Incentivizing Relationship Investment for Project Performance Improvement

Abstract

Collaboration between developers and contractors is pivotal to the efficient completion of construction projects. Relational contracting practice has been used to promote working partnerships. Construction incentivization can be a valuable contractual tool to build relationships. This study proposes that incentivization can serve as an instrumental means to forge interorganizational relationships and corresponding project performance improvements. With data collected from experienced construction professionals, the hypotheses are empirically supported by structural equation modeling. It is therefore concluded that in addition to its conventional uses, incentivization can be innovatively designed to develop and manage interorganizational relationships and engender project performance improvement.

Keywords

incentivization interorganizational relationships contracting behavior project performance.

Introduction

The design and completion of construction projects are undertaken by multidisciplinary teams, with members coming from different organizations. Successful development of construction facilities therefore requires their concerted efforts (Das & Teng, 1998). In practice, collaboration seems not the natural mode of working among team members because of their diverging interests, which mainly derive from their home organizations. Furthermore, these teams only exist for the project duration and hence are temporary organizations that would dissolve upon completion of the project (Suprapto et al., 2016). Long-term benefits are seldom taken seriously by the team members. To achieve collaboration among team members, their respective organizational relationships must be amicable during the project (Zhang et al., 2020). For effective completion of the project, it is therefore logical to develop and manage their interorganizational relationships. Agency theory is the mostly used framework to explain the interactions between the principal and agent (Ross, 1973). In construction, the principal is the developer, and the primary agent is the main contractor. Their relationship therefore is of prime importance (Cheung et al., 2011; Caldwell et al., 2017). Notwithstanding the desire to have contracting parties cooperating for the good of the project, agency theory projects that potential conflicts between them can also be expected because of their respective interests. When parties prioritize only their own interests, the practice of opportunistic behaviors is likely (Williamson, 1979), especially when project-specific assets are invested. For example, when the cost of a contract determination becomes exorbitant, unreasonable requests from contractors are not uncommon (Pang et al., 2015; Cheung et al., 2020). This buyer–seller relationship makes collaboration the exception rather than the norm. High uncertainty creates relational risks, which increases the inclination of a contractor to act opportunistically (Bryde et al., 2019). Furthermore, Zhu and Cheung (2021b) identified the existence of equity gaps between developers and contractors in terms of power, information, expected returns, and risks. Unaddressed equity gaps are likely to be met with retaliatory behavior such as noncooperation, procrastination, opportunism, and withdrawal. Contracting difficulty can be expected when opportunistic moves are practiced. To alleviate this performance bottleneck, investment to bring a relationship beyond the traditional buyer–seller type is advocated. Failing to enhance interorganizational relationships would stifle any effort to enhance project performance

According to the above theoretical deliberations, enhanced interorganizational relationships would improve project performance by enhancing collaboration and suppressing the practice of opportunism (Lui & Ngo, 2004; Williamson, 1985). In this regard, Nguyen and Garvin (2019) suggested that fundamental changes in contracting behavior are needed. It is believed that cooperative effort from contracting parties is the key. However, conventional contractual governance is inadequate to foster cooperation (Nguyen & Garvin, 2019). In this regard, Williamson (1979) pointed out that contract incompleteness is unavoidable in complex, long-term transactions (Williamson, 1979). Pragmatic construction project management therefore calls for a more flexible and objective-driven tool to manage contracting relationships. The use of incentive schemes has been suggested to fill this gap (Bower et al., 2002; Hughes et al., 2012). Contractual incentives have been commonly used to promote the extra efforts of project participants (Liu & Ma, 2020), prevent projects running into difficulties (Richmond-Coggan, 2001), and promote innovations (Meng & Gallagher, 2012). Zhu and Cheung (2020) proposed that incentive schemes can be devised to suppress dispute occurrence.

Construction incentivization includes all forms of incentive schemes that aim to uplift project performance. Conventional construction incentivization brings about extra effort from contracting organizations (Luthans & Kreitner, 1975). To this end, the success of construction incentivization is typically evaluated by the accomplishment or otherwise outcome of targets such as cost savings, early completion, and superior quality levels (Suprapto et al., 2016). However, despite the positive design intentions, it is not uncommon to find projects with incentive schemes ending in unsatisfactory performance. Should the effectiveness of construction incentivization be singularly evaluated by the final project outcome (Hughes et al., 2007)? It is suggested that construction incentivization should take care of the behavioral side of the project (Zhu et al., 2020; Zhu & Cheung, 2020). In this connection, Rose and Manley (2011) provided valuable empirical evidence of the effects of project relationships on performance. In fact, concerted efforts made among contracting parties are paramount as far as complex construction tasks are concerned. These viewpoints and evidence all point to the significant role that interorganizational relationships can play to engender project performance. Accordingly, examining the use of construction incentivization to develop interorganizational relationships makes both theoretical and practical sense. Evaluation of the effectiveness of construction incentivization is an informative exercise. This study aims to examine the use of construction incentivization for interorganizational relationship development, which will in turn enhance project performance. The findings of this study will inform innovative design of construction incentivization that embraces developing interorganizational relationships for more enduring project performance. The study is presented in four parts. The Key Constructs of the Study section discusses the conceptual relationships of construction incentivization, interorganizational relationships, and project performance. A relationship framework among these three constructs is proposed. The Data Collection and Analysis section details the empirical work to verify the conceptual relationship framework. Analysis of the findings and recommendations are presented in the Discussion and Management Implications section. The final section presents the Concluding Remarks that summarize the findings and contributions of the study.

Key Constructs of the Study

This study examines the use of construction incentivization to develop interorganizational relationships for the enhancement of project performance. This section first discusses the three key constructs (interorganizational relationships, construction incentivization, and project performance), and hypotheses of their relationships are developed.

Interorganizational Relationships

Interorganizational relationships are the foundation of enduring linkages among organizations (Oliver, 1990). In this study, interorganizational relationships focus on the properties and overall patterns of relationships found among organizations that are pursuing certain mutual interests but remaining independent and autonomous in seeking their respective individual interests (Cropper et al., 2008; Manata et al., 2021). Relational embeddedness also captures the quality of dyadic exchanges—the degree to which the exchange party knows and considers the other parties’ needs and goals, implying the existence of a trust relationship (Song et al., 2020). The degree of interdependence and reciprocity are also found to be useful to evaluate interorganizational relationships (Cheung et al., 2018). Accordingly, interdependency (Cropper at al., 2008; Fu et al., 2015; Cheung et al., 2018), trust (Cheung et al., 2014), reciprocity (Oliver, 1990), and relationship continuity are used in this study (Güth et al., 2000; Macneil, 1974). A dedicated review was conducted to longlist the features of the four parameters, which were operationalized into the construction context to be used in the study.

