Partnership in Recruitment Process Outsourcing Projects: The Outsourcing Firm Perspective

Abstract

This research provides insights into how to enhance recruitment process outsourcing (RPO) project outcomes by improving partnerships with the RPO provider. We posit that knowledge sharing and top management support enhance partnership quality by increasing both parties’ mutual dependence and commitment to the relationship. We conducted a survey of 150 RPO projects. The results demonstrate the effectiveness of knowledge sharing and top management support for enhancing partnership, leading to enhanced RPO project outcomes (i.e., recommended candidates’ person-job fit). Theoretical and practical implications of the results are discussed.

Keywords

recruitment process outsourcing partnership knowledge sharing top management support person-job fit person-organization fit

Introduction

In an economy characterized by globalization, disruptive business models/ecosystems, hyper-competition among firms, and rapid organizational change, firms need to find the right talents in a cost-effective way. However, many firms have limited access to the overall talent pool, and inefficient recruitment processes mean they take too long to hire the wrong talent (Martinez & Padamadan, 2019). Recruitment process outsourcing (RPO) providers have emerged to help firms manage such recruitment by leveraging their cross-industry, cross-geography recruitment knowledge and capabilities (Kock et al., 2012).

RPO occurs when firms outsource their talent recruitment projects wholly or partially to a third-party RPO provider (Wehner et al., 2012). Commonly, the recruitment project involves a series of activities, including recruitment demand confirmation, recruitment advertisement release, résumé gathering and filtering, interview arrangement, interview execution, background checks, candidate assessment and recommendation, contracting, offer posting, and so on (Siew-Chen & Vinayan, 2016). RPO can benefit firms by saving costs, improving recruitment efficiency, providing access to new talent markets or providing a fresh, expert perspective to a talent recruitment problem (Phillips & Gully, 2015). Nevertheless, many RPO projects result in poor matching of talents to organizational outcomes (Martinez & Padamadan, 2019).

In addition, RPO creates risks and additional costs for outsourcing firms, including a loss of organizational control over recruitment, coordination and transaction costs, and potential interest conflicts (Conklin, 2005). It is argued these risks and costs can be ameliorated by building a partnership with the RPO provider. Such partnerships increase both sides’ stake in maintaining the relationship, decrease unnecessary operational frictions, and induce commitment to the relationship (Gulati & Sytch, 2007; Lawler & Yoon, 1996). Because good RPO providers understand a firm’s strategic goals, they can select candidates that have both the appropriate skills (person-job fit) and align with the firm’s goals, culture, and strategy (person-organization fit).

However, research on how good RPO partnerships are formed is still lacking (Savino, 2016). Research generally agrees that mutual knowledge is an essential resource for improving partnership and project outcomes (Lee, 2001; Lee & Kim, 2005). Because knowledge cannot be easily sold, bought, and traded in the marketplace, acquiring knowledge is among the major motives for firms to form a partnership (Lee, 2001; Mowery et al., 1996). Prior studies also suggest top management support is critical for partnership formation (Eisenhardt & Schoonhoven, 1996; Sluyts et al., 2011; Wittmann et al., 2009). Top management, who occupies a vantage point to make decisions to align a firm’s internal structures and processes to its environment, plays a key role in establishing conditions for frequent exchange with partners, and thus the formation and strengthening of partnerships. Few studies juxtapose the two factors to see how they jointly and separately impact partnership formation. We argue that knowledge sharing and top management support increase exchanges between the outsourcing firm and its RPO provider at both the project and firm levels. As a result, both partners perceive the relationship as something that has its own value. This could make exiting the relationship difficult because of the emergent value of the relationship and thus partnership (Gulati & Sytch, 2007; Lawler & Yoon, 1996, 1998).

This article examines whether knowledge sharing and top management support can help enhance partnership quality between the RPO provider and the outsourcing firm during RPO projects, which ultimately leads to quality candidates being recommended who demonstrate desired person-organization fit and person-job fit. In this article, RPO projects are nonroutine RPO exercises, typically used to obtain rare talent (in our case, management executives). We find that knowledge sharing has a greater influence on partnership quality than top management support. We also find that partnership quality has a positive impact on person-job fit, but not person-organization fit.

The remainder of the article is organized as follows. We first review relevant literature on partnership quality, knowledge sharing, top management support, and evaluation of RPO outcomes. The methodology is next discussed. We then describe our findings and discuss the implications of our study. We finally draw a conclusion and discuss the limitations of our study.

Literature Review

Recruitment is an important human resources (HR) function that determines if the right talents are available to execute firm strategies (Phillips & Gully, 2015). RPO involves the outsourcing of all or parts of recruitment and selection activities (Wehner et al., 2012). RPO can improve firm efficiency via outsourcing common activities, such as job advertisement, résumé screening, or background checks (Nguyen & Chang, 2017). Recruitment can be influenced by factors within and outside firms’ control (e.g., business strategy, external labor supply, and demand). An RPO can create competitive advantage by providing access to resources otherwise inaccessible to outsourcing firms (e.g., external labor, new recruitment strategies), thereby reducing the variability and improving the probability of selecting appropriate talents (Phillips & Gully, 2015).

