The Impact of Omnichannel Shopping Experience and Channel Integration on Customer Retention: Empirical Evidence from China

Abstract

Creating a new retailing environment to meet the seamless experience requirements of consumers is a challenge for Omnichannel-related businesses. Based on the "appraisal-emotion-response" chain, the purpose of this research is to explore the psychological mechanism of omnichannel integration influencing customer retention and the moderating effect of customer showrooming experience. This research uses a structural equation model in partial least square software to analyze a two-stage survey (Study 1: n = 210; Study 2: n = 342) conducted in China. The results show that channel control experience has three dimensions: perceived channel attribute familiarity, channel type matching, and cross-channel access convenience; consistent interactive experience has two dimensions: information cross-channel consistency and cross-channel service support. Furthermore, both channel control experience and consistent interactive experience are favorable for customer retention through increased customer satisfaction (transactional and retailer satisfaction). Finally, customer showrooming experience positively moderates the relationship between consistent interactive experience and customer satisfaction. This research proposes a self-regulation process model to explain how omnichannel integration enhances consumers' experience, finally leading to consumer retention. The findings contribute to the omnichannel retail business literature and provide management implications for Asian retailers to implement an omnichannel business strategy.

1. Introduction

Consumers’ information accessing channels are increasingly diversified (Leu & Masri, 2021). Therefore, consumers will spend more psychological resources selecting shopping information and being stimulated by massive information to generate more purchasing power (Lemon & Verhoef, 2016). For retailers, consumers switching between different channels will increase the probability of transaction interruptions, increasing the risk of blurring retailer image perceptions and reducing customer loyalty. This inconsistency limits their ability to provide customers with higher-quality omnichannel environments.

In the past few years, more and more retailers have been exploring the omnichannel strategy (Nurfarida et al., 2021). Channel integration is one of the popular strategies retailers apply (Bijmolt et al., 2021), which is considered the key to cross-channel customer relations management. Existing research reveals that channel integration strategies can bring positive synergistic effects (Shi et al., 2020). However, channel integration may be a zero-sum game (Viejo-Fernández et al., 2020). It even has negative spillover effects or reduces the locking effect of channels (Kumar et al., 2019). For retailers, the integration benefits of enterprises may be offset by the inherent lack of complementarity caused by channel differences (Wagner et al., 2020). Therefore, it is challenging for retailers to manage omnichannel to provide a smooth channel switching experience while ensuring omnichannel information delivery and service quality.

Since omnichannel retailing aims to provide consumers with a seamless shopping experience, it provides consistent service and optimizes the sense of smooth contact-point switching. Therefore, the quality of channel integration should be evaluated from channel operation and service marketing. To fill this gap, this research aims to assess the integrated quality of omnichannel retailing by combining channel operation and service marketing perspectives. Thus, this paper proposes a framework based on the “appraisal-emotional-response” logic and explores the impact of the service environment of omnichannel retailing on customer retention intention.

2. Literature Review

2.1. Omnichannel Shopping Experience

Verhoef et al. (2015) summarized omnichannel retailing as collaborative management of various available channels and customer touchpoints. The consolidation of order fulfillment processes characterizes omnichannel retailing through continuous information exchange, joint operations, logistics, and cross-channel risk management (Hubner et al., 2016). Omnichannel retailing’s competitiveness lies in achieving and maintaining high-quality interactions at all customer touchpoints to create an overall consumer experience (von Briel, 2018). The goal of touchpoint management in omnichannel retailing is to provide customers with a seamless omnichannel experience, not just to improve the experience of individual key touchpoints.

Understanding an omnichannel shopping experience is a prerequisite for optimizing contact-point management (Elodie et al., 2017). With the advent of the Internet, mobile devices, and social media, consumers exhibit more complex shopping behaviors by connecting multiple sources across different channels. Furthermore, they use multiple channels simultaneously interactively, leading to more unpredictable purchase path contact points (Arslan et al., 2021). Therefore, customers’ omnichannel shopping experience has three characteristics: First, the combination of contact points is complex and diverse, and the consumers’ shopping path is difficult to predict. Second, the interaction between customers, brands, and channels is emphasized. Third, because consumers’ shopping process comprises discrete contact points, customers value the sense of fluency when moving from one contact to another. However, no matter what the contact point is, consumers should be locked in the retailing brand ecosystem (Flavian et al., 2020).

