Mitigation Measures for Information Asymmetry between Participants in Construction Projects: The Impact of Trust

Abstract

Sustainability requirements pose complex challenges for the construction industry, requiring adaptation strategies, innovative solutions, and collaboration between stakeholders to build resilient structures for the future. Nevertheless, effective collaboration between stakeholders is hindered by information asymmetry, which can produce disputes, endanger honest communication between the participants, and in the long term, negatively affect industrial productivity. To improve the sustainability of construction businesses and construction projects, there is a need for the implementation of mitigation measures for information asymmetry risks. This study presents possible mitigation measures for information asymmetry between clients and contractors in the construction industry. Mitigation measures were identified through a literature review and semi-structured interviews with industry professionals. Furthermore, a questionnaire was designed and employed to prioritize mitigation measures and explore their utility for mitigating three types of risks: adverse selection, moral hazard, and hold-up. The results of this study indicate that building trust, regular supervision and monitoring of work, thorough verification of bidders, and fair distribution of risks between the client and the contractor have the most utility in mitigating information asymmetry in construction projects. The practical contribution of this research includes defining the most useful measures to mitigate risks caused by information asymmetry. Project managers can apply the results of this research for more successful achievement of their project goals. Implementing effective risk management strategies, such as building trust between stakeholders, can help mitigate the impacts of unforeseen events and build resilience in construction projects.

1. Introduction

In 2020, 37% of all CO₂ emissions related to energy worldwide came from the construction industry [1]. Owing to its growth, construction will surely have a significant role in reaching future global sustainability targets, which are in place given the widespread worries about climate change and global warming [2]. Undoubtably, sustainability is one of the main objectives of the construction industry. However, construction projects have a well-known problem with achieving their objectives [3], even with the industry’s growing technological advancement. This is because construction projects often face many risks and uncertainties [4].

This study investigates the mitigation measures for risks arising from information asymmetry among participants in construction projects. Previous research has recognized these risks as significant for construction projects and indicates that they are still not adequately managed [5,6,7]. Information asymmetry, or the asymmetry in possessing information crucial for achieving project objectives, represents a situation where participants in such relationships do not share information with other parties [8]. The concept of information asymmetry originates from principal–agent theory, which describes a relationship in which a principal hires an agent to carry out a task on their behalf [9].

Information asymmetry is an important factor that affects decision-making and management processes in construction projects. Principal–agent theory can be applied to construction projects because there is an agency relationship among project participants, meaning there are principals and agents who act on behalf and for the account of the principals. In a construction project, the client is the main principal. The client’s agents include the designer, contractor, supervising engineer, project manager, and others. Similarly, a contractor can be a principal to their subcontractors. Given the large number of different participants and the complexity of construction projects, there are many principal–agent relationships, and therefore, many principal–agent problems, which pertain to situations where one party does not have all the information about the other party [10]. In other words, information asymmetry is present in all these relationships, which can lead to issues in planning, execution, and project management.

According to the simplest model of principal–agent theory in construction, the client is the principal, and the contractor is the agent who needs to build a certain structure for the client [10]. Such an agency relationship is characterized by information asymmetry between the principal and the agent, different risk preferences, and a desire to maximize the personal benefit, often leading to opportunistic behavior among project participants [11]. Therefore, this study investigates the relationship between the client and the contractor. The client may have more information about the financial aspects of the project, the budget, deadlines, or expectations from the contractor. This can lead to situations where the contractor is not fully aware of the financial constraints or goals of the client, which can affect the planning and execution of the project. On the other hand, the contractor has more information about their own efforts, the project progress, or the construction quality, which is difficult for the client to fully control since every form of control incurs additional costs.

There are three common problems within principal–agent theory, namely, hidden characteristics, hidden actions and information, and hidden intentions [12]. If not properly handled, risks resulting from information asymmetry between project participants might substantially undermine project goals [7].

The issue of hidden characteristics is present even before the principal and agent sign a contract (ex ante). This problem occurs when the principal cannot observe the agent’s characteristics ex ante, such as its efficiency or resource availability [13]. Adverse selection (AS) refers to risks that materialize in the form of hidden characteristics prior to the principal and agent signing a contract [13,14].

After the principal and the agent sign the contract, hidden actions and information problems arise. These issues are linked to the agent putting in less effort to complete the task [12]. This type of information asymmetry results from the principal’s inability to monitor the agent’s activities during the job execution process (hidden actions) and evaluate them (hidden information) [15]. As a result, the principal has knowledge of the agent’s performance results but is unable to determine whether or not the agent’s effort was maximal. Moral hazards (MHs) refer to risks that emerge following contract signing in the form of hidden information and activities [16].

The third issue, known as hidden intentions, pertains to a scenario in which the genuine intentions of one party become apparent to the other subsequent to the contract’s signature [12]. In this instance, one party’s opportunistic actions are exposed to the other, but because resources are already allocated to the partnership, the latter has little negotiating power. As a result, hold-up (HU) risks occur [15].

Recent construction research has incorporated principal–agent theory and information asymmetry [5,17,18,19]. In a systematic literature review on the topic of information asymmetry in management, Bergh et al. [20] recognized the need to explore the link between sources of information asymmetry and possible measures to mitigate it by forming lists of alternative solutions. This study was focused on that issue, specifically in the relationship between the client and the contractor in the execution of construction projects.

To effectively manage project risks, or to reduce their likelihood or impact on project objectives, it is necessary to understand possible mitigation measures. The goal of this study was to produce information about possible mitigation measures for risks caused by information asymmetry. To do so, this research objectives were (1) to identify the mitigation measures for risks caused by information asymmetry, and (2) to rank the identified measures according to their utility to mitigate the risks caused by information asymmetry.

In the following section, possible mitigation measures for information asymmetry between clients and contractors in the construction industry are outlined, as identified through a literature review and semi-structured interviews with industry professionals. This paper also further evaluates the identified measures by ranking them according to their utility in mitigating risks caused by information asymmetry. The mitigation measures are ranked according to their utility in mitigating three types of information asymmetry risks: AS, MH, and HU. The methods for collecting and analyzing data to rank the measures are presented in Section 3. Furthermore, this paper presents the results of the questionnaire survey and a discussion of the most useful mitigation measures.

This research provides a contribution in defining the most effective strategies to address the risks associated with information asymmetry in construction projects. Project managers can utilize these findings to improve their approaches, thereby enhancing the successful achievement of project goals. By systematically ranking mitigation measures based on their effectiveness, this study offers a valuable resource for industry professionals seeking to manage information asymmetry more efficiently.

2. Review of Possible Mitigation Measures for Information Asymmetry in Construction Projects

In this section, a review of measures identified through the literature review and semi-structured interviews with industry professionals is presented.