Partnership Quality

Research has generally found that partnership between suppliers and the outsourcing firm is a key success factor in outsourcing projects (Lee et al., 2003; Ren et al., 2011). Partnership allows the outsourcing firm to gain access to resources that are not available internally and to capitalize on resources available to suppliers. Partnership is defined as an interfirm relationship where parties involved have a long-term commitment to working together to achieve common objectives (Mehta & Mehta, 2010). In an RPO project, partnership refers to the cooperative relationship between the outsourcing firm and the RPO provider in which both willingly commit to the recruitment of appropriate candidates and share attendant benefits and risks. This article characterizes RPO as a partnership-building process, with the outsourcing firm seeking to gain needed resources (e.g., recruitment knowledge and skills) from the RPO provider and capitalize on its resources to create benefits for both parties. Meanwhile, the outsourcing firm has the ability to reward/punish the RPO provider (e.g., terminate the contract) when the provider does/doesn’t act in a desired way (Brito & Miguel, 2017). True partnership occurs when both the outsourcing firm and the RPO provider view the relationship as an object of attachment, regardless of other attractive alternatives (Gulati & Sytch, 2007; Lawler & Yoon, 1996).

Good partnership features trust, business comprehension, benefits and risk sharing, effective conflict resolution, and commitment (Lee & Kim, 2005). In most good RPO partnerships, the RPO provider goes beyond providing a list of potential candidates to the firm. The RPO provider will be able to recommend candidates compatible with organizational requirements, culture, goals, and vision; deliver value-added services, such as employer brand management; the outsourcing firm is also willing to invest more resources to facilitate project deliverables and even expand collaboration with the RPO provider (e.g., training of new hires). Both parties thus will be able to gain competitive advantage through the partnership.

Prior studies suggest that many potential antecedents help form and sustain partnership in outsourcing relationships and strategic alliances, including organizational (e.g., outsourcing readiness, top management attitudes/size, clear goals) (Eisenhardt & Schoonhoven, 1996; Ren et al., 2010; Sluyts et al., 2011) and relational characteristics (e.g., two-way communication, partner compatibility, client/supplier asset specificity, power, and interdependence) (Feller et al., 2013; Ren et al., 2011). Increasingly, studies have suggested that knowledge sharing and top management support are the most important direct or indirect predictors of partnership formation or strategic alliance (Chu & Wang, 2012; Feller et al., 2013; Sluyts et al., 2011; Wittmann et al., 2009). For example, Feller et al. (2013) demonstrate that knowledge sharing improves firms’ capability to manage R&D alliances. Chu and Wang (2012) identified that information sharing is the most powerful predictor of partnership quality because it reduces information asymmetry. Likewise, Wittmann et al. (2009) indicated top management support can substantially enhance alliance management competence, such as the ability to identify potential partners and manage partner relationships (β = .53). Sluyts et al. (2011) demonstrate that top management support greatly improves firms’ alliance learning processes and alliance management skills. However, these studies investigate outsourcing contexts that are not RPO. RPO differs from these contexts as the deliverables (i.e., human beings) are not stable entities and have unique characteristics based on personal strengths and assets. Also, these studies explore knowledge sharing and top management support separately, rather than explaining their joint and differential impacts on partnership formation and strengthening. In this study, we study how these two factors simultaneously contribute to partnership quality. Figure 1 is our research model in which we use person-job fit and person-organization fit to measure RPO project success. We will elaborate on these two measures later.

Figure 1

Research model.

Knowledge Sharing

Completion of an RPO project requires both explicit and implicit knowledge, including information about job requirements, recruitment procedures, plans, expectations, and performance evaluation. Knowledge sharing is regarded as an important process for interfirm cooperation that helps develop opportunities for new business, generate new ideas (Gulati & Sytch, 2007), and create knowledge about managing alliances and outsourcing relationships (Feller et al., 2013).

Repeated knowledge sharing at the project level increases the total knowledge in a relationship. This raises the opportunity costs of leaving a relationship and also increases both firms’ flexibility in adapting to their environment. In an RPO project, both the outsourcing firm and the RPO provider require information from each other. The RPO provider will need information about the firm, project requirements, and processes for achieving its business objectives. Likewise, the outsourcing firm would like to know more about the provider’s recruitment channels/methods, experience, project progress, and so forth. Continuous knowledge sharing thus creates both a common language and shared understanding about the project and therefore greater total value for both parties, leading to increased commitment toward the relationship and perceptions of mutual dependence (Lawler & Yoon, 1996, 1998).

Furthermore, knowledge sharing reduces the uncertainty of partner behaviors and activities, and thus produces more trust and positive feelings toward the partner. This is because knowledge sharing provides opportunities to learn more about the other party and makes partners’ acts of commitment more salient. Frequent knowledge sharing can also signal trust to partners and commitment to the relationship (Lawler & Yoon, 1996). For example, the outsourcing firm could provide a list of their major competitors to the RPO provider. Such a list is sometimes considered a trade secret by the outsourcing firm. Thus, the sharing behavior can reduce the RPO provider’s uncertainty about the outsourcing firm, and signal that the outsourcing firm treats the RPO provider as a trustworthy partner. This increases trust and improving partnership. Indeed, prior studies demonstrate that knowledge sharing is among the most important predictors of partnership quality (Chu & Wang, 2012; Feller et al., 2013). Hence, we propose:

H1 : Increased knowledge sharing will enhance partnership quality with the RPO provider.

Top Management Support

Top management is in charge of making and carrying out strategic decisions. They determine the acquisition, allocation, reconfiguration, and integration of internal and external resources for the delivery of organizational strategy. Top management support in an RPO project refers to participation of top management in project activities. Top management support includes provision of financial, physical, and human support (e.g., relaxed budget and timeline or business partners from functions working in the RPO project), establishment of new organizational structures (e.g., moving senior HR staffs to the RPO provider), or use of formal power in project execution or conflict resolution (Boonstra, 2013; Liu et al., 2015). We argue that the outsourcing firm’s top management support can contribute to the development and strengthening of partnership with the RPO provider in three ways.

