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Article

The Influence of the Big Five Personality Traits and Propensity to Trust on Online Review Behaviors: The Moderating Role of Gender

1
The WPI Business School, Worcester Polytechnic Institute, 100 Institute Road, Worcester, MA 01609, USA
2
Information Systems and Technology, Palumbo-Donahue School of Business, Duquesne University, 600 Forbes Avenue, Pittsburgh, PA 15282, USA
*
Author to whom correspondence should be addressed.
J. Theor. Appl. Electron. Commer. Res. 2024, 19(2), 1442-1470; https://doi.org/10.3390/jtaer19020072
Submission received: 3 March 2024 / Revised: 27 April 2024 / Accepted: 29 April 2024 / Published: 4 June 2024

Abstract

:
This study investigates the impacts of the Big Five personality traits and propensity to trust on the use and writing of online reviews. Additionally, this study examines how gender moderates these impacts. Results of a survey (n = 840) show that openness to experience and conscientiousness positively influence online review use, while openness to experience and extraversion positively influence online review writing. Moreover, gender moderates the impacts of extraversion, openness to experience, and agreeableness on online review writing, with no moderating effect observed for online review use. Our findings contribute to the electronic word-of-mouth (eWOM) literature and offer important practical insights for eWOM platforms.

1. Introduction

The fundamental principle of consumer behavior suggests that consumers can shape other consumers’ opinions and exert powerful influences on brands, products, and services [1,2,3,4]. User-generated online reviews of products and services are becoming increasingly important sources of information for shoppers and greatly influence purchase decisions and product sales [5,6,7,8]. The recent revolutionary technological improvements, the rise in new media channels, and the increasing number of internet users have provided a fecund ground and many opportunities for consumers to share their experiences through electronic word-of-mouth (eWOM) channels. Word-of-mouth is “informal communications directed at other consumers about the ownership, usage, or characteristics of particular goods and services and/or their seller” [9]. The digital form of word-of-mouth is easy to create and access by anyone and can direct potential consumers toward or away from specific products, brands, or services by sharing positive or negative experiences [10,11]. Thus, it is crucial to understand the nuances of user engagement in eWOM in terms of using and providing online reviews. The value of user-generated content lies in the notion that users read (use) and write (create) content, making the understanding of user engagement in eWOM crucial. Therefore, we specifically focus on using and writing online reviews as these two actions represent fundamental aspects of consumer behavior in sha** opinions and influencing purchasing decisions.
While prior studies have focused on understanding the behavioral aspects of online review use and writing, they exhibited shortcomings that this study aims to address. First, many eWOM studies were conducted between one and two decades ago, when online reviews had yet to become a significant source of information for purchasing decisions [10,12,13]. Second, prior studies have each conceptualized online review use and writing in a specific context, such as restaurants, books, travel experiences, and movies. It is important to conceptualize and examine these constructs as two individual characteristics defined as the extent to which one generally uses and writes reviews online. This aspect has been acknowledged as a drawback or shortfall in prior studies [14,15]. To address this crucial concern, we have undertaken a systematic approach in this study by develo** and validating two overarching constructs for online review use and online review writing.
Prior research has also noted that personality characteristics, such as the Big Five traits (i.e., extraversion, openness to experience, conscientiousness, neuroticism, and agreeableness) and propensity to trust (i.e., the general tendency to trust other people and things), can impact online review use and writing [15,16,17,18]. However, previous studies have either concentrated on specific contexts exclusively or measured online review behaviors as dichotomous variables. This approach may not adequately capture the full range of variations within these variables [14,17,19,20,21]. Moreover, prior research has predominantly emphasized motivations or intentions linked to the use and writing of online reviews, potentially failing to capture actual behaviors in practice. Manner and Lane [15] and Dixit et al. [21], along with other scholars, have drawn attention to these limitations in the existing literature. They have emphasized the need for utilizing more suitable measures and integrating online review behaviors across different products and services on various platforms into comprehensive scales. In this study, we address these concerns by measuring platform-independent online review use and writing across various goods and services as two overarching constructs. We then examine the influence of the Big Five traits and propensity to trust on these key constructs. We specifically focus on these personality characteristics because they have been identified as critical and influential factors in contexts involving knowledge utilization and sharing, including eWOM [18,22,23]. Thus, our findings make substantial theoretical contributions to the understanding of eWOM and user behaviors.
Previous studies have also looked at the impact of gender on online review generation intentions [14,15], but the moderating effect of gender on the relationships between personality traits and online review use and writing has largely been overlooked [16,17,21,24,25]. Females and males have different behaviors concerning online reviews; nonetheless, it is unclear how personality characteristics impact their tendencies toward reading and writing online reviews differently [26,27]. Understanding the moderating role of gender holds significant implications for online review platform providers and policymakers, in addition to making a substantial contribution to the literature on eWOM. Specifically, organizations that offer goods and services can enhance the user experience for online reviews by gaining a deeper understanding of the behavioral differences between female and male users in terms of their use and writing of online reviews. In this study, we investigate and explore this notion to provide valuable insights. In summary, we address the following research objectives:
(1)
Conceptualizing online review use and online review writing as two overarching eWoM constructs and systematically develo** scales to measure them;
(2)
Understanding the impacts of personality characteristics, including the Big Five factors and propensity to trust, on online review use and writing;
(3)
Understanding the moderating role of gender in the relationships between personality characteristics and online review use and writing.

2. Background

2.1. Using and Writing Online Reviews

The utilization of online reviews is closely linked to information-seeking behavior within the online environment. Several key factors have been identified as drivers for consumers actively seeking the opinions of others by reading their online reviews. The act of seeking others’ opinions has been found to support individuals in making well-informed decisions when contemplating purchasing or acquiring something new. Kotler and Keller [28] proposed a framework that conceptualizes customers’ purchase decisions as a five-stage process, which includes need recognition, information search, the evaluation of alternatives, purchase decision, and post-purchase evaluation. During the information search stage, potential customers turn to online reviews to gather information and assess various alternatives. The use of online reviews helps to reduce pre-purchase uncertainty and perceived risks, such as financial and social risks, particularly when dealing with complex products or services. Seeking the opinions of others through online reviews serves as a motivating factor in making informed decisions and mitigating uncertainties associated with acquiring something new [29,30]. In addition, studies have identified other motivations for using online reviews, such as entertainment [31], convenience, interpersonal utility, and leisure [32].
In a framework proposed by Kotler et al. [33], the authors further recognize the importance of online reviews and eWOM as crucial elements in the digital marketing landscape while integrating online and offline marketing efforts. This phenomenon, referred to as Marketing 4.0 by the authors, emphasizes the importance of two-way communication between companies and consumers and highlights that online reviews provide consumers with a platform to share their opinions, feedback, and experiences with brands, thereby facilitating dialogue and interaction. This customer-centric approach acknowledges that consumers seek authentic and relevant information from their peers when making purchasing decisions, and marketers need to leverage online reviews and eWOM to deliver personalized experiences that resonate with consumers.
The other side of the coin is providing opinions about products and services through writing online reviews. When consumers write online reviews, it involves sharing their knowledge or personal experiences by contributing original content on an online review platform. This can be a passive, one-time online review where they provide feedback or opinions on a product or service. Alternatively, consumers may actively participate in a community by consistently contributing to discussions, sharing insights, and providing ongoing reviews and recommendations. Both forms of engagement contribute to the collective knowledge and information available on online review platforms [34]. A significant body of literature has been devoted to understanding the motivations behind writing online reviews. Altruism towards other consumers or the seller of products/services has been identified as motivation in early studies and confirmed across various contexts [10,35,36]. Moreover, a wide range of personal benefits has been found to drive consumers to write online reviews. For instance, Peters et al. [37] highlighted the social value contributors expect from interacting with others. McGraw et al. [38] discovered that hedonic benefits, such as personal gratification, motivate online review writing behavior. Venting frustration and seeking retribution for negative experiences have also been identified as additional motivating factors for writing online reviews [10,39]. Nonetheless, a complete comprehension of how the personal characteristics of eWOM platform users impact their utilization and composition of online reviews is yet to be achieved. In this study, we focus on this gap.

2.2. Personality Traits

Personality traits are defined as “dimensions of individual differences in tendencies to show consistent patterns of thoughts, feelings, and actions” [40] (p. 25). Previous research has indicated that users’ beliefs, attitudes, and behaviors in the context of internet usage and online engagement can vary based on their personality traits [23]. Several personality models have examined the association between personality traits and using technology and social media for information-seeking or sharing. Among these models, the “Big Five” model has emerged as the dominant framework [41,42]. This model encompasses five traits: extraversion, agreeableness, conscientiousness, neuroticism, and openness to experience [40]. Accordingly, extraversion and agreeableness assess the strength and quality of individuals’ social interactions and connections. Conscientiousness measures impulse control, while neuroticism captures the tendency to experience negative emotions. Lastly, openness to experience reflects individuals’ inclination to seek out new and diverse experiences [43]. These traits build upon Eysenck’s [44] initial personality theory, which included three dimensions: extraversion, neuroticism, and psychoticism.
In a study conducted by Adrian Camilleri [20] regarding the role of personality traits in eWOM, it was discovered that extroversion and openness were positively linked to the use of online reviews among older males. On the contrary, neuroticism had a negative impact on this behavior. Bajcar et al. [45] and Hamburger et al. [46] also observed that individuals with neuroticism, who experience higher stress levels, were more likely to seek others’ opinions and use online reviews as a co** mechanism. Consequently, they were shown to rely on online reviews more than emotionally stable users. Adamopoulos et al. [47] employed machine learning techniques and an econometric analysis, revealing that introverted individuals were more responsive to eWOM, while agreeable and conscientious users were more effective in disseminating word-of-mouth information. The study by Halder et al. [48] found that all personality traits, except agreeableness, positively influenced information-seeking behavior. Additionally, extraversion and conscientiousness were identified as significant predictors of information needs.
Jani and Hanh [49] conducted a study that revealed how extraversion, agreeableness, and neuroticism impact customer satisfaction, hotel guest loyalty, and the intention to write online reviews. By integrating the expanded theory of planned behavior and the Big Five personality framework, Picazo-Vela et al. [50] discovered that neuroticism and conscientiousness are crucial factors in predicting an individual’s intention to write online reviews. In another study, Anastasiei et al. [51] examined the relationship between personality traits and intrinsic motivation to write online reviews about companies and products. They found that extraversion, agreeableness, and openness to experience were positively correlated with the willingness to write reviews, driven by the desire to assist the company and other consumers. Conversely, conscientiousness showed a negative association with the tendency to vent about negative shop** experiences. Individuals with neuroticism were more motivated to write online reviews for self-related benefits, such as social recognition. In a study by Manner and Lane [14], openness to new experiences and conscientiousness emerged as significant predictors of online review writing intention, while agreeableness was negatively correlated with the likelihood of writing reviews. Finally, Manner and Lane [15] found that individuals with high agreeableness scores were motivated by a desire to help others when writing online reviews. In contrast, those with high extraversion scores were driven by social interaction.
Previous studies have collectively provided insights into the relationship between the Big Five personality traits and online review behaviors, but they have primarily focused on specific contexts, leading to contradictory findings. Consequently, the broader impact of personality traits on using and writing online reviews across different product or service contexts has yet to be thoroughly examined. This study seeks to fill this research gap by investigating the influence of personality traits on online review behaviors in a context-independent setting.
In addition to the Big Five personality traits, another important personality characteristic that can affect both the use and writing of online reviews is the propensity to trust. Existing research has highlighted the role of trust in online interactions and its impact on review behaviors [25,52]. Therefore, this study also explores the influence of the propensity to trust in using and writing online reviews. By considering both personality traits and propensity to trust, this study aims to provide a comprehensive understanding of the factors that shape online review behaviors regardless of context.

