Selection of New Projects Considering the Synergistic Relationships in a Project Portfolio

Abstract

Multiple internal conflicts and external emergencies can occur when an enterprise implements a project portfolio (PP), making the PP inevitably deviate from the enterprise’s strategic objectives. As a means of project portfolio change (PPC) that aims to align the PP with strategic objectives, adding new projects can compensate for this deviation. Furthermore, the synergistic relationships in the PP can significantly impact the achievement of the enterprise’s strategic objectives. Therefore, this study presents a procedure for the selection of new projects that considers the synergistic relationships in the PP. First, the deviation between the PP and the enterprise’s strategic objectives is identified. Second, the synergistic relationships between candidate new projects and the projects in the PP are analyzed, based on which a model of new project selection is built. Third, by comparing the model simulation results of the attainment of the strategic objectives of several PPs, the new projects that can best achieve these strategic objectives are added to the PP. This procedure is illustrated using a numerical example showing its applicability and efficacy. For academia, this study provides a theoretical framework for the selection of new projects. Moreover, the straightforward procedure can help manage PPs in business practice.

1. Introduction

A project portfolio (PP) is a collection of projects and operations managed as a group to achieve strategic objectives [1]. In the multi-project context, a PP is undertaken as a primary mode by most enterprises in the fields of research and development [2], new project development [3], and technology management [4,5]. However, in practice, implementing enterprise strategies is always challenging [5]. Studies show that only approximately 35% of enterprise strategies are actually implemented [6]. Such failure primarily lies in the deviation between the PP and the enterprise’s strategic objectives [7], resulting in the PP not operating as expected, and disrupting the enterprise’s strategic planning. Therefore, the alignment of PPs with the enterprises’ strategic objectives has become an urgent and crucial issue. Against this backdrop, project portfolio change (PPC) serves as an effective tool for reducing the deviation between the PP and the enterprise’s strategic objectives [1]. In contrast to other approaches such as PP benefit forecasting and PP risk assessment for handling contingencies in advance, PPC is a post hoc solution that manages deviation by taking remedial measures. Overall, PPC can help correct any possible PP deviation.

In general, when a PP deviates from the enterprise’s strategic objectives, there are two kinds of PPC remedies: The first, most common remedy is fixing troubled projects through means such as adjusting the funding or schedule to bring them back on track [8,9]. However, the remediation of troubled projects cannot ensure the achievement of the expected results in every circumstance [10]. In the case of excessive deviation, the utility of remedial measures for troubled projects may not be enough to compensate for such high deviation. Furthermore, when the costs of repairing troubled projects far exceed the benefits that they create, the necessity of repairing them is questionable [11]. In contrast, updating the PP by adding new projects is another remedy [1]. As the new projects carry the enterprise’s strategic objectives, after the new projects are added to the PP, the deviation can be eliminated by achieving these strategic objectives. In addition to the new projects themselves, the changes brought by adding new projects to the PP can remove the deviation. For example, changes in resource utilization and scheduling in the PP mean that the PP needs to be replanned. The reformulated plan can deal with deviation caused by the misallocation of resources and schedule conflicts. The literature has confirmed that adding new projects can benefit a PP [12]. Nevertheless, there is minimal research on PPC by selecting new projects. As a result, there is a lack of a practical framework to help correct PP deviation and achieve enterprises’ strategic objectives.

The decision to engage in PPC by adding new projects is not arbitrary. One particular feature of a PP is the synergistic relationships between its projects due to the sharing of resources such as manpower and technology [13]. These relationships are conducive to generating additional benefits by fully utilizing resources and achieving the enterprise’s strategic objectives [14,15]. Adding new projects can alter the synergistic relationships in the PP and, hence, impact the realization of the enterprise’s strategy. Therefore, it is necessary to consider the synergistic relationships between projects when adding new projects. Only in this way can we give full play to the role of the new projects and compensate for the deviation between the PP and the enterprise’s strategic objectives. This study seeks to answer the following research question: How can new projects be selected to remedy the deviation between a PP and an enterprise’s strategic objectives considering the synergistic relationships in the PP?

To answer this question, a three-phase procedure for the selection of new projects is proposed. In the first phase, the deviation between a PP and an enterprise’s strategic objectives is identified using strategic alignment theory [16]. Strategic alignment theory is adopted in the second phase to select one or more new projects that can deal with the deviation identified in the first phase. If several new projects are obtained, in the third phase, the system dynamics (SD) method is adopted to analyze the impact of the synergistic relationships on the realization of the strategic objectives. SD is an effective approach to analyze and assess the dynamic behavior of complex systems in order to better understand their operational processes [17], which can be used in this phase to select the optimal new projects. Finally, a numerical example is presented to illustrate how to use the procedure proposed in this paper.

The rest of this paper is organized as follows: Section 2 reviews the PP literature based on two aspects—(i) project portfolio management and project portfolio change, and (ii) project portfolio synergy. In Section 3, a three-phase procedure for the selection of new projects is proposed in detail. In Section 4, a numerical example is given to illustrate the applicability and practicability of the procedure. In Section 5, the paper discusses the theoretical and managerial implications of our study, followed by the conclusions in Section 6.

2. Literature Review

2.1. Project Portfolio Management and Project Portfolio Change

As illustrated by the Project Management Institute, PP management is the centralized management of one or more PPs to achieve strategic objectives [1]. Coordinated PP management can deliver increased benefits to organizations [16]. The current literature highlights that PP management focuses on evaluating, prioritizing, and selecting projects in line with strategy [18,19]. Research on choosing the “right projects” has been relatively well developed [20]. However, a few studies have begun to explore how to implement the “right projects” [2,21,22,23]. Due to the widespread existence of internal (e.g., schedule conflicts, resource competition among projects, etc.) and external (e.g., stakeholder conflict, market instability, etc.) adverse factors in the implementation process [20,24,25], deviation between the PP and the enterprise’s strategic objectives often occurs, posing significant challenges to PP management. As an essential method of PP management, engaging in PPC can effectively deal with the deviation of the PP from the enterprise’s strategic objectives.

