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Article

Omni-Channel Intensity and Shopping Value as Key Drivers of Customer Satisfaction and Loyalty

by
Mitxel Cotarelo
,
Teresa Fayos
,
Haydeé Calderón
and
Alejandro Mollá
*
Department of Marketing, University of Valencia, 46022 Valencia, Spain
*
Author to whom correspondence should be addressed.
Sustainability 2021, 13(11), 5961; https://doi.org/10.3390/su13115961
Submission received: 16 April 2021 / Revised: 18 May 2021 / Accepted: 18 May 2021 / Published: 25 May 2021
(This article belongs to the Special Issue Multichannel and Omnichannel Retailing: Latest Advancements and Further Challenges)
Browse Figures
Versions Notes

Abstract

:
Omni-channel retailing consists of the complete alignment of the different channels and touchpoints that generate a seamless experience for consumers, allowing them to move freely through all channels. The consumer’s perception of a seamless and consistent omni-channel experience is called intensity. This study reveals that this intensity in the shopping experience can offer value to consumers, and that intensity and shopping value also influence satisfaction and loyalty. We propose a relationship model that had been tested in a quantitative study with PLS, with a representative sample of buyers who had used the Click and Collect system. The main contribution of this study is to the literature on the analysis of omni-channels from the consumer experience perspective, through an in-depth analysis of the concepts of intensity and shopping value, as well as their relationship with satisfaction and loyalty. The results revealed the existence of a positive relationship between intensity and shopping value, and between these two variables and satisfaction and loyalty.

1. Introduction

Electronic commerce is in its heyday, with constant growth in all countries, driven in part by the consequences of the pandemic and by the emergence of new technologies. Online channels may adopt different formats and coexist and interact with offline channels. This is known as the “omni-channel system”, which has brought about a change in the retail distribution paradigm [1,2].
Omni-channel retailing is described as the full adjustment of various channels and touchpoints, with an optimal-brand consumer experience as a consequence [3,4]. Omni-channel research has largely focused on the retail perspective and therefore needs to broaden its scope to encompass omni-channel retailing to understand and address different problems related to the retail consumer perspective [5]. The rise in omni-channel retailing has made buyers demand improvements in their shopping experience; hence the need for furthermore in-depth research due to the dearth of studies focusing on the omni-channel experience of consumers [6]. Several authors have highlighted the need for further analysis and more in-depth knowledge of aspects related to consumer experience in omni-channel purchase processes to provide a seamless shopping experience [5,7].
Today’s consumers are becoming more and more familiar with navigating on different channels and touchpoints, and expect to make consistent and fluid shopping journeys between these channels and experience so-called “omni-channel journeys” [8]. To ensure a seamless omni-channel experience, the customer needs to perceive that his or her purchase process is consistent and continuous. In this sense, reference [9] defined “intensity” as the combination of consistency and continuity in a process in which several channels come into play. Customers also seek to satisfy their needs through responses that offer them value [10]. Although there is abundant literature on purchase value, research into shopping value (SV) has failed to fully address “omni-channel retailing”, as most studies on SV, with perhaps the recent exception of [11], have focused on single-channel retailing and not on the interaction effects that can arise when consumers purchase at multiple touchpoints [8].
In the omni-channel environment, satisfaction and loyalty have been analysed from different perspectives [7,12]. However, further research needs to be carried out into continuous consumer usage intention or repeat usage intention [5,13,14]. Given that omni-channel retailing offers retailers the opportunity to make the experience so seamless that customers want to return, the authors propose examining this new relationship in greater depth.
The authors of [15] demonstrated the existence of an influence between aspects of the marketing strategy and omni-channel consumer loyalty. In [16] it was reported that although certain characteristics of omni-channel retailing have direct impacts on customer satisfaction, there is no evidence to support any relationship between other omni-channel characteristics and customer satisfaction. Further research is, therefore, necessary to demonstrate the existence of a positive relationship between SV and customer satisfaction, as well as customer loyalty, in the omni-channel context [17].
In general, a global comprehension of consumers has not yet been addressed in the literature in the new retail context [16]. Thus, based on the gaps detected in the literature, the aims of this study were as follows: (1) analyse how consistency and omni-channel continuity (intensity) influence consumer purchase value; (2) examine the influence of consistency and omni-channel continuity (intensity) on consumer satisfaction and loyalty; (3) analyse the influence of purchase value on consumer satisfaction and loyalty. To this end, we focused on a representative sample of consumers who had purchased online and collected in store (Click and Collect). This system integrates both online and offline purchasing, combining the strengths of both systems [18], thus enabling value creation through the interaction of both channels [19]. Additionally, when customers discern benefits in using online in-store touchpoints as part of the overall experience, they are more inclined to engage positively with omni-channel retailing [6]. Moreover, click and collect is a sustainable system [20] because eliminating trips and reducing failed deliveries reduces the carbon footprint [21].

