The 21st century has marked drastic changes in personality grooming and behavior toward colleagues and organizations. These changes have been attributed lately to the demands of finding and retaining reputable jobs. However, such motives sometimes also develop unseen and not so socially accepted habits as well. One such challenge that organizations are facing in this technological era is knowledge hiding behavior. This study aims to understand the BIG FIVE model personality traits’ role in knowledge hiding behavior, and how psychological ownership mediates these relationships. Knowledge hiding is a process of hiding knowledge at the workplace. A situation in which a co-worker gives confidential information to others, in this case it may be misleading. That is to say; hiding is not a trick; equally, managers do not view knowledge hiding as unreliable behavior (Takala and Urpilainen, 1999).

In the 20th century, the main focus of psychologists remained the identification and measurement of personality. They keenly observed and identified personality factors that remain stable with the passage of time and keep the same influence on individuals across time and situations. Researchers always had new ideas and their new ideas compelled them to work hard and explore ever more factors of personality. In the period from 1930 to 1960, they developed a large number of tools that are very helpful for personality assessment and can measure personality traits effectively (Kondratiuk-Nierodzińska, 2016).

The BIG FIVE personality factors are five core personality traits, namely extraversion, neuroticism, conscientiousness, openness to experience, and agreeableness. In this era, personality assessment became more popular in the community of psychologists, and they tried to explore novel aspects of personality assessment. A statistical method of factor analysis was introduced to identify different domains of personality. The name of Raymond Cattell is an important one in the history of the psychology of personality, as he developed a 16 personality factor inventory (Neave et al., 2020). This concluded that personality traits are not only related to normal factors, but also related to psychopathology. Psychological ownership means that employees see the organization as a part of them, and have strong feelings and responsibilities toward the organization, thus motivating employees to take more actions that are beneficial to the organization. Ubaydullaev (2021) explained the supportive or resistive (negative) behavior by employees in the process of organizational change based on the positive and negative effects of psychological ownership. Linkov et al. (2018) analyzed that psychological ownership that is consistent with organizational goals will reduce employees’ psychological conflicts and thus facilitate the reform of enterprises. In the process of enterprise reform, the level of ownership of organizational members will increase as the degree of participation in the change increases, thereby prompting them to adopt behaviors that are conducive to change (Yuan et al., 2021).

The rationale of this research is to explore how psychological ownership mediates between personality traits and knowledge hiding. Key personality traits have been extensively used to investigate differences in person and team behavior. Research by Dawkins et al. (2015) showed that personal factors such as period of service, roles and statutes, age, gender, and personality might psychologically affect the ownership. More research is needed to examine how and to what extent the main personal difference factors may influence psychological ownership. Previous studies have investigated the predictors of psychological ownership, with little attention being paid to the effect of personality characteristics and other important personal factors (Dawkins et al., 2015). The feelings of ownership can increase by having an appropriate personality characteristic that is compliant with different motivations.

The main objective of this study is to understand the role of the BIG FIVE model personality traits in knowledge hiding behavior; and how psychological ownership mediates and social status moderates these relationships.

In this study, the impact of personality variables on knowledge hiding has been checked. Moreover, the mediating role of psychological ownership and the moderating effect of social status has also been examined. This study follows a positivist approach. Avotra et al. (2021b) have defined the positivist approach as research that examines the causes of a variable that affect another variable. In this deductive study, the hypothesis-based theory has been proposed based on the literature review done that is either validated or refused with the help of different analysis techniques. The nature of the study is cross-sectional, i.e., the data is collected once, simultaneously through structured questionnaires. The total number of items used in this study to structure the questionnaire was 37 to do the analysis. The sampling design used for this study is convenient random sampling in which the respondents are approached in accordance with the convenience of availability and accessibility. The population frame for this study was the managerial level employees of corporate organizations of China. The sample size has been obtained based on the number of items used in the questionnaire. A few questions regarding the demographics have also been included in the start of the questionnaire addressing the age, gender, and education of the employees. The technique used for data analysis was Partial least square SEM with the help of the software Smart PLS 3.3.3. Prior studies scales have been used to measure the variables of the current study.

Since this study has used the Smart-PLS software 3.3.3 for the data analysis, there are two main steps involved in structural equation modeling. The first stage calculates the measurement model for the validity and the reliability of the data, while the second stage measures the structural model for hypotheses testing of the relationship developed based on the theoretical framework (Avotra et al., 2021a). In this study, first, the demographic profile of the respondents has been analyzed using frequencies and percentages. The results of a demographic analysis can be seen in Table 1.

This study has three steps in the data analysis. The first step has analyzed the demography of the respondents, the second stage validates the data, and in the third stage, the hypotheses were tested. This study followed the reflective-formative model. In the measurement model assessment, the data was validated using the reliabilities and the validities. The measurement model can be seen in Figure 2.