Interdependency

Williamson (1985) identified three dimensions of interdependence in economic transactions: uncertainty, asset specificity, and frequency. A lock-in situation occurs when the principal can induce the agent to make asset-specific investments (Williamson, 1979). Because the value of asset-specific investments substantially increases, the principal is unable to obtain an alternative agent without incurring extra expenses. The contractual parties thus rely heavily on one another, which is a state of interdependency (Cheung et al., 2018). The termination of construction contracts or a change of partner during project duration will cause substantive losses to both parties. For construction projects, costs increase for developers as work progresses (Cheung et al., 2014). Interdependence between developers and contractors is also realized when parties perceive that high termination costs are associated with ending the relationship (Sarkar et al., 1998). Interdependency has been found to be a pillar of interorganizational cooperation (Kumaraswamy & Anvuur, 2008). Mutually dependent contracting parties realize that completion of their respective tasks is intrinsically linked (Cheung et al., 2018). Interdependent contracting parties are more willing to cooperate, as they have common interests (Heide & Miner, 1992).

Reciprocity

The search for affiliation demonstrates the desire of individuals to be accepted, understood, and communicate with one another. The desire to be affiliated can also manifest in a fear of losing intimacy or an avoidance of interpersonal conflict (McClelland & Burnham, 2008). Human altruistic instinct is a powerful force that may turn self-interested individuals into cooperative individuals (Fehr & Fischbacher, 2003). From an organizational perspective and with reference to social exchange theory, reciprocity also motivates cooperation, collaboration, and coordination among contracting organizations (Wang et al., 2019). Reciprocating exchanges during project execution contribute to the development of trust (Swärd, 2016). Reciprocity therefore is one of the bases upon which an interorganizational relationship develops (Oliver, 1990). Schermerhorn (1975) mentioned that construction incentivization can enhance working relationships and be used to set common goals and interests toward cooperation. The alignment of objectives through construction incentivization is also found beneficial to creating a more cooperative relationship instead of adversarial approaches (Bower et al., 2002). After investigating four projects using incentive schemes, Rose and Manley (2011) found that the effectiveness of financial incentive is related to the willingness to enhance relationships. In analyzing 113 capital projects, Suprapto et al. (2016) also found that positive relational attitudes among team members of a partnering/alliance contract are likely to bring about a higher level of efficiency than a lump-sum contract.

Trust

Trust is often viewed as a foundation of social order (Cheung et al., 2014). For commercial organizations, trust is seen as compensation for contractual control (Zhang et al., 2018). It is central that every transaction includes contributions from participating parties. In construction, trust has been identified as one of the key drivers in fostering cooperation (Das & Teng, 1998; Chow et al., 2015; Suprapto et al., 2015, 2016). Project managers also agree that trust is not easy to develop and can easily break down if not properly maintained (Ceric, 2016). Thus, when parties are reciprocating positively, trust among them grows; however, a major unresolved conflict can destroy a trusting relationship. As a key driver of interorganizational cooperation, the degree of mutual trust becomes an important indicator of interorganizational relationships. Cheung et al. (2011) identified these major types of trust in construction contracting: (1) system-based trust, (2) cognition-based trust, and (3) affect-based trust. System-based trust refers to trust in the performance of systemized open communication. Such arrangements can build trust through strengthened communication among contracting parties. Cognition-based trust develops from the confidence in objective knowledge that demonstrates the trustworthiness of the contracting parties. The exchange of such knowledge can be attained through interaction or observation. Affect-based trust develops on a more sentimental platform and involves emotional bonds that connect individuals who value personal attachment.

Relationship Continuity

Ashkanasy (2011) found four determinants of interorganizational climate that are significantly correlated with project participants’ satisfaction: (1) goal compatibility, (2) mutual trust, (3) relationship stability, and (4) mutual respect (Lodish & Weitz, 1987; Bock et al., 2005). Relationship stability and long-term cooperation are important for developing interorganizational relationships. Generally, relationship continuity has two dimensions: (1) for a specific construction project, the parties involved must be able to fulfill their obligations to ensure the stability of the relationship for a significant period; and (2) both parties must intend to maintain their cooperative relationship over the long term (Bock et al., 2005).

Construction Incentivization

Bower et al. (2002) define incentivization as a process through which a receiver is motivated to achieve value-added services over those already specified and of material benefit to the users. The main purpose of incentivization is therefore to enable the attainment of project objectives, whereas concerned stakeholders can enrich their respective profits (Meng & Gallagher, 2012).

Moreover, no party to a construction incentivization should be disadvantaged. Financial incentives are the most used form of incentivization to balance risks and returns in construction contracting (Saka et al., 2021). Incentives for fixed-price contracts, cost-plus-award fees, and share-in-savings all apply monetary rewards. Comparatively, nonfinancial incentive schemes, such as more frequent payments and letters of appreciation, offer encouragement instead of tangible rewards (Hughes et al., 2007). The underlying needs of the developer and the motivations of the contractor are pivotal and central to construction incentivization (Zhu & Cheung, 2021a). Effective construction incentivization therefore involves the following features: (1) goal commitment (Locke et al., 1988), (2) expectation alignment (Wigfield & Eccles, 2002), (3) information exchangeability (Laffont & Tirole, 1988; Bryde et al., 2019), (4) risk efficiency (Boukendour & Hughes, 2014), and (5) relationship investment (Adams, 1963).

Goal Commitment

Goal commitment reflects a performer’s willingness to accept a goal regardless of its difficulty, originality, or the credibility of the assigning party (Zhu & Cheung, 2018). Organizations should be clear about how their goals can be translated into construction incentivization targets (Rose & Manley, 2011). When incentives and rewards are contingent on goal attainment, an agent’s efforts to achieve these goals should increase according to the extent of benefits (Locke & Latham, 1990). Incentives must be sufficient to engage an agent in achieving these goals knowing the difficulties that may arise. It is further found that construction incentivization targets should embrace both parties’ goals (Rowlinson, 2012). Notable efforts have been made to fulfill common goals in certain construction incentivizations, with the aim of engaging the parties to work together (Rose & Manley, 2011).

