Customer empowerment and engagement on sharing platform in the retailing sector: testing the mediating effects of service innovation and platform trust

Abstract

This article aims to investigate the effect of customer empowerment on their engagement on sharing platform in the retailing sector via the mediating role of service innovation and customer trust. This study utilized a quantitative design emphasizing mature theory research. The research sample consisted of 457 customers of sharing platform for the retailing sector, using a partial least square-structural equation model (PLS-SEM) for hypothesis testing. The result reveals that customer empowerment positively and significantly affects customer engagement directly and via service innovation as a mediating mechanism on the sharing platform. However, trust in the platform does not mediate this relationship. It is advisable to retailers on sharing platform to create a leading position in this market by enhancing customer engagement and promoting service innovation via customer empowerment. This paper develops a conceptual framework for customer engagement on sharing platform in the sharing economy via service innovation based on giving empowerment to customers.

Introduction

The retail industry is quickly evolving as a result of technological advancements, from in-store strategies to back-end operations (e.g., warehouses, supply chains) to communication (e.g., websites, social media platform) to merchandise promotion and display, and customer relations (Etemad, 2023; Grewal et al., 2017; Manioudis & Meramveliotakis, 2023; Naidoo & Gasparatos, 2018; Roy et al., 2023; Tilahun et al., 2023; Yang & Hu, 2024). Remarkably, the handshake between merchants and the sharing economy platform is one of the most notable changes in the retail business (Cheng, 2016; Nadeem et al., 2020). The sharing economy, also referred to as the platform economy, gig economy, peer-to-peer economy, access-based economy, or collaborative economy, among others, has emerged as an alternative source of products and services that were previously supplied by established industries (Rojanakit et al., 2022; Rossmannek & Chen, 2023). For more than a decade, the sharing economy has been expanding (Acquier et al., 2017); its economic value was estimated to increase from US$ 15 billion to US$ 335 billion by 2025 (Statista, 2019; World Economic Forum, 2017). The sharing economy platform (SP) are digital service that enables interactions between two or more distinct but interdependent sets of users (whether enterprises or individuals) who communicate through the service via the Internet (OECD, 2019). It spans sectors such as home-sharing (e.g., Airbnb), ride-hailing (e.g., DiDi), car-sharing (e.g., Zipcar), bike-sharing (e.g., Mobike), and fashion-sharing (e.g., My Wardrobe HQ), fashion (e.g., Rent-the-Runway), banking (e.g., Monzo), and medical equipment (e.g., Cohealo) (Rossmannek & Chen, 2023).

Customer engagement (CE) has become a fundamental concept in marketing and consumer research over the past decade (Hollebeek et al., 2022; Lim et al., 2022). Firms strive to engage with clients differently, surpassing mere economic transactions (Pansari & Kumar, 2018), which aims to inspire, enable, and assess a customer's voluntary participation in their marketing operations (Blut et al., 2023). CE, a concept that is intrinsically reciprocal and interactive, can serve as a prominent mechanism for analyzing the relationship between consumers and platform in the sharing economy (Bojovic et al., 2021; Elf et al., 2022; Gregori et al., 2024; Hollebeek & Belk, 2021). In the sharing economy, CE is indicative of macroscopical economic actors (macro-level), platform (meso-level), and service providers (micro-level) (Breidbach & Brodie, 2017). Though research investigating the nature of CE in digital contexts, there is a lack of a unifying framework that provides clear insights into how retailers can optimize their investments in engagement strategies on SP.

RQ1. How do retailers enhance their customer engagement on sharing economy platform?