For the reliabilities, Cronbach alpha and composite reliabilities have been used. On the other hand, in order to validate the results, Fornell and Larcker criteria and heterotrait–monotrait ratio has been used. The cut-off value mentioned in the literature for reliabilities is 0.7 while for validity the average variance extracted (AVE) should be more than 0.5. Both criteria are met in this study as can be seen in Table 2.

Moreover, to further validate the data collected, the HTMT ratio and Fornell and Larcker criterion were also calculated in the study. The values in the Fornell and Larcker should be highest at the top of each column. This can be validated and seen in Table 3 which gives the figures of the Fornell and Larcker test for the validity of the data.

Additionally, the HTMT ratio mentioned in the Table 4 has also validated the data with values around 0.9. The values above 0.9 may indicate the problem of multicollinearity if the reliabilities have not been met. However, this study meets the reliability and validity criteria using Cronbach alpha and composite reliability for reliabilities and Fornell and Larcker criterion and HTMT ratios for validities, hence no issues of multicollinearity may arise as Tables 2–4 illustrate the uniqueness of each variable in measuring their own constructs.

In the second phase of structural equation modeling, the hypotheses developed in the theoretical framework were checked to establish whether they supported the data or not. This phase of SEM includes the direct and indirect relationships. The direct relationships check the direct impact of a variable on another variable. However, in indirect relationships, the mediation of a certain variable is checked against the relationships of two other independent and dependent variables. In this study, the estimation results of beta, t-statistic, p-values, and adjusted R² have been used to accept or reject the hypotheses of the study. The algorithm for the structural model has been added in the study with Figure 3.

These results obtained from the structural model assessment can be seen in Table 5. There were 12 hypotheses in total, of which six hypotheses were accepted while others were rejected. Among the direct relationships hypothesized in this study, only openness to experience did not find any impact on the knowledge hiding t-statistic = 0.922, p-value = 0.357, thus rejecting H₂. However, the rest of the direct relationships were found as significantly having a positive contribution to knowledge hiding. Extroversion was found to be positively and significantly impacting the knowledge hiding with t−statistic = 7.739:p−value = 0.000, accepting H₁. In regard to H₃, conscientiousness was also found to have a significant impact on knowledge hiding t−statistic = 3.927:p−value = 0.000. Furthermore, neuroticism t−statistic = 4479:p−value = 0.000 and agreeableness t−statistic = 2.370:p−value = 0.018, thus supporting the H₄ and H₅ developed from the literature. Psychological ownership also found a significant role in knowledge hiding, t−statistic = 2.244:p−value = 0.025. Among the indirect effects of personality traits with knowledge hiding taking into account the mediation of psychological ownership, none of the relationships could find a significant mediating contribution of psychological ownership except neuroticism t−statistic = 2.035:p−value = 0.042, thus accepting H₁₀. The rejected hypotheses of mediation H₇, H₈, H₉, and H₁₁ were rejected with a small margin of insignificance. Moreover, regarding the moderation effect of social status in the relationship of psychological ownership and knowledge hiding, this could not be statistically approved hence, rejecting H₁₂. These results can be seen in Table 5.

This research aims to evaluate the proposed connection between knowledge hiding and personality traits from the perspective of online learning. In today’s world, information management systems are an integral part of every organization. Information management systems are seen as a channel through which organizations can extract, exchange and use information (Zhu et al., 2018).

It was hypothesized that extroversion has an impact on knowledge hiding. Findings from this study revealed that extraversion strongly predicts knowledge hiding. People who are extroverts can successfully hide their knowledge in online academia (Templer, 2012). The majority of research examining the prevalence of BIG FIVE characteristics in entrepreneur and management populations was conducted between 1960 and 2000 when most of the data was gathered. Because both entrepreneurs and managers can potentially supervise employees and manage various responsibilities, managers are commonly used as a real comparison.

It was also hypothesized that openness to experience has an impact on knowledge hiding. The findings of the study reject this hypothesis. People are open to the experience as they love to share their knowledge with others. It was also hypothesized that consciousness, neuroticism, and agreeableness have an impact on knowledge hiding. The findings of the study revealed that all these personality traits positively predict knowledge hiding. Previous studies also support the findings of this research. Abdellaoui et al. (2019) found that firms are much more open to new experiences, especially considerate, average for openness to experience, less agreeable, and much less emotionally unstable (or in the BIG FIVE lingo, O+, C+, E, A−, N−) in a meta-analysis of 23 research studies from 1970 to 2002 in foreign nations and noted in English-language journal articles.