2.2. Channel Integration Quality

Channel integration is one of the essential aspects of omnichannel retailing, which describes the retailer’s efforts to ensure close cooperation between multiple channels in order to achieve synchronized operations; thus, this is considered key to managing omnichannel (Gao et al., 2021). With multichannel developed into omnichannel (Li et al., 2018), the concept of channel integration quality was proposed (Sousa & Voss, 2006), which is the key indicator to creating a seamless purchasing experience (Chen et al., 2018; Kranzbühler et al., 2019). The continuity and integrity of the overall shopping experience depend on the retailers’ ability to integrate the touchpoints (channels), given that consumers travel to different points of contact to complete the entire shopping journey. Therefore, channel integration quality plays a crucial role in customer retention in omnichannel retailing and deserves further study.

2.3. Self-Regulation in Attitude-Intention Relationship

The self-regulation process refers to the ability of individuals to regulate their own attitudes, emotions, desires, and behaviors in pursuit of better results (Gotlieb et al., 1994). Lazarus (1991) believed that attitudes and subjective norms could not fully explain consumers’ behavioral intentions and proposed a general theoretical framework of “evaluation-emotion-response.” Considering the effect of self-regulation, Bagozzi (1992) further developed this framework and proposed the “appraisal-emotion-responses” chain to understand consumer behavior. We combined the Bagozzi (1992)’ framework, proposed a research model that reflects the impact of omnichannel integration on the process of omnichannel consumer engagement.

3. Hypotheses Development

3.1. Appraisal: Omnichannel Integration Quality

With the continuous improvement of omnichannel consumers’ status, in addition to channel attributes, the subjective perception has gradually become a criterion for dimensionality: users should feel fluent and coherent in converting different channels. Therefore, consumers will generate perceived fluency according to the service quality and interaction consistency between channels (Shen et al., 2018; Wu & Chang, 2016). Therefore, we define omnichannel integration quality as the seamless shopping experience achieved by customers through retailers’ omnichannel service support system. In an omnichannel retailing environment, considering consumers’ self-efficacy and perceived fluency (Shen et al., 2018), we summarize the omnichannel integration quality from “hardware” channel control experience (channel attributes) and “software” interactive consistent experience (subjective perception) (Sousa & Voss, 2006).

3.1.1. Channel Control Experience

In the context of omnichannel retailing, the most apparent feature of channel integration is that the dominant power is gradually transferred from retailers to customers, giving customers the freedom to understand and use channels. Therefore, the most crucial characteristic of a successful system “hardware” quality of omnichannel service delivery systems is customer-oriented. Furthermore, channel integration can reduce consumers’ uncertainty on retailers (Li et al., 2018), which to some extent, depends on consumers’ control experience over the omnichannel.

Therefore, we define channel control experience as the degree to which customers perceive that they can control the channel system (i.e., they are free to use channels) when making omnichannel purchases. In the context of omnichannel retailing research, the channel control experience of customers should also include these aspects: Firstly, the premise of omnichannel retailing is to layout multiple channels so that customers can choose matching channels according to their needs. Secondly, the service attributes of each channel should be familiar to customers and reduce the perceived risk of their use. Finally, the process of channel conversion should be smooth and straightforward, and the understanding cost of cross-channel access should be reduced as much as possible. Therefore, channel control experience is mainly embodied in perceived channel type matching, channel attribute familiarity, and cross-channel access convenience.

Perceived channel type matching is defined as the degree to which channel types provided by retailers can flexibly meet the customer’s choice needs (Shen et al., 2018). Accurately, retailers can show advantages in channel diversification through supporting customers to use different channels. Customers will value the flexibility to choose their preferred channel for specific shopping tasks. Compared with offering personalized channels to customers, when retailers allow only particular channels, customers are likely to question the retailer’s ability to build an omnichannel system.

Channel attribute familiarity is defined as customers’ understanding of available channels and the differences in service attributes of different channels. This dimension represents the transparency level of the retailers’ omnichannel service. In other words, the higher the transparency, the more familiar customers are with the channel, and the lower the perceived risk of using channels will be (Sousa & Voss, 2006). When retailers fail to integrate channels properly, customers become confused about the availability and service differences between channels, making their purchasing process difficult.