Consumers in the sharing economy have profoundly altered the business-customer relationship structure (Sawhney et al., 2005; Srivastava et al., 2001; Wang, 2020; Zouari & Abdelhedi, 2021). Besides making a purchase, customers also have the right to leave their reviews on the service quality of retailers, which primarily affects others' decisions and exerts pressure on businesses (Lim et al., 2022; Nadeem et al., 2020). Retailing companies may respond to this circumstance by implementing customer empowerment, a vector of CE (Loureiro et al., 2020; Ramani & Kumar, 2008). Customers in the sharing economy might not have a direct relationship with a salesperson, and trust needs to be established to empower them (Kantsperger & Kunz, 2010). Trust is intertwined with social dimensions and structures, which can only be established and stable over time despite the value of institution-based mechanisms, particularly when transacting with someone for the first time (Lane & Bachmann, 1996). This is not the case for sharing economy marketplaces (Laurell & Sandström, 2017), as the underlying structures and operations of the marketplace may not be well-known to the participating parties (Zamani et al., 2019). The literature has recognized trust's critical role in the sharing economy (Mao et al., 2020; Nisar et al., 2020). However, little empirical research has been conducted despite increasing interest in CE and recognizing that trust is critical in fostering engagement between consumers and service providers (Nyamekye et al., 2022).

The sharing concept has inspired many innovative products/services, which have become ubiquitous in all aspects of public life. The SE requires marketing scholars to reconsider innovation despite the substantial attention that service innovation in traditional services has received in the literature (Witell et al., 2016). The literature on service innovation in the SE has primarily focused on four themes: innovation categories, innovation diffusion and barriers, incumbent response, and innovation consequences (Sanasi et al., 2020). Despite these substantial contributions, there are still relevant research gaps, such as investigating the mediating function of SI in SE (Benoit et al., 2022). Besides, tracing the origins of retailer innovation in/under consumer pressure to materialize their power and engagement has not been clarified by previous studies.

This study aims to investigate the relationship between consumer empowerment and their engagement in sharing economy platform in the retailing sector, with the mediating effects of service innovation and trust. The subsequent sections of this article are organized as follows. This section presents the theoretical background, research framework, definitions of key constructs, and the formulation of hypotheses. The employed methods and procedures for data analysis are subsequently described. The results will be discussed, followed by the presentation of the conclusions. The discussion includes practical implications, limitations, and directions for future research.

Literature review and hypothesis development

Theoretical foundations

The study of CE has been informed by a variety of theoretical perspectives, including organizational psychology (Dwivedi, 2015), regulatory engagement theory (Hollebeek & Chen, 2014), relationship marketing (Bowden and Mirzaei, 2021; Brodie et al., 2011; Vivek et al., 2012), service-dominant logic (Rather et al., 2019), social exchange theory (Hollebeek, 2011), congruity theory (Islam et al., 2018), theory of planned behavior (Bitter et al., 2014), and stimulus-organism response theory (Islam & Rahman, 2017), and self-determination theory (Japutra et al., 2024), among others. The stimulus–organism–response (S–O–R) framework has been extensively employed in the investigation of consumer engagement (Islam & Rahman, 2017; Islam et al., 2020; Kim et al., 2020; Lian, 2021) and has been demonstrated to effectively interface with self-determination theory (STD) (Gu & Duan, 2024). The S–O–R paradigm was formulated by Mehrabian and Russell in 1974, building upon the theory of stimulus–response, suggesting that stimuli in the form of the environment and information influence an individual's responses, which in turn influence their behavior intentions (Bigne et al., 2020). The S–O–R model includes three components: stimulus (inputs), organism (processes), and response (outputs) (Mehrabian & Russell, 1974). Based on these components, customer interactions are expected to impact their engagement (Hossain et al., 2021). We extend the model in this study to include consumer empowerment as the stimulus, as it is a crucial component of the sharing economy platform. The organism operates based on customers' assessments and perceptions, mirroring the internal mechanisms between the stimulus and customers' ultimate reaction (Islam & Rahman, 2017). It is predicated on the innovation of the platform and trust among customers. The S–O–R model's response component represents customer engagement, which is the result of customers' actions and conduct (Ye et al., 2023).

