The Moderating Role of Mood on the Impact of Perceived Satisfaction on Online Product Evaluation ()
1. Introduction
It’s well established that one of the main objectives of companies’ existence is to gain more market share and make more profits. Customers’ satisfaction, especially for customer-oriented companies, is an important driver of firm profitability (Luo & Homburg, 2007) . Satisfied customers are more important to companies; not every customer will benefit the company the same. That is, those satisfied customers may become loyal customers and also will recommend the products to other customers, increasing the revenue and profits of the company.
Consumer researchers have long been studying motivations, perceptions, and attitudes regarding products and services to better understand and predict purchase decisions of consumers. Knowing the effect of these variables throughout the phases of decision-making could help marketers to stimuli motivations to favorable decisions. Research on the impact of affective states (such as mood) that are generated by consumption experiences is also important and has received the attention of researchers (e.g., Miniard, Bhatla, & Sirdeshmukh, 1992 ). This research stream has concentrated on the relationship between affective states, such as mood, and products evaluations. However, the moderating role of mood on perceived satisfaction is still vague. But why is this relationship important to be studied?
While understanding the customer’s mood state during product evaluation is important, it is also important to understand the effect of mood on enhancing or diminishing the impact of perceived satisfaction of other customers. That is, moods, although transient, can be pervasive, and may redirect perceptions and behaviour (Isen, 1984) . While mood states are generally beyond the control of marketing managers, many of them attempt to take careful considerations to factors that do not put customers in bad mood. For example, marketers may use humour to set consumers who see an ad or product evaluation in a good mood in order to foster a positive attitude toward the marketing stimuli. Additionally, moods can be influenced by service provider’s behavior such as a smile or an ambient service environment. Hence, customers’ moods can reflect how they feel during their encounters with the service provider and product evaluations.
2. Theoretical Background and Hypothesis Development
2.1. The Effect of Mood
Mood has been defined as a “low intensity and diffuse affective state” in which people might experience a sense of feeling that might be good, neutral or bad (Cohen, Pham, & Andrade, 2018) . Some researchers consider mood and emotions identical, but some differentiate between them. Whereas emotion is briefer, and a more intense affective response associated with specific stimuli, mood is milder, lasts longer, and has less salient causes (Clore, Gasper, & Garwin, 2001) . Additionally, Cohen and Areni (1991) suggest that emotions may disrupt ongoing activities, while mood may be present without the people being aware of their existence and their influence on their behaviors. Mood is of interest to us in the current research.
Mood can be induced by internal or external stimuli such as exposure to happy or sad news (Cohen, Pham, & Andrade, 2018) . An important aspect of mood state is that it is temporal in nature but has the ability to affect a person’s perspective and evaluation (Luomala & Laaksonen, 2000) . One explanation of this effect is that mood can lead to more or less involvement with what is been dealt with. Accordingly, because of higher involvement, mood might increase the accessibility of mood-congruent thoughts, therefore presenting bias on the evaluation (Petty, Gleicher, & Baker, 1991) . Consumer researchers have paid attention to the effect of mood on customers’ behavior.
The mood state of customers can lead to different effects on product evaluation. An excess of research has examined the role of mood states in the evaluation of customers of brands, ads, products and services (e.g., Munz & Munz, 1997; Miniard, Bhatla, & Sirdeshmukh, 1992; Knowles, Grove, & Burroughs, 1993 ). More specifically, the influence of mood on memory has been studied (Bagozzi, Gopinath, & Nyer, 1999) . A consumer in a positive mood state at the time of encoding can exhibit better recall of positive materials, relative to negative and neutral material. A positive mood might induce better elaboration, which might appear in the form of brand name recall, for example (Lee & Sternthal, 1999) .
The impact of mood on post-consumption product evaluations was also examined (Miniard, Bhatla, & Sirdeshmukh, 1992) . Mood has an influence on post-consumption attitudes toward brands. This effect is moderated by the intensity of the affect linked to consumption experience. Interestingly, the mood effect was absent when very strong positive or negative responses about the consumption was evoked. This means that attitudes toward brand were influenced by pre-consumption mood only when the experience was relatively neutral in affective intensity.
The effect of mood on the evaluation of advertisements and brands information was also examined (e.g., Knowles, Grove, & Burroughs, 1993 ). Knowles and colleagues (1993) have found that inducing people into positive moods can have significant effect on their recall memory. In their words: “delayed positive and negative mood states had opposite effects on memory-based recall of information, with subjects in the positive mood condition recalling significantly more information than those in the negative one” (Knowles, Grove, & Burroughs, 1993: 135) .
Mood states produce a direct impact on attitudes through a simple “affect association” process. When people are in a good mood, their evaluation of the subsequent materials can be affected by the positivity that is carried over from their mood state. For example, Goldberg and Gorn (1987) showed that the mood induced by positive or negative TV programs carries over to the affect experienced during commercials. The consumer’s mood can influence the attention process. A consumer in good mood is likely to pay extra attention to a message and hence use systematic processing (Wegener, Petty, & Smith, 1995) , that is, because customers associate their own happy mood with the message content.
