How Person–Organization Fit Impacts Work Performance: Evidence from Researchers in Ten Countries during the COVID-19

Abstract

It is important to provide researchers with the support they need to improve the Person–Organization (PO) fit in order to manage the negative impact of COVID-19 on work performance. Underpinned by the PO fit theory, drawing upon the survey data of 2321 researchers from ten countries initiated by Nature in 2021, this paper discusses how the independent variables of person–organization fit and organizational resources impact work performance, a dependent variable, moderated by career stages via a factor and path analysis. The results show that organizational resources and PO fit have significantly assisted researchers in managing the negative impacts of COVID-19 on work performance. In terms of national heterogeneity, for developing countries, it is more important to provide more organizational support to researchers than PO fit. However, for developed countries, personal demands would be focused on improving PO fit, which would be helpful for researchers’ work performance more effectively than providing organizational support blindly. Therefore, in order to improve the efficiency of organizational support, those that fit less but had more helpful aspects should be increased appropriately, while those that fit more but were less helpful should be reduced accordingly. It implies that it would be significant to emphasize differentiated and career-stage-sensitive support to researchers in different countries to improve researchers’ wellbeing and organizational performance.

1. Introduction

Given the context of COVID-19, appearing in early 2020 and spreading rapidly worldwide, the situation has seriously affected almost every part of life, including health [1], economy, and education across the globe. The pandemic has also led to an unprecedented impact and challenges on research activities worldwide due to travel restrictions and lockdown measures. With laboratory work shut down, and a large number of samples backlogged, the pandemic impacted the completion of the later project and also the progress of the investigation and sampling as well as stopping the academic exchanges. The COVID-19 pandemic has put the situations of researchers at various organizations and institutions at risk, which deteriorates an already challenging tenure-track job market.

Researchers contribute greatly to knowledge production by conducting systematic academic and scientific investigations and publishing research findings [2]. The ability to attract and retain ‘‘top talent’’ is rapidly becoming a key human resources management issue for institutions related to the scientific investigation field [3]. However, although the number of COVID-19-related publications is rapidly increasing, very little research has been conducted regarding the COVID-19 impact on the scientific community. Few empirical studies draw their attention to researchers in the academic landscape, though a cluster of post-doctoral researchers has been investigated [4,5]. For researchers, confinement policies enacted by most countries have implied a sudden switch to work from home, a transition to online teaching and mentoring, and an adjustment of research activities. As such, the need to understand how the pandemic impacted researchers is also urgent to better understand their wellbeing and facilitate their development [6].

Without exception, COVID-19 has had a major impact on social development and research efforts. Given the uncertainties and challenges that the COVID-19 pandemic has caused academic work, it is more important for organizations to support researchers, especially to meet their work needs, so that research can be carried out smoothly and scientific output can be promoted. How to make the best organization-employee fit is very important. Only when employees are allocated to positions that can best exert their abilities can the maximum effect of labor resources be exerted [7]. PO fit is one of the main factors that need to be considered for long-term employment and maintaining organizational resilience [8], which becomes more crucial during the turbulent pandemic time.

Therefore, the purpose of this study is to examine the impact of COVID-19 on researchers, drawn from the data in a world online survey organized by Nature about researchers globally in 2021. This is a primary research study using Nature survey data. This paper analyzed in depth how researchers’ PO fit impacts their work performance in the context of COVID-19. Our aim is to identify how the organizational resources would fit the personal demands of researchers from ten countries at their different career phases during the pandemic, aiming to provide effective support for researchers in the post-pandemic era.

2. Literature Review

2.1. The Impact of COVID-19 upon Research and Researchers

Researchers have already felt a high level of pressure, with the pressure to publish slightly greater than the pressure to attract external funding. Research has shown that the pandemic has exacerbated previously identified challenges and harms that academic researchers face, which include hindered development of research work [9], worsened mental health [10], reduced job security, and decreased funding opportunities [11]. The COVID-19 pandemic resulted in unprecedented closures of institutes and workplaces worldwide in the spring of 2020 [12], which directly resulted in academic research activities and work being significantly hampered, field visits and data collection being paralyzed, and funding resources being frozen and halted. Furthermore, animal centers and practical labs were closed, and many scientific and social congresses and symposiums were canceled, leaving postgraduates and scientific workers confined to their homes [9]. Therefore, many researchers’ experimental progress was hindered (e.g., due to the loss of samples and funds) [13]. Most life sciences and engineering fields rely on experimental facilities to complete their research; the closure of those facilities during the pandemic created a great obstacle to completing their research. Myers et al. [14], in their sample of 4535 respondents, reported a 24% reduction in research time across disciplines and a decline between 30 and 40% for biological and agricultural sciences.

The impact of the COVID-19 pandemic has been well documented on research productivity, disproportionately impacting researchers, particularly early-career researchers (ECRs) [15,16]. Lockdowns to contain the current COVID-19 pandemic could unduly impact early-career researchers’ careers. This is due to the vulnerability of their income, and the time-constrained nature of student and early-career researcher (ECR) research programs. Early-career researchers (e.g., post-docs) also rely on short-duration contracts (usually one to two years) and are expected to produce high outputs. A long break in their contracts could jeopardize their ability to complete the research program they proposed, compromising future job applications. For students and ECRs in ecology and evolution fields, the inability to conduct field or laboratory work essential to their studies may exacerbate these problems [11]. Harrop et al. [17] captured the challenges ECRs are facing during the pandemic and the support that is needed for career development and research. The study shows that reductions in productivity were reported by 85% of ECRs. Additionally, studies show that the lockdown intensified the productivity gap among the already under-represented group of female researchers and male academics [18].