As Pavlak [26] notes, deviation inevitably occurs, regardless of how a project is planned and executed. As a means of achieving an enterprise’s strategic objectives, PPC is undertaken when the deviation has been confirmed. According to the literature, the most common means of PPC is to adjust the troubled project [27,28]. Childs and Triantis [29] claim that switching the implementation priorities is usually chosen to remedy deviation when a project underperforms. Wang et al. [11] argue that remedial measures of increasing investment in troubled projects should be taken pursuant to the degree of deviation. Engwall and Jerbrant [30] argue that resources are always limited, and that the reallocation of PP resources can remedy the PP deviation under resource constraints [31]. Guan et al. [32] evaluated the comprehensive risk of the PP, and proposed risk-reduction strategies for troubled projects with the most significant risk to handle the PP deviation.

PPC can be undertaken not only by remediating troubled projects, but also by adding new projects to compensate for deviation. The Standard for Portfolio Management advocates that new projects can be added to align the PP with the enterprise’s strategic objectives, mainly for the following two reasons: One reason is that the functions of new projects can be utilized to achieve unfulfilled strategic objectives [20]. The other reason is that when implementing new projects, managers need to use resources, follow the schedule, etc., bringing corresponding changes to the PP, such as resource reallocation [33] and project priority adjustment [34]. These changes can partially remedy the deviation caused by unreasonable resource allocation and schedule conflicts. Hence, adding new projects can more effectively address the deviation between the PP and the enterprise’s strategic objectives. However, there is a lack of research conducting in-depth analysis of PPC by adding new projects, leaving a gap in the current literature that makes it challenging to provide guidelines for addressing the inconsistencies between PPs and enterprises’ strategic objectives. To fill this research gap, this study is dedicated to developing a method of engaging in PPC by adding new projects when deviation occurs.

2.2. Project Portfolio Synergy

Synergy was proposed by Haken [35] to coordinate multiple interactive resources and subjects to achieve certain objectives. It can not only effectively guide the business reorganization of enterprises and process improvement, but also promote incremental benefits through optimal resource allocation [36]. A PP emphasizes the interaction between different projects from the overall perspective of the organization to create more than the sum of its individual projects [37], which is highly consistent with the characteristics of synergy. Therefore, scholars have introduced synergy into the field of PP management.

PP synergy is defined as the additional effect generated by how projects interact with one another in the PP context [38], and is mainly studied from both the qualitative and quantitative perspectives [39,40,41]. In qualitative research, scholars mainly divide synergy into multiple dimensions. Bai et al. [42] identified three types of synergy—the synergy between project and strategy, the synergy within projects, and the synergy between project and environment—for selecting the right PP from a synergistic perspective. To evaluate the comprehensive level of management synergy, Li et al. [43] subdivided synergy into information synergy, organizational synergy, resource synergy, target synergy, and cultural synergy. Lopes and Almeida [38] proposed project scope synergy, financial synergy, and information synergy to explore the influence of synergy on the preferences of decision-makers. Furthermore, scholars have introduced concepts such as the order degree and order parameter to conduct quantitative research on synergies [42,44]. Li and Fei [45] established a measurement model for the degree of construction program management synergy, in accordance with the synergy principle of order parameters. Bai et al. [46] constructed a PP benefit evaluation model considering synergistic relationships, in which a parameter expresses the synergistic effect in the model. Cao et al. [47] proposed a PP allocation model based on the principle of order parameters, and the degree of strategic synergy development was used to measure the synergistic effect.

As mentioned above, existing research on PP synergy has been fruitful [48,49]. However, because adding new projects may change the PP synergy, this paper analyzes the synergistic relationships of a PP in light of the co-utilization among projects, and quantifies the impact of the synergistic relationships in the PP on the achievement of the enterprise’s strategic objectives.

3. The New Project Selection Procedure

In this paper, a procedure for the selection of new projects is proposed to solve the problem that occurs when a PP deviates from an enterprise’s strategic objectives. As illustrated in Figure 1, the procedure is composed of three phases: (i) identifying unfulfilled sub-strategic objectives, (ii) obtaining the set of feasible new projects, and (iii) determining the optimal new projects. In the first phase, the enterprise’s strategic objectives are divided into several sub-strategic objectives. Subsequently, information on the enterprise and its PP is collected to evaluate the strategic alignment and to identify unfulfilled sub-strategic objectives. Then, the second phase focuses on obtaining a set of feasible new projects that can help achieve the unfulfilled sub-strategic objectives within capital constraints by calculating the strategic alignment of the PP with the addition of new projects. Finally, in the third phase, the PP’s synergistic relationships are quantified to simulate the achievement of the enterprise’s strategic objectives through the new project selection model to determine the optimal new projects. For convenience, this section first introduces the parameters used in the procedure, as shown in

Table 1. Definition of notations.

Notation	Definition
vj	The set of sub-strategic objectives, j = 1,2,…,7
xj	The minimum requirement of sub-strategic objective j
yij	The contribution of project portfolio i to the sub-strategic objective j
f	Composition operator
bpij	The contribution of project portfolio i to the sub-strategic objective j
bjmin	The minimum requirement of sub-strategic objective j
SIij	The strategic alignment of PPi on sub-strategic objective j
P’i	The new project i
PPi	The project portfolio that includes new project i
ci	The capital of new project i
C	The total capital invested by the enterprise on new projects
wj	The weight of sub-strategic objective j
dis	The degree of information synergy
drs	The degree of resource synergy
dts	The degree of technology synergy
dfs	The degree of function synergy
${\mathsf{\xi }}_{j1}$	The contribution of information synergy to the sub-strategic objective j
${\mathsf{\xi }}_{j2}$	The contribution of resource synergy to the sub-strategic objective j
${\mathsf{\xi }}_{j3}$	The contribution of technology synergy to the sub-strategic objective j
${\mathsf{\xi }}_{j4}$	The contribution of function synergy to the sub-strategic objective j
RSO	The degree of realization of the enterprise’s strategic objectives
RSOij	The degree of realization of sub-strategic objective j considering PPi synergies
RSO’ij	The degree of realization of sub-strategic objective j with respect to PPi

.