First, top management can provide necessary resources and establish an environment that facilitates exchange with the RPO project. For example, top management could assign personnel from the HR department and the employing department to help clarify recruitment requirements with the RPO provider. This increases the outsourcing firm’s stakes in the relationship and enhances the RPO provider’s perceived continuity of partnership, leading to their commitment to the relationship (Lawler & Yoon, 1996).

Second, top management of the outsourcing firm can act in a collegial way toward the RPO provider, instead of exerting their power or authority, especially when dealing with potential conflicts. For example, top management can negotiate a reporting or decision-making structure to mitigate risks of foreseeable contingencies instead of referring to the formal control (e.g., candidate tracking or relationship management systems). This thus encourages exchange between top management and the RPO provider and induces the RPO provider’s positive feelings toward the relationship (Gulati & Sytch, 2007; Lawler & Yoon, 1996).

Finally, top management can foster trust between the RPO provider and the outsourcing firm by participating in project activities. For example, top management can attend important meetings with the RPO provider. Joint action or joint problem-solving helps partners develop greater overlap in goals, promoting a sense of shared responsibility that produces positive results (Lawler & Yoon, 1998). The participation further signals that the outsourcing firm attaches great importance to the project and predisposes both sides to collaborate, rather than dissolve the tie whenever operational frictions occur. This makes the value of the relationship more significant and real for both sides. In summary, top management support increases joint activities, resource investment, and greater goal convergence between the outsourcing firm and the RPO provider; and thus both sides’ stakes, positive feelings, trust, and commitment toward a relationship. Hence, we propose:

H2 : Increased top management support will enhance partnership quality with the RPO provider.

Recruitment Process Outsourcing Success

Enhanced partnership with the RPO provider should increase the likelihood of RPO project success. However, because finding matched talents is a common challenge in RPO projects (Martinez & Padamadan, 2019; Siew-Chen & Vinayan, 2016), RPO success should be measured with job dimensions that match the outsourcing firm’s strategic goals and objectives (Serrador & Turner, 2015). Any job opening varies on a range of dimensions, including knowledge, skill, and experience requirements, and organizational attributes. Two forms of fit thus are argued to be the key outcomes of most recruitment projects, namely person-job fit and person-organization fit (Pritchard & MacVaugh, 2017; Sekiguchi & Huber, 2011). Person-job fit refers to the matching degrees of personal knowledge, skills, and abilities (KSA) with the needs of a job or what a job offers (Boon et al., 2011). Accurate and realistic job information allows RPO providers to evaluate candidates’ fit with a job. For legal reasons, person-job fit is often used to justify selection decisions, with low person-job fit commonly used as a reason for rejecting candidates (Sekiguchi & Huber, 2011). Person-job fit generally predicts employees’ future performance (Kristof‐Brown et al., 2005), job satisfaction, voluntary turnover (Cao & Hamori, 2020), organizational identity, and mental health (Choi et al., 2017).

PO fit refers to the consistency between a person’s faiths and values and an organization’s values, goals, structures, or culture (Kristof-Brown, 2000). During recruitment and selection, the candidate’s interaction and response will signal their values, goals, and faith to the RPO provider (Swider et al., 2015). Therefore, as more complete and personal information is made available, the RPO provider will be better able to assess candidates’ personal values and goals. Candidates who match more attributes of the outsourcing firm are more likely to be selected. PO fit generally has positive impacts on individual job performance (Pritchard & MacVaugh, 2017), work motivation, and job satisfaction (Fan, 2018; Greguras et al., 2014).

Person-job (PJ) and person-organization (PO) fit thus are better measures of RPO outcome compared with such measures as cost (i.e., the average cost per hire), time, or scope (i.e., the number of hires made). Indeed, many studies have demonstrated that PJ and PO fit predict important human resource outcomes, such as job satisfaction, decreased turnover, or work engagement, and that PJ and PO fit lead to better organizational performance and profits (Albrecht et al., 2015; Koys, 2001; Lee & Bang, 2012). The direct effects of PJ and PO fit on organizational performance are even more obvious in executive-level hires (Hamori & Koyuncu, 2015).

Enhanced partnership with the RPO provider should increase the outsourcing firm’s perceived PJ fit of RPO outcomes. This is because enhanced partnership means the provider is familiar with the outsourcing firm’s main business and knows what kinds of candidates the outsourcing firm is looking for (i.e., required knowledge, skills, experiences). If the RPO provider is not familiar with the outsourcing firm’s business, it is likely the provider will just follow the written job description and recommend candidates who superficially satisfy job demands. For example, the RPO provider of an automobile manufacturing firm may recommend candidates who are certified project managers (e.g., PMP or PRINCE2) with experience in the automobile industry. However, the RPO provider might not realize the firm is specifically looking for candidates able to manage software projects, especially given the increased integration of software into automobiles.

In addition, a good partnership provides both the RPO provider and outsourcing firm with more opportunities to learn from each other and define realistic expectations clearly. For example, one common tactic in RPO projects is to give an open-ended job description to collect a larger pool of candidates. With a good partnership, the RPO provider can better communicate with candidates and help filter the candidate pool based on unwritten requirements.

