The role of overqualification, decision, and mindfulness on knowledge outcomes

ABSTRACT

This study theorizes that perceived over-qualification (POQ) may impact non-knowledge sharing outcomes such as knowledge hoarding and hiding. We cast participation in decision-making (PDM) and mindfulness on these links by exploring the 3-way interaction effects of POQ, PDM, and mindfulness on nurses’ knowledge hoarding and hiding. The research hypotheses were tested using data from a field sample of 379 nurses in Jordan, who responded to an online survey. Results indicate that nurses with high POQ are more likely to exhibit (a) knowledge hoarding and (b) knowledge hiding. Consequently, nurses with high POQ are less likely to exhibit (c) knowledge hoarding when PDM and mindfulness perceptions are high, but not when PDM and mindfulness perceptions are low, and (d) knowledge hiding when PDM and mindfulness perceptions are high, but not when PDM and mindfulness perceptions are low. Implications for the literature and practice are offered.

Keywords:
knowledge; Jordan; over-qualification; decision-making; mindfulness

RESUMO

O presente estudo teoriza que a sobrequalificação percebida (SQP) pode afetar os resultados do não compartilhamento de conhecimento (como nos casos de acumulação e ocultação de conhecimento). Observa-se a participação na tomada de decisão (PTD) e a atenção plena (ATP) (mindfulness) nessa relação, explorando os efeitos da interação em três vias, representadas pela SQP, PTD e ATP na acumulação e ocultação do conhecimento por parte de profissionais de enfermagem. As hipóteses de pesquisa foram testadas usando dados de uma amostra de campo de 379 profissionais de enfermagem da Jordânia, que responderam a uma pesquisa online. Os resultados indicam que enfermeiros com alta SQP são mais propensos a apresentar (a) acumulação e (b) ocultação de conhecimento. Consequentemente, enfermeiros com alta SQP são menos propensos a exibir (c) acumulação de conhecimento quando PTD e ATP são elevadas, mas não quando ambas são baixas, e (d) ocultação de conhecimento quando PTD e ATP são altas, mas não quando ambas são baixas. O artigo oferece ainda implicações para a literatura e a prática no campo.

Palavras-Chave:
conhecimento; Jordânia; sobrequalificação; tomada de decisão; atenção plena

RESUMEN

El presente estudio teoriza que la POQ puede afectar los resultados del no intercambio de conocimientos (como el acaparamiento y el ocultamiento de conocimientos). Proyectamos la participación en la toma de decisiones (PDM) y la atención plena (ATP) ‒mindfulness‒ en estos vínculos mediante la exploración de los efectos de una interacción de tres vías representadas por la POQ, PDM y ATP en el acaparamiento y la ocultación de conocimientos por parte de los profesionales de enfermería. Probamos nuestras hipótesis utilizando una muestra de campo de 379 profesionales de enfermería, en Jordania, que respondieron a una encuesta online. Los resultados indican que los respondientes con alta POQ tienen más probabilidades de exhibir conductas de (a) acaparamiento de conocimientos y (b) ocultación de conocimientos. En consecuencia, los profesionales de enfermería con una alta POQ tienen menos probabilidades de exhibir conductas de (c) acaparamiento de conocimientos cuando las percepciones de PDM y ATP son altas, pero no cuando ambas son bajas, y (d) ocultación de conocimientos cuando las percepciones de PDM y ATP son altas, pero no cuando ambas son bajas. Este estudio ofrece, asimismo, implicaciones para la literatura y la práctica.

Palabras clave:
conocimiento; Jordania; sobrecualificación; toma de decisiones; atención plena

INTRODUCTION

The COVID-19 pandemic has overwhelmed health institutions, increasing labor shortage, stress, and pressure on front-line workers while on the job (Alnazly, Khraisat, Al-Bashaireh, & Bryant, 2021). This has been offset by the urgent need for medical professionals to return to work after retirement or career breaks and the recruitment of new healthcare professionals, including nurses. The Jordanian government and private health institutions had to recruit new nurses and healthcare workers, and they have asked retired ones to return to work to meet the growing demand (Algunmeeyn, El-Dahiyat, Altakhineh, & Azab, 2020; Al-Khalidi, 2020). This recruitment and return strategy provided some relief for healthcare institutions and incumbent health professionals, but it also brought several pressing issues to the fore, such as perceived over-qualification (POQ) among nurses and healthcare professionals. POQ is a situation in which nurses’ qualifications—such as education, work experience, and skills—exceed those required for the job (Erdogan & Bauer, 2009; Maynard, Joseph, & Maynard, 2006). POQ has been associated with a reduced job and life satisfaction, a reduction in organizational commitment (Erdogan, Karaeminogullari, Bauer, & Ellis, 2020; Wassermann & Hoppe, 2019; Zheng & Wang, 2017), and increased withdrawal and turnover intentions (Erdogan & Bauer, 2009; Maynard & Parfyonova, 2013). Knowledge management and sharing are lifelines for operational excellence (Asurakkody & Kim, 2020; Vignochi, Goncalo, & Lezana, 2014), and past research mostly emphasizes health professionals’ knowledge sharing and dissemination (Anselmann & Mulder, 2020; Li-Ying, Paunova, & Egerod, 2016). Unfortunately, non-sharing behaviors such as knowledge hiding and hoarding are underexplored in the health sector, especially concerning nurses. Unlike knowledge sharing, knowledge hiding, and hoarding is a strategy devised to withhold knowledge from others for a variety of reasons, including distrust, time constraints, power loss, and status protection within an organization (Connelly & Zweig, 2015; Holten, Hancock, Persson, Hansen, & Høgh, 2016).

Mindfulness is a novel attribute that helps increase resilience among workers, which is believed to assist in avoiding falling prey to undesirable feelings at work, such as burnout, hurt feelings, negativity, and the like (Anasori, Bayighomog, & Tanova, 2020; Bajaj, Gupta, & Pande, 2016). Besides its direct mitigating role, mindfulness is a novel trait that has proven to be a strong buffer against undesirable work outcomes (Anasori et al., 2020; Daubenmier, Hayden, Chang, & Epel, 2014). Several studies noted that employees’ participation in decision-making (PDM) enhances positive feelings and facilitates empowerment, job satisfaction, employee control, and innovation (Cheng, Song, & Li, 2017; Da’as, 2019). Ding and Shen (2017) recommend additional investigation into the moderating role of PDM. Goñi-Legaz and Ollo-López (2017) documented that PDM increases job satisfaction and buffers the negative effects associated with job satisfaction in temporary contracts. Building on extant discussions, the research argues that mindfulness and PDM may buffer the adverse effects of POQ on hiding and hoarding behaviors. The contributions in this paper are four-folds. First, this work moves beyond the predominant linking of POQ with desired organizational outcomes, such as knowledge sharing, by linking it with knowledge hiding and hoarding behaviors. Technically, this paper extends and provides further evidence on inconclusive findings concerning POQ literature on nurses and other healthcare professionals. Second, this paper contributes to the literature by recognizing the importance of participation and mindfulness within POQ boundaries, shifting the principal focus beyond job autonomy (Ding & Shen. 2017; Goñi-Legaz & Ollo-López, 2017; Wu, Luksyte, & Parker, 2015) and toward the combination of internal personal resources (i.e., mindfulness) and external work resources (i.e., PDM). Third, existing POQ arguments and empirical evidence are mostly in other sectors (Erdogan et al., 2020; Maynard & Parfyonova, 2013; Triana, Trzebiatowski, & Byun, 2017; Wassermann & Hoppe, 2019); this work contributes from the lens of nursing management and HR practices. Last, there are several theoretical propositions stating that boundary conditions matter when it comes to the causal relationship of POQ and work outcomes. This paper is novel in that it proposes a three-way interaction effect of POQ, PDM, and mindfulness on knowledge hiding and hoarding. In doing so, we have responded to a call for contextual factors in research offered by (Erdogan et al., 2020; Wu et al., 2015), from both a theoretical and practical point of view.