The literature review involved a systematic review of previous research that has addressed information asymmetry in construction projects. Some of the results from the systematic literature review were previously published in [21]. This article reports part of the research regarding mitigation measures. The main goal of the literature review was to identify and extract possible measures to mitigate risks caused by information asymmetry. The reviewed scientific literature was categorized within two prominent online databases of scholarly publications, the Web of Science Core Collection and Scopus, providing a comprehensive view of the implications of information asymmetry for construction projects. The following keywords were used in the computer search: “asymmetric information”, “ information asymmetry”, “adverse selection”, “moral hazard”, “hold-up”, and “construction”. These terms were combined and searched across scientific paper titles, abstracts, and keywords. The obtained records were filtered in accordance with the accepted PRISMA methodology [22]. Ultimately, 64 articles met this study’s eligibility requirement of mentioning one or more risk mitigation strategies related to information asymmetries. Furthermore, to determine the practical value of data collected from the scientific literature, semi-structured interviews were conducted to add more richness and detail to the collected data [23]. This part of the research is explained in Section 3.

A review of the literature identified 13 possible measures for mitigating risks caused by information asymmetry. The measures are presented in

Table 1. List of possible mitigation measures for information asymmetry in construction projects according to the literature review.

ID	Mitigation Measures	Sources
M1	Incentives for the agent (bonuses)	[7,11,17,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53]
M2	Signaling (advertising, reputation)	[25,26,33,39,40,42,54,55,56,57,58,59,60,61]
M3	Building trust and cooperation	[7,17,19,25,30,42,45,56,61,62,63,64,65]
M4	Information systems	[8,19,25,30,41,42,45,50,51,56,60,63,66,67,68,69]
M5	Regular and thorough quality control	[11,29,33,34,35,40,51,70,71,72]
M6	Contractually defined benchmarks for monitoring the agent’s work	[7,17,26,30,39,45,58,73,74]
M7	Fair distribution of risk between the principal and the agent	[18,19,45,47,48,67,75,76]
M8	Contractual penalties	[7,26,29,45,50,77]
M9	Screening of bids	[17,27,34,35,60,78,79]
M10	Screening of bidders (certificates, guarantees, financial stability)	[17,50,55,60,61]
M11	Intrinsic awards for the agent, which include reputation enhancement, discretion, autonomy, responsibility, satisfaction in the job, stability, and mission alignment	[37,45,51,77]
M12	Vertical integration and strengthening the internal capabilities of principals (reducing outsourcing)	[34,35,62,79]
M13	Selection of a bidder that has a similar organizational culture (values, goals)	[25,42,80]

and are sorted by their frequency of occurrence in the literature.

In 38 articles, information asymmetry is discussed and developed further or enriched by new models or concepts. In another 28 articles, information asymmetry is only mentioned or applied as a concept in research on other topics. The majority of the retrieved articles bring new insights, frameworks, models, etc. Lützkendorf and Speer released the first paper of this type regarding information asymmetry in the markets for residential and commercial real estate in 2005 [57]. They conducted an investigation using the conceptual modeling method. They suggested a building information system as a remedy for the knowledge asymmetry between suppliers and purchasers, which is where the shaky connection to construction lies. The topic’s actual development began after 2007. Since then, case studies, questionnaire surveys, and simulation methods have been employed by most authors to enhance the principles under consideration. Employing a variety of research methods, including case studies, questionnaires, and simulations, the research on this topic is well-rounded and robust. This methodological diversity enhances the reliability and validity of the findings.

The most popular method used in the retrieved articles is simulation. Typically, incentive contracts are designed using the simulation method [27,32,33,38,46,51,52]. The impacts of implicit incentive systems, like changes in cooperation and reputation, are investigated [37,64]. The extensive use of simulation models allows for the exploration of various scenarios and the assessment of different mitigation measures. However, while helpful for scenario analysis, a large reliance on simulation techniques may oversimplify the complexity and human elements present in actual construction projects. The accuracy and applicability of the findings in real-world scenarios may be impacted by this simplification.

Furthermore, a number of case studies were used to investigate possible mitigation measures for information asymmetry problems (see [26,30,36,45,53,54,56,59,71,73,79]). The inclusion of detailed case studies, such as those on the Channel Tunnel Rail Link project [54], provides concrete examples of information asymmetry and its impacts. These case studies offer practical insights and illustrate the real-world application of theoretical concepts. Nonetheless, while case studies provide valuable insights, their findings may not be universally applicable due to the unique contexts and specificities of each project.

Articles also used questionnaire surveys and interviews to investigate the strategies for minimization of information asymmetry in construction projects [17,25,63]. Through surveys and interviews, the research delves into the causes and effects of information asymmetry, providing a deeper understanding of the underlying factors and their implications. Nevertheless, results derived from questionnaires and interviews can be subject to biases, such as self-reporting biases and limited sample sizes. Therefore, articles relying on one method should be carefully interpreted.

Most of the analyzed scientific articles mention one or more measures for mitigating risks caused by information asymmetry. However, the management of risks caused by information asymmetry is insufficiently represented, both in the scientific literature and in the practice of construction project management. The main theoretical terms (information asymmetry, adverse selection, moral hazard, hold-up) are often mentioned independently in articles, indicating that the topic is frequently investigated without real theoretical foundations.

Using a systematic literature review, this study was able to identify explicitly mentioned risk mitigation measures from the retrieved articles, considering all the positive and negative aspects of these studies. The mitigation strategies that are most commonly discussed in the literature concern designing so-called optimal contracts and managing them while they are being executed [31]. Among these steps is the definition of agent incentives. Contracts, for instance, include provisions intended to incentivize contractors to provide clients with truthful reports of their costs [24,65] and other pertinent information [67], finish the work in accordance with the plan [27,28], recover from unanticipated events [36], and adjust to changing project conditions [38,49,52]. The contract should also include a fair risk distribution [75], objective criteria for the contract’s enforceability [26,73], parties’ clear intentions [11], clearly defined performance requirements, technical specifications, and quality standards [58], and protective measures (guarantees) [61]. Contracts should also stipulate rewards for contractors in the event of early job completion and meeting the required quality [26], and for ensuring cost savings [45,76]. Similarly, contractors should be subject to penalties for not finishing the project within the allocated budget and timeline [76,77]. Additionally, the project should have an appropriate reporting and contract execution monitoring system [17,30], as well as a contractor performance evaluation system [39].

Before signing a contract, the principal, or client, should implement strategies to identify the characteristics of the agents or contractors who have submitted their bids (screening). This can be achieved in three different ways. First, the client can research the companies that have applied for the tender [55]. This involves investigating the background, reputation, and past performance of the bidding companies. The second way is to conduct a detailed analytical review of the contractors’ submitted bids [27]. This includes comparing the bids to market prices to ensure they are reasonable and competitive. The third option is to request guarantees from the bidders. This can be carried out by asking for deposits [39], advance payments, or bank guarantees [59], which ensure that the contractors are financially committed and capable of fulfilling their contractual obligations.

On the other hand, agents can also signal their characteristics to the principal by presenting their certificates [56] or advertising in various ways [56,60]. One of the significant risks for agents is price dumping; knowing certain methods for calculating the optimal bid can help them avoid this risk [78].

A large number of risks caused by information asymmetry can be prevented during the selection of the agent or bidder. This is achieved if the client has the opportunity to choose a bidder with a good reputation [33], a similar organizational culture [42,80], or with whom they have established long-term and partnership relationships [19].