2. Review of the Literature

2.1. Omni-Channel Retailing

Consumers are increasingly combining distribution channels, not only to complete a given purchase but also between purchases, thus, revealing so-called omni-channel behaviour [22]. Omni-channel retailing offers a holistic shopping experience that links physical stores with the rich digital information environment to provide excellent buyer experiences through all their touchpoints [23]. As retail evolves into a seamless omni-channel shopping experience, the distinction between physical and online stores is disappearing [24]. In fact, many retail stores with a physical presence already serve customers through multiple channels, while online retailers are establishing physical stores to improve their service [25].
Omni-channel retailing is one of the great revolutions in business strategy, with both practical and theoretical implications [25,26]. Channels that previously operated separately now converge in a single channel that delivers products and enables sales and returns with full visibility and control for businesses and consumers. Buyers do not care at all about how sellers resolve their purchases-deliveries-returns internally (e.g., what systems they need to provide the expected service) as they assume that sellers will do everything possible to meet customer expectations [27]. According to [4], the concept of omni-channel retailing focuses on the integration of activities in the different channels used by a company to match how customers increasingly shop.
This last area of interest, namely the integration of the distribution channel in the new omni-channel environment, has aroused a great deal of interest among researchers. From the retail standpoint, some authors have conducted in-depth research into the integration between physical and virtual channels, confirming the generation of competitive advantage as a result of integration [28]. Likewise, according to [29], channel integration is a key factor for inventory management, while the quality of channel integration positively influences perceived fluency [30].
Integration is an approach adopted by the company or retailer, but it is important to be aware that consumers do not always perceive their omni-channel experience as either consistent or continuous [9]. For this reason, the authors considered it necessary to address experience from the consumer perspective.

2.2. Omni-Channel Intensity

Omni-channel intensity is a consumer perception, which can be measured as the degree of perceived consistency and continuity in the use of multiple channels by the consumer [9]. It is made up of two key components: perceived consistency and seamlessness. According to [9] research, omni-channel intensity is considered a formative construct.
According to [31], perceived consistency is the coherence perceived by consumers regarding the mix of touchpoints offered by the retailer, and consumers are expected to be aware of this quality. Consumers use their mobile devices to visit online channels while in physical stores they compare products and prices, expecting the same products and prices on both channels [32]. They also increasingly expect information and purchasing options to be available as, when and where they want [33], so content consistency refers to the consistency of the information provided by retailers through physical and online channels [34]. The integration of information across channels is considered highly valuable [35] and retailers must ensure that in-store and online information is coherent [36].
Additionally, omni-channel retailing requires the integration of customer touchpoints to ensure a seamless customer experience, leading to sales based on improved interactions [33]. An omni-channel shopping experience is considered “seamless” or “continuous” if it occurs without any interruptions or hardly any friction, if the consumer is able to effortlessly move between or change shopping channels [24,37,38]. In other words, continuity refers to the consumer’s perception of no barriers between channels during the shopping experience, with a smooth transition whenever they move between channels [8,18,25].
The authors of [39] (p. 186) highlighted the importance of continuity, stating that “omni-channel marketing thus follows a customer-centered focus featuring a “holistic” shopping experience, one in which a customer’s buying journey is smooth and seamless, irrespective of the channels used”. Hence, the retailer’s goal is to remove the barriers between different touchpoints or make them less visible to the consumer [25] to offer them a frictionless shopping experience in the organisation’s brand ecosystem [24,31]. The aim of an omni-channel retailing strategy is to provide a smooth customer experience both online and offline, therefore, offering a significant competitive edge for retailers [9]. In this sense, reference [40] reported that, in the current retail environment, consumer experiences in one channel influences their perception of the other channels (specifically, it has been shown that consumers’ ratings of online stores are influenced by their interactions with in-store personnel), since consumers can also use the characteristics of in-store staff as a reference when rating a company’s online store.

