Introduction

“Imagine someone is at a store trying on an article of clothing. They check their phone to see if it is cheaper online.”

Rapp et al. (2015, p. 360) assert that mobile-assisted showrooming is defined as “a practice whereby consumers visit a brick-and-mortar retail store to (1) evaluate products/services firsthand and (2) use mobile technology while in-store to compare products for potential purchase via any number of channels” and Burns et al. (2019, p. 103) confirms that this practice “inherently involves an ethical component”. While this statement points to a consumer who always takes advantage of the services provided by offline retailers only to ultimately make their purchase in the online channel of another retailer (Viejo-Fernandez et al., 2020), in reality, this switch in retailer does not always occur in the purchase stage (Flavián et al., 2020). This paper proposes the mobile-assisted showroomer’s dilemma in order to assess the dilemma that such shoppers experience at the moment of decision in the brick-and-mortar store when they are holding an item in their hands, checking their phone, and hesitate between buying it (a) at the physical store or (b) through another cheaper online retailer. A dilemma is a problem offering two possibilities, neither of which is unambiguously acceptable or preferable. The literature distinguishes between competitive showrooming behavior (CB) (when the shopper switches retailers between the information-searching and purchase stages) and loyal showrooming behavior (LB) (where no such switch takes place) (Gensler et al., 2017; Schneider and Zielke, 2020). In this paper, the dilemma defines LB as the practice whereby the mobile-assisted showroomer does not switch channels and makes the purchase from the salesperson at the physical store (Fig. 1).

Fig. 1
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Mobile-assisted-showroomer’s dilemma at brick-and-mortar retailers.

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However, in recent years, intensive in-store smartphone use at physical retailers has driven CB (Chimborazo-Azogue et al., 2021), a trend that poses a real threat to brick-and-mortar retail (Sit et al., 2018; Frasquet and Miquel-Romero, 2021). The increase in CB has reached such an extreme that small independent retailers have considered charging shoppers to try products at their stores (Alonso, 2019; Bermejo, 2020). Understanding the impact of ethical judgment on CB vs. LB will help brick-and-mortar retailers reduce their losses. Despite the scale of the problem, no previous study has analyzed this relationship or considered this dilemma.

Previous research in the field of ethics shows that ethical judgment is key to determining consumers’ willingness to engage in ethically questionable behaviors (e.g., Vitell and Muncy, 1992; Burns et al., 2019; Arias-Oliva et al., 2020; De Andres-Sanchez et al., 2021). Given that, currently, various ethically questionable consumer practices have become prevalent that entail losses for brick-and-mortar retailers (Steenhaut and Van Kenhove, 2006), there is a need to study the role of ethical judgment in these new behavioral patterns.

The present study aims to examine the impact of ethical judgment on the mobile-assisted showroomer’s dilemma in relation to the display of CB vs. LB. Specifically, the study focuses on the clothing retail industry, as the nature of such products encourages showrooming: consumers need to interact with the product physically to better grasp its quality (Weathers et al., 2007; Cho and Workman, 2011; Acquila-Natale and Chaparro-Peláez, 2020).

At the theoretical level, this research validates the suitability of the dimensions of the Composite Multidimensional Ethics Scale (Composite MES) (Shawver and Sennetti, 2009) to explain the mobile-assisted showroomer’s dilemma, providing a new context for the application.

The remainder of this paper is divided into sections as follows. The section “Literature review” reviews the literature on (i) showrooming behavior and (2) the influence of ethical judgment on consumer behavior. The next section “Methodology” describes the sample and the methodology used in the empirical research. The section “Results” presents the results obtained. Finally, the last two sections discuss the main conclusions and practical implications of the study, as well as its limitations and future lines of research.

Literature review

Competitive vs. loyal showrooming behavior

The ability to combine online and offline channels in the purchase process has encouraged “research shopping” and “free-riding” behavior (Verhoef et al., 2007). These concepts refer, respectively, to “the propensity of consumers to research the product in one channel (e.g., the Internet), and then purchase it through another channel (e.g., the store)” (Verhoef et al., 2007, p. 129). One of the most representative examples of this behavior (along with webrooming) is showrooming.

