher-order constructs, the study adopted the PLS-SEM approach, utilizing SmartPLS 4 software for analysis. The analysis proceeded in four stages. The initial stage focuses on evaluating the measurement model, ensuring the reliability and validity of both formative and reflective constructs. This involves assessing indicator reliability, internal consistency reliability, convergent validity and discriminant validity for reflective constructs while examining collinearity and the significance of indicator weights for formative constructs. Additionally, common method bias is assessed to ensure the integrity of the data. The second stage evaluates the structural model using criteria such as collinearity, significance and path coefficients, f2, R2 and PLS prediction. Third, it analyzes the mediating roles of two variables. Finally, it uses ANOVA tests to explore differences in repurchase intentions among Generation Z customers based on demographics.
This study used the inverse square root method, recommended for the PLS-SEM analysis method by Sarstedt et al. (2021) to determine the size of the Minimum sample, with a significance of 5%, minimum path coefficients in the range of 0.05–0.1 and a power of 80%, the minimum sample size is 619. Actual data were collected from 10/2023–02/2024 using the convenience sample method and combining direct data collection in crowded places and online via forms. To ensure the representativeness of Gen Z customers in Vietnam, the research team implemented several strategies: clearly defining Gen Z as individuals born between 1995 and 2010; diversifying data collection locations across major cities; distributing online surveys through popular social media platforms; monitoring and adjusting sample demographics to reflect Gen Z characteristics and applying quality control measures to eliminate unsuitable responses. The research team gathered data from universities, shopping centers and entertainment venues while also leveraging social media platforms to reach a broader geographical spread. After screening for age appropriateness, completeness and consistency, the final sample comprised 1,498 responses. Of these, 105 surveys were deemed invalid due to various reasons, including lack of information, inconsistent answers, response patterns indicating lack of engagement (such as straight-lining where respondents choose the same answer for all questions, or zigzag patterns where they alternate between two responses regardless of the question content). This rigorous screening process resulted in a final valid sample of 1,393 responses, ensuring the quality and relevance of the data for analysis.
5. Result
5.1 Assessment of the measurement model
Table 2 presents the results of the measurement model with three reflective variables: co-production, value in use and repurchase intention. Their observed variables were evaluated to have positive significance, indicated by outer loadings exceeding 0.7 (Hair et al., 2019). Analysis conducted through the software indicates that all observed variables associated with these three factors exceed 0.8, with the smallest RI2 reaching 0.805. This finding demonstrates the substantial significance of all observed variables.
Assessment of first-order, reflective constructs
| Reflective constructs | Items coding | Outer loadings | Rho_c | Cronbach's alpha | AVE |
|---|---|---|---|---|---|
| Co-Production | CP1 | 0.853 | 0.965 | 0.960 | 0.735 |
| CP10 | 0.859 | ||||
| CP2 | 0.853 | ||||
| CP3 | 0.852 | ||||
| CP4 | 0.864 | ||||
| CP5 | 0.860 | ||||
| CP6 | 0.852 | ||||
| CP7 | 0.865 | ||||
| CP8 | 0.856 | ||||
| CP9 | 0.862 | ||||
| Value in Use | VU1 | 0.874 | 0.935 | 0.914 | 0.743 |
| VU2 | 0.858 | ||||
| VU3 | 0.861 | ||||
| VU4 | 0.856 | ||||
| VU5 | 0.862 | ||||
| Repurchase Intention | RI1 | 0.814 | 0.911 | 0.878 | 0.671 |
| RI2 | 0.805 | ||||
| RI3 | 0.815 | ||||
| RI4 | 0.826 | ||||
| RI5 | 0.837 |
Additionally, the reliability test results for the formative variables indicate strong reliability, with all factor structures surpassing the recommended thresholds of Cronbach's alpha reliability coefficient and composite reliability coefficient (Rho_c) exceeding 0.7. Overall reliability is further confirmed through the Rho_c and Cronbach's Alpha coefficient. Repurchase intention demonstrates the lowest reliability, with Cronbach's Alpha value at 0.878 and Rho_c at 0.911, indicating high-scale reliability that warrants retention for subsequent analysis steps.