Cross-channel access convenience is defined as the perceived cost of cross-channel access for customers and the sense of fluency of the transition. This dimension represents the retailer’s ability to support customer switching across systems. When the waiting time for channel switching is too long, and the process is too complicated, customers’ cross-channel experience will become incoherent. This will increase the cognitive cost of cross-channel access, affecting the convenience of the cross-channel shopping experience and increasing the risk of customer loss (Shen et al., 2018).

3.1.2. Consistent Interactive Experience

Since omnichannel emphasizes that users can freely switch between different channels, omnichannel attaches importance to the experience process’s perceived fluency. Therefore, consistency is one of the measurement standards for omnichannel integration quality (Shen et al., 2018). Specifically, cross-channel information consistency is a critical part of the interaction between customers and retailers in the pre-sale stage. In contrast, customers’ interaction experience in the transaction and the post-sale stage is more concerned with retailers’ service cross-channel support level.

Considering that, on the one hand, information quality and service quality are considered to be the key outputs to determine the success of information systems (DeLone & McLean, 1992); On the other hand, omnichannel, as a mixed business service, information quality and service convenience determine the customer perceived value of this process (Oh & Teo, 2010). Therefore, we believe that the omnichannel integrated interactive experience includes information and services. The consistent interactive experience between retailers and customers in the omnichannel environment is an essential feature of “software” integration quality. Thus, we propose the following concepts:

Information cross-channel consistency refers to how customers perceive the consistency of information such as product information, transaction information, and corporate image provided by retailers across channels. Consistency of information content helps customers obtain cross-information to eliminate confusion in cross-channel shopping and shorten the transaction process (Huebner et al., 2016).

Service cross-channel support refers to the degree of continuous service support that customers feel in crosschannel shopping. For example, products purchased online by customers support offline after-sales service, which reduces the maintenance risk and repair cost. The cross-channel support of services realizes the convenience of services from multiple perspectives, such as information acquisition, order completion, and user service, and increases consumers’ perceived value while reducing the risk perception (Oh & Teo, 2010).

3.2. Emotion Reaction: Satisfaction

Satisfaction is one of the important self-regulating emotional responses in Bagozzi’s (1992) framework, and satisfaction can lead to positive outcomes, especially in predicting future willingness to use services. According to the expectation disconfirmation theory, the customer will compare the actual behaviors and expectations after the p repurchase stage experience. If the expectation is higher than the evaluation, it will lead to dissatisfaction; otherwise, it will enhance satisfaction (Cyr et al., 2018).

According to the evaluation object, customer satisfaction can be divided into transactional satisfaction and retailer satisfaction (Jones & Suh, 2000). Transactional satisfaction refers to consumers’ evaluation of a particular service at a specific point of contact, usually judged by a single transaction (Zhao et al., 2012). Retailer satisfaction refers to retailers’ cumulative overall evaluation over time (Bitner & Hubbert, 1994). This research focuses on both aspects, which is more helpful in understanding the process of omnichannel integration for consumer emotional mechanisms when they engage in omnichannel consumption.

Perceived channel control is positively related to improving consumer satisfaction. According to isomorphic effects, controlling behavior contributes to the perceived quality of consumer interactions (Dourish, 2001). Further- more, when controllable behaviors are intuitive and observ- able, it shortens the psychological distance for consumers, reducing the perception of transactional uncertainty and cross-channel shopping friction, finally improving consu- mers’ transactional satisfaction.

Besides, the existing literature on relationship marketing demonstrates that the enterprises’ service investment leads to relationship maintenance (Dwivedi et al., 2019; Quang et al., 2021). The channel control experience can make customers feel the retailer’s integrated channel operation investment, and it can help appease customers worried about its risk. According to the principle of reciprocity, if customers perceive the construction effort of omnichannel integration of retailers, it is more likely to stimulate a positive emotional state, which in turn leads to a closer relationship between service providers and customers to provide higher satisfaction and promote customer retention (Fassnacht et al., 2019; Seck & Philippe, 2013). Therefore, hypothesis H1 is proposed:

H1: A consumer’s perceived channel control experience will positively influence the consumer’s (H1a) transaction specific satisfaction and (H1b) retailer satisfaction.