2.3. Propensity to Trust

Human social behavior is fundamentally built on interpersonal trust, which also extends to virtual communities. In traditional communication, the trustworthiness of the information source significantly influences how receivers perceive and react to the message [53]. However, in the online space, the source of information is often less prominent, making it more challenging to establish objective trust in the sender. In this context, the individual’s propensity to trust becomes crucial. The propensity to trust is a personality trait that reflects an individual’s general inclination to trust others [54]. According to the rational choice model, individuals with higher scores on the propensity to trust scale are more likely to trust the advice or information provided by others, even with limited information about them [55,56]. These individuals willingly make themselves vulnerable and maintain an optimistic view of others [24,57,58]. However, as more information about the trustee and their previous behavior becomes available, the impact of the propensity to trust on the extent of vulnerability decreases [59].
Previous studies have provided evidence supporting the influence of the propensity to trust on various aspects of online review behavior. These studies have shown that individuals with a higher propensity to trust are more likely to adopt eWOM and perceive it as a credible source of information [60,61]. The perceived credibility of online reviews, in turn, influences users’ cognitive and affective trust and increases their likelihood of finding the reviews helpful [62]. Both cognitive and affective trust has also been found to impact information-seeking and sharing behaviors on social networking sites (SNSs) [63].
Wang and McCarthy [64] explored user responses to brand images based on positive and negative online reviews. They found that individuals with a higher propensity to trust are more likely to read online reviews and are mainly influenced by positive reviews. Shaheen et al. [25] highlighted that the propensity to trust not only affects the adoption of online reviews but also significantly influences customers’ engagement with review platforms. However, despite these findings, the direct impact of propensity to trust on the general use and writing of online reviews remains unexplored in the existing literature, which is a focus of our study.

2.4. Gender

Gender has indeed been identified as a factor that influences users’ engagement with online reviews. The social role theory, proposed by Eagly [65], provides a framework for understanding gender-specific behaviors in the online environment. According to this theory, gender differences and similarities primarily stem from the societal roles of females and males. The theory suggests that gender is shaped by sets of behaviors, expectations, and socially constructed learning processes that define gender-specific behaviors [66]. These normative expectations for behavior contribute to gender differences in actual behavior, which are also manifested in online contexts. For instance, Richard et al. [67] examined the influence of gender on website involvement and exploratory behavior, as well as the subsequent attitudes and pre-purchase evaluations. Their findings supported the common belief that males are generally less likely to engage in information-seeking behaviors and have lower involvement with websites than females.
Applying the selectivity model, Park et al. [27] demonstrated that female consumers tend to be comprehensive information processors and are more inclined to read online customer reviews and use assistant agents while shop** online. Conversely, males are often characterized as focused information processors who prioritize the specific product they need and may overlook other cues. Park et al. [27] also highlighted utilitarian and hedonic differences, where males view information-seeking as a necessary step in online shop**. In contrast, females enjoy purchasing-related information searches, including reading product reviews. Furthermore, Kim et al. [68] discovered that females are more likely to read online reviews for convenience, quality assessment, and risk reduction, while males’ utilization of online reviews depends on their expertise in the specific domain. These studies, among others, shed light on the gender-based variations in online behaviors, emphasizing the importance of considering gender as a significant factor when examining user engagement with online reviews.
Gender has also been identified as a moderator in various studies examining online environments. Chent [69] investigated the impact of perceived benefits of online shop** on the purchase intention in an online context and found that gender moderates this relationship. Moreover, their findings indicated that males with a high trust propensity were more focused on assessing the benefits of online shop** and it influenced their online behavior more significantly compared to female consumers, highlighting the joint moderating role of trust propensity and gender. Similarly, Mladenovic [70] explored the motives behind writing online reviews in the post-vacation phase and discovered that gender differences were present primarily in altruistic behavior. This finding aligns with previous research by Shelly and Narang [36], which demonstrated that females tend to exhibit a higher inclination towards altruistic behavior than males. Finally, Choi et al. [71] found that social norms have a more significant impact on knowledge-sharing behavior on SNSs among females than males. Drawing on the Social Exchange Theory and Theory of Reasoned Action, their results highlight the gender differences in the influence of social norms on knowledge-sharing.
However, the role of gender in the relationship between personality characteristics and the use and writing of online reviews remains largely unexplored. This study aims to fill this gap in the literature by examining how gender moderates the impact of personality traits and propensity to trust on online review behavior.

3. Hypotheses’ Development

3.1. Using Online Reviews (H1–H5)

3.1.1. Propensity to Trust

Early studies have provided evidence of the positive impact of the propensity to trust on trust formation in online economic transactions [72]. Additionally, research suggests that individuals with higher levels of propensity to trust are more likely to trust bloggers and the content they post on their blogs [73]. This willingness of trustors to make themselves vulnerable to the trustee in the early stages of trust formation is also relevant in the context of online reviews. Shaheen [25] found a positive relationship between the propensity to trust and the adoption of online reviews, while Lin [52] demonstrated that the propensity to trust positively influenced the perceived credibility of online reviews and the trustworthiness of the reviewers. We hypothesize the following:
H1. 
Propensity to trust is positively associated with using online reviews.

3.1.2. Extraversion

Extraverts are individuals who actively seek stimulation from external sources and engage in social and confident behaviors across various activities [74]. With the wide availability of the internet, extraverts have numerous opportunities to connect with others and gather information. Previous research suggests that extraversion is associated with a higher inclination for online exploration. The action-oriented nature of extraverts leads them to engage in online activities, exploring the digital environment [75]. Gil de Zúñiga H [76] also found that extraverts tend to utilize social media platforms more frequently and actively seek news online. This propensity to seek information and engage in online interactions aligns with the inherent drive of extraverts to be interactive and connect with social groups [77]. Extraverts are likely to be active participants in online platforms and seek social interactions online. Therefore, we hypothesize the following:
H2. 
Extraversion is positively associated with using online reviews.

3.1.3. Openness to Experience

Openness to experience is closely linked to individuals’ inclination towards learning, preference for diversity and novelty, and adaptability to change [78]. This personality trait is reflected in the tendency for novelty-seeking. As a result, individuals with high levels of openness to experience are more inclined to adopt new products, technologies, and procedures. Conversely, individuals with lower openness to experience, which signifies a more close-minded nature, tend to prefer adhering to conventional practices and established routines instead of embracing new ideas or change [40,79]. Research has revealed that individuals with higher levels of openness to new experiences are more likely to utilize the internet for various purposes, including entertainment, communication, reading and writing blogs, and engaging in social media activities [80,81]. This trait is also manifested in being curious and receptive to others’ opinions [82]. Being open to different perspectives and having an interest in online content encompassing ideological diversity implies that users who are open to new ideas and experiences are more likely to engage with online reviews consciously. They seek to make informed decisions based on others’ experiences, even when the writer is not within their trusted network [83]. Therefore, online reviews can fulfill their desire to learn from diverse information and draw conclusions accordingly. We hypothesize the following:
H3. 
Openness to experience is positively associated with using online reviews.

3.1.4. Conscientiousness

Conscientious individuals are characterized by their disciplined, diligent, and dependable nature. They are detail-oriented, have a proactive approach to planning, and demonstrate thoroughness and persistence in their tasks and achievements [78,84,85]. Additionally, they exhibit cooperative behavior and work well in collaboration with others. In contrast, individuals with low conscientiousness tend to be disorganized, indecisive, and prone to procrastination, which can hinder their ability to make well-informed decisions.
Recent studies have highlighted the information-seeking behavior of conscientious individuals, particularly when it can enhance their work performance or provide personal benefits [86,87]. Ahmed et al. [88] found that conscientious students were proactive in seeking information, positioning them as active “seekers of information” (p. 125). Halder at al. [48] demonstrated that conscientious students maintained focus, encountered fewer obstacles during their information-seeking process, and preferred to rely on higher-quality sources. El Othoman et al. [89] discovered that conscientious individuals made more rational and less intuitive decisions. They also exhibited a dependent decision-making style, seeking advice and guidance from others to support their decision-making process. Based on these findings, we argue that conscientious individuals are more likely to read online reviews as part of their effort to make educated decisions. They value information that can assist them in their decision-making process and proactively seek reliable sources to guide their choices. We hypothesize the following:
H4. 
Conscientiousness is positively associated with using online reviews.

3.1.5. Neuroticism

Neuroticism is characterized by a lack of psychological and emotional adjustment, stability, and resilience when faced with stress [90]. Individuals who score high in neuroticism tend to exhibit anxiety, insecurity, shyness, low self-esteem, and sensitivity to ridicule. They are also more vulnerable than those who score lower on this trait [91,92]. Neurotic individuals often struggle with co** with uncertainty and display an increased intolerance towards it [45,93]. To gain a sense of belonging and social support, neurotic individuals may spend more time online. Online platforms can provide them with opportunities to cope with stress and seek reassurance [45,94]. They may turn to online reviews and seek recommendations from others to mitigate the anxiety and stress associated with making purchase decisions [95]. Neurotic individuals may be more inclined to rely on online reviews to seek social support, gain reassurance, and manage the anxieties and uncertainties associated with decision-making. Therefore, we hypothesize:
H5. 
Neuroticism is positively associated with using online reviews.

3.2. Writing Online Reviews (H6–H10)

3.2.1. Extraversion

Extraverts highly value interpersonal relationships and actively seek opportunities to engage with others [96]. They are more inclined to share knowledge, experiences, and emotions with others, driven by their self-presentation and self-disclosure tendencies [97,98]. Sharing information and develo** social connections are enjoyable for extraverts, and as such, they actively seek social contact with others [80,94].
Manner [15] indicated that extraverted individuals are more likely to participate in and contribute to online communities, driven by their desire to support community cohesion. They also develop relationships and feel attached to online communities [99]. Extraverts, motivated by the pursuit of rewards and self-worth [32,100], engage in social interactions to share knowledge and experiences on websites and online social networks [15,98,101]. Yen and Tang [101] found that extraverts are more likely to share their experiences, particularly intense positive or negative ones, after staying in a hotel. This behavior is attributed to the extraverts’ subconscious desire to alleviate the psychological tension resulting from the significant experience. Furthermore, extraverts tend to report high self-efficacy, believing in their competence to share knowledge and experiences about products and services in online environments [15,98,102,103]. Accordingly, we hypothesize the following:
H6. 
Extraversion is positively associated with writing online reviews.

3.2.2. Openness to Experience

Individuals with high openness to experience have various interests and actively utilize technology for entertainment and information-seeking purposes [100,104]. They are more inclined to explore and adopt new methods of communication and are open to trying out unconventional experiences [105]. They exhibit curiosity and actively seek out information. They are motivated to explore diverse topics and develop broader, more in-depth expertise in online reviews. Furthermore, openness to experience is associated with cooperative and altruistic tendencies, positively correlated with knowledge-sharing intentions [82,98,106]. Individuals who score high in openness to experience are more inclined to share their experiences on SNSs, as Manner and Lane [14] demonstrated. Their cooperative and altruistic nature makes individuals with high openness to experience more willing to share knowledge and experiences with others. They are motivated by the desire to explore new ideas and contribute to the collective understanding and well-being of the community [12]. Therefore, we hypothesize the following:
H7. 
Openness to experience is positively associated with writing online reviews.

3.2.3. Conscientiousness

Early literature has recognized highly conscientious individuals’ inclination to share knowledge in offline and online contexts [98,107]. These individuals are motivated by two key factors when participating in online activities and discussion boards, writing blogs, or leaving online reviews. First, they are driven by a sense of altruism and a strong belief in sharing knowledge, which aligns with their cooperative and dependable nature [12,108,109]. Second, they value thoroughness in their online reviews, considering it an essential aspect of completing the online transaction. As a result, conscientious individuals who score high on the trait scale of conscientiousness are more likely to engage in online knowledge-sharing and review writing [50]. Their attention to detail, organization, responsibility, and reliability are reflected in their messages [74]. Thus, due to the voluntary nature of online review writing, they are more likely to be written by detail-oriented individuals who score higher on the conscientiousness trait scale. Kaufman et al. [110] suggest that highly conscientious users’ eWOM tends to be more effective, as receivers perceive their messages as more valuable. This may be attributed to the trustworthiness and credibility associated with conscientious individuals’ communication styles. Thus, we hypothesize the following:
H8. 
Conscientiousness is positively associated with writing online reviews.

3.2.4. Neuroticism

Individuals with neuroticism often experience insecurity, shyness, distrust, low self-esteem, difficulty managing stress, and heightened sensitivity to criticism or ridicule [97]. Even though individuals with neuroticism may have strong identification with the collective, their lower emotional stability hinders their desire to share their knowledge [15]. Individuals with neuroticism may feel less emotionally stable and may be more hesitant to engage in activities, such as writing online reviews that expose their thoughts and opinions to strangers [14]. The fear of judgment and potentially negative feedback from others can be particularly daunting for individuals with neuroticism, which can decrease their intention to share knowledge and contribute to online reviews [50]. Additionally, the presence of businesses actively monitoring and potentially intimidating customers from posting negative reviews can further discourage individuals with neuroticism from engaging in online review writing [111]. Therefore, we hypothesize the following:
H9. 
Neuroticism is negatively associated with writing online reviews.