Expectation Alignment

To be effective, construction incentivization should add value in at least one of the following ways: (1) The contractor believes that improved performance to the desired level is possible, (2) the contractor believes that performance improvement efforts will lead to certain positive outcomes, and (3) the resultant outcomes should be attractive to the contractor (Abu-Hijleh & Ibbs, 1989). It is also found that financial incentives are commonly effective by offering higher contract returns. Additionally, value can be a subjective benefit for the development of organizations such as future cooperation and improved reputation. The level of confidence needed to achieve a goal is also important, as it is relevant to the expectancy factor. Self-efficacy theory (Bandura, 1982) confirms the importance of self-assurance regarding sufficiency to perform at a certain level. Blomquist et al. (2016) also found that project managers’ expectations influence their contracting behavior in performing their contract responsibilities. Organizations also need to have an adequate level of confidence in their partners to cooperate (Das & Teng, 1998). Poitras (2005) found that cooperation can manifest as commitment to jointly resolving problems. The description of construction incentivization should be persuasive, and the targets should be achievable (Richmond-Coggan, 2001). These elements of instrumentality then engender support to achieve the goals of the incentives, which means sufficient resources should be accorded.

Information Exchangeability

Information exchangeability denotes that an additional information-sharing system should be established by implementing construction incentivization. Setting incentives can have the effect of lessening information asymmetry and solving principal–agent problems (Schieg, 2008). It is also stressed that temporal embeddedness helps interorganizational projects manage uncertainties (Cropper et al., 2008). For example, construction incentivization milestones would reduce transactional uncertainty (Cropper et al., 2008). This is because for additional goals, an integrated monitoring and assessment mechanism is often needed to help diminish information deficits as a project unfolds (Schieg, 2008). These contracting behaviors reduce transactional uncertainty by demonstrating, through each completed event, that a project is on track and appropriate to its market context. Screening serves as another means for the developer to collect information (Cropper et al., 2008). Screening includes all activities through which the developer obtains better information on specific project tasks. These activities are often enhanced through construction incentivization. As specific tasks are mentioned and additional information-sharing platforms are often incorporated, settings relating to communication enrich information exchange, which in turn facilitates project progress and quality control (Hetemi et al., 2020).

Risk Efficiency

A major recurring problem encountered in designing cost incentive contracts concerns setting the risk-sharing ratio (Sadeh et al., 2000). A fair and efficient risk-sharing formula would incentivize contractors by removing suspicion and fostering trust (Boukendour & Hughes, 2014). Risk efficiency can be identified by the following: (1) The allocation of risks is more balanced toward project efficiency (Zhang et al., 2016), and (2) attitudes toward risks are aligned between both parties (Zou & Zhang, 2009). Risk reallocation is a key feature of construction incentivization (Chapman & Ward, 2008). Equitable reallocation of risks aligns the risk attitudes of developers and contractors. For example, ex post revision in profit sharing induces agents to align their goals with those of the given principles. Risk reallocation also aims to reduce excessive risk premiums and minimize future construction disputes. Construction incentivization that offers substantial time and money rewards has been found to spur innovation (Zou & Zhang, 2009).

Relationship Investment

Relationship investment is another important feature of construction incentivization. It was found that the party with a power advantage often makes greater motivational and relational investments in the party with less power by sharing relational attitudes and offering mutual support and trust. Status recognition that aims for better recognition of the weaker party has been found to be important to secure increasing engagement in the relationship (Adams, 1965). A contracting relationship has been promoted to pursue mutual project benefits (Cook & Emerson, 1978). Some strategic alliances are taken as rewards for strong performers (Richmond-Coggan, 2001). This action aims to encourage construction incentivization participants to focus on long-term returns instead of short-term gains and alters the interorganizational relationship from a short-term contractual relationship to one of longer-term collaboration. The practice of opportunism is thereby reduced.

Project Performance

Project performance refers to the degree of accomplishment of project goals. Multiple dimensions are therefore required to evaluate the respective project results (Ahmadi Digehsara et al., 2018). Eisenhardt (1988) argued that monitoring target outcomes is only appropriate for highly programmable tasks. Accordingly, when tasks are repetitive and outcomes can be predicted with a high degree of accuracy, using outcome-based incentives would be suitable. Moreover, the programmability of technically demanding construction tasks is rather low because of complex coordination and the uncertain environment under which these tasks are executed. Furthermore, tasks that require innovative solutions cannot be programmed when complex interorganizational interactions are involved (Zhang et al., 2020). For non- or less programmable tasks, Eisenhardt (1988) advocated that behavior-based criteria that reflect the ways in which parties behave should also be used. For example, evaluating outcomes cannot give the recognition of efforts in process, but these efforts in developing innovative solutions should not be ignored. In all projects, every opportunity should be allowed to develop technical and managerial innovations (Dulaimi et al., 2003).

Examples of improved project performance therefore include the attainment of (1) tangible outcomes such as timing, cost, quality, and safety targets (Yu et al., 2005); (2) behavioral outcomes such as commitment and joint problem-solving (Eisenhardt, 1989; Zhang et al., 2020); and (3) innovation (technical and managerial) (Dulaimi et al., 2003).

Hypotheses Development

The Effects of Interorganizational Relationships on Project Performance

A collaborative working environment is conducive for improving working efficiency (Gunduz & Abdi, 2020). An enhanced interorganizational relationship is therefore instrumental for project performance improvement. A restrained period of cooperation would lower the transaction costs (Liu et al., 2020). In fact, the value of relational attitudes and collaborative working has been recognized (Suprapto et al., 2016) after analyzing 113 projects. It was found that project participants tend to perform better with partnership/alliance contracts than those with conventional contractual arrangements. Kumaraswamy and Anvuur (2008) also highlighted that cooperation helps minimize transaction costs for complex megaprojects (Cheung et al., 2018). Working collaboratively enhances project performance through improved working efficiency (Suprapto et al., 2015). These additional efforts are relationship investments that reinforce interdependency among project participants (Cheung et al., 2018). The first hypothesis of this study is thus as follows:

H1: An interorganizational relationship contributes to project performance improvement.

