Before selecting a contractor and commencing construction work, creating documentation that describes the facility to be built is needed. Often, this documentation contains a large number of errors and deficiencies of significance. This study analyses a model comprising four latent variables and explores how three specific constructs – communication and change management (COM), project documentation supervision (PRS), and quality of technical specifications in the tender documentation (QTS) – contribute to construction project success (SPR).
The original data were collected from experienced Czech construction implementation professionals. A survey was conducted using an online questionnaire. Partial least squares structural equation modelling was used for analysis.
Both advanced COM and effective and thorough PRS positively affect SPR in the context of the time-, cost-, and quality-related concepts of the Iron Triangle. The quality of the technical specifications of tender documentation serves as an important mediating variable suggesting an independent review of this documentation before it is used for contractor selection.
In contrast to prior research, this study aims to elucidate the significance of documentation quality in relation to project success during the initial phase. The delivery and subsequent approval of documentation are posited as critical milestones that influence the performance dimensions of the iron triangle, namely, scope, time, and cost. Therefore, we argue that communication and change management should be central, primarily in the pre-investment phase, to ensure ideal error-free documentation.
1. Introduction
The quality of the information contained in tender documentation is an essential prerequisite for the successful completion of construction projects. According to Laryea (2011), a project’s tender documents typically contain the design and related specifications of what the client (investor) wants to build. Such documentation may include structural engineering drawings (e.g. foundation, floor, and roof plans), bills of quantities, standard specifications, material reports, site-specific geotechnical reports, and topographical surveys others, etc. (Akampurira and Windapo, 2018). Good quality documentation is of particular importance, as it serves as a basis for coordinating the work and acts as a management tool for resource allocation (Jarkas, 2014; Sospeter, 2023) and for the bid price calculation to be offered in the tender (Laryea, 2011). Accordingly, such documentation should be as detailed and accurate as possible (Zhou et al., 2021).
Previous studies identified various problems and difficulties related to documentation deficiencies (Andi and Minato, 2003; Juszczyk et al., 2014). Research has highlighted the importance of effective communication (Rehan et al., 2024), change management (Naji et al., 2022; Wang et al., 2024), and strategies for improving documentation quality and project delivery. However, these studies do not fully address this topic, leaving scope for further exploration from a more comprehensive perspective. The literature gap highlights the need to explore the relationship between specific technical knowledge, soft skills, and project success. Therefore, this study aims to fill this gap by examining how effective communication, change management, and supervision attributes facilitate the creation of quality technical specifications for tender documentation, thereby enhancing our understanding of their relationship mechanism with project success. We argue that communication, change management, project control, and quality of tender documentation collectively create a unique and complex coherent environment that contributes to the delivery of a successful construction project.
This study is particularly interested in how implementation construction companies (i.e. suppliers) perceive the above-mentioned complex relationships within a volatile project environment. It is expected that integrating soft skills with technical knowledge is a critical determinant of achieving project success. Therefore, project managers can execute projects smoothly from a technical perspective while also navigating change management dynamics through effective communication.
In Section 2, we develop our argument grounded on the project-based and construction management literature. In Section 3, we use the originally created PLS-SEM model to statistically test the four research hypotheses. Section 4 presents the results. The individual constructs used in the model are discussed in Section 5. Finally, based on this discussion, theoretical and managerial implications, research limitations, and future research directions are addressed in Section 6.
2. Review of literature
2.1 Project success and performance
Available project management literature recognises three basic performance areas known as the “iron triangle,” comprising time, cost, and quality. Accordingly, a successful project assumes that it is delivered on time, within a predefined budget, and of the required quality. However, considering the high complexity of construction projects, shortage of equipment or material, price fluctuations, and high rework rates (Cha and Kim, 2011), many of them fail in one or more aspects of the iron triangle.
To understand the causes of time, cost, and quality deficiencies, the attention of project managers should also be paid to other areas such as productivity, safety, stakeholders, sustainability, or team satisfaction (Cha and Kim, 2011; Galjanić et al., 2023; Moradi et al., 2021). Taking into consideration the variety of performance aspects of highly complex construction projects, no consensus has been reached on what makes a project successful, what constitutes a successful project, and how to plan and deliver it (Radujković et al., 2021).
Although we know that the success of a project can be expressed using the iron triangle, further research is needed to increase our understanding of specific components, such as the interplay of design changes between stakeholder dynamics, documentation defects, and project control activity. By systematically addressing these issues, an industry can enhance its practices, reduce risks, and ultimately achieve higher project success rates.
First, regarding project complexity, which is recognised by the number and heterogeneity of different interrelated elements (Burke and Morley, 2016), our study intends to focus on the issues of communication and change management. The rationale for this lies in the need to manage the complex array of data and activities required to deliver successful construction projects in a multi-stakeholder environment (Atkin and Skitmore, 2008). These stakeholders are recognised as the main source of uncertainty in a project, following the multiplicity of their conflicting objectives (Ward and Chapman, 2008). From this perspective, in Section 2.2, we follow Rehan’s empirical findings on the positive relationship between communication and project success (Rehan et al., 2024) as well as the conclusions drawn by Naji and his team on the effect of change-order management on project implementation (Naji et al., 2022).
Second, our study builds on Gibson’s argument that past research has not explicitly focused on assessing the engineering design components of a project, although they are believed to potentially have various performance impacts (Gibson et al., 2024). Therefore, Section 2.3 addresses the causes of tender documentation errors and the related strategies for improving documentation quality.