Effective quality control is crucial for mitigating risks associated with information asymmetry during construction [29]. Besides adequate control, participants should collaborate and share information and rewards from the very beginning of the project [63]. Communication among participants should be transparent and accountable [17,61], credible [61], honest [7], and fairly informal [30]. Additionally, trust among participants should be built and maintained throughout the entire project [25]. The principal should ensure intrinsic (non-monetary) rewards for the agent, which include reputation enhancement, discretion, autonomy, responsibility, job satisfaction, stability, and alignment of goals [37]. Finally, transparent information management can be facilitated through various information systems [66], such as BIM [68,69], blockchain [68], project management platforms [50], and the introduction of open-book accounting [19,41].

It can be assumed that not all of the mentioned measures are equally effective in reducing risks caused by information asymmetry and that they cannot be applied in all conditions. To determine which measures are more useful and which risks they can most effectively address, further research was conducted on the opinions of experts in the field of construction. The following section describes the data collection and processing methods used in this study.

3. Methods

The goal of the risk management process is to reduce the likelihood of risks occurring and/or their impact on the project. To determine the practical value of data collected from the scientific literature, semi-structured interviews were employed with experts who have significant experience in construction projects. The main advantage of the interview method is the richness and detail of the collected data [23]. Therefore, this method was chosen to further enrich the data from the literature.

Furthermore, to determine which of the mentioned measures are most important in the context of reducing information asymmetry risks in construction projects, a survey questionnaire was created. The purpose of the questionnaire was to facilitate group decision-making on the most useful measures for mitigating information asymmetry risks in construction projects.

Group decision-making was chosen for this research because it is necessary to consider four different perspectives:

• Clients in public projects (PubCl);
• Contractors in public projects (PubCon);
• Clients in private projects (PrCl);
• Contractors in private projects (PrCon).

Group decision-making has proven to be very useful compared to individual decision-making. The advantages include the following [81]:

• Better decisions:
  • As the number of group members increases, there is a higher likelihood that more stakeholders will be represented and their interests included in the decision-making process;
  • Involving specialized experts increases the probability that the decision-making process will consider more accurate cause-and-effect relationships of the phenomena being studied;
  • Groups tend to develop a greater number of potential options and are more creative;
• Commitment to the decision:
  • Individuals who contribute to the decision are likely to feel a sense of ownership over it;
  • Resistance to change and motivation to implement the decision in practice can increase with participation.

The survey questionnaire served as a method for collecting data from experts with significant experience in construction projects. Utility theory was employed to analyze the survey responses. This theory helps in understanding how individuals make decisions under conditions of uncertainty, such as assessing the perceived benefits and risks associated with different measures. Below is a description of all the methods used to collect data and analyze the results.

3.1. Interviews

The interviews were conducted with nine experts, all of whom had more than 17 years of work experience in construction projects and currently held senior management positions in their companies. The sample of respondents was purposefully selected because, due to the depth of data sought, it was necessary to interview experts with extensive experience in construction who had been involved in executing large and complex projects and were currently in senior management positions in their companies. Small samples are characteristic of qualitative research, which aims to obtain deeper data, focusing on a narrowly defined topic with a homogeneous structure of experts possessing a high level of expertise [23]. After conducting nine interviews, it was concluded that the answers to the questions began to repeat, indicating that further interviews were unnecessary, as data saturation had been reached.

Six of the respondents held the position of director in their company, while the other three closely collaborated with their company’s management. Most respondents had more than one role, as they performed a functional role within their company while also leading construction projects, participating as consultants, and supervising engineers or designers. All respondents had extensive work experience in construction projects, averaging 26 years. Three respondents came from organizations that act as public clients in construction projects. The remaining six were from private companies specializing in consulting services, project supervision, design, or project management. All respondents had worked on construction projects in Croatia. Four had international experience, while the others had worked exclusively in Croatia, often collaborating with foreign companies. The international experience of the respondents included working in Austria, Bosnia and Herzegovina, Montenegro, Qatar, Kosovo, Hungary, North Macedonia, Slovenia, Serbia, Tatarstan, and the United Arab Emirates. The types of projects in which the respondents had the most experience were public infrastructure and building construction projects, with less involvement in private investments. This distribution of project types is not surprising, given that the respondents were selected for their experience in large and complex projects, which in Croatia are predominantly related to public infrastructure investments. Each respondent participated in one interview, lasting from 52 min to 2 h. Special attention was given to creating a trusting atmosphere, to make the respondents feel as relaxed and open as possible in answering questions. The interviews were conducted at the respondents’ company premises, at the Faculty of Civil Engineering in Zagreb, and online via Skype and Microsoft Teams video conferences. During the interviews, the interviewer maintained a relaxed and friendly but objective, professional, and relatively detached approach to minimize influencing the respondents’ answers. The order of questions was changed, and follow-up questions were asked only when it was deemed that this would benefit the respondent’s train of thought. All respondents agreed to have the interviews recorded, after which the interviews were transcribed into MS Word. The transcripts provided a very rich source of data for interview analysis.

Based on their experiences, the experts evaluated the list of measures defined in the literature review. Furthermore, they supplemented the list of measures from the literature with new measures based on their extensive experience in construction projects. This resulted in a final list of measures for mitigating risks, which were quantified in the next step of the research using a survey questionnaire.

3.2. Questionnaire Survey

The questionnaire was intended for experts with significant experience in construction projects. It consisted of two parts. The first part included questions about the respondents’ experience in construction projects. In the second part, respondents were asked to evaluate the effectiveness of various risk mitigation measures.

The criteria for selecting respondents were the following:

• Significant work experience (more than five years) in construction projects, especially large-scale ones;
• Experience in executing construction projects, and familiarity with the roles of contractors and/or clients both before and after signing construction contracts.

Respondents who participated in the interviews were contacted again to complete the questionnaire. The snowball sampling method was then used for sampling. Snowball sampling is a non-probabilistic sampling method where existing respondents refer other potential respondents who might be included in completing the questionnaire [82]. This method allows the sample to grow like a snowball. It is suitable in cases where research is conducted among a group of highly specialized individuals with specific expertise, and random sampling is not feasible [83].

Respondents were initially asked to determine whether they participate in projects mainly as clients or contractors and whether they primarily have experience with private or public projects. Based on those answers, they completed the rest of the questionnaire.

Furthermore, respondents were asked to assess the usefulness of individual measures for mitigating risks associated with information asymmetry. The tables were structured so that the left column presented the measures, and the top row listed the three main groups of risks caused by information asymmetry. Respondents marked each table field with a value on a scale from 1 to 5. If they considered the usefulness of the measure in the left column to mitigate the risk from the group listed in the top row as ‘negligible’, they assigned it a value of 1. Conversely, if they considered the usefulness of the measure in the left column to mitigate the risk from the group listed in the top row as ‘crucial’, they assigned it a value of 5.

The aim of this part of the research was to rank the measures for mitigating risks based on group decision-making in four presented groups. An ordinal scale was used in this research because ordinal assessments have proven to be the most natural approach for decision-makers, while also not presenting difficulties for processing [84].

According to Berekméri and Zafeiris [85], the optimal number of experts involved in a decision-making process is between 5 and 30. Given that the results in this study were analyzed in four different groups (depending on the respondents’ experience with a specific type of project financing and their role), our objective was to collect between 5 and 30 responses in each group. However, we considered that it was also appropriate to analyze a smaller number of responses, as has been the case in other construction research (e.g., [86,87]).