Effective Construction Incentivization Improves Project Performance

Effective construction incentivization enhances project performance improvement through both outcome evaluation and contracting behavior observation. As mentioned earlier, construction incentivization is often evaluated as project outcomes. It has been found that the behavior of agents engaged in more programmed jobs is easier to observe and evaluate (Eisenhardt, 1989). For projects of high complexity and uncertainty, the observability of the tasks should be improved for early problem identification (Eisenhardt, 1989). Interim monitoring measures are needed to identify problems before it is too late. Contractual governance is effective to improve the observability of the agents’ behaviors (Holmstrom, 1979). For example, schedule incentives encourage contractors to report their work progress. Work segregation can also reduce the indeterminacy of other parties (Hosseinian, 2016). The measurability of behavior can therefore be articulated through a clearer risk-reward trade-off. Cost and schedule incentives are more effective if an open-book approach and clear milestones are used. Likewise, schedule incentives also enable delay mitigation measures such as acceleration (Wang et al., 2018). Thus, reallocating risks and/or benefits is an effective means to cope with agency problems, since the costs of complete monitoring are exorbitant (Holmstrom, 1979; Liu & Ma, 2020). In addition, more balanced risks also encourage contracting parties to adopt innovative ideas (Bower et al., 2002). Similarly, it is also possible to use construction incentivization to reduce uncertainty by establishing feedback and review mechanisms. As a result, information asymmetry between the principal and agent can also be reduced (Zhu & Cheung, 2021b). Zhu et al. (2020) also found empirical evidence that making information available can reduce the information asymmetry created ex ante, resulting in more transparent decisions. Quality incentive schemes aim to discourage substandard work (Meng & Gallagher, 2012). The second hypothesis is thus as follows:

H2: Construction incentivization is instrumental in improving project performance.

The Interorganizational Relationship Mediates Construction Incentivization to Enhance Project Performance

Relational contracting has been advocated as an effective means to improve performance, hence raising profit margins (Zhang et al., 2020). Bounded rationality theory (Simon, 1972) posits that decision makers are passionate economists. Individuals may experience distress when facing inequitable treatment. The limitation of rationality makes them settle for satisfying instead of optimal outcomes. People are therefore sensitive to satisfying relationships (Turner, 2021). For example, those of lower status are more dependent on others and more sensitive to relationship issues (Flynn et al., 2006). The crest for equity also manifests in interorganizational relationships such as expressing anger in unfair transactions (Fu et al., 2015). Without effective redress, the distress and mistrust generated would incubate opportunistic behavior that would destroy interorganizational relationships (Adams, 1965). The detrimental effects of mistrust, such as non-cooperation and miscommunication, have also been well documented (Lawler & Yoon, 1993; Wong et al., 2005).

Which contractual vehicle can be deployed to develop interorganizational relationships? Construction incentivization is proposed for this purpose for being a unique window to revisiting some of the underlying issues such as risk ownership and compensation pattern (Zhu & Cheung, 2021b). Jelodar et al. (2016) had also suggested the use of incentives to improve the relationships among project partners. Accordingly, rewards should be given to those exercising commitment, collaboration, and teamwork toward project performance. Construction incentivization can provide the necessary motivation. It would be even better if trust could thereby be cultivated (Ceric, 2016). In this connection, Rose and Manley (2011) found the importance of providing incentives when cooperation is solicited. The relevant studies point to the multifunction of construction incentivization instead of being used singularly as financial bait. Interorganizational relationships thus can be incentivized (Oliver, 1990; Cropper et al., 2008; Kwawu & Laryea, 2014). With improved interorganizational relationships, mutual trust can be enhanced with the effect of suppressing opportunistic behavior (Ceric, 2016), raising operational efficiency (Liu et al., 2017), and minimizing construction disputes (Zhu & Cheung, 2020). Equitable risk management (Gunduz & Abdi, 2020) and risk perceptions (Yao et al., 2019) are essential motivational factors involved in developing trust. Financial incentives are also beneficial to reinforcing calculated trust in interorganizational relationships at the company level and based on the rational pursuit of financial self-interest (Bresnen & Marshall, 2000). Figure 1 presents the conceptualized relationships among the three constructs of construction incentivization, interorganizational relationships, and project performance. The third hypothesis is thus as follows:

H3: Interorganizational relationships positively help construction incentivization achieve project performance improvement.

Figure 1.

The conceptual relationships among construction incentivization, interorganizational relationships, and project performance.

Based on these three hypotheses, Figure 1 presents the conceptual relationships of construction incentivization, interorganizational relationships, and project performance. For H1, the positive connection of interorganizational relationships and project performance is presented; for H2, the relationship between construction incentivization and project performance is manifested. For H3, among the three key factors, interorganizational relationships act as a mediator between construction incentivization and project performance.

Data Collection and Analysis

A questionnaire was developed to collect data for testing the hypotheses. Experienced construction project management professionals from Hong Kong were invited to provide data. Their contacts were obtained from government associations such as the Hong Kong Institute of Architects (HKIA), the Hong Kong Institute of Surveyors (HKIS), the Hong Kong Institute of Construction Managers (HKICM), listed real estate companies, and contracting companies located in Hong Kong. The questionnaire has five parts. Part 1 focuses on demographic information. In Part 2, the respondents were asked to respond to questions about a finished project they had participated in for at least one year and where the project had used construction incentivization. The particulars of the project were also solicited. Specific questions about their role in the planning of the construction incentivization were included. Parts 3, 4, and 5 included questions relating to the three constructs. All questions were developed based on the above literature review. The respondents indicated their agreement with the descriptions on a 7-point Likert scale, with values ranging from 1 (strongly disagree) to 7 (strongly agree). The openness and randomness of question setting are addressed to reduce respondent bias (Kalu, 2019). As the online questionnaire also counts the response time, responses with too short filling times were not accepted.

The data collected were analyzed by factor analysis, which is a statistical approach used to analyze interrelationships and explain these variables in terms of their underlying dimensions (Hair et al., 2010). For this study, PLS-SEM was also used due to the nature of theoretical development and sample size applied (Hair et al., 2014). Smart PLS 3 (Ringle et al., 2018) was used to estimate the measurement and structural models in later stages of data analysis. The research method proceeded as follows:

Because of the complex component structure of the key constructs, applying a hierarchical component model (HCM) of PLS-SEM is considered appropriate (Hair et al., 2014). To verify the hypothesized relationships among the three constructs, structural models are tested through PLS-SEM.