Third, the research design was influenced by (Agbaxode et al., 2023), who reported the most significant impacts of poor design documentation quality on project delivery. With the support of Sospeter’s argument that the quality of design documentation is crucial for the successful delivery of construction projects (Sospeter, 2023), we address the relevance and importance of quality documentation for project success in Section 2.4.
2.2 Communication within the construction project
Communication is one of the top competencies contributing to project success (Sampaio et al., 2022) as it facilitates the management of uncertainties, avoidance of mistakes and errors, conflict management, development of stakeholder relationships, and encouragement of teamwork (Rehan et al., 2024). Rehan et al. (2024) and (Ceric, 2014) claimed that the effective exchange of information is of vital importance for all construction projects, and thus should be open and with a quick information flow (Radziszewska-Zielina, 2010).
However, the coordination and dissemination of information in construction projects can pose significant challenges, particularly when dealing with a vast array of fragmented activities represented by thousands of data records. This complexity is exacerbated in multi-stakeholder environments, where factors such as conflicting information, which can be difficult to interpret (Love et al., 2017), information redundancy (Love et al., 2013), stakeholder information sharing (Cerić, 2021), and change management issues (Naji et al., 2022) can complicate effective communication and collaboration.
Therefore, satisfying the eight prerequisites of effective communication, as outlined by (Rehan et al., 2024), can mitigate information asymmetry (when stakeholders do not possess the same information simultaneously (Ceric, 2014). For example, it is crucial to ensure that design changes are promptly disseminated to contractors, who then implement them in a timely manner. Given the high frequency of changes in construction projects, selecting the appropriate communication formats and tools is pivotal for project management.
Recent advanced tools and approaches, such as Building Information Management (BIM) and the Common Data Environment (CDE), can effectively address the communication-related challenges of multilateral project complexity (Rehan et al., 2024). Using BIM and CDE, all data are recorded unequivocally and can be easily accessed by all stakeholders throughout the entire facility life cycle. Thus, the CDE-based BIM can be considered an effective workflow that addresses information specification, verification, and use (Patacas et al., 2020). Unfortunately, despite the advancement of new technologies and scientific literature, construction practices often recognise a large number of collisions in the digital models of buildings and facilities. Therefore, the BIM-related clash detection process (Juszczyk et al., 2025) across the so-called monodiscipline models (e.g. electricity, heating, or plumbing) cannot be neglected, as it often stems from insufficient communication between individual designers.
The current body of knowledge has proven that both effective communication (Rehan et al., 2024) and change management (Naji et al., 2022) contribute significantly to a project’s success throughout its lifecycle. However, previous research has not statistically examined the relationship between these two areas and the creation of quality documentation during the pre-investment phase of a construction project. It can be assumed that effective communication facilitated by CDE and BIM platforms, along with efficient change management and a well-structured timeline for developing individual sections of the documentation, collectively enhances the creation of error-free documentation, ultimately ensuring the successful delivery of the project. Thus, we propose the following two hypotheses concerning communication and change management.
Stakeholder communication and effective change management positively affect the delivery of high-quality technical specifications for tender documentation.
Stakeholder communication and effective change management positively affect project success.
2.3 Causes of tender documentation errors and strategies for improvements
The existing literature identifies a wide range of reasons for creating low-quality tender documentation. The complexity of construction projects necessitates the involvement of multiple specialisations in documentation development. Unfortunately, design consultants often operate independently without the necessary coordination, which frequently results in the proliferation of inaccuracies and various errors in design documents (Agbaxode et al., 2024a; Yap and Skitmore, 2018).
Several studies have prioritised the most problematic issues affecting the quality of design documentation. For instance, (Akampurira and Windapo, 2018) highlighted low design fees, selection of design firms based on the lowest bid price, limited time for checking and coordinating the entire design documentation, discounting professional fees below recommended levels, and poor communication among multidisciplinary teams as the top five factors. Additionally, (Agbaxode et al., 2024a) noted discrepancies between the bills of quantities, drawings, and specifications, as well as the exploitation of ambiguities in documents by individual project participants. Given the diverse causes of tender documentation errors, we provide a comprehensive overview of those provided by (Sospeter, 2023).
Regardless of the type of error in tender documentation, responsible stakeholders should implement strategic measures to ensure the delivery of high-quality tender documentation. The existing literature recommends several approaches, including the utilisation of quality control units and checklists (Abdallah et al., 2019), early involvement of key participants during the pre-design and design stages (Agbaxode et al., 2024b), application of BIM (Dosumu and Aigbavboa, 2018), and holding design consultants responsible for issuing poor design documentation (Agbaxode et al., 2023).
Furthermore, increasing design documentation fee allowances (Agbaxode et al., 2023), allocating sufficient time for documentation, and implementing effective coordination and control can help mitigate the recurrence of design errors. Notably, (Andi and Minato, 2003) highlighted that design fees typically constitute less than 1% of a project’s total lifecycle cost or less than 10% of total construction costs, underscoring the importance of investing in quality documentation to prevent more costly downstream issues. In summary, it is imperative to support continuous improvements in design processes.
As ascertained by (Dilawo and Salimi, 2019), quality processes require rigorous inspection by an owner representative to mitigate the likelihood of errors and the necessity for rework during the construction phase. From this perspective, self-checking using checklists (Abdallah et al., 2019) may have limited potential for enhancing documentation quality compared with independent verification by an experienced expert. Conversely, effective project-time management can provide adequate time for documentation processing, contributing to higher-quality documentation. However, this does not guarantee error-free documentation. Instead, the availability of sufficient time creates a prerequisite for implementing independent control, that is, documentation inspection (audit). The primary objective of an audit is to identify and remove errors, thereby facilitating the delivery of a successful project by mitigating the potential risks associated with substandard documentation. Based on these arguments and the claims of (Zhuman et al., 2024) that quality control is necessary at every stage of a construction project, hypothesis H3 is proposed as follows:
The involvement of an experienced project documentation supervisor positively affects the delivery of high-quality technical specifications for tender documentation.
