The traditional e-commerce business model becomes commoditized, and digital attackers are experimenting with new retail models in which the typical customer journey is likely to be a mix of offline and online, or omni-channel [1
]. Customers may evaluate products online and buy offline, or touch and feel offline and shop online, or even shift constantly between the offline channel and online channel [4
]. Omni-channel practice has developed rapidly, with at least 60 percent of shoppers now excited about omni-channel services; this is particularly the case in China, where the overwhelming majorities of shoppers—85 percent—are already omni-channel customers [6
]. However, some of these omni-channel customers may suffer from imbalanced resources or inconsistent treatment quality across different channels. This highlights the vital challenge to brands and retail companies of shaping and managing the omni-channel customer experience [7
Customer experience is defined as a customer’s holistic judgment of a firm’s offerings during indirect and direct encounters with the firm [5
]. Engendering optimal customer experience is vital for a firm to acquire successful marketing outcomes, and increase the likelihood of success [10
]. Thus, building a superior customer experience has become an important leading management objective [9
]. Optimizing customer experience lies at the heart of both physical retailing [17
] and virtual retailing services [19
]. Accordingly, the effectiveness of customer experience is becoming an essential and popular research topic in the retailing and services literature [14
Despite these fertile studies, research on customer experience has three main gaps. First, omni-channel businesses have become more and more common, as many customers alternate between offline channel and online channel [26
]. Thus, omni-channel businesses represent an unprecedented opportunity for brands and retail companies to leverage synergies between channels to synchronize customers’ multichannel experiences [27
]. Great efforts have been made to examine customer experience in both the offline channel environments (in the physical retailing literature) and online channel settings (in the virtual retailing literature), yet few studies have integrated offline and online research perspectives or developed an omni-channel understanding (Research Gap 1) of customer experience [5
Second, stemmed from channel integration research, omni-channel consistency has been well-defined as the integrated interaction quality which involves two dimensions: content consistency and process consistency [29
]. Based on these two dimensions, extant research has shed light on various types of channel consistency, such as promotion congruence [31
], visual e-channel congruence [32
], image congruity [33
], cross-channel congruence [1
], and retailer-brand incongruity [34
]. Although customer experience captures a holistic judgement of interaction quality, and it is becoming the norm for customers to expect a consistent shopping experience across different retail channels [28
], there has been little research on the consistency of multichannel customer experiences [35
]. Further, although customers experience offline and online channels separately, without exception, prior studies applied unilateral and holistic measures, and none used a dyadic measurement methodology for consistency (Research Gap 2) in comparing offline customer experiences with online ones [20
Third, the inconsistency between multichannel touch points can decrease customers’ omni-channel shopping value, cause confusion and incomprehension, and even result in negative emotions including frustration, anger and disappointment [1
]. Expectation disconfirmation theory (EDT) proposes that these undesirable evaluations result from one of the two directions of inconsistency between experiences and expectations—that is, positive inconsistency or negative inconsistency [36
]. Despite a great deal of research have identified the severe consequences of multichannel inconsistency [23
], there is limited research on the directions of this inconsistency (i.e., whether offline customer experiences surpass online customer experiences, and vice versa) in the customer experience literature (Research Gap 3).
To fill up the above research gaps, this research uses the EDT lens to scrutinize the dyadic nature of omni-channel customer experiences; that is, the “(in)consistency” between offline customer experience and online customer experience. Specifically, we intend to explore two research questions, as follows. (1) How does (in)consistency in omni-channel customer experiences influence brands’ and retail companies’ service success? (2) What kind of inconsistency in omni-channel customer experiences should brands and retail companies address to avoid service failure? In answering these research questions, the present study makes contributions to current literatures in three aspects. First, the current study contributes to the customer experience studies via introducing an omni-channel perspective that bridges customer experience research in offline and online retailing environments. Second, this study also contributes to the channel consistency research by using an indirect research view to capture customer experience consistency. Third, we contribute to expectation disconfirmation theory by comparing the influences of the two inconsistency directions. Thus, on the one hand, this study extends the theoretical perspective on the omni-channel consistency of customer experiences; on the other hand, it provides advices for retail channel design in customer experience management.
Before developing the corresponding hypotheses, to better pinpoint the different combinations of online and offline customer experiences, we propose a two-by-two matrix (see Figure 2
) that juxtaposes the quality of customer experiences (i.e., high vs. low) with the source of those customer experiences (i.e., online channel vs. offline channel). As indicated by the matrix, quadrant 1 represents customer experiences consistent at high levels of quality, quadrant 2 represents customer experiences consistent at low levels of quality, quadrant 3 represents customer experiences inconsistency where online customer experiences are better than offline ones, and quadrant 4 represents customer experiences inconsistency where offline customer experiences are better than online ones.
