The dark side of marketing deception: a multidimensional analysis of customer punitive intentions and switching behaviour

1 Introduction

Marketing deception (MD) has increasingly become an important issue in the marketing domain, particularly with the proliferation of online marketing environments. Marketing deception is a situation where a consumer is misled by a marketing strategy that is not based on the actual characteristics of the product, leading to a negative impact on consumer decision-making. Due to the perceived risk of being deceived, today's consumers are increasingly cautious and tend to seek validation for their purchase decisions through electronic word-of-mouth (eWOM). It is also evident that 82% of consumers use consumer opinions when conducting online transactions, showing high reliance on collective consumer intelligence to clear uncertainty and perceived risk (Karabas et al., 2021). These issues are particularly salient in the hospitality industry (Elshaer et al., 2019; 2023), given that customers often turn to social media channels to find information, compare service providers, book hotel lodging, make restaurant reservations, and plan travel and tourism experiences (Elshaer et al., 2018; Elshaer and Marzouk, 2019). Since hospitality services are mainly intangible and cannot be fully evaluated before consumption, it is particularly challenging for customers to avoid misleading marketing claims and deceptive promotional practices. Hence, transparency and trust are the key determinants of customer decision-making.

The implications of MD extend beyond transactional outcomes, as its long-term consequences negatively impact both customers and organizations. The implications of MD extend beyond transactional outcomes, as its long-term consequences negatively affect both customers and organizations. From an organizational perspective, deceptive marketing practices erode customer trust, damage corporate reputation, and weaken brand equity. From the customer's perspective, experiences of marketing deception generate mistrust, perceived injustice, and customer dissatisfaction, which subsequently influence future behavioral intentions. Marketing deception has been consistently associated with customer switching intentions (CSI), as dissatisfied customers are more likely to seek alternative service providers that demonstrate greater transparency, credibility, and ethical business practices (Riquelme et al., 2016). Within the hospitality sector, such switching behavior may involve choosing competing hotels, restaurants, travel agencies, or tourism service providers, thereby threatening customer retention, reducing customer lifetime value, and undermining long-term organizational competitiveness.

Given the strategic importance of customer retention, CSI represents a significant challenge for organizations, particularly in highly competitive digital markets (Romani et al., 2013). Elevated switching behavior undermines profitability, increases customer acquisition costs, and weakens market positioning. Consequently, organizations must adopt proactive strategies to mitigate CSI, including enhancing transparency, improving communication, strengthening customer relationships, and implementing ethical marketing practices. Furthermore, firms increasingly invest in personalized promotional strategies and loyalty-building mechanisms to create switching barriers and reinforce customer commitment, thereby preserving their customer base and sustaining competitive advantage (Yu et al., 2025). These challenges are particularly critical in hospitality markets, where customer loyalty is a key determinant of organizational success and where digital reviews and social media interactions substantially influence future booking and consumption decisions.

Apart from encouraging switching behaviour, marketing deception may also provoke more severe retaliatory reactions, referred to as customer punitive intentions (CPI). These reactions arise from consumers’ desire to retaliate against organisations they perceive as having engaged in unethical practices. CPI encompasses behaviours such as negative word-of-mouth (NWOM), customer complaints, online criticism, and protest actions, all of which may substantially damage an organisation's reputation. Recent studies indicate that punitive behavioural responses have become increasingly prevalent in digital environments, where dissatisfied consumers actively express their experiences and seek justice through various online platforms (Romani et al., 2012; Zarantonello et al., 2018). Moreover, customers increasingly believe that their online actions can influence organisational behaviour and public opinion, thereby increasing the likelihood of punitive responses (Russell et al., 2016).

The digital revolution, particularly the widespread adoption of social media, has further intensified the consequences of these consumer behaviours (Braunsberger and Buckler, 2011). Social media platforms provide consumers with highly influential channels through which they can communicate their experiences, opinions, and retaliatory responses toward organisations. Dissatisfied customers can easily share negative experiences, criticise firms publicly, and encourage other consumers to avoid particular service providers. Consequently, negative electronic word-of-mouth spreads rapidly and may significantly damage organisational reputation, particularly when deceptive marketing practices are perceived (Van Den Broek et al., 2017; Ribeiro et al., 2018). For hospitality organisations, where purchasing decisions are heavily influenced by online reviews, ratings, and customer-generated content, the reputational consequences of deceptive marketing can be particularly severe because potential customers frequently rely on these digital information sources before making booking or reservation decisions.

Although previous studies have examined the consequences of deceptive marketing, existing research has primarily focused on its direct effects on customer satisfaction, trust, loyalty, purchase intentions, and repurchase behaviour (Romani et al., 2012; Zarantonello et al., 2018). Comparatively less attention has been devoted to explaining the psychological mechanism through which multidimensional marketing deception translates into customer punitive intentions, particularly within digital hospitality environments where customers rely extensively on social media for information search and service evaluation. Moreover, although previous studies have examined individual forms of deception, such as deceptive pricing, misleading advertising, or product-related deception, limited research has conceptualised marketing deception as a multidimensional construct encompassing product, price, promotion, and distribution deception within a unified framework. Likewise, researchers have underexplored the mediating role of customer switching intentions in explaining how deceptive marketing practices ultimately generate punitive behavioural responses. Addressing these gaps is particularly important because hospitality customers increasingly depend on social media platforms during service search, comparison, booking, and post-consumption evaluation, making them especially susceptible to deceptive marketing practices (Elshaer and Marzouk, 2024; Xiang et al., 2015).

