Enhancing the Customer's Information-sharing Intention Through Omnichannel Strategies

Abstract

Purpose: An omnichannel strategy creates a consistent brand image and customer experience across all channels, making it easier for customers to interact with a business and share information. This research aimed to investigated the relationship between consumers' information-sharing intention and their omnichannel experiences. Research design, data, and methodology: Through an online survey conducted in Vietnam, the study obtained 915 responses. The study used Partial Least Square Structural Equation Modeling (PLS-SEM) to analyze research data and confirm proposed research hypotheses. Results: Research results indicated that information-sharing intention is affected by both online and offline customer experience, and at the same time, the study also confirmed that omnichannel's three characteristics (integration, individualization, interaction) positively impact on customer experience. Conclusions: From the research result, businesses may boost consumer trust and loyalty with the help of an omnichannel approach, which in turn increases customers' propensity to provide personally identifying information to the firm. One way to do this is to facilitate information exchange by delivering customized and relevant offers. Furthermore, companies show consumers the benefit of providing their data by utilizing it to enhance the customer experience.

1. Introduction

Internet availability and mobile phone use have altered human behavior, expectations, and consumer relationships with companies. Empowered customers today demand to interact with companies and have a consistent experience across all touchpoints. Furthermore, depending on the situation, customers transition from one channel to another or one touchpoint to another, resulting in omnichannel behavior (Furquim et al., 2022). New channels, especially digital ones, have emerged due to changes in consumer behavior and the proliferation of digital technologies and innovations. However, if customer interactions are not connected and defined at the customer level, adding new channels and touchpoints for consumers to communicate with organizations is futile. If multi-channel refers to the facilitation and upkeep of several channels, then an omnichannel approach to customer experience would suggest that all these channels work together to provide a seamless and meaningful interaction between the company and the consumer. The term "omnichannel management" refers to managing several channels and points of contact with customers in concert to improve both the customer experience and the business's overall efficiency and effectiveness (Khoa & Huynh, 2023).

An omnichannel strategy involves providing a seamless customer experience across all channels, such as in-store, online, and mobile. This can be achieved by integrating customer data and creating a consistent brand image across all channels. By implementing an omnichannel strategy, businesses can increase customer trust and loyalty, increasing the customer's intention to share information with the company. This can be done by providing personalized and relevant offers and sharing information easily and conveniently. Additionally, by using customer data to improve the customer experience, businesses can demonstrate the value of sharing information and building trust with customers. In today's highly competitive global market, when customers have several options and switching providers is inexpensive, prioritizing the customer experience as a means of setting oneself apart from the competition is essential. Also, customers' propensity to make purchases across several channels is affected by the excellence of those interactions (Hung & Khoa, 2022; Lee & Wu, 2017). As pure Internet businesses like Google, Apple, Facebook, or Amazon become direct potential competitors for nearly every traditional organization, it has become crucial to understand customer behavior to design an omnichannel strategy. In addition, the COVID-19 pandemic has caused significant changes in several consumer behaviors, including online shopping (Barta et al., 2021). Because of this, businesses have had to make rapid adjustments, elevating digital transformation and omnichannel customer experience from marketing jargon to strategic objectives.

Despite the fast rise of sharing commerce systems, academic attention is paid to them, and how trust may be created in online commerce platforms warrants much more attention, study, and debate. Indeed, electronic commerce platforms where non-business entities engage face-to-face usually raise greater privacy problems and vulnerabilities than e-commerce. Because of the absence of actual interaction, trust in internet companies is more difficult to establish than in offline firms (Ayaburi & Treku, 2020). Sharing commerce marketplace products are non-standardized, emphasizing the significance of the customer’s customer experiences level; each rental and its owner is unique. As a result, it is more difficult for omnichannel to deliver dependable products.

This study is based on the Stimulus-Organism- Response model (SOR) to identify the relationship between omnichannel characteristics (integration, interaction, individualization), customer experience (online and offline experience), and customer information-sharing intention. From the result, some managerial implications are proposed for businesses to enhance the customer’s information-sharing intention through customer experiences in omnichannel. This study added to the subject of customer experience by examining consumers' interactions in-store and online with a single firm, shedding insight into how the performance of multiple sales channels may impact one another.