2.3. Shopping Value (SV)

The stream of research on value in retailing is long, broad and diverse [41] (p. 79). In [42] (p. 233) it was reported that “in the context of shopping, value is defined as all factors that make up the complete shopping experience, not simply by the acquisition and utility of products”.
A relational approach to value [43] has evolved, complementing the dominant transactional approach towards an experiential perspective [44]. This approach prioritizes individual experiences during the entire buying and consuming process [45]. Thus, from the experiential perspective, the value of consumption is not represented by the purchase decision, but rather by the result of aggregate consumption experiences, since it is the affective response of the consumer to the object consumed [46].
Since Holbrook’s initial proposals, many studies have attempted to understand the essence of consumer experience, and noteworthy examples include research by [47,48]. Most retail researchers agree that consumer behaviour is experiential and combines hedonic, utilitarian and social values [9,41]. Recently, focusing now on the omni-channel environment, reference [49] considered it necessary to revisit the concept of value in the current digital context, reconsidering its dimensions for each possible touchpoint [9], while [50] concluded that customer value seems to be more important than touchpoints.

3. Hypothesis and Model Development

After reviewing the literature, it could be argued that omni-channel intensity, made up of perceived consistency and continuity, is a variable that can positively influence consumer satisfaction and customer loyalty.
In [51], consumer satisfaction is defined as a customer assessment in terms of whether a service meets their needs and expectations. In an online context, according to [52], consumers perceive that they have an experience with a brand rather than with a channel, and that brand acquires greater importance because it is at the intersection between touchpoints [9]. The authors of [53] demonstrated that brand experience is strongly linked to satisfaction, trust and intentions for future purchasing. Online retailing adds touchpoints and thus enhances customer satisfaction, brand loyalty and purchase frequency [33].
According to [33], in an omni-channel system, consumer satisfaction can be affected by aspects that are part of the seamless experience, such as last-mile fulfilment, while [32] proposed to smoothly integrate online and offline store images to ensure consistency, so as to provide positive experiences that generate satisfaction.
Omni-channel loyalty can be thought of as the union of physical and digital loyalty marketing to confront the challenges generated by new players and new consumers. At the omni-channel level, retailers must incorporate all the various touchpoints to attain deeply loyal customers [54]. Moreover, omni-channel retailing provides loyal customers with an “authenticated” space where activities are all perceived as relevant due to their personalization and seamlessness, whether they take place before, during or after the purchase [55]. It was concluded in [56] that consumer loyalty in an omni-channel system is influenced by the seamless experience, manifested in the delivery of the product. In [57], it was demonstrated that content consistency positively influences customer engagement, which in turn leads to positive word-of-mouth and repurchase intention.
The following hypotheses were therefore proposed:
Hypothesis 1 (H1).
Omni-channel intensity is positively related to consumer satisfaction.
Hypothesis 2 (H2).
Omni-channel intensity is positively related to consumer loyalty.
Consumer expectations of the integrated use of offline and online shopping channels give retailers the opportunity to create an innovative offering that enhances consumer value. To achieve this, retailers must use multiple initiatives to synchronize bricks and clicks, combining both physical and digital touchpoints consistently, so that the core elements of the brand are aligned in each shopping channel [25,31]. The authors of [58] suggest that consistency has a powerful impact on utilitarian shopping value but not on hedonic shopping value, while instant connectivity and integration have a positive effect on both. Although the literature relating intensity to value is extremely scarce and inconclusive, reference [9] suggests that a lack of consistency and seamlessness can undermine omni-channel shopping value. Therefore, Hypothesis 3 is proposed:
Hypothesis 3 (H3).
Omni-channel intensity is positively related to omni-channel shopping value.
In [59], it was concluded that shopping value, from the standpoint of consumption as an experience as proposed by [44], has two components, one utilitarian and the other hedonic, which exert a clear and positive influence on satisfaction [60,61] and on consumer loyalty in a retail purchasing environment [60]. Hence, these relationships need to be contrasted in the current omni-channel shopping environment [62].
In the online environment, reference [63] investigated the role of consumer-online store interactivity determining that bi-directionality provides hedonic value, that synchrony was a key element in utilitarian value and that both influenced customer satisfaction as a whole. More recently, reference [64] reported that perceived value is a determinant of satisfaction with the store. In an online shopping environment, reference [65] established the relationship between certain utilitarian components of shopping value in an online purchasing environment that positively affect consumer satisfaction and their repurchasing intentions. Similarly, reference [58,66,67,68,69] have demonstrated that the dimensions of shopping value have a positive effect on customer retention and loyalty. However, reference [50] also affirmed that only hedonic shopping value has a positive effect on loyalty, since, in an omni-channel purchase, the consumer seeks something more than the actual purchase of a product. Finally, reference [69] examined the shopping value perceived by consumers using smart technology and determined that perceived value influences loyalty to stores to the extent that consumers perceive utility, ease of use, relative advantage and enjoyment.
From the review of the concept of shopping value in an omni-channel environment, a connection between shopping value, consumer satisfaction and loyalty emerges, therefore the following hypotheses were proposed:
Hypothesis 4 (H4).
Omni-channel shopping value is positively related to consumer satisfaction.
Hypothesis 5 (H5).
Omni-channel shopping value is positively related to consumer loyalty.
Finally, different multi-channel and omni-channel studies have confirmed that consumer satisfaction is a predictor of loyalty [12,56,70,71,72]. Moreover, reference [73] recently demonstrated, for different consumer segments according to their degree of use of touchpoints, that product and journey satisfaction explains customer loyalty. The positive impact of customer satisfaction on loyalty was also confirmed in [74], for three different omni-channel scenarios. In the context of click and collect, a priori, the benefits of the positive experience translate into greater loyalty; however, there is no consensus on whether a high degree of satisfaction would lead to loyalty [19], so further research is required. Therefore, the following hypothesis was proposed (see Figure 1):
Hypothesis 6 (H6).
Satisfaction is positively related to loyalty.