Finally, a good partnership also implies a trusting relationship between the RPO provider and the outsourcing firm. The firm thus is more willing to disclose confidential information to the RPO provider, such as its future strategic directions. As a result, the provider can search for candidates whose KSA portfolio better meets the outsourcing firm’s future demands. Hence, we propose:

H3 : Enhanced partnership quality is positively associated with the outsourcing firm’s perceived person-job fit of recommended candidates.

Likewise, good partnership can also enhance person-organization fit. Partnership helps RPO providers have a better understanding of the outsourcing firm’s culture, values, and the types of talents that fit the culture. For example, if the outsourcing firm emphasizes employee loyalty and stability, the RPO provider will not recommend candidates who change jobs frequently. In addition, the RPO will be more able to post recruitment advertisements that convey cultural information about the outsourcing firm correctly. Job seekers with poor cultural fit thus will be less attracted to the firm.

In a good partnership, the RPO provider is more likely to remain open to the outsourcing firm’s culture and values. Through interaction, the RPO provider assimilates to the outsourcing firm’s working style and creates shared values that allow both to articulate their own core values and culture. As a result, the cultural difference between the RPO provider and the outsourcing firm becomes smaller. This influences which attributes of candidates are valued by the RPO provider and how strongly the RPO provider focuses on those attributes (Gyrd-Jones & Kornum, 2013). The RPO provider thus will be able to recommend candidates compatible with the outsourcing firm’s culture. For example, an RPO provider will develop a respect for rules and high-power distance when it constantly interacts with an outsourcing firm featuring a strict hierarchy. The RPO provider thus is more likely to emphasize candidates who respect rules and bureaucracy to the outsourcing firm during selection. Hence, we propose:

H4 : Enhanced partnership quality is positively associated with the outsourcing firm’s perceived person-organization fit of recommended candidates.

Methodology

Sample

Our target population was a subset of the approximately 64,000 companies in the Suzhou Industrial Park (SIP) in China in 2019. In China, micro- and small enterprises account for 84.4% of the enterprise population (China National Bureau of Statistics, 2019). These firms are too small to use RPO services (Susomrith & Brown, 2013). Our target population is therefore within the remaining 15.6% (approximately 9,984 companies). The SIP was established in 1994 as a bilateral project between the Singaporean and Chinese governments with a focus on high-tech industry. SIP is one of the best among over 200 state-level industrial parks in China as of 2019 (You, 2019). The SIP contributed approximately US$57.2 billion to the GDP in 2019. Like other Chinese industrial parks, the SIP is a self-sufficient system that includes an industrial production area, a scientific research area, a residential area, a recreational area, and a business service area (Geng & Hengxin, 2009).

From the target population, we obtained a sample of 153 responses (150 valid). Table 1 presents the demographic characteristics of the sample. More than 40% of the respondents were from the manufacturing industry (42%). Numbers in parentheses are the industrial distribution of the population in the SIP as of 2018. A chi-square goodness of fit test of the parenthetical and non-parenthetical numbers demonstrated that our sample was not representative (chi-square = 56.16, df = 8, p < .01). Specifically, the manufacturing industry was overrepresented (42% vs. 31.36%) and the retail industry was underrepresented (15.33% vs. 37.9%). According to the Suzhou Statistics Bureau (2019), the manufacturing industry in the SIP in 2018 accounted for 53.32% of new hires, and the retail industry accounted for only 23.47%. That manufacturing was the sector actively recruiting might explain why they were overrepresented in our data. Also, given the small size of the average retailer in the SIP, fewer RPO projects are expected, which might explain why we had fewer such respondents in our sample. In addition, the total investment in emerging high-tech industry in the SIP is more than 650 times that in the service industry in 2018 (Suzhou Statistics Bureau, 2019). This also potentially explains the over-representativeness of manufacturers in our sample. Firm size was measured by the number of employees. As expected, medium to large firms are more likely to outsource RPO projects (Susomrith & Brown, 2013). The number of employees of most firms surveyed was between 100 and 999 (89.33%), in other words, medium to large firms. About 80% of the firms surveyed had worked with the same RPO provider for over one year (78.67%). The majority of RPO projects lasted between one and three months (76%). This corresponds to a recent industry report (Martinez & Padamadan, 2019) indicating that, beyond the middle management level, most RPO projects take 30 to 60 days, and this extends to beyond 60 days for C-suite level hiring. About two-thirds of the projects recruited fewer than 20 people (64%).

Table 1

Demographic Characteristics of the Sample

	Frequency	Percentage Actual (Expected)
Industry
Processing and manufacturing	63	42.00 (31.36)
Internet/communications	12	8.00 (7.7)
Real estate/construction	32	21.33 (17.9)
Financial/banking	2	1.33 (.0.26)
Wholesale/retail trade	23	15.33 (37.9)
Management consulting/intermediary service	4	2.67 (0.38)
Transport/warehousing	6	4.00 (2.02)
Tourism	1	0.67 (1.4)
Others	7	4.67 (1)
Firm size (number of employees)
0–99	4	2.67
100–299	43	28.67
300–499	53	35.33
500–999	38	25.33
Over 1000	12	8.00
Cooperation time between outsourcing firm and RPO provider (years)
Below 0.5	3	2.00
0.5–1	29	19.33
1–1.5	73	48.67
1.5–2	35	23.33
Over 2	10	6.67
Duration of the RPO project (days)
30–59	65	43.33
60–89	49	32.67
90–119	18	12.00
Over 120	18	12.00
People recruited from the RPO project
0–9	30	20.00
10–19	66	44.00
20–29	43	28.67
Over 30	11	7.33

Note. RPO = recruitment process outsourcing.