The following is how this paper is structured. The next part provides a survey of the available literature to provide the groundwork for the theoretical framework. It is offered the study model used to explore the relationship between the research constructs. In this part, the content explains and justifies each of the hypotheses. The third part describes the study methodology, followed by the results and a discussion of survey findings. The last portion discusses the practical and theoretical consequences of the results, the study's shortcomings, and future research ideas.

2. Literature Review

Recently, the SOR framework was used to detect consumer online activity. It was studied to understand better online customer behavior and consumers' emotional and behavioral responses to omnichannel merchants. A recent study demonstrates the interconnectedness of the Stimuli-Organism-Response system in an online setting. In this research, omnichannel qualities such as integration, individualization, and interactivity are stimuli that produce customer experiences. Furthermore, customer experiences might be a mediator in predicting the consumers' desire to share information (Nyrhinen et al., 2022; Yin et al., 2022). This part presented the omnichannel and its characteristics, customer experience, research framework, and hypotheses development.

2.1. Omnichannel and Its Characteristics

Omnichannel commerce integrates all channels into a unified system. Every channel on this platform may "see" what the others are up to, allowing for the possibility of coordinated policy and strategy adjustments. Omni-channel retail is more advanced than multi-channel retail since it involves a unified image of profiting on the market for a product or service. All channels that add to the product's market value will benefit. Unlike multi-channel purchasing, this method requires interaction between offline and internet stores.

The term "bricks and clicks retail" was used to describe the complementary nature of the brick-and-mortar store's physical location and the Internet-based store's virtual one (Turban et al., 2018). It targets young people who can shop through multiple channels (Vasiliu et al., 2016). For this reason, emphasizing that omnichannel facilitates customer purchases across channels cannot be overstated. An example of cross-channel behavior would be a customer who sees an advertisement for a product on television and then goes to a physical store to buy it.

According to previous studies, omnichannel commerce necessitates some characteristics, including integrated (Beck & Rygl, 2015), personalized (Ailawadi & Farris, 2017; Cui et al., 2020), and interactive omnichannel shopping (Berman & Thelen, 2018; Verhoef et al., 2010). An omnichannel merchant caters to the needs of their customers by providing a unified shopping experience across all channels and paying close attention to their feedback. The digital experience is only one aspect of omnichannel retail that has been the subject of research (Hilken et al., 2018), shopping process continuity (Chen et al., 2018), and numerous payment options (Shi et al., 2020). Buyer responses to omnichannel retail may be measured in several ways, including repeat business and shopping intent (Gao et al., 2021; Zhang et al., 2018). So, this research, drawing on the existing literature, focuses on three factors that promote omnichannel retailing: Customer experience is comprised of three interconnected elements: (1) integration, or the management of all available channels or touchpoints to deliver a seamless customer experience; (2) personalization, or the meeting of customers' unique needs; and (3) interaction, or the opportunity to engage with the business, the brand, or other customers.

2.2. Customer Experience in Omnichannel

Customer experiences have been a major concern for practitioners and academics for the last decade. Several scholars and researchers have provided definitions of customer experiences in this context. Holbrook and Hirschman (1982) pioneered the notion of customer experiences. They speculated that the mental balancing of price and value might account for a small fraction of actual consumer behavior. They suggested a shift from the current information processing paradigm to one that gives more weight to one's inward experiences, feelings, and subconscious. The intention was to provide a whole picture of the consumer experience, including intellectual, emotional, spiritual, and sensual dimensions. Therefore, consumer encounters may be an amorphous, out-of-control phenomenon (Verhoef et al., 2010).

The term "customer experience" refers to consumers' impressions and feelings after interacting with a company's products, services, and marketing (Gao et al., 2021). The increasing emphasis from both businesses and universities has focused on the customer experience because of its significant influence on a company's competitive edge (Becker & Jaakkola, 2020). Experts in marketing, service and tourism have extensively studied the knock-on effects of poor customer service. Furthermore, they found that excellent customer service may lead to brand loyalty, satisfaction, word of mouth, shopping frequency, brand equity, and trust. Furthermore, according to certain research, customer experience might reduce negative outcomes such as perceived risk (Chauhan & Sarabhai, 2019; Rahman et al., 2022).