2.4 Importance of documentation quality for project success
Previous findings on the influence of tender documentation quality on project delivery have addressed the link between documentation quality and project success. (Agbaxode et al., 2023) highlighted that quality documentation plays a significant role in project delivery efficiency, particularly due to its inevitable nature in the construction sector. A consensus exists on the projection of low-quality documentation within all three aspects of the iron triangle; that is, it leads to quality problems and cost and time overruns (Agbaxode et al., 2023; Akampurira and Windapo, 2018; Shoar and Payan, 2022).
More specifically, low-quality tender documentation can lead to issues such as the generation of reworks, extra works, and shoddy work (Agbaxode et al., 2023), negative effects on the facility life cycle (Alkilani and Loosemore, 2024), the occurrence of contract claims (Andi and Minato, 2003), increased lifecycle costs (Kocot et al., 2024), unclear project scope, and ambiguous invoicing (Mikulík et al., 2022). Therefore, design professionals and personnel responsible for preparing documentation play a significant role in influencing project success (Assaf et al., 2018). Generally speaking, the delivery of quality documentation is often neglected. At the same time, (Venters, 2024) claims that the costs of producing quality documentation at the design stage of a project are typically lower than those of correcting errors during its execution. Any problem or deficiency not addressed during the preparation of design documentation will manifest sooner or later during the execution phase of the construction project.
However, previous studies have provided limited evidence on the effect of documentation quality on project success. Although it is believed that the quality of design documentation is crucial for the successful delivery of construction projects (Sospeter, 2023), there is no statistical evidence. As ascertained by (Shoar and Payan, 2022), studies on the causes and effects of design documentation are scarce and lack a systematic approach to investigating them. Previous studies have addressed these issues from various perspectives, including focusing on the relationships between construction project success and change management, as well as examining the effects throughout the entire project lifecycle (Naji et al., 2022). The identification of various specific impacts of poor design documentation quality on project delivery was provided by (Agbaxode et al., 2023), but only regarding the relative importance index, with the aim of ranking them. Certain insights into the impact of design documentation quality on project performance were also provided by (Shoar and Payan, 2022; Sospeter, 2023), but were investigated from a qualitative point of view and focused on the factors affecting the quality of design documentation. Thus, this literature gap prompts an investigation of this impact from a quantitative perspective.
Hence, we propose the following hypothesis.
High-quality technical specifications of tender documentation have a positive effect on successful projects.
3. Methodology
3.1 Research instrument
The general concept of the research instrument is developed based on the seminal literature addressing communication and change management issues (Hwang and Low, 2012; Rehan et al., 2024), the theory of project success (Radujković et al., 2021) and performance management theory (Korhonen et al., 2023). Furthermore, we build on project governance theory as effective project governance supports project success achievement (Musawir et al., 2017). Specifically, we focused on documentation supervision (Kocot et al., 2024; Sospeter, 2023) in the early stages of the project and issues determining documentation quality (Agbaxode et al., 2024b; Govender et al., 2024) for design-bid-build project delivery methods. Finally, based on the stakeholder’s theory (Freeman and McVea, 2001), we follow the argument of (Philips-Ryder et al., 2013) that documentation quality issues should be addressed from the perspectives of individual stakeholders.
Individual questions were derived based on the addition of preceding qualitative and quantitative research (Mikulík and Hanák, 2024) addressing the significance of deficiencies of technical specifications in construction tender documentation by knowledge gained from the analysed literature, which is presented in Section 2. With respect to stakeholder theory (Freeman, 1999; Ward and Chapman, 2008), this study examines the perspective of implementation companies that deliver construction work. Such an approach allows us to examine the perspective of the key stakeholder who takes over the project documentation created by the designer from the client (investor), based on which construction work is to be carried out.
Based on a mix of knowledge gained from the available literature, a research model including four constructs was developed (see Figure 1). Because tender documentation often contains errors, which are sometimes only discovered during actual construction, there is need to communicate and manage them effectively. In addition to the errors, there are other reasons for these changes. However, any changes must be communicated properly to avoid undesirable information asymmetry.