Whereas LB is the behavior most valued by physical retailers (Viejo-Fernandez et al., 2020), CB is the one they most fear. Competitive consumers take advantage of the services provided by the brick-and-mortar store without bringing them any benefit in return, as they ultimately make their purchase through a different online retailer (Viejo-Fernandez et al., 2020). This behavior is directly associated with the aforementioned concept of “free riding,” which has a more negative connotation than the term “research shopping” (Schneider and Zielke, 2020).

As the competitive segment is the most common (Frasquet and Miquel-Romero, 2021) and the one that poses a direct threat to brick-and-mortar retail (Sit et al., 2018), in recent years, numerous studies have sought to understand the drivers of CB and devise counterstrategies to curb it. Table 1 shows the main studies in the field of CB and their respective conclusions.

Table 1 Studies on retailer switching during the purchase process and conclusions regarding CB.
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Despite the growing body of literature on showrooming, to the authors’ knowledge, no study has yet looked at the effects of the dimensions of ethical judgment on mobile-assisted showrooming customers’ decision to engage in CB or LB (dilemma).

The influence of ethical judgment on behavior

Current use of the term “ethics” reflects the plurality of legal, moral, and religious convictions in pluralistic democratic societies (Arias-Oliva et al., 2020). In this regard, ethical judgment is the cognoscitive process whereby people “judge which course of action is morally right” (Trevino, 1992, p. 445). The theoretical framework offered by the Composite MES offers insight not only into consumers’ ethical choice (in this research, CB vs. LB) but also into the reasons for this choice (here, the mobile-assisted showroomer’s dilemma) (Reidenbach and Robin, 1988, 1990; Shawver and Sennetti, 2009).

To this end, the Composite MES includes five dimensions: moral equity, relativism, egoism, utilitarianism, and contractualism. This complex construct is based on the premise that individuals use more than one rationale to make ethical judgments and that each of these rationales will have a given importance depending on the situation being faced (Reidenbach and Robin, 1990; Shawner and Senetti, 2009).

Moral equity refers to consumer decisions evaluated in terms of “their inherent fairness, justice, goodness, and rightness” (Reidenbach and Robin, 1990, p. 645). This dimension is also related to the acceptance of certain behavior by social groups, such as family (Leonard and Jones, 2017). Previous literature shows that moral equity influences the direction of behavior (Leonard et al., 2017; Pelegrín-Borondo et al., 2020). Higher levels of moral equity in consumers are associated with a lower likelihood to engage in ethically questionable behaviors (Shoham et al., 2008; Arli et al., 2015).

Relativism refers to “the guidelines, requirements, and parameters inherent in the social/cultural system” (Reidenbach and Robin, 1990, p. 646). Decisions made for relativist reasons are subject to the dictates of a specific society (Reidenbach and Robin, 1990). This suggests that: (i) rules are not universal but built on the traditions of each society; (ii) a greater degree of social interaction is required for this dimension to appear than the moral equity dimension (Lin and Ho, 2008); and (iii) the behavioral decisions of individuals from modern cultures are not as affected by this dimension as those of individuals from more historically rooted cultures, who do make decisions based on relativism (Lin and Ho, 2008). Some studies indicate that consumers guided by relativistic motives generally accept ethically questionable behaviors (e.g., Steenhaut and van Kenhove, 2006; Vitell and Patwardhan, 2008), while others indicate that relativism works against acceptance of such behaviors (Shoham et al., 2008).

Egoism “refers to acting in a manner that only promotes one’s long-term self-interests” (Nguyen and Biderman, 2008, p. 628). Egoistic decisions and actions are driven by the benefits of self-promotion and self-satisfaction they entail (Arias-Oliva et al., 2020). Although some studies demonstrate the significant influence of egoism on individual decisions (Van Doorn and Verhoef, 2015; Lin and Ho, 2008), others find no significant effects on this relationship (Han et al., 2017; Kiatkawsin and Han, 2017). Specifically, ethical actions seem to be less likely when a consumer scores high on egoistic values (Urien and Kilbourne, 2011; Osburg et al., 2019).