3.1. Phase 1: Identifying Unfulfilled Sub-Strategic Objectives

There are three steps in the first phase: The first step is to divide the enterprise’s strategic objectives and construct a strategic objective index system to accurately analyze the deviation between the PP and the enterprise’s strategic objectives. Then, the second step aims to collect information about the enterprise’s minimum requirements for the sub-strategic objectives and the contributions of the PP to meeting the sub-strategic objectives, which can provide a reference for identifying unrealized objectives. Finally, in the third step, the unfulfilled sub-strategic objectives are identified by applying strategic alignment theory.

• Step 1: Construct the strategic objective index system

The balanced scorecard (BSC) is applied to translate a strategy into specific and measurable objectives: financial, customer, internal process, learning, and growth [50,51]. This approach has been widely adopted in modeling organizational strategy, but it may omit environmental and moral issues. Noting these limitations, the sustainability balanced scorecard (SBSC), which adds the perspective of sustainability, is introduced and employed in this study to decompose a strategy into its sub-objectives. Combining these perspectives enables organizations to monitor short-term financial results while tracking the progress and performance of intangible assets and focusing on environmental and social issues [52]. The strategic objective index system provided by Bai et al. [53] is divided pursuant to the SBSC, aggregating the most critical indices in the literature. These evaluate candidate projects based on the index system to build a PP that can achieve strategic objectives. The index system can be applied to analyze the achievement of the enterprise’s strategic objectives, and to evaluate candidate new projects. The index system (

Table 2. The strategic objective index system.

Sub-Strategic Objectives	Index Factors
Profitability (S1)	Increase profits (S11)
	Mitigate cost ($S_{12}$)
Customer satisfaction ($S_2$)	Predict customer preference ($S_{21}$)
	Offer high quality of services ($S_{22}$)
	$\mathrm{Shortened}\mathrm{order}\mathrm{processing}\mathrm{time}(S_{23}$)
$\mathrm{Brand}\mathrm{market}\mathrm{value}(S_3$)	$\mathrm{Expand}\mathrm{market}\mathrm{share}(S_{31}$)
	$\mathrm{Improve}\mathrm{brand}\prime s\mathrm{value}(S_{32}$)
$\mathrm{Management}\mathrm{maturity}(S_4$)	$\mathrm{Establish}\mathrm{a}\mathrm{standardized}\mathrm{management}\mathrm{system}(S_{41}$)
	$\mathrm{Creation}\mathrm{of}\mathrm{PM}\mathrm{manuals}(S_{42}$)
	$\mathrm{Establish}\mathrm{management}\mathrm{information}\mathrm{platform}(S_{43}$)
$\mathrm{Manufacturer}\mathrm{development}\mathrm{and}\mathrm{innovation}(S_5$)	$\mathrm{Improve}\mathrm{efficiency}\mathrm{of}\mathrm{productivity}(S_{51}$)
	$\mathrm{Shorten}\mathrm{lead}\mathrm{time}(S_{52}$)
	$\mathrm{Improve}\mathrm{quality}\mathrm{of}\mathrm{products}(S_{53}$)
	$\mathrm{Product}\mathrm{development}(S_{54}$)
Employees $\mathrm{development}\mathrm{and}\mathrm{innovation}(S_6$)	$\mathrm{Increase}\mathrm{employees};\mathrm{satisfaction}(S_{61}$)
	$\mathrm{Enhance}\mathrm{employees}\prime \mathrm{ethics}(S_{62}$)
	$\mathrm{Increase}\mathrm{knowledge}\mathrm{and}\mathrm{skills}\mathrm{of}\mathrm{employees}(S_{63}$)
	$\mathrm{Increase}\mathrm{employees}\prime \mathrm{acceptance}\mathrm{of}\mathrm{corporate}\mathrm{culture}(S_{64}$)
$\mathrm{Organization}\mathrm{contribution}(S_7$)	$\mathrm{Provision}\mathrm{of}\mathrm{social}\mathrm{welfare}(S_{71}$)
	$\mathrm{Human}\mathrm{resource}\mathrm{management}(S_{72}$)
	$\mathrm{Environmental}\mathrm{protection}(S_{73}$)

) can be adjusted in accordance with the actual situation of the enterprise.

• Step 2: Collect information on the enterprise and the PP

First, the enterprise’s minimum requirements for the sub-strategic objectives and the contribution of the PP to meeting these objectives are evaluated by four linguistic terms: “excellent”, “good”, “average”, and “indifferent”; these terms are represented by four levels: A, B, C, and D, respectively. After collecting the essential information, the evidence reasoning (ER) approach is used to transform the linguistic terms of multiple indicator factors into the exact values of each sub-strategic objective. ER is an algorithm developed based on the evidence combination rule of Dempster–Shafer theory [54]; it can convert a qualitative description into quantitative information and effectively aggregate the attributes of a multilevel structure. In this section, this method is applied to transform and aggregate the linguistic assessments of a multilevel sub-strategic objective index to obtain the values of the enterprise’s minimum requirements for sub-strategic objectives, along with the contribution of the PP to meeting those objectives.

• Step 3: Calculate the strategic alignment of the PP

Strategic alignment is the degree of matching between projects and enterprises’ strategic objectives. It is expressed as the ratio of the contribution value of the project to the enterprise’s strategy to the value of the minimum requirements for that strategy [55]. This paper considers the PP as a whole and calculates the PP’s strategic alignment based on Equation (1):

$${\mathrm{SI}}_{\mathrm{j}}=\frac{{\mathrm{bp}}_{\mathrm{j}}}{{\mathrm{b}}_{\mathrm{jmin}}}$$