This study is grounded in the Stimulus–Organism–Response (S–O–R) framework, originally proposed by Mehrabian and Russell (1974), which explains how environmental stimuli influence individuals’ internal cognitive and affective states, subsequently shaping their behavioural responses. The S–O–R framework has become one of the most widely adopted theoretical perspectives for explaining consumer behaviour in online, tourism, and hospitality contexts (Kim et al., 2020). Within the present study, marketing deception represents the external stimulus because it reflects customers’ perceptions of deceptive marketing practices encountered while interacting with hospitality service providers through Facebook. Customer switching intentions constitute the organism, representing customers’ internal cognitive evaluation of deceptive experiences and their intention to seek alternative providers. Finally, customer punitive intentions represent the behavioural response, manifested through retaliatory behaviours such as negative electronic word-of-mouth, complaints, and protest actions against the organisation. Accordingly, the S–O–R framework provides a theoretically robust explanation of how deceptive marketing practices trigger internal psychological evaluations that subsequently translate into punitive customer behaviours within digital hospitality environments (Vieira, 2013).

In this context, this study aims to better understand how multidimensional marketing deception–encompassing product, pricing, promotion, and distribution deception– shapes customer switching intentions, which subsequently lead to customer punitive intentions. The study specifically investigates customers who had previously used Facebook to search for, book, reserve, or consume hospitality services, including hotel accommodation, restaurant services, and travel- or tourism-related offerings. By examining these relationships within the hospitality context, the study extends the application of the Stimulus–Organism–Response framework to digital hospitality marketing while providing practical insights into how hospitality organisations can reduce the adverse consequences of deceptive marketing practices, strengthen customer trust, and enhance long-term customer retention.

2 Literature review

2.1 Marketing deception

Marketing Deception (MD) has been recognized as one of the unethical marketing practices by many researchers and scholars, which affects the integrity of the relationship between organizations and consumers. Marketing deception is defined as “a series of deceptive marketing practices whereby marketers intentionally deliver false or exaggerated information to shape the perceptions and purchase behaviors of customers” (Gshayyish, 2023). These deceptive marketing practices may include the manipulation of product characteristics, pricing structures, promotional activities, and distribution processes of products, resulting in wrong perceptions or expectations of consumers (Al-Batal, 2021). Furthermore, MD is not only about deceiving, but it also involves a violation of ethical and professional marketing standards, which makes it a violation of the basic marketing principles of transparency, fairness, and respect for customers (Hersh and Aladwan, 2014). This issue is particularly important in the hospitality industry, where customers rely heavily on social media and online information when booking accommodation, reserving restaurants, or purchasing tourism-related services. Given the intangible nature of hospitality services, misleading marketing claims can substantially influence customers’ perceptions and behavioral responses (Xiang et al., 2015).

The aforementioned literature also conceptualized MD as a multidimensional construct, which is comprised of different aspects of marketing mix variables, as argued by Leonidou et al. (2013). Product deception involves deceiving consumers through imitating renowned brands, failure to reveal critical product information, or failure to reveal critical product attributes such as safety risks or expiration dates. Pricing deception, on the other hand, involves artificially inflating the prices of goods or services or making false claims about the product's origin, often for the purpose of inflating prices. Distributional deception involves delivering a product that does not match the product specifications advertised, especially in an online environment. Lastly, promotion deception entails exaggerated claims, false advertising, or false promotions. From these dimensions, it is evident that MD is integral at different stages of the consumer experience, thus impacting consumer perceptions. Accordingly, the present study conceptualizes MD as a multidimensional stimulus within the Stimulus–Organism–Response (S–O–R) framework (Mehrabian and Russell, 1974). As an external environmental stimulus, deceptive marketing practices shape customers’ cognitive evaluations, which subsequently influence customer switching intentions (organism) and customer punitive intentions (response). This perspective provides a theoretical explanation of how deceptive marketing practices trigger subsequent behavioral responses in hospitality settings.

2.2 Customer switching intentions

Customer Switching Intentions (CSI) are a key customer behavior in service and marketing research, defined as the customer's intention to terminate his or her relationship with the current service provider and switch over to another service provider (Lu and Shi, 2024). Customer Switching Intentions are usually motivated by customer dissatisfaction, a sense of injustice, or a loss of trust, especially in situations where customers feel that the organization has not lived up to expectations or has used deceitful practices (Ahmed et al., 2025). Several factors have also been identified in the literature as contributing to Customer Switching Intentions, which include service failures, the inability of service providers to address customer needs, pricing strategies, and the handling of customer complaints (Nurlinda and Anam, 2024). In addition, customers are also motivated by the presence of competitive forces and alternative service providers (Nurlinda and Anam, 2024).

2.3 Customer punitive intentions

Customer punitive intentions (CPI) comprise different forms of retaliatory actions exhibited by customers in response to perceived organizational misconduct, especially unethical and fraudulent behavior (Grappi et al., 2013). This behavior is driven by a need for justice and to demonstrate dissatisfaction with an organization (Armstrong and Green, 2013). Customer punitive intentions can be divided into two main types: destructive and constructive punitive behavior. Constructive punitive behavior aims to persuade an organization to alter its behavior. Such behavior may comprise complaining to others, boycotting an organization, and participating in advocacy and protest activities. Destructive punitive behavior is driven by a need to punish an organization and may comprise engaging in word-of-mouth negativity (NWOM), discouraging others from transacting with an organization, and damaging an organization's reputation (Romani et al., 2013).