In contrast to egoism, utilitarianism seeks to produce “the greatest good for the greatest number” (Nguyen and Biderman, 2008, p. 628). The individual considers the consequences of action (or inaction) to determine whether it is good for society (Reidenbach and Robin, 1990). Therefore, utilitarian actions will be more prevalent in societies with a greater sense of community. Likewise, people who make more utilitarian judgments are typically the ones who process in a comparative way (Love et al., 2016). In the present case, CB and LB are compared, and “[s]ince one action is compared to another, utilitarianism promotes efficiency. That is, a less efficient action is likely to produce less utility than a more efficient action, and is, therefore, less ethical” (Reidenbach et al., 1991). The literature on the explanatory power of utilitarianism for individual ethical behavior is contradictory. Whereas some studies present this dimension as a determinant factor in the formation of ethical judgments (Cohen et al., 1993; Olarte-Pascual et al., 2021), others find no empirical support for this relationship (Jones and Leonard, 2016; Leonard and Jones, 2017).

Finally, contractualism is linked to the “individual perception of what is right versus wrong based on notions of an implied contract that exists between business and society” (Nguyen and Biderman, 2008, p. 633). Consumer behavior is influenced by an unwritten contract or tacit promise between the consumer and society. Contractualism is an antecedent to determining ethical behavioral intention (Olarte-Pascual et al., 2021). Likewise, consumers whose ethical judgments are heavily influenced by this dimension reject ethically questionable behaviors (Reidenbach et al., 1991).

Based on this theoretical framework, it can be proposed that the Composite MES is a useful tool for examining the impact of ethical judgment on the consumer dilemma between CB and LB. A general hypothesis concerning ethical judgment and five sub-hypotheses related to each of the dimensions are thus established:

H1. Ethical judgment explains the mobile-assisted showroomer’s dilemma between competitive vs. loyal behavior.

H1.1 The greater the role of moral equity in the mobile-assisted showroomer’s dilemma, the lower the likelihood of exhibiting CB.

H1.2 The greater the role of relativism in the mobile-assisted showroomer’s dilemma, the lower the likelihood of exhibiting CB.

H1.3 The greater the role of egoism in the mobile-assisted showroomer’s dilemma, the greater the likelihood of exhibiting CB.

H1.4 The greater the role of utilitarianism in the mobile-assisted showroomer’s dilemma, the lower the likelihood of exhibiting CB.

H1.5 The greater the role of contractualism in the mobile-assisted showroomer’s dilemma, the lower the likelihood of exhibiting CB.

Methodology

This study focuses on the fashion industry. This industry was chosen because of its role as a driver of economic activity and it is one of the fastest-growing industries in terms of purchases made through digital devices and, thus, its ability to attract different types of customers through online and offline channels (Mosquera et al., 2019).

The data were collected through structured face-to-face surveys focused on Spanish mobile-assisted showroomers consumers. The survey takers collected the information with the Google Form application. The questionnaire began with a filter question to identify these types of consumers. Specifically, respondents were asked whether they had ever used their smartphone inside a physical store for any of the following things: to look for product information, to compare prices, to compare products, to read reviews by other shoppers, to share photos with friends and family, or to pay. The data were collected from May to July 2021.

The mobile-assisted showroomer’s dilemma was posed through a common hypothetical scenario: “Imagine someone is at a store trying on an article of clothing. They decide to check their smartphone to see if it is cheaper online. They discover that it is cheaper at another online retailer and decide to use their smartphone to buy it from that online retailer and leave the store where they have been trying on the garment without buying it.” Respondents assessed the mobile-assisted showroomer’s dilemma through the items of the five dimensions of the Composite MES (Shawver and Sennetti, 2009). The items were scored on an 11-point Likert scale (0–10). The questionnaire ended with a dichotomous (yes/no) question to determine whether the respondent would choose a CB or LB: “Would you act the same way as the person in the described scenario?”.