(1)

$${\mathrm{bp}}_{\mathrm{j}}=\mathrm{f}\left(\left({\mathrm{y}}_1{,\mathrm{v}}_1\right),\left({\mathrm{y}}_2{,\mathrm{v}}_2\right),\dots ,\left({\mathrm{y}}_{\mathrm{n}}{,\mathrm{v}}_{\mathrm{n}}\right)\right)0\le {\mathrm{bp}}_{\mathrm{j}}{<1,\mathrm{y}}_{\mathrm{in}}\in \left\{\mathrm{A},\mathrm{B},\mathrm{C},\mathrm{D}\right\}$$

$${\mathrm{b}}_{\mathrm{jmin}}=\mathrm{f}\left(\left({\mathrm{x}}_1{,\mathrm{v}}_1\right),\left({\mathrm{x}}_2{,\mathrm{v}}_2\right),\dots ,\left({\mathrm{x}}_{\mathrm{n}}{,\mathrm{v}}_{\mathrm{n}}\right)\right)0\le {\mathrm{b}}_{\mathrm{jmin}}{<1,\mathrm{x}}_{\mathrm{n}}\in \left\{\mathrm{A},\mathrm{B},\mathrm{C},\mathrm{D}\right\}$$

where ${\mathrm{SI}}_{\mathrm{j}}\ge 1$ indicates that the PP can achieve sub-strategic objective $\mathrm{j}$. Conversely, $0\le {\mathrm{SI}}_{\mathrm{j}}<1$ indicates that the PP deviates from sub-strategic objective $\mathrm{j}$.

3.2. Phase 2: Obtaining the Set of Feasible New Projects

In the second phase, the candidate new projects must be screened twice to obtain a set of feasible new projects. First, candidate new projects that are infeasible with existing capital constraints are filtered out. Second, the remaining projects are further screened in accordance with the strategic alignment. After these two steps, we have the final set of feasible new projects.

• Step 4: Filter candidate new projects through capital constraints

The addition of new projects brings changes to the original activities, such as the re-procurement of resources and reconfiguration of management personnel, and these changes require capital support. This study uses capital constraints to prescreen candidate projects. Capital constraints can be expressed as follows:

$$\begin{gathered} {\displaystyle \sum }_{\mathrm{i}=1}^{\mathrm{m}}{\mathrm{c}}_{\mathrm{i}}{\mathrm{x}}_{\mathrm{i}}\le \mathrm{C} \\ {\mathrm{x}}_{\mathrm{i}}\in \left\{0,1\right\},\mathrm{i}=1,2,\dots ,\mathrm{m} \end{gathered}$$

(2)

where ${\mathrm{x}}_{\mathrm{i}}$ denotes whether the new project set ${\mathrm{P}}_{\mathrm{i}}^{\prime }$ is selected; it takes the value of 1 if chosen, and 0 otherwise. The set of candidate new projects filtered by capital constraints can be expressed as $\mathrm{X}=\left\{{\mathrm{x}}_1{,\mathrm{x}}_2{,\dots ,\mathrm{x}}_{\mathrm{m}}\right\}$.

• Step 5: Calculate the strategic alignment of each candidate

After obtaining new projects that satisfy the enterprise’s capital constraints, the set of candidate new projects is screened again pursuant to strategic alignment to obtain feasible new projects that can remedy the deviation. Firstly, it is assumed that the new project set ${\mathrm{X}}_{\mathrm{i}}$ is added to the PP to obtain ${\mathrm{PP}}_{\mathrm{i}}$. Then, the contribution of ${\mathrm{PP}}_{\mathrm{i}}$ to the unfilled sub-strategic objective $\mathrm{j}$ is evaluated through the same principle applied in Step 2. Next, in accordance with Step 3, the strategic alignment of ${\mathrm{PP}}_{\mathrm{i}}$ with the sub-strategic objective $\mathrm{j}$ (${\mathrm{SI}}_{\mathrm{ij}})$ can be obtained. ${\mathrm{SI}}_{\mathrm{ij}}<1$ means that ${\mathrm{PP}}_{\mathrm{i}}$ cannot achieve the unfulfilled sub-strategic objective $\mathrm{j}$ and should be eliminated. Conversely, ${\mathrm{SI}}_{\mathrm{ij}}\ge 1$ indicates that ${\mathrm{PP}}_{\mathrm{i}}$ can achieve the unfulfilled sub-strategic objective $\mathrm{j}$, and that the new project set ${\mathrm{X}}_{\mathrm{i}}$ is a feasible solution.

3.3. Phase 3: Determining the Optimal New Projects

The third phase, consisting of two steps, aims to select the optimal new projects among the set of feasible new projects. First, the synergetic relationships between projects in the ${\mathrm{PP}}_{\mathrm{i}}$ are analyzed; second, in light of these synergistic relationships, a model for the selection of new projects is built to simulate the realization of the enterprise’s strategic objectives. By comparing the simulation results of several PPs, the new projects in the PP that can best achieve the strategic objectives are deemed optimal.

• Step 6: Analyze the synergistic relationships between projects

Synergistic relationships between projects are produced by sharing activities [56], which are essential in achieving enterprises’ strategic objectives [57]. This paper focuses on four forms of synergy: information synergy, resource synergy, technology synergy, and function synergy. Information synergy [38,42] represents the degree of sharing of information flow in the transmission and exchange of information between the projects in a PP. It exists in any environment where information flows. Resource synergy [42,58] refers to the degree of sharing of resources generated by sharing manpower, machines, and other material resources between components. Technology synergy is used to illustrate the degree of sharing of technology, and originates from using the same technology across multiple projects. Function synergy is the degree of overlap of project functions, and is conducive to the overall function of the PP. In view of these four synergies, this paper discusses the synergies between projects by analyzing the co-utilization of information, resources, technology, and functions.

The types of information, resources, technologies, and functions related to each project must first be collected. On this basis, these types are summarized and classified to judge the co-utilization relationships between the projects. As shown in Figure 2, if projects share certain types of resources, information, or technologies, they will be clustered together. The connections between them indicate that they have a co-utilization relationship. The black lines represent the original co-utilization relationships within the PP, while the colored lines, such as the green and blue lines, express the co-utilization relationships between new projects and the projects within the PP. Similarly, if projects have the same function, they will be aggregated and wired together. $\mathrm{Xki}$ indicates that project $\mathrm{i}$ requires type $\mathrm{k}$ of $\mathrm{X}(\mathrm{X}=\mathrm{I},\mathrm{R},\mathrm{T},\mathrm{F}).$ For instance, $\mathrm{I}13$ means that project $3$ requires type $1$ of $\mathrm{I}$, while ${\mathrm{I}12}^{\prime }$ indicates that new project $2$ requires type $1$ of $\mathrm{I}$.