Regarding convergence, in line with Hock and Ringle (2010), the scale establishes convergent validity if the AVE reaches 0.5 or higher, suggesting that the average latent variable explains at least 50% of the variation in variables. In this model, the AVE value of the outcome variable exceeds 0.6, indicating a solid convergence among the observed variables.
The analysis revealed that all other observed variables exhibited significant results except for the ISI1 variable with a p-value of 0.052, which exceeds the 0.05 significance threshold. Further examination of the outer loading value of ISI1 revealed a value of 0.848, indicating its continued significance. Regarding the quality of observed variables presented in Table 3, all 20 observed variables across the three factors exhibit high quality, with outer loadings consistently above 0.8.
Assessment of first-order, formative constructs
| Formative constructs | Items | p-values (Outer weight) | Outer loadings | VIF |
|---|---|---|---|---|
| Interactive Service Innovation | ISI1 | 0.052 | 0.848 | 2.516 |
| ISI2 | 0.039 | 2.390 | ||
| ISI3 | 0.019 | 2.728 | ||
| ISI4 | 0.044 | 2.377 | ||
| ISI5 | 0.004 | 2.395 | ||
| ISI6 | 0.012 | 2.385 | ||
| Supportive Service Innovation | SSI1 | 0.001 | 2.839 | |
| SSI2 | 0.000 | 2.525 | ||
| SSI3 | 0.001 | 2.757 | ||
| SSI4 | 0.003 | 2.576 | ||
| SSI5 | 0.000 | 2.672 |
To assess discriminant validity, Henseler et al. (2015) propose an alternative perspective on assessing discriminant validity. If the HTMT index of a pair of factors exceeds 0.9, it indicates a violation of factor differentiation. The analysis presented in Table 4 reveals that all three variables have HTMT index values below 0.9, except Co-production and Value co-creation due to this second-order construction, while VU exhibited the highest value at 0.878, within an acceptable threshold.
Assessment of discriminant validity
| Factor | Heterotrait-monotrait ratio (HTMT) | Fornell-Larcker | ||||||
|---|---|---|---|---|---|---|---|---|
| Co-production | Repurchase intention | Value co-creation | Value in use | Co-production | Repurchase intention | Value co-creation | Value in use | |
| Co-Production | 0.858 | |||||||
| Repurchase Intention | 0.646 | 0.593 | 0.819 | |||||
| Value Co-Creation | 1.000 | 0.694 | 0.964 | 0.634 | 0.785 | |||
| Value in Use | 0.662 | 0.616 | 0.878 | 0.621 | 0.552 | 0.806 | 0.862 | |
Common method bias in PLS-SEM occurs when the measurement method, not the network of causes, influences results. This phenomenon can stem from questionnaire instructions or social desirability in responses, causing shared indicator variation. Kock and Lynn (2012) introduced the full collinearity test to assess both vertical and lateral collinearity simultaneously. This automated procedure generates variance inflation factors for all latent variables. A high VIF indicates pathological collinearity and potential common method bias. If all VIF from the full collinearity test are 3 or lower, the model is considered free from common method bias, ensuring more reliable results in PLS-SEM analysis (Table 5).
5.2 Assessment of the structural model
It is imperative to examine multicollinearity before evaluating the model's effects using the VIF (Hair et al., 2019). The result shows that all VIF values are less than 3, the lowest is the inner VIF in relationship between supportive service innovation and interactive service innovation. Therefore, the research model often encounters collinearity.
The coefficient of determination, R2 adjusted (Table 6), signifies the extent to which independent variables explain the variation in a dependent variable within the model. Accordingly, the independent variables explained 42.6% of the variation in repurchase intentions of Generation Z customers.
Coefficient of determination (R2 adjusted)
| R-square adjusted | |
|---|---|
| Interactive Service Innovation | 0.160 |
| Repurchase Intention | 0.426 |
| Value Co-creation | 0.324 |
It is essential to consider the f2 coefficient to assess the significance of an independent variable's impact on the dependent variable. This coefficient measures the effectiveness of each independent variable's influence on the dependent variable (Cohen and Levinthal, 1990). The results presented in Table 7 show that the impact of interactive service innovation on customer satisfaction is very small or non-existent. The impact of support service innovation on the remaining factors in the model is at a medium level. The remaining relationships have a small impact.