4. Methodology

To develop this research, a quantitative study was carried out based on the omni-channel buying experience of consumers who had purchased products through online channels and collected the merchandise in store. The selection of this specific shopping experience was not arbitrary, as, according to [75], it is growing rapidly in Europe due, among other reasons, to the “haste” of consumers to obtain their products. The click and collect system offers consumers the advantage of greater flexibility since they do not have to make sure someone is at home, and it is often cheaper since it saves shipping costs [76], and contributes to sustainability [20]. In short, retailers offering their consumers this channel not only increases efficiency but also reduces costs and ecological impacts while meeting consumer expectations [77].

4.1. Measurement Scales

Based on the proposed theoretical model for testing the hypotheses (Figure 1), the indicators used to quantify the variables to be analysed in the model were chosen based on the analysis of prior observational studies. All the selected measurement scales had been formerly approved in the literature and are shown in Table 1.
The omni-channel intensity scale was developed from the scale proposed by [9], whose research grasped the theoretical essence of omni-channel shopping, developing a concept the aforementioned authors called “omni-channel intensity”.
Perceived shopping value was measured in this study using the scale proposed by [78]. This scale has been used in related fields (e.g., research by [79]), and in the recent study by [80] on shopping using mobile devices to study its implications on value.
Customer satisfaction was one of the central dependent variables in this study. Conceptually speaking, satisfaction is the result of a purchase insofar as consumers compare costs and benefits with anticipated consequences [81]. From an operational standpoint, satisfaction represents the sum of different judgements of attribution regarding satisfaction; from this perspective, satisfaction is a measurement of a specific transaction [82,83]. The approach used in this study focused on consumer satisfaction as a specific shopping experience relating to the perception standards conceptualised by [84] and adapted by [85]. The measurements proposed by these authors were adapted to the B2C context.
In the literature on marketing channels, some authors have related loyalty with affective commitment, arguing that affective commitment best describes the emotional component of loyalty [86]. According to [87], if affective commitment is significant, it should result in an incentive to further continue the relationship. Since this brand of engagement does not encompass cost-benefit evaluations, purchase behaviour is likely to be developed from the emotional factor associated with the relationship between the parties [88]. We, therefore, proposed using the consumer loyalty scale tested by [85] developed in the field of omni-channel purchasing and comprising operational, relational and also emotional components. This scale (see Table 1) was adapted to the scope of this analysis, in accordance with [12].