• Step 7: Establish the new project selection model

In view of the project co-utilization diagram, the new project selection model is proposed by employing the SD method. Multiple synergistic relationships between projects within the PP can affect the achievement of the enterprise’s strategic objectives. SD, proposed by Forrester, can visualize the synergistic relationships between projects in an understandable and tractable manner. Simultaneously, it can also measure the impact of synergies on the enterprise’s strategic objectives and simulate different schemes (i.e., PPs). Therefore, this study uses this method to establish a model for the selection of new projects considering the synergistic relationships in the PP to explore the value of strategic achievements, and provides guidelines for managers to evaluate new projects.

As there is a complex synergistic relationship between the projects within the PP, adding new projects will break the original synergistic relationship. It is necessary to determine the boundaries of the system when new projects are added to the PP to compensate for the deviation. The implementation mode and the external environment affect the success of the enterprise’s strategic objectives. This study only discusses the impact of the implementation mode of PP. Therefore, the factors included in the system are sub-strategic objectives, synergies, projects, and project elements.

The SD method mainly includes four types of variables: state variables, rate variables, auxiliary variables, and constants. Based on their characteristics and the properties in the new project selection model simulation, these four types of variables are explored in this study. State variables change over time, and they can ultimately determine the state of the system. Since the statuses of sub-strategic objectives and various synergies are affected by time, they are set as state variables. The increment of each sub-strategic objective and the synergies are set as rate variables, reflecting the input speed of the state variables. Auxiliary variables are intermediate variables used to describe the information transfer and conversion between the state and rate variables. Because multiple elements and projects are the basis for generating several synergies, the elements and projects are set as auxiliary variables. Because the contribution of new projects to meeting the sub-strategic objectives is a certain value, it is set as a constant.

In combination with the co-utilization relationships between projects shown in Figure 2, the names and quantities of the rate variables, auxiliary variables, and constants are determined, along with the arrows pointing between variables. Similarly, based on the relationship between the co-utilization relationship and the strategic objectives in Figure 2, the names and quantities of the state variables, the arrows among them, and the other three variables are fixed, as shown in Figure 3.

Figure 3 shows the relationships between the enterprise’s strategic objectives, sub-strategic objectives, synergies, and projects. According to the SBSC, the enterprise’s strategic objectives are divided into seven sub-strategic objectives to analyze the achievement of the enterprise’s strategic objectives more accurately. These sub-strategic objectives are subordinate to the enterprise’s strategic objectives and determine their realization. PP synergy is generated by projects interacting with one another in the PP context. The interaction of information, resources, technology, and functions among the projects in the PP boosts the generation of information synergy, resource synergy, technology synergy, and functional synergy, which promote the achievement of the enterprise’s strategic objectives. Next, this study carries out a quantitative analysis.

The success of the enterprise’s strategy depends on the achievement of each sub-strategic objective. The degree of realization and importance of each sub-strategic objective jointly determine the success of the enterprise’s strategy. In this paper, the varying importance of each sub-strategic objective is given by experts, and it is expressed by the weight w_j. The degree of achievement of the enterprise’s strategic objectives [12] is as follows:

$$RSO={\displaystyle \sum }_{j=1}^{7}RS{O}_{ij}^{\prime }\times w_j$$

(3)

Typically, the achievement of the sub-strategic objectives mainly consists of two aspects: (i) the realization of ${\mathrm{PP}}_{\mathrm{i}}$, and (ii) the strategic realization increment brought by PP synergies. In this paper, the realization of ${\mathrm{PP}}_{\mathrm{i}}$ is indicated by strategic alignment, and the strategic realization increment brought by PP synergies is determined by project co-utilization relationships and expert experience. The realization brought by ${\mathrm{PP}}_{\mathrm{i}}$ itself to sub-strategic objective j is quantitatively denoted by SI_ij. The strategic realization increment brought by PP synergy to sub-strategic objective j is denoted by RSO_ij. The overall realization of the sub-strategic objective j can be expressed as follows:

$$\begin{gathered} {\mathit{RSO}}_{\mathit{ij}}^{\prime }{=\mathit{SI}}_{\mathit{ij}}{+\mathit{RSO}}_{\mathit{ij}} \\ {\mathit{RSO}}_{\mathit{ij}}{=d}_{\mathit{is}}^{{\xi }_{j1}}{+d}_{\mathit{rs}}^{{\xi }_{j2}}{+d}_{\mathit{ts}}^{{\xi }_{j3}}{+d}_{\mathit{fs}}^{{\xi }_{j4}}j=1,2,\dots ,7 \end{gathered}$$

(4)

where ${\mathit{SI}}_{\mathit{ij}}$ is obtained by calculating the strategic alignment in Step 5; $d_{\mathit{is}}^{{\xi }_{j1}}{,d}_{\mathit{rs}}^{{\xi }_{j2}}, d_{\mathit{ts}}^{{\xi }_{j3}}{,\mathrm{and}d}_{\mathit{fs}}^{{\xi }_{j4}}$ represent the strategic realization increments brought by information synergy, resource synergy, technology synergy, and function synergy to the achievement of the sub-strategic objective $j$, respectively; $d_{\mathit{is}}$ is the degree of information synergy, which is determined by the co-utilization of information among projects, while $d_{\mathit{rs}}$, $d_{\mathit{ts}}$, and $d_{\mathit{fs}}$ have analogous meanings. As a power value, $\xi$ represents the nonlinear impact of synergy on the enterprise’s strategic objectives. Wei et al. [59] established a mathematical model to explore project value, in which $\xi$ is a power value that represents the influence of the technology co-utilization relationship on value. In this paper, synergy arises because of some co-utilization relationships between projects. Similarly, this paper sets $\xi$ as a power value to represent the influence of synergistic relationships on sub-strategic objectives.

3.4. Model Validation

The validity of a model indicates the suitability of the model for serving its purpose. To build confidence in the model discussed in this paper, two tests were conducted—namely, the structure verification test, and the extreme conditions test.