We also employed self-determination theory (SDT) to elucidate how consumers interact with sharing platform. Self-determination theory, theorized by Ryan and Deci (2000), is a theoretical framework that investigates the motivation and characteristics of human behavior. The theory underscores motivational processes, asserting that individual behaviors are shaped by factors that meet their psychological requirements. It implies that autonomy, relatedness, and competence requirements influence individuals' behavioral tendencies. SDT emphasizes the fulfillment of three fundamental human psychological needs: autonomy (the sense of being uncompelled to act and adhere to one's aims and values), competence (the sense of being able and practical), and relatedness (the sense of being connected to others and a sense of belonging). The more customers' needs for autonomy, competence, and relatedness are met, the more they experience self-determination in the regulation of their behaviors, which may lead to increased engagement with the SP. In this study, we extend the S–O–R and SDT in the context of SE.

Customer empowerment and engagement on the sharing economy platform

Marketing literature has extensively addressed the concept of consumer engagement (Brodie et al., 2011; Steinhoff et al., 2023; Vivek et al., 2012). Customer engagement (CE) within the sharing economy is indicative of their level of involvement with macroeconomic actors (at the macro level), platform (at the meso level), and service providers (at the micro level), which is a psychological state that is induced by interactive customer experiences with a focal object (Chen et al., 2022). Marketing scholars have primarily conceptualized CE as a multidimensional construct encompassing cognitive, affective, and behavioral dimensions (Calder et al., 2009). In this study, based on Calder et al. (2009), we concentrate on developing customer-platform engagement based on pertinent consumer experiences, which concentrates on the use of online platform as a means for retailers to establish consumer engagement (Thakur, 2016).

Empowerment is concerned with the enhancement of subjective and endogenous factors, including motivation, trust, intimacy, unity, and identity, in the relationships between enterprises, as well as the improvement of social relations between organizations (Anderson & Berdahl, 2002; Fuchs & Schreier, 2011; Gao & Bai, 2014; Han & Xie, 2023; Reinartz et al., 2019). Customer empowerment outcomes, such as co-creation in the design of products and services, may result in customer engagement because their participation is primarily aimed at meeting their needs (Geyer-Schulz & Meyer-Waarden, 2014). Platform facilitate interactions among multiple entities, including clients and businesses (Wichmann et al., 2022). They facilitate information exchange, product and service sales, and social interaction (Bonina et al., 2021; Wirtz et al., 2019). Enterprises can generate a favorable emotional response from customers, for whom empowerment is synonymous with liberation and independence, by allowing customers to have a crucial role in selecting products and services (Auh et al., 2019). However, the linkage of customer empowerment and engagement on sharing platform still needs improvement.

H1. There is a relationship between customer empowerment and engagement on sharing platform in the retailing sector.

Customer empowerment and engagement on the sharing economy platform: the mediating role of service innovation

Service innovation (SI) refers to the use of new technologies and concepts in the service process to enhance the competitive advantage of enterprises, expand the scope of services, update service content, add new service items, co-creation new value for customers, and change and improve existing services and products (Dung & Dung, 2024; Ordanini & Parasuraman, 2011; Teece et al., 1997; Thrane et al., 2010; Varadarajan, 2024). Generally, innovations, and services innovation in particular, have been categorized according to the degree of change (i.e., radical and incremental innovations) (Snyder et al., 2016) or whether the change is related to a process or an outcome (i.e., service or product (Kumar et al., 2024). In the context of SE, Den Hertog et al. (2010) distinguish six objective objects, including the most appropriate form of service innovation: (i) a revolutionary concept regarding the organization of a solution to a customer's problem or need, (ii) a new customer interaction that pertains to the role customers play in the creation of value, (iii) a new value system or a set of business partners that recognize that a network of providers is increasingly offering new services, (iv) a new revenue model recognize the importance of long-term profitability for innovations, (v) innovations may also be linked to new delivery systems, such as personnel, organization, and culture, (vi) the technological delivery system is the sixth dimension of service innovation, which means that not only interactions with customers (dimension two) but also the entire process of operating, monitoring, or exchanging information with other stakeholders may be affected (Benoit et al., 2022).