Two aspects of CPI have been emphasized. One is NWOM, which is “the dissemination of unfavorable information about an organization or product through person-to-person communication.” NWOM is a compelling tool, particularly as it is drawn from non-commercial sources and is likely to have a greater impact on consumer perceptions than other forms of communication, even positive forms (Balaji et al., 2016).

2.4 Hypotheses development

Marketing deception (MD), however, has been consistently established as a major antecedent for customer punitive intentions (CPI), especially under situations where customers feel a sense of unfairness, transparency, and ethical violations. In situations where an organization practices deceptive marketing strategies, the customer is likely to develop negative emotions, which may cause them to retaliate against the organization. This retaliation often comes in the form of negative word-of-mouth (NWOM) and customer protest behavior (CPB), which are two major components of CPI (Iqebal and Siddiqui, 2019; Grappi et al., 2013).

From the perspective of the S–O–R framework (Mehrabian and Russell, 1974), marketing deception represents an external environmental stimulus that shapes customers’ evaluations of a service provider. When customers perceive misleading information regarding products, prices, promotions, or service delivery, these deceptive cues generate negative cognitive and emotional responses, including distrust, frustration, and perceived injustice. Such internal evaluations increase customers’ likelihood of engaging in punitive behavioral responses directed toward the organization, including negative word-of-mouth and protest behavior (Vieira, 2013).

Past research has established that deceptive marketing practices influence customers to retaliate against an organization that is perceived to be dishonest. Riquelme et al. (2016), for example, established that customers are more likely to retaliate against an organization through negative word-of-mouth (NWOM) if they feel that the organization has been deceptive. Similarly, Grappi et al. (2013) established that customers are more likely to retaliate against an organization if they are aware of its unethical practices. This implies that marketing deception not only influences customer satisfaction but also affects customer behavior aimed at punishing the organization.

Moreover, empirical studies have indicated that there is a strong association between MD and CPI, given that deceptive practices negatively affect customer satisfaction and the strength of the relationship between the business and the customer (Fernandes and Clamote, 2016). The emotions that are produced as a result of deception, such as anger, are a major NWOM behavior, given that customers want to share the experience with others (Chipulu et al., 2016). Furthermore, CPB is a direct reaction to misconduct, where customers engage in behaviors such as boycotts, complaints, and resistance against an organization (Antonetti and Maklan, 2017). Moreover, distribution deception has been related to customer resistance and avoidance (Lindenmeier et al., 2012), while promotion deception, particularly advertising deception, has been related to increased negative evaluations and retaliatory actions (Ullah and Hussain, 2015). Based on the above discussion, the following hypothesis is proposed:

H1: Marketing deception has a significant positive effect on customer punitive intentions.

Marketing deception (MD) has also become an important factor in service situations where customers want to switch (CSI). Marketing deception occurs in situations where customers perceive that an organization has used deceptive marketing, which results in a decrease in the level of trust in the organization, thereby leading to customer dissatisfaction, which in turn leads to customer switching intentions. Thus, a decrease in trust can be considered one of the most significant negative outcomes of marketing deception, which directly leads to customer switching and customer relationships (Elziny et al., 2026; Riquelme et al., 2016). Deceived customers are more likely to doubt the organization's reliability and credibility, especially when its claims differ from the actual service. This situation, in turn, creates a sense of injustice, leading customers to be less confident in dealing with the organization in the future, thereby making them willing to switch to other organizations (Romani et al., 2013).

Consistent with the S–O–R framework, customers’ exposure to deceptive marketing practices constitutes a negative environmental stimulus that alters their internal evaluations of the service provider. As customers perceive inconsistencies between marketing promises and actual service experiences, trust declines while dissatisfaction and uncertainty increase. These internal evaluations reduce customers’ willingness to maintain the relationship and strengthen their intention to switch to alternative hospitality providers that are perceived as more reliable and transparent. In addition to these findings, empirical research also supports the link between MD and CSI, especially concerning various aspects of the marketing mix. Deception about products significantly drives customer switching behavior and lowers repurchase intentions to avoid negative experiences (Wilkins et al., 2016). However, there is also an argument that switching costs may be a factor in moderating this link between MD and CSI. Based on the above discussion, the following hypothesis is proposed:

H2: Marketing deception has a significant positive effect on customer switching intentions.

Customer switching intentions (CSI) have also been recognized as an important antecedent of customer punitive intentions (CPI), especially in situations when customers sense unethical or deceptive organizational behavior. Marketing deception, including product, price, distribution, and promotion dimensions, often leads to customer switching. The loss of credibility of the marketing organization, which is a result of marketing deception, not only induces customer switching but also results in several retaliatory reactions, including boycotts, complaint behavior, and even lawsuits, from the customer's side (Garbarino and Maxwell, 2010; Lindenmeier et al., 2012; Riquelme et al., 2016; Ullah and Hussain, 2015). The emotional and cognitive effects experienced by the customer explain this change from switching intentions to punitive behavior. This phenomenon occurs because dealing with deceptive marketing practices can cause customers to feel anger, frustration, and a sense of injustice. This change can cause the customer to retaliate against the organization. Thus, it is proposed that customers who show switching intentions are more likely to show retaliatory behavior, which can include word-of-mouth and protest behavior targeting the organization's reputation (Chipulu et al., 2016; Iqebal and Siddiqui, 2019).