If marketers and retailers try to induce positive or negative moods in consumers, it is important to understand that not all positive or negative mood states will influence evaluations and choice in the same way (Lerner & Keltner, 2001) . When consumers experience negative mood state, they tend to consume something that lighten their mood (Cohen, Pham, & Andrade, 2018) . Consequently, if marketers can build associations between products and what makes people feel happy, consumers with bad mood might be much more likely to purchase those products (Jansson-Boyd, 2019) . In addition, the mood that consumers are hoping to change can predict the activities they will be interested in. If an individual is experiencing anxiety, he/she is less likely to take part in something risky and might purchase something with high certainty of guaranteed benefits (Raghunathan & Pham, 1999) .
Research on mood effect on information processing has shown that positive mood activates heuristic processing whereas negative mood activates systematic processing (see Wen, 2021 for review). On one hand, the heuristic processing, associated with positive mood, leads people to perceive their environment to be benign and no problem is around. Put differently, focusing on positive states primes people’s thinking that their current situation is nonthreatening and requires no particular action. On the other hand, the systematic processing, associated with negative mood, leads people to perceive that there is a problem that needs to be rectified. Focusing on negative states informs people that there is a problem in the environment and a specific action is needed to mitigate this. With the current situation that many people use their phones when are in bad mood, the online reviews that customers post might be biased.
2.2. Online Reviews
Customers evaluate products based on different attributes. Not all attributes are of the same importance to customers. For example, perceived satisfaction of customers who already have purchased the product has an important impact on the evaluation. Additionally, customers use different mechanisms when evaluating a product. Not only rational factors affect product evaluation but also emotional ones. Consumers’ researchers have already established that product evaluation is an important indicator and predictor of different consequent behavior such as purchase intention and recommendation willingness (e.g., Goldberg & Gorn, 1987 ). Importantly, online advertising has an important effect on customers’ satisfaction (Nwokah & Ngirika, 2018) .
Customers get in touch with other customers’ reviews either face to face or online. Both of these communication methods play role in shaping customers’ way of judgement and decision making. Previous research has shown mixed results on the effect of word of mouth (WOM). For example, Herr, Kardes, & Kim (1991) show that WOM is effective only on informational level. That is, customers need to share information about the product in their WOM in order for the WOM to be effective. Howard & Gengler (2001) has suggested that emotions can be a central part of WOM. So, in order for the WOM to be effective, not only the informational part is important but also the emotional content.
Online reviews, or electronic WOM (eWOM), have, also, an important effect on customers evaluation. There are some differences between traditional face to face WOM and eWOM. One of the main differences is that nonverbal cues (e.g., facial expressions) can be presented in WOM but not in eWOM. Facial expressions are effective in conveying emotional states and facilitating the communication and message transition (Walther & D’Addario, 2001) . Nevertheless, in the online environment, the role of virtual facial expressions, such as emojis, as a way of product evaluation, can affect customers evaluations (Das, Wiener, & Kareklas, 2019) . In their research, Das and colleagues (2019) have examined the effect of including emoji in advertisements on consumers’ purchase intentions. They found that the presence of emoji leads consumers to experience higher positive affect, which in turn, leads to higher purchase intentions. Additionally, they found that there is a moderating effect of product type on this relationship, that is, emojis are only effective for promoting hedonic (vs. utilitarian) products.
In the online environment, customers who write online reviews, sometimes, express only feelings related to using a product, such as what they felt after buying the product or their opinions because of using the product (Kim & Gupta, 2012) . Additionally, the online review can be based on the story that a customer says about how a certain product has made his or her life better or worse. Overall, customers care about knowing the evaluation of other customers, face to face or virtually, before making a decision on a certain product. However, their evaluation might be transmitted or changed based on another factor, the emotions of the reviewer.
2.3. Emotional Contagion
Because of emotional contagion (Hatfield, Cacioppo, & Rapson, 1993) , people catch emotions of others (Small & Verrochi, 2009) . This process happens through two different mechanisms: mimicry and feedback reaction (Hatfield, Cacioppo, & Rapson, 1993; Howard & Gengler, 2001) . While mimicry induces a person (i.e., receiver) to adopt the behavior of the sender, feedback reaction is a result of the link between emotional experience and expression to lead to a physical reaction such as smiling, crying or cheering.
Emotional contagion is facilitated by several factors. For example, research on emotional contagion has established that the likelihood of emotional contagion and its intensity depend on the level of receivers’ susceptibility (Hatfield, Cacioppo, & Rapson, 1993) . People are more likely to mimic others’ emotions if they pay attention to them, have interpersonal ties and are able to read others emotional expressions (Lohmann, Pyka, & Zanger, 2017) .
Different ways facilitate emotional contagion in the e-commerce platforms. For example, emojis help in conveying the emotional state of the reviewer (Lohmann et al., 2017) . Owing to the effectiveness of emotions’ importance in marketing, many companies emphasize the emotional role in their marketing communication activities such as advertising (Stewart, Morris, & Grover, 2007) and customer service (Mattila & Enz, 2002) . Positive emotions might incentivize a certain customer to purchase. Also, that certain customer might post a positive review that will change another customer’s perceptions of a product, an e-commerce site or a brand. Emotional contagion’s interaction effect with mood is still, however, an understudied area.