The model shows four variables represented by circles, with positive relationships indicated by straight solid arrows labeled with hypothesis numbers (H 1 through H 4) and a plus sign. The variable “C O M” is positioned at the top center, “P R S” at the bottom left, “Q T S” at the bottom right, and “S P R” on the right. The hypothesized relationships between the variables are as follows: “H 1 plus” flows from “C O M” to “Q T S.” “H 2 plus” flows from “C O M” to “S P R.” “H 3 plus” flows from “P R S” to “Q T S.” “H 4 plus” flows from “Q T S” to “S P R.” The variables and their full names from the “Note” section are as follows: “C O M”: “Communication of the stakeholders and changes in technical specifications.” “P R S”: “Project documentation supervision.” “Q T S”: “Quality of technical specifications of the tender documentation.” “S P R”: “A successful project.”Research model
The model shows four variables represented by circles, with positive relationships indicated by straight solid arrows labeled with hypothesis numbers (H 1 through H 4) and a plus sign. The variable “C O M” is positioned at the top center, “P R S” at the bottom left, “Q T S” at the bottom right, and “S P R” on the right. The hypothesized relationships between the variables are as follows: “H 1 plus” flows from “C O M” to “Q T S.” “H 2 plus” flows from “C O M” to “S P R.” “H 3 plus” flows from “P R S” to “Q T S.” “H 4 plus” flows from “Q T S” to “S P R.” The variables and their full names from the “Note” section are as follows: “C O M”: “Communication of the stakeholders and changes in technical specifications.” “P R S”: “Project documentation supervision.” “Q T S”: “Quality of technical specifications of the tender documentation.” “S P R”: “A successful project.”Research model
Accordingly, the first construct was stakeholder communication and changes in technical specifications (COM). The occurrence of errors and other deficiencies can be reduced significantly through thorough control activities. Thus, we propose the following second construct: Project documentation supervision (PRS). The first two constructs have all the prerequisites to support the creation of quality documentation; therefore, the third construct forms the technical specifications of the tender documentation (QTS). Finally, because the overarching driver is represented by reaching the success of a given construction project, the fourth construct is designed as a successful project (SPR). Project success was intentionally evaluated from the perspective of an iron triangle. Although the iron triangle dimensions cannot wholly measure various success-related issues of highly complex construction projects, they are still considered to effectively communicate the interrelations among the central success criteria of construction professionals (Kumar et al., 2023). The items for each construct were as follows, with four constructs developed based on the research model:
Communication of the stakeholders and changes in technical specifications (COM):
Communication and proper recording of all changes in the tender positively affect the quality of the technical specifications of the tender documentation. (COM-1)
Changes in the drawing documentation during processing can best be handled by a CDE (CDE → BIM) to which everyone always has access. (COM-2)
Using the meeting minutes, it is possible to avoid errors, deficiencies, and misunderstandings. (COM-3)
Errors caused by changes in drawing documentation during processing can best be handled by preparing a list of works, supplies, and services only after the drawing documentation has been submitted and approved. (COM-4)
Project supervisor (PRS)
To eliminate inaccuracies in documentation, the project supervisor must have the authority to make comments and return documents for revision. (PRS-1)
The project supervisor should check the drawing documentation before processing a list of work, supplies, and services. (PRS-2)
The project supervisor must have knowledge (experience) in the construction, design, and creation of a list of work, supplies, and services. (PRS-3)
Quality of technical specifications of the tender documentation (QTS):
The flawless technical specifications of the tender documentation ensure the project’s success in terms of cost, time, and quality. (QTS-1)
With perfect technical specifications, the occurrence of overwork/underwork decreases. (QTS-2)
The costs of technical specifications are negligible compared to the construction costs, and they are not worth saving. (QTS-3)
Developing flawless technical conditions requires time and resource coordination. (QTS-4)
A successful project (SPR)
Project success is measured using the iron triangle (time, quality, and cost). (SPR-1)
The quality of technical specifications has a positive effect on the time plan and schedule of a project. (SPR-2)
The quality of technical specifications positively affected the construction costs of the project. (SPR-3)
The quality of technical specifications positively affects the quality of a project’s construction work. (SPR-4)
Project success can be ensured through effective project management and appropriate tools. (SPR-5)
The answers were provided using a 7-point Likert scale: 1 = strongly disagree, 2 = disagree, 3 = rather disagree, 4 = neither agree nor disagree, 5 = rather agree, 6 = agree, and 7 = strongly agree.
3.2 Subjects and procedure
The survey was conducted anonymously using an online questionnaire between July and September 2024. A purposive sampling method was used to ensure that respondents had relevant experience in the investigated area and were able to respond to the questions. Respondents were surveyed in two ways. The first 390 email addresses were obtained from the publicly available websites of construction companies operating in the Czech market. These respondents were invited directly via email and were primarily construction managers working for supplier companies. The second method of finding respondents involved using social media, specifically the Facebook group “Designers, architects – a group for construction professionals,” which gathers specialists from the Czech Republic in the field of construction. Members of the aforementioned group were invited to participate by posting announcements about the survey. The group was established in 2015, and the number of members at the time of the announcement was published amounted to 13,400. Of all the respondents who opened the questionnaire, 49.9% completed it.
The survey received 171 responses from various companies. This survey focused on implementation companies, that is, companies that play the role of suppliers in the project and deliver construction work. The sample comprised 61 enterprises. Due to the low response rate, the survey results may not be completely representative or may be biased. Furthermore, the search for respondents using Facebook may have excluded some. The use of a second means of recruiting respondents – invitations via email – may have offset potential bias to some extent. Furthermore, it should be noted that the results of the analyses presented in Tables 1–4 suggest a wide variation in the characteristics of the respondents, which does not indicate the presence of substantial biases.
