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Emotional intelligence and consumer decision-making styles: the mediating role of brand trust and brand loyalty

Future Business Journal volume 9, Article number: 57 (2023) Cite this article

Abstract

This paper brings to light emotional intelligence’s impact on consumer decision-making styles during purchases. We show how brand trust (BT) and brand loyalty (BL) act as mediators between emotional intelligence (EI) and decision-making styles. We further indicate how consumers rely on emotional intelligence (EI) when purchasing products or services based on specific decision-making styles and patterns. We examine this issue by selecting customers who shop at the Accra and West Hills Malls. Seven hundred and fifty (750) respondents from the two selected malls comprised the study’s sample size. The respondents were chosen using the simple random and accidental/convenient sampling approach. The study hypotheses were examined using cross-sectional survey data. We use confirmatory factor analysis and structural equation modeling to analyze the data. We exhibit reliable information that emotional intelligence mediates the relationship between BT and BL, while the relationship between brand trust and brand loyalty is more strongly mediated at higher levels of EI. The result indicates a partial mediation between emotional intelligence and decision-making style through brand loyalty. This paper aims to increase knowledge on the importance of emotional intelligence from the perspective of customers through decision-making styles.

Introduction

Emotional intelligence is currently feeding firms on how consumers think and feel about their products. Therefore, the new standard for conducting business is for production and service firms to recognize, access, and generate emotions to aid thought and comprehend consumer emotions, and reflectively control emotions to foster the emotional and intellectual development of their products. For example, Japanese automobile companies such as Honda, Toyota, and Nissan had their research department focusing on the emotional intelligence of customers in terms of colors, shape, size, pricing, and design in relation to the companies’ operational costs of their cars [26], while British Airways has its share of how emotional intelligence is applied in terms of customers being asked after a flight in a survey as to how they feel about the fight and what their expectations were in terms of the service they had received during the flight. Furthermore, a New York Times report revealed that Hyundai has directed its creative designers and production managers in South Korea to ensure that consumer emotional intelligence is considered in terms of safety features, comfortability of passengers, and new models of cars they are producing [50]. Therefore, to implement efficient marketing tactics and thrive in today’s cutthroat market, a marketer must be aware of the elements impacting consumers’ buying habits.

Businesses must be abreast with how consumers think about their products before and during purchases, and one area they should concentrate on is the emotional intelligence (EI) of consumers. EI is increasingly used as a factor in the decision-making process of customers, especially during purchases [3, 43]. Studies on emotional intelligence and emotional competence have recently been expanded to include emotional self-efficacy and emotional confidence (ESE) [16, 31, 40]. Moreover, the emotional confidence of customers has increased which is in line with their feelings and experience during the purchase of products [34]. EI depends on experience and how well society views its emotional abilities. Researchers have made significant efforts to grasp how EI affects business but not customers’ purchasing skills and decision-making approaches [32, 46, 50]. Due to this notion, some studies have concluded that there is no association between EI and customers’ purchase decision-making styles, while others have found conflicting results [16, 23, 31, 61], whereas others have noted the existence of a favorable link [3, 43, 63]. This body of evidence raises questions about whether and when it may be advantageous for firms to understand and appreciate customers’ decision-making styles concerning their emotional intelligence (EI), considering brand trust and brand loyalty. It is this knowledge gap this study seeks to address.

Moreover, self-report or ability-based measures of emotional intelligence (EI) have typically been employed in marketing research to assess how successfully frontline staff uses EI to interact with customers [10, 13, 32, 33, 45, 65] but the focus has never been on customers purchasing decision. However, Day and Carroll [13] indicated that EI alone is not enough to predict customers. Despite the overwhelming evidence supporting the potential advantage of El achieving organizational performance which has been researched in the area of human resource management by Santos et al. [54], team members by Liu and Liu [38], leaders in public human service by Ruestow [52], visitors by Prentice et al. [51], and lawyers by Beason [7] while Peters [49] also discuss how to make it possible for employees’ reputations regarding EI in various organizational and professional contexts, and it has not been done in the area of consumer decision-making styles. This indicate that not much attention has not been given to the motive behind customers’ decision-making style toward purchases.

However, as a novelty, the present study analyzes and adds to the body of knowledge on consumer decision-making style and emotional intelligence. In order to remove any ambiguity in the existing emotional intelligence literature, we first conceptually emotional intelligence construct from an output-based perspective, and we explained how this approach might be connected to consumer decision-making style conceptualization. In light of the foregoing, the following research issues are examined in this study:

  1. 1.

    What is the essence of emotional intelligence toward consumer decision-making styles?

  2. 2.

    How does emotional intelligence influence decision-making style toward brand trust and brand loyalty?