Numerous investigations have shown that this trend is not always followed. There is evidence to support this, for instance, Kroencke et al. (2020) found that in a survey of 218 business owners and managers in a major Canadian city, employees were less diligent and pleasant than business owners and less extraverted (O+) than business managers. To explain these distinctions between entrepreneurship and the average employee, researchers often use the “attraction–selection–attrition model.” As a result of this model, employees are drawn to jobs whose requirements and possibilities match their innate talent and motivations. At the same time, companies and investors select candidates who meet their criteria. Employees then stay in their area of employment when they discover their professional scenario is more enjoyable than alternative employment options. Entrepreneurs have a greater willingness to learn from mistakes than managers do. Entrepreneurs, according to researchers, are drawn to continually changing environments and innovative problems because of the novelty (Ali et al., 2021). Entrepreneurs’ willingness to take on new problems and work in unique contexts may help individuals who offer innovative solutions, business methods, and goods. As a result, instead of seeking for novel ideas, managers are typically chosen by their bosses for their capacity to carry out and provide consistent, high-quality work with low variation for a particular set of guidelines. Because of this, studies believe that entrepreneurship attracts people who are more willing to try new things. According to Tong (2010) higher conscientiousness is by far the most substantial difference among entrepreneurship. Agreeableness is a combination of a drive for success and the ability to rely on one’s own abilities (Kaur and Anand, 2018). When it comes to dependability, successful entrepreneurs are about the same, but employees come out on top when it comes to accomplishment (Beaty et al., 2016). For example, (Watson et al., 2019) found that entrepreneurs have higher levels of achievement motivation than other workers. Spark and O’Connor (2021) also found that entrepreneurs have higher levels of achievement motivation than managers.

A common theory holds that high achievers prefer working in circumstances where their successes are directly linked with their efforts rather than in a bigger institutional context where commercial accomplishment is less directly linked to one’s own efforts. There is little agreement on whether entrepreneurs have a greater extraversion score than managers. Research suggests extraversion is more crucial for entrepreneurs since they sell their ideas to potential investors, partners, workers, and customers as salesmen. There is, however, no conclusive difference found by Mann et al. (2017) in the research. According to Fang (2017), entrepreneurs are less extroverted than managers, which suggests that many business owners run their small enterprises from their residences to avoid the massive bureaucracy that requires one to be obsessively social. Self-employed people and growth-oriented founders exhibit extremely different qualities depending on how you define an “entrepreneur.” When it comes to cooperativeness and psychoticism (A−, N−), employees tend to score lower than managers on average. According to some theories, entrepreneurs don’t have to worry about impressing others because they will ultimately get to be the executives of their very own companies. In contrast, managers must at the very least, properly respect their superiors.

It was also hypothesized that psychological ownership has an impact on knowledge hiding (Ma et al., 2020). The findings of the study reject this hypothesis. It was also hypothesized that psychological ownership mediates the relationship between extroversion and knowledge hiding. The findings of the study reject this hypothesis. It was also hypothesized that psychological ownership mediates the relationship of openness to experience and knowledge hiding. The findings of the study reject this hypothesis (Butt and Ahmad, 2019). It was also hypothesized that psychological ownership mediates the relationship between conscientiousness and knowledge hiding. The findings of the study reject this hypothesis. It was also hypothesized that psychological ownership mediates the relationship between neuroticism and knowledge hiding. The findings of the study accept this hypothesis. It was also hypothesized that psychological ownership mediates the relationship of agreeableness and knowledge hiding. The findings of the study reject this hypothesis. It was further hypothesized that social status moderates the relationship between psychological ownership and knowledge hiding. The findings of the study reject this hypothesis. Previous studies supported the findings of this research. Differing characteristics were found among self-employed people in recent research, while similar characteristics are being measured among various aspects of entrepreneurship or varying degrees of purpose. All these differences are interesting and policy significant on a macro-level as representations of entrepreneurs against the average individual (Connelly and Zweig, 2015). There were six face-to-face interviews with business owners at companies and 501 evaluations filled out by students at Slovenian academic institutions, resulting in the classification of individuals into four groups: entrepreneurs who are already in business (20% of responses); entrepreneurs who plan to start a business in the next 3 years (9.9%); entrepreneurs who are thinking about starting a company in the market (42.4%); and non-entrepreneurs (the remaining 27.7%). Researchers found variations that mirrored the conceptual findings for openness: businesspeople who are already in business are the most receptive to learning from their mistakes, whereas aspiring entrepreneurs are slightly more closed off. When it comes to agreeableness, small business owners are the least agreeable of all. However, meta-analyses have found no correlation between conscientiousness and agreeableness or psychoticism.