Measurement

We developed the following measurement items for individual variables from prior research and adapted these items to the RPO context:

Person-Job Fit

To measure person-job fit, four reflective items were adapted from Sekiguchi and Huber (2011). The items include: (1) educational background of the management-level candidate recommended by the RPO provider matches our job requirements; (2) work experience of the management-level candidate recommended by the RPO provider matches our job requirements; (3) knowledge and skills of the management-level candidate recommended by the RPO provider matches our job requirements; and (4) performance of the management-level candidate recommended by the RPO provider matches our expectations. Items were measured on a five-point scale, ranging from strongly disagree to strongly agree.

Person-Organization Fit

Measures of person-organization fit were adapted from Sekiguchi and Huber (2011) and Tanwar and Kumar (2019), including: (1) personal values of the management-level candidate recommended by the RPO provider fit the culture of our firm; (2) personal goals of the management-level candidate recommended by the RPO provider fit the goals of our firm; (3) character of the management-level candidate recommended by the RPO provider is similar with that of the typical employees in our firm; and (4) working style of the management-level candidate recommended by RPO provider fit the style of our firm. Items were measured on a five-point scale, ranging from strongly disagree to strongly agree.

Partnership Quality

Partnership quality was measured by five reflective items adapted from Lee (2001): (1) our firm and the RPO provider trust each other in all situations; (2) our firm and the RPO provider know each other’s business goals and work together; (3) our firm and the RPO provider share the benefits and risks in the recruitment process; (4) the culture and strategy of our firm and those of the RPO provider are compatible; and (5) both our firm and the RPO provider keep promises and carry out the contracts. Items were measured on a five-point scale, ranging from strongly disagree to strongly agree.

Knowledge Sharing

We adapted the six reflective items from Lee (2001) to measure knowledge sharing, which are: (1) our firm and the RPO provider share the information of job requirements with each other; (2) our firm and the RPO provider share recruitment business manuals, methods, and channels with each other; (3) our firm and the RPO provider share successful and unsuccessful recruitment cases with each other; (4) our firm and the RPO provider share related industry reports or magazines with each other; (5) our firm and the RPO provider share our work experience; and (6) our firm and the RPO provider share recruitment experiences and expertise with each other. Items were measured on a five-point scale, ranging from strongly disagree to strongly agree.

Top Management Support

Top management support was measured by ﬁve reflective items (Thong et al., 1996), including: (1) top management of our firm participates in the RPO project meetings; (2) top management of our firm analyzes the information needed for recruitment; (3) top management of our firm evaluates the recommendations from the RPO provider; (4) top management of our firm takes part in the decision-making of the RPO project; and (5) top management of our firm is involved in monitoring the process. Items were measured on a five-point scale, ranging from strongly disagree to strongly agree.

Control Variables

We controlled for firm size to rule out rival explanations for our findings. Previous studies have shown that firm size is closely related to the resources available for projects, thereby influencing project success.

The questionnaire was pretested on HR experts from three outsourcing firms and one RPO provider in the SIP. Those HR experts were in charge of RPO projects for recruiting management-level talents in the past year. We asked these HR experts to check the relevance and readability of our questionnaire, which allowed us to detect defective questions and check the questionnaire format. The questionnaire, in the form of a web link and QR code, was distributed to the HR department of registered firms in the SIP.

The questionnaire began with a set of instructions, explaining the research purpose and asking HR personnel to identify their latest RPO project for recruiting management-level talents. The HR personnel who answered our questionnaire had an average company tenure of 2.23 years. This suggests they should have a sufficient understanding of the overall organizational culture and be able to objectively evaluate the person-job fit based on job description provided by the employing department. A reminder was sent to subjects via WeChat after two weeks from the initial contact. A total of 153 questionnaires were received. Three responses were incomplete, leaving 150 valid questionnaires. Our sample size is small, when compared with the population. To assess whether nonresponse influenced our sample composition, we assessed nonresponse bias. We performed t-tests between the initial wave of responses (the first 25% of responses) and the late wave (the last 25%; Armstrong & Overton, 1977). Results indicated no significant difference in variables under study (all p values > .05).

Analysis and Results

Our model involves a mediation effect, and therefore structural equation modeling tools were appropriate for this analysis. We performed our analysis using both partial least squares structural equation modeling (PLS-SEM, using smartPLS 3.3.2) and traditional covariance-based SEM (using R lavaan). We followed the two-step approach in which we assessed the reliability and validity of measures before evaluating the structural relationships (Anderson & Gerbing, 1988).

Testing the Measurement Model

The measurement model was examined for the reliability, convergent, and discriminant validity of focal constructs in our research model. To obtain a model that better represents the data, six items were dropped because those items had the highest absolute value of standardized residual covariance. Then, we evaluated reliability after dropping these six items. To assess the reliability, composite reliability values and Cronbach α were used. Table 2 presents the reliability, validity, and factor loadings of each scale. In Table 2, all values, except for one (i.e., TMS2), exceed the value of 0.70 (Hair et al., 2017) or at least no less than 0.6 (Hair et al., 1998).