Companies with high SI competence may facilitate CE (Chen et al., 2016). In a sharing economy, firms employ platform to enhance innovation procedures, capitalizing on user-generated content and social networks (Ebrahimi et al., 2023). Platform facilitate innovative and practical methods of interaction and collaboration during the innovation process (Testa et al., 2020). When customers engage in buying behaviors on a sharing economy platform, they behave as co-creators of value in exchanging experiences and assessing service quality (Peeroo et al., 2019; Shin & Perdue, 2022; Shin et al., 2020). Through a sharing platform, empowered customers may promote continual innovation within organizations and the long-term viability of the business model (Grawe et al., 2017; Naghi Ganji et al., 2018). However, studies on the sharing platform that focus on SI through customer empowerment and building long-term consumer involvement still need to be updated (Dellaert, 2019; Fu et al., 2017).

H2. Service innovation mediates the relationship between customer empowerment and their engagement on sharing platform in the retailing sector.

Customer empowerment and engagement on the sharing economy platform: the mediating role of trust

Trust is widely discussed in sharing economy research (Breidbach & Brodie, 2017). Trust is present at the individual and meso levels (sharing platform levels) among the three-level micro-meso-macro typology of the sharing economy (Cheng, 2016). Trust is fundamental to the economic model of sharing between users and the platform (Constantiou et al., 2017; Räisänen et al., 2021). On a sharing platform, there may be no opportunity for direct connection between purchasers and vendors throughout the transaction process (Tauscher & Kietzmann, 2017). The typical buying and selling selections might be made considering earlier purchasers' feedback (Hollowell et al., 2019; Williams et al., 2020). Thus, customers in the sharing economy highly trust stakeholders, including service providers, retailers, and platform, while engaging in buying transactions (Hawlitschek et al., 2016).

Placing an emphasis on user trust and transitioning into an open and transparent platform may encourage users to use the platform (Kong et al., 2020). One crucial aspect that constitutes openness and transparency in technological platform is the empowerment of customers (Köbis et al., 2021). Empowered customers may share their views and individual experiences when using the services of a sharing economy. Also, when customers lack direct contact with service providers, relying on previous customer suggestions, instructions, and feedback plays a significant role in establishing customer buying orientations and trust in suppliers (Hollowell et al., 2019). However, the mediating function that trust plays in a relationship that is both empowering and engaging is still up for debate in retail transactions in the sharing economy (Bowden & Mirzaei, 2021; Busalum & Ghabban, 2021).

Placing an emphasis on user trust and transitioning into an open and transparent platform may encourage users to use the platform (Kong et al., 2020). One crucial aspect that constitutes openness and transparency in technological platform is the empowerment of customers (Köbis et al., 2021). Empowered customers may share their views and individual experiences when using the services of a sharing economy. Also, when customers lack direct contact with service providers, relying on previous customer suggestions, instructions, and feedback plays a significant role in establishing customer buying orientations and trust in suppliers (Hollowell et al., 2019). However, the mediating function that trust plays in a relationship that is both empowering and engaging is still up for debate in retail transactions in the sharing economy (Bowden & Mirzaei, 2021; Busalum & Ghabban, 2021). To the best of our knowledge, no research explicitly examines the mediating role of trust in consumer engagement on SP.

H3. Customer trust mediates the relationship between customer empowerment and their engagement on sharing platform in the retailing sector.

The proposed research model is shown in Fig. 1.

Fig. 1

Conceptual framework

Methodology

Research context

Vietnam is well positioned to play a vital role in the next chapter of Asia's consumption story. Traditional grocery stores are being displaced by modern retailers, mainly supermarkets and convenience stores, in most consumer markets (larger hypermarket formats are still present but growing less rapidly). However, digitalization has quickly transformed how Vietnamese shops go beyond the classic retail modernization narrative in two arenas. First, e-commerce is evolving so quickly that it can circumvent the transition from traditional to modern store-based retail. By 2025, e-commerce in Vietnam may be nearly as significant as traditional modern food retail. Second, conventional trade is also quickly digital. Vietnam has about 680,000 offline stores that sell essential foods and fast-moving consumer products. A significant convergence is reshaping consumer demand, with digital ecosystems aggregating numerous consumer demands and supplying them with varying degrees of integration. Super applications, which provide a one-stop digital shop for clients through numerous uses, functions, and additional services, are at the most integrated end of the range.