The questionnaire was created in MS Word and in an online version (Google Forms). It was distributed to a total of 85 email addresses collected using the snowball sampling method. Reminders to complete the questionnaire were sent twice, and the researcher regularly communicated with respondents who needed explanations of certain terms within the questionnaire. Finally, 52 responses were collected: 25 clients in public projects, 19 contractors in public projects, 4 clients in private projects, and 4 contractors in private projects.

The respondents included those with significant work experience in construction: 7 respondents had 5–10 years of experience, 20 had 11–20 years of experience, 20 had 21–30 years of experience, and 5 respondents had more than 30 years of experience. Most respondents worked as project managers, followed by company directors. In the survey, respondents also reported on their roles in projects, which generally aligned with their current job positions, with most having performed multiple roles before their current employment. Most respondents worked in privately owned companies (40 of them), while a smaller portion worked in public companies (12 of them). Additionally, most respondents were from Croatia (48), while a smaller number were from Bosnia and Herzegovina (4). However, the respondents also had significant work experience in other countries. Some of them had worked on construction projects in Austria, Azerbaijan, Bosnia and Herzegovina, Bulgaria, Montenegro, the Czech Republic, Iran, Italy, Qatar, Kosovo, Kuwait, Hungary, North Macedonia, Oman, Poland, Russia, Saudi Arabia, the United States, Slovakia, Slovenia, Serbia, the United Arab Emirates, and the United Kingdom. For as many as 19 respondents, the value of all projects they had worked on exceeded 500 million EUR.

3.3. Utility Theory

The responses were analyzed using the MS Excel software (Version 2406). Since individuals have different attitudes, motivations, and personalities, they attribute different meanings and importance to each element of the scale (1–5) [88]. The nature of the data collected this way shows a variability in the distance between individual scale elements, which depends on each decision-maker’s preferences. Therefore, a method that considers the decision-makers’ preferences and associated uncertainties, such as utility theory, was needed to process these data. This method was chosen as appropriate for this research because the utility function quantifies the entire range of uncertainty associated with the preferences of decision-makers by assigning a numerical value to different levels of criterion satisfaction [89]; utility theory thus enables the use of various types of input data, with the utility function normalizing and consolidating all of them.

Respondents rated each measure concerning each type of risk caused by information asymmetry on a scale from 1 to 5. However, the respondents had different attitudes, motivations, and personalities, so they attributed different meanings and importance to each element of the scale (1–5) [88]. Therefore, some respondents broadly distributed their answers (e.g., using all ratings from 1 to 5), while others rated the importance of alternatives almost equally (e.g., giving only ratings of 3 and 4 for individual (sub)criteria). To equally account for their preferences and answer distribution method, individual utility functions were constructed for each respondent. Alternatives with greater weight or utility were highlighted as better choices than those with lesser weight or utility.

3.3.1. Individual Utility Functions

Utility theory allows the selection of a utility function to best represent the decision-makers’ preferences. A monotonic linear utility function was applied, having been used in other construction research [10,90]; thus, it was chosen here as well.

For each respondent and each type of risk, an individual utility function was determined as follows:

• The range of measure values assigned by the respondent to each type of risk was determined.
• The lowest value was assigned a utility function value of “0”.
• The highest value was assigned a utility function value of “1”.
• Other utility function values were determined by interpolation between the minimum and maximum values.

An example of a utility function, v_AS(x_AS), is given for the values x_AS assigned by the respondent to measures concerning the risk group AS, as shown in

Table 2. Example of utility function value calculation (normalization).

xAS	vAS(xAS)
2	0
3	0.333
4	0.666
5	1

x_AS—value assigned to measure x concerning the type of risk AS. v_AS(x_AS)—utility function value (weight) of measure x concerning the type of risk AS.

.

3.3.2. Aggregated Utility Function

The responses collected from the survey were part of a group decision-making process where decision-makers/experts evaluated alternative solutions to achieve a common goal, taking into account their different opinions, preferences, or judgments [91]. In this research, respondents were divided into four groups based on their role in construction projects (client or contractor) and their experience with a certain type of project (public or private).

In group decision-making, the results of individual decision-making need to be further aggregated into a common decision, which represents the main problem of group decision-making [92]. In the literature, there are various ways to aggregate individual expert responses, differing in complexity, use of auxiliary mathematical methods, consideration of risks, or the appropriate structure of the decision-making problem [93]. When it is possible to gather a group of decision-makers and intervene in the decision-making process during the discussion, the aim is to achieve a consensus at the end of the discussion [94]. However, in cases where the group structure is such that there are differences in the knowledge, experience, or managerial level of decision-makers, it is more appropriate to use a relative weighting of their judgments [93]. Collecting expert responses via a survey, as performed in this research, is suitable for the use of weights, and respondents were assigned the following weights:

According to experience (p_e):

• 5–10 years: 0.9;
• 11–20 years: 1.0;
• 21–30 years: 1.1;
• More than 30 years: 1.2;

According to managerial level (p_m):

• Site manager: 0.8;
• Construction manager: 0.9;
• Supervising engineer: 1.0;
• Project manager/Consultant: 1.1;
• CEO: 1.2.

In addition to determining weights, when the group structure is such that it is more appropriate to collect individual expert responses, two different methods are used to aggregate individual expert responses [93]:

• Aggregation of individual judgments—AIJ;
• Aggregation of individual priorities—AIP.

With the AIJ, the judgments of all experts for a criterion or alternative are averaged in the first step using the geometric or arithmetic mean [95]. The AIJ is mostly used when the group structure is homogeneous and decision-makers agree to act as one [93].

When the group structure is such that experts possess different knowledge and experience and want to participate in decision-making only with their own views, the AIP is commonly used. With this method, the ranking and importance of alternatives are calculated for each individual expert, and only at the end are their individual priorities averaged [96,97].

According to the Yap et al. [98], the AIP better reflects the real priority ranking in group decision-making. Additionally, the AIP allows for the presentation of individual results of each expert, and for these two reasons, it was chosen for this research. Thus, expert responses were analyzed individually, and the final aggregation into a common decision was made in the last step.

Therefore, the value of the overall utility function U(x) for mitigation measure x was calculated based on the following expression (adapted from [81]) for each of the four groups of respondents:

$$U\left(x\right)={{\displaystyle \sum }}_{j=1}^m{p}_{ej}{p}_{mj}{v}_j\left(x\right),$$

(1)

where

• v_j(x)—utility of mitigation measure x for the j-th respondent;
• p_ej—weight for the experience of the j-th respondent;
• p_mj—weight for the managerial level of the j-th respondent;
• m—number of respondents in the group.

Mitigation measures were finally ranked according to the size of their overall utility function value. In this way, the utility of measures for mitigating risks caused by information asymmetry in construction projects was determined.

3.3.3. Sensitivity Analysis

After obtaining the final ranking of mitigation measures for risks caused by information asymmetry, a sensitivity analysis was employed to evaluate the stability of the results. Performing a sensitivity analysis involves examining how changes in input variables affect the rankings and overall results. For this research, the most appropriate method to obtain insights into the stability of the results was to use a different weighting technique. According to Jansen [99], the equal weight function can be applied. This method ignores information regarding the relative weight of each survey respondent, which simplifies the decision-making process. Thus, the approach makes the assumption that each participant is equally weighted: (1) assuming all the weights for experience are 1.0, and (2) assuming all the weights for the managerial level are 1.0 (see Equation (1)). The results obtained using this approach are then compared with the original results.