2.2. The Effect of Person–Organization Fit

Given the uncertainty and challenges during the pandemic, how organizations support the researchers (employees) has become more important and would affect their career development. To achieve long-term employment relationships and organizational flexibility, a good match between individuals and organizations is key [8]. Underpinned by the person–environment fit theory, the person–organization fit theory mainly discusses the compatibility between individuals and organizations, as well as the premise and possible results of realizing such compatibility [19]. Most researchers broadly define PO fit as the compatibility between individuals and organizations [20].

How organizations and employees match is very important, which determines the decisions of organizations and the behaviors of employees. To achieve long-term employment relationships and organizational flexibility, a good match between individuals and organizations is key [8]. According to the PO fit theory, only when the labor force is allocated to the position, giving full play to its ability, can the maximum effect of labor resources be exerted [7]. Many PO fit studies internationally have confirmed that the match between individuals and organizations will contribute to individual job satisfaction [21] and organizational culture [22,23]. Furthermore, research consistently indicates that applicant–job and applicant–organization fits are related to many perceptions and attitudes related to employees’ work experiences in the late stage of employment [24].

Two distinctive perspectives of PO fit are explored to include supplementary and complementary fit [20] as well as needs–supplies and demands–abilities [25]. From the needs–supplies perspective, PO fit occurs when an organization satisfies individuals’ needs, desires, or preferences. In contrast, the demands–abilities perspective suggests that fit occurs when an individual has the abilities required to meet organizational demands. Kristof [20] integrated the two distinctions above and investigated organization supplies, such as financial, physical, and psychological resources, as well as the task-related, interpersonal, and growth opportunities that are demanded by employees. When these organizational resources meet employees’ demands, needs–supplies fit is achieved. Similarly, organizations demand contributions from their employees in terms of time, effort, commitment, knowledge, skills, and abilities. The demands–abilities fit is achieved when these employee resources meet organizational demands.

Organizational Resources. Within the demands–resources perspective, supportive relationships with supervisors (perceived supervisor support) or peers are organization resources that would affect individuals’ willingness to engage in development activities in the organization and is significant for subordinate performance and success. Organizational resources serve as an important dimension in the person–organization fit theory in the face of high organizational pressure from job demands [26]. Therefore, they emphasize the influence of organizational resources on individual motivation and believe that the organizational environment promotes or hinders the formation of motivation by supporting or hindering autonomy, ability, and relationship needs. Karim and Roger [27] emphasized that leaders’ incentives, encompassed in organizational resources, to researchers in a university have an important impact on improving researchers’ innovation abilities.

Researchers in Different Career Stages and Personal Demands. Research shows that development opportunities that meet the expectations of individuals will improve their job satisfaction [28]. However, with the changes in roles and work contents in different stages of the occupation, the psychological needs of employees will also change accordingly. Being a rather dynamic than a static life phase, careers encompass the continuous progress of self-development. Studies showed that early-career researchers are more likely to be realistic and passionate about their job with more stress [29] to get accustomed to their new occupation and academic appointment confusion, identity, anxiety, as well as conflicting messages [30]. Researchers in the mid-career stage usually are more productive as they develop their independence with skills and funding [31]. In the late-career stage, as retirement age approaches, most employees begin to lose their sense of responsibility and only care about how to successfully achieve career goals and maintain a certain level of performance while preparing for retirement [32].

2.3. Theoretical Framework

To sum up, the literature on the impact of COVID-19 on researchers focuses more on a broad perspective rather than their work performance and how organizational support would facilitate the development of researchers in their different career stages, which this study contributes to. As Figure 1 shows, based on the person–organization fit, the conceptual framework of Kristof [20], this study would explore the person–organization fit of researchers from ten countries with the compatibility between personal demands and organizational resources to investigate how organizational resources would impact researchers’ work performances.

Aiming to investigate how the COVID-19 pandemic impacted researchers and their work in ten countries, this study is underpinned by the following four main research questions:

(1)

How were researchers’ work performances impacted by the COVID-19 pandemic?

(2)

Can the person–organization fit facilitate researchers to mitigate the negative impact of COVID-19?

(3)

Is there heterogeneity in the role of organizational resources and the person–organization fit for researchers in different career stages and different work performances?

(4)

What would be the more helpful organizational resources for researchers during the pandemic?

3. Methodology

3.1. Data

The data in this paper are from the Global Salary and Job Satisfaction Survey initiated by Nature in 2021 and supported and collected by Shift Learning, a market research company based in London. This survey, which education research specialists at Shift Learning are conducting on behalf of Springer Nature, aims to explore how the current COVID-19 outbreak impacts researchers, as well as their expectations in their careers in the long term.

The survey, in English, Mandarin Chinese, Spanish, French, and Portuguese, which ran from 7 June to 11 July via e-mail campaigns, drew responses from more than 3210 working scientists around the world. This survey addressed the impacts of the COVID-19 pandemic, including salary freezes, canceled job offers, and postponed experiments and fieldwork.

To address the issue of sample diversity and numbers, several filters were implemented as follows: (1) the sample number is at least over 50; (2) the respondents are excluded if they are not related to the research itself; (3) the respondents are full-time researchers. Therefore, we draw upon the data of full-time researchers from ten countries (United States, United Kingdom, Germany, China, Canada, Brazil, Australia, India, Italy, and Switzerland), with 2321 samples in total.

As

Table 1. Sample description (N = 2321).