Furthermore, Vietnam is well positioned to capitalize on the sharing economy's expanding opportunities. With a well-educated and young population and about 70% of people possessing a smartphone, Vietnam's economy stands to benefit significantly from these emerging technologies. The rise of the sharing economy was one of the most significant transformations in recent years. Therefore, testing the changing customer behavior in the retailing sector via the sharing economy platform in Vietnam is necessary for both practical and theoretical implications (Delteil et al., 2022).

Research design, sample, and data collection

Using a multi-theoretical approach, the author applied a quantitative design emphasizing mature theory research (Edmondson & McManus, 2007).

Due to the need for a commonly agreed method for estimating sample size for SEM, scholars depend primarily on rules of thumb. In this work, the sample size was chosen by rules of thumb and necessary parameter values, such as the predicted effect size, desired statistical power level, latent variables, observable variables, and probability level (Soper, 2020). This study used a convenience sample technique to adopt a purpose sample of 500 customers (457 valid data) who already purchased products or services via the sharing economy platform (Grab, Go-jek, and Be) in Vietnam. The selection of these three sharing economy platform firms (brands) for the study was based on their widespread recognition and prevalence within Vietnam’s sharing platform market (Giang et al., 2024). The survey was conducted from May 2023 to September 2023. The authors collected data using direct interviews, deemed appropriate for the Vietnamese culture, where interpersonal interaction is the primary mode of communication. The research team members interviewed customers during their breaks in shopping malls and supermarkets in Ho Chi Minh City, Vietnam, and recorded their answers. A flag-down fare was paid to each customer as compensation after the interviews. The respondents were informed that their responses might remain anonymous and confidential. Moreover, the author abides restrictively by the regulations and guidelines governing study participants' confidentiality (Smith, 2003). Four hundred sixty-five completed surveys were received, of which 457 were valid and fulfilled the required information.

Table 1 demonstrates the representativeness of the sample with the relevant parameter values.

Table 1 Sample characteristics

Measures

The scales were developed based on prior empirical studies and background hypotheses. The reliability and validity of the number of points on the Likert scale have been debated among users since its introduction in 1932 (Colman et al., 1997; Preston & Colman, 2000). The participants' evaluations are not influenced by the number of response categories (Altuna & Müge Arslan, 2016; Pearse, 2011). The current study used a self-reported reflective scale for all dimensions in the model, as judged on a five-point Likert scale ranging from 1-totally disagree and 5-totally agreed via customer perception.

Customer empowerment on the sharing platform

Customer empowerment is multidimensional and cannot be encapsulated by a single concept (Llorente-Alonso et al., 2024). Besides, empowerment should be evaluated in terms of self-determination, which includes the ability to govern behavior, determination, and awareness of each individual in activities from which to choose and change actions (Deci et al., 1989; George, 2015). Thus, control over the surroundings and activities is essential for empowerment. In this study, the author adopted Spreitzer's (1995) scale to assess the perceived element of confidence in one's capacity to measure customer empowerment in the context of user empowerment in the sharing economy platform, based on 7-items (e.g., "I can choose to enjoy the product in different places; “the service employee would adjust the service delivery based on my request” (Chandran and Morwitz, 2005; Han & Li, 2006; Prentice et al., 2016).

Service innovation of the sharing platform

Service innovation refers to the use of new technologies and concepts in the service process to enhance the competitive advantage of enterprises (Ordanini & Parasuraman, 2011; Teece et al., 1997; Thrane et al., 2010; Varadarajan, 2024). The service innovation of the sharing economy platform was based on 4-items (e.g., “This platform uses new information technology to promote information sharing." (Zhang & Hu, 2021).