Consistency theory argues that people will have uncomfortable and unpleasant emotions if people contact information opposite to cognition (Kruglanski et al., 2018). In addition, exposure to a large amount of new information may make individuals feel that the existing knowledge is threatened by inconsistency; they will selectively seek support information or avoid receiving inconsistent information (Garmaroudi et al., 2021).

In the omnichannel environment, there are numerous channels for customers to contact with brand information. In attracting customers through multiple channels, the importance of consistency has been repeatedly mentioned. In the cross-channel decision-making process, the higher the consistency between customers’ information and the previous product cognition attitude, the higher the customer’s trust in the product and the shorter the transaction process can be (Schramm-Klein et al., 2011).

Therefore, in the post-purchase phase, retailers support consistent cross-channel service after sales, increasing customers’ confidence in retailers and reducing their perceptions of transaction risk and purchase uncertainty. Interactive integration is conducive to retailers’ consistent content, which will weaken customers’ contradictory experiences and improve their satisfaction during omnichannel consumption. It also brings consumers a satisfied and trustworthy reputation for retailers, which will reduce the uncertainty of customers’ adoption of retailers’ services and shorten the psychological distance between customers and retailers. Therefore, hypothesis H2 is proposed:

H2: A consumer’s perceived interactive consistent experience will positively influence the consumer’s (H2a) transaction-specific satisfaction and (H2b) retailer satisfaction.

Although transactional and retailer satisfaction differs in definition and service purpose, they do not exist in isolation. Existing studies have confirmed the positive correlation between transactional and retailer satisfaction (Otto et al., 2020). This positive relationship has been proved in the mobile service environment and business. Mobile business users’ satisfaction follows the dynamic law of transactional satisfaction to service providers’ cumulative satisfaction (Zhao et al., 2012). Therefore, based on the above literature conclusions, we speculate the relevant hypothesis H3:

H3: A consumer’s transaction-specific satisfaction will positively influence his/her retailer satisfaction.

3.3. Responses: Retention Intention

Customer retention is closely related to customer loyalty and is the opposite of customer churn (Kumar & Ayodeji, 2021). Retention reduces the cost of acquiring customers, the management cost and increases customers’ profit (Becker et al., 2009). Due to technical support, omnichannel customers enhance their ability to obtain shopping information, significantly improving information asymmetry. It makes the relationship between customers and firms less viscous and difficult to retain.

Customer satisfaction plays a vital role in service marketing because it is a good indicator to predict the intention of subsequent behaviors (Huré et al., 2017). Many empirical studies have also pointed out that customer satisfaction positively affects customers’ continuous intentions (Elbeltagi & Agag, 2016; Shin et al., 2017). This positive effect is dynamic and predictive of future use. Satisfied customers tend to request the same service again and use it more often than dissatisfied customers. In the context of e-retailing ethics research, the close relationship between customer satisfaction with the service provider and repurchase behavior also exists (Elbeltagi & Agag, 2016). Meanwhile, Jones and Suh (2000) proposed that transaction satisfaction and retailer satisfaction positively correlate with purchase intention. To sum up, we propose the following hypothesis H4:

H4: A consumer’s (H4a) transaction-specific satisfaction and (H4b) retailer satisfaction positively influences consumer’s retention intention.

3.4. The Moderating Effect of Showrooming Experience

The diversification of channels exacerbates customers’ “research shopping” behavior, which creates a potential problem for retailers – showrooming (Ralf et al., 2010). In addition, the channels’ function is degraded from distribution to “display, ” which seriously affects retailers’ channel construction (Rapp et al., 2015). With omnichannel retailing becoming the mainstream of development, scholars also considered exhibition halls’ influence on omnichannel stra- tegy. Fan et al. (2021) found that building a showroom may benefit or hurt the e-tailer’s omnichannel strategy since they incorporate the impacts of competition and consumer heterogeneity in channel preferences.