Literature review and hypotheses development

Theoretical position

The theory of customer brand engagement serves as the foundation for this investigation. Consumer brand engagement (CBE), according to Brodie et al. [8], is a psychological state that results from a customer’s interactions with a focal agent, such as a product, business, or brand. The firm depends on customers’ favorable brand-related cognitive, emotional, and behavioral activity occurring during or related to key customer/brand contacts. CBE, according to Hollebeek [28], is the cornerstone of the engagement paradigm. This is the core notion of fostering a solid relationship with the customer that motivates [48]. CBE is related to consumers’ preferences for a certain brand and is consistent with customers’ affiliation to a product that they turn to buy, resulting in trust and loyalty though conceptually distinct from various marketing conceptions [28]. Consumers’ preference for flawless brands results in brand trust and loyalty. Customers choose specific brands when they shop at the mall, which fosters brand trust and loyalty, but the choice to buy a product depends on the customers’ emotional intelligence, based on how they feel about a specific product.

Emotional intelligence (EI) and decision-making style (DMS)

Day and Carroll [13] and Zeidner et al. [65] used meta-analysis to investigate the connection between emotional intelligence (EI) and customer intention toward consumer buying behavior. Their study revealed that consumers could be evaluated objectively using ability-based tests and subjectively using trait-based assessments of the concept, which have come under fire for being prone to forgery and social desirability bias [13]. To understand emotional intelligence, Moore [47] confirmed that a non-significant or negative connection between EI and consumers’ purchase intention was equal to that of research indicating a positive association in a percentage of his trials as supported by Grant [21].

On the other hand, Joseph and Newman [30] came to the conclusion that for EI to be successful, customers must feel comfortable sharing their emotions with clients. This argument was founded on the understanding that consumers must cope with uncertainties and uncomfortable circumstances when interacting with salespeople, such as trust [62], impolite salespeople [31], or remarks that make them feel guilty while buying a product [61]. Customers, regardless of their emotional intelligence, are likely to experience emotions under these circumstances, particularly if they lack confidence in it. Based on the above, it is proposed that:

H1

Emotional intelligence (EI) has a significant positive association with Decision-Making Style.

Emotional intelligence (EI) and Brand trust (BT.)

Emotional intelligence (EI) is seen as the capacity to recognize, access, and generate emotions to support thought grasp emotions, and reflectively govern emotions to foster emotional and intellectual development as indicated by Mayer and Salovey [43]. According to Lopez et al. [39], emotional intelligence (EI) is the capacity to understand how to manage one’s own emotions as well as those of others. Deci [14] demonstrated that EI is believed to perform a number of crucial activities, including organizing and prioritizing incoming information, focusing attention on matters of immediate relevance, and motivating others to take the necessary actions. A committed relationship between a buyer and a seller only emerges after some time has passed and they get to know one another.

In the same vein, turning EI into brand trust requires a number of positive consumer experiences. Previous research indicates that when overall satisfaction increases brand confidence of customers is expected to increase as well leading to the welfare and interests of customers, which in turn promotes trust [10, 19, 32, 33, 45]. As a result, brand trust will rise proportionately to the extent to which EI is felt by customers. Consequently, it is plausible to believe that EI and brand trust are associated as a result of the prior empirical evidence and debate. The following can therefore be postulated:

H2

Emotional intelligence (EI) has a significant positive relationship with brand trust (BT.)

Brand Trust (BT) and Decision-Making Style (DMS)

More empirical research on brand trust as confirmed by Peterson [50], Fitness [18] and Day and Carroll [13] indicate that consumer expectation of a product, certain qualities, circumstance, or performance leads to brand trust. Additionally, customers depend on trusted brands to make them feel secure [6]. For instance, customers’ perception of risk while choosing a brand is reduced by brand trust [25]. Furthermore, risk and uncertainty are eliminated, especially when the customer is feeling vulnerable. Although studies have highlighted direct impact, brand trust influences purchasing behavior and speeds up the decision-making process [10, 32, 33, 35]. Prior studies also highlighted that brand trust basically leads to customer satisfaction [10, 32, 33, 36, 45]. Additionally, Beason [7] confirmed that brand trust is the conviction that the company will keep its commitments to customers.

While most studies acknowledge the impact of collaboration on decision-making styles Kidwell et al. [32] emphasize that customers have a long-term relationship with a brand based on an easy decision-making process. Consequently, in their respective investigations, Peters [49], Matzler [41], Hsu and Cai [29], and Sahin [55] all indicated that brand trust influences decision-making styles. Along these lines, Peters [49], Beason [7] and Bakewell and Mitchell [4] confirmed that greater brand trust in a product positively influences decision-making by a customer. Likewise, Peterson [50] demonstrate that consumer decision style is influenced by specific product based on brand trust. Against this background, due to the close ties to consumers’ purchasing behavior due to brand trust, researchers have paid close attention to identifying specific consumer decision-making styles across time [10, 25, 33]. Therefore, we posit the third hypothesis is as follows:

H3

Brand trust (BT) has a direct relationship with Decision-Making Style (DMS)

Emotional intelligence (EI) and Brand loyalty (BL)

Although studies have highlighted the direct impact of EI from the viewpoint of consumers [10, 32, 33, 45], none has focused on brand loyalty. Additionally, Mayer and Salovey [43] indicate that through the emotional ability model which was enhanced by Baer [3] to include consumer behavior, brand loyalty has a positive influence on consumers’ decision-making process. Patterson et al. [48] and Joseph and Newman [30] indicate brand loyalty capabilities must be able to, directly and indirectly, influence consumer decision-making based on their personal emotional intelligence of the product in question. For instance, Beason [7] and Peters [49] elucidated an understanding of how emotional intelligence assists in consumers’ decision-making process. As Kidwell et al. [32] indicate, customers with high emotional intelligence counterattacked impulse purchases.