LITERATURE REVIEW AND HYPOTHESES

Perceived over-qualification, knowledge hiding, and hoarding behaviors

Nurses’ and healthcare workers’ knowledge of how their knowledge, skills, and abilities (KSAs) outweigh the demands of their work is referred to as perceived over-qualification (Erdogan & Bauer, 20 09). Perceived over-qualification (POQ) creates a type of underemployment where “the individual has surplus skills, knowledge, abilities, training, experience and other qualifications that are not required by or utilized on the job” (Erdogan, Tomás, Valls, & Gracia 2018, p. 217). The conceptualization of over-qualification is twofold: objective and perceived over-qualification. The former is the more objective, fair, and unbiased form of assessment, whereas the latter is completely subjective. Nurses’ qualifications (e.g., KSAs) are compared to requirements stated in the job description to determine objective over-qualification (Martinez, Lengnick-Hall, & Kulkarni, 2014), while nurses’ personal opinions about their underutilization are referred to as POQ (Erdogan et al., 2018). Over-qualification can be assessed objectively by managers and decision-makers, and as such, has fewer attitudinal and behavioral consequences as opposed to perceived over-qualification. Several studies documented that POQ is a source of undesired work outcomes (Maynard & Parfyonova, 2013). Despite ample empirical claims, the literature is undercooked alongside mixed results and assumptions on the consequences of POQ. Some scholars purport that POQ enhances withdrawal behaviors (Triana et al., 2017) and knowledge sharing (Zhang, Li, & Cao, 2017). Others suggest that POQ reduces extra-role behaviors (Erdogan et al., 2020), life satisfaction (Wassermann & Hoppe, 2019), commitment, and job performance (Zheng & Wang, 2017). Knowledge hiding and hoarding are particularly virulent forms of reluctance to share knowledge in the workplace (Connelly, Zweig, Webster, & Trougakos, 2012; Holten et al., 2016). Knowledge hiding and hoarding behaviors embody the cessation of the nurses, filtering the knowledge to share or withholding information from their peers. These are distinct concepts with theoretical and empirical evidence. Connelly et al. (2012) denoted that scope, request, and intentionality are distinguishing factors between hiding and hoarding.

• I. Knowledge hoarding is a less-intentional type of concealment as only unrequested knowledge is concealed from others, while hiding is an intentional type of concealment, where both requested and unrequested knowledge is concealed from others (Connelly & Zweig, 2015; Holten et al., 2016).

• II. Knowledge hoarding has a smaller behavioral scope than knowledge hiding (Connelly & Zweig, 2015; Holten et al., 2016).

• III. Knowledge hoarding is comprised of facets of the knowledge that are not necessarily explicit or known to others, thereby limiting the seekers’ ability to know or make requests, yet this is essential for organizational success and performance (Evans, Hendron, & Oldroyd, 2014).

The reasons for knowledge hiding and hoarding by members of an organization include safeguarding personal competence, an unwillingness to invest time, fear of knowledge parasites, the avoidance of exposure and power control, injustices, mistreatment in the workplace, and poor-quality work relationships (Abubakar, Behravesh, Rezapouraghdam, & Yildiz, 2019; Aljawarneh, Alomari, Alomari, & Taha, 2020; Connelly, Černe, Dysvik, & Škerlavaj, 2019; Connelly & Zweig, 2015; Holten et al., 2016). In the context of this study, overqualifed nurses are likely to develop negative feelings toward their peers and distance themselves in an elitist manner. Past discoveries showed quitting as a final resort to resolving a poor ft, synonymous with POQ (Follmer, Talbot, Kristof-Brown, Astrove, & Billsberry, 2018). Superior knowledge grants nurses an advantage, which explains the motive to withhold information for personal gain to avoid potential losses and maintain relative status as compensation for their ill-ftting placement (Li, Liao, & Han, 2021). Nurses with high POQ are less willing to put forth their best efforts in collaboration and information sharing due to the perception of being under-rewarded or under-recognized. Thus, they conceal knowledge from others to showcase and portray ownership of their superior and valuable skills.

• H1: Perceived over-qualification will positively influence knowledge hoarding among nurses.

• H2: Perceived over-qualification will positively influence knowledge hiding behavior among nurses.

Moderating role of participation in decision-making and mindfulness

Conventionally, mindfulness has been portrayed as “the clear and single-minded awareness of what actually happens to us and in us at the successive moments of perception” (Thera, 1972, p. 5), or as “keeping one’s consciousness alive to the present reality” (Hanh, 1976, p. 11). Mindfulness depicts one’s cognizance of internal and external affairs and events as phenomena, “rather than as the objects of a conceptually constructed world” (Olendzki, 2005, p. 253). In essence, mindfulness permits an “immediacy of direct contact with events as they occur, without the overlay of discriminative, categorical, and habitual thought, consciousness takes on a clarity and freshness that permits more flexible, more objectively informed psychological and behavioral responses” (Brown, Ryan, & Creswell, 2007, p. 215). Mindfulness, described as one’s conscious attention to the environment and present moment (Brown & Ryan, 2003), is an individual attribute that can influence how individuals are affected by negative environments.