Although this research has added to our understanding of consumer experience, most have focused on either offline or online contexts. Few studies have examined the omnichannel consumer experience, and those that have tended to be descriptive (Shi et al., 2020). How customers feel when their online and in-person interactions with a company collide when they use an omnichannel service is only one of many important questions that have yet to be answered. To this end, more data-driven studies of the omnichannel customer experience are required. In omnichannel purchasing, consumers purchase over many channels (including online and in-store) (Shen et al., 2018). Therefore, the omnichannel consumer experience must include both the digital and the brick-and-mortar dimensions (Siqueira et al., 2019). One research found that companies need to consider customers' preferences across channels to provide omnichannel customers with a seamless experience (Picot-Coupey et al., 2016). Therefore, businesses adopting an omnichannel approach have a huge challenge: coordinating their customers' offline and online experiences. Successful channel inconsistency management is a prerequisite for omnichannel enterprises.

2.3. Research Framework and Hypotheses Development

Mehrabian and Russell (1974) developed the SOR paradigm, in which environmental stimulation (S) results in emotional response (O), promoting behavioral response (R). Several academics have stated its significance in retail contexts from diverse fields, such as purchase decisions, impulsive purchasing, and service fairness. Numerous SORbased marketing research studies indicate the link between emotional reaction and customer response regarding intention, purchase, consultation, and return.

Zhu et al. (2019) have recently used the SOR framework to identify customer online behavior. It was investigated to understand online consumer behavior and consumers' emotional and behavioral reactions to omnichannel retailers. Recent research confirms the interdependence of the Stimuli-Organism-Response in an online environment. In this study, omnichannel characteristics, such as integration, individualization, and interaction, are stimuli (Yin et al., 2022) which create the customer experiences. Moreover, customer experiences can be considered the antecedent of the customers’ information-sharing intention (Nyrhinen et al., 2022). The theoretical model is presented in Figure 1.

Figure 1: Theoretical Model

Consumers' propensity to disclose personal information is influenced by several factors, some of which have been identified by previous marketing and information systems studies. Consumers' reluctance to provide firms with personal information stems largely from misgivings about the safety of their data, as shown by several studies (Mutimukwe et al., 2020). Customers concerned about their privacy avoid revealing personal information to internet shops. The consumer's characteristics, the nature of the information being shared, and the context in which it is being shared may all impact the customer's comfort level with disclosing that information (Khoa & Huynh, 2022). Data suggests that consumers are less likely to provide sensitive information, and younger consumers are more willing to divulge personal data than their more seasoned counterparts. Some related studies were summarized in Table 1.

Table 1: Some Related Studies in Customer Experience, Information Sharing in Omnichanel

Satisfying customer experiences increases a customer's confidence in the store, positively impacting informationsharing intention (Nyrhinen et al., 2022). Customers agree to give information, such as their data, to shops they trust, but only in exchange for a good customer experience. Furthermore, there is a reciprocal relationship: with consumer data, a shop may customize and give better customer experiences (Piccialli & Jung, 2016). customer experiences may be automatically customized depending on client data in sophisticated online commerce. Hence, this study proposed hypotheses H1 and H2:

H1: Online customer experiences positively impact the customers’ information-sharing intention on omnichannel.

H2: Offline customer experiences positively impact the customers’ information-sharing intention on omnichannel.

The synchronization of online and offline channels is called integration (Thaichon et al., 2022). Studies show that the younger the client, the more personal information they are willing to provide, whereas the older they are, the less likely they are to expose it (Berman & Thelen, 2018). This integrated strategy combines all touchpoints and channels to provide customers with a smooth purchasing experience (Beck & Rygl, 2015). Customers must work harder to remember contradictory information if they are presented with too much data or sensory impulses across several channels (Dolbec & Chebat, 2013). Confidence in a company's abilities is harmed when customers experience frustration and confusion due to receiving contradictory information or services from different channels. Maintaining aesthetic cohesion across platforms helps create experiences that are consistent, recognizable, and memorable for customers. Sensory brand experiences may be used to connect to a brand, especially when cognitive consistency and sensory variety help flush out the sensory memories from long-term memory (Iglesias et al., 2019). Hypotheses H3 and H4 were proposed:

H3: Integration positively impacts online customer experiences on omnichannel.