Based on the concepts established by Peters [49], emotional intelligence is associated with consumer purchasing behavior. Despite the overwhelming evidence supporting emotional intelligence, Patterson et al. [48], Joseph and Newman [30] and Rust and Oliver [53] highlight the importance of customers being loyal to a brand based on the consistency of purchasing specific products without hesitation. Furthermore, Lee [36] and Grant [21] propose the idea of loyal customers being more profitable to keep than acquire new ones. Additionally, customers who are extremely devoted to a brand are willing to spend more, which means more profit for businesses with loyal customers [45]. The hypothesis is proposed based on the literature above that:

H4

Emotional intelligence (EI) has a direct relationship with brand Loyalty (BL)

Brand loyalty (BL) and Decision-making style (DMS)

Empirically, there is evidence to suggest that brand loyalty has an influence on the attitude of consumers’ decision-making styles [30, 48, 53]. Brand loyalty allows consumers to purchase more of a product from a company based on what motivates them, which could are emotional, cognitive, or behavioral levels [7, 38, 51, 52, 54]. When consumers think favorably of brands, they became committed to them [58]. Customers turn to develop strong and long-lasting relationships with brands leading to brand loyalty [21]. Consequently, brand loyalty is the intention of the customer to continue a relationship with the brand based on the performance of the product and customers’ expectations of the product being met [7, 49, 58].

Generally, there has not been a strong consensus on the emotional intelligence (EI) concept, or its constituents [7, 48]. Research has not taken into account how EI and brand loyalty interact, despite studies highlighting the direct effects of decision-making based on individual behavior (Fig. 1). Therefore, a person’s emotional intelligence determines their ability to make better decisions. The hypothesis is proposed based on the literature above that:

Fig. 1
figure 1

Conceptual model on the relationship between the variables

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H5

Brand trust (BT) has a direct relationship with Decision-Making Style (DMS)

Methods

The paper aims to examine the link between emotional intelligence toward consumer decision-making styles with reference to mediation between brand trust and brand loyalty. Primary data were sourced from the field of study through questionnaire administration. Before the actual study, approval from the owners of Accra and West Hills malls was sought to gain permission to speak with customers. Consistent with prior studies [10, 13, 32, 33, 44, 45, 65], the cross-sectional survey design was used for the study. Additionally, while different writers have varied opinions on how to choose the sample size, in most circumstances, it is advisable to use a large sample size [12, 57, 64]. Stevens [57] recommends a minimum of 45 participants per predictor for a viable equation when doing factor analysis.

Moreover, Tabachnick and Fidell [60] use the following formula to get the sample size for the specified number of independent variables: N > 50 + 8 m (where m = number of independent variables). A precise sample size was chosen, and questionnaires were sent to the chosen respondents in accordance with these conditions and others, as stated by Yin [64]. According to the owners of Accra and West Hill Mall, there were 780 consumer purchases made each day. Moreover, simple random and accidental/convenient sampling technique were used to select customers [57]. The data was elicited between March and May 2022. The following criteria were used to select customers:

  1. a.

    must be a regular customer at the mall.

  2. b.

    buying things for at least 2 years

  3. c.

    willingness and availability to participate in the study.

Variable measurement

In this study, brand trust, brand loyalty, consumer decision-making styles, and emotional intelligence (EI) were all measured using a questionnaire. Emotional intelligence was measured using a 16-item scale adopted/adapted from Kidwell et al. [32]. The questionnaire has a total of 16 items over five domains, including self-awareness, motivating oneself, emotion regulation, social skills, and empathy. The results of the validity and reliability construct were reliable (Cronbach’s alpha EI coefficient = 0.736, the range of the EI’s correlation coefficient: 0.332–0.597; significant at p 0.05).

Decision-making style was measured from a 50-item scale adopted/adapted from Sproles [56] which focused on attitudes toward shopping and purchasing, while brand trust was measured using scales adapted from Sung and Kim [59] and Matzler et al. [42]. Brand loyalty was measured using a scale adapted from Chaudhuri and Holbrook [9]. A six-point Likert-type scale question with endpoints rated from (1 = extremely dissatisfied; 6 = extremely satisfied) was used to measure customer satisfaction. All constructs-related questions were measured using a five-point Likert-type scale (1 = strongly disagree; 5 = strong agree).

Data analysis

Structural equation modeling (CB-SEM) was used to assess the study model. The validity of the model was verified using exploratory and confirmatory investigations. The structural model and the designated SEM techniques were then compared [24]. Using the bootstrapping method (5000 resamples), the significance and loadings of the path coefficients were tested [24].