To guarantee the quality of the adaptation of the measurement scales, a sequential linguistic validation process was followed, organized in the following stages (Muñiz et al., 2013): (a) production of a Spanish language version of the questionnaire, based on the original scales reviewed by bilingual experts from the Ethicomp international research network on ethics and technology; and (b) pre-tests were undertaken.

The survey was administered to a sample of 784 consumers. A total of 136 surveys were rejected as the respondent did not report having engaged in a mobile-assisted showrooming behavior at a physical store, resulting in a final sample of 648 valid surveys; 47.2% of the respondents were men, and 52.8% were women. By age group, 18.2% of the respondents were between the ages of 16 and 25, 18.5% between the ages of 26 and 35, 17.7% between the ages of 36 and 45, 27.6% between the ages of 46 and 55, and 17.9% aged 56 or over.

To examine the impact of ethical judgment on the likelihood that a consumer would exhibit CB vs. LB, a confirmatory factor analysis (CFA) was performed to confirm the existence of the five dimensions (EQS 6.1 software), followed by binary logistic regression analysis (IBM SPSS software).

Results

A total of 44.91% of the respondents said they would have a CB vs. 55.09% who said they would have an LB (Table 2).

Table 2 Distribution by gender and age: CB vs. LB.
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Confirmatory factor analysis

Sampling adequacy was verified by means of the Kaiser–Meyer–Olkin (KMO) measure (KMO = 0.94 > 0.8). Bartlett’s sphericity test confirmed that the correlation matrix was not an identity matrix (chi-square of ~8511.91 with 67 degrees of freedom; p = 0.000 < 0.001) (Hair et al., 2010).

The results of the CFA confirm the existence of the five dimensions and indicate a good fit between the empirical data and the measurement model: BBNFI = 0.98; BBNNFI = 0.97; CFI = 0.98; robust CFI = 0.98; GFI = 0.95; AGFI = 0.97; and RMSEA = 0.08.

Satisfactory reliability indicators were obtained for all variables based on standardized loadings (>0.5) and t-values (>1.96). Likewise, both the construct reliability (composite reliability coefficient (CRC) > 0.70) and the convergent validity criterion (average variance extracted (AVE) > 0.50) were satisfactory for all the dimensions (Table 3).

Table 3 Convergent validity and reliability analysis.
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Table 4 shows adequate discriminant validity (for all dimensions, the value one falls outside the confidence interval around the absolute value of the covariance).

Table 4 Discriminant validity.
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The CFA process resized the scales such that the mean value of all scales was 0 points, with scores ranging from approximately −8.5 to 7.

Binary logistic regression

The five dimensions accepted in the CFA become the model’s independent variables (F1. Moral equity, F2. Relativism, F3. Egoism, F4. Utilitarianism, F5. Contractualism). To analyze the dilemma, exhibiting CB was taken as the dependent variable. A value of 1 indicated a competitive consumer, and a value of 0, a loyal one.

The Hosmer–Lemeshow chi-square goodness-of-fit test indicated that the model adequately fits the data (chi-square of 9.18, 8 degrees of freedom, p-value of 0.328). Likewise, the omnibus test revealed that one or more factors can significantly predict the probability of engaging in CB (chi-square of 307.48, 2 degrees of freedom, p-value of 0.000).

Nagelkerke’s R2 statistic was used to quantify the model’s predictive power. The proportion found was 50.60%. The model’s predictive efficiency was 78.2%, i.e., it correctly classifies 78.2% of the cases.

The forward selection (Wald) stepwise selection method was used to create the binary logistic regression model. Variables were added to the model depending on: (i) their correlation with the dependent variable; (ii) the significance of the relationship between the independent variable and the dependent variable measured with the Wald statistic; and (iii) the likelihood-ratio test, which measures the significance of the unincluded variables.

Table 5 shows the independent variables showing a direct and significant relationship with the likelihood of having a CB. Of the five proposed variables, only relativism and egoism are determinants of this type of behavior. The sign of the B coefficient determines whether the effect on the dependent variable is direct (+) or inverse (−).