Within the S–O–R framework, customer switching intentions represent the organismic state that bridges external marketing stimuli and behavioral responses. Switching intentions reflect customers’ internal evaluation that continuing the relationship is no longer desirable. Once this cognitive state develops, customers are more likely to externalize their dissatisfaction through punitive behaviors, such as spreading negative word-of-mouth, lodging complaints, or discouraging others from using the service provider. Consequently, switching intentions provide an important psychological mechanism linking deceptive marketing practices with customer punitive intentions. The S–O–R framework further suggests that an internal cognitive or affective state influences behavioral responses. The S–O–R framework indicates that an internal cognitive or affective state often precedes behavioral responses. The S–O–R framework indicates that an internal cognitive or affective state often precedes behavioral responses. Accordingly, marketing deception is expected to influence customer punitive intentions indirectly through customer switching intentions. Rather than responding immediately with punitive behaviors, customers first evaluate whether to terminate their relationship with the organization. Once switching intentions develop, they increase the likelihood of retaliatory actions aimed at expressing dissatisfaction or discouraging others from engaging with the organization. Therefore, customer switching intentions are expected to partially mediate the relationship between marketing deception and customer punitive intentions. Based on the above discussion, the following hypothesis is proposed (see Figure 1):

H3: Customer switching intentions have a significant positive effect on customer punitive intentions.

H4: Customer switching intentions mediate the relationship between marketing deception and customer punitive intentions.

3 Methods

3.1 Research population and sampling

The research population comprised hospitality customers in Egypt who used Facebook to search for, book, reserve, or purchase hospitality services, including hotel accommodation, restaurant services, and tourism-related offerings. According to recent statistics, Egypt had an estimated population of approximately 108,401,747 in 2025, with nearly 52,000,000 Facebook users, representing approximately 47.9% of the total population. Given the widespread use of Facebook as a digital platform for hospitality marketing and customer engagement, it provided an appropriate context for investigating the proposed research model.

As the sampling frame for the research was not well defined, the population was considered to exceed 100,000, resulting in a recommended minimum sample size of 384 respondents according to Sekaran and Bougie (2016). In situations where the population is large, sampling becomes necessary to ensure feasibility in terms of time and cost (Daniel, 1999). A representative sample is necessary for improving the generalizability of survey results (Browner et al., 1988). Although the final usable sample consisted of 350 valid questionnaires after removing incomplete and invalid responses, this sample size remains adequate for variance-based structural equation modeling (PLS-SEM). Hair and Alamer (2022) note that PLS-SEM is appropriate for analyzing complex research models using relatively moderate sample sizes and places greater emphasis on statistical power than on conventional minimum sample recommendations for population surveys. Furthermore, an a priori power analysis using G*Power indicated that the available sample exceeded the minimum number of observations required to detect medium effect sizes at the recommended significance level and statistical power.

The research was conducted by targeting Facebook users who had previously searched for, booked, reserved, or consumed hospitality services through the platform. The initial sample comprised 415 respondents. After screening the questionnaires and removing incomplete, inconsistent, and invalid responses, 350 valid questionnaires were retained for the final analysis, representing an effective response rate of approximately 84%.

3.2 Data collection instrument

Data were collected using a structured questionnaire designed to test the proposed hypotheses (Elshaer et al., 2022). Before proceeding to the main questionnaire, respondents were asked a screening question to confirm that they had previously used Facebook to search for, book, reserve, or purchase hospitality services. Only respondents meeting this criterion were allowed to complete the survey.

The questionnaire consisted of three sections. The first section measured marketing deception (MD) as a multidimensional construct comprising product deception, pricing deception, distribution deception, and promotion deception, using 20 items adapted from previous studies (Al-Heali, 2020; Gaber et al., 2018; Leo/tgcqnidou et al., 2013; Singh, 2012). The second section measured customer switching intentions (CSI) as a single construct using four items adapted from Wang et al. (2024). The third section measured customer punitive intentions (CPI) through two dimensions—negative word-of-mouth and customer protest behavior—using 10 items adapted from Antonetti and Maklan (2016), Grappi et al. (2013), and Romani et al. (2013). All questionnaire items were measured using a five-point Likert scale ranging from 1 (“strongly disagree”) to 5 (“strongly agree”).

4 Results

Table 1 presents the results of the measurement model assessment, including indicator reliability, internal consistency reliability, and convergent validity. Indicator reliability was assessed using outer loadings. According to Hair and Alamer (2022), outer loadings of 0.70 or higher are considered satisfactory, although indicators with loadings above 0.50 may be retained when supported by adequate construct reliability and convergent validity. The results indicate that all retained indicators satisfied the recommended thresholds, confirming satisfactory indicator reliability.

Table 1. Loading indicator, reliability, and validity for MD, CSI, and CPI.