3.2.5. Agreeableness

Individuals who score high in agreeableness possess traits such as friendliness, sympathy, helpfulness, trust, altruism, cooperation, modesty, and straightforwardness. These agreeable individuals have a natural inclination to avoid conflict in social interactions and actively provide support to enhance the well-being of others [112]. The cooperative nature of agreeable individuals suggests that they are more inclined to share knowledge about goods or services in online and face-to-face contexts to assist others in making more informed choices [82,98,99,113]. In contrast, individuals who score lower on agreeableness tend to prioritize their interests when using the internet and technology, engaging in activities such as customizing their phones, or participating in entertainment activities like playing games. Their focus is less on providing support to others and more on self-gratification [79]. Given the prosocial and cooperative behaviors exhibited by agreeable individuals, including their involvement in volunteering activities, it can be inferred that they are more likely to engage in posting online reviews to assist others in making informed decisions [82,97,98,99]. Accordingly, we hypothesize the following:
H10. 
Agreeableness is positively associated with writing online reviews.

3.3. Moderating Effects of Gender

Gender differences have been extensively studied in various fields, examining their impact on cognitive performance, social behavior, and psychological well-being [114,115,116]. These studies have highlighted significant personality traits and social behavior variations between males and females. Characteristics such as impulsivity, emotions, anxiety, interests, helpfulness, communication, and leadership have been found to differ between genders [100,116,117,118].
The differences in information-seeking and knowledge-sharing behaviors between males and females are apparent in offline interpersonal settings and online environments [26]. These gender differences also extend to the reading and writing of online reviews, as these behaviors reflect individuals’ personality traits and social behaviors in eWOM environments. Considering these observations, we propose that gender can moderate the relationships hypothesized in previous sections (H1–H10). In other words, gender may influence the strength or direction of these relationships, emphasizing the need to examine the role of gender in understanding the dynamics of online review use and writing.

3.3.1. Using Online Reviews (H11a–H11e)

3.3.1.1. Gender × Propensity to Trust

Individuals with a high propensity to trust are generally more willing to trust others, even with limited information about their trustworthiness. Gender differences in trust-related behaviors have been observed in various experimental settings. For instance, studies using the investment or dictator game, such as the one designed by Berg et al. [119], have shown that females tend to have lower expectations from unknown trustees than males do [120]. This finding, coupled with the general tendency of females to exhibit higher risk aversion, suggests that females may not expect as much valuable input from strangers as males do [121,122].
Research also indicates that males tend to be more comfortable taking risks and making decisions based on a rational choice model, prioritizing maximum benefits even if it involves higher risks [55]. On the other hand, females tend to prefer knowing the characteristics of the trustee and processing information more thoroughly before making decisions to mitigate risks [123]. In the context of online reviews, this suggests that females may be less influenced by their overall level of trust in online reviews. Even if they trust online reviews, the anonymity of reviewers may make females less inclined to rely on them for decision making. We hypothesize the following:
H11a. 
The relationship between propensity to trust and online review use is stronger for males.

3.3.1.2. Gender × Extraversion

Extraverts are socially active and seek stimulation from others. They have a higher sense of control over stress [124]. Males’ more resilient psychological response and sense of control suggest that they are more likely to rely on their self-efficacy and experience when needing information, and they feel that they are in control of the environment [20,125]. Gender difference has been found in assertiveness as a related measure of extraversion, further suggesting that males desire agency and dominance [116,126]. Thus, males are less inclined to be persuaded but prefer to be persuasive. In other words, compared with females, males are less likely to be influenced by their extraversion when using online reviews. We hypothesize the following:
H11b. 
The relationship between extraversion and online review use is stronger for females.

3.3.1.3. Gender × Openness

Individuals characterized by openness to experience are known to be creative, imaginative, and appreciative of new experiences and opportunities to exhibit creativity. Several emotion-based facets of openness to experiences, such as feelings, fantasy, sensations, aesthetics, and values, have been used to measure this trait [92]. Females have been found to exhibit the expression and attribution of most areas of emotional functioning, including nonverbal sensitivity and expressiveness [127]. Accordingly, we argue that compared with males, females tend to exhibit greater emotional expression and sensitivity and are more likely to be influenced by their openness to experience when using online reviews. We hypothesize the following:
H11c. 
The relationship between openness and online review use is stronger for females.

3.3.1.4. Gender × Conscientiousness

Conscientious individuals are hardworking, determined, and persevering in tasks [74]. Collecting relevant information through careful planning and develo** strategies to support educated decisions is a common characteristic of conscientious people [92]. The strong self-control exhibited by conscientious individuals drives them to prioritize the execution of their planned strategies over personal interests. Conscientious females may experience higher anxiety levels when their decision-making process lacks proper planning [128,129]. Therefore, we argue that conscientiousness has a more intense effect on online review use among females and we hypothesize the following:
H11d. 
The relationship between conscientiousness and online review use is stronger for females.

3.3.1.5. Gender × Neuroticism

Navigating multiple online platforms and selecting reliable sources can be challenging and discomforting for individuals with neuroticism. Individuals with neuroticism may experience confusion and adverse emotional reactions when trying to identify helpful reviews written by strangers and assess the credibility of the sources [130]. Research suggests that females with low scores on neurotic scales are more prone to develo** self-destructive addictions, and the impact of hardship on low self-esteem is more pronounced among females [131]. Females tend to avoid situations that trigger negative emotions, especially when reviews contain discrete emotions such as anxiety and anger [132]. Given that the impact of negative emotions is greater for females with neuroticism compared to males with neuroticism, we hypothesize the following:
H11e. 
The relationship between neuroticism and online review use is stronger for females.

3.3.2. Writing Online Reviews (H12a–H12e)

3.3.2.1. Gender × Extraversion

Extraversion has a greater impact on the well-being of males compared to females. Males with higher levels of extraversion experience increased self-esteem and self-efficacy and a stronger sense of ego. They are also more inclined to share their experiences and actively seek feedback from others. [133,134]. On the other hand, extraverted females are more oriented toward interpersonal relationships in interaction than sharing experiences without receiving feedback online. Extraverted males desire a sense of control and think of themselves as dominant [20,125]. As a result, males are more motivated to validate their ego and establish new relationships through knowledge-sharing, while females tend to focus on maintaining existing relationships. As such, we argue that extraversion has a more pronounced effect on the likelihood of males writing online reviews compared to females. We hypothesize the following:
H12a. 
The relationship between extraversion and online review writing is stronger for males.

3.3.2.2. Gender × Openness

Females, often characterized by their artistic and aesthetic predisposition, exhibit higher openness to experience. They are creative, imaginative, and appreciative of new experiences and creative opportunities [11]. Reis [135] found that females demonstrate creativity in various aspects of their lives, including relationships, family and home-related work, aesthetics, and personal interests. They are also known for their compassion, helpfulness, and emotional sensitivity. As a result, females are more inclined to engage in online support groups and share their experiences to foster a sense of community and empower others in gender-specific topics and common areas like travel and product reviews [136,137]. Considering their ability to generate ideas from sensory information and their emotional sensitivity, we argue that the impact of openness to experience on writing online reviews is more pronounced among females than males. We hypothesize the following:
H12b. 
The relationship between openness and online review writing is stronger for females.

3.3.2.3. Gender × Conscientiousness

The achievement-oriented nature of conscientious individuals is reflected in their adherence to plans and goal-oriented behavior. Female students who score high on conscientiousness exhibit higher attendance levels and better academic and job performance [138,139]. Females also engage in knowledge-sharing online, driven by their altruistic tendencies [140]. For conscientious individuals, writing online reviews is considered an integral part of the overall experience, and omitting this step can lead to anxiety [50]. This anxiety is likely more pronounced in females, indicating that they are more inclined to complete transactions by providing online reviews. In other words, females are more influenced by their anxiety towards writing online reviews. Therefore, we argue that conscientiousness has a stronger impact on the likelihood of females writing online reviews than males. We hypothesize the following:
H12c. 
The relationship between conscientiousness and online review writing is stronger for females.

3.3.2.4. Gender × Neuroticism

Neurotic individuals typically have lower levels of self-esteem and perceived self-efficacy [141]. Females, on average, tend to score higher on anxiety and low self-esteem than males [142]. Guadagno et al. [143] found that emotional stability has a stronger negative impact on perceived self-efficacy for females than for males. Additionally, females generally have lower trust in others, which, combined with their low self-esteem and higher risk aversion, leads to a reluctance to share knowledge through online reviews [144]. The emotional reactions associated with neuroticism are more likely to influence females’ willing-ness to share their knowledge than neurotic males. Therefore, we propose that neuroticism has a more pronounced effect on the likelihood of females writing online reviews than males. We hypothesize:
H12d. 
The relationship between neuroticism and online review writing is stronger for females.

3.3.2.5. Gender × Agreeableness

Females are often described as more agreeable and nurturing due to sociocultural influences and gender stereotypes [65]. This leads to differences in online behavior, with agreeable females focusing on relationship maintenance and having more online connections than males [145,146]. In contrast, agreeable males are less likely to post information online [147]. Given that females exhibit a stronger sense of belonging, emotional sensitivity, and compassion and have higher online presence and loyalty, we argue that agreeableness has a stronger impact on writing online reviews among females than among males [148]. We hypothesize the following:
H12e. 
The relationship between agreeableness and online review writing is stronger for females.
The research model is provided in Figure 1.

4. Method

4.1. Instrument Development

This study follows a survey approach. We designed a survey instrument to measure the constructs. The measurement items for the independent variables, including the personality traits and trust propensity, were adapted from the extant literature. To measure the dependent variables, namely online review use and online review writing, we developed two measurement scales and validated the scales through a well-established scale development process that has been used in prior studies [149]. First, we prepared an initial set of items based on the relevant literature to measure the two constructs. Then, we assessed the content validity of the items by conducting two focus group sessions at a university in the northeast United States. The sessions involved two PhD students, two master’s students, a faculty member, and the principal investigator of this study. The participants in those sessions were users of online reviewers and were familiar with the context of this study. Additionally, the faculty member and PhD students had prior experience in conducting research related to SNSs and users’ online behaviors. In each session, the measurement items were discussed, reworded, consolidated, or removed to make sure the items represented the focal constructs properly. We iteratively conducted this process until a consensus was achieved on the appropriateness of the scales. Table 1 presents the final set of measurement items for the two constructs.
Next, we pilot-tested the scales using a sample of students at a university in the northeast United States to assess the construct validity of the scales. In total, 109 usable responses were collected. We conducted a Principal Component Analysis (PCA) with Varimax rotation in SPSS 28. As expected, two components were extracted, explaining 76.71% of the variance in the eight measurement items (Table 1). Each item loaded significantly on its corresponding construct, with all loadings greater than the threshold of 0.7, as suggested the literature [150], assuring the convergent and discriminant validity of the scales for the two constructs. Finally, we assessed the reliability of the scales using Cronbach’s alpha coefficients. The results showed that both scales were adequately reliable (Cronbach’s alpha > 0.7). Hence, the psychometric properties of the scales for online review use and online review writing were assured. The full instrument, including the measurement items for the eight constructs, is presented in Appendix A (Table A1).

4.2. Data Collection (Main Study)

To test the hypotheses, we collected data from Amazon Mechanical Turk (MTurk) using CloudResearch MTurk Toolkit [151]. MTurk is an online crowdsourcing platform for data collection that is effective in gathering representative and valid datasets [152,153]. We implemented several attention check questions and data quality functionalities provided by the CloudResearch toolkit to automatically exclude careless respondents [154,155]. To minimize the potential effect of social desirability, anonymity was ensured for all participants. Informed consent to participate was provided at the beginning of the survey, which participants had to accept in order to proceed with the survey. Furthermore, the participants were informed that there was no single correct answer to each survey question, and they were asked to answer the questions as honestly as possible. For this study, respondents had to be at least 18 years old and a resident of the United States. As a result, we collected and analyzed 840 completed surveys. The age of the respondents ranged from 18 to 75 years old, with an average age of approximately 36 years old (Std = 11.64). About 34% of the respondents were male. Regarding education, 20.5% of the respondents possessed a graduate degree, 39.3% had a bachelor’s degree, 15.1% had an associate degree, 24.3% were high school graduates, and 0.8% had not completed high school.
The study materials, including the data collection procedure and survey questionnaire, underwent review by the Institutional Review Board (IRB) at the first author’s institution and were determined to be exempt from further IRB review.