Heterogeneity occurs when underlying groups of data are characterized by significant differences. To check if there are differences among different groups, a multigroup analysis (MGA hereafter) is needed. PLS-MGA is suggested to analyze nonparametric data (Henseler et al., 2009). For this study, it is also necessary to determine whether the relationship between construction incentivization and a project is influenced by different project roles (the developer/contractor or construction incentivization initiator/recipient).

Over 450 questionnaires were distributed through the mail and online; 142 valid responses were collected from construction professionals. The response rate was approximately 31%, and the questionnaire was closed to other construction industry studies (25%–30%) (Cheung et al., 2018; Easterby-Smith et al., 1991). Table 1 presents the contractual and organizational roles of the respondents for the investigated project.

Table 1.

The Relationship Between the Organizational and Contractual Roles in Construction Incentivization

		The Contractual Role in Construction Incentivization		Total
		Initiator	Recipient	Total
Project role	Developer	68	5	73
	Developer	93%	7%	100%
	Contractor	18	51	69
	Contractor	26%	74%	100%
Total		86	56	142
Total		59%	41%	100%

As expected, most construction incentivization projects were planned and implemented by developers, and contractors were the primary recipients. Among the 73 developer respondents, only five are construction incentivization recipients. To summarize, 79% (68 responses) of the construction incentivization projects investigated were initiated by the developer, and only 21% (18 responses) were initiated by the contractor. Table 2 shows the data for Parts 3 through 5 of the survey.

Table 2.

Descriptive Statistics for Parts 3 Through 5 of the Survey

No.	Description		Mean	Std.	Cronbach’s alpha (α)
Part 3	Interorganizational relationships				0.909
Q3.1	Interdependency(Cheung et al., 2018)	Lost transaction costs were unrecoverable when switching to another counterpart.	5.13	1.08	0.679
Q3.2		Lost time was unrecoverable when switching to another counterpart.	5.12	1.18
Q3.3		Lost project information and data were unrecoverable when switching to another counterpart.	4.30	1.15
Q3.4	Reciprocity(Suprapto et al., 2015)	Shared norms developed between the two senior management teams.	4.96	1.00	0.762
Q3.5		Project participants sensed being treated fairly when dedicating efforts toward the attainment of common goals.	5.05	1.20
Q3.6		A culture free of blame was established between the two contracting parties.	4.48	1.25
Q3.7	Trust(Cheung et al., 2011)	A good management system was established to reinforce goal achievement such as continual improvement, profit making, and business expansion.	5.27	0.95	0.901
Q3.8		Misunderstandings were avoided through open communication.	5.63	0.95
Q3.9		Information included in the contract document was explained to the affected parties.	5.35	1.01
Q3.10		Project participants engaged in positive interactions to obtain more information from the other party.	5.55	0.86
Q3.11		It is believed that one of the parties had confidence in working with the other party because it was considered honest.	5.64	0.75
Q3.12		Both parties were considerate about understanding one another’s needs and feelings at work.	5.20	0.98
Q3.13		Considerate behavior enhanced the working capacity of the counterpart.	5.26	0.99
Q3.14		A strong interorganizational relationship developed between the two parties.	5.40	0.98
Q3.15	Relationship Continuity(Bock et al., 2005)	Both parties perceived the working environment as collaborative.	5.51	0.96	0.814
Q3.16		Both parties perceived future working opportunities to be likely.	5.44	0.98
Q3.17		Both parties were willing to accept short-term dislocation by believing that it would balance out over the long run.	5.32	0.96
Part 4	Construction incentivization				0.911
Q4.1	Goal Commitment(Locke et al., 1988)	The incentive plan includes common goals agreed on by the contracting parties.	5.76	0.83	0.800
Q4.2		Notable efforts have been directed to fulfill the common goals.	5.72	0.86
Q4.3		Extra efforts had been used to fulfill the common goals when confronted with difficulties.	5.70	0.89
Q4.4	Expectation Alignment(Williamson, 1985).	The expected performance was achievable for project participants.	5.80	0.84	0.730
Q4.5		Reasonable financial bonus was set commensurate with the expected performance.	5.46	1.19
Q4.6		The performance exceeding expectations led to a certain level of rewards.	5.20	1.34
Q4.7	Information Exchangeability(Schieg, 2008)	Project information was easier to access than expected under construction incentivization.	5.01	1.08	0.612
Q4.8		Project information was exchanged smoothly under construction incentivization during the whole project.	5.40	0.93
Q4.9		The project participants’ unobserved behavior was now monitored under construction incentivization.	4.84	1.11
Q4.10	Risk Efficiency(Zou et al., 2007; Zou & Zhang, 2009)	The tender documents revealed a risk allocation pattern that was more balanced than the market norm.	5.00	1.21	0.761
Q4.11		The construction incentivization enabled a risk allocation pattern more equitable than the pattern displaced in the tender documents.	5.03	1.17
Q4.12		Sufficient resources were provided to promote innovation.	5.04	1.18
Q4.13		Sufficient resources were provided to prevent project failure.	5.32	1.07
Q4.14	Relationship Investment(Cook & Emerson, 1978; Oliver, 1990)	The spirit of partnership was promoted to pursue mutual benefits for the project.	5.57	1.16	0.790
Q4.15		Provisions are included in the construction incentivization to compensate additional works due to unforeseen events.	5.26	1.21
Q4.16		The compensation for item Q3.16 was based on the principle of deriving a win-win situation.	5.57	1.04
Q4.17		The construction incentivization focused more on long-term returns instead of short-term gains.	5.25	1.05
Part 5	Project performance				0.897
Q5.1	Behavior Outcome(Eisenhardt, 1988)	The contractor’s behavior could be systematically evaluated during the whole project.	5.24	1.07	0.858
Q5.2		Programmable tasks were completed at each stage of the project.	5.09	1.14
Q5.3		Unexpected situations and difficulties encountered were handled effectively by contracting parties.	5.09	1.10
Q5.4		The contracting parties cooperated with one another to maximize common interests, not just for their own interests.	5.07	1.24
Q5.5		The contracting parties will seek cooperation and value cocreation in the future.	5.15	1.14
Q5.6	Hard Outcome(Yu et al., 2005)	The project cost fell within overall budget limits.	5.10	1.36	0.891
Q5.7		This project achieved a satisfactory level of project quality.	5.41	1.10
Q5.8		This project was completed on time.	4.49	1.65
Q5.9		The volume of disputes was controlled to a reasonable range.	5.25	1.09
Q5.10		The number of disputes was controlled to a reasonable range.	5.20	1.14
Q5.11	Innovation(Dulaimi et al., 2003)	Innovations were generated by the developer through the project.	4.53	1.47	0.796
Q5.12		Innovations were generated by the contractor through the project.	4.63	1.50
Q5.13		Improvements in project performance (e.g., cost savings, shortened construction periods, and quality improvements) surpassed expectations.	4.76	1.42
Valid N		142