Number of employees in the surveyed enterprises
| No. of employees | No. of companies | Share in the sample |
|---|---|---|
| 1 employee/self-employed | 2 | 3.3% |
| 2–9 employees | 4 | 6.6% |
| 10–49 employees | 12 | 19.7% |
| 50–249 employees | 20 | 32.8% |
| 250 or more employees | 23 | 37.7% |
| Total | 61 | 100.0% |
Source(s): Authors’ own work
The usual investment amount of the analysed companies
| The usual investment amount | No. of companies | Share in the sample |
|---|---|---|
| Up to 1 EUR million excl. VAT | 9 | 14.8% |
| 1–1.9 EUR million excl. VAT | 8 | 13.1% |
| 2–5.9 EUR million excl. VAT | 15 | 24.6% |
| 6.0–19.9 EUR million excl. VAT | 22 | 36.1% |
| 20 or more EUR million excl. VAT | 7 | 11.5% |
| Total | 61 | 100.0% |
Source(s): Authors’ own work
3.3 Data analysis
The data were analysed using partial least squares structural equation modelling (PLS-SEM) with SmartPLS 4 software (Ringle et al., 2024), allowing the exploration of specific interactions among various project-related factors (Batra, 2024). The PLS-SEM was used based on the argument that it represents the most appropriate approach for establishing new theories in the construction management field, particularly when a small sample size is available (Madushika and Lu, 2025). Furthermore, according to Hair et al. (2019), PLS-SEM is an appropriate method of statistical analysis when the survey consists of a small population, resulting in a small sample size, as in the case of the analysed group; this is particularly relevant when analysing financial ratios or similar datasets, dealing with non-normally distributed data, and addressing the complexity of the research model. In the analysed research model, all latent variables were reflective. The PLS-SEM method requires checking whether the research model meets a series of requirements, and only after these are satisfied can one proceed to the actual analyses. The first step was to verify the reliability of the indicator by checking the indicator loadings. Ideally, their values should be 0.70 or higher, but nonetheless, values of 0.60 and above are accepted in exploratory models (Hair et al., 2011, 2019, 2021). The next step is verifying the values of composite reliability (CR) and Cronbach’s alpha; their values are within 0.7–0.95 (Hair et al., 2021). The average variance extracted (AVE) values of each construct were checked, and their minimum value was assumed to be 0.50 (Chin, 2010; Sarstedt et al., 2021). Finally, discriminant validity was assessed. This can be executed using the Fornell-Larcker criterion analysis. It should be checked whether the square root of the AVE of each latent variable has a value higher than the correlation between the latent variable and the other constructs (Fornell and Larcker, 1981; Koohang et al., 2017). The next step in the assessment of discriminant validity is to check cross-loadings. This verified that each indicator was assigned the correct latent variable (Hair et al., 2011). However, it should be mentioned that the Fornell-Larcker-Criterion, as a tool for checking discriminant validity, has been criticised by some authors because of its low sensitivity (e.g. Henseler et al., 2015). For this reason, the authors propose a new method for assessing discriminant validity, the heterotrait-monotrait ratio of correlations (HTMT), which is becoming increasingly popular in the literature. In this method, the values obtained in the most conservative approach must not exceed 0.85 (Henseler et al., 2015). The PLS-SEM analysis should also include checking the coefficients of determination (R2) of all dependent latent variables. The R2 values indicate the explanatory power of the model (Hair et al., 2021). Once the above criteria are verified, one can proceed to the hypothesis-testing stage.
4. Research results
4.1 Establishing convergence validity
The first step was to establish convergence validity. For this purpose, the measurements of each construct were checked, including the indicator loadings, AVE, CR, and Cronbach’s alpha (Table 5). Most indicators met the condition that their loadings should be greater than 0.70. The loading values of the three indicators were below this limit. However, it should be recalled that in many publications, it is stressed that for exploratory models, the minimum lower bound is 0.60 (e.g. Hair et al., 2011, 2019, 2021). The AVE values of all the constructs were above 0.50. Table 5 shows that all constructs fulfil this condition. Next, CR and Cronbach’s alpha must be greater than 0.70; this condition is met for all the analysed latent variables.
Assessment of measurement – convergence validity
| Construct/indicator | Loadings | AVE | Composite reliability | Cronbach’s alpha |
|---|---|---|---|---|
| COM (Communication of the stakeholders and changes in technical specifications) | 0.56 | 0.83 | 0.73 | |
| COM-1 (Communication and proper recording of all changes in tender documentation) | 0.68 | |||
| COM-2 (Changes in the drawing documentation during processing) | 0.70 | |||
| COM-3 (Using the minutes during the meeting) | 0.85 | |||
| COM-4 (Errors caused by changes in the drawing documentation) | 0.75 | |||
| PRS (Project supervisor) | 0.76 | 0.90 | 0.84 | |
| PRS-1 (Eliminating inaccuracies in the documentation – project supervisor authority) | 0.91 | |||
| PRS-2 (The project supervisor – check the drawing documentation) | 0.93 | |||
| PRS-3 (The project supervisor’s knowledge of construction, design, and creating a list of works, supplies, and services) | 0.77 | |||
| QTS (Quality of technical specifications of the tender documentation) | 0.54 | 0.82 | 0.71 | |
| QTS-1 (Flawless technical specifications of the tender documentation) | 0.88 | |||
| QTS-2 (Perfect technical specifications -occurrence of overwork/underwork decreases) | 0.76 | |||
| QTS-3 (The costs of technical specifications – negligible compared to the price of construction) | 0.63 | |||
| QTS-4 (Developing flawless technical conditions requires time and resource coordination) | 0.64 | |||
| SPR (A successful project) | 0.66 | 0.91 | 0.87 | |
| SPR-1 (Project success is measurable using the iron triangle) | 0.75 | |||
| SPR-2 (The quality of the technical specification has a positive effect on the time plan/schedule of the project) | 0.87 | |||
| SPR-3 (The quality of the technical specification has a positive effect on the construction costs of the project) | 0.85 | |||
| SPR-4 (The quality of the technical specification has a positive effect on the quality of the construction works of the project) | 0.86 | |||
| SPR-5 (The success of the project can be ensured by good project management) | 0.74 |
Source(s): Authors’ own work
4.2 Establishing discriminant validity
The Fornell-Larcker criterion was used to establish discriminant validity (Table 6). As we can observe, the square roots of the AVE, shown in bold, on the diagonal are higher than the correlations between the constructs.