Results

Assessment of the measurement model

To make sure the constructs used in the study were reliable and valid, a diagnostic test was conducted. Validity examines the precision and the extent to which concepts are adequately captured by items, while reliability gauges the consistency of items [2]. Thresholds were properly followed for each of the measurement criteria to ensure the study’s validity and reliability. To ensure the validity and reliability of the study, the indicator loading must be larger than 0.7 and the composite reliability must be greater than 0.6. [24, 27]. For the investigation, a reflecting measurement model was created. By evaluating factor loadings, composite reliability (CR), and average extracted variance, the model was put to the test (AVE). The results are presented in Table 1.

Table 1 Respondents’ profile
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Factor loadings, composite validity and reliability

Table 2 reveals that all item loadings exceeded the recommended value of 0.7. Composite reliability values, which depict the degree to which the construct indicators of the latent construct, exceeded the recommended value of 0.7, while average variance extracted, which reflects the overall amount of variance in the indicators accounted for by the latent construct, exceeded the recommended value of 0.5. Table 2 shows that the composite reliability values range from 0.888 to 0.973. All the values for the construct exceeded the threshold of 0.70. It can be concluded that all the constructs are reliable. The convergent validity of the indicators was also assessed. Convergent validity is gauged with average variance extracted (AVE), which should yield a minimum value of 0.50 or higher, indicating that a construct explains at least 50% of the variance in the underlying indicators. An examination of all AVEs in Table 2 shows that all constructs explained at least 50% variation in their indicators, so convergent validity was achieved (Fig. 2).

Table 2 Construct reliability and validity
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Fig. 2
figure 2

Outer loadings and R-values

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Discriminant validity

There was also an evaluation of the discriminant validity. Low correlations between the measure of interest and the measurements of other constructs are indicative of discriminant validity, which is the degree to which the measures do not reflect certain other variables. According to Fornell and Larcker’s [17] criterion, the factorial loadings in each concept should be greater than all other correlation values among the latent variables in order to ensure discriminant validity [11, 17]. The square root of the AVE (diagonal values) for each construct in Table 3 is greater than the corresponding correlation coefficients, demonstrating sufficient discriminant validity [17]. The discriminant validity result in Table 3 shows that all the factorial loadings in their respective constructs are higher than all the other correlation values among the latent variables. The implication is that each latent variable is genuinely different from the other. It also means that there is uniqueness in the measurements of the constructs. Therefore, the rule of thumb proposed by Fornell and Larcker [17] was met in this study.

Table 3 Fornell–Larcker
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Path coefficients

The research hypothesis was tested after assessing the measurement model to ensure it meets the PLS-SEM criterion. The hypotheses specifically focused on examining the effects of emotional intelligence on decision-making and the mediating role of brand trust and brand loyalty. The hypotheses were tested by assessing the direction and strength using the path coefficient (β) and significance level with t-statistics obtained through 5000 bootstraps, a two-tailed test suggested by Hair et al. [24]. Based on the study’s goal, Table 4 shows how the results of the hypotheses tested with PLS-SEM were presented.

Table 4 Path coefficient
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Discussion

The study was designed to determine H1 to H5. For H1, which was to predict the effect of emotional intelligence on decision-making styles, it is hypothesized that emotional intelligence significantly influences decision-making. The result of the study supports the hypothesis. This is because the t-stat value was 3.434, which was above the threshold of 1.96 (β = 0.311; p = 0.001; p < 0.5). It implies that emotional intelligence significantly influences decision-making. A percentage change in emotional intelligence will lead to a 31.1% change in decision-making. This implies that emotional intelligence plays an important role in decision-making. These support the view of Peter’s [49] research, which indicates that customers with high EI are more likely to make bold decisions based on the situations they face while purchasing a product. Moreover, this finding supports the assertion by Chaudhuri and Holbrook [9] that when EI increases, it significantly influences decision-making. Subsequently, EI directly influences decision-making styles, which is supported by Ruestow [52] argument that EI can be implemented in the selection, placement, and promotion processes, as well as to evaluate customers’ success.

For H2, the study seeks to establish the effect of emotional intelligence on brand trust. It is hypothesized that emotional intelligence significantly influences brand trust. The result of the study supports the hypothesis. This is because the t-stat value was 6.050, which was above the threshold of 1.96 (β = 0.520; p = 0.000 p < 0.5). It implies that emotional intelligence significantly influences brand trust. A percentage change in emotional intelligence will lead to a 52.0% increase in brand trust. This implies that emotional intelligence plays an important role in brand trust in customers’ decisions in buying a product. This confirms the assertion made by Grant [21], Lee [36], Delpechitre and Beeler [15] that customers with high EI turn to develop and prefer products they have used before, leading to brand trust. Moreover, customers with high levels EI exhibit deep knowledge of products leading to self-awareness and emotional regulation toward specific products.

With reference to H3, which examined the effect of brand loyalty on decision-making, it is hypothesized that brand loyalty significantly influences decision-making. The result of the study supports the hypothesis. This is because the t-stat value was 3.486, which was above the threshold of 1.96 (β = 0.489; p = 0.000 p < 0.5). It implies that brand loyalty significantly influences decision-making by customers. A percentage change in brand loyalty will lead to a 48.9% increase change in the decision-making of customers. This implies that brand loyalty plays an important role in making decisions in various consumers’ purchase decisions at the mall. This confirms the assertion by Stevens [57] that when they developed the consumer style inventory (CSI), more parsimonious categories of decision-making styles are perfectionistic, price-value consciousness; brand consciousness; novelty-fashion consciousness; confusion by over choice; recreational shopping consciousness; impulsiveness and habitual brand–loyalty all must be looked at since it has a relationship with each other.