4.2. Method

The developed questionnaire contained 24 questions structured as follows: frequency of purchase and category of product purchased, assessment of omni-channel intensity, assessment of omni-channel purchase value, assessment of consumer satisfaction, and assessment of consumer loyalty. Except for the first group, questions with Likert scales and scored on a scale from 1 to 5 (1 = totally disagree to 5 = totally agree) were used. This scale was used to obtain faster responses from the participants. However, the weighting conserved the properties of all the original scales academically validated by their authors; the only adaptations derived from translation and adaptation to the context of this study. A two-stage pre-test with ten individuals was performed and the survey was modified to make it explicit and to improve the organisation of the contents.
The geographical scope of the study was Spain, where it is estimated that 20 million people purchased online in 2019, with a growth forecast of 10% [89]. This research focused on the online shopping and store pick-up experience, which was selected because it reflected international consumer trends and the adaptation of retail. Online shopping and store pick-up is one of the best ways to meet the demands of consumers who require a virtually instantaneous response to their purchases [90]. According to a study by Field Agent, 51% of online consumers consider themselves highly predisposed to buying using the click and collect option [91], which clearly benefits retailers offering in-store pick-up points (e.g., Walmart, Target or Best Buy). In Spain, 26% of consumers claimed that a Click and Collect service, either through a self-service kiosk or staff at the door with mobile applications, would make their in-store experience more positive [92].
Given the difficulty in selecting only consumers who used the Click and Collect service, we decided to follow the approach described by [93] and select the sample non-probabilistically using the exponential-type snowball method. In line with [74], in their omni-channel study, the questionnaire was sent to known people with proven experience of online shopping and store pick-up, asking them to disseminate the questionnaire to people fulfilling this requirement. The first group through which the questionnaire was disseminated were Spanish higher education lecturers and PhD students, who, in turn, redistributed it to eligible acquaintances and so on. In total, 285 questionnaires with valid responses were obtained; all of them meet the requirement of having made at least one omni-channel purchase in the previous month.
The data extracted from the questionnaire was examined using the SmartPls version 3.2.7, which is a statistical tool based on SEM (structural equations modelling) that provides causal relationships between manifest and latent variables delivering fewer contradictory results than the regression analysis in the detection of mediation effects [94].

5. Results

5.1. Descriptive Analysis of the Measurement Model

Table 2 shows the descriptive analysis of purchase frequency and the category in which the individuals in the sample had purchased. Of the 285 that started the questionnaire, 134 who indicated that they had never bought by this method were eliminated, leaving a final sample of 151 individuals, with fashion and accessories being the most purchased category by this method.
Two indicators were used to analyse reliability: the traditional internal consistency criterion through Cronbach’s alpha and the composite reliability measure. In the preliminary results, the analysis of indicator loads indicated that the OIS3 indicator was below the cut-off criterion of 0.6. Likewise, a potential multi-collinearity problem was detected in the BVA3 indicator since values above 5.0 were obtained; in the context of PLS-SEM, a VIF value of 5 or higher indicated a potential collinearity problem [95]. Therefore, these indicators were eliminated, thus improving the results of the model. Although only one indicator (OIC2) had a significant weight for the formative construct (p = 0.03), in the evaluation of formative measurement indicators, according to [96], we considered the absolute importance of outer loadings significance of the remaining formative indicators (OIC1 = 0.683; OIC2 = 0.855; OIC3 = 0.764; OIC4 = 0.823; OSI1 = 0.691; OSI2 = 0.735).
Table 3 presents the reliability and validity results and shows that, in terms of compound reliability, all the factors presented values greater than 0.7.
Discriminant validity was analysed following the [98] criterion. Table 4 shows that all the square roots of the AVE for each construct were greater than the highest correlation with any other construct, so the measurement model confirmed the discriminant validity. A more accurate measurement for assessing discriminant validity is the heterotrait-monotrait ratio of correlations (HTMT) criterion [99]; Table 5 shows the result of this analysis, which also confirmed its validity, as the results were higher than 1.

5.2. Analysis of the Structural Model and Hypothesis Testing

To analyse the predictive capacity of the structural model, we first evaluated the R2 obtained by bootstrapping that reflected the amount of variance of the construct explained by the model. Following [100], the R2 of each dependent construct had a value of 0.1. As shown in Figure 2, all the constructs exceeded that value. Secondly, the predictability of the model was evaluated by applying the Stone-Geisser Q2 Test described by [101] for each dependent construct through the blindfolding procedure. It was verified that all the constructs exceeded 0, thus confirming the predictive capacity of the model (Figure 2).
Thirdly, hypothesis testing was performed to evaluate the significance of the model relationships using the Bootstrapping test of 500 subsamples and a two-tailed Student’s t-distribution test with a significance of 0.05, in accordance with [95]. The results are shown in Table 6, which also includes the standardized regression coefficients indicating the intensity and direction of the relationship, as well as the statistical significance and relevance of all the proposed relationships. According to the results obtained, all the hypotheses were accepted.
Table 6 shows that the most powerful relationships in the model were those of omni-channel intensity with shopping value (β = 0.634; p < 0.005) and satisfaction (β = 0.624; p < 0.005). It was also interesting to note that the value of the relationship between shopping value and loyalty (β = 0.562) was much higher than the value for satisfaction (β = 0.358), which will be discussed later.