5. Analysis and Results

5.1. Measurement Validity and Reliability

In order to assess the construct validity of the measures, we conducted a PCA with Varimax rotation in SPSS 28. As expected, eight factors were extracted, explaining 76.34% of the variance in the items. The results demonstrated that all the items loaded on their focal constructs (loadings > 0.7), with the exception of one of the conscientiousness items (CON2), which was removed from the final factor structure presented in Appendix A (Table A2). Also, the loading of one of the agreeableness items (AGR2) was 0.698, which was very close to 0.7; thus, we decided to keep that item in the factor structure.
Next, we calculated the inter-construct correlations, as well as average variance extracted (AVE) and its square root for each construct. As presented in Appendix A (Table A3), the square roots of AVEs are all greater than 0.5, which suggest that each construct explains at least 50% of the variance in the corresponding items [156,157]. Furthermore, the square root of AVE for each construct is greater than the correlation between that construct and all other constructs. Therefore, both discriminant validity and convergent validity were ensured and our measures were shown to be psychometrically appropriate. We also used Cronbach’s alpha coefficients and composite reliability scores to examine the reliability of the measurement scales. The results showed that the reliability scores exceeded the threshold of 0.7 [150], indicating that the scales are adequately reliable (Table A3). The only exception was agreeableness with Cronbach’s alpha = 0.655. Nonetheless, because the composite reliability score for that scale was 0.722 and the three items measuring agreeableness were theoretically relevant and extensively validated in prior studies, and given that removing each of the three items did not significantly improve the scale’s reliability, we decided to retain all those items to measure that construct.
To examine and address the potential issue of common method bias, we conducted Harman’s single-factor test by loading all the measurement items into an unrotated factor to “determine whether the majority of the variance can be explained by one general factor” [158]. The results showed that a single factor would explain only 20.54% of the variance in the measurement items, suggesting that common method bias was not likely an issue in the dataset.

5.2. Hypothesis Testing

To test the hypotheses, we conducted two separate hierarchical linear regression models, each focusing on one of the two dependent variables (Table 2). The first model (i.e., Model 1) focused on online review use and intended to test the main and moderating effects corresponding to H1–H5 and H11a–H11e. As presented in Table 2 the hierarchical process involved entering the variables into the model in three steps. In the first step (i.e., Model 1a), only the control variables, including age, gender, and education, were used as predictor variables. We found that females and younger respondents were significantly more likely to use online reviews, whereas education did not show a significant relationship with online review use. In the second step (i.e., Model 1b), the five personality variables were added to the model as predictors. The results showed that openness and conscientiousness positively influenced online review use, supporting H3 and H4. However, propensity to trust, extraversion, and neuroticism were not significantly associated with online review use, suggesting that H1, H2, and H5 were not supported. In the third step (i.e., Model 1c), the interaction terms were added to the model to test the moderating effects of gender on the relationships between personality characteristics and online review use. Our results showed that the F-value of the model did not change significantly at a p-value < 0.05 between Model 1b and Model 1c, indicating that overall, gender did not have a significant moderating impact on the relationships between personality characteristics and online review use. Consistent with this result, none of the coefficients associated with the moderating effects of gender in Model 1c were statistically significant at a p-value < 0.05. Thus, H11a–H11e were not supported.
We conducted a similar hierarchical multiple regression model with online review writing as a dependent variable (i.e., Model 2) to test the main and moderating effects of the variables associated with H6–H10 and H12a–H12e. As presented in Table 3, the results of the first step (i.e., Model 2a) showed no significant relationships between the control variables, namely gender, age, and education, and online review writing. The results of the second step (i.e., Model 2b) demonstrated that extraversion and openness positively influenced online review writing, supporting H6 and H7. However, the hypothesized effects of conscientiousness (H8), neuroticism (H9), and agreeableness (H10) were not supported. The results of the third step (i.e., Model 2c) indicated that gender moderated the impacts of extraversion, openness, and agreeableness on online review writing, whereas gender did not moderate the effects of the other two personality traits, namely conscientiousness and neuroticism, on online review writing. More specifically, we found that the positive effect of extraversion on online review writing was stronger for males than females. Openness showed a significant and positive impact on online review writing for females but not for males. Moreover, while agreeableness significantly and positively influenced online review writing for males, this effect was not significant for females. These moderating effects were also plotted using an interaction software package as presented in Figure 2, Figure 3 and Figure 4. In summary, H12a, H12b, and H12e were supported, whereas H12c and H12d were not supported.
Finally, we calculated and used variance inflation factors (VIFs) to examine the potential issue of multicollinearity between variables in Model 1 and Model 2. We found that none of the VIFs were greater than the threshold of 10 [159], indicating that no significant multicollinearity existed in the models.

6. Theoretical Contributions

The literature on online review use and writing is fragmented across different dimensions, such as cognitive, emotional, and behavioral aspects [160,161,162]. Prior studies have identified personality traits as important factors influencing the motivation to use or write online reviews in specific contexts [10,163]. However, there is a need to conceptualize and examine these constructs as distinct characteristics related to the general extent of online review use and writing [14,15]. This study fills this gap by develo** comprehensive constructs and measurement scales for online review use and writing. Additionally, in this study, we empirically investigated the role of the Big Five personality traits and propensity to trust in online review use and writing.
The findings reveal that the propensity to trust does not significantly impact online review use, contrasting with previous studies suggesting a positive influence. Shaheen et al. [25] and Thakur [162] found that propensity to trust positively influences the adoption of e-commerce reviews as well as customer engagement with certain e-commerce websites and on specific mobile device platforms. Therefore, our study showed that when we examine the effects of propensity to trust on online review use as a general construct, propensity to trust does not significantly impact online review use. Our findings also revealed that while extraversion increases online review writing, consistent with prior research, it had no impact on online review use [15,103]. Rollero et al. [77] and Gil de Zúñiga [76] found that information-seeking, especially on SNSs, is positively impacted by extraversion, whereas Camilleri [20] found that extraversion increases the frequency of online review use in a shop** decision-making context. This suggests that while extraverts engage in online reviews and seek information in specific contexts, their attraction to online reviews may vary depending on the setting, such as products, services, or social media.
Similarly, conscientiousness influenced online review use, supporting prior research. However, conscientiousness did not play a significant role in online review writing, unlike previous studies, emphasizing its motivational effect. Our results are in contrast to those of Picazo-Vela et al. [50] who measured intention to write online reviews and Yoo and Gretzel [109] who showed that conscientious individuals are motivated to write online reviews in travel-related media. Two plausible explanations for the non-significant effect of conscientiousness in our study are (1) the context-free measurement of actual online review writing behavior and (2) the tendency of conscientious individuals to prioritize tasks over interpersonal relationships, perceiving writing online reviews as unproductive [88,89].
Furthermore, this study diverges from the existing literature by finding that individuals with neuroticism, who typically exhibit emotional instability and intolerance for uncertainty, are less likely to write online reviews. This contradicts previous findings suggesting a higher likelihood of health-related information-seeking and venting negative experiences through online reviews among individuals with neuroticism [50,93]. Our results are different and a plausible explanation may be that individuals with neuroticism may spend more time online for specific topics to seek information and social support, leading to a focus on venting negative experiences in their online reviews [14,45,50,95].
Regarding agreeableness, a trait associated with cooperation and belongingness, previous studies have shown its positive impact on information sharing and self-expression in social media. However, this study revealed that agreeableness did not significantly influence online review writing in a context-free setting, suggesting that agreeable individuals may not necessarily share their experiences across all situations and domains [97,164,165].
Overall, this study highlights the significantly positive effects of openness, conscientiousness, and extraversion on online review use, supporting existing research and underscoring the importance of fulfilling information needs and seeking social approval and acceptance. These personality traits are associated with a tendency to interact, share, and seek validation offline and online, making online review use and writing a suitable medium for building relationships and expressing opinions. The findings contribute to the current understanding of the impact of the Big Five personality traits on consumers’ online behavior.
Additionally, our findings enhance the understanding of gender differences in online review use and writing. While the previous literature has primarily focused on the direct impact of gender, this study explored the moderating role of gender in the relationships between personality traits and online review behaviors [14,15,17,166]. The results indicated a distinction between females and males in their tendencies toward writing online reviews, particularly among those with higher levels of extraversion, openness, and agreeableness. The literature suggests that extraverted females prefer interpersonal relationships, while extraverted males tend to share information online to assert dominance and challenge others [134,167,168]. This study confirmed that extraversion has a stronger effect on writing reviews for males than females, potentially due to males being more influenced by their egos and experiencing higher subjective well-being through leaving online reviews [169]. Moreover, openness to experience has a greater impact on online review writing for females than males, which is consistent with previous research indicating females’ compassion, participation in online support groups, and empowerment of others in health- or travel-related topics [136,137]. Contrary to previous research, this study showed that agreeableness has a stronger impact on online review writing for males than females. The changing boundaries of traditional gender roles and fluid social norms may have influenced males’ cooperative behaviors, making agreeableness more significant [145,146,148]. Thus, this study provides a contemporary perspective on the differential impacts of agreeableness on the willingness to write online reviews between male and female users. Notably, while gender directly impacts online review use, it does not significantly moderate the relationship between personality characteristics, including the propensity to trust, and online review use. This suggests that personality characteristics exert a similar influence on both males’ and females’ tendencies to read online reviews [116].
Our study collectively offers a comprehensive and contemporary view on online review use and writing and suggests that gender’s direct effect does not automatically translate to a moderating effect between the personality traits and online review use and writing. The importance of this research is that it is the first to empirically validate the connections between personality traits and online review outcomes in a general context, considering the moderating role of gender. This study fills a crucial gap in the literature and contributes to a deeper understanding of how personality traits and gender intersect with online review behaviors.

7. Practical Implications

This study offers practical insights for online review platforms, suggesting how platform providers can leverage users’ personality traits to enhance engagement in online review use and writing.
For users high in openness, platform providers can capitalize on their willingness to write and use online reviews, particularly among females. For example, gamification techniques can make the review process more enjoyable and entertaining for open users. This approach can include interactive elements and novel approaches that bring a fun and engaging twist to the traditional online review experience. Such strategies can be especially effective for products and services targeted toward females.
To engage extravert users, platform providers can offer opportunities to earn statuses or badges based on their reviews and allow readers to rate specific aspects of the reviews. These interactive features align with the competitive and socially oriented characteristics of extraverts. Allowing comments on reviews and enabling reviewers to respond can mimic the social interaction preferred by extraverts. It is recommended to focus on providing interactive reviews for products and services more likely to be used or purchased by male users, as their review writing tends to be more influenced by extraversion.
The positive relationship between conscientiousness and online review use suggests that conscientious customers carefully consider others’ insights before making purchasing decisions. Customizable displays of review scores in a structured, dashboard-like format can benefit conscientious users. Although our study found that conscientiousness did not significantly influence online review writing, encouraging conscientious customers to leave reviews by emphasizing that reviews are part of the overall shop** experience could be beneficial. Including reminders at the checkout stage can also tap into their organized and task-oriented personalities.
Highly agreeable users, particularly males, seek acceptance from others and appreciate opportunities to share detailed experiences. As such, platform providers can enhance engagement for highly agreeable users, especially males, by enabling them to respond to questions related to their reviews or the products and services they reviewed, thereby fulfilling their desire for acceptance and helpfulness. Notifications for relevant questions can also prompt them to provide direct answers and feel more engaged in their reviews.
In summary, the results of our study and the suggested practical implications provide an opportunity for user experience designers and platform providers to better meet the unique preferences of users based on their personality traits. By tailoring platform features to accommodate diverse user preferences and communication styles, companies can promote fairness and accessibility in online review platforms and enhance trust and integrity within the review ecosystem. From a highly structured, dashboard-like overview of existing reviews to an innovative gamified online review writing experience can greatly amplify the value online reviews can provide to both customers and brands.