Fornell-Larcker criterion
| Construct | PRS | QTS | SPR | COM |
|---|---|---|---|---|
| PRS | 0.87 | |||
| QTS | 0.53 | 0.74 | ||
| SPR | 0.58 | 0.65 | 0.81 | |
| COM | 0.53 | 0.52 | 0.64 | 0.75 |
Source(s): Authors’ own work
Table 7 lists the cross-loadings. We may see that the correlation of each indicator is the highest for the construct to which it has been assigned. We argue that the discriminant validity of our research model was established.
Cross-loadings
| Indicator | PRS | QTS | SPR | COM |
|---|---|---|---|---|
| PRS-1 | 0.91 | 0.52 | 0.57 | 0.56 |
| PRS-2 | 0.93 | 0.46 | 0.55 | 0.50 |
| PRS-3 | 0.77 | 0.39 | 0.39 | 0.31 |
| QTS-1 | 0.55 | 0.88 | 0.54 | 0.45 |
| QTS-2 | 0.23 | 0.76 | 0.52 | 0.43 |
| QTS-3 | 0.36 | 0.63 | 0.33 | 0.39 |
| QTS-4 | 0.39 | 0.64 | 0.50 | 0.25 |
| SPR-1 | 0.49 | 0.41 | 0.75 | 0.52 |
| SPR-2 | 0.57 | 0.53 | 0.87 | 0.63 |
| SPR-3 | 0.42 | 0.63 | 0.85 | 0.56 |
| SPR-4 | 0.38 | 0.59 | 0.86 | 0.47 |
| SPR-5 | 0.54 | 0.48 | 0.74 | 0.43 |
| COM-1 | 0.33 | 0.26 | 0.46 | 0.68 |
| COM-2 | 0.36 | 0.40 | 0.39 | 0.70 |
| COM-3 | 0.53 | 0.42 | 0.58 | 0.85 |
| COM-4 | 0.35 | 0.45 | 0.47 | 0.75 |
Source(s): Authors’ own work
According to (Henseler et al., 2015), establishing discriminant validity using the Fornell-Larcker criterion alongside cross-loadings has very low sensitivity, which is unacceptable. This is why another method was used to confirm discriminant validity: the heterotrait-monotrait ratio of correlations (HTMT) – Table 8. In this method, the highest, although most conservative, value is 0.85 (Henseler et al., 2015). As shown in Table 8, none of the values exceeded this threshold. Thus, the discriminant validity of the model was established.
4.3 The structural model
The coefficient of determination (R2) values for technical specifications of the tender documentation (QTS) amounted to 0.36, and for a successful project (SPR) reached 0.55. The values are considerable and notable, especially considering the fact that (Falk and Miller, 1992) perceive values 0.10 and higher as meaningful. It is also worth noting that the second latent variable, a successful project (SPR) with a higher coefficient of determination, is the most important explained variable in the research model.
4.4 Accepting or rejecting hypotheses
Bootstrap validation using 5,000 samples was used to check the statistical significance of the results. Bootstrapping was used to estimate the shape, bias, and spread of sampling distribution. It is based on a large number of predefined bootstrap samples (Henseler et al., 2009).
Table 9 presents path coefficients, standard deviation, t-values, and p-values, which determine the acceptance/rejection of hypotheses. H1, which stated, “Stakeholders’ communication and effective change management has a positive effect on the delivery of high-quality technical specifications of the tender documentation,” has been accepted (βo = 0.33; t = 1.98; p < 0.05). H2, which stated, “Stakeholders’ communication and effective change management has a positive effect on a successful project,” has been accepted (βo = 0.42; t = 3.52; p < 0.001). H3, which stated, “Project supervisor has a positive effect on the delivery of high-quality technical specifications of the tender documentation,” has been accepted (βo = 0.35; t = 2.18; p < 0.05). H4, which stated, “High-quality technical specifications of the tender documentation have a positive effect on a successful project,” has been accepted (βo = 0.43; t = 2.77; p < 0.01).
The acceptance or rejection hypotheses
| Hypothesis | Path | βo | Bootstrap results | Hypothesis accepted or rejected | |||
|---|---|---|---|---|---|---|---|
| βm | SD | t-value | p-value | ||||
| H1 | COM → QTS | 0.328 | 0.318 | 0.166 | 1.983 | <0.05 | Accepted |
| H2 | COM → SPR | 0.419 | 0.427 | 0.119 | 3.522 | <0.001 | Accepted |
| H3 | PRS → QTS | 0.354 | 0.331 | 0.163 | 2.175 | <0.05 | Accepted |
| H4 | QTS → SPR | 0.434 | 0.407 | 0.156 | 2.771 | <0.01 | Accepted |
Source(s): Authors’ own work
The relationships between specific latent variables are illustrated graphically in Figure 2. It shows the path coefficients and coefficients of determination (R2) of the dependent variables (inner circles).