Customer trust on the sharing platform

Customer trust on the sharing platform was conceptualized as a second-order construct, which includes four dimensions—perceived risk (3 items, e.g., “I believe that there could be negative consequences when using this platform.”), benevolence (2 items, e.g., “I believe that this platform is interested in understanding my needs and preferences.”), competence (2 items, e.g., “I think that this platform is competent and effective in.”), reciprocity (3 items, e.g., “I can trust the information presented to me by this platform.") (Gulati et al., 2019).

Customer engagement on the sharing platform

In this study, based on Calder et al. (2009), we concentrate on developing customer-platform engagement based on pertinent consumer experiences, which concentrates on the use of online platform as a means for retailers to establish consumer engagement (Thakur, 2016). Customer engagement on the sharing platform was conceptualized as a second-order construct measured through 11 items of four different customer experiences: monetary evaluation (3 items, e.g., "This platform gives exclusive time-bound offers."), social facilitation (2 items, e.g., "I bring up things I have seen on this platform in conversations with other people."), enjoyment (3 items, "Browsing an online platform is like a treat for me."), utilitarian (3 items, "It is easy to find the information I need using sharing platform.") (Thakur, 2016).

Common method variance testing

In this study, one of the major concerns is the common method variance (CMV) because the researcher collects respondents' opinions for both explanatory and dependent variables from the same participant (Podsakoff & Organ, 1986). This research adopted the methodology proposed by Podsakoff et al., (2003, 1986) to eliminate CMV concerns. Scales were generated from various sources, including in-depth interviews, focus group discussions, and expert opinions (triangulation process), and at each outcome, the generated items were cross-validated among the approaches (Lindell & Whitney, 2001). Besides, nonlinear interaction terms were added to the model (Harrison et al., 1996). Harman's single-factor test showed that no single factor emerges, and the general factor should account for most of the covariance (Tehseen et al., 2017). Thus, CMV was not a reason to be concerned that might affect the results of this study.

Partial least squares structural equation modeling (PLS-SEM)

The PLS-SEM method enables researchers to estimate complex models with many constructs, indicator variables, and structural paths without making distributional assumptions about the data (Hair et al., 2012a, 2012b, 2019; Ringle et al., 2015). Furthermore, PLS-SEM is a causal-predictive approach to SEM that emphasizes prediction in estimating statistical models whose structures are intended to provide causal explanations (Wold, 1982). As a result, the technique overcomes the seeming dichotomy between explanation and prediction, which is the foundation for establishing managerial implications, as is commonly emphasized in academic research (Hair et al., 2019).

Results

Examining the measurement models

Internal consistency reliability. Table 2 shows that the composite factor reliability coefficients of the constructs (C.R) are in the range of 0.807–0.934, which indicates that they meet the criteria for reliability of internal consistency (Joreskog, 1971). The average variance extracted (AVE) for each construct in the model is greater than or equal to the recommended threshold of 0.50, which reveals the research model constructs' convergent validity (Hair et al., 2019). (see Table 2).

Table 2 Results of reliability and convergent validity tests of lower order of constructs

This paper appraises customer engagement on sharing platform and customer trust as particular conceptions, reflecting the higher-order constructs supported by theory, as shown in Table 3.

Table 3 Results of reliability and convergent validity tests of higher order of constructs

The variance shared throughout all model constructs that fall below their AVEs, as shown in Table 4, reveals the discriminant validity of research constructs (Hair et al., 2019).

Table 4 Fornell–Larcker criterion analysis for testing discriminant validity and correlations matrix among higher order of constructs

Hypothesis testing

R² value, F Square, goodness-of-fit, Stone–Geisser's Q², and path coefficients are the metrics that are used to evaluate the structural model's linkages as well as the predictive power of the model. Other metrics that can be used include goodness-of-fit and goodness-of-shape (Hair et al., 2019). Because the VIF values of the model's predictor constructs are less than 5.00, collinearity is not an issue with the model (Hair et al., 2017).

The R² value of the endogenous constructs is a measure of the model's ability to explain and predict within the sample (Hair et al., 2019). The R² values of the model's endogenous constructs, customer engagement, service innovation, and customer trust, are 0.609, 0.511, and 0.055, respectively. The model is considered a good match with a standardized root mean square residual (SRMR) value of 0.074. (Joreskog & Sorbom, 1982). The following Q² values were positive and greater than 0, indicating that the PLS-path model has a minor to maximum predictive relevance: customer engagement (Q² = 0.435).