H4: Integration positively impacts offline customer experiences on omnichannel.

Individualization describes a company's prowess in incorporating consumer feedback, adapting to customers' ever-evolving wants and requirements, and delivering customized goods and services through their preferred channels (Lehrer et al., 2018). Customers demand consistent, real-time, and tailored experiences across all channels of communication and purchase (Komulainen & Makkonen, 2018). Personalization aims to maximize customer satisfaction by providing them with the greatest possible service and goods (Tyrväinen et al., 2020). Additionally, it provides customers with tailored suggestions based on their habits and interests, such as more specific brand marketing or purchasing websites (Berman & Thelen, 2018). The best suggestions are those that cater to the customer's aesthetic tastes and satisfy their senses. Furthermore, it has been shown that giving customers what they want through customized information may lead to good feelings, which can impact their emotional and cognitive experience (Tyrväinen et al., 2020). Thus, this study predicted that:

H5: Individualization positively impacts online customer experiences on omnichannel.

H6: Individualization positively impacts offline customer experiences on omnichannel.

The term "interaction" is used to describe the many ways in which customers may engage with businesses across several media. To strike the optimal balance between physical and online distributions, omnichannel retailers focus on their interplay (Ailawadi & Farris, 2017). The traditional divide between one-way and two-way interaction channels is blurred in omnichannel settings. In omnichannel commerce, in addition to the traditional channels of distribution and interaction (such as payment, consumption, and after-purchase services), a retailer may also use communication channels to reach out to customers and sell to them. Retailers may benefit from letting customers try things by giving them more confidence in their purchases, stirring up positive emotions, and encouraging them to use the product for longer (Verhoef et al., 2015). Academics have recommended a sensory contact approach to improve brand recognition and loyalty by encouraging customer participation on both cognitive and affective levels (Wiedmann et al., 2017). A good case in point is IKEA Norway, which in 2007 began offering a free overnight service where clients may stay in specially constructed guestrooms. Customer engagement improves sensory and physiological experiences (Petersen et al., 2004). Consequently, the rest hypotheses were proposed:

H7: Interaction positively impacts online customer experiences on omnichannel.

H8: Interaction positively impacts offline customer experiences on omnichannel.

3. Research Method

The researchers tried using convenience products, including food, clothing, and cosmetics, as case studies. To continue, the researchers asked participants if they were familiar with or had recently seen a product combination that provides omnichannel solutions. Then, the respondents were given several questions about their omnichannel shopping experiences. The partial least square structural equation modeling (PLS-SEM) was used to examine the proposed research model. The data after the screening was processed by SmartPLS software following the data process proposed by Hair Jr et al. (2016).

In this study, the sampling method is purposive sampling. Selection criteria were applied to target Vietnamese respondents aged 18 years and above who had bought from omnichannel during the last 12 months. The survey was conducted for 7 months, from January to July 2022. When panel members agreed to participate in the survey, they received an email with a link to the questionnaire. As the questionnaire was designed to be completed, participants were given online rewards to encourage completion. There were 915 respondents, and their demographic summary is performed in Table 2.

Table 2: Participant Demographic

An online survey was administered to Vietnamese customers who had made purchases through many channels to compile the research data. The questionnaire provided a concise overview of the omnichannel concept. All scales in this research were adapted from prior research. 6 items measured integration (INT), Individualization (IND) was measured 4 items, and Interaction (INE) measured by 5 items; were retrieved from Yin et al. (2022). Online (OnCX) and Offline (OfCX) customer experiences were measured by three items per construct (Gao & Fan, 2021). Finally, the customer’s information-sharing intention (ISI) was modified from the research of Hur et al. (2017). 5-point Likert scale was used to measure all research constructs.

4. Data analysis

Cronbach's Alpha (CA) and Composite Reliability (CR) were used to determine internal consistency reliability, which is more than 0.7; it is regarded as dependable (Leung, 2015). Table 3 shows that CA and CR are both dependable. The Average Variance Extracted (AVE) is supposed to be larger than 0.5; moreover, each indication's outer loading value must be greater than 0.708 (Hair Jr et al., 2016). Consequently, all constructs were convergent validity.