We use EDT to provide theoretical support on the potential outcomes of consistency and inconsistency. EDT has roots in the marketing literature and has received vast attention in consumer behavior research [36
]. EDT research address that customers obtain satisfaction through following the causal flow: first, forming initial beliefs and expectations when starting to use the product or service [48
]; second, cognitively comparing performance during a subsequent period against initial expectations and calculating the (dis)confirmation [47
]; and finally, determining their satisfaction level according to “a combination of expectations and disconfirmation” [37
] (p. 283). Based on the EDT, expectation represents a set of pre-exposure beliefs about the product or service [37
], and disconfirmation is “a subjective post-usage comparison that can result in one thinking performance was better, the same as, or worse than expected” [49
] (p. 89).
Following this logic, we propose that in an omni-channel retailing context, a customer’s expectation is a consistent, interchangeable, and seamless shopping journey [1
]. When the customer’s experience on the second channel exceeds (falls short of) his/her experience on the first channel, positive (negative) disconfirmation occurs [50
]. In the present study, we use the notions of “expectation-(dis)confirmation” to differentiate customer experience consistency from inconsistency (i.e., quadrants 1 and 2 vs. quadrants 3 and 4). The EDT also posits that outcome evaluations are a function of disconfirmation magnitude between expectations and experiences such that satisfaction increases as the disconfirmation magnitude decreases and the degree of confirmation increases [36
]. In this research, we use the notions of “disconfirmation magnitude” to differentiate the two scenarios of consistency (i.e., quadrant 1 vs. quadrant 2) and the two directions of inconsistency (i.e., quadrant 3 vs. quadrant 4).
3.1. Differentiating Customer Experience Consistency from Inconsistency
Applying the tenets of EDT to differentiate customer experience consistency from inconsistency, expectation confirmation increases as customers’ online and offline ratings of experiences become increasingly similar (i.e., high-high and low-low ratings: quadrants 1 and 2 of Figure 2
), and expectation disconfirmation increases as customers’ online and offline ratings of experiences diverge (i.e., high-low and low-high ratings: quadrants 3 and 4 of Figure 2
). When customers perceive both online and offline experiences to be of a high quality, excellent and superior omni-channel customer experiences are consistent. Similarly, when customers perceive both online and offline experiences to be of a low quality, mediocre or even disappointing omni-channel customer experiences are consistent. However, when customers’ expectation of a consistent shopping journey is unrealized, inconsistency occurs between the offline and online customer experiences.
Based on EDT, customers are more likely to develop satisfaction as the consistency of customer experiences increases. Before engaging a brand’s services through either online or offline retail channels, customers usually develop an initial expectation that the services from both channels ought to be seamless and consistent [1
]. Through navigating the different purchase stages of the customer journey, isolated experiences pertaining to online and offline channels are built up [5
]. As the isolated online and offline customer experiences are consistent (regardless of whether they are consistently high quality or low quality), customers will cognitively recognize the consistency, and their initial expectations will be met. Thus, customer experience consistency has important consequences for customer satisfaction, as satisfaction follows when customers’ expectations are met [37
EDT also suggests that customer satisfaction will decrease as the inconsistency of customer experiences increases. EDT posits that any disconfirmation between experiences and expectations, whether negative or positive, will produce negative resulting outcome evaluations [36
]. When the inconsistency between offline and online customer experience increases, a customer’s cognitive cost and perceived risk are also intensified [28
]. On the one hand, the customer needs to pay more cognition effort to switch among inconsistent channels [51
]; on the other hand, the purchase task becomes more ambiguous and riskier as the information displayed by different channels becomes asymmetric [52
]. Therefore, even when the experience on the latter channel exceeds the experience on the former channel, disconfirmation still exists where customers’ expectations (i.e., a consistent shopping journey) are not met, which may result in psychological discomfort for customers, affecting their beliefs, attitudes, and actions [53
]. This psychological discomfort could trigger customers’ negative emotional response [21
]. Hence, this study proposes that:
Hypothesis 1 (H1).
The more consistency (compared with inconsistency) between online customer experiences and offline customer experiences, the greater the customer satisfaction.