Country	N	Position/Role	Percent
United States	1002	Postdoctoral fellow/research associate	22.99%
United Kingdom	433	Research/staff scientist	18.90%
Germany	184	Full professor	9.17%
China	146	Assistant professor	9.08%
Canada	108	Associate professor	8.52%
Brazil	105	Technician/technical manager	7.65%
Australia	101	Middle or senior management	3.82%
India	88	Data analyst/scientist	2.91%
Italy	78	Lecturer/instructor or other primarily teaching job	2.87%
Switzerland	56	Project manager	2.26%
Age	Percent	Consultant	1.83%
25-	4.82%	Research Director/VP of research	1.56%
26–30	12.87%	Clinician	1.61%
31–40	39.07%	Professional	1.56%
41–50	20.51%	Science communications	1.22%
51–60	13.86%	Other	4.05%
61–70	7.39%	Field of work	Percent
71+	1.48%	Biomedical and clinical sciences	41.11%
Gender	Percent	Ecology and evolution	7.30%
Female	51.37%	Health care	6.95%
Male	46.02%	Geology and environmental science	6.43%
other	2.61%	Social sciences	6.35%
Career Stage	Percent	Chemistry	5.74%
Career Stage	Percent	Field of work	Percent
Early career	43.33%	Engineering	5.35%
Mid-career	37.77%	Physics	4.48%
Late career	18.90%	Agriculture and food	4.39%
Workplace	Percent	Computer science and mathematics	3.69%
Academia	63.41%	Astronomy and planetary science	2.04%
Industry	16.69%	Other science-related fields	6.17%
Government	7.95%	Degree	Percent
Non-profit	5.65%	Higher Degree (PhD/MD/JD etc.)	79.09%
Clinical	2.87%	Master’s level (MSc/MA/MBA)	12.19%
other	3.43%	Undergraduate/Bachelor’s degree or equivalent	8.72%

establishes, among 2321 samples, almost 41.11% work in biomedical and clinical science, followed by ecology and evolution (7.30%). Additionally, 63.41% work in academia, 16.69% in industry, 7.95% in government, and 5.65% at non-profit organizations. Respondents spanned a broad spectrum of job titles, including postdoctoral researchers (22.99%) and staff scientists (18.90%), among whom almost 79.09% have a PhD degree. Female researchers slightly outnumber male researchers, and 2.61% of researchers identified as non-binary or preferred not to say. Most respondents are 31–40 years old and claim to be in the early-career stage.

3.2. Variables

3.2.1. Independent Variables: Person–Organization Fit

Drawn upon the studies by Kristof [20], the person–organization fit in this study is measured from the individual level and defined as the compatibility between personal demands and organizational resources. As Figure 2 shows, the Global Salary and Job Satisfaction Survey by Nature investigated the organizational resources perceived by each researcher and the importance of their personal demands in seven dimensions: interpersonal, career related, time, physical, commitment, financial, and psychological. According to Eisenberger [33] and Rhoades [34], throughout this paper, the term organizational resources refers to the extent to which an organization values individual contributions and its care about employee wellbeing, etc., which is perceived by employees. Meanwhile, personal demands refer to the degree of need for 28 various organizational resources that the researcher personally believes. To summarize, we only focus on the complementary fit and do not discuss the supplementary fit in this play due to the existing data set available.

Since the 28 organizational resource items and the 28 personal needs are a one-to-one correspondence, the person–organization fit of each item is then calculated by the following formula:

$${POF}_{i,n}=\frac{{OS}_{i,n}}{{PD}_{i,n}}\times 100\%$$

(1)

In Formula (1), POF_i,n represents the i-th person–organization fit of the n-th researcher. OS_i,n represents the satisfaction of the i-th organizational resources of the n-th researcher. PD_i,n represents the importance of the i-th personal demand of the n-th researcher.

The 28 specific organizational resources and personal demands are shown in

Table 2. 28 Specific organizational resources/personal demands.

Dimension	Items	Abbreviation
Interpersonal	Communication with supervisor	CFW
	Relationship with colleagues (including social events organized either by the company or amongst colleagues)	RWC
Career related	Career advancement opportunities	CAO
	Access to workplace-sponsored training and seminars	ATW
	Job security	JS
	Opportunity to work on interesting projects	OTW
	Amount of guidance from supervisor	AOG
	Ability to choose remote/hybrid working options	ATC
	Work independence	DOI
	Recognition for achievements	ROA
Time	Amount of time for research	ATO
	Work/life balance	WLB
	Compatibility of job with family life/raising children	COJ
	Time off (e.g., vacation, bank holidays, personal days, sick days)	TO
	Commuting time	CT
	Total hours worked	THW
Physical	Workplace facilities and comfort	WFA
	The safety of the work environment/workplace	FSI
Commitment	Diverse representation within management and leadership (e.g., race, gender, sexual orientation)	DRW
	Organization’s commitment to a diverse and inclusive workplace	OCD
	Organization’s commitment to environmental sustainability	OCE
Financial	Salary/compensation	SC
	Availability of funding	AOF
	Financial resources of organization	FRO
	Benefits (e.g., health and dental insurance, retirement plan)	BEN
Psychological	Personal sense of accomplishment	PSO
	Work interest	WI
	Meaningfulness of job	MOJ

. All survey questions utilized a 5-point Likert scale. Among them, the organizational resources are measured by satisfaction from extremely dissatisfied, somewhat dissatisfied, neither satisfied nor dissatisfied, and somewhat satisfied to extremely satisfied. They are assigned a value of 1 to 5 in turn, while the personal demands are measured by the degree of feeling: somewhat unimportant, not at all important, neither important nor unimportant, somewhat important, and extremely important, which are assigned a value of 1 to 5 in turn. Moreover, the values of Cronbach’s Alpha in each dimension are all above 0.8, suggesting it is a reliable measure of organizational resources and personal demands during COVID-19.