Table 5 Equation variables.
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The influence of relativism (H1.2) (B: −12.052; p < 0.01) and egoism (H1.3) (B: 12.515; p < 0.01) on the consumer’s decision to engage in CB was confirmed.

Discussion and implications

The literature demonstrates the importance of ethical judgment in understanding the antecedents of ethically questionable behaviors (e.g., Vitell and Muncy, 1992; Burns et al., 2019; Arias-Oliva et al., 2020). In this regard, intensive in-store smartphone use has driven CB (Chimborazo-Azogue et al., 2021), a type of behavior that, according to Burns et al. (2019), includes an ethical component and one that has economic repercussions for the survival of brick-and-mortar retailers (Sit et al., 2018; Frasquet and Miquel-Romero, 2021).

The present research is pioneering in the application of ethical judgment to the mobile-assisted showroomer’s dilemma, which refers to the dilemma that such consumers experience at the moment of decision in a brick-and-mortar store when they are holding a product in their hands and hesitate between buying it (a) at the store (LB) or (b) through a cheaper online retailer (CB). In this study, 44.91% of these consumers would choose CB, while 55.09% would choose LB, thereby confirming that this dilemma exists and reflecting a reality that needs to be addressed. Both behaviors can have positive and negative implications and repercussions for the retailer and the consumer. Additionally, both the consumer’s and the retailer’s future decisions may vary as a result of the choice. At the theoretical level, the paper demonstrates the suitability of the Composite MES (Shawver and Sennetti, 2009) for the context of showrooming behavior. The results also show that ethical judgment explains 50.6% of the mobile-assisted showroomer’s dilemma.

This research also identifies, for the first time, the critical role played by two of the five dimensions of ethical judgment in the likelihood of exhibiting CB: relativism and egoism. Specifically, while the relativism dimension is negatively associated with the likelihood of exhibiting CB, the egoism dimension is positively associated with it. The remaining dimensions (moral equity, contractualism, and utilitarianism) do not affect the likelihood of exhibiting CB.

The relativism dimension includes behaviors considered acceptable in a given culture. In the present case, the ability to try a product at one retailer or use the salesperson’s time and resources, among other things, before buying it at another is questioned. In accordance with Reidenbach and Robin (1990), the negative relationship found between relativism and the likelihood of exhibiting CB could be explained by understanding that society continues to attach great importance to the role of brick-and-mortar retailers. The characteristics of the study country itself may explain why showrooming consumers reject CB (Arli et al., 2015): Spanish society has a strong tradition of shopping at physical stores. In late 2020, retail accounted for around 13% of Spanish businesses, employing about 9% of all employees. Both indicators are above the EU average (CaixaBank Research, 2021). The results of the effect of relativism on behavior are in line with the findings of Shoham et al. (2008), but contrary to those of many previous authors (e.g., Steenhaut and van Kenhove, 2006; Vitell and Patwardhan, 2008), who find that relativist motives are precisely what leads to the acceptance of ethically questionable behaviors. In this regard, in the context of a relatively new behavior—being in a brick-and-mortar store and being able to purchase, at that moment, the same product at another cheaper retailer—traditional values prevail, which would be explained by the idea that “social and cultural systems are important in helping us define our ethical beliefs” (Reidenbach and Robin, 1990, p. 646).

The positive relationship between egoism and the likelihood of CB indicates that the greater the benefits obtained by the consumer through the CB (in the mobile-assisted showroomer’s dilemma, financial savings), the more likely this behavior is to emerge. The results for the egoism dimension are in line with those of previous studies (Urien and Kilbourne, 2011; Osburg et al., 2019). In the scenario studied here, the consumer values the gains: I am touching the item I am going to buy (an experience that only an offline retailer can provide), and I am moreover going to buy it from the cheapest supplier (win-win). Consumers who engage in CB have accepted the ethics of this behavior. Furthermore, according to Arias-Oliva et al. (2020), egoism entails high levels of satisfaction, relegating other dimensions of ethical judgment to the background.