6. Discussion, Conclusions and Limitations

6.1. Discussion and Conclusions

The main contribution of this study is to the literature on the analysis of omni-channel from the consumer experience point of view, through an in-depth analysis of the concepts of intensity and value, as well as their relationship with satisfaction and loyalty.
Firstly, the strong relationship between intensity and shopping value must be highlighted. The consumer’s perception that their shopping experience runs smoothly and seamlessly provides greater value to the brand. Omni-channel consumers may use various channels to shop [102] and will prefer ones that add value above their expectations (e.g., better information, product evaluations or price comparisons) and better match their shopping profile. Consumers want brands to communicate with them with the same level of relevance regardless of the channel they choose to interact with the brand. The authors of [103] found that the ability to easily switch from one channel to another and consistency in the retailer’s range of products and prices on any channel result in positive brand perception.
Additionally, our results confirmed that consumers obtain greater satisfaction when the organization offers the customer a barrier-free shopping experience, thus facilitating mobility and offering consistency between the different shopping channels. This finding confirmed the results reported by [49,104], who argued the need for synchronization between channels to facilitate the consumer’s omni-channel journey, thus, providing greater value and leading to satisfaction.
In [105], it was confirmed that retailers with the best variety of shopping channel offerings, as well as in-store collection and return services, achieved better relationships with their customers and a positive impact on loyalty. As highlighted by [8], the offer of a holistic, barrier-free system of shopping channels that immerses the consumer in the brand ecosystem will strengthen loyalty. Our findings confirmed the aforementioned research results, revealing the need to offer customers dynamic shopping opportunities on all channels and adapted to their expectations.
In the omni-channel environment, shopping value has been confirmed as a key element in its relationship with consumer satisfaction and loyalty, as highlighted in previous research by [106,107]. As previous literature (e.g., [108]) has suggested, in the highly competitive retail environment, and in order to apply the most appropriate strategy, it is crucial that professionals identify the causal links between value drivers and customer satisfaction and determine how they influence loyalty. However, our results confirmed that not only is the value–satisfaction–loyalty chain relevant, but also that in the omni-channel environment the direct effect of value on loyalty is more relevant than the indirect influence through satisfaction. Recently more authors have been suggesting that it makes increasingly less sense to measure satisfaction because it is a very unsophisticated variable; however, the fact that the relationships of intensity and omni-channel shopping value with loyalty are stronger than the relationships between satisfaction and loyalty suggests that additional items should be proposed for inclusion on the satisfaction scale when used in the omni-channel environment, thus, opening an interesting future line of research through a qualitative approach. This approach was also proposed by [109], who indicated that the reliability of quantitative value measurements is threatened by the methodological problem of uncertainty regarding the links between satisfaction and value, and also by [62] when they proposed revisiting the value chain for the omni-channel environment, and further by [11] who proposed re-examining the composition of value in this context.
Consumers do not understand omni-channel retailing, they only understand shopping experiences, and, in omni-channel shopping experiences, they seek different options for seamlessly acquiring and then collecting products. Consequently, they find it easy and natural to move from one shopping system to another, obtaining the same information in all of them, and the same retail offer. Retail companies must therefore strive to provide combined, barrier-free and attractive offerings so that customers do not feel undervalued or disappointed when using one channel or another, since, according to [35], webroomers have a greater perception of time/effort savings and of making the right or smart purchases than showroomers.
Therefore, it is important to centralize user communication services or support services to ensure a comprehensive knowledge base of the same. By centralising information, retailers can control customer journeys and thus personalise services and avoid potential conflict points. Likewise, retailers need to develop the same marketing tools in all viewing and purchase options (brand image, offers, promotions, assortments), merging the e-commerce website, mobile app and physical stores into a consistent shopping experience. To achieve this, they must work on forging the link between the physical store and the online store, ensuring a smooth experience regardless of the path taken by the consumer to shop and collect their purchases. The authors of [62] propose that each company should develop a customized omni-channel strategy since individual firms have different channels and resources. However, specifically for the online purchase and store pickup option, reference [110] indicates that because store collection generates more traffic at the point of sale (which implies sales conversations and thus potential conversions), in addition to satisfying the customer by offering the desired collection speed, it is also an excellent opportunity for the retailer, who could use order steering strategies to promote it.
In [6], it was highlighted that the effect of brand familiarity on omni-channel purchases is less likely in online shopping because online shoppers are more price sensitive. However, our results revealed a strong influence of shopping value, measured as brand equity, on loyalty. We, therefore, agree with [52] when proposing that retailers invest in building brand loyalty in the online environment, and with [4] when they state that if the retailer’s brand is recognized by consumers and translates into true brand loyalty, consumers will even be willing to switch brands to shop at their favourite store. Retailers must, therefore, conduct in-depth analyses on how to give value to their own brand and use all the tools at their disposal to communicate that value to consumers. Moreover, consumer perception that the company offers a sustainable system, such as click and collect, will positively and directly affect both shopping value and loyalty. Communicating this new value to the consumer is, therefore, a new challenge for companies, but also for researchers, given that we have not found any literature on the study of consumer communication of the click and collect option as a contribution to sustainability.
In line with [110], a concern retailers face during the current pandemic is the need to constantly conduct e-shopping and contactless payments, as well as re-designing store collections for customers. The authors of [111] point out in a McKinsey report that retailers should continually enhance pick up services during this time of social distancing. Therefore, reference [6] suggest that retailers should apply new technologies and customer data in order to acknowledge their shopping patterns and customize their interactions, maintaining a seamless experience.