3.2.2. Dependent Variable: Work Performance

The dependent variable is the impact of COVID-19 on researchers’ work performance with fourteen items, as shown in

Table 3. Rotated factor matrix (N = 2321).

Items	Abbreviation	Data Collecting	Cooperation and Communication	Research Writing
Conducting lab-based experiments	CLE	0.735	0.221	0.07
Conducting fieldwork	CF	0.75	0.172	0.061
Data collection	DC	0.725	0.208	0.186
Teaching responsibilities	TR	0.248	0.716	0.115
Supervising colleagues	SC1	0.292	0.71	0.145
Applying for jobs	AFJ	0.313	0.432	0.258
Discussing ideas with PI/supervisor/colleagues	DIW	0.099	0.729	0.419
Sharing research findings	SRF	0.066	0.71	0.4
International collaborations/projects	ICP	0.258	0.763	0.236
Collaborations/projects with internal colleagues	CPW	0.184	0.803	0.164
Writing fellowship or grant proposals	WFO	0.159	0.412	0.599
Data analysis	DA	0.318	0.143	0.627
Writing	W	0.052	0.228	0.914
Literature review	LR	0.026	0.207	0.715

. The Cronbach’s Alpha of this scale is 0.907. The options include significant negative impact, some negative impact, no impact, some positive impact, and significant positive impact, which are assigned values of 1–5 in turn. The smaller the value, the more negatively the researcher believes that COVID-19 will have a negative impact on that area of work.

According to these fourteen items, factor analysis was adopted to reduce them into three dimensions. The rotated factor matrix is shown in Table 3. Bartlett = 14,310.264, p < 0.0001, and KMO = 0.927. All the above indicates that the correlation matrix is not an identity matrix, so factor analysis is considered. Three factors are generated, which encompass collecting data (conducting lab-based experiments, fieldwork, and data collection), research writing (data analysis, literature review, writing and writing fellowship or grant proposals, and cooperation and communication (the other seven items)). Based on the factor analysis, the factor analysis score of each researcher was calculated to measure three dimensions of work performance.

3.2.3. The Moderator: Career Stage

The career stages in an individual’s work span are related to age, rank, and years of job experience. This study, initiated by Nature, employed three levels of career stages self-judged by researchers, namely early career (ECRs), mid-career (MCRs), and late career (LCRs), to broadly explore how the researchers’ demands have been achieved in the context of organizational resources.

3.3. Statistical Model

In order to analyze the impact of organizational resources and person–organization fit on work performance and compare the magnitude of the impact, Amos is used for path analysis. Based on the theoretical model shown in Figure 1 and the variable settings, the econometric model is shown in Figure 3.

4. Findings

4.1. The Impact of COVID-19 on Researchers’ Work Performance

Since means from Likert Scale data do not have practical meanings, descriptive analysis of the 14-item factor analysis of the three types of work performance after dimension reduction was carried out instead of calculating the means of the 14 items directly. As Figure 4 shows, the COVID-19 pandemic has a negative impact on researchers’ work performance but differs in the course of work and career stages. Collecting data, including conducting lab-based experiments, fieldwork, and data collection, is more negatively impacted by COVID-19. Cooperation and communication are next, while most researchers believe COVID-19 makes no impact on research writing. This may be due to the fact that since COVID-19, the experiments and investigations of researchers have been hindered, but they have more time for writing.

Judging from the difference in career stages, in seven of the ten countries (Brazil, the United States, Germany, Canada, and Switzerland), the work performance of LCRs is the least affected by COVID-19, while ECRs are the most affected. However, there are also some different situations. In the UK, Australia, and China, MCRs have suffered the most negative impact, while LCRs are the least affected. In Italy, MCRs suffered the least negative impact, while ECRs the are most affected. In India, ECRs suffered the least negative impact, while LRCs suffered the most.

4.2. Person–Organization Fit of Researchers

Table 4. Person–organization fit of researchers.