8. Limitations and Future Research

This study has a few limitations. First, our sample was recruited through MTurk, which may introduce certain biases and limit the generalizability of our findings. Although we implemented various quality assurance measures [151], such as attention check questions and randomization techniques, the use of an MTurk sample might introduce biases and limit the generalizability of our findings. Future research should aim to replicate our study using diverse samples from different sources to validate and potentially extend our results. Using samples outside of the US can also extend the generalizability and reliability of our findings. Second, relying on self-reported responses can be subject to response biases, potentially inflating the observed correlations between the variables under investigation [170]. Future studies could consider using more indirect measures and techniques to assess personality traits, reducing the potential impact of self-report biases on the results. Furthermore, examining variations in customer experiences, such as differentiating between reviews for higher-end and lower-end products or services, could offer valuable insights into online review behaviors. Additionally, considering situational factors, such as the occasion of the reviewed product/service (e.g., personal use, business use, gift) and the frequency of purchase/use (first-time, one-time, repeated), could further enhance our understanding of the phenomenon. Moreover, future research could explore how specific platform characteristics appeal to individuals with different personality traits. With the rise in influencer-promoted goods and services, examining how personality traits influence user preferences regarding different types of reviews would be beneficial, considering the blurred line between paid promotions and unbiased product reviews. Furthermore, as online platforms and social media continue to evolve rapidly, future research could explore the impact of emerging technologies, such as AI recommendation and generative AI tools, on the relationship between personality traits, gender, and online review behavior. Investigating how AI algorithms influence the perception and interpretation of online reviews based on user characteristics could provide valuable insights into the changing dynamics of eWOM. Finally, our study focused solely on personality traits, gender, and behavioral outcomes, neglecting cognitive, emotional, and affective aspects of online review use and writing [171]. Future studies could incorporate these dimensions to provide a more comprehensive understanding of the topic.

9. Conclusions

This study made significant contributions to the online review domain by develo** and validating two overarching constructs for online review use and writing, which can be applied across different contexts and platforms. Through empirical measurements, we examined the influence of the Big Five personality traits and propensity to trust on these online review behaviors. Additionally, we explored how gender moderates the relationships between personality traits and online review writing. Our findings emphasize the significance of considering consumers’ personality traits, as they substantially impact their engagement in online review use and writing. Furthermore, we found that gender plays an influential role in sha** the relationships between extraversion, openness, agreeableness, and online review writing. By considering these factors, businesses and online platforms can better engage users and optimize their online review experiences, ultimately enhancing the value and impact of online reviews in decision-making processes and outcomes.

Author Contributions

All individuals who meet authorship criteria are listed as authors in this paper. Moreover, all authors confirm that they have participated adequately in the work to take responsibility for the content of the paper. Specifically, N.K. contributed to develo** the research questions, proposing the hypotheses, collecting and analyzing data, writing the Method and Results sections, and providing comments on the Introduction, literature review, discussion, and Conclusions sections. K.B. contributed to revising and improving the research questions, conducting the literature review, and writing the Introduction, Background, Hypotheses’ Development, discussion, and Conclusions sections. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional Review Board of WORCESTER POLYTECHNIC INSTITUTE.

Informed Consent Statement

Informed consent was obtained from all individual participants involved in the study. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee.

Data Availability Statement

The dataset collected and analyzed for this study is available and can be sent to the journal privately or shared publicly upon request.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A. Measures, Loadings, and Psychometric Characteristics

Table A1. Measurement Items.
Table A1. Measurement Items.
ConstructsItems References
Online Review
Use
ORU1: When deciding on purchasing different products, I ________ use online reviews. (Never/Always)
ORU2: When deciding on which restaurant to go to, I _______ use online reviews. (Never/Always)
ORU3: When deciding on which hotel to stay at, I _______ use online reviews. (Never/Always)
ORU4: When deciding on which places to visit, I _______ use online reviews. (Never/Always)
New items (developed for this study)
Online Review
Writing
ORW1: I ______ post online reviews about my restaurant experiences. (Never/Very frequently)
ORW2: I ______ post online reviews about my hotel experiences after I stay at a hotel. (Never/Very frequently)
ORW3: I ________ post online reviews about different products that I buy. (Never/Very frequently)
ORW4: I ________ post online reviews about different places that I visit. (Never/Very frequently)
New items (developed for this study)
Trust PropensityTRU1: It is generally easy for me to trust a person/thing. (Strongly disagree/Strongly agree)
TRU2: My tendency to trust a person/thing is high. (Strongly disagree/Strongly agree)
TRU3: I tend to trust a person/thing, even though I have little knowledge of it. (Strongly disagree/Strongly agree)
TRU4: Trusting someone or something is not difficult. (Strongly disagree/Strongly agree)
Lee and Turban [172]
Personality TraitsI see myself as someone who (Strongly disagree/Strongly agree)
NEU1: ----- Worries a lot.
NEU2: ----- Gets nervous easily.
NEU3: ----- Remains calm in tense situations. (R)
EXT1: ----- Is talkative.
EXT2: ----- Is outgoing, sociable.
EXT3: ----- Is reserved, quiet. (R)
OPE1: ----- Is original, comes up with new ideas.
OPE2: ----- Values artistic, aesthetic experiences.
OPE3: ----- Has an active imagination.
AGR1: ----- Is sometimes rude to others. (R)
AGR2: ----- Has a forgiving nature.
AGR3: ----- Is considerate and kind to almost everyone.
CON1: ----- Does a thorough job.
CON2: ----- Tends to be lazy. (R)
CON3: ----- Does things efficiently.
Lang et al. [173]
Notes—(R): Reverse-coded; item CON2 was removed from the final factor structure as it did not load on its focal construct.
Table A2. Factor Loadings (Main Study).
Table A2. Factor Loadings (Main Study).
Latent Construct ItemComponents
12345678
Online Review UseORU10.0000.0640.772−0.0190.0780.0720.0840.057
ORU20.0040.1980.8100.040−0.0090.025−0.0150.000
ORU3−0.0200.0960.8110.007−0.0080.0370.0940.046
ORU40.0060.1480.8660.0470.0140.0080.0300.022
Online Review WritingORW10.0160.8960.1650.099−0.0410.0010.004−0.008
ORW20.0110.8880.1360.077−0.0710.0630.0340.013
ORW3−0.0020.8490.1020.0460.0090.0610.0680.022
ORW40.0300.9010.1400.144−0.0530.0510.0090.022
Trust PropensityTRU10.9090.016−0.0110.117−0.0800.0140.1350.025
TRU20.9310.045−0.0060.106−0.0770.0020.1280.027
TRU30.8950.0410.0010.057−0.025−0.0130.059−0.017
TRU40.758−0.056−0.0020.116−0.216−0.0460.176−0.050
NeuroticismNEU1−0.125−0.0510.045−0.0960.9000.035−0.075−0.036
NEU2−0.104−0.0550.060−0.1840.8990.013−0.077−0.057
NEU30.1210.0370.0180.075−0.7400.1660.0780.187
ExtraversionEXT10.1410.1010.0510.877−0.0450.1550.0290.022
EXT20.1810.1730.0510.852−0.1970.1310.0760.055
EXT3−0.069−0.0930.020−0.8790.1350.015−0.0210.028
OpennessOPE10.0250.1260.0210.135−0.1620.7720.0070.203
OPE20.0010.0670.0970.0060.0180.8330.0880.013
OPE3−0.057−0.0240.0160.0990.0160.8380.0580.017
AgreeablenessAGR1−0.066−0.022−0.056−0.0580.1170.123−0.741−0.169
AGR20.2840.0600.072−0.008−0.1070.1900.698−0.068
AGR30.1840.0380.0900.066−0.0090.1730.7780.248
Conscientiousness CON1−0.0440.0200.018−0.002−0.1040.0910.2130.849
CON30.0170.0150.0980.030−0.1400.1000.0860.864
Notes: The underlined values are the loadings on the focal constructs. Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Rotation converged in six iterations.
Table A3. Reliability Score, AVEs, and Inter-construct Correlations.
Table A3. Reliability Score, AVEs, and Inter-construct Correlations.
ConstructCACRAVE(1)(2)(3)(4)(5)(6)(7)(8)
Online Review Use (1)0.8460.8550.6650.815
Online Review Writing (2)0.9230.9420.7810.307 ***0.884
Trust Propensity (3)0.9180.9340.7670.0020.0490.876
Neuroticism (4)0.8520.9030.7220.035−0.113 ***−0.261***0.850
Extraversion (5)0.8870.9270.7560.078 *0.249 ***0.267***−0.302 ***0.869
Openness (6)0.7840.8550.6640.113 ***0.135 ***0.007−0.104 **0.204 ***0.815
Agreeableness (7)0.6650.7270.5470.156 ***0.109 ***0.361***0.235 ***0.156 ***0.170 ***0.740
Conscientiousness (8)0.7490.9120.7340.112 ***0.0610.0190.242 ***0.074 *0.211 ***0.319 ***0.857
Notes: Cronbach’s Alpha = CA; Composite Reliability = CR; Average Variance Extracted: AVE. The diagonal elements, underlined and in bold font, represent the square roots of the AVEs. The off-diagonal numbers represent Pearson correlation coefficients between the constructs. *** p < 0.001, ** p < 0.01, * p < 0.05.