4. Results

Based on their experiences, the interviewed experts evaluated the list of measures defined in the literature review. They commented on the usefulness of individual measures for mitigating risks caused by information asymmetry. Notably, for 12 out of the 13 measures defined in the literature, the respondents identified usefulness in reducing information asymmetry risks; thus, these measures were successfully verified. They did not agree on the usefulness of measure M12, as it involves reducing outsourcing, which, given the current conditions of increased demand for construction work and a weak supply of labor and construction companies, would be limiting for construction projects. Specifically, seven out of nine experts interviewed believe that the M12 is not applicable under current labor market conditions. They explained that subcontracting in construction projects more often results in adding value rather than having negative implications for the projects. Since seven out of nine experts could not verify this measure, it was excluded from the next step of the research, namely, the questionnaire survey.

Furthermore, the experts supplemented the list of measures from the literature with new measures based on their extensive experience in construction projects. This resulted in a final list of measures for mitigating risks, shown in

Table 3. Final list of possible mitigation measures for information asymmetry in construction projects.

ID	Mitigation Measures	Interview Results
M1	Incentives for the agent (bonuses)	verified
M2	Signaling (advertising, reputation)	verified
M3	Building trust and cooperation	verified
M4	Information systems	verified
M5	Regular and thorough quality control	verified
M6	Contractually defined benchmarks for monitoring the agent’s work	verified
M7	Fair distribution of risk between the principal and the agent	verified
M8	Contractual penalties	verified
M9	Screening of bids	verified
M10	Screening of bidders (certificates, guarantees, financial stability)	verified
M11	Intrinsic awards for the agent, which include reputation enhancement, discretion, autonomy, responsibility, satisfaction in the job, stability, and mission alignment	verified
M12 *	Vertical integration and strengthening the internal capabilities of principals (reducing outsourcing)	not verified
M13	Selection of a bidder that has a similar organizational culture (values, goals)	verified
M14	Replacement of the employees	added
M15	Third-party dispute resolution	added
M16	Communication protocols	added

* M12 is excluded from the following analysis because it was not verified by the interviewed professionals.

, which were quantified in the next step of the research using a survey questionnaire.

Furthermore, this study aimed to determine the utility of individual measures for reducing the risk of information asymmetry. Mitigation measures identified through the literature review and semi-structured interviews with experts were ranked according to risk types: adverse selection (AS), moral hazard (MH), and hold-up (HU), using the data acquired through the questionnaire survey and analyzed using utility theory.

Table 4. Ranking by priorities, according to the utility of mitigation measures for the adverse selection (AS); PubCl—public clients, PubCon—contractors in public projects; PrCl—private clients, PrCon—contractor in private projects.

ID	Mitigation Measure	Ranking (PubCl)	Ranking  (PubCon)	Ranking  (PrCl)	Ranking (PrCon)
M1	Incentives for the agent (bonuses)	12	11	11	9
M2	Signaling (advertising, reputation)	9	13	6	13
M3	Building trust and cooperation	1	5	1	2
M4	Information systems	10	7	12	7
M5	Regular and thorough quality control	2	6	4	6
M6	Contractually defined benchmarks for monitoring the agent’s work	5	4	8	3
M7	Fair distribution of risk between the principal and the agent	4	1	5	5
M8	Contractual penalties	8	12	8	11
M9	Screening of bids	3	3	7	1
M10	Screening of bidders (certificates, guarantees, financial stability)	6	2	3	4
M11	Intrinsic awards for the agent, which include reputation enhancement, discretion, autonomy, responsibility, satisfaction in the job, stability, and mission alignment	15	14	15	12
M13	Selection of a bidder that has a similar organizational culture (values, goals)	11	10	1	7
M14	Replacement of the employees	13	15	10	13
M15	Third-party dispute resolution	14	9	13	13
M16	Communication protocols	7	8	13	10

shows the final results, with a priority ranking for the utility of measures in mitigating the risks from the adverse selection (AS) group.

The results of this research, shown in Table 4, indicate that the risks of adverse selection (AS) that arise before the contract is signed between the client and the contractor can be most effectively mitigated through building trust and fostering cooperation. This measure ranked first according to the opinions of both private and public project clients. Private clients also highlighted the importance of selecting contractors with a similar organizational culture. This measure is useful for private projects where clients can freely choose the contractors they wish to work with. In public projects, this is often not feasible due to different selection criteria, which are usually tied to the criterion of the most economically advantageous bid. Contractors in public projects believe that the most useful measure for them is the fair distribution of risks between the client and the contractor. Thus, a well-defined contract is considered the best protection against the consequences of AS risks. On the other hand, contractors in private projects believe that the most useful way to reduce AS risks is for clients to more thoroughly verify the submitted bids, to avoid an adverse selection of contractor from the start.

The least useful measures for mitigating AS risks are intrinsic rewards for agents, which clients ranked last. Similarly, measures related to employee replacement and third-party dispute resolution also ranked low.

The differences in opinions between clients and contractors are most evident in that clients consider signaling contractor characteristics to be more important than contractors do. This is also seen in the measure related to defining contractual penalties. On the other hand, contractors give more importance to the use of information systems than the clients. The differences between private and public projects are evident in that the selection of a business partner with a similar organizational culture ranks much higher in private projects, while communication protocols are considered more important in public projects.

Figure 1 is a visual representation of normalized utility values for individual measures for mitigating AS risks, obtained through weighted averaging within the four groups of respondents.

Table 5. Ranking by priorities, according to the utility of mitigation measures for the moral hazard (MH); PubCl—public clients, PubCon—contractors in public projects; PrCl—private clients, PrCon—contractor in private projects.

ID	Mitigation Measure	Ranking (PubCl)	Ranking  (PubCon)	Ranking  (PrCl)	Ranking (PrCon)
M1	Incentives for the agent (bonuses)	15	12	7	8
M2	Signaling (advertising, reputation)	11	15	9	13
M3	Building trust and cooperation	2	4	3	3
M4	Information systems	6	6	11	6
M5	Regular and thorough quality control	1	3	1	1
M6	Contractually defined benchmarks for monitoring the agent’s work	4	5	2	1
M7	Fair distribution of risk between the principal and the agent	3	1	9	5
M8	Contractual penalties	9	13	4	11
M9	Screening of bids	7	9	13	4
M10	Screening of bidders (certificates, guarantees, financial stability)	8	2	13	9
M11	Intrinsic awards for the agent, which include reputation enhancement, discretion, autonomy, responsibility, satisfaction in the job, stability, and mission alignment	14	14	15	12
M13	Selection of a bidder that has a similar organizational culture (values, goals)	12	8	8	6
M14	Replacement of the employees	10	11	5	13
M15	Third-party dispute resolution	13	7	11	13
M16	Communication protocols	5	10	6	10

shows the final results, with priority ranking for the utility of measures in mitigating risks from the moral hazard (MH) group.