Direct effects

To determine the statistical significance of each path coefficient, Chin (1998) suggested carrying out a bootstrapping technique using a total of one thousand individual samples as part of the analysis. The predicted route coefficients and their respective bootstrap values and T values are presented in Table 5. As expected, customer empowerment was found to have a favorable and statistically significant impact on customer engagement (β = 0.410, t = 8.197, p < 0.001). Thus, the data obtained provide complete support for H1.

Table 5 The total direct effect with standardized regression weights

Indirect effects

Table 6 reveals that service innovation partially mediates the relationship between customer empowerment and engagement (β = 0.306, p < 0.001). Thus, H2 is fully approved by the data. Besides, the variance accounted for (VAF) method tests the structural model of indirect influences. This method is considered the best approach for PLS-SEM, which uses the resampling method and has higher statistical power than the Sobel method (Hair et al., 2013). The mediation effect may be categorized as follows: ≥ 80 percent means it has a full mediation effect, 20–80% is a partial mediation effect, and ≤ 20 percent reveals no mediation effect. The formula for calculating VAF is (an indirect effect)/(total effect). The mediation effect of service innovation between customer empowerment and the customer engagement platform is 0.306/0.721 = 0.4244 or 42.44%. However, we did not find the mediating effect of customer trust on the nexus between customer empowerment and engagement on sharing platform (β = 0.005, p = 0.518), which results in the rejection of H3.

Table 6 The total indirect effects of customer empowerment on customer engagement platform through the mediating role of empowerment and trust

Total effects

The comprehensive effects of the final hypothesized model are presented in Table 7 and Fig. 2.

Table 7 The total effects of customer empowerment on customer engagement

Fig. 2

PLS-SEM paths

Robust check

The study utilized structural equation modeling (SEM) to determine the coherence of the findings. The findings demonstrated that the model exhibited high accuracy and the coefficients of direct paths aligned with the PLS-SEM.

• ● χ²= 298.59, df = 147.00, p = 0.000 (< 0.05).

• ● χ²/df = 2.03, GFI = 0.93, TLI = 0.97, CFI = 0.97, NFI = 0.95, SRMR = 0.039 and RMSEA = 0.047.

Discussion and conclusion

Research findings

The sharing economy is expected to expand (Statista, 2019) and could considerably remedy sustainability issues (Cherry & Pidgeon, 2018), particularly within the retail sector. Prioritizing client interaction is essential for expanding and sustaining a platform's user base (Dessart et al., 2016; Kumar & Kaushal, 2023; Lim & Rasul, 2022; Rasool et al., 2020). Despite prior research addressing and suggesting numerous strategies for attaining CE, empirical investigations are deficient within the framework of sharing economy platform. This study, situated within the Stimulus-Organism-reaction (S–O–R) and self-determination theory, demonstrates that consumer empowerment is a stimulus to enhance CE as a reaction. Besides, firm service innovation and customer trust might be catalysts to convert customers' vested rights into customer engagement.

Theoretical implications

In light of the era of exponential growth in digitalization, marketers are beginning to understand that consumer contributions extend beyond regular purchases, with an increasingly closer connection, spanning the creation, delivery, and capture of value between customers, retailers, and platform via engagement mechanism (Alimamy & Nadeem, 2022; Kumar, 2022; Utami et al., 2022). Even though CE is a comparatively new concept, it is a well-developed concept in the marketing literature (Lemon & Verhoef, 2016; Lim et al., 2022). In addition, the customer-firm relationship and CE models are further diversified by the emergence of new technologies, including augmented and artificial reality and online social media (Steinhoff et al., 2019; Wirtz et al., 2019). CE on sharing platform is a proxy for their experiences and behavior (e.g., happiness, trust, value-in-use, brand loyalty, word-of-mouth, or price perception (Alfalih, 2022; Winell et al., 2023). Though there is increasing research on investigating the nature of CE in digital contexts (Blut et al., 2023), there is still a lack of a unifying framework that provides clear insights into how retailers can optimize their investments in engagement strategies on sharing platform (Roy et al., 2023).