Additional results from the study indicate that for H4, it was hypothesized that brand trust significantly influences decision-making. The result of the study did not support the hypothesis. This is because the t-stat value was 0.556, which was less the threshold of 1.96 (β = 0.089; p = 0.556; p > 0.5). It implies that brand trust does not influence the decision-making of consumers purchasing decisions. A percentage change in brand trust by 8.9% will not cause any change in decision-making. This implies that brand trust does not play a significant role in customers’ decision-making process before and during purchases at the mall. These additional findings further enhance brand trust in consumer decision-making style, while Lee [36] find no support for this since trust is a state of expectation about a particular subject, situation or person. Customers rely on a brand they can trust, making them feel safe during purchase [5]. Brand trust ensures customers believe the brand is sufficient to meet their needs and wants. Brand trust decreases the perceived risk of customers while choosing the brand. It eliminates risk and uncertainty, especially in an environment where the customer feels vulnerable.

Again, H5 hypothesized that emotional intelligence significantly influences brand loyalty. The result of the study supports the hypothesis. This is because the t-stat value was 7.524, which was above the threshold of 1.96 (β = 0. 554; p = 0.000 p < 0.5). It implies that emotional intelligence significantly influences brand loyalty during consumer purchase decision-making style. A percentage change in emotional intelligence will lead to a 55.4% increase in brand loyalty. This implies that emotional intelligence plays an important role in brand loyalty regarding customers purchasing a product. Consequently, it indicates that when consumers are making a purchase, it is easier to consider the product’s brand loyalty. This confirms the assertion by Aaker [1] that product reputation and trust describe the feeling that an individual, group, or organization can rely upon to fulfill their promises; these attributes play a key role in the development of customer loyalty [25, 36]

A mediation analysis was performed to assess the mediating role of brand trust on the relationship between emotional intelligence and decision-making. The total effect of emotional intelligence on decision-making was found to be significant (β = 0.628, t = 10.017, p = 0.000). The impact of emotional intelligence on decision-making was found to be significant when the mediation variable brand trust was included (β = 0.311, t = 3.434, p = 0.001). The indirect effect of emotional intelligence on brand trust decision-making was insignificant (β = 0.046, t = 0.552, p = 0.581). This indicates brand trust cannot mediate the relationship between emotional intelligence and decision-making.

Subsequently, the mediation analysis was performed to assess the mediating role of brand loyalty on the relationship between emotional intelligence and decision-making. The total effect of emotional intelligence on decision-making was found to be significant (β = 0.628, t = 10.017, p = 0.000). The impact of emotional intelligence on decision-making was found to be significant when the mediation variable brand loyalty was included (β = 0.489, t = 3.486, p = 0.000). The indirect effect of emotional intelligence on decision-making by brand loyalty was found to be significant (β = 0.271, t = 3.132, p = 0.002). To test for the strength of the mediation, the variance accounted for (VAF) was calculated as Hair et al. [24] recommended. The VAF is calculated as the indirect effect/total effect × 100. According to Hair et al. [24], one can interpret VAF values in the following way: VAF > 80% indicates full mediation, 20% VAF 80% means partial mediation, and VAF 20% indicates no mediation (Table 5).

Table 5 Mediation effect
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The result shows a partial mediating effect between emotional intelligence and decision-making style through brand loyalty because the variance accounted for (VAF) value was 55.4%. The result implies that emotional intelligence enhances decision-making with brand loyalty. This confirms the view of Lambert et al. [35] that satisfied customers are expected to be loyal, as revealed by their enthusiasm to repurchase and applaud the product of interest or brand [8]. Studies by Kidwell et al. [32], Goleman [20], Guy and Lee [22], and Delpechitre and Beeler [15] demonstrated that satisfaction is a crucial mediator that links brand loyalty and customers.

Managerial implications

This study also has a wide range of important managerial ramifications. First, this study empirically investigates the link between emotional intelligence and consumer decision-making preferences with a focus on brand loyalty and brand trust. The current study is early research that provides diverse and useful implications to managers of the mall, since it will affect how consumers make decisions during purchasing of product. Managers should consider consumers’ emotional intelligence into pricing of product and quality of the product displayed at their shop. We argue that managers should invest in developing and sustaining EI of their sales force, by building and sustaining EI which can prove to be challenging.

Additionally, when managers of the mall are arranging product at the mall, they should consider the brands of the products, and bear in mind the emotional intelligence of the target market especially customers. This must be communicated through creative, original, and innovative means so that the brand can continue to grow and gain the trust and loyalty of its customers. Relationships between customers and brands also showed promise as useful indicators of brand trust and loyalty. In order to build a loyal consumer base, industry professionals are urged to establish and sustain distinctive, positive, and long-lasting relationships between customers and brands. As a result, managers of the mall, need to keep in mind and concentrate on the emotional intelligence and competency of consumers. Despite its widespread application in practice, earlier research casts doubt on the utility of EI when customers buy their items.