The research results presented in Table 5 show that the risks of a moral hazard (MH) that materialize after the client and contractor sign a contract can be most effectively mitigated through regular and thorough quality control. Contractors in private projects also highlighted the importance of contractually defined benchmarks for monitoring the agent’s work. Therefore, to reduce MH risks, most participants consider the best measures to be those related to controlling the agent’s work. Contractors in public projects, similar to AS risks, believe that the most useful measure for them is the fair distribution of risks between the client and the contractor. Furthermore, similar to AS risks, participants agree on the usefulness of building trust and cooperation, which ranks just after control when discussing MH risk mitigation.

The least useful measures for mitigating MH risks are incentives for agents, both monetary and intrinsic. Similarly, measures related to signaling contractor characteristics, employee replacement, and third-party dispute resolution also ranked low.

Differences in opinions between clients and contractors are most evident in that clients consider communication protocols more important than contractors do. This is similarly seen with the measure related to defining contractual penalties. Contractors, on the other hand, consider the verification of bidders more important than clients do. Differences between private and public projects are visible in that incentives for contractors rank much higher in private projects, while a fair distribution of risk is considered more important in public projects.

Figure 2 is a visual representation of normalized utility values for individual measures for mitigating MH risks, obtained through weighted averaging within the four groups of respondents.

Table 6. Ranking by priorities, according to the utility of mitigation measures for the hold-up (HU); PubCl—public clients, PubCon—contractors in public projects; PrCl—private clients, PrCon—contractor in private projects.

ID	Mitigation Measure	Ranking (PubCl)	Ranking  (PubCon)	Ranking  (PrCl)	Ranking (PrCon)
M1	Incentives for the agent (bonuses)	15	12	7	8
M2	Signaling (advertising, reputation)	11	15	10	13
M3	Building trust and cooperation	1	4	1	4
M4	Information systems	8	6	12	5
M5	Regular and thorough quality control	3	3	2	7
M6	Contractually defined benchmarks for monitoring the agent’s work	4	5	3	1
M7	Fair distribution of risk between the principal and the agent	2	1	7	3
M8	Contractual penalties	6	13	3	11
M9	Screening of bids	7	9	14	1
M10	Screening of bidders (certificates, guarantees, financial stability)	9	2	15	9
M11	Intrinsic awards for the agent, which include reputation enhancement, discretion, autonomy, responsibility, satisfaction in the job, stability, and mission alignment	13	14	13	11
M13	Selection of a bidder that has a similar organizational culture (values, goals)	10	8	9	5
M14	Replacement of the employees	14	11	5	13
M15	Third-party dispute resolution	12	7	11	13
M16	Communication protocols	5	10	6	10

shows the final results, with the priority ranking for the utility of measures in mitigating risks from the hold-up (HU) group.

The research results presented in Table 6 show that the risks of HU that materialize after the client and contractor sign a contract can be most effectively mitigated by trust and fair distribution of risks. For clients, building trust ranked highest in terms of usefulness, while contractors in public projects place more importance on the fair distribution of risks, and contractors in private projects prioritize control.

The least useful measures for mitigating HU risks are rewards for agents, both monetary and intrinsic, signaling contractor characteristics, and screening of bidders. Other measures that were rated low include the replacement of employees and third-party dispute resolution.

Differences in opinions between clients and contractors are most evident in that clients consider trust a somewhat more important measure than contractors do. This is similarly seen with measures related to defining contractual penalties and using communication protocols in projects. Differences between private and public projects are visible in that monetary rewards for contractors rank higher in private projects.

Figure 3 is a visual representation of normalized utility values for individual measures for mitigating MH risks, obtained through weighted averaging within the four groups of respondents.

To examine how changes in input variables affect the rankings and overall results, a sensitivity analysis is employed. For this research, the most appropriate method for obtaining insights into the stability of the results was to use a different weighting technique. The ranking of the mitigation measures was again calculated in two scenarios: (1) assuming all the weights for experience are 1.0, and (2) assuming all the weights for the managerial level are 1.0 (see Equation (1)).

The results obtained in the first scenario (p_ej = 1.0) show a high percentage of alignment with the original research results. In the group of measures for mitigating adverse selection risks, changes in the ranking of measures occur only between M1 and M13 in the group of public clients, and between M2 and M9 in the group of private clients. In the group of measures for mitigating moral hazard risks, the only change in the ranking of measures occurs between M11 and M15 in the group of public clients. In the group of measures for mitigating hold-up risks, changes in the ranking of measures occur between M11 and M15 in the group of public clients, while only in the group of contractors in public projects is there a significant change in the ranking of measures, as follows: M7, M3, M6, M5, M10, M9, M1, M13, M16, M4, M8, M15, M11, M14, M2.

The results obtained in the second scenario (p_mj = 1.0) also show a high percentage of alignment with the original research results. In the group of measures for mitigating adverse selection risks, changes in the ranking of measures occur only between M6 and M7 in the group of public clients, between M1 and M8 in the group of contractors in public projects, and between M2 and M9 in the group of private clients. In the group of measures for mitigating moral hazard risks, the only change in the ranking of measures occurs between M14 and M16, and it is between M1 and M8 in the group of contractors in public projects. In the group of measures for mitigating hold-up risks, only in the group of contractors in public projects is there a significant change in the ranking of measures, as follows: M7, M6, M3, M5, M10, M9, M1, M13, M16, M8, M4, M15, M11, M14, M2.

Based on the conducted sensitivity analysis, it was concluded that the results of this research were robust and reliable. The only significant sensitivity in the change in priorities for mitigation measures occurred in the group of contractors in public projects when discussing measures for mitigating hold-up risks. This indicates that the ranking of measures in this group is sensitive to changes in the experience and managerial level of decision-makers.

5. Discussion

This study provides valuable insights for researchers and managers by highlighting effective measures to mitigate risks associated with information asymmetry in construction projects. Theoretical advancements are made through the integration of principal–agent theory and information asymmetry in construction risk management. The application of these theoretical frameworks in construction projects through an extensive literature review enabled the identification of mitigation measures for risks caused by information asymmetry, which were then verified through interviews and ranked through the survey questionnaire. Practically, we suggest implementing the identified mitigation measures to better manage risks and improve project outcomes. Additionally, our findings emphasize the importance of trust and collaboration between project participants to address information asymmetry in construction projects.

The findings of this study on the utility of measures for mitigating information asymmetry risks are described in the remainder of this section. Measures that were highlighted as the most significant for reducing these risks through the survey are emphasized in order. The research results are commented on in line with the theoretical framework.

5.1. The Impact of Trust in Mitigating Information Asymmetry Risks

The results of this research show that for reducing risks caused by information asymmetry before the contract signing, both public and private clients consider trust to be the most useful measure. For contractors, trust is also one of the most useful measures, ranking second for contractors in private projects and fifth for contractors in public projects. After the contract signing, to reduce the MH risks, trust ranked second, third, or fourth in all respondent groups. To mitigate the HU risks, trust was also ranked first for both public and private clients and fourth for contractors. These results are consistent with other studies, where trust was identified as one of the main measures for reducing information asymmetry in construction projects, especially during the execution phase [10]. To rank the strategies for mitigating information asymmetry, Cerić [10] used the Delphi method. She conducted a study among 27 highly experienced project managers and found that trust is the most significant measure for mitigating information asymmetry, according to the project managers. The results of her study align with the survey results presented in this paper. Additionally, Cerić ranked six strategies as follows: (1) trust; (2) bureaucratic control; (3) information technology; (4) reputation; (5) organizational culture; (6) incentives. This study ranked a larger number of potential measures for mitigating risks caused by information asymmetry and also provided a priority ranking of measures for three groups of risks: adverse selection, moral hazard, and hold-up. Furthermore, differences in the opinions of clients/contractors working on public/private projects were identified. Consequently, this study extends the results obtained by Cerić using the Delphi method [10].