Impact efficiency coefficient (f2)
| Interactive service innovation | Repurchase intention | Supportive service innovation | Value co-creation | |
|---|---|---|---|---|
| Interactive Service Innovation | 0.000 | 0.045 | ||
| Repurchase Intention | ||||
| Supportive Service Innovation | 0.191 | 0.032 | 0.271 | |
| Value Co-creation | 0.045 |
To evaluate the predictive power of the independent variable on the dependent variable in the model, Hair et al. (2019) recommend using the root mean square coefficient (RSME). RMSE is the square root of the average of the squared difference between the prediction and the actual observation. To evaluate the model's predictive capacity, it is necessary to compare the RMSE values of each indicator with the RMSE of LM. According to the evaluation standards in Table 8, it shows that the independent variables in the model have high predictive ability except RI2 and ISI4.
Predictive power
| Variables | PLS-SEM_RMSE | LM_RMSE |
|---|---|---|
| RI1 | 0.948 | 0.948 |
| RI2 | 0.909 | 0.906 |
| RI3 | 0.901 | 0.902 |
| RI4 | 0.934 | 0.936 |
| RI5 | 0.917 | 0.921 |
| ISI1 | 0.898 | 0.901 |
| ISI2 | 0.802 | 0.805 |
| ISI3 | 0.809 | 0.810 |
| ISI4 | 0.793 | 0.791 |
| ISI5 | 0.828 | 0.830 |
| ISI6 | 0.855 | 0.856 |
Table 9 shows that supportive service innovation demonstrates significant positive effects on Interactive service innovation, and particularly strong influence on value co-creation. Meanwhile, Interactive Service Innovation also shows positive impacts, albeit to a lesser extent on value co-creation. Notably, Value Co-Creation plays a crucial role in the model, with strong influences on Repurchase Intention. However, the two factors, Interactive and Supportive service innovation, have opposite effects on repurchase intention. While the relationship between Interactive service innovation and repurchase intention is not significant due to p-values exceeding 0.05, on the contrary, supportive service innovation has a positive effect on repurchase intention. Consequently, besides hypotheses H3a, which is not accepted, the remaining hypotheses are accepted. All accepted hypotheses exhibit a positive effect based on the analysis of the coefficients of the original sample. Notably, the most substantial positive impact is observed for value co-creation on repurchase intention.
Result of the structural model
| Hypothesis | Path coefficients | t-statistic | p-values | Result | |
|---|---|---|---|---|---|
| H1 | Supportive Service Innovation → Interactive Service Innovation | 0.400 | 13.820 | 0.000 | Supported |
| H2a | Interactive Service Innovation → Value Co-Creation | 0.189 | 6.436 | 0.000 | Supported |
| H2b | Supportive Service Innovation → Value Co-Creation | 0.467 | 19.210 | 0.000 | Supported |
| H3a | Interactive Service Innovation → Repurchase Intention | 0.017 | 0.560 | 0.577 | Not Supported |
| H3b | Supportive Service Innovation → Repurchase Intention | 0.166 | 16.643 | 0.000 | Supported |
| H4 | Value Co-Creation → Repurchase Intention | 0.541 | 19.210 | 0.000 | Supported |
Regarding the mediating role of value co-creation in the relationship between service innovation and customer repurchase intention, Table 10 shows that the indirect impact of supportive service innovation on repurchase intention demonstrates the strongest effect at 0.253, while interactive service innovation shows a coefficient of 0.102.
Results of evaluating mediate variables
| Hypothesis | β | p-values | Result | ||
|---|---|---|---|---|---|
| H5a | Interactive Service Innovation → Value Co-Creation → Repurchase Intention | 0.102 | 0.000 | Supported | Full Mediation |
| H5b | Supportive Service Innovation → Value Co-Creation → Repurchase Intention | 0.253 | 0.000 | Supported | Partial Mediation |
Baron and Kenny (1986) proposed a method to evaluate the mediating role of the factors in the model. Only indirect-only mediation shows that the mediating role of the factors in the relationship to be tested is the full mediation role, which is consistent with hypothesis H5a. However, the simultaneous existence of direct and indirect effects of supportive service innovation on repurchase intention indicates that Value co-creation plays a partial mediation role in the above relationship.