Table 2 presents the general descriptive statistics of the data. The mean scores for most of the questions regarding interorganizational relationships are all above 5 (slightly agree), suggesting that basically all the construction incentivization projects achieved a satisfying level of interorganizational relationship. For interorganizational relationship development, the lowest score (Q3.3: Misunderstandings were avoided through open communication and Q3.1: It is believed that one of the parties had confidence in working with the other party because it was considered honest) is 4. Thus, the respondents agreed that the interorganizational relationship was maintained at a sufficient level in these two areas. Responses with the highest mean scores are related to trust building. System-based trust (Q3.8) and cognition-based trust (Q3.11) were achieved in all the projects.

For Part 4, the average scores of most responses are all above 4 (Neutral). The highest mean score was obtained for Q4.4 (The expected performance was considered achievable for the project participants) (5.80) and for Q4.1 (showing that incentive plans applied common goals set by the contracting parties) (5.76). The standard deviations of these two items are 0.84 and 0.83, respectively, which are the lowest two among all the items measured in Part 4. For Part 5 (project performance), all the mean scores are above 4. The results show that all the behavioral outcomes are the most satisfying, with all the mean scores being above 5. The highest mean score was found for Q5.7 (this project achieved a satisfactory level of project quality) and the lowest was found for Q5.8 (this project was completed on time).

Collinearity arises when two indicators are highly correlated (Hair et al., 2010). Collinearity can have an impact on the estimation of weights and statistical significance in PLS-SEM analysis (Hair et al., 2014). Hence, redundant or conflicting indicators should be removed as deemed appropriate. In this study, no redundant or conflicting indicators were detected after Pearson’s correlation test. Cronbach’s alpha (α) is widely used to assess the internal consistency of the constructs. A threshold value of 0.6 has been proposed (Davcik, 2014). All the indices in Table 2 are acceptable for further analysis. For PLS, composite reliability is a measure of internal consistency (Hair et al., 2014). The composite reliability of all constructs should satisfy the threshold of 0.70 (Hair et al., 2014; Davcik, 2014). Moreover, average variance extracted (AVE) is also tested to check convergent validity (Hair et al., 2012). An AVE of higher than 0.5 is acceptable, but 0.4 is still adequate when the composite reliability level is higher than 0.6 (Fornell & Laecker, 1981). The composite reliability and AVE of these constructs are summarized in Table 3.

Table 3.

Composite Reliability and Average Variance Extracted (AVE)

	Composite Reliability	Average Variance Extracted (AVE)
Interorganizational relationships	0.94	0.51
Interdependency	0.88	0.90
Reciprocity	0.76	0.68
Trust	0.91	0.60
Relationship continuity	0.82	0.73
Construction incentivization	0.93	0.43
Goal commitment	0.88	0.71
Expectation alignment	0.79	0.57
Risk efficiency	0.85	0.59
Information exchangeability	0.85	0.66
Relationship investment	0.87	0.62
Project performance	0.92	0.48
Hard outcome	0.89	0.62
Behavior outcome	0.90	0.64
Innovation	0.88	0.71

Among the interorganizational relationship parameters, Q5.3 (lost time was unrecoverable when switching to another counterpart) has low loading (0.008) with no significance (0.968) in the HCM analysis. Cheung et al. (2018) found similar results, and Q5.3 was removed for consistency. With that, the data pass the specifications and hence can be used for PLS-SEM analysis.

PLS-SEM Analysis

The following provides an account of the PLS-SEM analysis of the study. The reflective measurement model fit was also assessed (Hair et al., 2014).

Stage 1: Testing the relationship between interorganizational relationship and project performance (H1)

The data were tested through bootstrapping with 5,000 subsamples at a significance level of 5%. A one-tailed t-test was also conducted. The null hypothesis should be rejected if p > 0.05. The path coefficients of the PLS-SEM analysis results are shown in Figure 2.

Figure 2.

PLS-SEM analysis results for H1.

A positive correlation was found between interorganizational relationships and project performance. When applying a 5% significance level, all the relationships in the structural model are significant. All the path loadings are of a significant level; among them, relationship investment has the highest loading (0.867). For project performance, behavioral and hard outcomes have high loadings (0.90). Harvesting innovations through construction incentivization seems less forthcoming than these two outcomes.

Stage 2: Testing the relationship between construction incentivization and project performance (H2)

Similarly, the path coefficients were tested by bootstrapping with 5,000 subsamples at a significance level of 5%. The PLS-SEM analysis results are shown in Figure 3.

Figure 3.

PLS-SEM analysis results for H2.

A positive correlation was also found between construction incentivization and project performance. When applying a 5% significance level, all relationships of the structural model are significant. All path loadings are valued at approximately 0.80 at a significant level of 5%; among them, relationship investment again has the highest loading (0.869).

Stage 3: Testing the role of interorganizational relationships between construction incentivization and project performance (H3)

Based on the same bootstrapping procedure, the PLS-SEM analysis results for H3 are shown in Figure 4.

Figure 4.

PLS-SEM analysis results for H3.

Figure 4 presents the interorganizational relationship as a mediator of construction incentivization on project performance. When applying a 5% significance level, the relationships among construction incentivization, interorganizational relationships, and project performance as projected by the framework (see Figure 2) are validated. The total effect of construction incentivization on project performance is 0.702 (see Figure 3). Within the total effect, the direct effect between construction incentivization and project performance is 0.349 (see Figure 4). The indirect effect of construction incentivization on project performance is 0.355 (0.782*0.454 = 0.355), accounting for approximately 50% of the total effect of construction incentivization on project performance. This result further suggests the mediating role of interorganizational relationships. In sum, the relationship framework shows a positive correlation between construction incentivization and project performance. The interorganizational relationship acts as a partial mediator between these two constructs.