Internal consistency reliability was evaluated using Cronbach's alpha (α) and composite reliability (CR). As shown in Table 1, all constructs reported Cronbach's alpha and composite reliability values above the recommended threshold of 0.70, indicating satisfactory internal consistency and demonstrating that the measurement items consistently represented their respective latent constructs (Hair and Alamer, 2022).

Convergent validity was assessed using the Average Variance Extracted (AVE). The AVE values for all constructs exceeded the recommended threshold of 0.50, indicating that each construct explained more than 50% of the variance of its indicators and therefore demonstrated satisfactory convergent validity (Hair and Alamer, 2022).

Table 2 presents the descriptive statistics for the study variables. The findings reveal that mean scores of all constructs were higher than the midpoint of the five-point Likert scale (3.0), which indicated that respondents perceived relatively high levels of marketing deception (MD), customer switching intentions (CSI), and customer punitive intentions (CPI). As far as the dimensions of marketing deception are concerned, the respondents perceived promotion deception as the most deceptive marketing practice, as its mean score (M = 4.14, SD = 0.64) was the highest among all other dimensions. It was followed by distribution deception (M = 3.92, SD = 0.68), product deception (M = 3.69, SD = 0.60), and pricing deception (M = 3.59, SD = 0.65). In addition to this, customer punitive intentions (M = 3.97, SD = 0.57) and customer switching intentions (M = 3.95, SD = 0.68) also revealed relatively high mean scores, which showed that respondents tended to switch service providers and indulge in punitive behaviors in the event of deceptive marketing practices.

Table 2. Mean and St. deviation of MD, CSI, and CPI.

Discriminant validity was evaluated by examining the correlations among the study constructs (Elshaer et al., 2024). As shown in Table 3, the dimensions of marketing deception exhibited relatively high positive correlations. This pattern is theoretically expected because product deception, pricing deception, distribution deception, and promotion deception represent conceptually related dimensions of the broader marketing deception construct rather than independent phenomena. Consequently, strong intercorrelations among these dimensions do not necessarily indicate construct redundancy but instead reflect their shared conceptual domain. To further assess construct distinctiveness, additional measurement model diagnostics were examined and supported the adequacy of discriminant validity. Accordingly, the dimensions were retained because each captures a distinct aspect of marketing deception identified in the marketing literature (Leonidou et al., 2013; Hair and Alamer, 2022). Nevertheless, the relatively high correlations should be interpreted with caution, and future research is encouraged to investigate the higher-order structure of marketing deception using alternative measurement models.

Table 3. Correlation coefficients between MD, CSI, and CPI.

Note: ** Correlation is significant at the 0.01 level (two-tailed).

Table 4 presents the multiple regression analysis results concerning the effect of marketing deception (MD) on customer switching intention (CSI). The results indicate that several dimensions of marketing deception significantly predict CSI, although the strength and significance of the individual predictors vary. Regarding product deception, failure to honor warranties was the strongest predictor (β = 0.374, t = 6.972, p < 0.001), followed by differences in the advertised brand (β = 0.223, t = 4.434, p < 0.001) and product specifications (β = 0.200, t = 3.645, p < 0.001). However, differences in product quality and measurements were not statistically significant (p > 0.05).

Table 4. Multiple regression analysis results for the effect of marketing deception on customer switching intention.

β = standardized multiple regression coefficient; r = zero-order correlation coefficient; r² = squared correlation coefficient. Results are statistically significant when p < 0.05. The signs of β and the corresponding t-values are consistent. Statistical presentation: The r and r² columns describe the bivariate relationship of each item with CSI, whereas β, t, and p describe each item's unique contribution in the multiple regression model. Overall model statistics (R, R², adjusted R², F, and model p-value) should be reported separately if available.

For pricing deception, false discounts had the strongest effect on CSI (β = 0.489, t = 9.674, p < 0.001). Differences between the agreed and delivery prices (β = 0.166, p = 0.002) and the nondisclosure of prices (β = 0.193, p < 0.001) were also significant. Regarding distribution deception, delivery delays represented the strongest predictor (β = 0.344, t = 5.983, p < 0.001), whereas the marketer's selection of the delivery location was not significant (p = 0.904). Finally, all promotion-deception variables had significant positive effects on CSI, with differences between advertised and actual product information producing the strongest effect (β = 0.275, t = 4.515, p < 0.001). Overall, the findings provide partial support for the proposed positive effect of marketing deception on customer switching intention because some individual predictors were not statistically significant.

Table 5 presents the correlation and multiple regression results for the relationship between marketing deception and customer purchase intention (CPI). The results indicate that 16 of the 20 marketing-deception variables make statistically significant contributions to CPI. Regarding product deception, failure to honor warranties produced the strongest effect (β = 0.388, t = 7.577, p < 0.001), followed by differences between the advertised and actual brands (β = 0.321, t = 6.690, p < 0.001). However, differences between the advertised and received product quality did not produce a significant unique effect (β = 0.065, p = 0.252).

Table 5. Correlation and multiple regression results for marketing deception and customer punitive intention.