The structure verification test checks whether the model structure adequately corresponds to the relevant descriptive knowledge of the real-world system [60,61]. The foundation of the SD model is a certain logical relationship between variables. Therefore, the structure verification test was utilized in this paper to ensure the validity of the model by checking whether the logical relationship between variables is correct. The “Model Check” function of VENSIM DSS was used to test the model structure. A model might need several changes until “Model is OK” is displayed.

The extreme conditions test explores whether the model behaviors in extreme conditions match the behaviors of the real system in the same situations [60,61,62]. Models behave logically in extreme conditions, meaning that a model is robust to extreme inputs [63]. For instance, the achievement of the enterprise’s strategic objectives will decline if the achievement of a sub-strategic objective is very poor. To conduct this test for this model, the extreme conditions of no “Profitability”, “Customer satisfaction”, and “Brand market value” are assumed, and the achievement of the enterprise’s strategic objectives under the aforementioned conditions is analyzed. The results of the model pass the extreme conditions test by showing a downward trend of the achievement of the enterprise’s strategic objectives when the sub-strategic objectives are not achieved. For example, Figure 4 illustrates the result of no “Profitability”. The general condition refers to the situation where the initial value of “Profitability” is not zero. In this case, the achievement of the sub-strategic objective “Profitability” is zero, which further leads to a reduction in the achievement of the enterprise’s strategic objectives. This result illustrates that the model passes the extreme conditions test.

After passing the two model tests above, the validity of the model was proven. The developed model was ultimately determined, and could be utilized in selecting the optimal new projects.

4. Numerical Examples

In this section, numerical examples are presented to validate the applicability of the proposed new project selection procedure. Here, a commercial real estate enterprise—one of the largest of its kind in Xi’an, Shaanxi Province, China—is taken as the example. The enterprise focuses on architectural design and the application of specialty materials, and is presently investing in building a PP containing four projects. The PP is in the preliminary stage, and has been in operation for one year. However, in implementation, force majeure has resulted in the deviation of the enterprise’s strategic objectives from expectations. To solve this problem, the enterprise decided to invest in new projects for the PP to ensure the achievement of these objectives. CNY 3 million has been invested in new projects to engage in PPC. After preliminary screening, seven new candidate projects were chosen. The investment costs of the seven candidates, which are denoted by $P_1^{\prime }$, $P_2^{\prime }$, $P_3^{\prime }$, $P_4^{\prime }$, $P_5^{\prime }$, $P_6^{\prime }$, and $P_7^{\prime }$, respectively, are shown in

Table 3. Project costs (million CNY).

Project	$P_1^{\prime }$	$P_2^{\prime }$	$P_3^{\prime }$	$P_4^{\prime }$	$P_5^{\prime }$	$P_6^{\prime }$	$P_7^{\prime }$
Cost	1.4	1.5	3.2	2	3	2.6	3.5

.

4.1. Phase 1: Identifying Unfulfilled Sub-Strategic Objectives

Phase 1 began with the formation of a team of experts, including high-level executives and professional department managers (i.e., scheduling, process control, and human resources). These managers had a better grasp of the enterprise’s strategic objectives and the PP implementation conditions, and were able to provide a more reasonable evaluation. Each expert was given the list of strategic objective indices (Table 1), and was asked if the list correctly represented the needs and situation of their enterprise. After discussions, they confirmed that the list was appropriate and that adding or removing indices was not necessary. Next, each expert was required to evaluate the enterprise’s minimum requirements for sub-strategic objectives and the contributions of the PP to meeting the sub-strategic objectives. The linguistic terms “indifferent”, “average”, “good”, and “excellent” were used. The following set of evaluation grades was defined:

$$\mathrm{H}=\left\{\mathrm{indifferent}\right.\left({\mathrm{H}}_1\right),\mathrm{average}\left({\mathrm{H}}_2\right),\mathrm{good}\left({\mathrm{H}}_3\right),\left.\mathrm{excellent}\left({\mathrm{H}}_4\right)\right\}$$

The utility of each grade is given as follows.

$$U\left(H_1\right)=0.1,U\left(H_2\right)=0.55,U\left(H_3\right)=0.65,U\left(H_{14}\right)=0.95$$

Then, a meeting was held, and a unanimous consensus (

Table 4. The contributions of the PP to meeting the sub-strategic objectives.

Sub-Strategic Objectives	Index Factors	Minimum Strategic Requirements	The Contribution of PP to Meeting the Sub-Strategic Objectives
$\mathrm{Profitability}(S_1$)	$\mathrm{Increase}\mathrm{profits}(S_{11}$)	B	A
	$\mathrm{Mitigate}\cos t(S_{12}$)	B	A
$\mathrm{Customer}\mathrm{satisfaction}(S_2$)	$\mathrm{Predict}\mathrm{customer}\mathrm{preference}(S_{21}$)	A	B
	$\mathrm{Offer}\mathrm{high}\mathrm{quality}\mathrm{of}\mathrm{services}(S_{22}$)	B	B
	$\mathrm{Shortened}\mathrm{order}\mathrm{processing}\mathrm{time}(S_{23}$)	B	C
$\mathrm{Brand}\mathrm{market}\mathrm{value}(S_3$)	$\mathrm{Expand}\mathrm{market}\mathrm{share}(S_{31}$)	A	B
	$\mathrm{Improve}\mathrm{brand}\prime s\mathrm{value}(S_{32}$)	B	C
$\mathrm{Management}\mathrm{maturity}(S_4$)	$\mathrm{Establish}a\mathrm{standardized}\mathrm{management}\mathrm{system}(S_{41}$)	C	C
	$\mathrm{Creation}\mathrm{of}\mathrm{PM}\mathrm{manuals}(S_{42}$)	B	B
	$\mathrm{Establish}a\mathrm{management}\mathrm{information}\mathrm{platform}(S_{43}$)	A	B
$\mathrm{Manufacturer}\mathrm{development}\mathrm{and}\mathrm{innovation}(S_5$)	$\mathrm{Improve}\mathrm{efficiency}\mathrm{of}\mathrm{productivity}(S_{51}$)	B	B
	$\mathrm{Shorten}\mathrm{lead}\mathrm{time}(S_{52}$)	C	B
	$\mathrm{Improve}\mathrm{quality}\mathrm{of}\mathrm{products}(S_{53}$)	B	A
	$\mathrm{Product}\mathrm{development}(S_{54}$)	B	A
Employees $\mathrm{development}\mathrm{and}\mathrm{innovation}(S_6$)	$\mathrm{Increase}\mathrm{employees}\prime \mathrm{satisfaction}(S_{61}$)	C	B
	$\mathrm{Enhance}\mathrm{employees}\prime \mathrm{ethics}(S_{62}$)	B	C
	$\mathrm{Increase}\mathrm{knowledge}\mathrm{and}\mathrm{skills}\mathrm{of}\mathrm{employees}(S_{63}$)	B	C
	$\mathrm{Increase}\mathrm{employees}\prime \mathrm{acceptance}\mathrm{of}\mathrm{corporate}\mathrm{culture}(S_{64}$)	A	B
$\mathrm{Organization}\mathrm{contribution}(S_7$)	$\mathrm{Provision}\mathrm{of}\mathrm{social}\mathrm{welfare}(S_{71}$)	B	B
	$\mathrm{Human}\mathrm{resource}\mathrm{management}(S_{72}$)	C	B
	$\mathrm{Environmental}\mathrm{protection}(S_{73}$)	A	B