Table 2

Measurement Items

Scale Items	Factor Loading
Person-job fit: CR = .905; Cronbach α = .844; AVE = .761
PJ1	Educational background of the management-level candidate recommended by the RPO provider matches our job requirements.	0.863
PJ2	Work experience of the management-level candidate recommended by the RPO provider matches our job requirements.	0.900
PJ3	Knowledge and skills of the management-level candidate recommended by the RPO provider matches our job requirements.	0.854
PJ4	Performance of the management-level candidate recommended by the RPO provider matches our expectations.	Dropped
Person-organization fit: CR = .959; Cronbach α = .936; AVE = .885
PO1	Personal values of the management-level candidate recommended by the RPO provider fit the culture of our firm.	Dropped
PO2	Personal goals of the management-level candidate recommended by the RPO provider fit the goals of our firm.	0.942
PO3	Character of the management-level candidate recommended by the RPO provider is similar with that of the typical employees in our firm.	0.950
PO4	Working style of the management-level candidate recommended by RPO provider fits the style of our firm.	0.931
Partnership quality: CR = .0.899; Cronbach α = .0.849; AVE = .0.691
PQ1	Our firm and the RPO provider trust each other in all situations.	0.799
PQ2	Our firm and the RPO provider know each other’s business goals and work together.	0.911
PQ3	Our firm and the RPO provider share benefits and risks in the recruitment process.	Dropped
PQ4	The culture and strategy of our firm and that of the RPO provider are compatible.	0.827
PQ5	Both our firm and the RPO provider keep promises and carry out the contracts.	0.780
Knowledge sharing: CR = .887; Cronbach α = .832; AVE = .662
KS1	Our firm and the RPO provider share the information of job requirements with each other.	Dropped
KS2	Our firm and the RPO provider share recruitment business manuals, methods, and channels with each other.	0.753
KS3	Our firm and the RPO provider share successful and unsuccessful recruitment cases with each other.	Dropped
KS4	Our firm and the RPO provider share related industry reports or magazines with each other.	0.857
KS5	Our firm and the RPO provider share our work experience.	0.842
KS6	Our firm and the RPO provider share recruitment experiences and expertise with each other.	0.798
Top management support: CR = .869; Cronbach α = .803; AVE = .628
TMS1	Top management of our firm participates in the RPO project meetings.	Dropped
TMS2	Top management of our firm analyzes the information needed for recruitment.	0.604
TMS3	Top management of our firm evaluates the recommendations from the RPO provider.	0.806
TMS4	Top management of our firm takes part in the decision-making of the RPO project.	0.884
TMS5	Top management of our firm is involved in monitoring the project.	0.846

Note. AVE = average variance extracted; CR = composite reliabilities; RPO = recruitment process outsourcing.

We next assessed the convergent and discriminant validity of both the overall model and individual constructs. With regard to overall model fit, we obtained Comparative Fit Index (CFI) = .968, Root Mean Square Error of Approximation (RMSEA) = .050, and Standardized Root Mean Square Residual (SRMR) = .053. Hu and Bentler (1999) recommend a cutoff value of 0.95 for CFI, 0.06 for RMSEA, and 0.08 for SRMR, suggesting our CFA model had overall good convergent and discriminant validity.

Hair et al. (2017) suggest that factor loadings, composite reliability (CR), and average variance extracted (AVE) be applied to evaluate convergent validity. Factor loadings for all items are beyond the suggested value of 0.7 (Hair et al., 2017) or at least no less than 0.6 (Hair et al., 1998). The composite reliability values (Table 1) that describe the level to which the construct indicators demonstrate the latent construct, ranged from 0.869 to 0.959, higher than the recommended value of 0.7 (Hair et al., 2017). The AVE that shows the variance in the indicators explained by the latent construct ranged from 0.628 to 0.885, exceeding the recommended value of 0.5 (Hair et al., 2017). All values to measure convergent validity were greater than acceptable values, demonstrating the scales have sufficient convergent validity.

Discriminant validity is established when (1) the loading of every indicator on its assigned construct exceeds its loading on other constructs; and (2) the correlations between the construct and other constructs in the model are lower than the square root of the AVE by the indicators evaluating that construct (Henseler et al., 2015). Tables 3 and 4 indicate that all constructs have sufficient convergent and discriminant validity.

Table 3

Interconstruct Correlations

	Knowledge Sharing (KS)	Person-Job Fit (PJ)	Person-Organization Fit (PO)	Partnership Quality (PQ)	Top Management Support (TMS)
KS	(0.814)
PJ	−0.069	(0.873)
PO	−0.066	0.171	(0.941)
PQ	0.374	0.254	−0.01	(0.831)
TMS	0.119	0.251	0.016	0.30	(0.792)

Note. Numbers in parentheses on the diagonal represent the square root of the AVE.

Table 4

PLS Confirmatory Factor Analysis and Cross-Loadings

	Knowledge Sharing (KS)	Person-Job Fit (PJ)	Person-Organization Fit (PO)	Partnership Quality (PQ)	Top Management Support (TMS)
KS2	0.753	−0.012	−0.134	0.250	0.082
KS4	0.857	−0.072	−0.073	0.323	0.176
KS5	0.842	−0.039	−0.009	0.334	0.084
KS6	0.798	−0.109	−0.020	0.214	−0.004
PJ1	−0.094	0.863	0.099	0.205	0.300
PJ2	−0.077	0.900	0.163	0.255	0.193
PJ3	−0.006	0.854	0.182	0.197	0.174
PO2	−0.060	0.165	0.942	−0.015	0.010
PO3	−0.086	0.162	0.950	0.004	0.020
PO4	−0.029	0.155	0.931	−0.020	0.016
PQ1	0.351	0.136	−0.024	0.799	0.307
PQ2	0.388	0.203	−0.004	0.911	0.214
PQ4	0.382	0.125	−0.090	0.827	0.190
PQ5	0.117	0.378	0.081	0.780	0.283
TMS2	0.070	0.110	−0.112	0.132	0.604
TMS3	0.161	0.137	0.021	0.234	0.806
TMS4	0.125	0.246	0.004	0.268	0.884
TMS5	0.052	0.261	0.068	0.280	0.846

Note. Shaded boxes demonstrate convergent validity.