6.2. Limitations and Future Lines of Research

This study only focused on online purchase and store collection without taking into consideration the device used to make the purchase, thus revealing potential lines for future research. Likewise, the scope of analysis should be broadened to incorporate other elements such as logistic service quality or new shopping scenarios that may stem from the changes in consumer trends or different technological advances. It would also be worthwhile to add moderators to the relationship between omni-channel intensity and the other variables studied to determine the extent to which the characteristics or attitudes of consumers towards retailers could influence the identified relationships; we propose, for instance, to include consumers’ sustainable attitudes as moderating variables. Finally, we acknowledge that a larger sample, allowing cross-sector comparisons, would also facilitate the advancement of knowledge of the omni-channel environment about which we have so much to learn. It is essential for academic to develop closer relations and collaboration with retailers, who have the relevant big data to analyse.

Author Contributions

Investigation, validation and formal analysis were carried out by M.C.; Conceptualization and supervision, H.C. and T.F.; Methodology and writing-review and editing, T.F. and A.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research has been financed by the Spanish Research Agency. Ministry of Economy, Industry and Competitiveness’s R&D Program (Project ECO2017-83051-R).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

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Sustainability 13 05961 g001 550
Figure 1. Model.
Figure 1. Model.
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Sustainability 13 05961 g002 550
Figure 2. Model: structural results and significant relationships (1) As it is a formative construct, it has been decided to indicate the outer weights. *** denotes the significance level of results.
Figure 2. Model: structural results and significant relationships (1) As it is a formative construct, it has been decided to indicate the outer weights. *** denotes the significance level of results.
Sustainability 13 05961 g002
Table
Table 1. Scales.
Table 1. Scales.
AuthorsConstructItems
[9]Omni-channel
Intensity		OIC1: Prices were the same in each purchase channel.
OIC2: The offers were consistent and adapted to each purchase channel.
OIC3: Product information was the same in each purchase channel.
OIC4: The product range was coherent and adapted to each channel.
OIS1: It is easy to switch from the online shop to the physical shop.
OIS2: It is easy to move from the online store to the physical store.
OIS3: Barriers to moving from one shopping channel to another have been perceived
[78,79,80,81,82,83]Omni-channel Shopping valueBVA1: Overall, buying this brand is worth the money and time.
BVA2: Overall, buying this brand is worth the sacrifice I have made.
BVA3: Overall, buying this brand is worth the energy I have wasted.
[84,85]Consumer SatisfactionSAT1: In general, I am very satisfied with the service of this store.
SAT2: Compared with other stores, my current shopping experience with this one has been superior.
SAT3: This store is very close to offering a “perfect” service.
SAT4: This store differs from others by its superior service.
[12,85]Consumer LoyaltyLOY1: I am really interested in what happens to this store.
LOY2: I am proud to comment to others that I have purchased from this store.