The central aim of involving employees in decision-making is to gain from the knowledge, know-how, and skills of employees in modern organizations. Participation in decision-making (PDM) is a process whereby planning, problem-solving, and related activities are carried out jointly with managers and employees (Valoyi, Lessing, & Schepers, 2000) in the form of organizational democratic values designed to promote equity, shared responsibility in making decisions, and joint governance with superiors and subordinates to improve organizational goals (Behravesh, Abubakar, & Tanova, 2020). Not only does PDM grant workers direct control, but it also puts forth a discretionary effort, resulting in superior performance (Sun, Aryee, & Law, 2007). It is also important to note that participation does not always motivate, nor does a lack of participation always demotivate (Valoyi et al., 2000). Past work found that PDM has buffering capability toward unwanted work outcomes (Ding & Shen, 2017; Goñi-Legaz & Ollo-López, 2017). Shared decision-making among healthcare workers has produced positive work outcomes in various countries (Joseph-Williams et al., 2017; Rodrigues, Barrichello, & Morin, 2016). It can be argued that allowing employees to exert some level of influence on work processes and decisions enhances positivity, commitment, innovation, satisfaction, and information sharing and collaboration (Aslam, Muqadas, & Imran, 2018; Cheng et al., 2017; Da’as, 2019). On the other hand, job autonomy can buffer the negative effects of over-qualification on employee well-being in European countries, and the authors recommend testing other buffers on similar relationships in non-Western countries, such as Jordan (Wu et al., 2015). Several researchers argued that identifying moderators addressing the repercussions of POQ on attitude and behavior (Erdogan et al., 2020; Erdogan & Bauer, 2009; Wu et al., 2015) ensures organizations take advantage of employees’ POQ. Sesen and Ertan (2019) also suggested buffering factors reducing POQ are required. We, therefore, respond to the call for more research on theory‐based moderators by combining PDM and mindfulness as buffers on the link between POQ and knowledge hiding and hoarding.

• H3: Employee participation in decision-making and mindfulness moderates the relationship between perceived over-qualification and knowledge hiding among nurses.

• H4: Employee participation in decision-making and mindfulness moderates the relationship between perceived over-qualification and knowledge hoarding among nurses.

Figure 1.
Hypothesized research model

METHODOLOGY

Research instruments

The research model is comprised of fve distinct constructs adapted from past studies and operationalized to fulfll the objectives of this study. The constructs, sources, and scales are described in the succeeding paragraphs. Perceived over-qualification (POQ) was measured using the Maynard et al. (2006) nine-item scale. Participation in decision-making (PDM) was measured using the Sun et al. (2007) four-item scale. knowledge hiding behavior (KHB) was measured using the Connelly et al. (2012) twelve-item scale with sub-dimensions (evasive hiding, rationalized hiding, and playing dumb). Knowledge hoarding (KHR) was measured using the Evans et al. (2014) four-item scale. Participants evaluated the extent of their hoarding behaviors and experiences. Mindfulness (MND) was measured using the Brown and Ryan (2003) fifteen-item scale. Employees’ states of mindfulness were generated by reverse scoring the items prior to analysis. Demographic information of participating nurses—such as gender, age, educational level, organizational tenure, and type of health institution (i.e., private or public)—were also obtained. This information was used as control variables during the analysis. POQ, PDM, and knowledge hoarding and hiding were anchored using a seven-point scale, where 1=strongly disagree, and 7=strongly agree, while MND was anchored on a six-point scale, where 1=almost never and 6=almost always. The survey items are shown in Exhibit 1.

Exhibit 1.
Survey items

Perceived overqualification
1. “My job requires less education than I have”
2. “The work experience that I have is not necessary to be successful on this job”
3. “I have job skills that are not required for this job”
4. “Someone with less education than myself could perform well on my job”
5. “My previous training is not being fully utilized on this job”
6. “I have a lot of knowledge that I do not need in order to do my job”
7. “My education level is above the education level required by my job”
8. “Someone with less work experience than myself could do my job just as well”
9. “I have more abilities than I need in order to do my job”

Knowledge hoarding
1. “I keep news about what I am doing secret from others until the appropriate time”
2. “I avoid releasing information to others in order to maintain control”
3. “I control the release of information in an efort to present the profle I want to show”
4. “Information is a resource that needs to be carefully guarded”

Knowledge hiding
Evasive hiding
1. “Agreed to help him/her but never really intended to”
2. “Agreed to help him/her but instead gave him/her information diferent from what s/he wanted”
3. “Told him/her that I would help him/her out later but stalled as much as possible”
4. “Ofered him/her some other information instead of what he/she really wanted”
Playing dumb
1. “Pretended that I did not know the information”
2. “Said that I did not know, even though I did”
3. “Pretended I did not know what s/he was talking about”
4. “Said that I was not very knowledgeable about the topic”

Knowledge hiding
Rationalized hiding
1. “Explained that I would like to tell him/her, but was not supposed to”
2. “Explained that the information is confdential and only available to specific people”
3. “Told him/her that my boss would not let anyone share this knowledge”
4. “Said that I would not answer his/her questions”

Participation in decision-making
1. “Employees in this job are often asked by their supervisor to participate in decisions”
2. “Individuals in this job are allowed to make decisions”
3. “Employees are provided the opportunity to suggest improvements in the way things are done”
4. “Supervisors keep open communications with employees in this job”

Mindfulness -
1. “I could be experiencing some emotion and not be conscious of it until sometime later”
2. “I break or spill things because of carelessness, not paying attention, or thinking of something else”
3. “I find it dificult to stay focused on what’s happening in the present”
4. “I tend to walk quickly to get where I’m going without paying attention to what I experience along the way”
5. “I tend not to notice feelings of physical tension or discomfort until they really grab my attention”
6. “I forget a person’s name almost as soon as I’ve been told it for the first time”
7. “It seems I am “running on automatic” without much awareness of what I’m doing”
8. “I rush through activities without being really attentive to them”
9. “I get so focused on the goal I want to achieve that I lose touch with what I am doing right now to get there”
10. “I do jobs or tasks automatically, without being aware of what I’m doing”
11. “I find myself listening to someone with one ear, doing something else at the same time”
12. “I drive places on “automatic pilot” and then wonder why I went there”
13. “I find myself preoccupied with the future or the past”
14. “I find myself doing things without paying attention”
15. “I snack without being aware that I’m eating”

Sampling and data collection method

The adapted research instruments were originally in English, and since most Jordanian nurses use official Arabic to carry out their duties, researchers translated instruments from English to Arabic with the help of professional translators, who employed a back-translation technique. To ensure the correctness of the translation regarding language and cultural cues, a pretest with 20 nurses showed that the instruments were clear and free of ambiguities. The research sample was obtained using a probabilistic approach, so each nurse in the population of interest was identifed and had an equal chance of being included in the sample. This sampling approach is known as the simple random sampling technique. Participants were asked not to disclose their identities to reduce the potency of common method bias (CMB), highlighted by Podsakoff, MacKenzie, and Podsakoff (2012). An online survey was used to increase the nurses’ perception of anonymity. The survey link was sent via email and other outlets, such as WhatsApp groups, by HR officers. According to The Hashemite Kingdom of Jordan Ministry of Health (2019), there were registered nurses (25,326), associate degree nurses (4,783), and assistant nurses (1,713). In total, 17 hospitals participated in the study (eight private and nine public), and a total of 379 usable responses were retrieved. The obtained sample size appeared to be adequate, given the population and sampling methodology.