We assessed the multicollinearity of individual predictor constructs in our research model (Hair et al., 2017). The variance inflation factors (VIF) of all predictor constructs are between 1.00 and 1.03, and far below the cutoff value of 5, indicating no multicollinearity problem in our model.

Common method bias was also evaluated and controlled by utilizing the marker variable method (Chin et al., 2012). This survey adopted an irrelevant construct (i.e., software usage behaviors). We then conducted the construct level correction (CLC) to partial out the common method variance (CMV) effects on the structural model. Accurate estimates of the structural paths thus were obtained.

Testing the Structural Model

Figure 2 demonstrated the outcomes of the structural path analysis. The overall fit of the structural model based on the covariance-based SEM estimates was 0.962 for CFI, 0.051 for RMSEA, and 0.071 for SRMR, meeting the Hu and Bentler (1999) criteria of good fit.

Figure 2

Full sample path model. Note: *p < .05; **p < .01; numbers in parentheses are R lavaan SEM estimates.

For the PLS estimates, the researchers used the bootstrapping method to generate 5,000 samples to assess the significance of paths. The structural model has an R² of 0.24 for partnership, 0.103 for PJ fit, and 0.066 for PO fit. Most hypotheses (H1, H2, and H3) were supported, except for H4 (b = −0.05, p > .05). Similar results were obtained using the covariance-based SEM, with an R² of 0.222 for partnership, 0.048 for PJ fit, and 0.009 for PO fit. H1, H2, and H3 were supported, but H4 was not (b = −0.05, p > .05). Our findings suggest that both top management support and knowledge sharing can enhance partnership in an RPO project, which further leads to enhanced PJ fit in the RPO outcome. Further, according to both PLS-SEM and covariance-based SEM estimates, knowledge sharing has a greater effect (0.37 > .25, 0.54 > .49) on partnership quality than top management support.

To assess if the difference between the two effects is statistically significant, we then examined the overlap between the bias corrected 95% confidence intervals (CI) of these two effects. Table 5 shows the lower bound, higher bound, and point estimate of the 95% CIs of both knowledge sharing and top management support in the PLS-SEM report. The overlap is between 0.193–0.411 (PLS) and 0.287–0.785 (R lavaan), in other words, more than one half the average margin of error. This thus indicates that the difference is not statistically significant (p > .05; Cumming, 2009).

Table 5

Confidence Intervals and Point Estimates of Two Paths

Path	B.C. 95% Confidence Interval (PLS)			B.C. 95% Confidence Interval (R Lavaan)
Path	Lower Bound	Point Estimate	Upper Bound	Lower Bound	Point Estimate	Upper Bound
knowledge sharing->partnership quality	0.193	0.369	0.568	0.287	0.536	0.785
top management support->partnership quality	0.085	0.245	0.411	0.101	0.487	0.873

Discussion and Implications

Our findings supported most hypotheses in the model (i.e., H1, H2, and H3), and confirms the significance of knowledge sharing and top management support in forming partnerships in RPO projects for project success (Ren et al., 2010; Sluyts et al., 2011). The effect size of these two predictors in predicting partnership quality (r² = 24% and 22.2% in both analyses) is far beyond the medium level (>13%) and close to a larger level (>26%; Cohen, 1992). This demonstrates that the combined adoption of both approaches (i.e., knowledge sharing, top management support) is critical for building partnerships. Together, knowledge sharing and top management support increase exchange between the outsourcing firm and the RPO provider at the project and firm levels, and thus their perceived mutual dependence and commitment to the relationship and enhanced partnership. Separately, knowledge sharing (β = .37 or .54) can generate a medium to large effect on partnership that is more noticeable to careful observers (>.30 as medium or >.50 as large; Cohen, 1992). Likewise, top management support (β = .25 or .49) can generate a small to medium effect on partnership (>.10 as small or >.30 as medium; Cohen, 1992). The slightly reduced effect in our data could be because top management in Chinese society tends to adopt a centralized and directive management style. Exchange or interaction with top management thus can bring less positive feelings or social consequences, such as like or trust. Future studies should examine if the reduced effect holds in cultures with low power distance.

Second, we argue that, like other types of projects, RPO projects require a context-specific set of measures to assess project success, in other words, PJ fit and PO fit, apart from the generic measures of project cost, time, and scope that are used to assess project management success (Sekiguchi & Huber, 2011; Serrador & Turner, 2015). Our study demonstrates PJ fit is positively associated with partnership quality (H3). Indeed, good partnership allows fine-grained information and tacit knowledge to be shared between organizations. The RPO provider thus can acquire information needed for evaluating candidates’ PJ fit and focus on finding the matched talents for outsourcing firms. Person-job fit thus could help resolve the persistent challenge of finding and identifying quality talents in RPO projects (Martinez & Padamadan, 2019; Siew-Chen & Vinayan, 2016).