Although most studies have verified the negative impact of showrooming, from the analysis of customers’ intrinsic motivation, the showrooming behavior reflects their emphasis on reducing uncertainty, finding ideal self definition needs, and shopping at a low cost or efficient way (Li et al., 2018). Consumers are more likely to be passively exposed to large amounts of complex and unfamiliar channel information in an omnichannel environment. When information exceeds customers’ processing load, it can significantly catalyze insecurity within the customer. In this context, the showroom experience is analogous to self-efficacy and represents the customer’s confidence and expertise in cross-channel usage. Based on previous self efficiency studies in the omnichannel, the showrooming behavior improves the customers’ ability to evaluate information from multiple sources by comparing their evaluation with their own psychological needs, reflecting the customer’s tendency to seek diversification.

Therefore, this research regards showrooming experience as the heterogeneous feature of customers and explores whether customers’ showrooming experience will moderate omnichannel integration on customer satisfaction. We propose that consumers with previous showrooming experience will have greater perceived control during omnichannel switching and be more inclined to seek diversification, leading to satisfaction with the omnichannel shopping process. The following hypothesis H5–6 is presented:

H5: Customer showrooming experience could strengthen the positive relationship between channel control experience and transaction-specific satisfaction (H5a) and retailer satisfaction (H5b).

H6: Customer showrooming experience could strengthen the positive relationship between interactive consistent experience and transaction-specific satisfaction (H6a) and retailer satisfaction (H6b).

Based on the above theoretical thinking, this research explores the influence mechanism of omnichannel integration on customer retention intention and introduces two types of satisfactory emotional responses as mediators. In this research, channel control experience and interactive consistent experience reflect consumers’ desire to experience omnichannel integrated services. In addition, this research applied showrooming behavior experience into this research model as the heterogeneity of omnichannel customers and explored this moderating effect. The theoretical model is shown in Figure 1.

Figure 1: Research Model

4. Research Methods and Results

This research adopts the multi-stage research method. In study 1, we conduct an exploratory factor analysis and confirmatory factor analysis to demonstrate the dimension and structure of channel integration quality. In study 2, we use the structural equation model to test the hypothesis of the relationship between channel integration quality, customer satisfaction, showrooming experience, and outcome variables.

4.1. Study 1

Study 1 evaluates the dimensions, reliability, and validity of channel integration quality constructs in the Chinese omnichannel context. We conducted an online empirical survey administered through So jump (http://www.sojump. com), the most popular online survey website in China, with a sample database of 26 million Chinese individuals (Li et al., 2018; Xiao & Mou, 2019). All respondents should answer a screening question to determine whether he/she had a profound experience with omnichannel integration. If their answer was no, the respondent could not continue the questionnaire. Respondents who completed the questionnaire received 10 CNY. An initial sample of 210 respondents was used to assess the multi-dimensional nature of the channel integration structure. 58 percent of respondents were women, and 42 percent were men. Most of the respondents (63 percent) were between 20 and 40 years old, and 64 percent had a bachelor’s degree or above.

As omnichannel retailing research is still in its infancy, there is no mature scale for integrating omnichannel retailing. Considering omnichannel shopping characteristics, we divided the integration of omnichannel retailing into two parts: channel control experience and interactive consistent experience, by referring to the relevant research scales of (Madaleno et al., 2007; Srinivasan et al., 2002; Oh & Teo, 2010; Bendoly et al., 2005). We further adapted with the characteristics of omnichannel retailing. All measures were anchored on a 7-point Likert scale ranging from strongly disagree ‘1’ to strongly agree ‘7’.

210 questionnaires were divided into the exploratory analysis (EFA) and confirmatory factor analysis (CFA). We first used IBM SPSS 24.0 to conduct exploratory analysis (EFA) on the 13 items of channel control experience. The results revealed a three-factor solution through the maximum variation analysis of principal component analysis, which conformed to the theoretical derivation results. Two terms were removed from further analysis based on factor load and cross load. The three-factor solution accounted for 69% of the total variance, and the first factor accounted for 26% of the total variance. To the items of interactive and consistent experience, after eliminating the items that did not conform to the factor load, two factors were obtained through analysis. The two factor solution accounted for 71% of the total variance, and the first factor accounted for 36% of the total variance.

After that, the confirmatory factor analysis (CFA) was used as a dimensional validation for channel integration quality construction. This study conceptualized channel integration quality as an I-type construct, including reflective second-order constructs and first-order constructs (Jarvis et al., 2003). CFA data results showed that channel control experience was suitable for CMIN/DF = 1.960, IFI = 0.982, TLI = 0.974, CFI = 0.982, RMSEA = 0.065. The second order factor load was significant, with values ranging from 0.64 for cross-channel access convenience to 0.88 for perceived channel attribute familiarity. The results supported the concept of high-order hardware quality integration (see Table 1).