Choice for analytical methods

Partial least squares structural equation modeling (PLS-SEM) is a method to deal with and handing models with constructs in formative and reflective format, respectively. Unlike covariance-based structural equation modeling (CB-SEM), PLS-SEM can work with both small and large sample sizes and non-normal data, and its statistical assumptions are not strict compared to CB-SEM. Prediction-oriented PLS-SEM evaluation is not susceptible to model misspecification; it is also fruitful for exploring relationships with weak theoretical foundations (Hair, Hult, Ringle, & Sarstedt, 2016; Henseler, Ringle, & Sarstedt, 2015). These assets of PLS-SEM make it suitable for studying model variables. We examine the estimated parameters in the research models with the help of SmartPLS and Hayes’s Process Macro applications on a two-step approach: (1) a measurement model for the suitability and validity and/or reliability of the instruments, and (2) a hypothesized model for causational inference of the three-way interaction affects, as this technique is not available in SmartPLS.

ANALYSIS AND RESULTS

Information about the sample

The participants’ information is described as follows: 45.9% are male nurses, and 54.1% are female nurses. Approximately 12.7% are within the 21 and 30 age group, 54.1% are within the 31 and 40 age group, 26.9% are within the 41 and 50 age group, and the rest are above 50 years old. Approximately 12.7% have diplomas, 60.4% have bachelor’s degrees, and 26.9% have postgraduate degrees. Approximately 12.4% have been working for less than four years, 39.3% have been working for between fve and nine years, and 48.3% have been working for more than ten years. Finally, 53.6% work in public hospitals, and 46.4% work in private hospitals.

Measurement model

As a first step, we sufficiently evaluated the measurement model in terms of the scale items’ factor loadings and significance levels based on the 0.50 and 1.960 thresholds (see Table 5 for details). In essence, we removed the scale items having a low/cross-loading, and the average variance extracted (AVE) for each variable was within the 0.50 threshold (Hair et al., 2016; Henseler et al., 2 015 ). Next, the internal consistency reliability of the constructs was evaluated using Cronbach’s alpha (Cα) and composite reliability (CR) indicators. As Table 1 reports, the estimates were above the 0.70 benchmarks for Cα and CR, respectively. These results demonstrate the existence of convergent validity and construct reliability. Following that, we looked at the discriminant validity; AVE-value square roots should be greater than the correlation estimates in a model with discriminant validity (Fornell & Larcker, 1981) after comparing the AVE-value square roots for constructs with the correlation estimate between them. In Table 1, the AVE-value square roots (the diagonal value) are greater than the correlation estimates (lower triangular matrix) (Hair, Sarstedt, Ringle, & Gudergan, 2017). As Table 1 reports, the newly introduced heterotrait-monotrait ratio of correlations (HTMT) for discriminant validity were evaluated, and the correlation estimates (upper triangular matrix) were all below the 0.90 benchmarks (Henseler et al., 2015). These results demonstrate the non-existence of discriminant validity.

Table 5.
Measures descriptive statistics

	O	M	SD	t	ρ
POQ1 ‹- POQ	0.820	0.820	0.019	42.865	0.000
POQ2 ‹- POQ	0.718	0.720	0.029	24.769	0.000
POQ3 ‹- POQ	0.810	0.810	0.022	37.513	0.000
POQ4 ‹- POQ	0.852	0.853	0.014	62.265	0.000
POQ5 ‹- POQ	0.731	0.731	0.029	24.807	0.000
POQ6 ‹- POQ	0.805	0.805	0.025	32.731	0.000
POQ7 ‹- POQ	0.859	0.859	0.017	50.406	0.000
POQ8 ‹- POQ	0.839	0.840	0.019	44.504	0.000
POQ9 ‹- POQ	0.762	0.764	0.034	22.584	0.000
PDM1 ‹- PDM	0.762	0.757	0.051	14.881	0.000
PDM2 ‹- PDM	0.819	0.816	0.037	22.385	0.000
PDM3 ‹- PDM	0.834	0.831	0.038	21.849	0.000
PDM4 ‹- PDM	0.857	0.852	0.028	30.098	0.000
MND1 ‹- MND	[*]
MND2 ‹- MND	[*]
MND3 ‹- MND	0.741	0.742	0.027	27.664	0.000
MND4 ‹- MND	0.627	0.626	0.039	15.919	0.000
MND5 ‹- MND	0.747	0.747	0.028	27.138	0.000
MND6 ‹- MND	0.620	0.618	0.047	13.054	0.000
MND7 ‹- MND	0.752	0.753	0.029	26.090	0.000
MND8 ‹- MND	0.796	0.797	0.028	28.441	0.000
MND9 ‹- MND	0.729	0.726	0.031	23.323	0.000
MND10 ‹- MND	0.841	0.841	0.016	53.142	0.000
MND11 ‹- MND	[*]
MND12 ‹- MND	[*]
MND13 ‹- MND	0.701	0.698	0.036	19.401	0.000
MND14 ‹- MND	0.735	0.734	0.030	24.817	0.000
MND15 ‹- MND	[*]
KHR1 ‹- KHR	0.876	0.876	0.015	57.113	0.000
KHR2 ‹- KHR	0.927	0.926	0.010	92.263	0.000
KHR3 ‹- KHR	0.916	0.915	0.012	78.694	0.000
KHR4 ‹- KHR	0.780	0.780	0.038	20.776	0.000
KHB1 ‹- KHB	0.707	0.706	0.035	20.386	0.000
KHB2 ‹- KHB	0.799	0.799	0.022	36.191	0.000
KHB3 ‹- KHB	0.891	0.890	0.015	60.736	0.000
KHB4 ‹- KHB	0.824	0.823	0.020	42.124	0.000
KHB5 ‹- KHB	0.930	0.930	0.010	89.621	0.000
KHB6 ‹- KHB	0.907	0.907	0.009	104.715	0.000
KHB7 ‹- KHB	0.937	0.937	0.006	170.369	0.000
KHB8 ‹- KHB	0.889	0.889	0.012	75.039	0.000
KHB9 ‹- KHB	0.873	0.874	0.014	64.641	0.000
KHB10 ‹- KHB	0.839	0.839	0.018	46.207	0.000
KHB11 ‹- KHB	0.846	0.846	0.014	62.630	0.000
KHB12 ‹- KHB	0.790	0.789	0.021	36.949	0.000
Information:O=Original Sample; M=Sample Mean; SD = Standard Deviation; t=T-Statistics; ρ=P-Values; [*] = Excluded Measures

• Source: Prepared by the authors from data obtained from the Smart PLS software (2022).

Table 1.
Measurement model matrix

	Variables	Cα	Rho	CR	AVE	1	2	3	4	5
1	POQ	0.93	0.94	0.94	0.64	0.80	0.18	0.14	0.32	0.49
2	PDM	0.84	0.87	0.89	0.67	-0.14	0.82	0.41	0.09	0.25
3	MND	0.90	0.92	0.92	0.54	-0.12	0.37	0.73	0.23	0.46
4	Knowledge hoarding	0.90	0.93	0.93	0.77	0.32	-0.03	-0.21	0.88	0.59
5	Knowledge hiding	0.97	0.97	0.97	0.73	0.49	-0.23	-0.44	0.55	0.86
Information: Cα = Cronbach’s alpha; CR= composite reliability index; AVE= average variance extracted. Lower triangular matrix is the Fornell-Larcker criterion coefficients. Upper triangular matrix is the HTMT coefficients. Middle bold value is the square root of AVE

• Source: Prepared by the authors from data obtained from the Smart PLS software (2022).