3.2. Differentiating the Two Scenarios of Customer Experience Consistency
According to EDT, under the condition of customer experience consistency (i.e., high-high vs. low-low ratings: quadrant 1 vs. quadrant 2 of Figure 2
), the quality of customer experiences should be positively related to customer satisfaction. Customers expect exceptional online experiences [20
]. A compelling online experience (e.g., offering location-based content by the use of GPS) increases customers’ engagement, leads them to spend more time on the brand’s website or mobile app, and facilitates the usage of online channels [19
]. Customers also seek exceptional offline experiences [18
]. A pleasurable offline experience can induce customers to try products, taste in-store samples, and, most importantly, to shop [55
Further, positive experiences, whether online or offline, will increase customers’ confidence that they are not being taken advantage of and that the brand is concerned about their welfare [56
]. Such perceptions of honesty, benevolence, and competence by the brand will lead to higher levels of customer satisfaction [57
]. Therefore, brands that offer both online and offline services of outstanding quality can meet customers’ expectations of consistent and excellent shopping experiences. Brands that provide ordinary omni-channel services can meet customers’ expectation of a consistent shopping journey but not their expectation of an excellent shopping experience. EDT posits that outcome evaluations are a function of the size of the gap between expectations and experiences such that satisfaction increases as the degree of confirmation increases [27
]. Therefore, when online and offline customer experiences are consistently high quality than when they are consistently low quality, the customer satisfaction will be higher. Thus, we propose this:
Hypothesis 2 (H2).
Customer satisfaction is higher when online and offline customer experiences are consistent at a higher level than when online and offline customer experiences are consistent at a lower level.
3.3. Differentiating the Two Directions of Customer Experience Inconsistency
When customers do not have consistent customer experiences between the online shopping channel and the offline retail channel, two outcomes are seemingly plausible (i.e., high-low vs. low-high ratings: quadrant 3 vs. quadrant 4 of Figure 2
). First, many firms are now devoting a large marketing investment to build customer experience via mobile applications and websites [19
], and every aspect of the customer journey, such as product information search and purchase transaction, could be conveniently realized through the online retail channel [20
]. Customer perceptions of online channel experiences may then dominate, rendering offline customer experiences irrelevant. Alternatively, because online shopping is viewed by customers as impersonal and lacking scalability [54
], given customers’ requirements for a sensory evaluation of the product, interpersonal communication, and instant gratification [58
], customer perceptions of offline channel experiences may be a stronger driver of satisfaction.
In discussing the effects of disconfirmed expectations, EDT researchers argue that a negative psychological state of cognitive dissonance occurs when individuals expect a certain event, but they experience something different [59
]. If the disconfirmation magnitude is small, such as in the person’s zone of tolerance, they will adjust their expectations to reduce cognitive dissonance [60
]. However, if the magnitude is large and outside the person’s zone of tolerance, cognitive dissonance will trigger an irreversible negative effect on service outcomes [36
Customers prefer the retail channel that provides the highest value, such as the best information, detailed and accurate product descriptions, and interpersonal interactions [1
]. In the offline stores, customers can physically touch the product, directly assess the product quality, and instantly receive input from salespersons, which is satisfying to them. Customers thus put more emphasis on and have higher expectations for offline shopping [58
]. Therefore, a poor offline customer experience is more unacceptable for customers than a poor online customer experience. Perceiving a better offline customer experience than online customer experience is thus more likely to remain within the zone of tolerance.
Customers are also inclined to select a retail channel that minimizes their time, effort, and psychic costs [61
]. As the increasing adoption of mobile phone technologies, these expectations are much easier to be realized in online retail channels but are challenging for physical stores [1
]. That is, customers expect offline stores to provide a much better customer experience than online stores because they spend more time, effort, and psychic costs on offline channels. Therefore, given the lower levels of online experience quality, a poor-quality offline customer experience is more likely to fall outside customers’ zone of tolerance. As such, customer satisfaction is lower when a customer perceives the online customer experience to be better than the offline one compared to the reverse. Therefore, this study proposes this:
Hypothesis 3 (H3).
Customer satisfaction is lower when online customer experiences are better than offline experiences compared to the reverse.
3.4. Customer Satisfaction as Mediator of the Effect of (In)Consistency on Service Success
EDT suggests that as a function of customers’ prior expectations and disconfirmation, satisfaction can influence their behaviors, including continuance intention and repurchase intention [36
]. Customers’ perception of a brand as a source of consistent and compelling experiences can increase the perceived value of the brand, which may remain fresh in the customers’ memory until their next consumption [17
]. Thus, customer experience (in)consistency may have impact on the service value and repurchase intention [11
]. In addition, a high level of customer experience can promote customers to engage in positive word-of-mouth [18
]. It represents the customers’ willingness to share their experiences with others and recommend that others use or switch to the particular brand [54
]. After perceiving high levels of brand value from their consistent shopping journey, customers are motivated to create positive attitudes toward the brand (e.g., satisfaction) that may generate positive word-of-mouth, such as advocating for the brand’s consistent omni-channel services, high product quality, or acceptable shopping costs [62
]. As such, this study proposes this:
Hypothesis 4 (H4).