References

  1. Chevalier, J.A.; Mayzlin, D. The effect of word of mouth on sales: Online book reviews. J. Mark. Res. 2006, 43, 345–359. [Google Scholar] [CrossRef]
  2. Clemons, E.K.; Gao, G.; Hitt, L.M. When online reviews meet hyper differentiation: A study of the craft beer industry. J. Manag. Inf. Syst. 2006, 23, 149–171. [Google Scholar] [CrossRef]
  3. Kim, K.; Yoon, S.; Choi, Y.K. The effects of eWOM volume and valence on product sales—An empirical examination of the movie industry. Int. J. Advert. 2018, 38, 471–488. [Google Scholar] [CrossRef]
  4. Bhat, N.Y. The influence of Electronic word of mouth (Ewom) on Consumers Purchase Intention: A review and analysis of the existing literature. IOSR J. Eng. 2020, 10, 27–36. [Google Scholar]
  5. Fink, L.; Rosenfeld, L.; Ravid, G. Longer online reviews are not necessarily better. Int. J. Inf. Manag. 2018, 39, 30–37. [Google Scholar] [CrossRef]
  6. Nguyen, P.; Wang, X.; Li, X.; Cotte, J. When Novices Have More Influence than Experts: Empirical Evidence from Online Peer Reviews. Adv. Consum. Res. 2018, 46, 719–721. [Google Scholar]
  7. Cui, G.; Lui, H.-K.; Guo, X. The effect of online consumer reviews on new product sales. Int. J. Electron. Commer. 2012, 17, 39–58. [Google Scholar] [CrossRef]
  8. Mathwick, C.; Mosteller, J. Online Reviewer Engagement: A Typology Based on Reviewer Motivations. J. Serv. Res. 2016, 20, 204–218. [Google Scholar] [CrossRef]
  9. Westbrook, R.A. Product/Consumption-Based Affective Responses and Postpurchase Processes. J. Mark. Res. 1987, 24, 258–270. [Google Scholar] [CrossRef]
  10. Hennig-Thurau, T.; Gwinner, K.P.; Walsh, G.; Gremler, D.D. Electronic word-of-mouth via consumer-opinion platforms: What motivates consumers to articulate themselves on the Internet? J. Interact. Mark. 2004, 18, 38–52. [Google Scholar] [CrossRef]
  11. Rosario, A.B.; Sotgiu, F.; De Valck, K.; Bijmol, T.H.A. The Effect of Electronic Word of Mouth on Sales: A Meta-Analytic Review of Platform, Product, and Metric Factors. J. Mark. Res. 2016, 53, 297–318. [Google Scholar] [CrossRef]
  12. Wasko, M.M.; Faraj, S. Why should I share? Examining social capital and knowledge contribution in electronic networks of practice. MIS Q. 2005, 29, 35–57. [Google Scholar] [CrossRef]
  13. Filieri, R.; McLeay, F. E-WOM and accommodation: An analysis of the factors that influence travelers’ adoption of information from online reviews. J. Travel Res. 2013, 53, 44–57. [Google Scholar] [CrossRef]
  14. Manner, C.; Lane, W. Who posts online customer reviews? The role of sociodemographics and personality traits. J. Consum. Satisf. Dissatisfaction Complain. Behav. 2017, 30, 23–32. [Google Scholar]
  15. Manner, C.; Lane, W. Personality Traits as Predictors of Online Customer Review Motivations. J. Soc. Media Soc. 2018, 7, 184–210. [Google Scholar]
  16. Tata, S.V.; Prashar, S.; Parsad, C. Intention to write reviews: Influence of personality traits, attitude and motivational factors. J. Syst. Inf. Technol. 2021, 23, 218–242. [Google Scholar] [CrossRef]
  17. Moiescu, O.I.; Dan, I.; Gica, O.-A. An examination of personality traits as predictors of electronic word-of-mouth diffusion in social networking sites. J. Consum. Behav. 2022, 21, 450–467. [Google Scholar] [CrossRef]
  18. Al-Samarraie, H.; Eldenfria, A.; Dawoud, H. The impact of personality traits on users’ information-seeking behavior. Inf. Process. Manag. 2017, 53, 237–247. [Google Scholar] [CrossRef]
  19. Yu, T.-K.; Lee, N.-H.; Chao, C.-M. The Moderating Effects of Young Adults’ Personality Traits on Social Media Immersion. Front. Psychol. 2020, 11, 554106. [Google Scholar] [CrossRef]
  20. Camilleri, A.R. Who doesn’t read online consumer reviews, and why? Personal. Individ. Differ. 2021, 179, 110954. [Google Scholar] [CrossRef]
  21. Dixit, S.; Badgaiyan, A.J.; Khare, A. An integrated model for predicting consumer’s intention to write online reviews. J. Retail. Consum. Serv. 2019, 46, 112–120. [Google Scholar] [CrossRef]
  22. Jadin, T.; Gnambs, T.; Batinic, B. Personality traits and knowledge sharing in online communities. Comput. Hum. Behav. 2013, 29, 210–216. [Google Scholar] [CrossRef]
  23. Barnes, R.; Mahar, D.; Wong, I.; Rune, K. A Neurotic Extrovert Who is Open to New Experiences? Understanding How Personality Traits May Impact the Commenting Behaviors of Online News Readers. J. Broadcast. Electron. Media 2017, 61, 557–573. [Google Scholar] [CrossRef]
  24. Zhang, M. Assessing Two Dimensions of Interpersonal Trust: Other-Focused Trust and Propensity to Trust. Front. Psychol. 2021, 12, 654735. [Google Scholar] [CrossRef] [PubMed]
  25. Shaheen, M.; Zeba, F.; Chatterjee, N.; Krishnankutty, R. Engaging customers through credible and useful reviews: The role of online trust. Young Consum. 2020, 21, 137–153. [Google Scholar] [CrossRef]
  26. Thompson, S.H.; Lougheed, E. Frazzled by Facebook? An exploratory study of gender differences in social network communication among undergraduate men and women. Coll. Stud. J. 2012, 46, 88–98. [Google Scholar]
  27. Park, J.; Yoon, Y.; Lee, B. The Effect of Gender and Product Categories on Consumer Online Information Search. Adv. Consum. Res. 2009, 36, 362–366. [Google Scholar]
  28. Kotler, P.; Keller, K.L. Marketing Management, 12th ed.; Prentice-Hall: Upper Saddle River, NJ, USA, 2005. [Google Scholar]
  29. Moe, W.W.; Trusov, M. The value of social dynamics in online product ratings forums. J. Mark. Res. 2011, 48, 444–456. [Google Scholar] [CrossRef]
  30. You, Y.; Vadakkepatt, G.G.; Joshi, A.M. A meta-analysis of electronic word-of-mouth elasticity. J. Mark. 2015, 79, 19–39. [Google Scholar] [CrossRef]
  31. Park, S.; Nicolau, J.L. Asymmetric effects of online consumer reviews. Ann. Tour. Res. 2015, 50, 67–83. [Google Scholar] [CrossRef]
  32. Hicks, A.; Comp, S.; Horovitz, J.; Hovarter, M.; Miki, M.; Bevan, J.L. Why people use Yelp.com: An exploration of uses and gratifications. Comput. Hum. Behav. 2012, 28, 2274–2279. [Google Scholar] [CrossRef]
  33. Kotler, P.; Kartajaya, H.; Setiawan, I. Marketing 4.0: Moving from Traditional to Digital; Wiley: Hoboken, NJ, USA, 2016. [Google Scholar]
  34. Gong, W.; Li, X. Engaging fans on microblog: The synthetic influence of parasocial interaction and source characteristics on celebrity endorsement. Psychol. Mark. 2017, 34, 720–732. [Google Scholar] [CrossRef]
  35. Qiao, D.; Lee, S.-Y.; Whinston, A.; Wei, Q. Financial Incentives Dampen Altruism in Online Prosocial Contributions: A Study of Online Reviews. Inf. Syst. Res. 2020, 31, 1361–1375. [Google Scholar] [CrossRef]
  36. Shelly, B.; Narang, R. Effects of gender and stress on altruism. Int. J. Indian Psychol. 2018, 6, 2–10. [Google Scholar] [CrossRef]
  37. Peters, K.; Chen, Y.; Kaplan, A.M.; Ognibeni, B.; Pauwels, K. Social media metrics: A framework and guidelines for managing social media. J. Interact. Mark. 2013, 27, 281–298. [Google Scholar] [CrossRef]
  38. McGraw, A.P.; Warren, C.; Kan, C. Humorous complaining. J. Consum. Res. 2015, 41, 1153–1171. [Google Scholar] [CrossRef]
  39. Anderson, E.T.; Simester, D.I. Reviews without a purchase: Low ratings, loyal customers, and deception. J. Mark. Res. 2014, 51, 249–269. [Google Scholar] [CrossRef]
  40. McCrae, R.R.; Costa, T. Personality in Adulthood: A Five-Factor Theory Perspective, 2nd ed.; Guilford Press: New York, NY, USA, 2003. [Google Scholar]
  41. Zha, X.; Zhang, J.; Yan, Y.; ** Consumers’ Perception of Brand Image. Int. J. Hosp. Tour. Adm. 2023, 24, 387–414. [Google Scholar] [CrossRef]
  42. Eagly, A.H.; Wood, W. Social role theory. In Handbook of Theories of Social Psychology; Van Lange, P.A.M., Kruglanski, A.W., Higgins, E.T., Eds.; Sage Publications Ltd.: New York, NY, USA, 2012; pp. 458–476. [Google Scholar]
  43. Venkatesh, V.; Morris, M.G. Why don’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behaviour. MIS Q. 2000, 24, 115–139. [Google Scholar] [CrossRef]
  44. Richard, M.-O.; Chebat, A.-C.; Yang, Z.; Putrevu, S. A proposed model of online consumer behavior: Assessing the role of gender. J. Bus. Res. 2010, 63, 926–934. [Google Scholar] [CrossRef]
  45. Kim, E.K.K.; Mattila, A.; Baloglu, S. Effects of Gender and Expertise on Consumers’ Motivation to Read Online Hotel Reviews. Cornell Hosp. Rev. 2011, 52, 399–406. [Google Scholar] [CrossRef]
  46. Chent, Y.; Yan, X.; Fan, W.; Gordon, M. The joint moderating role of trust propensity and gender on consumers’ online shop** behavior. Comput. Hum. Behav. 2015, 43, 272–283. [Google Scholar]
  47. Mladenovic, D.; Kra**a, A.; Milojevic, I. Motives for writing online reviews in post-vacation phase. Int. J. Cult. Tour. Hosp. Res. 2019, 13, 244–256. [Google Scholar] [CrossRef]
  48. Choi, J.H.; Ramirez, R.; Gregg, D.G.; Scott, J.E.; Lee, K.-H. Influencing Knowledge Sharing on Social Media: A Gender Perspective. Asia Pac. J. Inf. Syst. 2020, 30, 513–531. [Google Scholar] [CrossRef]
  49. Teo, T.S.H.; Liu, J. Consumer trust in e-commerce in the United States, Singapore, and China. Omega 2007, 35, 22–38. [Google Scholar] [CrossRef]
  50. Lu, L.C.; Chang, W.P.; Chang, H.H. Consumer attitudes toward blogger’s sponsored recommendations and purchase intention: The effect of sponsorship type, product type, and brand awareness. Comput. Hum. Behav. 2014, 34, 258–266. [Google Scholar] [CrossRef]
  51. Barrick, M.R.; Mount, M.K. The big five personality dimensions and job performance: A meta-analysis. Pers. Psychol. 1991, 44, 1–26. [Google Scholar] [CrossRef]
  52. Moore, K.; Mcelroy, J.C. The Influence of Personality on Facebook Usage, Wall Postings, and Regret. Comput. Hum. Behav. 2012, 28, 267–274. [Google Scholar] [CrossRef]
  53. Gil de Zúñiga, H.; Diehl, T.; Huber, B.; Liu, J. Personality Traits and Social Media Use in 20 Countries: How Personality Relates to Frequency of Social Media Use, Social Media News Use, and Social Media Use for Social Interaction. Cyberpsychol. Behav. Soc. Netw. 2017, 20, 540–552. [Google Scholar] [CrossRef]
  54. Rollero, C.; Daniele, A.; Tartaglia, S. Do men post and women view? The role of gender, personality and emotions in online social activity. Cyberpsychol. J. Psychosoc. Res. Cyberspace 2019, 13, 1. [Google Scholar] [CrossRef]
  55. Costa, P.T.; McCrae, R.R. Revised NEO Personality Inventory (NEO-PI-R) and NEO Five Factor Inventory (NEO-FFI) Professional Manual; Psychological Assessment Resources, Inc.: Odessa, FL, USA, 1992. [Google Scholar]
  56. Butt, S.; Phillips, J.G. Personality and self-reported mobile phone use. Comput. Hum. Behav. 2008, 24, 346–360. [Google Scholar] [CrossRef]
  57. Correa, T.; Hinsley, A.W.; de Zúñiga, H.G. Who interacts on the web? The intersection of users’ personality and social media use. Comput. Hum. Behav. 2010, 26, 247–253. [Google Scholar] [CrossRef]
  58. Tsao, W.C. Big five personality traits as predictors of Internet. Int. J. Manag. 2013, 30, 374–386. [Google Scholar]
  59. Cabrera, Á.; Collins, W.C.; Salgado, J.F. Determinants of individual engagement in knowledge sharing. Int. J. Hum. Resour. Manag. 2006, 17, 245–264. [Google Scholar] [CrossRef]
  60. Matz, S.C. Personal echo chambers: Openness-to-experience is linked to higher levels of psychological interest diversity in large-scale behavioral data. J. Personal. Soc. Psychol. 2021; advance online publication. [Google Scholar]