According to Anser et al. (2021), business owners are much more willing to try new things than the general population. However, other characteristics are more difficult to pin down, and the remaining ambiguity can be explained thus. Quantitative measurements, which often only catch a few hundred people, account for much of the diversity across research (Zhai et al., 2021). Meta-analyses are limited because of the influence of environmental factors on the entrepreneurial traits of each community, making cross-population, industry, and cultural generalizations unfeasible. We may be able to distinguish between the clutter of tiny amounts and the real variations in entrepreneurial personality traits across situations if more studies are undertaken, which would be a big accomplishment. An additional criticism of the BIG FIVE framework is that these macro personality traits are overly general, making it difficult to forecast entrepreneurial behavior based on specific situational circumstances. Furthermore, understanding a person’s BIG FIVE character may not assist in knowing the exact mechanism by which their identity influences their entrepreneurship actions and attitudes (Chen et al., 2020).

Owing to this lack of satisfaction and the inability to paint a complete picture of the entrepreneurial human, BIG FIVE researchers turned in developing a 13-dimensional personality framework that includes other traits including consciousness, organizational innovation, locus of control, and the desire to succeed. These are the things we will go through next. Furthermore, it’s not uncommon for this to be done on purpose (Fang, 2017). Information sharing is widely regarded as essential for knowledge refinement, generation, and individual recognition. Ma et al. (2020) found that it is frequently overlooked. According to a study conducted on Chinese skilled professionals, 59% of them engage in information concealment behavior (Neave et al., 2020). The essential principles of organizational learning including “knowledge sharing,” “expertise withholding,” and “expertise stockpiling” must not be overlooked in order to grasp the knowledge concealing architecture. Different organizations have diverse attitudes on the sharing of knowledge. Some people believed that sharing should be discouraged because it could leak company secrets, while others see tremendous value in disseminating information within a company. This term describes the process of exchanging information (knowledge) between people and groups, organizational units, as well as organizations themselves (Beaty et al., 2016). In the absence of information exchange, organizations would be forced to perpetually reinvent themselves to take advantage of previous experiences and expertise they could have used (Connelly and Zweig, 2015). As a part of the information transfer phenomena, they argue that “knowledge concealing,” “information hoarding,” and “information sharing” are all interconnected. The authors characterized a person’s deliberate attempt to conceal or hide information demanded by another person as a knowledge concealment structure (Avotra et al., 2021a). Information holding, a similar notion, differs from information concealing in that an individual might be unable to communicate the knowledge due to error or ignorance in some cases. Whilst some people are more inclined to be chatty, others may have a willingness to give knowledge. There are those who believe that knowledge is power, which they most likely learned in workplaces. These individuals may hoard understanding and be unwilling to share it, which leads to inefficiency and provider separation (Jonason et al., 2017).

There are numerous reasons why knowledge transmitters keep their expertise close to their chests. One issue is the risk of losing market value after putting in years of study and training. As a result, employees have a strong sense of ownership over the gathered knowledge. The second argument is that information sharing is expensive and adds additional responsibilities or burdens to those disseminating the knowledge on top of their usual responsibilities. A third factor is a fear of harboring “knowledge parasites” that have not put in as much work as the potential knowledge sharer has. Fourth, they avoid having their knowledge evaluated by others. Finally, subordinates deliberately hoard information in the belief that superiors dislike knowledgeable subordinates who know more or think they know more than their superiors. On the other hand, Superiors may purposefully withhold information from colleagues to maintain the competitive advantage of authority (Watson et al., 2019). Knowledge concealment is motivated by a variety of factors. Some of them cover personal causes like routine and laziness, whereas cultural aspects are also mentioned (Smith et al., 2021).

Knowledge hiding has been one of the most studied variables in knowledge management. Although knowledge hiding is considered a negative human behavior it is not always harmful. Sometimes individuals hide their knowledge in order to gain some professional advantages over their colleagues, or sometimes for personal interests. However, the role of the nature of the person has been overlooked in literature in understanding the role of knowledge hiding. Therefore, this study has proposed the role of personality traits in the knowledge hiding behaviors of individuals. Among the five traits of the BIG FIVE model of personality, all personality traits except for openness to experience, have been found to have a significant contribution in knowledge hiding behavior. However, the psychological contract is found to mediate only the relationship of neuroticism and knowledge hiding. The significant results show that the attainment of individuals’ inner motives makes them hide their knowledge and exploit it for their best use. Another objective of knowledge hiding is when individuals spend a long time gaining knowledge, they feel reluctant in sharing with others because they tend to feel that they own it as they have spent their valuable years acquiring it. There are many other factors that strongly contribute to knowledge hiding, such as psychological pressure and the workplace environment. In future research, these factors should also be explored from the perspective of knowledge hiding.

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

The studies involving human participants were reviewed and approved by Zhejiang University, China. The patients/participants provided their written informed consent to participate in this study. The study was conducted in accordance with the Declaration of Helsinki.

JW conceived and designed the concept, collected the data, and wrote the manuscript. The author read and agreed to the published version of the manuscript.

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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