For pricing deception, false discounts were the strongest predictor of CPI (β = 0.436, t = 9.770, p < 0.001), followed by the nondisclosure of prices (β = 0.319, t = 7.224, p < 0.001). However, the difference between online and traditional retail prices was nonsignificant (β = 0.030, p = 0.451). Regarding distribution deception, delivery delays produced the strongest effect (β = 0.329, t = 6.170, p < 0.001), whereas the marketer's selection of the delivery location was nonsignificant (β = 0.053, p = 0.314). For promotion deception, variation in product information among marketers was the strongest predictor (β = 0.293, t = 6.189, p < 0.001). However, emphasizing product advantages while omitting drawbacks did not make a significant unique contribution (β = 0.030, p = 0.537). Overall, the findings provide substantial but partial item-level support for the proposed relationship between MD and CPI. Confirmation of the overall hypothesis should be based on the model-level R², F-value, and associated p-value.

Table 6 summarizes the separate regression models examining the relationships between the four MD dimensions and both CSI and CPI. All models are statistically significant (p < 0.001). Distribution deception explains the greatest proportion of variance in CSI (R² = 0.613), whereas pricing deception explains the greatest proportion of variance in CPI (R² = 0.682). Promotion deception explains the smallest proportion of variance in CSI (R² = 0.523), while product deception explains the smallest proportion of variance in CPI (R² = 0.601). Overall, the four MD dimensions significantly predict both CSI and CPI when examined separately.

Table 6. Regression model summaries for the effects of MD dimensions on CSI and CPI.

Table 7 presents the simultaneous effects of the four MD dimensions on CSI and CPI. Both regression models are statistically significant (p < 0.001). Distribution deception is the strongest predictor of both CSI (β = 0.427, p < 0.001) and CPI (β = 0.466, p < 0.001). Pricing and promotion deception also significantly predict both outcomes. Product deception significantly predicts CPI (β = 0.196, p = 0.008) but does not make a significant unique contribution to CSI (β = 0.047, p = 0.575). Thus, the findings provide partial support for the effect of MD dimensions on CSI and full support for their effects on CPI.

Table 7. Multiple regression results for the effects of MD dimensions on CSI and CPI.

As seen from Table 8, all hypothesized relationships were statistically significant at the 0.001 level of confidence. It is possible to observe that marketing deception had a statistically significant positive impact on both customer punitive intentions (β = 0.332) and customer switching intentions (β = 0.796). This result means that, in addition to directly promoting punishment, marketing deception leads to higher switching intentions among customers. In turn, customer switching intentions significantly and positively influenced punitive intentions, with a β value of 0.301. This fact means that customers who plan to discontinue their relationships with service providers are more prone to act in a punishing manner. Moreover, the results of the mediation analysis indicated that there was a significant indirect effect of marketing deception on customer punitive intentions through customer switching intentions (β = 0.336). This resulted in a very high total effect (β = 0.800). From this perspective, this study leads to the conclusion that customer switching intentions partially mediated the relationship between marketing deception and customer punitive intentions.

Table 8. Summary of direct and indirect hypothesis testing.

Figure 2 reveals the relationship between the four dimensions of marketing deception (MD), i.e., product deception (X1), pricing deception (X2), distribution deception (X3), and promotion deception (X4). The results reveal significant and positive correlations among all dimensions of marketing deception, highlighting their close relationship and conceptual distinction as separate entities within the overall construct of marketing deception. In more detail, product deception (X1) reveals significant and positive correlations with pricing deception (X2), distribution deception (X3), and promotion deception (X4), highlighting their relationship in terms of deceptive marketing practices in product-related areas. Similarly, pricing deception (X2) reveals significant and positive correlations with distribution deception (X3) and promotion deception (X4), highlighting their relationship in terms of deceptive marketing practices.

Moreover, distribution deception (X3) and promotion deception (X4) reveal significant and positive correlations, highlighting their relationship in terms of deceptive marketing practices. The strength of these correlations reveals their relationship as a single construct of marketing deception. The above findings reveal the multidimensional construct of marketing deception and confirm the theoretical assumption of marketing deception, highlighting the relationship among deceptive marketing practices in different areas of the marketing mix.

5 Discussion

This study analyzed how marketing deception impacts customer punitive intentions, with the switching intentions of customers serving as a mediator, specifically in the context of social commerce on Facebook in Egypt. Using the Stimulus–Organism–Response (S-O-R) theory, the results have confirmed empirically that deceptive marketing acts as an effective environmental stimulus that affects the internal evaluation of the customers and consequently motivates their punitive behavior. The results have indicated that marketing deception not only positively affects the customer's punitive intentions but also encourages customers to increase their intentions to switch to other providers. Furthermore, customer switching intentions serve as a significant mediator of marketing deception and customer punitive intentions.

The positive relationship observed in the results indicates that deceptive marketing is associated with customer punitive intention due to the violation of customers’ perceptions of fairness, honesty, and relationship norms. In situations where there are differences in what was promised in promotions and what customers actually received, customers develop a feeling of unjust treatment and hence are more motivated to punish the company for this misconduct. From the S-O-R approach viewpoint, marketing deception can be regarded as the external stimulus, while customer punitive intentions are the behavioral reaction following the customers’ negative cognition and emotions. Instead of being passive victims of deceptive actions, customers attempt to correct this injustice by engaging in behaviors that are punishing, such as complaining, spreading negative word of mouth, and dissuading other customers from working with the firm. The obtained results coincide with those of previous studies, which have established that marketing deception decreases customers’ trust and motivates them to punish companies for their unethical conduct (Riquelme et al., 2016; Romani et al., 2013).