There is a widespread agreement among academics and practitioners that stakeholders in the contemporary connected world, including customers, have become more empowered (Chen et al., 2022; Wang, 2020; Zouari & Abdelhedi, 2021). In the sharing economy, stakeholders can compare and choose the most advantageous offers with a single click to publish comments on various websites or online stores (e.g., star rating) (Auh et al., 2019; Nadeem et al., 2020). Although customer empowerment is seemingly a prerequisite for customer engagement, the topics of customer engagement and empowerment in sharing platform are addressed separately in topical literature based on fragmented and inconsistent findings (Benoit et al., 2022; Kaur et al., 2023; Ostrom et al., 2015). This research sheds light on the advanced knowledge of the influence mechanism of customer empowerment on their engagement on sharing platform directly and via the mediating role of service innovation in the retailing sector (Shankar et al., 2021).

In the sharing economy platform, customer empowerment is vital in creating co-value (Li et al., 2021). Customers who perceive themselves as powerful concerning a firm are frequently more content and loyal than those who believe they hold insufficient power (Auh et al., 2019) and have an increased preference for action, increased creativity, and positive emotions (Abboud et al., 2023). Research has also identified benefits for firms with high customer power, including improvements in customer insights, positive service appraisals, and co-designed offerings (Jaakkola & Alexander, 2014). Conversely, customers may need help to attain their desired service outcomes when experiencing low power (Fitzgerald et al., 2020).

Besides, the research has revealed that the implementation of service innovation in the sharing platform has a significant impact on both the advancement of efficiency and the stimulation of customer engagement with the foundation of empowered customers (Wahyudiono et al., 2024; Xu et al., 2020). Empowered customers might also be the source of service innovation primarily through platform co-creation and further promote customer engagement with the organization (Barile et al., 2024; Fernandes & Remelhe, 2016). Informed, networked, empowered, and active consumers increasingly co-create value with the firm (Zhang et al., 2020). On the platform, customers can leave comments, reviews, and feedback, a valuable material source for suppliers to calibrate and innovate the products and services provided (Fu et al., 2017; Tuunanen et al., 2024).

Managerial implications

Retailing firms need to develop customer engagement on a platform based on customer empowerment through service innovation to cope with the competitive pressure and changes in consumer behavior. It is acknowledged that customer power is a critical need that should be prioritized to facilitate value co-creation and establish a competitive organizational advantage. Retailers should frequently endeavor to empower customers throughout their customer journey, which encompasses a variety of interactions that extend beyond transactional purchases. Firms must also focus more on the review system and create a transparent evaluation to encourage customers to express their experiences after purchasing a sharing economy platform.

Conclusion

This study was conducted in light of the rapidly growing sharing economy platform in the retailing sector in emerging economies. To comprehend transformation, customer empowerment was revealed as a significant path to customer engagement on the sharing platform. Besides, the study also emphasizes the significance of service innovation as a mediator between empowerment and consumer engagement on sharing platform.

This study also contains certain limitations. A self-evaluation survey and cross-sectional data are related to the first issue regarding sample bias. Because convenience sampling techniques were used, substantial concerns exist about the generalizability of the results. This suggests that longitudinal research strategies may benefit future customer engagement studies in the sharing economy. Service innovation might be classified into four primary dimensions: service output, service provider competitiveness, service provider technology, and customer competitiveness (Gadrey et al., 1995). It also encompassed four dimensions: innovation concept, customer interaction interface, service delivery, and technology selection (Den Hertog et al., 2003). Thus, future research should consider these components of platform service innovation in buffering the nexus between customer behavior and the platform. The result of this study does not support the role of platform trust in customer engagement with the sharing platform. However, future studies should consider the other components of trust and its effects on the relationship between customer empowerment and engagement on sharing platform.