Before the contract signing, the lack of information about the future business partner and the tender documentation can only be compensated for with detailed checks from the contract participants. Such checks are costly and time-consuming for both clients and especially for contractors. Contractors need to invest financial resources into checks without knowing if they will even secure the job. Therefore, it is clear that long-term contractual relationships and cooperation between clients and contractors from the beginning of the project, as well as sharing information, honest and informal communication, joint problem-solving, and building trust, mitigate risks before contract signing [19,45,62]. For example, a significant risk before signing a contract between the client and the contractor involves the lack of knowledge about the tender documentation details, including the project documentation. Contractors, if they maintain good relationships with other construction participants, can informally reach out to designers to obtain information that would otherwise require them to allocate considerable resources. Thus, trust-based services in construction can reduce information asymmetry risks even before the contract is signed between the client and the contractor. For contractors, a good trustful relationship with the client can help to improve their cash flow. For example, in construction projects, there are so-called hidden reserves. These are “supports” for contractors within the implementation of the contracts, where the price for the client does not increase, but internal reserves are released to improve the contractor’s cash flows. If the contractor is competent enough in delivering quality to the satisfaction of the supervision and the client, they will access these withheld funds sooner. If participants know and can trust each other, agency costs will be lower from the very start of the project [100].

Private clients also attributed equal importance to the similar organizational structure of the client and contractor companies. This measure is closely linked to trust, as trust is easier to build if two companies have similar organizational cultures [42]. In private projects, clients can choose contractors without any restrictions. Therefore, they most often choose them based on trust and the similarity of organizational cultures between the two companies. Such preconditions ensure lower agency costs throughout the project and reduce risks associated with information asymmetry both before and after contract signing.

On the other hand, public clients do not have the option to select contractors based on these criteria. Public procurement requires the selection of the economically most favorable offer, meaning that clients in public projects may be paired with business partners (contractors) who are unknown and perhaps not trustworthy. However, it is significant that trust was also ranked first among public clients. In the literature [45], trust is recognized as one of the non-financial rewards for agents. It is assumed that agents will behave less opportunistically if they have good and trustworthy relationships with the principal. They will each put in more effort and be more honest in the relationship. Therefore, trust is one of the main measures for reducing hold-up risks in the project as well as moral hazards. Everything is connected to the possibility of future work with the same principal and maintaining good relationships in the future [19]. Thus, public (as well as private) clients can use trust-building from the very beginning of the project as a pledge for better cooperation after contract signing.

According to Cerić [10], participants usually enter a project with optimism and a certain level of trust in the other contractual party. The level of trust changes during the project, and it is important to maintain a certain level of trust for the project to be successful.

5.2. Other Mitigation Measures for Information Asymmetry in Construction Projects

5.2.1. Control (Supervision and Monitoring)

Reducing the risk of MH after the contract signing is considered most effective through quality control by both public and private clients, as well as contractors in private projects. For contractors in public projects, quality control is also one of the most useful measures, ranking third. Furthermore, reporting and monitoring project progress is equally as important as quality control for contractors in private projects. For AS and HU risks, supervision and monitoring are also among the most significant risk mitigation measures.

Supervision and monitoring of the agent’s work are key measures taken against information asymmetry according to principal–agent theory [42]. The assumption is that regular control of the agent’s actions can prevent the consequences of opportunistic behavior. However, risks caused by information asymmetry arise because the client has limited resources for implementing control and cannot always know what the agent is doing.

In addition to construction quality, further criteria such as deadlines, costs, and other factors are crucial for the project’s success. Therefore, it is necessary to monitor parameters beyond just quality. These parameters are not defined by law or standards, so guidelines for conducting such control should be outlined in the contracts. For this purpose, time schedules, cost plans, and other plans should be created, depending on the parameters that need to be monitored [29].

5.2.2. Screening (of Bids and Bidders)

Screening of bids and bidders is a significant measure for reducing information asymmetry risks. Contractors in private and public projects place greater importance on these measures compared to clients. They find these measures equally useful both before and after the contract signing between the client and the contractor. Before contract signing, clients see greater benefits of these measures for reducing adverse contractor selection risks. On the other hand, clients rated these measures as less important for mitigating risks that arise after contract signing. Private clients ranked them as least useful, while for public clients, they were in the middle of the list of mitigation measures.

Interestingly, contractors view these measures as very useful for mitigating MH and HU risks. This is because large construction projects often involve additional works not initially included in the cost estimate. In these cases, renegotiations between the client and the contractor occur regarding the price of additional works. Clients often believe that contractors take advantage of these situations and offer prices higher than are realistic. This can create an atmosphere of mistrust between the client and the contractor, potentially leading to MH and HU risks. In private projects, clients can request adjustments to bids or reissue tenders if they notice bids are unrealistic, too low, or too high compared to market prices.

5.2.3. Fair Distribution of Risks

A fair distribution of risk is ranked first among the useful measures for contractors in public projects, both before and after contract signing. This measure is also significant in other respondent groups, with slightly greater importance in public projects compared to private ones.

A fair distribution of risk entails that the risk should be borne by the party best able to manage it, which is better for the project. However, in practice, risks are not always distributed fairly. In public projects, it is important that the risk belongs to the party that can manage it best because then there are no additional costs that contractors factor into their bids.

5.2.4. Organizational Culture

Organizational culture is a key area of study within organizational theory, exploring how organizations function, their impact on their environment, and how external factors influence them [101]. A comprehensive definition provided by Hofstede [102] (p. 11) states that culture is “the collective programming of the mind that distinguishes the members of one group or category of people from another”.

When discussing organizational culture, groups represent organizations. Components of organizational culture include shared assumptions, values, attitudes, norms, and symbols among individuals within an organization. According to Schieg [42], companies can collaborate more effectively if they share or have similar values, attitudes, and norms—that is, if they share an organizational culture. Therefore, selecting a contractor with a similar organizational culture is one of the possible measures to mitigate information asymmetry risks for clients.

According to results of this research, choosing a contractor with a similar organizational culture is a significant measure among private clients, ranking first alongside trust. Private clients consider this the most useful measure against AS risk. Contractors in private projects also view this measure as beneficial after contract signing, as it can reduce risks related to HU (ranked fifth in this group) and MH (ranked sixth in this group). However, the application of this measure is limited in the sense that there must be prior collaboration between the parties before signing the contract.

5.2.5. Contractual Penalties

Penalties for contractors in construction projects fall under contractual categories. Private clients consider penalties a useful measure against information asymmetry risks both before and after contract signing. Among private clients, penalties rank third and fourth across all risk categories. However, other project participants do not share the same view. Contractors rank this measure 11th (private) and 13th (public) in terms of usefulness.