In addition to this, the findings show that there is a significant positive impact of marketing deception on customers’ switching intentions. Marketing deception not only harms the current evaluation of the service provider but also reduces the likelihood of future customer relationships with the same organization. When customers conclude that the organization intentionally deceived them about any features of its products or services, they lose considerable confidence in the organization. Customers lose considerable confidence in the organization when they conclude that it intentionally deceived them about any features of its products or services. considerably. Therefore, customers tend to seek other organizations to work with that they will see as more credible and reliable. In terms of the S-O-R model, customer switching intentions correspond to the organismic state, which reflects how the customers process internally the experience gained from the interaction with the organization in the context of its marketing deception. Customers don't immediately punish the organization but instead assess whether to continue the relationship.

Moreover, customer switching intentions also emerged as an important predictor of customer punitive intentions. It indicates that customers who have already decided to end their relationship with a dishonest company are also more likely to exhibit punitive behaviors toward such organizations. The moment they psychologically separate themselves from such a firm, the costs of punishment reduce drastically for them. Thus, they are more prone to indulge in actions that involve the dissemination of negative information about the firm via online reviews, social media conversations, complaints, and other kinds of punishment behavior. This research extends prior studies by demonstrating that switching intentions encompass not only behavioral intentions regarding future purchases but also represent a crucial psychological phase that occurs before any punitive behavior.

One of the most crucial insights provided by the present study relates to the mediating impact of customer switching intentions. The presence of the indirect effect indicates that customer punitive intentions are not a direct consequence of deceptive marketing practices. Specifically, customers do not immediately take action against firms practicing deceptive marketing tactics. On the contrary, deception affects customers’ psychological evaluation of the firm because of their increased intentions to terminate the relationship. Such disengagement in turn facilitates customers’ punitive intentions. In other words, customer switching intentions serve as a psychological mediator connecting deceptive marketing practices with customer punitive intentions. These findings corroborate the notion implied by the S-O-R model suggesting that stimuli affect behavior through changing the individual's internal psychological state (Mehrabian and Russell, 1974). Thus, the mediation effects contribute to a more profound understanding of how deceptive marketing practices impact customers compared to the research studying direct relationships.

These results can also be applied in a larger body of studies devoted to deceptive marketing because they show that not only does the consumer become dissatisfied with an organization, but he/she is capable of engaging in certain actions designed to negatively affect the firm's reputation. According to Leonidou et al. (2013) and Fernandes and Clamote (2016), previous studies have largely focused on the negative consequences of deceptive marketing in terms of customers’ trust, satisfaction, and loyalty. This study complements the literature on deceptive marketing by illustrating how deceptive marketing leads to both customers distancing themselves from the organization and engaging in behaviors that seek to damage the reputation of the organization. In the context of today's social commerce such as Facebook, consumers have multiple ways to share negative experiences with wide audiences on the Internet.

These findings are especially significant for social commerce on Facebook since social networking sites greatly increase the power of customers to communicate their negative experiences with other customers. Unlike the conventional brick-and-mortar setting, Facebook provides disgruntled customers with the possibility to disseminate the information instantly through comments, reviews, recommendations, and group discussions. This implies that the punishments incurred due to the use of deceptive marketing can extend beyond the interactions between particular customers and firms and impact the purchasing decisions of many potential customers.

From a theoretical point of view, the current study contributes to the stimulus–organism–response theory in terms of deceptive marketing since it experimentally distinguishes between the internal psychological reactions of customers and their further behavioural reactions. While many earlier studies paid much attention to the relationships between marketing deception and customers, there has been relatively little interest shown in the psychological mechanism of how deception influences customers’ punitive intentions. This study makes it clear that the switching intention of customers serves as an organismic reaction that links marketing deception with customers’ punitive intentions and thus increases the theoretical basis for the applicability of the S-O-R theory in social commerce situations. Thus, it is obvious that the customers’ behaviour in the intermediate psychological stage shapes their behaviour by the intermediate psychological stage, rather than their reaction to deceptive marketing. This phenomenon occurs through the intermediate psychological stage, rather than as a direct reaction to deceptive marketing.

In general, the results indicate that the outcomes of deceptive marketing tactics go far beyond just the immediate dissatisfaction experienced by the customers. Deceptive marketing creates mistrust, damages the customer–organization relationship, encourages customers to switch to other organizations, and finally drives behaviors aimed at punishing the organization. As customers become more connected via social networking sites, any organization that indulges in deceptive marketing tactics faces considerable reputation risk, which could have an impact on current and potential customers. Therefore, the organization must be honest and consistent in its communication to prevent such customer behavior.

6 Conclusion

6.1 Theoretical contribution

The study contributes significantly to the marketing deception, customer behavior, and social commerce literature from various perspectives. In terms of marketing deception literature, the study advances this field through an understanding of the direct and indirect influence of marketing deception on customer punitive intentions. Although other works have considered the consequences of marketing deception in terms of customer satisfaction, trust, loyalty, company image, or repurchasing intention (Bozkurt and Gligor, 2019; Mohsen and Enad, 2019; Sadiqe, 2023), little work has been done empirically in exploring how marketing deception triggers customer retaliation. This study widens the field of marketing deception through an empirical investigation of how marketing deception motivates customers to disengage from the service provider and retaliate against the organization.