  61. Landers, R.N.; Lounsbery, J.W. An investigation of Big Five and narrow personality traits in relation to Internet usage. Comput. Hum. Behav. 2006, 22, 283–293. [Google Scholar] [CrossRef]
  62. Molleman, E.; Nauta, A.; Jehn, K.A. Person–job fit applied to teamwork: A multilevel approach. Small Group Res. 2004, 35, 515–539. [Google Scholar] [CrossRef]
  63. Martin, R. Gender and Emotion Stereotypes in Children’s Television. J. Broadcast. Electron. Media 2017, 61, 499–517. [Google Scholar] [CrossRef]
  64. Miraj, M.; Chuntian, L.; Mohd Said, R.; Osei-Bonsu, R.; Rehman, R.U. How Information-Seeking Behavior, Essential Technologies, and Resilience Enhance the Academic Performance of Students. Front. Psychol. 2021, 12, 651550. [Google Scholar] [CrossRef]
  65. Ahmed, S.; Rehman, F.; Sheikh, A. Impact of personality traits on information needs and seeking behavior of LIS students in Pakistan. Inf. Discov. Deliv. 2021, 47, 125–134. [Google Scholar] [CrossRef]
  66. El Othman, R.; El Othman, R.; Hallit, R.; Obeid, S.; Hallit, S. Personality traits, emotional intelligence and decision-making styles in Lebanese universities medical students. BMC Psychol. 2020, 8, 46. [Google Scholar] [CrossRef] [PubMed]
  67. Uliaszek, A.A.; Zinbarg, R.E.; Mineka, S.; Craske, M.G.; Sutton, J.M.; Griffith, J.W.; Rose, R.; Waters, A.; Hammen, C. The role of neuroticism and extraversion in the stress-anxiety and stress-depression relationships. Anxiety Stress Co** 2010, 23, 363–381. [Google Scholar] [CrossRef] [PubMed]
  68. Eysenck, H.J. Dimensions of Personality; Transaction Publishers: New Brunswick, NJ, USA, 1998. [Google Scholar]
  69. McCrae, R.R.; John, O.P. An introduction to the five-factor model and its applications. J. Personal. 1992, 60, 175–215. [Google Scholar] [CrossRef] [PubMed]
  70. Hirsh, J.B.; Inzlicht, M. The devil you know: Neuroticism predicts neural response to uncertainty. Psychol. Sci. 2008, 19, 962–967. [Google Scholar] [CrossRef] [PubMed]
  71. Amiel, T.; Sargent, S.L. Individual differences in Internet usage motives. Comput. Hum. Behav. 2004, 20, 711–726. [Google Scholar] [CrossRef]
  72. König, T.M.; Clarke, T.B.; Hellenthal, M.; Clarke, I., III. Personality effects on WoM and eWoM susceptibility—A cross-country perspective. Int. Mark. Rev. 2022; ahead-of-print. [Google Scholar]
  73. McElroy, J.; Hendrickson, A.; Townsend, A.; DeMarie, S. Dispositional factors in Internet use: Personality versus cognitive style. MIS Q. 2007, 31, 809–820. [Google Scholar] [CrossRef]
  74. Seidman, G. Self-presentation and belonging on Facebook: How personality influences social media use and motivations. Personal. Individ. Differ. 2013, 54, 402–407. [Google Scholar] [CrossRef]
  75. Wang, C.-C.; Yang, Y.-J. Personality and intention to share knowledge: An empirical study of scientists in an R&D laboratory. Soc. Behav. Personal. Int. J. 2007, 35, 1427–1436. [Google Scholar]
  76. Matzler, K.; Bidmon, S.; Grabner-Kräuter, S. Individual determinants of brand affect: The role of the personality traits of extraversion and openness to experience. J. Prod. Band Manag. 2006, 15, 427–494. [Google Scholar] [CrossRef]
  77. DeYoung, C.G. Cybernetic big five theory. J. Res. Personal. 2015, 56, 33–58. [Google Scholar] [CrossRef]
  78. Yen, C.-L.; Tang, C.-H. Hotel attribute performance, eWOM motivations, and media choice. Int. J. Hosp. Manag. 2015, 46, 79–88. [Google Scholar] [CrossRef]
  79. Thoms, P.; Moore, K.S.; Scott, K.S. The relationship between self-efficacy for participating in self-managed work groups and the big five personality dimensions. J. Organ. Behav. 1996, 17, 349–362. [Google Scholar] [CrossRef]
  80. Lischka, H.M.; Dedick, Y. Extraversion and Market Mavenism Mediate the Relationship between Review Involvement and the Intention to Create Online Consumer Reviews. J. Consum. Satisf. Dissatisfaction Complain. Behav. 2017, 30, 31. [Google Scholar]
  81. McCrae, R.R.; Costa, J.P.T. Conceptions and Correlates of Openness to Experience. In Handbook of Personality Psychology; Hoga, R., Johnson, J., Briggs, S., Eds.; Elsevier: Amsterdam, The Netherlands, 1997; pp. 825–847. [Google Scholar]
  82. Liu, D.; Campbell, W.K. The Big Five personality traits, Big Two metatraits and social media: A meta-analysis. J. Res. Personal. 2017, 70, 229–240. [Google Scholar] [CrossRef]
  83. Matzler, K.; Renzl, B.; Müller, J.; Herting, S.; Mooradian, T.A. Personality traits and knowledge sharing. J. Econ. Psychol. 2008, 29, 301–313. [Google Scholar] [CrossRef]
  84. Liao, H.; Chuang, A. A multilevel investigation of factors influencing employee service performance and customer outcomes. Acad. Manag. J. 2004, 47, 41–58. [Google Scholar] [CrossRef]
  85. Wasko, M.M.; Faraj, S. It Is What One Does: Why People Participate and Help Others in Electronic Communities of Practice. J. Strateg. Inf. Syst. 2000, 9, 155–173. [Google Scholar] [CrossRef]
  86. Yoo, K.H.; Gretzel, U. Influence of personality on travel-related consumer generated media creation. Comput. Hum. Behav. 2011, 27, 609–621. [Google Scholar] [CrossRef]
  87. Kaufman, S.B.; Quilty, L.C.; Grazioplene, R.G.; Hirsh, J.B.; Gray, J.R.; Peterson, J.B.; DeYoung, C.G. Openness to experience and intellect differentially predict creative achievement in the arts and sciences. J. Personal. 2016, 84, 248–258. [Google Scholar] [CrossRef]
  88. Poddar, A.; Banerjee, S.; Sridhar, K. False advertising or slander? Using location-based tweets to assess online rating-reliability. J. Bus. Res. 2019, 99, 390–397. [Google Scholar] [CrossRef]
  89. Tan, W.-K.; Yang, C.-Y. Internet applications use and personality. Telemat. Inform. 2014, 31, 27–38. [Google Scholar] [CrossRef]
  90. Taggar, S. Individual creativity and group ability to utilize individual creative resources: A multilevel model. Acad. Manag. J. 2002, 45, 315–330. [Google Scholar] [CrossRef]
  91. Weisberg, Y.J.; Deyoung, C.G.; Hirsh, J.B. Gender Differences in Personality across the Ten Aspects of the Big Five. Front. Psychol. 2011, 2, 11757. [Google Scholar] [CrossRef] [PubMed]
  92. Schmitt, D.P.; Realo, A.; Voracek, M.; Allik, J. Why can’t a man be more like a woman? Sex differences in Big Five personality traits across 55 cultures. J. Personal. Soc. Psychol. 2008, 94, 168–182. [Google Scholar] [CrossRef] [PubMed]
  93. Costa, P.; Terracciano, A.; McCrae, R.R. Gender differences in personality traits across cultures: Robust and surprising findings. J. Personal. Soc. Psychol. 2001, 81, 322–331. [Google Scholar] [CrossRef] [PubMed]
  94. Lundeberg, M.A.; Fox, P.W.; Punćcohaŕ, J. Highly confident but wrong: Gender differences and similarities in confidence judgments. J. Educ. Psychol. 1994, 86, 114–121. [Google Scholar] [CrossRef]
  95. Oberst, U.; Renau, V.; Chamarro, A.; Carbonell, X. Gender stereotypes in Facebook profiles: Are women more female online? Comput. Hum. Behav. 2016, 60, 559–564. [Google Scholar] [CrossRef]
  96. Berg, J.; Dickhaut, J.; McCabe, K. Trust, reciprocity, and social history. Games Econ. Behav. 1995, 10, 122–142. [Google Scholar] [CrossRef]
  97. Bohnet, I.; Yael, B. Institutions and Trust: Implications for Preferences, Beliefs and Behavior. Ration. Soc. 2007, 19, 99–135. [Google Scholar] [CrossRef]
  98. Chaudhuri, A.; Gangadharan, L. An Experimental Analysis of Trust and Trustworthiness. South. Econ. J. 2007, 73, 959–985. [Google Scholar] [CrossRef]
  99. Gong, B.; Yang, C.-L. Gender Differences in Risk Attitudes: Field Experiments on the Matrilineal Mosuo and the Patriarchal Yi. J. Econ. Behav. Organ. 2012, 83, 59–65. [Google Scholar] [CrossRef]
  100. Levin, D.; Whitener, E.; Cross, R. Perceived trustworthiness of knowledge sources: The moderating impact of relationship length. J. Appl. Psychol. 2006, 91, 1163–1171. [Google Scholar] [CrossRef] [PubMed]
  101. Ebstrup, J.F.; Eplov, L.F.; Pisinger, C.; Jørgensen, T. Association between the Five Factor personality traits and perceived stress: Is the effect mediated by general self-efficacy? Anxiety Stress Co** 2011, 24, 407–419. [Google Scholar] [CrossRef] [PubMed]
  102. Keshavarz, S.; Baharudin, R. The Moderating Role of Gender on the Relationships between Perceived Paternal Parenting Style, Locus of Control and Self-Efficacy. Procedia—Soc. Behav. Sci. 2012, 32, 63–68. [Google Scholar] [CrossRef]
  103. Feingold, A. Gender differences in personality: A meta-analysis. Psychol. Bull. 1994, 116, 429–456. [Google Scholar] [CrossRef] [PubMed]
  104. Derks, D.; Fischer, A.H.; Bos, A.E.R. The role of emotion in computer-mediated communication: A review. Comput. Hum. Behav. 2008, 24, 766–785. [Google Scholar] [CrossRef]
  105. Scher, S.J.; Osterman, N.M. Procrastination, conscientiousness, anxiety, and goals: Exploring the measurement and correlates of procrastination among school-aged children. Psychol. Sch. 2002, 39, 385–398. [Google Scholar] [CrossRef]
  106. Liu, T.; Liu, Z.; Zhang, L.; Mu, S. Dispositional mindfulness mediates the relationship between conscientiousness and mental health-related issues in adolescents during the COVID-19 pandemic. Personal. Individ. Differ. 2022, 184, 111223. [Google Scholar] [CrossRef] [PubMed]
  107. Grange, C.; Benbasat, I.; Burton-Jones, A. With a little help from my friends: Cultivating serendipity in online shop** environments. Inf. Manag. 2019, 56, 225–235. [Google Scholar] [CrossRef]
  108. Ruiz, S.M.; Valmas, M.M.; Sawyer, K.S. Influence of alcoholism and gender on the relationship between personality and drinking motivation. Addict. Sci. Clin. Pract. 2015, 10, A56. [Google Scholar] [CrossRef]
  109. Yin, D.; Bond, S.D.; Zhang, H. Anxious or Angry? Effects of Discrete Emotions on the Perceived Helpfulness of Online Reviews. MIS Q. 2014, 38, 539–560. [Google Scholar] [CrossRef]
  110. van der Rijt, J.; Van den Bossche, P.; Segers, M.S.R. Understanding informal feedback seeking in the workplace: The impact of the position in the organizational hierarchy. Eur. J. Train. Dev. 2013, 37, 72–85. [Google Scholar] [CrossRef]
  111. Li, Y.; Lan, J.; Ju, C. Self-esteem, gender, and the relationship between extraversion and subjective well-being. Soc. Behav. Personal. Int. J. 2015, 43, 1243–1254. [Google Scholar] [CrossRef]
  112. Reis, S.M. Toward a Theory of Creativity in Diverse Creative Women. Creat. Res. J. 2010, 14, 305–316. [Google Scholar] [CrossRef]
  113. Huang, S.S.; Wei, X. Offline versus online travel experience sharing: The national profile of China. Int. J. Cult. Tour. Hosp. Res. 2019, 13, 183–189. [Google Scholar] [CrossRef]
  114. Stavrositu, C.; Sundar, S.S. Does blogging empower women? Exploring the role of agency and community. J. Comput.-Mediat. Commun. 2012, 17, 369–386. [Google Scholar] [CrossRef]
  115. Conrad, N.; Patry, M.W. Conscientiousness and Academic Performance: A Mediational Analysis. Int. J. Scholarsh. Teach. Learn. 2012, 6, n1. [Google Scholar] [CrossRef]
  116. Schippers, M. Social loafing tendencies and team performance: The compensating effect of agreeableness and conscientiousness. Acad. Manag. Learn. Educ. 2013, 13, 62–81. [Google Scholar] [CrossRef]
  117. Khalifa, A.H. What motivates consumers to communicate eWOM: Evidence from Tunisian context. J. Strateg. Mark. 2022, 1–18. [Google Scholar] [CrossRef]
  118. Bandura, A.; Locke, E.A. Negative self-efficacy and goal effects revisited. J. Appl. Psychol. 2003, 88, 87–99. [Google Scholar] [CrossRef]