Table 1: Channel Control Experience Second-Order CFA Analysis Summary

The operationalization of channel control experience produced a reliable high order structure, which included three reflective factors: perceived channel attribute familiarity, perceived channel type matching, and cross channel access convenience. Similarly, CFA data results showed that interactive and consistent experience was suitable for CMIN/DF = 0.968, IFI = 0.993, TLI = 0.974, CFI = 0.989, RMSEA = 0.000. The second-order factor was loading from service cross-channel support 0.69 to information cross-channel consistency of 0.88. The results showed that the second-order factor of software quality integration significantly (see Table 2). Thus, interactive consistent experience as a higher-order structure contained service cross-channel support and information cross-channel consistency these two reflect factors.

Table 2: Interactive Consistent Experience Second-Order CFA Analysis Summary

4.2. Study 2

4.2.1. Sample and Procedure

A web-based survey was carried out in China. To avoid ambiguity, 20 respondents completed the pilot study. The formal questionnaire was confirmed after modifying the feedback from the interviewees. The research assistant cooperates with professional market research companies, participates in the whole questionnaire survey, and is responsible for supervising its research process to ensure data authenticity (Fan et al., 2020). After completing the survey, the participants would receive cash rewards. All participants were randomly selected and asked to give anonymous questions. Over three weeks, a market research firm administered the survey to actual retailing shoppers with prior experience with omnichannel retailers within the last three months. Eventually, the sample came to consist of 242 respondents. 16 respondents were discarded due to incompletion, yielding a final sample of 226 responses for subsequent analyses. Of the 226 respondents, 88 were male, and 138 were female. A majority of the respondents were young adults, with 92% of generation Y. Besides, the number of master’s degrees also accounted for 87.6% of the sample. To detect the potential non-response bias, t-tests were conducted to compare the mean values between the early and late respondents for demographics. No significant differences were found, suggesting that non-response bias was not a threat in this study.

Measurement items for customer satisfaction were adopted from (Olsen & Johnson, 2003; Zhao et al., 2012). Retention intention from Bojei et al. (2013) includes showrooming from Rapp et al. (2015). We made minor modifications to the measurement items to fit the current research context. All constructs were assessed using perceptual scales with response measures on a 7-point Likert scale, and multiple items were 2 to ensure construct validity and reliability.

4.2.2. Measurement Model

A two-step structural equation modeling analysis approach was adopted to test the research model. We first checked the reliability test and three indices adopted: Cronbach’s alpha, composite reliability (CR), and average variance extracted (AVE), and the judgment criteria were greater than 0.70, 0.70, and 0.50, respectively. The results revealed that CR values were above the suggested threshold of 0.7, and Cronbach’s α values of all latent variables were between 0.882 and 0.948. The questionnaire data had ideal reliability and could be further analyzed. Additionally, as shown in Table 3, discriminant validity was achieved, as the square root of the AVE for each construct was well above their shared correlation with other constructs.

Table 3: Discriminant Validity Analysis

Note: FA-channel attribute familiarity, CC-channel type matching, CO-cross-channel access convenience, CON-information cross-channel consistency, SP-service cross-channel support, TS-transactional satisfaction, RS- retailer satisfaction, CR-customer retention intention, SR-showrooming experience.

*.< 0.05; **. < 0.01.

Common method deviations were tested before structural model analysis to prevent systematic errors. In addition, Harman single factor test was adopted in this study. After an exploratory factor analysis of all scale items by SPSS, the explanatory power (explanatory variance rate) of the first factor was 36.932%, which was lower than the standard 40% (Podsakoff et al., 2012). Therefore, this study was not affected by the common variance bias.