Customer satisfaction mediates the relationships between customer experience (in)consistency and customers’ (a) repurchase intention and (b) word-of-mouth.
5. Analysis and Results
H1 predicted a consistency effect such that the greater the consistency between customers’ online and offline experiences, the greater the customer satisfaction. As the result of Model 2 presented in Table 4
, the curvature of the inconsistency line (ONCX = −OFFCX) is significantly negative (
), demonstrating that the higher customer satisfaction results from the equivalent between online and offline customer experiences, and any deviations from the consistency line (ONCX = OFFCX) are associated with lower customer satisfaction. In sum, H1 was supported.
H2 predicted that the high level consistent between online and offline customer experiences produce higher customer satisfaction than the low level consistent. As the result of Model 2 shown in Table 4
, the slope of the consistency line (ONCX = OFFCX) was significant and positive (
), suggesting that the high-high consistency condition was associated with higher customer satisfaction than the low-low consistency condition. Thus, these results suggest support for H2.
H3 proposed an asymmetrical inconsistency effect such that customer satisfaction is lower when customers perceive better online experiences than offline ones compared to when customers perceive better offline experiences than online ones. This reflects the significant negative slope of the inconsistency line (ONCX = −OFFCX). The result of Model 2 in Table 4
shows that the slope for the inconsistency line (ONCX = −OFFCX) was negatively significant (
), thus supporting H3.
H4 predicted that the mediation role of customer satisfaction in the relationship between customer experience (in)consistency and service outcomes (i.e., repurchase intention, word-of-mouth). As presented in Table 5
, the effect of customer experience (in)consistency on customer satisfaction (
) was significant. The impacts of customer satisfaction on repurchase intention (
) and on word-of-mouth (
) both were significant and positive, as predicted. The indirect effect between customer experience (in)consistency and repurchase intention that was carried through customer satisfaction was 0.207 and significant (95% BC-CI [0.131, 0.305]), supporting H4a. The indirect effect between customer experience (in)consistency and word-of-mouth that was carried through customer satisfaction was 0.249 and significant (95% BC-CI [0.179, 0.335]), supporting H4b. In addition, the direct impacts of customer experience (in)consistency on repurchase intention (
) and word-of-mouth (
) were significant, which indicates that the influence of customer experience (in)consistency on service outcomes (i.e., repurchase intention, word-of-mouth) is partially mediated by customer satisfaction. Total effect includes the direct and indirect effect. Thus, the total effect of customer experience (in)consistency on repurchase intention was 0.511. Similarly, the total effect of customer experience (in)consistency on repurchase intention was 0.593.
The arrival of digital technologies is reshaping firms’ retail practices and customer purchase journeys. The boundaries between different retail channels have blurred and faded away, and omni-channel customers often simultaneously use offline and online channels to minimize their inputs and optimize their purchase decisions [44
]. However, omni-channel retailers implementing customer experience management programs still face a vital challenge: how to balance and manage the omni-channel customer experience (in)consistency to achieve service success [28
]. Our study examines how various combinations of online and offline customer experiences differ in driving customer satisfaction and ultimate service success.
The results first reveal that consistency between a customer’s online and offline channel experience is generally better than omni-channel customer experience inconsistency for obtaining customer satisfaction, word-of-mouth, and repurchase intention. In addition, higher levels of customer experience consistency are superior to lower levels for achieving service success. These results align with those of most previous studies [1
] in predicting positive outcomes from omni-channel customer experience consistency.
Unexpectedly, enlightened by the polynomial regression approach, our results also disclose several more nuanced findings on the three-dimensional relationship among online customer experience, offline customer experience, and service outcomes. First, when implemented separately, the online and offline customer experiences exhibit diverse effects: offline customer experience is more effective in improving customer satisfaction, while online customer experience is more effective in influencing repurchase intention and word-of-mouth (see Models 2, 5, and 8 in Table 4
). These results help to consummate the research of Gao et al. [70
], which proposes that customer experience quality is always beneficial to performance outcomes. By differentiating online and offline channels, this study uncovers the distinct effectiveness of multichannel customer experience on service performance.
Second, when the qualities of online and offline customer experience are inconsistent, the offline high-quality/online low-quality configuration is always more helpful than the online high-quality/offline low-quality configuration for improving customer satisfaction. These findings complement the research design of Gao et al. [28
] by interpreting the significant difference between the two directions of inconsistency. All of these results reinforce the importance of customer experience consistency in omni-channel retailing practices. Thus, this study not only provides new evidence into the customer experience literature but also provides practical guidance for customer experience management programs.