  119. Kling, K.C.; Hyde, J.S.; Showers, C.J.; Buswell, B.N. Gender differences in self-esteem: A meta-analysis. Psychol. Bull. 1999, 125, 470–500. [Google Scholar] [CrossRef]
  120. Guadagno, R.E.; Okdie, B.M.; Eno, C.A. Who blogs? Personality predictors of blogging. Comput. Hum. Behav. 2008, 24, 1993–2004. [Google Scholar] [CrossRef]
  121. Chaudhuri, A.; Sbai, E. Gender differences in trust and reciprocity in repeated gift exchange games. In Economic Psychology and Experimental Economics; Routledge: London, UK, 2013. [Google Scholar]
  122. Wood, W.; Eagly, A.H. Two traditions of research on gender identity. Sex Roles 2015, 73, 461–473. [Google Scholar] [CrossRef]
  123. Eagly, A.H.; Wood, W. Universal sex differences across patriarchal cultures ≠ evolved psychological dispositions. Behav. Brain Sci. 2005, 28, 281–283. [Google Scholar] [CrossRef]
  124. Muscanell, N.L.; Guadagno, R.E. Make new friends or keep the old: Gender and personality differences in social networking use. Comput. Hum. Behav. 2012, 28, 107–112. [Google Scholar] [CrossRef]
  125. Awad, N.F.; Ragowsky, A. Establishing trust in electronic commerce through online word of mouth: An examination across genders. J. Manag. Inf. Syst. 2008, 24, 101–121. [Google Scholar] [CrossRef]
  126. Kordzadeh, N.; Warren, J. Communicating Personal Health Information in Virtual Health Communities: An Integration of Privacy Calculus Model and Affective Commitment. J. Assoc. Inf. Syst. 2017, 18, 45–81. [Google Scholar] [CrossRef]
  127. Nunnally, J. Psychometric Theory, 2nd ed.; Mcgraw-Hill: Hillsdale, NJ, USA, 1978. [Google Scholar]
  128. Litman, L.; Robinson, J. Conducting Online Research on Amazon Mechanical Turk and Beyond; SAGE Publications, Inc.: Thousand Oaks, CA, USA, 2020; Volume 1. [Google Scholar]
  129. Steelman, Z.R.; Hammer, B.; Limayem, M. Data Collection in the Digital Age: Innovative Alternatives to Student Samples. MIS Q. 2014, 38, 355–378. [Google Scholar] [CrossRef]
  130. Lee, S.-Y.; Rui, H.; Whinston, A.B. Is best answer really the best answer? The politeness bias. MIS Q. 2019, 43, 579–600. [Google Scholar] [CrossRef]
  131. Curran, P.G. Methods for the detection of carelessly invalid responses in survey data. J. Exp. Soc. Psychol. 2016, 66, 4–19. [Google Scholar] [CrossRef]
  132. Lowry, P.B.; D’Arcy, J.; Hammer, B.; Moody, G.D. “Cargo Cult” science in traditional organization and information systems survey research: A case for using nontraditional methods of data collection, including Mechanical Turk and online panels. J. Strateg. Inf. Syst. 2016, 25, 232–240. [Google Scholar] [CrossRef]
  133. Fornell, C.; Larcker, D.F. Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 1981, 18, 39–50. [Google Scholar] [CrossRef]
  134. MacKenzie, S.B.; Podsakoff, P.M.; Podsakoff, N. Construct measurement and validation procedures in MIS and behavioral research: Integrating new and existing techniques. MIS Q. 2011, 35, 293–334. [Google Scholar] [CrossRef]
  135. Podsakoff, P.M.; MacKenzie, S.B.; Lee, J.-Y.; Podsakoff, N.P. Common method biases in behavioral research: A critical review of the literature and recommended remedies. J. Appl. Psychol. 2003, 88, 879–903. [Google Scholar] [CrossRef]
  136. Myers, R.H. Classical and Modern Regression with Applications; Duxbury Press: Belmont, CA, USA, 1990; Volume 2. [Google Scholar]
  137. Teng, S.; Khong, K.W.; Goh, W.W.; Chong, A. Examining the antecedents of persuasive eWOM messages in social media. Online Inf. Rev. 2014, 38, 746–768. [Google Scholar] [CrossRef]
  138. Zheng, X.; Cheung, C.M.K.; Lee, M.K.O.; Liang, L. Building brand loyalty through user engagement in online brand communities in social networking sites. Inf. Technol. People 2015, 28, 90–106. [Google Scholar] [CrossRef]
  139. Thakur, R. Customer engagement and online reviews. J. Retail. Consum. Serv. 2018, 41, 48–59. [Google Scholar] [CrossRef]
  140. King, R.A.; Racherla, P.; Bush, V.D. What we know and don’t know about online word-of-mouth: A review and synthesis of the literature. J. Interact. Mark. 2014, 28, 176–183. [Google Scholar] [CrossRef]
  141. Zhao, L.; Lu, Y.; Wang, B.; Chau, Y.K.; Zhang, L. Cultivating the sense of belonging and motivating user participation in virtual communities: A social capital perspective. Int. J. Inf. Manag. 2012, 32, 574–588. [Google Scholar] [CrossRef]
  142. Wang, J.-L.; Jackson, L.A.; Zhang, D.-J.; Su, Z.-Q. The relationships among the Big Five Personality factors, self-esteem, narcissism, and sensation-seeking to Chinese University students’ uses of social networking sites (SNSs). Comput. Hum. Behav. 2012, 28, 2313–2319. [Google Scholar] [CrossRef]
  143. Zhang, L.; Shao, Z.; Li, X.; Feng, Y. Gamification and online impulse buying: The moderating effect of gender and age. Int. J. Inf. Manag. 2021, 61, 102267. [Google Scholar] [CrossRef]
  144. Brandt, T.; Laiho, M. Gender and personality in transformational leadership context: An examination of leader and subordinate perspectives. Leadersh. Organ. Dev. J. 2013, 34, 44–66. [Google Scholar] [CrossRef]
  145. Amichai-Hamburger, Y. Internet and personality. Comput. Hum. Behav. 2002, 18, 1–10. [Google Scholar] [CrossRef]
  146. Simoncic, T.E.; Kuhlman, K.R.; Vargas, I.; Houchins, S.; Lopez-Duran, N.L. Facebook use and depressive symptomatology: Investigating the role of neuroticism and extraversion in youth. Comput. Hum. Behav. 2014, 40, 1–5. [Google Scholar] [CrossRef] [PubMed]
  147. Brutus, S.; Aguinis, H.; Wassmer, U. Self-Reported Limitations and Future Directions in Scholarly Reports: Analysis and Recommendations. J. Manag. 2012, 39, 48–75. [Google Scholar] [CrossRef]
  148. Antil, J.H. Conceptualization and Operationalization of Involvement. In Advances in Consumer Research; Kinnear, T.C., Ed.; Association for Consumer Research: Provo, UT, USA, 1984; pp. 203–209. [Google Scholar]
  149. Lang, F.R.; John, D.; Lüdtke, O.; Schupp, J.; Wagner, G.G. Short assessment of the Big Five: Robust across survey methods except telephone interviewing. Behav. Res. Methods 2011, 43, 548–567. [Google Scholar] [CrossRef]
  150. Lee, M.K.; Turban, E. A trust model for consumer internet shop**. Int. J. Electron. Commer. 2001, 6, 75–91. [Google Scholar] [CrossRef]
Figure 1. Research model.
Figure 1. Research model.
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Figure 2. The moderating effect of gender on the relationship between extraversion and online review writing.
Figure 2. The moderating effect of gender on the relationship between extraversion and online review writing.
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Figure 3. The moderating effect of gender on the relationship between openness and online review writing.
Figure 3. The moderating effect of gender on the relationship between openness and online review writing.
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Figure 4. The moderating effect of gender on the relationship between agreeableness and online review writing.
Figure 4. The moderating effect of gender on the relationship between agreeableness and online review writing.
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Table 1. Factor Loadings (Pilot Study).
Table 1. Factor Loadings (Pilot Study).
Component 1
(Online Review Writing) Cronbach’s Alpha = 0.846
Component 2
(Online Review Use) Cronbach’s Alpha = 0.853
ORU1: When deciding on purchasing different products, I ____ use online reviews (1—never, 7—always).0.0740.846
ORU2: When deciding on which restaurants to go to, I ____ use online reviews. 0.3360.705
ORU3: When deciding on which hotel to stay at, I ____ use online reviews. 0.1540.873
ORU4: When deciding on which places to visit, I ____ use online reviews. 0.1650.838
ORW1: I ______ post online reviews about my restaurant experiences.0.9260.120
ORW2: I ______ post online reviews about my hotel experiences after I stay at a hotel.0.8740.175
ORW3: I ______ post online reviews about different products that I buy.0.8550.233
ORW4: I ______ post online reviews about different places that I visit.0.8950.188
Table 2. Results of Regression Analysis: H1–H5 and H11a–H11e.
Table 2. Results of Regression Analysis: H1–H5 and H11a–H11e.
Step 1
(Model 1a)
Step 2
(Model 1b)
Step 3
(Model 1c)
(Constant)5.324 ***
(0.180)
3.788 ***
(0.402)
2.860 ***
(0.715)
Gender (male = 0, female = 1)0.329 ***
(0.084)
0.291 ***
(0.087)
0.296 ***
(0.090)
Age−0.008 *
(0.003)
−0.009 **
(0.003)
−0.010 **
(0.003)
Education0.003
(0.034)
0.000
(0.034)
0.009
(0.034)
Trust Propensity (H1) −0.001
(0.030)
0.035
(0.055)
Extraversion (H2) 0.041
(0.027)
−0.013
(0.051)
Openness (H3) 0.106 **
(0.038)
0.232 **
(0.075)
Conscientiousness (H4) 0.138 **
(0.044)
0.183 *
(0.083)
Neuroticism (H5) 0.021
(0.027)
0.033
(0.053)
Gender × Trust Propensity (H11a) −0.048
(0.065)
Gender × Extraversion (H11b) 0.074
(0.061)
Gender × Openness (H11c) −0.169 +
(0.087)
Gender × Conscientiousness (H11d) −0.070
(0.098)
Gender × Neuroticism (H11e) −0.015
(0.062)
R20.0250.0580.065
ΔR20.0250.0330.007
ΔF6.870 ***5.532 ***1.197
Notes: Dependent variable: Online review use. Standard errors are reported in parentheses. *** p < 0.001, ** p < 0.01, * p < 0.05, + p < 0.1.
Table 3. Results of Regression Analysis: H6–H10 and H12a–H12e.
Table 3. Results of Regression Analysis: H6–H10 and H12a–H12e.
Step 1
(Model 2a)
Step 2
(Model 2b)
Step 3
(Model 2c)
(Constant)2.693 ***
(0.205)
1.281 **
(0.446)
1.355 +
(0.758)
Gender (male = 0, female = 1)0.018
(0.096)
−0.006
(0.096)
−0.055
(0.097)
Age0.005
(0.004)
0.002
(0.004)
0.002
(0.004)
Education−0.058
(0.039)
−0.066 +
(0.038)
−0.088 *
(0.038)
Extraversion (H6) 0.195 ***
(0.030)
0.308 ***
(0.055)
Openness (H7) 0.115 **
(0.042)
−0.075
(0.083)
Conscientiousness (H8) 0.007
(0.050)
−0.102
(0.092)
Neuroticism (H9) −0.020
(0.030)
0.044
(0.056)
Agreeableness (H10) 0.043
(0.044)
0.234 **
(0.083)
Gender × Extraversion (H12a) −0.155 *
(0.065)
Gender × Openness (H12b) 0.243 *
(0.096)
Gender × Conscientiousness (H12c) 0.160
(0.109)
Gender × Neuroticism (H12d) −0.089
(0.066)
Gender × Agreeableness (H12e) −0.261 **
(0.098)
R20.0040.0920.112
ΔR20.0040.0870.021
ΔF1.18915.120 ***3.665 **
Notes: Dependent variable: Online review writing. Standard errors are reported in parentheses. *** p < 0.001, ** p < 0.01, * p < 0.05, + p < 0.1.
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Kordzadeh, N.; Bozan, K. The Influence of the Big Five Personality Traits and Propensity to Trust on Online Review Behaviors: The Moderating Role of Gender. J. Theor. Appl. Electron. Commer. Res. 2024, 19, 1442-1470. https://doi.org/10.3390/jtaer19020072

AMA Style

Kordzadeh N, Bozan K. The Influence of the Big Five Personality Traits and Propensity to Trust on Online Review Behaviors: The Moderating Role of Gender. Journal of Theoretical and Applied Electronic Commerce Research. 2024; 19(2):1442-1470. https://doi.org/10.3390/jtaer19020072

Chicago/Turabian Style

Kordzadeh, Nima, and Karoly Bozan. 2024. "The Influence of the Big Five Personality Traits and Propensity to Trust on Online Review Behaviors: The Moderating Role of Gender" Journal of Theoretical and Applied Electronic Commerce Research 19, no. 2: 1442-1470. https://doi.org/10.3390/jtaer19020072

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