LOY3: I consider this store the best shopping alternative for this type of product.
LOY4: I would recommend this store to others.
LOY5: I buy regularly in this store.
LOY6: I bought more from this store than from others with similar products.
Table
Table 2. Descriptive analysis.
Table 2. Descriptive analysis.
Purchase Frequency Click and CollectnResponse RateProduct CategorynResponse Rate
Never.13447%Fashion and accessories.8959%
Less than 1 time a month.11239%Food53%
1 time a month.279%Fast food11%
2 to 5 times a month.104%Furniture and decoration.32%
6 to 10 times a month.21%Books and music107%
More than 11 times a month.00%Cosmetic and beauty products21%
Answers collected285 Sport products.43%
Toys53%
Products for children11%
Automotive accessories.11%
Pharmaceutical products.21%
Electronic products.1913%
Others.96%
Answers collected151
Table
Table 3. Reliability and validity of the constructs.
Table 3. Reliability and validity of the constructs.
ConstructItemLoadingsOuter Weights
OC
intensity **		OIC10.6830.150
OIC20.8550.346
OIC30.7640.158
OIC40.8230.198
OIS10.6910.191
OIS20.7350.253
Cronbach’s AlphaComposite ReliabilityAVE
Shopping valueBVA10.9310.8680.9380.883
BVA20.949
LoyaltyLOY10.7090.8730.9040.612
LOY20.820
LOY30.754
LOY40.846
LOY50.820
LOY60.736
SatisfactionSAT10.8420.9020.9320.774
SAT20.874
SAT30.887
SAT40.915
** In the case of formative construct Cronbach Alpha does not make any sense as it tests internal consistency; The indicators of a formative latent variable need not correlate and neither they do represent a single sub-dimension; so we cannot calculate alpha and using factor analysis due to the fact it does not serve any purpose [97].
Table
Table 4. Discriminant validity according to the Fornell-Larcker criterion.
Table 4. Discriminant validity according to the Fornell-Larcker criterion.
LoyaltyOC IntensityOC Shopping ValueSatisfaction
Loyalty0.782
OC Intensity0.514
OC Shopping Value0.6620.6340.940
Satisfaction0.6460.6240.6090.880
Table
Table 5. Discriminant validity according to the HTMT criterion.
Table 5. Discriminant validity according to the HTMT criterion.
LoyaltyOC Shopping Value
OC Shopping Value0.748
Satisfaction0.7150.683
Table
Table 6. Model hypothesis testing results.
Table 6. Model hypothesis testing results.
HypothesisStructural RelationshipsStandardized βSample Mean (M)Standard Deviation (STDEV)T Statistics |O/STDEV|p ValuesStatistical Significance
H1OC Intensity → Satisfaction0.6240.6340.04912.6720.000***
H2OC Intensity → Loyalty0.5140.5300.0569.0980.000***
H3OC Intensity → OC Shopping Value0.6340.6480.04613.6440.000***
H4OC Shopping Value → Satisfact0.3580.3480.0744.8190.000***
H5OC Shopping Value → Loyalty0.5620.5550.0797.1410.000***
H6Satisfaction → Loyalty0.3850.3850.0854.5220.000***
*** p < 0.0005.
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Cotarelo, M.; Fayos, T.; Calderón, H.; Mollá, A. Omni-Channel Intensity and Shopping Value as Key Drivers of Customer Satisfaction and Loyalty. Sustainability 2021, 13, 5961. https://doi.org/10.3390/su13115961

AMA Style

Cotarelo M, Fayos T, Calderón H, Mollá A. Omni-Channel Intensity and Shopping Value as Key Drivers of Customer Satisfaction and Loyalty. Sustainability. 2021; 13(11):5961. https://doi.org/10.3390/su13115961

Chicago/Turabian Style

Cotarelo, Mitxel, Teresa Fayos, Haydeé Calderón, and Alejandro Mollá. 2021. "Omni-Channel Intensity and Shopping Value as Key Drivers of Customer Satisfaction and Loyalty" Sustainability 13, no. 11: 5961. https://doi.org/10.3390/su13115961

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