The model shows four variables represented by circles, with relationships indicated by straight solid arrows labeled with hypothesis numbers (H 1 through H 4) and corresponding numerical values. The variable “C O M” is positioned at the top center, “P R S” at the bottom left, “Q T S” at the bottom right, and “S P R” on the right. The hypothesized relationships between the variables are as follows: “H 1 (0.33)” flows from “C O M” to “Q T S.” “H 2 (0.42)” flows from “C O M” to “S P R.” “H 3 (0.35)” flows from “P R S” to “Q T S.” “H 4 (0.43)” flows from “Q T S” to “S P R.”The research model: results
The model shows four variables represented by circles, with relationships indicated by straight solid arrows labeled with hypothesis numbers (H 1 through H 4) and corresponding numerical values. The variable “C O M” is positioned at the top center, “P R S” at the bottom left, “Q T S” at the bottom right, and “S P R” on the right. The hypothesized relationships between the variables are as follows: “H 1 (0.33)” flows from “C O M” to “Q T S.” “H 2 (0.42)” flows from “C O M” to “S P R.” “H 3 (0.35)” flows from “P R S” to “Q T S.” “H 4 (0.43)” flows from “Q T S” to “S P R.”The research model: results
To conduct a robustness check, the potential nonlinearity of the relationships was examined using a quadratic effect analysis. This is a popular method used by many authors in the field of robustness assessment, as shown in the compilation created by (Sarstedt et al., 2020). The bootstrapping results showed that all the relationships tested using the quadratic effect were statistically insignificant, confirming the linearity of the relationships tested.
5. Discussion
This study sought to reveal how communication and change management (COM), project documentation supervision (PRS), and the quality of technical specifications of tender documentation (QTS) contribute to project success in the construction environment (SPR). First, while communication competencies are considered exclusively soft skills related to the ability to communicate in different contexts (Alvarenga et al., 2019), communication should also determine various project technical requirements (Ziek and Anderson, 2015), which change during documentation development. Our findings, based on the analysed PLS-SEM model, confirm that effective communication and change management influence not only the quality of the technical specifications in the tender documentation (QTS) but also directly contribute to the project’s success (SPR) in relation to the iron triangle (time, quality, and cost). This is in line with the research of (Alvarenga et al., 2019; Naji et al., 2022), who concluded that communication and change management during the entire project have an impact on project success. However, while calls for consolidating various project-related attributes in relation to project success are mostly focused on the entire life cycle, we suggest that these relationships should be examined in delimited project phases and in the context of defined milestones. By taking the delivery of documentation as a key milestone, it is possible to study the factors affecting its quality, as well as the subsequent impact of documentation quality on the success of the project.
The results also support the requirements for the use of a CDE for BIM-based projects. This approach provides equal access to information for all stakeholders and a digital footprint of key decisions, which can be useful in the case of potential disputes or claims. Our findings support those of previous studies (Parisi et al., 2021; Seyis and Ozkan, 2024), highlighting the need to promote digitalised communication among stakeholders as one of the most important information asymmetry risk-minimisation strategies (Ceric, 2014). The model also emphasises the need for consistent recording of information communicated and decisions made at oral meetings using meeting minutes and subsequent sharing in digital form.
Second, our findings acknowledge the need for an independent review of documentation (PRS) before it can be used as a basis for selecting contractors. Early involvement of key participants contributes to the quality of documentation creation (Agbaxode et al., 2024b) and despite the asserted importance of expertise awareness in adoption strategies promoting documentation quality improvement (Abdallah et al., 2019; Agbaxode et al., 2023), our results are contrary to the statement that project owners are experienced, and thus independent analyses of available documentation are not needed (Larsen et al., 2021). Specifically, the outputs of the presented model statistically confirm the significance of independent documentation supervision, supporting previous studies showing that strict quality control procedures are necessary to reduce mistakes and inconsistencies (Obasanjo Olubukola et al., 2024). Our results show that project documentation supervision (PRS) plays a crucial role in ensuring the quality of the technical specifications in the tender documentation. However, the PRS must be represented by an expert with extensive experience in construction execution, design, and cost estimation. As control is often a misunderstood aspect of project management (Gardiner and Stewart, 2000), documentation quality control in the preconstruction stage should be supported by predefined quality standards (Willar et al., 2023).
The quality of technical specifications (QTS) serves as a fundamental basis for suppliers of construction works (construction companies). Without a clear understanding of their requirements, critical errors cannot be identified or rectified. At the same time, the supervisor needs to have knowledge of design and construction production valuation, as these two disciplines form the core of the technical specifications. It is equally important for supervisors to have the authority to review, provide feedback, and return documents for revision. Without this capability, the PRS control over the process is significantly limited. Furthermore, the model suggests that supervisors should review technical specifications before they are handed over to the cost estimation team to develop bills of quantities and costs. This step is strongly recommended to avoid the occurrence of potential changes in drawing documentation after the preparation of the list of works, supplies, and services, thereby mitigating the risk of opportunistic behaviour by contractors (Love et al., 2017). By emphasising the role of experience and competencies, this study follows up on previous papers, which, for instance, argue that design firms can improve their own design practice when they can exercise control over a project by considering liquidated damages resulting from defective design (Andi and Minato, 2003).
It should be noted that flawless technical conditions for tender documentation are practically unattainable and require a significant amount of time and resource coordination. However, the fewer errors they contain, the less likely extra work or less work might occur during the implementation of construction work. At the same time, it can be argued that the costs of creating technical conditions are negligible compared to total construction costs (Andi and Minato, 2003). Thus, the presented results are in line with previous studies emphasising the creation of a suitable time and economic environment for the development of the technical specifications of tender documentation (Akampurira and Windapo, 2018; Andi and Minato, 2003; Sospeter, 2023), and that their rigorous preparation based on high awareness, advanced experience sharing, and independent control contributes significantly to their overall quality, and hence positively impacts the success of the project.
For the control process to be effective, it must be based on actual numerical data. Therefore, various performance indicators can be applied to cover the full scope of influencing factors. The indicators proposed by (Herrera and Castañeda, 2024; Naji et al., 2022) can be monitored as inspiration. However, indicators such as Design Errors and Rework, which tracks the number of design errors detected and the amount of rework required during the project, should be considered not just in absolute values; instead, relative values should also be applied, e.g. regarding the value of investment costs or an enclosed area of the facility.