The second contribution of the current study to the literature is that it adds to the S-O-R framework by empirically illustrating how marketing deception works on the psychological level to affect customers’ behaviors. In other words, marketing deception can be defined as an environmental stimulus; customer switching intention serves as an organismic response; and customer punitive intention is the last behavioral response. Even though the S-O-R framework has been extensively used to understand consumers’ behavior in an online environment, few studies have utilized the above framework to explore how customers react to deceptive marketing tactics. The results of the current study show that customer switching intention works as an intermediary variable by which customers’ punitive behavior is affected through marketing deception.

Thirdly, this research expands the literature by focusing on customer switching intentions as a mediating variable between marketing deception and customer punitive intentions. Earlier studies have focused on switching intentions in relation to electronic service quality, customer satisfaction, and ethics perception (Elshaer et al., 2025; Ghias et al., 2022). Meanwhile, other studies have focused on separate aspects of customer behavior that are considered punitive, such as complaints, boycotts, and negative word-of-mouth (Garbarino and Maxwell, 2010; Lindenmeier et al., 2012). In contrast, there is not enough information about the connection between switching intentions and deceptive marketing actions. The identification of customer switching intentions as a mediator allows for a deeper understanding of customer behavior.

Fourth, the study makes an important contribution to the marketing ethics literature by synthesizing marketing deception, switching intentions, and punishing intentions into a single framework. Contrary to prior studies that focused separately on each variable, the study model analyzes the relationship between these constructs in their totality, thereby revealing the psychological reactions caused by unethical marketing activities and how they lead to the behavior of punishment.

Additionally, this study adds to the body of literature on online customer behavior by offering empirical data based on Facebook-enabled social commerce in Egypt. While previous studies have considered unethical marketing behavior in retailing and e-commerce, evidence based on social commerce is relatively scarce, especially among emerging markets. This is because of the dynamic nature of social media, through which customers can swiftly communicate their views through reviews and comments and thus amplify the negative effects of marketing deception. In this regard, the current results add to the body of literature by identifying the effects of marketing deception on customer behavior in social commerce.

6.2 Practical contribution

The implications of the study's findings for marketing managers are numerous, especially in the digital and hospitality marketing fields, where customer trust and transparency are key drivers for marketing success. First, organizations should focus on implementing ethical marketing strategies that are free from deception in all aspects of the marketing mix. Ensuring that honesty is upheld in product information, pricing, distribution, and promotion is critical to building customer trust, which in turn reduces negative behavioral responses such as customer switching and punitive reactions. Second, marketing managers should seek to develop customer relationships that are based on ethics by providing products that meet customer expectations, being credible in all customer interactions, and being transparent in their communication with customers. Such customer relationships based on trust not only satisfy the customer but also create loyalty.

Third, organizations are urged to promote transparency regarding customers’ rights and the legal process in the case of unethical business practices. This promotes customers’ sense of security, which in turn boosts their confidence in the organization, thereby reducing the likelihood of customer flight to other organizations. Fourth, organizations are urged to seek to convert customers into brand advocates through the use of ethical business practices. This way, customers are likely to promote the organization positively, as opposed to engaging in negative behaviors towards it in the case of unethical business practices. Fifth, marketing ethics should be considered a key driver of organizational success, especially in a competitive environment where organizations are competing for customers’ loyalty. This way, organizations can use ethical business practices as a differentiator in a competitive environment. Sixth, organizations should seek to develop a comprehensive framework for ensuring compliance with ethical standards in marketing. Moreover, the institutionalization of ethical practices through the formulation of guidelines and training programs can assist marketers in avoiding deceptive practices and promoting integrity. Finally, marketers should effectively manage the various components of the marketing mix to incorporate ethical standards. This includes the provision of products that meet the needs of customers, the formulation of fair prices for products, the use of appropriate and reliable channels for the distribution of products, and the creation of promotional campaigns that are honest and sensitive to culture.

6.3 Limitations and future research

The current study has some limitations that must be acknowledged. First, the current research used a cross-sectional approach, which does not allow for establishing cause-and-effect relationships between the study variables. It is recommended that future studies apply longitudinal or experimental approaches to study the dynamics of how customers perceive marketing deception and how they behave.

Second, data were collected from Facebook users who were involved in online shopping in Egypt. Therefore, the results cannot be generalized beyond a similar context of social commerce. Further studies need to replicate the model developed in the current paper across various countries and cultures using different digital platforms.

Thirdly, all variables have been measured using self-reported data collected through one questionnaire; thus, the risk of common method bias is high despite the various procedures implemented during data collection. Future researchers may consider it beneficial to collect data from more than one source or at several occasions to avoid any method bias. Fourthly, this study examined the concept of customer switching intentions as the only mediating variable between marketing deception and customers’ punitive intentions. Future research can adopt the proposed model and test for other mediating variables such as customer anger, perceived injustice, customers’ trust, or customers’ dissatisfaction, among others. Lastly, this study has adopted the Stimulus-Organism-Response (S-O-R) approach in the development of the theoretical framework. Future research can incorporate other theories in their frameworks, such as justice theory, attribution theory, or psychological contract theory, among others.

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Footnotes

Edited by: Tereza Semerádová, Technical University of Liberec, Czechia

Reviewed by: Solomiia Fedushko, Lviv Polytechnic National University, Ukraine

Andriati Fitriningrum, PPM School of Management, Indonesia