The Statistical Fit of the Relationship Frameworks

The R² value is the most used measure to evaluate the fitness of a structural model. The value is a measure of a model’s predictive accuracy and is calculated as the squared correlation between a specific endogenous construct’s actual and predicted values (Hair et al., 2014). It has been suggested that R² and adjusted R² values of greater than 0.10 are acceptable (Falk & Miller, 1992). The R² value of the overall model is shown in Table 4.

Table 4.

The R² Value of the Overall Model

Factor	Stage 1 (H1)		Stage 2 (H2)		Stage 3 (H3)
Factor	R²	R²Adjusted	R²	R²Adjusted	R²	R²Adjusted
Construction incentivization	–	–	–	–	–	–
Goal commitment	–	–	0.67	0.667	0.667	0.664
Expectation alignment	–	–	0.652	0.649	0.650	0.648
Information exchangeability	–	–	0.617	0.614	0.617	0.614
Relationship investment	–	–	0.753	0.751	0.754	0.753
Risk efficiency	–	–	0.72	0.718	0.722	0.720
Interorganizational relationship	–	–	–	–	0.613	0.610
Interdependency	0.235	0.229	–	–	0.246	0.241
Reciprocity	0.661	0.659	–	–	0.656	0.653
Relationship continuity	0.821	0.820	–	–	0.822	0.821
Trust	0.952	0.951	–	–	0.951	0.951
Project performance	0.495	0.492	0.495	0.492	0.574	0.568
Behavior outcome	0.879	0.878	0.879	0.878	0.878	0.877
Hard outcome	0.821	0.82	0.821	0.82	0.818	0.817
Innovation	0.472	0.469	0.472	0.469	0.477	0.474

Effect size f² and Stone-Geisser’s Q² value were examined to evaluate the R² values of all endogenous constructs (Hair et al., 2014). Cohen (1988) suggested that values of 0.02, 0.15, and 0.35 represent weak, moderate, and large effects, respectively. The Q² value is also assessed by the blindfolding procedure. The smaller the difference between the predicted and original values, the greater the Q² value (Ringle et al., 2018). The degree of Q² values is considered as low, moderate, and high at respective values of 0.02, 0.15, and 0.35 (Hair et al., 2014). Accordingly, the R² values and effect size f² of the study satisfy the thresholds. The f² and Q² values of the constructs are shown in Table 5.

Table 5.

Effect Size f² and Q² Values

	Stage 1 (H1)		Stage 2 (H2)		Stage 3 (H3)
	Effect size f²	Q² (=1-SSE/SSO)	Effect size f²	Q² (=1-SSE/SSO)	Effect size f²	Q² (=1-SSE/SSO)
Construction incentivization	–	–	–	–	–	–
Goal commitment	–	–	2.028	0.470	2.001	0.470
Expectation alignment	–	–	1.872	0.420	1.858	0.413
Information exchangeability	–	–	1.611	0.34	1.611	0.338
Risk efficiency	–	–	2.566	0.41	2.593	0.410
Relationship investment	–	–	3.041	0.44	3.073	0.436
Interorganizational relationship	–	–	–	–	–	0.301
Interdependency	0.307	0.194	–	–	0.327	0.204
Trust	19.673	0.561	–	–	19.572	0.561
Relationship continuity	4.596	0.586	–	–	4.613	0.586
Reciprocity	1.951	0.434	–	–	1.903	0.430
Project performance	1.108	0.244		0.23	–	0.267
Behavior outcome	7.105	0.548	7.272	0.55	7.217	0.550
Hard outcome	4.689	0.488	4.582	0.49	4.508	0.489
Innovation	0.927	0.324	0.895	0.32	0.914	0.321
Construction incentivization–project performance	–	–	0.982	–	0.11	–
Construction incentivization–interorganizational relationship	–	–	–	–	0.187	–

Heterogeneity

Following the research design, a heterogeneity test was conducted to enrich the implications of the proposed framework with regard to the key stakeholders involved. To achieve this, the different views of the developer, contractor, construction incentivization initiator, and construction incentivization recipient were analyzed. The group differences between the developers and contractors are shown in Table 6.

Table 6.

Group Differences Between the Developers and Contractors

Description	Path Coefficients-diff (Developer–Contractor)	p-Value new (Developer vs. Contractor)
Construction incentivization → Information exchangeability	-0.179	0.035
Construction incentivization → Risk efficiency	0.012	0.012
Construction incentivization → Interorganizational relationship	0.169	0.003

Table 6 summarizes the significant differences found through PLS-MGA and shows the different rankings of the primers of construction incentivization for developers and contractors. Information exchangeability tends to be a more significant contributor for the contractor than developer. Comparatively, the group difference of risk efficiency is small. For the effect of construction incentivization on building interorganizational relationships, the relationship tends to be stronger for the developer than contractor. From the PLS-MGA study, the group differences are shown in Table 7.

Table 7.

Group Differences Between Construction Incentivization Initiators and Recipients

Description	Path Coefficients-diff (initiator–recipient)	p -Value new (initiator–recipient)
Construction incentivization → Information exchangeability	-0.179	0.007
Construction incentivization → Expectation alignment	-0.141	0.003

From the MGA of construction incentivization initiators and recipients, no significant differences were detected for the structural relationships among construction incentivization, interorganizational relationship, and project performance. The results show that construction incentivization recipients recognize the value of construction incentivization most in terms of improving communication effectiveness and aligning the expectations of two parties.

Discussion and Management Implications

The two major findings of this study are summarized as follows.

Developers are more receptive to using construction incentivization to effect interorganizational relationships than contractors.

The effectiveness of construction incentivization in encouraging interorganizational relationship building differs between developers and contractors. Compared to contractors, developers have a greater interest in building interorganizational relationships through construction incentivization. Moreover, Table 7 shows that the relationship between construction incentivization and interorganizational relationships is much stronger for respondents initiating the construction incentivization. The investigation also shows that most construction incentivization projects are introduced unilaterally. Differences are also found between construction incentivization initiators and recipients. Recipients recognize construction incentivization less than initiators. This result shows that construction incentivization has a less positive effect on recipients in nurturing trust and developing relationship continuity.