6. Conclusion
Although many studies exist on the different aspects of project success, they mostly relate to the specific effects that appear during the entire project lifecycle. This study highlights the importance of understanding how communication, change management, and supervision affect the delivery of successful construction projects through high-quality technical specifications of tender documentation. Thus, our study supports the need for adequate quality control at every stage of a project (Zhuman et al., 2024).
6.1 Implications for research
This quantitative study contributes to the literature on project success by asserting the importance of a crucial project milestone: the delivery of high-quality technical specifications for tender documentation. Our study extends the available theory by adopting a multifunctional perspective on documentation quality and considering the communication, change management, and control functions. Specifically, the findings reveal the crucial role of information technologies in supporting communication and effective change management to achieve time-, cost-, and quality-related project goals. These, in synergy with thorough documentation control, contribute to achieving low-error-intensive structural engineering drawings and other nongraphic information in the tender documentation. This is in line with the current project success research stream, where complexity is not to be reduced but instead embraced (Ika and Pinto, 2022; Tywoniak et al., 2021).
Thus, we evolved the understanding of achieving the ultimate success of a project by integrating selected project milestones to explore more complex relationships that can be examined as additional latent variables in research models. Additionally, this study contributes to the body of knowledge dealing with the soft and hard aspects of communication, as well as stakeholder theory. It emphasises the importance of examining the attitudes of individual stakeholders separately. While our study focuses on the contractor’s perspective, it can be assumed that the perspectives of the investor or designer on the issue under investigation may be different.
6.2 Implications for practice
A deeper understanding of the investigated constructs can facilitate the delivery of successful projects. Highlighting the impact of the examined constructs within the model demonstrates that organisations should attend to the practices of using digital communication to effectively handle changes. This includes the adoption of CDE and BIM tools as well as compliance with the sequence of individual processes, such as the preparation of the list of works, supplies, and services only after the drawing documentation has been submitted and approved.
These results suggest that practices of project management should not rely on the self-controlling effect of experienced personnel on documentation quality. Instead, we suggest adopting the practice of automatically engaging in independent documentation supervision. This might limit the risk of inadequate attention so that internal checks are not effectively formed due to the lack of awareness of responsibility (Yang et al., 2025).
Accordingly, this study highlights the importance of effective project governance with clear responsibilities for achieving project goals through high-quality technical specifications of tender documentation. Consistent with the conclusions of (Jawad et al., 2024), we argue that such efficiency should be supported by defined and documented processes used by all stakeholders. While the process of documentation supervision might be defined in certain environments, for example, when governmental project managers are in charge of validating project documents for quality assurance (Brunet, 2019), such an approach is typically applied only in a limited number of countries and usually for major public infrastructure projects. When considering private projects or local public projects, the question is what kinds of quality assurance are ensured and whether it also covers documentation quality assurance.
The results demonstrate the positive impact of quality documentation on all three key areas of project performance: cost, time, and quality. Fewer error-intensive documents contribute positively to reducing the amount of additional work (and thus, the generation of cost overruns) and changes to the project during its implementation. Consequently, this positively impacts the schedule and quality of delivered work. From a societal perspective, this ultimately leads to increased public trust in construction projects as the intensity of information asymmetry is suppressed and the number of disputes decreases.
This study aims to enhance foundational principles for producing high-quality documentation in construction projects. A proactive strategy is strongly advised to promptly detect and resolve deviations from specifications, thereby optimising project efficiency and reducing potential costs associated with corrective actions and scheduling problems.
6.3 Limitations
Despite the contributions of this study, four aspects of the current study are considered as limitations. First, it is essential to acknowledge that this study relies on the specific context of the Czech construction market. Therefore, the findings of this study can only be generalised after considering national specificities regarding the requirements for tender documentation. However, given that the Czech Republic is a member state of the European Union, within which a common umbrella regulation exists in the context of public procurement, the findings presented in this study have potential for application in a wider European context.
Second, the data used in this study represent only a single stakeholder’s point of view, that is, the implementation company. Therefore, future research, in addition to comparisons with other geographical locations, should focus on the perception of the researched problem from the perspective of other project participants, such as clients and designers.
Third, the limited sample size significantly affects the empirical generalisability of the findings. Therefore, future research must investigate the differences across various specialisations of construction companies (industrial buildings, transport structures, etc.), as these types of projects may be affected by certain specifics. Fourth, the presented findings are valid for the traditional project delivery method, Design-Bid-Build. Therefore, they cannot be applied to Design and Build projects, in which the milestone of processing detailed project documentation has different consequences.
6.4 Future research directions
Based on the findings and limitations of this study, several avenues for future research are proposed. First, it would be beneficial to investigate documentation quality and its influence on project success from the perspective of key stakeholders, including clients and designers, across diverse geographical contexts. Understanding these viewpoints may enhance our understanding of the issues at hand.
Additionally, we advocate for research focused on the development of advanced performance metrics that assess the processes associated with documentation creation and quality assurance. The absence of effective indicators and their insufficient practical application represent significant barriers to the advancement of documentation quality. Addressing these gaps could facilitate substantial improvements in this area.
This paper was prepared under Brno University of Technology project, titled “Management of selected technical and economic processes taking place in construction projects” (No. FAST-S-25-8819) and supported by funds granted by the Minister of Science under the “Regional Initiative for Excellence” Programme for the implementation of the project “The Poznań University of Economics and Business for Economy 5.0: Regional Initiative – Global Effects (RIGE).”