Dimension	Items	Personal Demands					Organizational Resources					Person–Organization Fit
		Total	Early Career	Mid-Career	Late Career		Total	Early Career	Mid-Career	Late Career		Total	Early Career	Mid-Career	Late Career
Financial	AOF	88.25%	91.06%	86.42%	85.03%	↓	45.41%	47.63%	43.06%	44.56%		67.41%	69.47%	65.64%	65.75%
	BEN	86.55%	86.26%	86.75%	86.82%	↑	61.56%	58.51%	60.74%	70.73%	↑	79.42%	77.84%	78.33%	85.53%	↑
	FRO	87.30%	86.32%	87.05%	90.18%	↑	52.80%	57.02%	48.42%	51.84%		75.33%	79.04%	72.20%	73.07%
	SC	92.61%	93.34%	93.57%	88.97%		53.27%	49.40%	52.51%	64.36%	↑	73.96%	71.13%	73.06%	82.79%	↑
Commitment	DRW	69.69%	74.87%	66.71%	63.28%	↓	37.26%	34.94%	36.79%	45.02%	↑	67.11%	66.33%	65.47%	72.99%
	OCD	78.43%	81.49%	77.42%	73.17%	↓	50.86%	50.63%	49.24%	55.07%		74.97%	74.67%	74.06%	77.79%
	OCE	79.30%	79.35%	79.03%	79.71%		46.75%	44.78%	46.69%	51.55%	↑	74.59%	73.14%	74.33%	78.59%	↑
Time	ATO	91.55%	91.68%	92.50%	89.28%		59.75%	68.40%	51.63%	55.35%		75.74%	81.41%	70.26%	73.17%
	COJ	84.99%	85.17%	86.67%	80.94%		54.23%	49.76%	53.56%	66.54%	↑	72.30%	69.12%	71.47%	81.90%	↑
	CT	84.26%	85.13%	84.62%	81.41%	↓	71.10%	72.74%	69.42%	70.65%		89.24%	90.31%	87.93%	89.44%
	THW	81.16%	81.87%	83.47%	74.88%		56.70%	59.05%	52.54%	60.06%		78.42%	80.11%	75.07%	81.65%
	TO	88.84%	89.83%	89.83%	84.37%	↓	68.62%	67.32%	67.75%	73.89%	↑	82.84%	81.79%	81.60%	88.28%
	WLB	93.70%	93.82%	95.56%	89.70%		59.28%	58.61%	56.56%	66.75%		73.55%	73.07%	71.39%	79.38%
Career related	AOG	69.24%	80.80%	64.38%	48.09%	↓	55.10%	58.88%	48.16%	58.71%		79.78%	81.23%	75.86%	85.13%
	ATC	78.60%	76.53%	79.83%	80.98%	↑	70.15%	69.06%	68.48%	75.91%		87.10%	87.26%	85.80%	89.38%
	ATW	66.94%	68.78%	67.62%	61.08%	↓	52.89%	54.95%	50.00%	53.91%		78.10%	78.81%	76.42%	80.02%
	CAO	90.35%	96.15%	92.22%	71.35%	↓	39.70%	44.23%	35.87%	34.72%	↓	62.05%	63.95%	59.17%	63.62%
	DOI	95.15%	93.01%	96.37%	97.66%	↑	78.19%	76.44%	77.98%	82.45%	↑	87.59%	88.16%	86.33%	88.80%
	JS	93.42%	94.19%	94.09%	90.24%	↓	57.28%	49.23%	58.28%	75.41%	↑	73.98%	68.38%	74.40%	87.20%	↑
	OTW	98.05%	98.68%	98.00%	96.67%	↓	74.32%	75.23%	71.33%	78.27%		81.69%	81.89%	80.26%	84.16%
	ROA	86.46%	86.51%	87.73%	83.80%		48.20%	49.46%	45.91%	50.00%		72.11%	73.57%	69.72%	73.69%
Interpersonal	CFW	88.06%	92.48%	86.30%	80.38%	↓	59.79%	62.90%	55.36%	60.84%		78.70%	80.40%	75.97%	80.00%
	RWC	85.11%	86.25%	85.30%	82.08%	↓	63.01%	61.94%	62.81%	66.08%	↑	81.72%	80.77%	81.67%	84.18%	↑
Psychological	MOJ	96.96%	96.56%	97.19%	97.43%	↑	74.87%	73.95%	73.13%	80.48%		82.64%	82.53%	80.94%	86.31%
	PSO	97.89%	97.27%	98.01%	99.07%	↑	67.87%	65.45%	65.67%	77.73%	↑	77.70%	76.38%	76.35%	83.36%
	WI	99.08%	98.78%	99.53%	98.83%		79.55%	79.01%	77.20%	85.51%		83.08%	82.83%	81.48%	86.88%
Physical	FSI	86.84%	88.70%	88.47%	79.24%	↓	73.00%	76.53%	68.43%	74.15%		86.32%	87.39%	83.78%	89.28%
	WFA	80.25%	80.71%	81.46%	76.72%		60.71%	61.94%	58.68%	62.10%		82.91%	83.77%	81.07%	84.79%
Total		86.39%	87.70%	86.65%	82.55%	↓	59.72%	59.93%	57.36%	64.02%		77.87%	78.03%	76.07%	81.33%

Note: the symbol of ↑ means gradually increase with career development while ↓ means gradually decrease with career development.

shows the personal demands, organizational resources, and person–organization fit of researchers in different career stages. Because means from Likert scale data do not have practical meaning, the percentage of organizational resources that are satisfied (including some satisfied and extremely satisfied) and the percentage that is considered important (including some important and extremely important) are separately calculated instead of calculating the means of each supply or demand directly.

From the perspective of personal demands, the average demand of these 28 items of researchers is 86.39% and gradually decreases with career development. WI, PSO, SC, WLB, and ATO are in high demand at all career stages; however, demands for ATW, WFA, OCE, and THW have been low; demands for MOJ, DOI, BEN, and FRO are high and getting higher with career development; demand for ATC is low but getting higher with career development; demands for AOF, JS, OTW, CAO, CFW, FSI and TO are high but decrease with career development; demands for RWC, OCD, DRW, and AOG are low and decreases with career progression.

From the point of view of organizational resources, the overall satisfaction of researchers on organizational resources is 59.72%. Among them, MCRs have the lowest satisfaction (57.36%), and LCRs have the highest satisfaction (64.02%). Satisfaction with OTW, FSI, CT, ATC, RWC, and TO is high across career stages; however, satisfaction with FRO, AOG, THW, OCE, and ROA is consistently low; satisfaction with DOI, PSO, and BEN is high and increase with career development; satisfaction with JS, SC, COJ, OCE, and DRW is low but increase with career development; satisfaction with CAO is low and decrease with career development.

Overall, the PO Fit of researchers is 77.87%, and, among them, the fitness of MCRs is the lowest (76.07%), while LCRs is the highest (81.33%). The PO Fit of BEN, SC, OCE, COJ, JS, and RWC increase with career development. Meanwhile, there are three specific cases: (1) the improvement of the PO fit of BEN is due to the simultaneous improvement of personal demands and organizational resources; (2) the improvement of the PO fit of SC, OCE, and COJ is due to the improvement of organizational resources; (3) the improvement of PO fit of JS and RWC is due to the improvement of organizational resources and the decline of personal demands.