As a popular multi-collinearity indicator, variance infation factors (VIF) measure the extent to which the variance of a predictor on a response variable is infated by other predictors. As Table 2 reports, the issue of multi-collinearity is dismissed, given that VIF were less than fve. CMB was tested statistically using the Harman one-factor test, where the explained variance for combined factors is expected to be less than 50%. We found that the combined factors only explained 34.5% of the variance, dismissing the threat of CMB (Podsakoff et al., 2012).

Table 2.
Collinearity information

	Predictor Variables	Knowledge hoarding	Knowledge hiding
1	POQ	1.025	1.025
2	PDM	1.171	1.171
3	MND	1.164	1.164
Information: VIF values

• Source: Prepared by the authors from data obtained from the Smart PLS software (2022).

Hypothesized model

After establishing the reliability and validity of the measurement model, latent variable scores were obtained from SMARTPLS software at the end of measurement model testing. The research model was tested using Hayes’s Process Macro Model-3 with 5,000 bootstrap runs. The test for the three-way interaction effect was administered following experts’ suggestions (Aiken, West, & Reno, 1991). Control variables—such as gender, age, educational level, tenure, and type of organization (i.e., private or public hospitals)—were entered into the equation alongside the main predictors: POQ, PDM, and mindfulness and their interaction terms.

DISCUSSION

Research findings

The findings are presented in Tables 3 and 4. For the main direct effects, POQ exerted positive and significant effects on knowledge hoarding (β = 0.32; t = 5.93; ρ < 0.01) and knowledge hiding (β = 0.41; t = 9.77; ρ <0.01). This suggests that nurses who perceive themselves as overqualifed are prone to hoard and hide knowledge from other nurses. Simply, a one-unit increase in POQ results in a 0.32 unit increase in knowledge hoarding and a 0.41 unit increase in knowledge hiding. These findings support hypotheses H1 and H2. As shown in Table 3, results revealed a three-way interaction between POQ, PDM, and mindfulness toward knowledge hoarding (ΔR²=0.03; F=13.47; df1=1.00; df2=366.00; p<0.01), significant with (β = -0.16; t = -3.67; ρ < 0.01). The results showed that a high PDM and mindfulness buffers the positive relationship between POQ and knowledge hoarding. When POQ is high, lower levels of knowledge hoarding occur when both PDM and mindfulness are high. This finding supports hypothesis H3. Figure 2 shows the nature of the interactions.

Table 3.
The 3-way interaction effects on knowledge hoarding

Predictor(s)	Coefficient	SE	t-value	p-value	LLCI	ULCI
Constant	-0.95	0.33	-2.91	0.00	-1.60	-0.31
Gender	0.60	0.10	5.91	0.00	0.40	0.81
Age	0.41	0.08	5.00	0.00	0.25	0.57
Education	-0.01	0.08	-0.11	0.91	-0.16	0.15
Tenure	-0.27	0.09	-3.06	0.00	-0.45	-0.10
Hospital type	-0.17	0.10	-1.62	0.11	-0.37	0.04
POQ	0.32	0.05	5.93	0.00	0.22	0.43
PDM	-0.08	0.06	-1.34	0.18	-0.19	0.04
MND	-0.09	0.05	-1.66	0.10	-0.19	0.02
POQ*PDM	0.02	0.06	0.32	0.75	-0.09	0.13
POQ*MND	0.10	0.05	1.81	0.07	-0.01	0.20
PDM*MND	0.01	0.04	0.32	0.75	-0.07	0.10
POQ*PDM*MND	-0.16	0.04	-3.67	0.00	-0.25	-0.07

Information:
F statistics = 11.87
R squared = 0.28
Significance = 0.01
SE= standard error
LLCI = lower level confdence interval
ULCI = upper level confdence interval

• Source: Prepared by the authors from data obtained from the Smart PLS software (2022).

Table 4.
The 3-way interaction effects on knowledge hiding

Predictor(s)	Coefficient	SE	t-value	p-value	LLCI	ULCI
Constant	-0.34	0.25	-1.34	0.18	-0.84	-0.16
Gender	0.27	0.08	3.42	0.00	0.12	0.43
Age	0.40	0.06	6.30	0.00	0.27	0.52
Educação	-0.26	0.06	-4.31	-0.00	-0.38	0.14
Tenure	0.40	0.07	-5.79	0.00	-0.54	-0.26
Hospital type	0.38	0.08	4.81	0.00	0.23	0.54
POQ	0.41	0.04	9.77	0.00	0.33	0.50
PDM	-0.03	0.04	-0.62	0.53	-0.11	0.06
MND	-0.24	0.04	5.73	0.00	-0.32	0.16
POQ*PDM	0.04	0.04	0.87	0.38	-0.05	0.13
POQ*MND	0.08	0.04	1.96	0.05	-0.00	0.16
PDM*MND	-0.07	0.03	-2.20	0.03	-0.14	0.01
POQ*PDM*MND	-0.08	0.03	-2.47	0.01	-0.15	-0.02

Information:
F statistics = 39,77
R squared = 0.57
Significance = 0.01
SE= standard error
LLCI = lower level confdence interval
ULCI = upper level confdence interval

• Source: Prepared by the authors from data obtained from the Smart PLS software (2022).

Figure 2.
A 3-way interaction plot on knowledge hoarding

As shown in Table 4, the results revealed a three-way interaction between POQ, PDM, and mindfulness toward knowledge hiding (ΔR²=0.01; F=6.08; df1=1.00; df2=366.00; ρ < 0.01), significant with (β = -0.08; t = -2.47; ρ < 0.01). The results showed that a high PDM and mindfulness buffer the positive relationship between POQ and knowledge hiding. When POQ is high, lower levels of knowledge hiding occur when both PDM and mindfulness are high. This finding supports hypothesis H4. Figure 3 shows the nature of the interactions.