Finally, our findings do not support H4. In other words, partnership is not associated with PO fit. This might be because PO fit is difficult to assess and hard to quantify. Even with good partnership, RPO providers’ judgment could sometimes be contaminated by personal prejudice and bias (e.g., social attractiveness of candidates, RPO providers’ perceived similarity with candidates). Also, it is difficult to evaluate candidates’ PO fit within a short period of time. Indeed, our data indicated that 76% of the projects lasted only for one to three months (Table 2). If candidates deliberately manage recruiters’ impression of them during the hiring process, recruiters may fail to detect that candidates are a poor cultural fit (Bolino et al., 2016). Therefore, for RPO partners to evaluate PO fit, some conditions may need to be met first, including RPO providers’ ability to detect candidates’ impression management and longer project duration. Another explanation is that PO fit is particularly important for C-suite executive hires (Watkins, 2007), but may be less so for less senior management whose jobs still feature a large portion of the technical aspect, such as the management of routine tasks. Given our data also included those of senior and middle management hires, the association between partnership and PO fit thus may be less obvious. Future studies should examine if such association between partnership and PO fit exists in RPO projects that involve the top management hires.

This study has implications for practitioners. First, the RPO project should not be considered as a one-off transaction. Rather, partnership with the RPO provider should be cultivated to jointly create value and share risks. Two critical factors that help build partnership are knowledge sharing and top management support. Our findings suggest that outsourcing firms should seek out a high level of knowledge sharing to engage the RPO provider in a series of repeated exchange. At the same time, top management can strengthen the relationship by providing necessary resources and participating in joint activities or joint problem-solving to increase exchange frequency with the RPO providers. Most importantly, top management should act in a collegial way when dealing with potential or foreseeable conflicts to induce the RPO provider’s trust and positive feelings toward the relationship. With good partnership, both the outsourcing firm and RPO provider would not confine themselves to the minimal level of resource sharing and exchange. The RPO provider thus could gain necessary information and focus on the critical aspect of the project to deliver talents that meet the outsourcing firm’s need. Finally, our study suggests outsourcing firms should have reasonable expectations about their partners’ capability for hiring good cultural fits on their behalf. More explicit discussions about cultural indicators and a reasonable project duration might help RPO partners achieve project success.

Conclusion and Limitations

This article has demonstrated how cultivating a good partnership with the RPO provider improves the chances that an outsourcing firm can obtain a good RPO outcome. This study developed and tested a conceptual model that posits knowledge sharing and top management support can affect partnership quality, leading to positive project outcomes (i.e., PJ and PO fit). We found that both top management support and knowledge sharing enhance partnership, leading to better PJ fit. However, we found no support that partnership quality predicts PO fit.

This article has several limitations. First, data were collected retrospectively and various cognitive biases on the parts of subjects could therefore have affected results. However, this limitation was partly offset by requiring HR personnel to recall a recent RPO project in the past year. Another limitation is related to the single source of data, in other words, the HR personnel of the outsourcing firm. To offset common method bias, we adopted the marker variable approach to partial out the common method variance. As an alternate approach, common method bias can be diluted if data are collected from multiple sources. Future research should collect dyadic data from both the RPO provider and the outsourcing firm. Third, the firms we surveyed are viewed in the Chinese context. The findings thus may not be applicable for firms in other cultural backgrounds. Further research is needed to see whether such relationships are generalizable to other situations. Fourth, given the huge target population, our sample size (150) may seem small and skewed (42% manufacturers). However, the lack of nonresponse bias of our data demonstrates survey quality may not be a serious concern (Schouten et al., 2009). Additionally, the skewed sample reflects the reality that in 2018 the majority of firms that outsourced their RPO were in the manufacturing industry. In addition, the RPO projects examined in this article focus on management-level talents. Further research is thus needed to see whether our findings are generalizable to projects involving the recruitment of low-ranking talents. Finally, all data collected were cross-sectional; as a result, while we can establish there is correlation among our constructs, we cannot affirm causation.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Author Biographies

Gloria Hui Wen Liu is a lecturer (Assistant Professor) in the International Business School Suzhou, Xi’an Jiaotong-Liverpool University. Her research interests include digital technology and business transformation, IS project control and coordination, e-marketing, and knowledge management. Gloria has published her work in several publications, including Computers in Human Behavior, Journal of the AIS, and Pacific Asia Journal of the Association for Information Systems. She can be contacted at glorialiu2007@gmail.com

Cecil Eng Huang Chua is an Associate Professor at the Missouri University of Science & Technology. He received a PhD in Information Systems from Georgia State University, a Master of Business by Research from Nanyang Technological University, and both a Bachelor of Business Administration in Computer Information Systems and Economics and a Master’s Certificate in Telecommunications Management from the University of Miami. Cecil has published his work in several publications, including Information Systems Research, Journal of the AIS, MIS Quarterly, and the VLDB Journal. He is a senior editor for both AIS Transactions on Human-Computer Interaction and the Pacific Asia Journal of the Association for Information Systems, desk editor for the Project Management Journal, and an associate editor for both Information & Management and the Information Systems Journal. Cecil has consulted for a range of organizations including Daimler SEAsia, General Motors Singapore, the Singapore Ministry of Defense, and Fonterra—the New Zealand milk cooperative that produces one-third of the world’s globally traded milk. He can be contacted at cchua@mst.edu

Yixuan Hu works in a company specializing in human resource management systems in Suzhou. She was a postgraduate researcher in the International Business School Suzhou, Xi’an Jiaotong-Liverpool University. Her research interests are in the areas of human resource management and project management. She can be contacted at yixuan.hu18@alumni.xjtlu.edu.cn

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