From the PO fit of researchers in each country, as shown in Figure 5, among the ten countries, the PO fit of researchers in Switzerland is the highest (86.07%), while the PO fit in Brazil is the lowest (68.40%). Moreover, the difference in PO fit between countries is related to the level of economic development level in each country. As Figure 5 shows, the PO fit in these ten countries is related to their GDP per capita in 2020. Countries with high GDP per capita have a high degree of PO fit, while in countries with low GDP per capita, the PO fit of researchers is also relatively low.

4.3. Organizational Resources, Person–Organization Fit, and Work Performance of Researchers

Based on the theoretical framework shown in Figure 1, the path model, as shown in Figure 3, was built to show the overall relationship between organizational resources, PO fit, and researchers’ work performances. The results shown in

Table 5. Path analysis of person–organization fit and work performance.

	Organizational Resources → Work Performance				PO Fit → Work Performance
	Total	Early Career	Mid-Career	Late Career	Total	Early Career	Mid-Career	Late Career
Work Performance	0.283 ***	0.281 ***	0.312 ***	0.214 ***	0.312 ***	0.299 ***	0.334 ***	0.326 ***
Data Collecting	0.558 ***	0.575 ***	0.591 ***	0.452 ***	0.615 ***	0.618 ***	0.575 ***	0.488 ***
Research Writing	0.437 ***	0.295 ***	0.513 ***	0.623 ***	0.482 ***	0.395 ***	0.789 ***	0.719 ***
Cooperation and Communication	0.954 ***	0.922 ***	0.948 ***	0.934 ***	0.846 ***	0.837 ***	0.589 ***	0.788 ***
RMSEA	0.021	0.025	0.025	0.031	0.021	0.023	0.024	0.042
Default model	1881.20	1620.45	1575.00	14,486.41	1873.15	1573.88	1544.76	1703.27
Saturated model	1890.00
Independence model	43,101.60	18,208.99	18,159.55	8884.13	39,886.97	16,755.22	17,134.59	8076.18
NFI	0.969	0.940	0.942	0.888	0.965	0.935	0.939	0.836
RFI	0.960	0.924	0.927	0.860	0.957	0.920	0.924	0.810
IFI	0.984	0.977	0.979	0.964	0.983	0.976	0.979	0.922
TLI	0.980	0.970	0.973	0.954	0.978	0.970	0.973	0.909
CFI	0.984	0.976	0.979	0.963	0.983	0.976	0.978	0.921
N	2321	997	869	435	2321	997	869	435

Notes: (1) *** p < 0.01. (2) Due to the limitation of space, the influence coefficient of 28 specific supports and 13 specific work performances were not included in this table.

demonstrate a good model fit (RMSEA < 0.05, NFI > 0.9, RFI > 0.9, IFI > 0.9, TLI > 0.9, CFI > 0.9, default model < saturated model < independence model). Judging from the standardized estimates and the significance of standardized estimates, organizational resources have significantly helped researchers in all career stages defend against the negative impact of COVID-19 on work performance. Organizational resources help MCRs the most (0.312), ECRs second (0.281), and LCRs the least (0.214). From the perspective of three specific aspects of work performance, organizational resources are most helpful to cooperation and communication, least helpful to ECRs and LCRs’ research writing, and least helpful to LCRs’ (0.452) data collecting. Certainly, the magnitudes and significance of the coefficients here are only relative but not absolute.

Additionally, organizational resources were replaced by PO fit to compare the influence of PO fit and organizational resources on work performance. The result also shows a good model fit. Moreover, PO fit also makes a significant positive impact on assisting researchers to manage the challenges that COVID-19 brings, which plays a more important role than organizational resources (0.312 > 0.283) in all career stages and three types of work performance. More robustly, the ranking of PO fit’s impact on work performance across dimensions does not differ much from organizational resources.

Further heterogeneity analysis of ten countries, as shown in Figure 6, showed that the influence of PO fit is not always greater than that of organizational resources in different countries but is related to the economic development level of a country. On the one hand, in some developing countries with low and mid economic development (such as India, Brazil, and China), the influence of organizational resources is greater than that of PO fit. However, with the development of the economy, the impact of PO fit increases rapidly. In countries with higher economic development levels, PO fit plays a greater role than organizational resources.

4.4. Specific Organizational Resources: Which Helps More?

Among 28 specific organizational resources, which helps more? In the path analysis, we also obtained the standardized regression coefficients of 28 specific organizational resources, which can be seen as the degree of contribution of each organizational resource to work performance. At the same time, the mean value of each PO fit was combined, as shown in Table 4, namely the degree of fit. In this way, 28 items can be divided into four types: type I is for those that fit more and were helpful, while type II is for those that fit more but were unhelpful; type III is for those that fit less but were helpful, while type IV is for those that fit less and were unhelpful. For researchers in different career stages and countries,

Table 6. The degree of specific PO fit and its contribution.