Conclusion

According to the study’s conceptual framework, the results have managerial and academic ramifications for researchers and production companies in terms of how consumers’ emotional intelligence and decision-making processes might affect their trust and loyalty to a brand. First, by examining how emotional intelligence is applied to produce effective consumer decision-making styles, the study empirically supports the significance of the theory of customer brand engagement (CBE) in establishing and maintaining long-lasting relationships between a customer and a brand. By empirically demonstrating that the attachment and activation components of customer brand engagement foster a sense of loyalty among consumers, the study also emphasizes the connection between customer brand engagement and brand loyalty. The study strengthens our understanding of the value of customer brand involvement in relation to consumer decision-making styles.

Despite making a significant contribution to the field of marketing literature, this study has major drawbacks. First off, the study’s conclusions cannot be generalized because the data were only gathered from one business sector and one nation (Ghana) using a random sample. By employing various research methods to validate the conceptual model of this study in other nations with various cultures, future research may be able to solve this issue. Future research should examine the main emotional intelligence factors in relation to consumer preferences and tastes. Future studies should also look into the factors that led to the emergence of EI in consumers. It would be more beneficial to establish and manage an emotionally competent consumer market if we understood the precursors to EI. Future studies should focus on brand loyalty and examine how emotional cues can affect customer decision-making processes. Additionally, additional research can concentrate largely on how emotions are used in face-to-face interactions where verbal and nonverbal communication of emotions is unrestricted and open. Future studies should also look into the factors that led to the emergence of EI and ESE among salespeople, while early family influence can shape EI in early life (Additional file 1).

Availability of data and materials

All data generated or analyzed during this study are included in this published article [and its supplementary information files].

Abbreviations

EI:

Emotional intelligence

DMS:

Decision-making styles

BT:

Brand trust

BL:

Brand loyalty

SEM:

Structural equation modeling

CFA:

Confirmatory factor analysis

CSI:

Consumer style inventory

References

  1. Aaker D (2022) Brand leadership. The Free Press

  2. Ahari N, Abdullah Z, Fie DYG, Alam SS (2018) A study of job stress on job satisfaction among university staff in Malaysia: an empirical study. Eur J Soc Sci 8(1):121–131

    Google Scholar 

  3. Baer D (2018) Emotional intelligence predicts job success: Do you have it? Fast Company (December 16). https://www.fastcompany.com/3023335/emotional-intelligence-predicts-jobsuccess-do-you-have-it

  4. Bakewell M, Mitchell G (2023) Price and brand name as indicators of quality dimensions for consumer durables. J Acad Mark Sci 28(3):359–374

    Google Scholar 

  5. Ballester AL (2023) Brand loyalty: the link between attitude and behavior. J Advert Res 36(6):22–35

    Google Scholar 

  6. Ballester AL (2016) A comparison of attitudinal loyalty measurement approaches. J Brand Manag 9(3):193–209

    Google Scholar 

  7. Beason OL (2015) Emotional intelligence, leader-member exchange, job stress, and job satisfaction: A study of practicing attorneys. Regent University, ProQuest Dissertations Publishing. 3712088.

  8. Brodie RJ, Hollebeek LD, Juric B, Ilic A (2021) Customer engagement: conceptual domain, fundamental propositions, and implications for research. J Serv Res 14(3):252–271

    Google Scholar 

  9. Chaudhuri A, Holbrook MB (2021) The chain of effects from brand trust and brand affect to brand performance: the role of brand loyalty. J Mark 65(2):81–93

    Google Scholar 

  10. Chen G, Jaramillo RE (2014) The power of momentum: a new model of dynamic relationships between job satisfaction change and turnover intentions. Acad Manag J 54(1):159–181

    Google Scholar 

  11. Chin C (2022) Examining the structural relationships of destination image, tourist satisfaction and destination loyalty: an integrated approach. Tour Manag 29(4):624–636. https://doi.org/10.1016/j.tourman.2007.06.007

    Article  Google Scholar 

  12. Creswell JW (2020) Designing and conducting mixed methods research, 2nd edn. Sage, Thousand Oaks, CA

    Google Scholar 

  13. Day AL, Carroll SA (2018) Faking emotional intelligence (EI): comparing response distortion on ability and trait-based ei measures. J Organ Behav 29(6):761–784

    Google Scholar 

  14. Deci G, Olafsen B, Ryan KK (2018) From brands in general to retail brands: a review and future agenda for brand personality measurement. Mark Rev 12(1):91–106

    Google Scholar 

  15. Delpechitre D, Beeler L (2018) Faking it: Salesperson emotional intelligence’s influence on emotional labor strategies and customer outcomes. J Bus Ind Market 33(1):53–71

    Google Scholar 

  16. Esmaeilifar R, Iranmanesh M, Shafiei MW, Hyun SS (2022) Effects of low carbon waste practices on job satisfaction of site managers through job stress. RMS 14(1):115–136