Figure 3.
A 3-way interaction plot on knowledge hiding

A sizeable portion of health professionals thinks they are overqualifed for their roles. POQ has been labeled problematic with varied consequences (Erdogan et al., 2020). HR scholars are challenged with identifying potential buffers to reduce the ill consequences of POQ. As a new and unstudied phenomenon, little is known about the nexus between POQ, PDM, and mindfulness regarding knowledge outcomes such as hoarding and hiding amidst the COVID-19 pandemic at the outset of this research. This paper flls the void in the literature by examining the three-way interaction effects between POQ, PDM, and mindfulness on knowledge hoarding and hiding. For Hypotheses 1 and 2, this work found that POQ has a positive and significant effect on knowledge hoarding and hiding behaviors. This means that when nurses perceive they are overqualifed, they are more likely to hoard and hide knowledge from their peers, including requested (i.e., knowledge hiding) and unrequested (i.e., knowledge hoarding) knowledge. POQ has been shown to have a positive impact on knowledge sharing (Erdogan et al., 2020; Zhang et al., 2017) and knowledge hiding (Li et al., 2021). In line with work in other cultural settings, this work extends by showing that POQ is a predictor for increased knowledge hoarding and hiding behaviors amongst nurses in Jordan. The liberal cultural orientation of Jordanians as opposed to other Arabian nations plays a key role in the findings. Hypothesis 3 suggests that the impact of POQ on knowledge hoarding varies by the degree of PDM and mindfulness. The findings support this prediction by suggesting that when nurses perceive they are overqualifed, they tend to have contempt for less qualifed nurses, exhibited by the hoarding of knowledge. However, the impact is lesser when PDM and mindfulness are high, such that the overqualifed nurses are less sensitive to POQ due to their PDM and mindfulness. Hypothesis 4 suggests the impact of POQ on knowledge hiding varies by the degree of PDM and mindfulness. The findings support this prediction by suggesting that when nurses perceive they are overqualifed nurses, they are more likely to have contempt for less qualifed nurses, exhibited by the hiding of knowledge. Prior research noted that more qualifed and overqualifed individuals are less likely to share knowledge with less qualifed counterparts (Erdogan et al., 2020), and they might take matters to greater lengths by intentionally hiding knowledge (Li et al., 2021). To expand and complement past work, this research shows the possibility of the interaction effects of PDM and mindfulness on the link between POQ and knowledge hiding and POQ and knowledge hoarding.

Theoretical and managerial implications

The results of this study contribute to POQ and the nursing HR literature in several ways. First, this work contributes to the POQ research stream by focusing on the non-knowledge sharing perspective. In doing so, we identifed two related yet distinct consequences. Although a few works have linked POQ with counterproductive behaviors (Maynard & Parfyonova, 2013; Triana et al., 2017; Wassermann & Hoppe, 2019), to our knowledge, this is the first study to look at knowledge hoarding and hiding simultaneously. Our results have shown that POQ is associated with high knowledge hoarding and hiding. This is important as it expands the current knowledge of POQ consequences and may help healthcare organizations manage nurses’ POQ. Linking POQ with knowledge hoarding and hiding offers a more complex picture, specifically in the Arabian cultural context. This new proposition opens future avenues for conducting an even deeper investigation into POQ effects on non-sharing domains such as knowledge sabotage and interactions with other resourceful concepts. This study also contributes to POQ theory via the three-way interaction effects. Research on potential buffers of POQ on work outcomes is sparse (Alfes, Shantz, & Baalen, 2016). This research developed and tested an empirical model that shows the relevance of PDM and mindfulness in reducing the undesired outcomes of POQ. This research adds to the POQ theoretical framework by identifying conditions attenuating the effects of POQ on work-related outcomes. It is also noteworthy that we have utilized the three-way interaction effects to unveil the proposed associations, as past work mostly tested the effects of two-way interactions (see Alfes et al., 2016; Wu et al., 2015).The results contribute to practice in several ways. The COVID-19 pandemic has created a catastrophe in the healthcare sector; specifically, the Jordanian government and private healthcare institutions have either recruited new nurses or called back retired ones to join their efforts with the incumbent nurses when battling the virus. Unfortunately, the majority of healthcare institutions have HR practices stressing the importance of hiring nurses and healthcare professionals with specific KSAs; this emphasis is mostly highlighted during the recruitment and selection stages. The results of this study illustrate that managers need to consider the KSAs of existing nurses because having a team of nurses with varying KSAs can be problematic given the accrued tendencies of knowledge hoarding and hiding behaviors. Our findings suggest that managers cannot avoid hiring nurses with varying levels of KSAs because more-skilled nurses can bring benefits to the organization. Managing such skills should be prioritized by positioning HR practices so they nourish employees’ PDM. Furthermore, nurses should be counseled on how to develop mindfulness, as such abilities can increase their desire to share knowledge with less-qualifed peers. Finally, nurses cannot be forced to share knowledge; thus, more qualifed nurses may hold negative emotions with respect to the less-qualifed ones. To avoid such situations, managers are encouraged to create an atmosphere characterized by mentor-protégé relationships in the form of PDM. If so, overqualifed or more qualifed nurses will be less likely to hoard or hide knowledge because of the accrued joy and sense of accomplishment in seeing their protégés develop as professionals.

Limitations and further research propositions

The research findings should be viewed with caution due to limitations such as self-reported data, cross-sectional design, and sampling technique. Our recommendation to scholars is to source alternative data rather than utilize self-reported data. The longitudinal and experimental design could be expanded to make up for shortcomings associated with cross-sectional design. The findings cannot be generalized due to the data being focused on a single industry in a single country; this warrants the need for research to replicate this research in other industries or countries. This study did not consider the quality of work relationships, as nurses may hoard and hide knowledge from their alienated colleagues. Similarly, it is possible that team cohesion may influence nurses’ knowledge hoarding and hiding. Hence, we suggest that future work should gauge how the quality of work and team cohesion shape POQ and related outcomes.