Dimension	Item	Total	Early Career	Mid- Career	Late Career	United States	United Kingdom	Germany	China	Canada	Brazil	Australia	India	Italy	Switzerland
career	CAO	III	III	III	III	III	III	III	III	III	IV	III	III	III	III
	AOG	I	I	III	II	I	I	III	IV	I	II	I	II	I	III
	ROA	III	III	III	III	III	III	III	I	III	I	III	III	III	III
	JS	IV	IV	IV	II	IV	IV	IV	III	IV	IV	III	IV	II	III
	ATW	II	II	II	IV	II	II	II	III	II	IV	III	IV	IV	III
	OTW	I	I	I	I	I	I	I	III	I	I	II	III	I	II
	ATC	II	II	II	I	II	II	II	IV	II	II	II	IV	II	I
	DOI	I	I	I	I	I	I	I	I	I	II	II	I	I	I
commitment	DRW	IV	IV	III	IV	IV	IV	IV	IV	IV	IV	IV	II	IV	IV
	OCD	III	III	III	III	III	III	III	I	IV	III	I	I	IV	III
	OCE	IV	IV	IV	IV	IV	II	IV	I	IV	III	IV	I	IV	IV
interpersonal	CFW	I	I	III	III	III	I	III	I	I	II	I	I	III	III
	RWC	I	I	I	I	I	II	I	II	I	I	II	I	I	I
financial	AOF	IV	IV	IV	IV	IV	IV	IV	III	III	IV	III	IV	IV	III
	BEN	II	IV	II	II	II	IV	II	IV	II	IV	II	IV	IV	II
	SC	IV	IV	IV	II	III	IV	II	IV	IV	IV	I	IV	IV	II
	FRO	IV	II	IV	III	II	IV	II	IV	IV	IV	III	IV	IV	II
physical	WFA	I	I	I	I	I	I	II	I	I	III	II	I	III	II
	FSI	I	I	I	I	I	I	I	I	I	I	I	I	I	II
psychological	PSO	III	III	I	I	III	III	III	I	I	I	III	I	III	III
	MOJ	I	I	I	I	I	I	I	I	I	I	I	I	I	II
	WI	I	I	I	I	I	I	I	I	I	I	I	I	I	II
time	COJ	IV	IV	III	II	III	IV	III	IV	IV	III	IV	IV	II	IV
	WLB	III	III	III	III	III	III	III	IV	III	III	III	III	III	I
	ATO	IV	II	IV	IV	IV	IV	IV	IV	IV	IV	IV	II	II	II
	TO	II	II	II	II	II	II	II	II	II	I	II	IV	II	II
	THW	II	II	IV	I	I	III	II	IV	II	I	III	II	II	II
	CT	II	II	II	II	II	II	II	II	II	II	II	II	II	II

summarizes the attribution of 28 items. In order to improve the efficiency of organizational support and better help researchers, the organizational support in type III should be increased appropriately to meet the personal demands of researchers, while the organizational support in type II should be reduced appropriately to avoid ineffective investment and waste of support.

5. Discussion

There are four issues to be addressed in this section. The first involves that the impact of COVID-19 on the work performance of researchers differs in career stages. Secondly, among the three dimensions of work performance, research writing is relatively less negatively impacted, while data collecting is most negatively impacted by COVID-19. The third issue is to discuss the country or the resource sensitivity of the PO fit and its effect on work performance. The last issue is to discuss limitations and future research.

5.1. The Impact of COVID-19 on the Work Performance of Researchers Differs across the Career Stages

On the one hand, data show that the work performance of ECRs is most negatively affected by COVID-19 in most countries (Brazil, the United States, Germany, Canada, and Switzerland) among three cohorts of three career stages, which is consistent with the results of existing studies. Harrop et al. [17] concluded that researchers in the earliest phases of their career, specifically postdoctoral fellows in assistant professor (or equivalent) positions are particularly vulnerable to the impact of the pandemic on job security, career development, and long-lasting effects of pandemic-related disruptions.

On the other hand, it is easy to overlook that the work performances of researchers in the mid- and late-career stages are also negatively affected by COVID-19. This indicates that MCRs and LCRs also need organizational support to resist the impact of COVID-19. Further analysis in this study showed that researchers in different career stages require different organizational resources. For ECRs and MCRs, interpersonal support is the most helpful, while for LCRs, career-related resources are the most helpful; for ECRs, commitment resources are the least helpful, and financial resources are the least helpful for MCRs and LCRs.

In addition, the different personal demands of researchers at different career stages should not be ignored. For example, data present that researchers in all three career stages value WI, PSO, SC, WLB ATO, MOJ, DOI, BEN, and FRO. Furthermore, with the development of careers, the demands of researchers for MOJ, DOI, BEN, FRO, and ATC gradually increase, while the demands for AOF, JS, OTW, CAO, CFW, FSI, TO, RWC, OCD, DRW and AOG are gradually declining.

5.2. Among the Three Dimensions of Work Performance, Research Writing Is Relatively Less Negatively Impacted, While Data Collecting Is Most Negatively Impacted by COVID-19

Among the three dimensions of work performance, it is evident that research writing is relatively less negatively impacted by COVID-19. However, when working from home appears, the impact of COVID-19 on cooperation and communication and research writing gets complicated.

Firstly, virtual interactions play complicated roles in cooperation and communication, with pros and cons. The pandemic has enhanced online communication and virtual interactions observed across disciplines to a certain extent and promoted the development of online educational technology. Conferences, workshops, and seminars adapted to digital formats became more inclusive and enabled scientists to potentially reach broader audiences. Prior to the pandemic, international academic mobility and scientific exchange were commonly threatened by limited travel budgets and visa-related issues [35]; then, inadvertently, virtual meetings addressed these concerns, especially for ECRs from countries with strong mobility issues. Ellis et al. [36] proposed that the majority of researchers (73%) believe that science and technology will enhance and upgrade the dialogue with people across the globe.

Secondly, working from home serves as a complex factor in relation to research writing. On the one hand, working from home gives researchers more time and freedom for research writing. The pandemic provides an opportunity for researchers with more time to study and plan future research activities with the decrease in commuting and work hours. Ellis et al. [36] find that the COVID-19 pandemic is being treated as an opportunity by six out of ten researchers with regard to having more time to plan for future research activities (78%). In Beck et al.’s [37] research, half of the respondents indicated that they would prefer to remain working from home, which is reflected across various occupations, and most felt that it increased their work productivity. Although there might be reduced productivity, people still preferred to remain working from home, as it is more likely to be related to an improved work–life balance [38]. On the other hand, for researchers with childcare responsibilities, the quality of working from home will be affected. Furthermore, if researchers can not manage their time well, it will lead to increasingly blurred work–life boundaries. Therefore, it is recommended by Kramer and Kramer [39] that universities and companies have now had to make the necessary adjustments for working at home to open up new opportunities for more workplace flexibility in the future.