    Google Scholar 

  17. Fornell C, Larcker DF (1981) Evaluating structural equation models with unobservable variables and measurement error. J Mark Res 28(February):39–50

    Google Scholar 

  18. Fitness J (2021) Emotional intelligence and intimate relationships. In: Ciarrochi J, Forgas JP, Mayer JD (eds) Emotional intelligence and everyday life. Psychology Press, New York, pp 6–18

    Google Scholar 

  19. Ganesan S (2014) Determinants of long-term orientation in buyer-seller relationships. J Mark 58(2):1–19. https://doi.org/10.1177/002224299405800201

    Article  Google Scholar 

  20. Goleman D (2021) Emotional intelligence: Why it can matter more than IQ. Jossey-Bass, Bantam Books, New York.

    Google Scholar 

  21. Grant A (2014) Emotional intelligence is overrated. LinkedIn (September 30), https://www.linkedin.com/pulse/20140930125543-69244073-emotional-intelligence-isoverrated/

  22. Guy ME, Lee HJ (2015) How emotional intelligence mediates emotional labor in public service jobs. Rev Public Personnel Admin 35(3):261–277

    Google Scholar 

  23. Haakonstad JM (2021) Emotional Intelligence Predictors of Sales Performance”, doctoral dissertation. Walden University, Department of Psychology

    Google Scholar 

  24. Hair JF, Hult GTM, Ringle C, Sarstedt M (2013) A primer on partial least squares structural equation modeling (PLS-SEM). Sage Publications

  25. Han H (2015) Image congruence and relationship quality in predicting switching intention conspicuousness of product use as a moderator variable. J Hosp Tourism Res 37(3):303–329

    Google Scholar 

  26. Harrigan P, Lall T (2018) Customer engagement with tourism social media brands. Tour Manag 59:597–609. https://doi.org/10.1016/j.tourman.2016.09.015

    Article  Google Scholar 

  27. Henseler J, Hubona G, Ray PA (2016) "Using PLS path modeling in new technology research: updated guidelines", Industrial Management & Data Systems 116(1):2-20. https://doi.org/10.1108/IMDS-09-2015-0382

  28. Hollebeek LD (2014) Demystifying customer brand engagement: Exploring the loyalty nexus. J Mark Manag 27(7–8):785–807. https://doi.org/10.1080/0267257X.2010.500132

    Article  Google Scholar 

  29. Hsu C, Cai LA (2019) Brand knowledge, trust and loyalty—a conceptual model of destination branding. International CHRIE Conference-Refereed Track. Paper 12. http://scholarworks.umass.edu/refereed/Sessions/Friday/1

  30. Joseph DL, Newman DA (2020) Emotional intelligence: an integrative meta analysis and cascading model. J Appl Psychol 95(1):54–78

    Google Scholar 

  31. Jin JH, Lee EJ (2019) The mediating effect of workplace spirituality on the relation between job stress and job satisfaction on cancer survivors returning to work. Int J Environ Res Public Health 16(19):1–13

    Google Scholar 

  32. Kidwell B, Hardesty DM, Murtha BR, Sheng S (2015) Emotional intelligence in marketing exchanges. J Mark 75(1):78–95

    Google Scholar 

  33. Kidwell B, McFarland RG, Avila RA (2017) Perceiving emotion in the buyer-seller interchange: the moderated impact on performance. J Personal Selling Sales Manag 27(2):119–132

    Google Scholar 

  34. Kirk BA, Schutte NS, Hine DW (2018) Development and preliminary validation of an emotional selfefficacy scale. Personality Individ Differ 45(5):432–436

    Google Scholar 

  35. Lambert EG, Hogan NL, Paoline EA, Baker DN (2017) The good life: the impact of job satisfaction and occupational stressors on correctional staff life satisfaction—an exploratory study. J Crim Just 28(2):1–26

    Google Scholar 

  36. Lee HJ (2018) How emotional intelligence relates to job satisfaction and burnout in public service jobs. Int Rev Adm Sci 84(4):729–745

    Google Scholar 

  37. Lee HJ (2019) What induces online loyalty? Online versus offline brand images. J Bus Res 62:557–564

    Google Scholar 

  38. Liu XY, Liu J (2023) effect of team leader emotional intelligence and team emotional climate on team member job satisfaction a cross-level. Nankai Bus Rev Int 4(3):180–198

    Google Scholar 

  39. Lopez SM, Extremera N, Luthans F (2014) Emotional intelligence and teacher burnout: a systematic review. Int J Educ Res 85:121–130

    Google Scholar 

  40. Masihabadi A, Rajaei A, Koloukhi AS, Parsian D (2015) Effects of stress on auditors’ organizational commitment, job satisfaction, and job performance. Int J Organ Leadersh 4(3):303–314

    Google Scholar 

  41. Matzler JD (2018) Target articles: emotional intelligence: theory, findings, and implications. Psychol Inq 15(3):197–215

    Google Scholar 

  42. Matzler K, Grabner-Kräuter, Bidmon S (2018) Risk aversion and brand loyalty: the mediating role of brand trust and brand effect. J Prod Brand Manag 17(3): 154–162