Based on normalized utility values of this measure, it can be concluded that penalties are somewhat more effective in private projects compared to public ones. This could be attributed to contractors in public projects being highly sensitive to market changes and the cautious nature of public clients. The slower effectiveness of penalties in public projects can also be attributed to the long duration of projects. Penalties coming due at the end of a multi-year project may not be effective. Therefore, when defining contracts, attention should be paid to project implementation by specifying various forms of penalties, such as penalties for delays or missed interim milestones.

5.2.6. Communication Protocols

Another significant measure for mitigating all types of information asymmetry risks, according to clients, is the implementation of communication protocols. From the perspective of contractors, however, communication protocols are somewhat less significant (ranking 10th in both public and private projects). The goal of developing communication protocols in construction projects is to plan clear communication lines among participants and systematically store communications such as letters, information, requests, orders, project documentation, and more. In these ways, clearly defining communication needs and monitoring communication ensures a reduction in information asymmetry through a formal exchange of information between clients and contractors. Based on the difference between client and contractor opinions, it can be concluded that clients place more emphasis on formal communication than contractors.

5.2.7. Replacement of the Employees

According to private clients, replacing company representatives on the construction site is another significant measure against all forms of information asymmetry risks (ranked fifth). In other respondent groups, this measure is not considered important. Specifically, private clients are more inclined to resort to personnel replacement on individual projects compared to public clients, likely due to simpler administrative procedures.

5.2.8. Information Systems

Contractors in private projects consider the use of information systems one of the more significant measures for reducing HU risks. For mitigating MH risks, it ranked sixth among public project clients and contractors in both public and private projects. Private project clients, however, consider it the least useful. Various information systems and technologies enable faster, more open, and efficient communication among project participants.

Information systems are valuable for consolidating various documents exchanged during a project. They can enable standardized data formats and ensure information availability to all participants at any time. Therefore, they significantly reduce the possibility of information asymmetry in projects [42]. Prerequisites for using information technologies include educating all project participants and their willingness to use the designated technologies.

5.2.9. Signaling

One of the less useful measures for mitigating information asymmetry risks is signaling contractors’ characteristics before signing a contract to the client. Among private clients, this measure ranks sixth in terms of usefulness, while it is less accessible in other groups. Contractors bidding for private projects have the opportunity to provide additional information to clients about themselves, their staff, qualifications, finances, and more, if they believe it could present them in a better light. Private clients can then decide to select that contractor based on these additional insights.

On the other hand, in public projects, the public procurement process is strictly formalized, and anything contractors submit outside the requested documents cannot be considered.

5.2.10. Third-Party Mediation

Another mitigation measure recognized as less useful is mediation among participants. Interpersonal problems can negatively impact relationships among companies involved in construction projects. However, mediation is still poorly recognized in construction projects. More often, other measures such as replacing those employees with new ones are resorted to.

5.2.11. Incentives (Monetary and Intrinsic)

The greatest disparity in this study’s results and principal–agent theory is in the importance of the last two measures: incentives and intrinsic rewards for contractors. These measures ranked lowest in usefulness in public projects, whereas in private projects, incentives are somewhat more recognized, placing them in the middle of the scale of effective measures for mitigating MH and HU risks post signing of the contract between clients and contractors. Contrary to these research findings, incentives are commonly cited in principal–agent theory papers as a measure to mitigate information asymmetry between principals and agents. Many studies [19,26,45,76] have focused extensively on the incentives in construction projects. However, the results of this study place financial and especially non-financial rewards for contractors in a questionable position regarding reducing information asymmetry risks and their impact on project success.

In practice, incentives for contractors are indeed utilized and specified in contracts. This is more frequent in private projects, where contractors are rewarded for early project completion. In public projects, provisions exist to incentivize contractors to propose improvements or better solutions and then share the financial gains with the client.

Bonuses in public projects can be particularly sensitive because there is a perception that contractors might manipulate or submit unrealistically low bids to win the contract, hoping to later earn bonuses or other incentivized rewards defined in the contract. This can lead to doubts about the fairness of the tendering process and result in undesired consequences such as reduced trust between the client and the contractor, and even legal disputes.

Therefore, the implementation of bonuses in public projects requires careful regulation, clearly defined terms and criteria, and a transparent allocation process to minimize potential impacts on the integrity of the tendering process and relationships among project participants.

Intrinsic rewards, on the other hand, are recognized as the least useful in all groups of respondents and for all forms of information asymmetry risks. Such incentives are more specific to the relationship between employees and the company as agent and principal, rather than between contractor and client companies.

6. Conclusions

The results of this study can be used for the process of managing information asymmetry risks in construction projects. The ranking of mitigation measures by their usefulness for mitigating each of the three groups of observed risks can be used by experts in risk registers to define responses to risks that prove significant in their projects.

Furthermore, this study provides a foundation for future research on the topic of information asymmetry in construction. The possibility of mitigating these risks and their effect on project objectives will be increased. The mitigation measures proposed in this research need to be tested on actual projects to investigate their effectiveness in achieving project objectives. This can be achieved through longitudinal research that could monitor the relationships among project participants and the application of measures from the beginning to the end of the project. This research did not specify a list of measures for each risk; instead, the measures were grouped by risk categories. Therefore, future research would benefit from identifying more detailed connections between the application of measures to specific risks. The effectiveness of the measures could be determined based on the achievement of project objectives.

The measure highlighted in this research as the most useful for mitigating information asymmetry risks is the trust among project participants. Thus, this research has once again confirmed the importance of trust and cooperation for the success of construction projects. To successfully implement this measure in practice and measure its impact on achieving objectives, it is necessary to establish effective mechanisms for measuring trust in construction projects. Future research should focus on testing existing models for measuring trust and possibly improving or expanding these models.

On the other hand, this research identified the weak application of the measure related to bonuses, or rewards, for contractors in construction projects. This is one of the measures prominently highlighted in the literature as highly useful for mitigating information asymmetry. Future research may focus on determining the limitations and benefits of applying this measure in construction projects.

The limitation of this research pertains to the sampling of respondents for the survey presented in this paper. Specifically, it was not possible to secure a random sample; instead, respondents were purposefully selected based on a minimum of five years of experience in the construction industry and knowledge of the relationship between clients and contractors during the project execution phase. Most respondents were from Croatia, while a smaller number were from neighboring Bosnia and Herzegovina. However, the international experience of the respondents lends significance to the results of this research in other contexts. Many of the respondents shaped their opinions based on their experience of working on international projects where their companies were involved.

Furthermore, given the diversity of construction projects, our ranking by priority of mitigation measures has certain limitations. Nonetheless, recognizing that the priority list of mitigation measures will not be the same for all projects, four different rankings for mitigation measures were defined for four groups of respondents: clients/contractors in public/private projects.

Finally, it can be concluded that information asymmetry poses a challenge in managing construction projects but also provides an opportunity to develop strategies that will improve efficiency and reduce risks. Through building trust, transparency, well-defined contracts, regular monitoring, and other measures defined in this study, it is possible to mitigate the negative consequences of information asymmetry and ensure the successful execution and sustainability of construction projects.