REFERÊNCIAS

• Abubakar, A. M., Behravesh, E., Rezapouraghdam, H., & Yildiz, S. B. (2019). Applying artificial intelligence technique to predict knowledge hiding behavior. International Journal of Information Management, 49, 45-57. doi: 10.1016/j.ijinfomgt.2019.02.006
  » https://doi.org/10.1016/j.ijinfomgt.2019.02.006
• Aiken, L. S., West, S. G., & Reno., R. R. (1991). Multiple regression: Testing and interpreting interactions Thousand Oaks, USA: Sage Publications.
• Alfes, K., Shantz, A., & Baalen, S. van. (2016). Reducing perceptions of overqualification and its impact on job satisfaction: The dual roles of interpersonal relationships at work. Human Resource Management Journal, 26(1), 84-101. doi: 10.1111/1748-8583.12094
  » https://doi.org/10.1111/1748-8583.12094
• Algunmeeyn, A., El-Dahiyat, F., Altakhineh, M. M., & Azab, M. (2020). Understanding the factors influencing healthcare providers’ burnout during the outbreak of COVID-19 in Jordanian hospitals. Journal of Pharmaceutical Policy and Practice, 13(1), 1-8. doi: 10.1186/s40545-020-00262-y
  » https://doi.org/10.1186/s40545-020-00262-y
• Aljawarneh, N. M., Alomari, K. A. K., Alomari, Z. S., & Taha, O. (2020). Cyber incivility and knowledge hoarding: Does interactional justice matter? VINE Journal of Information and Knowledge Management Systems, 52(1), 55-70. doi: 10.1108/VJIKMS-12-2019-0193
  » https://doi.org/10.1108/VJIKMS-12-2019-0193
• Al-Khalidi, S. (2020). Jordan races to expand hospitals to cope with COVID-19 surge Recuperado de https://www.reuters.com/article/us-health-coronavirus-jordan-hospitals-idUSKBN27Z24D
  » https://www.reuters.com/article/us-health-coronavirus-jordan-hospitals-idUSKBN27Z24D
• Alnazly, E., Khraisat, O. M., Al-Bashaireh, A. M., & Bryant, C. L. (2021). Anxiety, depression, stress, fear and social support during COVID-19 pandemic among Jordanian healthcare workers. Plos One, 16(3), e0247679. doi: 10.1371/journal.pone.0247679
  » https://doi.org/10.1371/journal.pone.0247679
• Anasori, E., Bayighomog, S. W., & Tanova, C. (2020). Workplace bullying, psychological distress, resilience, mindfulness, and emotional exhaustion. The Service Industries Journal, 40(1-2), 65-89. doi: 10.1080/02642069.2019.1589456
  » https://doi.org/10.1080/02642069.2019.1589456
• Anselmann, V., & Mulder, R. H. (2020). Transformational leadership, knowledge sharing and reflection, and work teams’ performance: A structural equation modelling analysis. Journal of Nursing Management, 28(7), 1627-1634. doi: 10.1111/jonm.13118
  » https://doi.org/10.1111/jonm.13118
• Aslam, U., Muqadas, F., & Imran, M. K. (2018). Exploring the sources and role of knowledge sharing to overcome the challenges of organizational change implementation. International Journal of Organizational Analysis, 26(3), 567-581. doi: 10.1108/IJOA-07-2017-1189
  » https://doi.org/10.1108/IJOA-07-2017-1189
• Asurakkody, T. A., & Kim, S. H. (2020). Effects of knowledge sharing behavior on innovative work behavior among nursing students: Mediating role of self-leadership. International Journal of Africa Nursing Sciences, 12, 100190. doi: 10.1016/j.ijans.2020.100190
  » https://doi.org/10.1016/j.ijans.2020.100190
• Bajaj, B., Gupta, R., & Pande, N. (2016). Self-esteem mediates the relationship between mindfulness and well-being. Personality and Individual Differences, 94, 96-100. doi: 10.1016/j.paid.2016.01.020
  » https://doi.org/10.1016/j.paid.2016.01.020
• Behravesh, E., Abubakar, A. M., & Tanova, C. (2020). Participation in decision-making and work outcomes: Evidence from a developing economy. Employee Relations: The International Journal. 43(3), 704-723. doi: 10.1108/ER-08-2018-0228
  » https://doi.org/10.1108/ER-08-2018-0228
• Brown, K. W., & Ryan, R. M. (2003). The benefits of being present: Mindfulness and its role in psychological well-being. Journal of Personality and Social Psychology, 84(4), 822. doi: 10.1037/0022-3514.84.4.822
  » https://doi.org/10.1037/0022-3514.84.4.822
• Brown, K. W., Ryan, R. M., & Creswell, J. D. (2007). Mindfulness: Theoretical foundations and evidence for its salutary effects. Psychological Inquiry, 18(4), 211-237. doi: 10.1080/10478400701598298
  » https://doi.org/10.1080/10478400701598298
• Cheng, H., Song, F., & Li, D. (2017). How middle managers’ participation in decision-making influences firm innovation performance. Chinese Management Studies, 55(2), 413-426. doi: 10.1108/MD-04-2016-0217
  » https://doi.org/10.1108/MD-04-2016-0217
• Connelly, C. E., Černe, M., Dysvik, A., & Škerlavaj, M. (2019). Understanding knowledge hiding in organizations. Journal of Organizational Behavior, 40(7), 779-782. doi: 10.1002/job.2407
  » https://doi.org/10.1002/job.2407
• Connelly, C. E., & Zweig, D. (2015). How perpetrators and targets construe knowledge hiding in organizations. European Journal of Work and Organizational Psychology, 24(3), 479-489. doi: 10.1080/1359432X.2014.931325
  » https://doi.org/10.1080/1359432X.2014.931325
• Connelly, C. E., Zweig, D., Webster, J., & Trougakos, J. P. (2012). Knowledge hiding in organizations. Journal of Organizational Behavior, 33(1), 64-88. doi: 10.1002/job.737
  » https://doi.org/10.1002/job.737
• Da’as, R. A. (2019). Teachers’ skill flexibility: Examining the impact of principals’ skills and teachers’ participation in decision making during educational reform. International Journal of Educational Management, 33(2), 287-299. doi: 10.1108/IJEM-12-2017-0382
  » https://doi.org/10.1108/IJEM-12-2017-0382
• Daubenmier, J., Hayden, D., Chang, V., & Epel, E. (2014). It's not what you think, it's how you relate to it: Dispositional mindfulness moderates the relationship between psychological distress and the cortisol awakening response. Psychoneuroendocrinology, 48, 11-18. doi: 10.1016/j.psyneuen.2014.05.012
  » https://doi.org/10.1016/j.psyneuen.2014.05.012
• Ding, C. G., & Shen, C. K. (2017). Perceived organizational support, participation in decision making, and perceived insider status for contract workers: A case study. Management Decision, 55(2), 413-426. doi: 10.1108/MD-04-2016-0217
  » https://doi.org/10.1108/MD-04-2016-0217
• Erdogan, B., & Bauer, T. N. (2009). Perceived overqualification and its outcomes: The moderating role of empowerment. Journal of Applied Psychology, 94(2), 557. doi: 10.1037/a0013528
  » https://doi.org/10.1037/a0013528
• Erdogan, B., Tomás, I., Valls, V., & Gracia, F. J. (2018). Perceived overqualification, relative deprivation, and person-centric outcomes: The moderating role of career centrality. Journal of Vocational Behavior, 107, 233-245. doi: 10.1016/j.jvb.2018.05.003
  » https://doi.org/10.1016/j.jvb.2018.05.003
• Erdogan, B., Karaeminogullari, A., Bauer, T. N., & Ellis, A. M. (2020). Perceived overqualification at work: Implications for extra-role behaviors and advice network centrality. Journal of Management, 46(4), 583-606. doi: 10.1177/0149206318804331
  » https://doi.org/10.1177/0149206318804331