The ANOVA analysis examining demographic differences shows varying patterns across different characteristics. Gender analysis reveals no statistically meaningful differences in repurchase intention, with p-values exceeding 0.05, indicating that gender categories including male, female and other classifications do not substantially influence repurchase intention among Vietnamese Generation Z respondents. However, the analysis demonstrates statistically significant variation in repurchase intention levels across regional groupings and educational attainment, with p-values below 0.001. These findings indicate that geographical factors within Vietnam and educational backgrounds substantially influence Generation Z consumers' repurchase behavioral patterns.
6. Discussion
This research assesses service innovation's influence on Generation Z customers' repurchase intention, exploring value co-creation dimensions unexplored in previous studies. The results illustrate the significant impact of value co-creation intermediary factors in stimulating repeat purchases among young Vietnamese customers.
The study has demonstrated the positive impact of service innovation on value co-creation (H2a, H2b). Notably, supportive service innovation has shown a more significant influence across the dependent variables, with path coefficients H2b reaching 0.467 compared to 0.189 for H2a. This study also aligns with the findings of Salunke et al. (2013), highlighting the importance of interaction and support in enhancing contribution activities and creating value for young customers.
Our findings support the emergence of a Generation Z-specific service innovation processing model. While Tai et al. (2021) found direct technology-mediated effects in hospitality contexts, our broader service investigation reveals more complex mediation requirements. The supported hypothesis H1, demonstrating supportive service innovation's positive influence on interactive service innovation, establishes a stronger foundational relationship than reported in previous studies (Ta and Yang, 2018), suggesting that Vietnamese Generation Z consumers place exceptional emphasis on integrated innovation approaches.
Most significantly, the lack of direct effect of interactive service innovation on repurchase intention reveals fundamental differences in Generation Z consumer behavior compared to previous studies. This finding corroborates Gunawan et al. (2023) observations of non-significant direct relationships in digital-native segments, but extends their work by providing theoretical explanation through value co-creation mediation. This contrasts sharply with YuSheng and Ibrahim’s (2019) findings in traditional banking contexts, where direct service innovation effects were significant.
The strongest empirical relationship in our model is the impact of value co-creation on repurchase intention, with a coefficient of 0.541 and statistical significance at the 0.001 level, which represents the most substantial pathway to Generation Z customer loyalty and aligns with previous value co-creation studies by Park and Ha (2016). This enhanced relationship strength suggests that Generation Z consumers demonstrate exceptional responsiveness to collaborative value creation opportunities compared to general consumer populations. From a theoretical perspective, our findings validate SDL propositions that value is co-created rather than delivered (Vargo and Lusch, 2008), while revealing generation-specific intensification of these principles where SDL's collaborative value creation premise resonates particularly strongly with digital-native generations who expect interactive, participatory experiences across all consumption contexts.
The findings reveal important differences from the Fatima et al. (2021) study with general customers in Pakistan's telecom industry. For interactive service innovation, Fatima found both direct effects with a coefficient of 0.080 and indirect effects through value creation. Our Generation Z study shows only indirect effects with a coefficient of 0.102 and no direct impact, with a coefficient of 0.017 and p-values exceeding 0.05. This shift from partial to full mediation indicates that Generation Z consumers evaluate interactive features solely through value co-creation rather than accepting them as inherently valuable.
Regarding supportive service innovation, our findings align with the Fatima et al. (2021) partial mediation pattern, where both direct effects and mediated effects through value co-creation exist simultaneously. These results indicate that Vietnamese Generation Z consumers demonstrate enhanced responsiveness to collaborative value creation opportunities. This dual pathway model – where supportive innovations provide both operational utility and engagement facilitation – extends existing literature by demonstrating how generation-specific expectations intensify established theoretical relationships rather than fundamentally altering them.