  43. Mayer JD, Salovey P (2017) What is emotional intelligence? In: Salovey P, Sluyter D (eds) Emotional development and emotional intelligence: educational implications. Basic Books, New York, pp 3–31

    Google Scholar 

  44. Mayer JD, Roberts RD, Barsade SG (2017) Human abilities. Emotional intelligence. Annual Review of Psychology 59:507–536. https://doi.org/10.1146/annurev.psych.59.103006.093646

  45. Mayer JD, Roberts A, Barsade G (2018) Emotional intelligence and the identification of emotion. Intelligence 22(2):89–113

    Google Scholar 

  46. McFarland RG, Rode J, Shervani TS (2016) A contingency model of emotional intelligence in professional selling. J Acad Mark Sci 44(1):108–118

    Google Scholar 

  47. Moore JE (2022) One road to turnover: an examination of work exhaustion in technology professionals. MIS Q 24(1):141–168

    Google Scholar 

  48. Patterson PG, Johnson LW, Spreng RA (2016) Modeling the determinants of customer satisfaction for business-to-business professional services. J Acad Mark Sci 25(1):4–17

    Google Scholar 

  49. Peters MR (2015) The impact of job stressors on job satisfaction as mediated by emotional intelligence and organizational citizenship behavior. Dissertations Doctor of Philosophy Southern Illinois University Carbondale, ProQuest Dissertations Publishing. 10194871

  50. Peterson RA (2022) Self-efficacy and personal selling: review and examination with an emphasis on sales performance. J Personal Selling Sales Manag 40(1):57–71

    Google Scholar 

  51. Prentice CD, Lopes S, Wang X (2022) Emotional intelligence or artificial intelligence—an employee perspective. J Hosp Market Manag 29(4):377–403

    Google Scholar 

  52. Ruestow JA (2018) The effect of a leader's emotional intelligence on follower job satisfaction and organizational commitment: An exploratory mixed methodology study of emotional intelligence in public human services. Dissertations Doctor of Philosophy Capella University, ProQuest Dissertations Publishing. 3330706

  53. Rust RT, Oliver RW (2022) Video dial tone: the new world of services marketing. J Serv Mark 8(3):5–16

    Google Scholar 

  54. Santos S, Tuškej U, Golob U, Podnar K (2015) The role of consumer-brand identification in building brand relationships. J Bus Res 66(1):53–59

    Google Scholar 

  55. Sahin A (2021) The effects of brand experiences, trust, and satisfaction on building brand loyalty; empirical research on global brands. Procedia Soc Behav Sci 24:1288–1301. https://doi.org/10.1016/j.sbspro.2011.09

    Article  Google Scholar 

  56. Sproles GB, Kendall EL (1986) A methodology for profiling consumer decision-making styles. J Consum Affairs 20:267–279

    Google Scholar 

  57. Stevens SL (2014) Issues and procedures in adopting structural equation modeling technique. J Appl Quant Methods 3(1):76–83

    Google Scholar 

  58. Sop F, Kozak V (2019) Does brand-consumer social sharing matter? A relational framework of customer engagement to brand-hosted social media. J Bus Res 85:175–184. https://doi.org/10.1016/j.jbusres.2017.12.050

    Article  Google Scholar 

  59. Sung Y, Kim J (2020) Effects of brand personality on brand trust and brand effect. Psychol Mark 27(7):639–661

    Google Scholar 

  60. Tabachnick BG, Fidell LS (2018) Using multivariate statistics, 6th ed. Allyn & Bacon/Pearson Education, Boston, MA

  61. Uysal HT (2019) The mediation role of toxic leadership in the effect of job stress on job satisfaction. Int J Bus 24(1):55–73

    Google Scholar 

  62. Verbeke W, Bagozzi RP (2022) Sales call anxiety: exploring what it means when fear rules a sales encounter. J Mark 64(3):88–101

    Google Scholar 

  63. Wisker ZL, Poulis A (2015) Emotional intelligence and sales performance. A myth or reality? Int J Bus Soc 16(2):185–200

    Google Scholar 

  64. Yin RK (2018) Case study research and applications: design and methods, 6th edn. Sage, Thousand Oaks, CA

    Google Scholar 

  65. Zeidner M, Matthews G, Roberts RD (2014) Emotional intelligence in the workplace: a critical review. Appl Psychol 53(3):371–399

    Google Scholar 

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Acknowledgements

The authors would like to acknowledge the support of the respondents from the Mall and owners of the malls in Ghana. We thank all the respondents who devoted time to fill and return the questionnaires sent to them.

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  1. Department of Marketing and Entrepreneurship, School of Business, University of Education, Winneba, Ghana

    George Kankam

  2. Department of Marketing, Procurement and Supply Chain Management, School of Business, University of Cape Coast, Cape Coast, Ghana

    Isaac Tetteh Charnor

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GK contributed 70% and ITC contributed 30%.

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Kankam, G., Charnor, I.T. Emotional intelligence and consumer decision-making styles: the mediating role of brand trust and brand loyalty. Futur Bus J 9, 57 (2023). https://doi.org/10.1186/s43093-023-00239-8

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