• Evans, J. M., Hendron, M. G., & Oldroyd, J. B. (2014). Withholding the ace: The individual-and unit-level performance effects of self-reported and perceived knowledge hoarding. Organization Science, 26(2), 494-510. doi: 10.1287/orsc.2014.0945
  » https://doi.org/10.1287/orsc.2014.0945
• Follmer, E. H., Talbot, D. L., Kristof-Brown, A. L., Astrove, S. L., & Billsberry, J. (2018). Resolution, relief, and resignation: A qualitative study of responses to misft at work. Academy of Management Journal, 61(2), 440-465. doi: 10.5465/amj.2014.0566
  » https://doi.org/10.5465/amj.2014.0566
• Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. Recuperado de https://www.jstor.org/stable/3151312
  » https://www.jstor.org/stable/3151312
• Goñi-Legaz, S., & Ollo-López, A. (2017). Temporary contracts, participation in decision making and job satisfaction in European workers. International Journal of Manpower, 38(6), 875-892. doi: 10.1108/IJM-04-2016-0086
  » https://doi.org/10.1108/IJM-04-2016-0086
• Hanh, T. N. (1976). Miracle of mindfulness Boston, USA: Beacon.
• Hair, J. F., Jr., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) Los Angeles, USA: Sage Publications.
• Hair, J. F., Jr., Sarstedt, M., Ringle, C. M., & Gudergan, S. P. (2017). Advanced issues in partial least squares structural equation modeling Los Angeles, USA: Sage Publications.
• Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115-135. doi: 10.1007/s11747-014-0403-8
  » https://doi.org/10.1007/s11747-014-0403-8
• Holten, A. L., Hancock, G. R., Persson, R., Hansen, Å. M., & Høgh, A. (2016). Knowledge hoarding: Antecedent or consequent of negative acts? The mediating role of trust and justice. Journal of Knowledge Management, 20(2), 215-229. doi: 10.1108/JKM-06-2015-0222
  » https://doi.org/10.1108/JKM-06-2015-0222
• Joseph-Williams, N., Lloyd, A., Edwards, A., Stobbart, L., Tomson, D., Macphail, S., & Thomson, R. (2017). Implementing shared decision making in the NHS: Lessons from the MAGIC programme. BMI, 18(357), j1744. doi: 10.1136/bmj.j1744
  » https://doi.org/10.1136/bmj.j1744
• Li, C. S., Liao, H., & Han, Y. (2021). I despise but also envy you: A dyadic investigation of perceived overqualification, perceived relative qualification, and knowledge hiding. Personnel Psychology. 75(1), 91-118. doi: 10.1111/peps.12444
  » https://doi.org/10.1111/peps.12444
• Li-Ying, J., Paunova, M., & Egerod, I. (2016). Knowledge sharing behaviour and intensive care nurse innovation: The moderating role of control of care quality. Journal of Nursing Management, 24(7), 943-953. doi: 10.1111/jonm.12404
  » https://doi.org/10.1111/jonm.12404
• Maynard, D. C., Joseph, T. A., & Maynard, A. M. (2006). Underemployment, job attitudes, and turnover intentions. Journal of Organizational, 27, 509-536. doi: 10.1002/job.389
  » https://doi.org/10.1002/job.389
• Maynard, D. C., & Parfyonova, N. M. (2013). Perceived overqualification and withdrawal behaviors: Examining the roles of job attitudes and work values. Journal of Occupational and Organizational Psychology, 86(3), 435-455. doi: 10.1111/joop.12006
  » https://doi.org/10.1111/joop.12006
• Martinez, P. G., Lengnick-Hall, M. L., & Kulkarni, M. (2014). Overqualifed? A conceptual model of managers’ perceptions of overqualification in selection decisions. Personnel Review, 43(6), 957-974. doi: 10.1108/PR-06-2013-0104
  » https://doi.org/10.1108/PR-06-2013-0104
• Olendzki, A. (2005). The roots of mindfulness. In C.K Gerner, R. D Siegel, & P. R Fulton (Eds.), Mindfulness and Psychotherapy (pp. 241-261). New York, USA: Guilford.
• Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. (2012). Sources of method bias in social science research and recommendations on how to control it. Annual Review of Psychology, 63, 539-569. doi: 10.1146/annurev-psych-120710-100452
  » https://doi.org/10.1146/annurev-psych-120710-100452
• Rodrigues, A. L., Barrichello, A., & Morin, E. M. (2016). Os sentidos do trabalho para profissionais de enfermagem: Um estudo multimétodos. RAE-Revista de Administração de Empresas, 56(2), 192-208. doi: 10.1590/S0034-759020160206
  » https://doi.org/10.1590/S0034-759020160206
• Sesen, H., & Ertan, S. S. (2019). Perceived overqualification and job crafting: The moderating role of positive psychological capital. Personnel Review, 49(3), 808-824. doi: 10.1108/PR-10-2018-0423
  » https://doi.org/10.1108/PR-10-2018-0423
• Sun, L. Y., Aryee, S., & Law, K. S. (2007). High-performance human resource practices, citizenship behavior, and organizational performance: A relational perspective. Academy of Management Journal, 50(3), 558-577. Recuperado de https://www.jstor.org/stable/20159873
  » https://www.jstor.org/stable/20159873
• The Hashemite Kingdom of Jordan Ministry of Health. (2019). Annual Statistical Book 2019 Amman, Jordan.
• Thera, N. (1972). The power of mindfulness San Francisco, USA: Unity Press.
• Triana, M. D. C., Trzebiatowski, T., & Byun, S. Y. (2017). Lowering the threshold for feeling mistreated: Perceived overqualification moderates the effects of perceived age discrimination on job withdrawal and somatic symptoms. Human Resource Management, 56(6), 979-994. doi: 10.1002/hrm.21812
  » https://doi.org/10.1002/hrm.21812
• Valoyi, E. G., Lessing, B. C., & Schepers, J. M. (2000). Participation in decision making. SA Journal of Industrial Psychology, 26(3), 32-38. doi: 10.4102/sajip.v26i3.717
  » https://doi.org/10.4102/sajip.v26i3.717
• Vignochi, L., Goncalo, C. R., & Lezana, A. G. R. (2014). How do hospital managers use performance indicators? RAE-Revista de Administração de Empresas, 54(5), 496-509. doi: 10.1590/S0034-759020140504
  » https://doi.org/10.1590/S0034-759020140504
• Wassermann, M., & Hoppe, A. (2019). Perceived overqualification and psychological well-being among immigrants. Journal of Personnel Psychology, 18(1), 34-45. doi: 10.1027/1866-5888/a000219
  » https://doi.org/10.1027/1866-5888/a000219
• Wu, C. H., Luksyte, A., & Parker, S. K. (2015). Overqualification and subjective well-being at work: The moderating role of job autonomy and culture. Social Indicators Research, 121(3), 917-937. doi: 10.1007/s11205-014-0662-2
  » https://doi.org/10.1007/s11205-014-0662-2
• Zhang, L. N., Li, Y. M., & Cao, Y. (2017, October). The relationship study of perceived over qualification and knowledge sharing on team performance. 3rd Annual International Conference on Management Science and Engineering (MSE 2017) (Vol. 50, pp. 229-233). Guangxi, China. Atlantis Press.
• Zheng, B., & Wang, Z. (2017). Perceived overqualification and its outcomes: The moderating role of organizational learning. Social Behavior and Personality: An International Jjournal, 45(10), 1675-1690. doi: 10.2224/sbp.6349
  » https://doi.org/10.2224/sbp.6349

Edited by

Guest Scientific Editor: A. Mohammed Abubakar

Publication Dates

• Publication in this collection
  13 May 2022
• Date of issue
  2022

History

• Received
  22 July 2021
• Accepted
  19 Oct 2021