4.2.3. Structural Model

After reliability and validity analysis, AMOS was used for model structure fitting analysis (Table 4). There was a good fit between the structural model and the dataset (CMIN/ DF = 1.363, GFI = 0.976, RMSEA = 0.040, IFI = 0.977, TLI = 0.974, and CFI = 0.976). The results from the model path in the following table 4 show that the channel control experience of customer perception had a significant positive correlation with transactional satisfaction (β = 0.465, p < 0.001) and a positive correlation with retailer satisfaction (β = 0.139, p < 0.05). Interactive consistent experience had a significant positive correlation with transactional satisfaction (β = 0.520, p < 0.001) and also had a positive correlation with retailer satisfaction (β = 0.205, p < 0.05). Transactional satisfaction would positively affect retailer satisfaction (β = 0.645, p < 0.001). Finally, transactional satisfaction (β = 0.194, p < 0.05) and retailer satisfaction (β = 0.580, p < 0.001) had a positive correlation with customer retention intention, supporting hypotheses 1–4.

Table 4: Model Path Result

Note: P*** < 0.001, P** < 0.01, P* < 0.05.

4.2.4. Test of the Moderation Effect

The hierarchical regression method was used to test the moderating influence of the moderating variable of the customer’s showrooming experience. The analysis results are shown in Table 5.

Table 5: Hierarchical Regression Analysis of Moderate Effects

Note: CE-channel control experience, IE-interaction consistent experience, TS-transactional satisfaction, RS-retailer satisfaction, SR-howrooming experience.

P*** < 0.001, P** < 0.01, P* < 0.05.

This study suggested that the omnichannel integration quality might have a differentiated effect on the consumer engagement process under the moderation effect of the customer’s showrooming experience. According to the results of regression model 2–3 and model 3–3, the addition of customer showrooming experience variables, interaction consistent experience, and customer showrooming interaction had a moderating effect on transactional satisfaction (β = 0.122, p < 0.05) and retailer satisfaction (β = 0.126, p < 0.05). However, there was no moderating effect of showrooming experience on channel control experience and transactional satisfaction (β = 0.023, p > 0.05), and there was no moderating effect on channel control experience and retailer satisfaction (β = 0.092, p > 0.05). Thus, hypothesis 5 was not supported, while hypothesis 6 was supported. Through the above structural model analysis and moderating effect test, the results are summarized in Table 5.

5. Discussion and Conclusion

5.1. Discussion

By combining with the self-regulation process, this research explores the influence of omnichannel integration quality, customer satisfaction, and showrooming experience on customer retention in the omnichannel context. Specifically, we find that omnichannel integration quality, as the focus of “hardware” conditions and context “software” perception, when receiving these stimulate, customers will compare these with prior expectations, thus affecting consumer satisfaction. Furthermore, from the channel operation perspective, the quality of omnichannel hardware integration can be measured by the customer channel control experience, including channel attribute familiarity, channel type matching, and cross-channel access to these three important dimensions. Finally, the quality of omnichannel software integration is measured by customer and retailer interaction’s consistent experience from the service marketing perspective. According to the standardization coefficient results, information cross-channel consistency and service cross-channel support significantly impact interactive consistent experience.

Second, in a highly integrated retail environment, dynamic emotional responses to customer self-regulation processes are stimulated, and retention intentions are enhanced in return for the retailer’s integration efforts. The path analysis results show that optimizing channel control experience was conducive to improving customers’ satisfaction with a single transaction and increasing their satisfaction with their retailers. Customers’ interactive consistent experience has a significant positive correlation effect on transactional satisfaction and positively correlated retailer satisfaction. Besides, the interactive consistent experience has a higher impact on customer satisfaction than the channel control experience, supporting the importance of channel integration literature to prioritize research on content and service integration (Miranda et al., 2018; Shen et al., 2018). It added empirical support to the research literature on channel integration in an omnichannel environment.

Finally, we demonstrate the moderating effect of consumer experience on omnichannel integration experience (Saghiri et al., 2017). Showrooming experience positively moderates the relationship between interactive consistent experience and transactional satisfaction, and retailer satisfaction. However, customer showrooming experience cannot moderate the relationship between channel control experience and satisfaction, which is different from the previous research (Li et al., 2018): Showrooming positively mediates the negative effect between channel integration and the uncertainty of retailers. This research reveals that the customer showrooming experience represents the skill level of customers’ cross-channel use. Therefore, it provides a sense of control highly correlated with the uncertainty risk. According to the self-efficacy theory, the channel control experience represents the degree of customers’ free use of the channel. Therefore, experience control, to some extent, made up for the gap in customers’ ability to switch channels, and the impact on customers with different experiences may not be very different.