Table 3: Reliability and Convergent Validity

The Fornell-Larcker criteria were used to assess discriminant validity. The top variable correlation value in each column is greater than the correlations between latent constructs, showing that discriminant validity is proven using the Fornell-Larcker criterion (Fornell & Larcker, 2018). Finally, the reflecting measurement model proved sufficient convergent and discriminant validity. The Fornell-Larcker index in Table 4 indicates that the discriminant validity requirements are met. The model may be used to examine structural models.

Table 4: Discriminant Validity

The structural model was pre-tested for predictive accuracy, fidelity, and validity by inspecting its variance inflation factor (VIF), coefficient of determination, and predictive relevance. An absence of collinearity in the data has been deemed to exist if inner VIF values are less than 5 (Hair Jr et al., 2016). Table 5 shows that the inner VIF values of the constructed objects are below the threshold value as determined by this research. Therefore, the result provided further evidence of the model's robustness and revealed no collinearity in the data used in the current investigation.

Table 5: VIF

Table 6 points out the result of R², f², and Q². Validating the model's in-sample predictive capability are R² values of 0.401 for customers' intentions to share information, 0.266 for offline customer experience, and 0.545 for online customer experience. Q² scores much above zero when using a 7-point omission distance for blind prediction demonstrate the model's predictive significance for out-ofsample prediction. Moreover, the effect size of OnCX on ISI; and INT on OnCX were medium (f² > 0.15), and the rest effect size was small (f² > 0.02) (Hair Jr et al., 2016).

Table 6: f², R², Q²

This study used bootstrapping with 5,000 resamples to test the stated hypotheses. For hypothesis testing, the path coefficient and t-value are utilized. Table 7 shows the results of PLS-SEM. Online customer experiences strongly impact the customer’s information-sharing intention (Beta = 0.460, t = 11.749), and offline customer experiences positively affect the customer’s information-sharing intention (Beta = 0.262, t = 6.598), which supports H1 and H2. Similarly, the research claimed that integration positively impacts online customer experiences (Beta = 0.352, t = 8.785) and offline customer experiences (Beta = 0.198, t = 4.914); hence, H3 and H4 were supported. Online customer experience was also influenced by Individualization (Beta = 0.155, t = 3.923); and Interaction (Beta = 0.258, t = 7.722); consequently, H5, and H7 were supported. Results from Table 6 also supported two rest hypotheses, H6 and H8, as Individualization (Beta = 0.234, t = 5.424); and Interaction (Beta = 0.226, t = 5.757) positively impacted the offline customer experience. All hypotheses were supported by a 99% of confidence level.

Table 7: PLS-SEM Result​​​​​​​

5. Discussion

As a result, online and offline customer experiences have emerged as a valuable weapon for merchants seeking a competitive edge by collecting information from customers’ sharing. Most past research on customer experience has focused on either online or physical settings, with little emphasis dedicated to the omnichannel retailing environment (Shi et al., 2020). Rising mobile technologies have transformed the consumer experience, and the lines between channels are blurring. Customers have shifted from single-channel purchasing procedures to purchase journeys that integrate several channels fluidly and interchangeably (Flavián et al., 2020). For example, consumers may search for things on the internet and then visit a real shop to validate the information and make a purchase; they inspect a product in person and then order online. Thus, the question of how shoppers' offline and online interactions influence their mental state and their propensity to divulge private information in an omnichannel retail setting remains unanswered (Nyrhinen et al., 2022).