7. Conclusion
This study examined the mediating role of value co-creation in the relationship between service innovation and Generation Z repurchase intention in Vietnam's emerging service economy. The findings revealed that value co-creation serves as a complete mediator for interactive service innovation and a partial mediator for supportive service innovation, highlighting the critical importance of collaborative value creation in driving customer loyalty among digital-native consumers in emerging market contexts.
7.1 Theoretical implication
This study advances the theoretical understanding of service innovation, value co-creation and consumer behavior by offering novel insights into their interplay among Generation Z consumers in Vietnam.
First, this research refines measurement theory by proposing and validating value co-creation as a second-order construct comprising co-production and value-in-use dimensions. By developing a scale tailored to digital service contexts, the study provides a theoretically robust instrument for capturing the participatory nature of digitally native consumers.
Second, the study enriches service innovation theory by demonstrating the differential effects of interactive versus supportive service innovation dimensions. The finding that supportive service innovation exhibits stronger influence challenges traditional assumptions about customer-facing features being primary drivers of engagement. This theoretical distinction provides new insights into resource allocation strategies and innovation prioritization frameworks for service organizations.
Third, this research advances mediation theory by establishing value co-creation as a complete mediator between interactive service innovation and repurchase intention. This finding shifts theoretical understanding from direct innovation-loyalty relationships to process-dependent mechanisms, suggesting that innovation effectiveness is contingent upon customer engagement facilitation rather than innovation sophistication alone.
Finally, this research extends the theory by examining these relationships within the specific context of Generation Z consumers in Vietnam’s developing service economy. This contextual contribution goes beyond simple geographic extension by theoretically explaining how generational characteristics and cultural factors influence the theoretical relationships in our model. This addresses the call by Tai et al. (2021) for theoretical development in cross-cultural service contexts while providing a theoretical framework for understanding how generational and cultural factors modify established service innovation relationships.
7.2 Practical implication
This research provides practical insights for service businesses in Vietnam to enhance business efficiency by increasing Generation Z customers’ repurchase intentions. The study's broad scope and participants' diverse service experiences allow findings to be widely applicable across service businesses. Crucially, the mediating role of value co-creation indicates that innovation alone will not influence repurchase intentions among Generation Z customers.
First, organizations should implement co-creation-enabled digital platforms rather than traditional innovation approaches. Service providers must design digital systems and delivery mechanisms that inherently facilitate customer participation throughout the service journey, allowing Generation Z consumers to actively contribute to service design and improvement processes. For example, Nasco Logistics has adopted digital booking platforms, real-time tracking systems and AI-powered customer support to streamline operations while offering customized logistics services. Allowing customers to personalize service packages, such as selecting specific shipping routes or preferred delivery times, demonstrates how service providers can effectively implement value co-creation.
Second, service providers must systematically integrate value co-creation opportunities into innovation initiatives. This involves creating visible customer contribution mechanisms, establishing feedback systems demonstrating how customer input influences service development and ensuring Generation Z consumers see tangible evidence of their participation impact.
Third, organizations should explicitly recognize and reward customer contributions throughout the value creation process. Making customer participation visible and valuable transforms consumers from passive recipients to active partners, maximizing the mediating effect of value co-creation on repurchase intentions. This recognition can take forms such as personalized acknowledgments, contribution-based rewards, public recognition of customer input in service improvements or exclusive access to co-created features, fostering deeper emotional connections and loyalty among Generation Z consumers.
Finally, businesses should consider demographic characteristics when developing innovative strategies, tailoring approaches to specific customer groups’ preferences to maximize efficiency in improving repurchase intentions among Gen Z customers.
These implications are broadly applicable across service sectors, providing a generalizable framework for enhancing Generation Z customer retention through strategic value co-creation integration in emerging economy contexts.
7.3 Limitations and future research avenues
Nevertheless, the research team cannot avoid the mistakes that make several study limitations exist. An insufficient sample size prevented the establishment of statistical significance in the two theories regarding the impact of service innovation on Generation Z customers’ repurchase intention. Additionally, as this study broadly applies to service sectors, its generalizability to specific sectors may be limited. Therefore, future studies should explore the implications within the context of specific service sectors in Vietnam.