The three hypotheses (H1, H2, and H3) are empirically validated.

Path coefficients were tested with 142 valid responses through bootstrapping with 5,000 subsamples at a significance level of 5%. PLS-SEM analysis results show that the three hypothesized relationships are supported. It is found that interorganizational relationship (H1) and construction incentivization (H2) are instrumental for behavior-based project performance improvement. Validating H3 is the most important as far as the role of interorganizational relationship is concerned. Although both interorganizational relationship and construction incentivization can engender project performance, when behavior outcomes matter the interorganizational relationship becomes influential, accounting for approximately 50% of the total effect between construction incentivization and project performance. The role of interorganizational relationship is therefore critical (Hair et al., 2014). This three-step analysis presents the flow of the development logic of the relationship framework. The interrelationship among the three constructs is built on the theoretical findings between construction incentivization and interorganizational relationship on project performance separately first and then holistically. The findings clearly explain why the use of outcome targets does not guarantee the success of construction incentivization. The soft element of the interorganizational relationship is often neglected, as insufficient effort is made to foster trust and cooperation.

The two major findings inform the following management implications:

The details of construction incentivization should be negotiated and agreed on by the parties involved.

The first major findings of the study indicate that construction incentivization recipients are less receptive to the construction incentivization. Thus, unilateral imposition of a construction incentivization will be different with the expectations of the recipient. Several potential defects of construction incentivization are solely decided on by the developers. First, there is a high chance that only the interests of the developers are taken into consideration. Second, a take it or leave it attitude is likely to be perceived. Third, the outcome targets may not be achievable without the input of the ultimate performers. As such, they may all run against the key elements of construction incentivization: goal commitment, information exchangeability, expectation alignment, risk efficiency, and relationship involvement. Most importantly, if the reward is not commensurate with the efforts required, the construction incentivization will fail.

Construction incentivization must incorporate measures to develop interorganizational relationships.

The second major findings of the study confirm the often-neglected design coordination of construction incentivization. Conventionally, construction incentivization only deals with hard project outcomes such as time, cost, quality, and safety. The reward of construction incentivization is heavily if not solely attached to the attainment of quantified project targets. As explained in the Data Collection and Analysis section, this approach is not suitable for non- or less programmable complex construction tasks. This issue is far more damaging when unanticipated happenings require the collective efforts of the contracting parties. Zhu and Cheung (2021a) advocated that equity gaps are conducive for contracting organizations practicing opportunistic behavior. This study enlightens novel design of construction incentivization, in other words, to embrace behavior outcomes as part of the project outcome targets. Specifically, the behavioral measure of interorganizational relationships should be monitored longitudinally and the reward for same should be separated from hard outcome targets. The evaluation of interorganizational relationships can make use of the respective measurements developed in this study (see items 3.1 through 3.7 in Table 2).

Concluding Remarks

Construction work is project based but requires inputs from different professional disciplined organizations. With individual interests, engendering collective effort from these organizations to accomplish project goals is challenging. The interorganizational relationship underpins the willingness to collaborate. As such, it is essential for project leaders to foster interorganizational relationships. It is suggested that construction incentivization can play a pivotal role in delivering project performance when it is designed to develop interorganizational relationships.

Through a literature review for interorganizational relationship, interdependency, trust, reciprocity, and relationship continuity were studied and five key features of construction incentivization were found: goal commitment, information exchangeability, expectation alignment, risk efficiency, and relationship investment. Project performance is developed in terms of behavioral and hard outcomes and innovation. Three hypotheses are developed as follows:

H1: An interorganizational relationship contributes to project performance improvement;

H2: Construction incentivization is instrumental in enhancing project performance; and

H3: An interorganizational relationship developed through construction incentivization will engender project performance improvement.

A PLS-SEM analysis was accordingly conducted with data obtained from construction professionals. Two major findings were obtained. First, construction incentivization details should be negotiated and agreed on by the parties involved. Second, construction incentivization must incorporate measures to develop interorganizational relationships.

This study contributes to interorganizational motivation studies by offering a novel way to engender performance improvement through incentivization. Systematic analysis on interorganizational relationships and project performance establish that relationship investment incentivizes performance improvement. Furthermore, construction incentivization can be more effective when behavior-based motivators are incorporated. Construction incentivization, therefore, can be used beyond its conventional scope of setting targets and rewards. Moreover, the ways of construction incentivization must not be unilaterally sanctioned by the initiators. Aligning the interests of both the construction incentivization initiators and recipients shall pave the groundwork for cooperation.

Notwithstanding, a larger sample size would also add merit to the findings. The study was conducted in Hong Kong, and there may be differences in the contracting arrangements of other geographic locations; moreover, the corresponding planning of construction incentivization in different regions may be similar.

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) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The work described in this article was fully supported by CityU SRG (project no. 7005684) and HK RGC GRF (project no. 11202722).

ORCID iD

Liuying Zhu

Author Biographies

Dr. Liuying Zhu works at the School of Management, Shanghai University. She studied construction management and received her MSc degree (distinction) and PhD degree from the City University of Hong Kong. Dr. Zhu is a member of the Construction Dispute Resolution Research Unit (CDRRU). Her research mainly focuses on construction project management, construction incentivization, and project dispute avoidance. Dr. Zhu is the author of several publications in international journals and book chapters in these domains. She can be contacted at zhuliuying@shu.edu.cn.

Professor Sai On Cheung is the Lead of the Construction Dispute Resolution Research Unit (CDRRU) of the Department of Architecture and Civil Engineering, City University of Hong Kong. Building on his industrial experience in contract administration, Professor Cheung has developed research programs in and has published widely on organizational issues in construction, contract, and dispute management. The CDRRU has also published the following research monographs: “Trust in Co-operative Contracting in Construction,” “Construction Dispute Research: Conceptualisation, Avoidance and Resolution,” “The Soft Power of Construction Contracting Organisations,” and “Construction Dispute Research Expanded.” Professor Cheung is a recipient of the 2010 City University of Hong Kong Teaching Excellence Awards. He can be contacted at Saion.Cheung@cityu.edu.hk

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