) was reached through collective discussions.

Following the ER method [54], linguistic terms related to the enterprise and the PP were converted into the value of minimum strategic requirements and the value of the PP’s contribution to meeting the enterprise’s strategic objectives. Then, the strategic alignment of the PP was calculated based on Equation (1). As shown in

Table 5. The values of portfolio strategic alignment.

Sub-Strategic Objectives	${\mathit{S}}_1$	${\mathit{S}}_2$	${\mathit{S}}_3$	${\mathit{S}}_4$	${\mathit{S}}_5$	${\mathit{S}}_6$	${\mathit{S}}_7$
The value of the PP’s contribution to meeting the enterprise’s strategic objectives	0.750	0.693	0.650	0.767	0.711	0.65	0.833
The value of minimum strategic requirements	0.750	0.821	0.875	0.767	0.711	0.762	0.767
Strategic alignment	1	0.844	0.743	1	1	0.853	1.086

, the values of $S_2$ (customer satisfaction), $S_3$ (brand market value), and $S_6$ (employees’ development and innovation) were less than 1, meaning that they were identified as unfulfilled sub-strategic objectives in light of the criteria in Section 3.1.

4.2. Phase 2: Obtaining the Set of Feasible New Projects

The set of feasible new projects that can achieve the unfulfilled sub-strategic objectives $S_2$, $S_3$, and $S_6$ was obtained through two screening processes. First, based on the project cost (Table 3) and enterprise total capital, candidate new projects were prescreened as follows:

$$\begin{gathered} {\displaystyle \sum }_{i=1}^7{c}_i{x}_i\le 3 \\ {x}_i\in \left\{0,1\right\},i=1,2,\dots ,7 \end{gathered}$$

(5)

Because $P_3^{\prime }$ and $P_7^{\prime }$ dissatisfy the capital constraint, they were eliminated, and only one new project could be selected to add to the PP pursuant to this constraint. The initial solution set $X_1$ = $\left\{x_1\right\}$, $X_2$ = $\left\{x_2\right\}$, $X_4$ = $\left\{x_4\right\}$, $X_5$ = $\left\{x_5\right\}$, $X_6$ = $\left\{x_6\right\}$ was obtained.

Then, assuming that new projects that satisfy the capital constraint are separately added to the PP, there are five different PPs (

Table 6. The changed project portfolio.

Project portfolio	${\mathit{PP}}_1$	${\mathit{PP}}_2$	${\mathit{PP}}_3$	${\mathit{PP}}_4$	${\mathit{PP}}_5$
New projects contained	$P_1^{\prime }$	$P_2^{\prime }$	$P_5^{\prime }$	$P_4^{\prime }$	$P_6^{\prime }$

). The experts (the same experts engaged in the previous steps) were asked to assess the five PPs in light of Steps 2 and 3 in Section 3.1. The strategic alignment of the five PPs was calculated, and the calculation results are shown in

Table 7. Strategic alignment of the project portfolio.

	${\mathit{PP}}_1$	${\mathit{PP}}_2$	${\mathit{PP}}_3$	${\mathit{PP}}_4$	${\mathit{PP}}_5$
$S_1$	0.867	1.100	0.867	1.000	1.167
$S_2$	0.844	1.000	0.934	1.061	1.131
$S_3$	0.743	1.143	0.857	1.143	1.000
$S_4$	0.767	1.001	1.000	1.000	0.903
$S_5$	0.711	1.071	1.283	1.000	1.179
$S_6$	0.919	1.100	0.919	1.100	1.048
$S_7$	0.924	1.136	0.903	1.100	0.884

. The strategic alignment results for $S_2$, $S_3$, and $S_6$ of ${\mathit{PP}}_1$ were all less than 1, as was that of ${\mathit{PP}}_4$. These findings indicate that ${\mathit{PP}}_1$ and ${\mathit{PP}}_3$ cannot simultaneously realize $S_2$, $S_3,$ and $S_6$. Thus, ${\mathit{PP}}_1$ and ${\mathit{PP}}_3$ were excluded, and the feasible new projects were $P_2^{\prime }$, $P_4^{\prime }$, and $P_6^{\prime }$.

4.3. Phase 3: Determining the Optimal New Projects

As stated in Section 3.3, the project co-utilization diagram is portrayed pursuant to the co-utilization relationships between projects within the PP. There are three types of information, four types of resources, four types of technologies, and four types of functions. Based on the analysis of using the same types of information, resources, and technologies, and having the same functional attributes between projects, the project co-utilization diagram can be obtained, as shown in Figure 5.

Figure 5 depicts the relationships between projects, along with their impact on strategic objectives. Combined with the elements in Figure 5, the new project selection model (Figure 3) is used to select new projects in light of the set of variables and equations in Step 7.