Furthermore, data collecting is most negatively affected, which agrees with Myers et al.’s [14] analysis. They found that the COVID-19 pandemic has affected many areas of research, with disciplines that rely on laboratories and time-sensitive experiments being more affected than other disciplines. More importantly, data collecting is the initial stage in the research process. Advances in data collection will directly impact research writing, communication, and collaboration. Therefore, other than organization resources, effective measures would be taken to support researchers conducting lab-based experiments, fieldwork, and data collection. Alternatively, a concerted effort between funding agencies, universities, and the public may be operative.

5.3. PO Fit and Its Effect on Work Performance Presents the Country- or Resource-Sensitive

On the one hand, as stated in the literature review section, the vast majority of current research focuses on the contribution of PO fit to job satisfaction [22] and organizational culture [22,23] and less on the role of PO fit on work performance. Additionally, currently, the PO fit theory is mainly applied in the selection of employees during recruitment. Higgins et al. [40] point out that PO fit is one of the main factors that need to be considered when hiring employees for long-term employment and maintaining organizational resilience. Interviewing is one of the most commonly used means for personnel selection. However, the results of this study show that PO fit still makes a significant impact on the work performance of researchers. This indicates that the PO fit theory can not only be applied to employee recruitment and screening in the selection process but also provide guidance for promoting employee career development and human resource management. In addition to the organizational resources to improve employee performance, PO fit is likely to be emphasized when providing professional development, retaining quality staff, and other journeys of human resource management.

On the other hand, although PO fit has a greater inhibitory effect on job burnout than organizational support in most countries, the influence of PO fit is not always greater than that of organizational support in different countries. PO fit and its effect on work performance present the country with resource sensitivity. It indicates that when social resources are relatively scarce, it is more significant to provide more organizational support to researchers than to meet individual needs. However, when social resources are sufficient, personal needs would be focused on improving the PO fit, which can reduce the job burnout of researchers rather than providing organizational support with no importance.

5.4. Limitations and Future Research

Despite the contribution to the existing literature, further studies could be carried out to investigate the work performance of researchers when organizational support is greater than personal demands. Although we have conducted a heterogeneity analysis of the actual situation in ten countries, different countries have different policies and research contexts. Therefore, future studies can conduct in-depth analyses of specific countries. Given the PO fit theory, measurement is conducted only between individual needs and organizational supply in the complementary fit, namely needs–supplies fit, without discussing supplementary fit and demands–abilities fit. It is mainly due to the fact that the survey data analyzed in this study were already publicly available with their fixed items in the questionnaire. We were unable to add relevant questions to our own study design. It also leads to the 28 items used for measuring PO fit being predesigned by Nature. Therefore, future research could be conducted to include the supplementary fit and demands–abilities fit of researchers. Moreover, the PO fit calculated in this paper is mostly less than 100%, so we would not be able to make an in-depth analysis of the situation where supply is greater than demand. However, in reality, if supply is much higher than demand (when PO fit is more than 100%), it may also have a detrimental effect on researchers. Therefore, in the future, we will focus on the work performance of researchers when organizational support is greater than personal demands.

6. Conclusions

The importance and originality of this study could be presented with its theoretical and practical significance. From a theoretical point of view, this study casts new light on the application of the person–organization fit theory and primarily provides the evidence-informed human resource management of the application of the person–organization fit theory in the context of the pandemic, which was measured using the compatibility between the personal demands of researchers and organizational resources perceived by researchers in seven dimensions and establishes the link between PO fit and work performance. Generally, the PO fit of the researchers sampled is 77.87% and is the highest in the late-career stage (81.33%). Correspondingly, the work performance of researchers is more negatively affected in the early-career stage. However, organizational resources and PO fit have significantly assisted researchers in all career stages for their work performance. In terms of national heterogeneity, when resources are relatively scarce in some developing countries, it is more important to provide more organizational support to researchers. However, when resources are sufficient in developed countries, personal needs should be focused on improving PO fit, which demonstrates a strong effect of person–organization fit on the work performance of researchers. Therefore, this paper expands the application scope of the PO fit theory to a certain extent, expanding it from the selection of employees during recruitment to promoting employee career development and from job satisfaction to work performance.

Pragmatically, how to respond to COVID-19 in the context of the global pandemic to support researchers in the long run is informed by this study. This paper provides a reference for how to better help researchers manage the negative impact of COVID-19 at the organizational level in the post-pandemic era. Additionally, three implications could shed light on the future research policies and practices to supply and facilitate the development of researchers all over the world to make the junior talents survive during the pandemic and afterward. Firstly, regarding career stages, researchers in different career stages have their individualized demands and satisfaction with organizational resources, which informs that the organizational resources require a more nuanced consideration in order to provide effective support for researchers. Secondly, this study reinforces the existing literature to emphasize the differentiated and career-stage-sensitive resources and support to researchers in the world. More specifically, what organizations should expand support in the post-pandemic era are the items that help more but supplies/fit less. Thirdly, what support organizations should provide to researchers in their career stages matters and varies in different countries. In order to improve the efficiency of organizational support and better help researchers reduce their job burnout, those that fit less but had helpful aspects should be increased appropriately, while those that fit more but had unhelpful aspects should be reduced appropriately to avoid ineffective investment and waste of support.