2.4. Interaction Effect
The current study will shed light on the role of mood on evaluating the satisfaction effect of others on the evaluation of a product. In particular, if someone, in a good mood, reads a positive evaluation of another person, his good mood will amplify his evaluation of the product. On the other hand, someone with negative mood will lower his evaluation of a product if he reads a negative review of a product.
Understanding this important interaction effect has an important implication for marketers. For example, if the target group of customers would evaluate a product in a situation where it is predicted that they will be not in a good mood, marketers might take an action to mitigate the hindering impact of the negative mood. As a result, some measures or indications of the mood of evaluators and customers might be present to understand more the impact of mood on the evaluation is. Additionally, customers would be more informed if they knew that the customer who posted a specific review or evaluation was in a certain mood.
Overall, it is important to ensure that consumers are in a suitable mood when deciding what to consume. Otherwise, they may end up linking a particular product with negative mood and henceforth evaluate the product in a disapproving way. In general, this research predicts that:
H1: There is an interaction effect between perceived satisfaction and mood on product evaluation such that participants in good mood will evaluate the product higher when they read a review of a satisfied customer (Figure 1).
3. Method
200 participants (60.8% Males) were hired to answer an online questionnaire. Choosing this number of sample was because of two reasons. First, VanVoorhis & Morgan (2007) has indicated that having more that 30 observations per variable allows for detecting effects in regression analysis. In the current study, there are three variables (i.e., independent variable, a moderator and a dependent variable). 200 participants should be enough in detecting the effects. The second reason is the monetary constraints of the study since participants were paid for participating in the study. Participants were shown a picture of a review that a customer has written about a laptop and then were asked to answer some questions about the variables of the study.
The dependent measure, “My opinion of this laptop is”, had three elements (α =
**p < 0.01, ***p < 0.001.
0.967) on a 7 points semantic differential scale (1 = Very Bad/Very Negative/Very Unfavorable, 7 = Very Good/Very Positive/Very Favorable).
The independent measure is “How did the person who posted the review feel about buying this product?” The measure had two elements (α = 0.971) with a 7 points semantic differential scale (1 = Very Dissatisfied/Very Sad, 7 = Very Satisfied/Very Happy).
Then participants answered two elements (α = 0.899) of a current mood measure on a 7 points semantic differential scale (1 = Very Sad/Very Bad, 7 = Very Happy, Very Good).
4. Results
Table 1 presents the results. In step 1, the IVs’ effect on the DV was tested without adding the interaction term. As shown in Table 1 (step 1), mood and perceived satisfaction significantly predicted the purchase intention. These results, although not hypothesized, show that these two variables are significant predictors of purchase intention. The better the mood of the customer, the higher the probability that he/she will purchase. Same as for perceived satisfaction, the more the reviewer is satisfied, the higher the probability is for the purchase intention.
We tested the hypothesis using the moderated regression procedures. As shown in Table 1, adding the interaction term in step 2 shows that there is a significant interaction between mood and perceived satisfaction in predicting product evaluation (β = 0.598, p < 0.01; Step 2), supporting the hypothesis. These results suggest that when someone is in a good mood and reads a review of a satisfied customer, there will be a higher evaluation of the product.
5. Discussion
There is plethora of research on the role of mood and perceived satisfaction on product evaluation. This research was conducted to test the interaction effect of mood and perceived satisfaction in predicting the product evaluation in an online environment. Online reviews are an important driver for customers to make decisions online. However, the impact of the customer’s mood in understanding the effect of the review on purchase intention is not very clear. The current study meant to uncover this relationship.
Laptops are products that need more involvement and consumers perceive the purchase of a laptop a risky decision because of the complexity of the choice and high prices (Meents, 2009) . Marketing managers of laptops and similar products can find the current research impactful in terms of making sure that customers are in a good mood when purchasing such products. Specifically, marketing managers might offer discounts or monetary incentives for customers who are in the process to purchase a laptop online. This step might lead to better mood that would urge customers to finalize the purchase. Also, showing the best reviews of customers who already purchased a product online is important also in order to facilitate the purchase of the product. For those customers who are already in good mood, showing the best reviews helps to increase the probability of purchase. Also, for customers who are already in front of good reviews, trying to do an action that enhances the good mood would help to increase the probability of purchase.
Future research can conduct the current study on different products’ categories. For example, what types of products are better to be sold for customers in bad mood (if any). Additionally, what can marketers do to find out customers who are not in a good mood and trying to change their mood by shopping online. Those customers can be offered special discounts or incentives to urge them to buy. What actions can be done by marketers to reach to this objective and what is the impact of it.
Finally, the current research tried to shed light on a very important issue that is of help not only to entrepreneurs and small online business owners but also for large online stores to enhance their customer experiences. Customers and companies would like to find out what make them happy and profitable respectively. Finding important factors, even if minor, that help to achieve these goals would add value to e-commerce websites and also for the life of customers and people in general.