The results obtained can help retailers formulate strategies to curb CB and boost LB. The first implication is that any organization seeking to compete in the physical channel should develop a strategy based on the showrooming consumer’s ethical judgment. The intensity and direction of the effects of the two significant dimensions of ethical judgment (relativism and egoism) on the intention to engage in CB suggest that the following practical implications will help drive LB.

Based on the study scenario, the most direct benefit sought by individuals with a high component of the egoism dimension is to save money on their purchases. Setting prices at the same level or lower than the competition’s seems to be the most immediate option. However, reducing margins can lead to losses, especially for retailers that only operate in an offline context (Mehra et al., 2018). Furthermore, lowering prices does not fully exploit the potential to influence CB and depends directly on the quality of the salesperson-customer interaction (Fassnacht et al., 2019). Building on these premises, the following actions are proposed. First, salespeople should focus their efforts on making the customer perceive exclusivity in the offered products; if the consumer perceives that there are no other products like them, there will not be the same level of competition, and the likelihood of CB will fall (Arora and Sahney, 2018; Mehra et al., 2018). Second, retailers should implement strategies based on financial benefits, such as direct discounts for the purchase of several items (cross-selling) or coupons redeemable with future purchases, which can also help boost loyalty (Rapp et al., 2015; Arora et al., 2017). Finally, third, retailers should enable smartphone use throughout the purchase process through a good WiFi network. The literature shows that showrooming consumers prefer to interact with their smartphone rather than a salesperson and that smartphone use positively influences purchase intention (Mosquera et al., 2019). Strategies that link the online context (smartphones) to the physical in-store one make it possible to create unique experiences and retain competitive showrooming consumers (Schneider and Zielke, 2021). In this regard, Zara is a pioneer in the implementation of omnichannel “Click &…” strategies, which encourage competitive showroomers to use their smartphones throughout the in-store purchase process. Examples include “Click & Find” (allows shoppers to use their app to search for an item and, if it is available in the store they are in, shows them a floor plan of the store, indicating the floor and/or section where they can find it), “Click & Try” (allows shoppers to reserve a fitting room, notifying them when it is available through their smartphone), and “Click & Go” (shoppers can use the app to browse any store and place orders that will be ready for pick up within 30 min of completing the purchase) (https://www.zara.com/es/). LB is a major opportunity for physical retail, especially independent retailers.

Separately, the inverse relationship between relativism and the likelihood of exhibiting CB could indicate that this behavior is still regarded as an unethical consumer practice by more than half the population in Spain. To prevent this behavior from gaining acceptance, marketing efforts should continue to emphasize the threat that CB poses to retail (Viejo-Fernandez et al., 2020; Frasquet and Miquel-Romero, 2021) and focus on reducing or eliminating positive social perceptions of this behavior.

Limitations of the study and future lines of research

The present study has certain limitations. First, the data were obtained in a specific industry, namely, fashion. The sensory nature of clothing products encourages showrooming behavior, and it is important to know the likelihood that shoppers will engage in CB (Acquila-Natale and Chaparro-Peláez, 2020). However, in order to extrapolate the results obtained, the model should be tested in other product categories or industries that do not encourage showrooming so directly (e.g., food).

Second, the sample consisted exclusively of Spanish mobile-assisted showroomers. Replicating the study with consumers from other countries and cultures would enrich the knowledge of how consumers form their ethical judgment. The literature establishes that membership in a given society can influence the results obtained (Reidenbach and Robin, 1990). Likewise, it is proposed to address webrooming behavior, which occurs when customers search for products online before going to a physical store for a final evaluation and finally making the purchase.

Third, this study focuses on LB in direct purchases from a salesperson at a brick-and-mortar store. But LB also occurs when the purchase is made online from the same retailer. The scope of future research could thus be expanded to include other alternatives to the ethical dilemma to explore this behavior in greater depth.

Finally, a qualitative analysis of the data could also broaden the field of consumer ethical judgment. Only 7% of studies in this field use a qualitative methodology; doing so would make it possible to address the reasons behind ethically questionable choices (Hassan et al., 2022).