5.2. Theoretical Implications

This research contributes to this emerging research direction in the following ways. First, this research provides new insights into customer experience in the context of omnichannel integration. Recent studies have shown that customers are increasingly seeking the quality of shopping experiences. The diversified choices of channels, seamless contact points, and personal preferences are considered the driving force for the rapid development of omnichannel retailing (Mishra et al., 2021). Previous research on customer experience mainly focused on traditional channel strategies, and little attention has been paid to the omnichannel experience. This research determines the multi-dimensional structural framework of omnichannel integration experience by considering the integration attributes of omnichannel retailing by combining it with interactive marketing and channel operation. The framework expands the research scope and enriches the understanding of customer experience in a channel-intensive, dynamic marketing environment.

Second, the self-regulating attitude theory is adopted in this study to explain how customers’ experience evaluation of omnichannel retail reflects their psychological mechanism and drives their retention intention. This research expanded the explanatory power of the self-regulation process in the omnichannel context. It enriched the theoretical understanding of how omnichannel integration experience can influence customers’ retention intention through the “Stimulus-Organism-Response” mechanism.

Furthermore, this research explores the boundary condition of omnichannel retailing integration. In the relevant literature, such as retailing sales (Fassnacht et al., 2019), the “showrooming phenomenon” is mainly regarded as a negative existence. Although some studies have explored the positive effect of showrooming in integrating multichannel, they have neglected its impact on the psychological and cognitive aspects (Li et al., 2018). This research considers showrooming experience just like self-efficacy, enhancing consumers’ perceived control of diversified channel selection. Thus, this research explores the positive impact of showrooming, enriching, and complementing the research on customer feature subdivision management under omnichannel retailing.

5.3. Managerial Implications

This research provides some necessary suggestions for the practice of omnichannel retailers. First, omnichannel integration needs to improve customers’ channel control experience. All channel attributes of retailers should be open and transparent so that customers are more familiar with omnichannel attributes, which reduces the perceived risk of customers using new channels. Meanwhile, providing customers with enough channel types helps meet customers’ flexible matching of channel demands in different stages. As a result, customers can feel the freedom of channel use; finally, the friction of switching channels should be reduced to make cross-channel access more convenient and smoother.

Second, omnichannel integration requires retailers to aim at interactive consistency in service marketing to maximize channel synergies. No matter which channels customers contact, retailers must ensure that customers perceive a consistent image of retailers. Retailers should pay attention to two aspects of consistency in their interaction with customers: information and service. First, retailers ensure that each channel conveys consistent content to avoid customers receiving contradictory information when obtaining information from different channels and reducing the psychological cost of information processing. Second, retailers should ensure the consistency of customers’ cross channel services. For example, retailers can provide after sales offline service for online products. The support degree of retailers’ cross-channel services will improve retailers’ responsible image and reduce customers’ distrust of retailers.

Besides, this research also proves that customers’ showrooming experience may lead to adverse effects such as “free-riding, ” which also positively influences customer retention in omnichannel integration. Therefore, retailers should pay attention to the customer groups with showrooming behavior and optimize the showrooming experience. Furthermore, implementing omnichannel interactive integration for the customer groups with showrooming experience can better promote the customer attitude and retention intention. In other words, when dealing with showrooming customers, retailers should not only focus on the short-term negative substitution effect of offline channels but also focus on the long-term positive complementary impact on channel integration quality—attracting such customers through marketing efforts, promoting customer relationships, and strengthening customer locking.

5.4. Limitations and Future Research

This research has a few limitations that can provide some directions for future work. First, this research was conducted via Chinese consumers. Cross-cultural research’s external validity should be tested because of cultural differences in consumers’ emotional response to omnichannel retailing. Secord, we adopt self-reported cross-sectional data regarding customer experience. Finally, in the future, panel data should be adopted to enable a more accurate and dynamic analysis of the impact of omnichannel integration on customer retention intention.

*Acknowledgments:

We sincerely thank the editor-in-chief and anonymous reviewers for their comments. This paper was supported by the China Postdoctoral Science Foundation (2021M690654) and the Jiangsu University Philosophy and Social Science Research Major Project (2021SJZDA033).