Besides, omnichannel characteristics positively impact customer experience. Customers feel more control of their purchase experience when they see channel integration. Furthermore, the ambient signals of multiple channels instore influence customers' perceptions and emotions (Lazaris et al., 2022). Consumers are more likely to remain and engage with the retail environment if they have favorable emotional and cognitive experiences. Combining omnichannel signals in the physical shop has been demonstrated to impact customers' enjoyment and arousal, favorably affecting their buying behavior (Raney & Bryant, 2019). By integrating customer data and creating a consistent brand image across all channels, businesses can provide a seamless customer experience. This means that customers can easily transition between different channels and have a consistent experience, whether in-store, online, or mobile. For example, if a customer starts browsing products online but then decides to visit a physical store, integration allows the store associates to access the customer's browsing history and provide a more personalized and relevant shopping experience. Additionally, integrating customer data can enable businesses to provide personalized and relevant offers, increasing customer loyalty and trust, which leads to increased sales and customer retention. Integration is crucial for creating a positive and seamless customer experience across all channels, enhancing customer satisfaction and loyalty (Hamouda, 2019b).

In addition, customers make purchases depending on how they feel about a product (Rahman et al., 2022), and if customization makes customers feel better about a brand, they are more likely to have a positive experience with the product. Retailers employ big data analysis tools, for instance, to provide specific customer discounts (Lehrer et al., 2018). These customized product suggestions save clients time and encourage them to use and purchase (Tyrväinen et al., 2020). For instance, consumers may make more educated decisions by customizing pricing data. Finally, today's interactive touchpoints serve as mental and emotional meeting places for brands and customers to bond and share experiences. Customers are increasingly creating material for personal use or publishing, such as online conversations and articles, thanks to the proliferation of mobile devices and social media (Khoa, 2023; Omar et al., 2021). Recent research suggests that customer attitudes and subsequent purchases are affected by user-generated material that is brand-related (Thakur & AlSaleh, 2018).

6. Conclusion

This research showed that omnichannel qualities, including integration, interaction, and personalization, positively impact online and offline customer experience. Integration has the strongest impact on the online customer experience, and individualization has the strongest influence on the offline customer experience as they purchase from omnichannel systems. Moreover, the finding is interesting as the customer can share information if they have good experience in the shop and online system such as a website or mobile applications.

This research contributes to the theory. This research aimed to provide a bridge between the fields of customer service research in traditional stores and e-commerce platforms. This research contributes to the field of customer experience by evaluating the interplay between customers' in-store and online interactions with a single company, and by doing so, it sheds light on how the success of different sales channels might influence one another. The results clearly describe the customer experience in an omnichannel scenario, enriching our knowledge of customer experience. The information-sharing intention in omnichannel is very important. The resulting research points out that information-sharing intention was impacted by online and offline customer experience. Access to customer information helps companies learn more about their clientele, improve their products and services, and reach out to them more effectively. While both businesses and consumers stand to gain from an increased focus on customer data, the challenge for businesses is in getting customers to trust them enough to provide their information in the first place.

Second, professionals, from sales and service managers to omnichannel brand strategists, are concerned with the customer experience's impact on service success. Based on our findings, practitioners can learn several important lessons about creating unified retail channels and improving omnichannel consumer experiences. This research result shows that customers want a unified shopping experience across brick-and-mortar stores and digital marketplaces. Practitioners (such as marketing directors and brand marketing managers) should be cognizant of the challenges inherent in ensuring a seamless transition between a customer's in-store and online experiences. That is why successful retail managers pay special attention to all available retail channels to improve their customer's overall satisfaction. Furthermore, customers prioritize highly consistent omnichannel customer experiences above less consistent ones. Brand marketers and retail management must realize the significance of a cohesive omnichannel customer experience in influencing customers' final purchases.

Furthermore, the backing from upper management should be appreciated because of the significant difficulty in allocating and distributing resources to multiple channels during the retail channel design process. A company's top brass may prioritize retail channel design as an enterprise-wide deployment, using their authority to create a customer-friendly, well-balanced retail channel system. Moreover, companies, to prevent service failure, should prioritize ensuring a positive customer experience in traditional brick-and-mortar stores before shifting their focus to e-commerce.

This study surveyed our clientele to gather information for our model. Our cross-sectional sample may limit our capacity to draw causal conclusions, despite our model testing supporting the expected associations. Research in the future might use a longitudinal design to verify a causal link between omnichannel customer experience and service results. Secondly, the studies were carried out in Vietnam. This might restrict how far our results can be applied. Our results on the efficacy of consistency across an omnichannel consumer experience may not translate to other nations. The results of future studies might be applied to different cultures to see whether our theories hold up.