During the implementation of the PP, deviation from the enterprise’s strategic objectives occurs from time to time. Based on the adoption of the annual review cycle to monitor and review the implementation of the PP every year, the achievement of the enterprise’s strategic objectives is checked every 1–2 years. By inputting the initial values obtained in Table 6 into the model, the results are calculated through VENSIM DSS. In Figure 6, the horizontal axis represents the simulation time, while the vertical axis represents the achievement of the enterprise’s strategic objectives.

According to Figure 6, the simulation results of the three PPs are greater than 1 in the period of 1–2 years, indicating that the deviation between the PP and the enterprise’s strategic objectives has been effectively remedied after the addition of the new project. However, in the simulation results of the three PPs, a discrepancy appears over time. The reason for this is that the synergistic relationships are distinct due to the different new project added, leading to differences in the contribution of the synergistic relationships to achieving the enterprise’s strategic objectives. Clearly, ${\mathit{PP}}_4$ achieves the enterprise’s strategic objectives to the greatest extent, followed by ${\mathit{PP}}_5$ and, finally, ${\mathit{PP}}_2$. Thus, the optimal PP is ${\mathit{PP}}_4$, and the optimal new project is $P_4^{\prime }$.

5. Discussion

A PP may deviate from its enterprise’s strategic objectives, further leading to the failure of the enterprise’s strategy. Especially under the impact of the COVID-19 pandemic, many construction projects have been suspended due to the lack of timely supply of personnel and materials, which has greatly deviated from the expected objective. To help solve the problem of PP deviation, this paper proposes a three-phase procedure for the selection of new projects. The procedure combines strategic alignment theory and the SD method and considers the synergistic relationships in the PP, enriching the PPC research. Additionally, it provides a tool for managers to achieve their enterprises’ strategic objectives.

5.1. Research Implications

The addition of new projects can help solve the problem of PP deviation. However, current PP research mainly focuses on PP selection [64,65,66] and the adjustment of troubled projects [67]. There is less research on how to add new projects to pursue PPC. As a result, new project selection methods have been lacking. This paper proposes a three-phase procedure for the selection of new projects to provide guidelines for solving PP deviation. Additionally, it extends the existing PPC theory in two ways:

(1)

Strategic alignment theory is applied to identify the deviation between a PP and an enterprise’s strategic objectives. This provides a foundation for the selection of new projects. Only by analyzing the deviation as accurately as possible can we select the optimal new projects from multiple options to remedy deviation. However, there are few methods for clarifying deviation. Strategic alignment theory, which is commonly perceived to be effective for PP selection [68,69,70], is a feasible methodology. However, how strategic alignment can be utilized to analyze PP deviation is unclear. This study illustrates how we can quantify PP strategic alignment to determine whether a PP is consistent with its enterprise’s strategic objectives. The result can be applied to judge whether new projects can compensate for deviation, thereby providing insights for selecting new feasible projects.

As the scale of construction enterprises has gradually changed, it has become the new normal for them to implement and manage multiple construction projects at the same time. A construction project is often divided into multiple unit projects, single projects, and sub-projects in the implementation process. The simultaneous implementation of these disaggregated projects (referred to as sub-projects in this paper) will form a PP (multi-project management model) that covers all parent projects and supports the achievement of the construction enterprise’s strategic objectives. Due to the long period, many procedures, and complex management of construction PPs, how to monitor the implementation of construction PPs and grasp the deviation in a timely manner is a problem faced by construction enterprises. The deviation analysis by strategic alignment provides a different idea for researching the PP management of construction enterprises. The research object of the numerical example of this study is a construction PP, and effectively verifies that the strategic alignment can identify the deviation.

(2)

The introduction of synergy provides a new idea for new project selection research. Synergy is a unique attribute of a PP compared with a single project, and it greatly impacts enterprises’ strategic objectives. The addition of new projects inevitably changes the synergistic relationships between projects, affecting the achievement of the enterprise’s strategic objectives. Especially for construction PPs, the integrated management of the disaggregated project (regarded as a sub-project in this paper) leads to intricate synergies in terms of materials, technology, personnel, capital, etc. Adding new projects inevitably brings great changes to the synergistic relationships within the PP. Therefore, consideration of synergy is essential for decisions on the selection of new projects. However, current research on the selection of new projects merely discusses the characteristics of the new projects themselves, and omits the synergistic relationships between new projects and the PP in the process of evaluating the new projects [12,71]. This study qualitatively analyzes the synergy between new projects and the existing projects within the PP, and quantifies its contribution to achieving the enterprise’s strategic objectives. The procedure presented in this study is conducive to fully considering the contributions of new projects to minimizing deviation.

For a construction PP, due to their long implementation cycle, the inclusion of many subjects, and intricate processes, consideration of the synergistic relationships between new projects and the existing projects within the PP is conducive to avoiding conflicts caused by resources and scheduling in the subsequent implementation. The introduction of synergy provides a new research direction for construction PP management.

5.2. Managerial Implications

Owing to the complex synergistic relationships within a PP, deviation in one project can affect the rest of the PP, exacerbating the seriousness of the problem. Under a fiercely competitive environment, significant deviation may affect an enterprise’s strategic layout and even threaten its survival. Under the impact of the COVID-19 pandemic, the development of the construction industry is facing the dilemma that construction PPs deviate from enterprises’ strategic objectives owing to the interruption and delay of their implementation. Therefore, there is an urgent need to solve the problem that occurs when a PP deviates from an enterprise’s strategic objectives. In this paper, the procedure of adding new projects was used to carry out in-depth research on the problem of PP deviation, which has certain management significance.

(1)

The application of strategic alignment proposed in this study provides a practical method for managers to judge whether a PP deviates from the enterprise’s strategic objectives. Managers have many methods and tools for building a satisfactory PP, but schemes for evaluating PPs’ implementation are still lacking. It is essential for PP management to analyze PP deviation in implementation. Strategic alignment is used in this paper to determine whether the PP is operated as planned, so as to keep track of its progress. The calculated result of PP strategic alignment can be viewed as a signal of deviation, highlighting which part(s) of the enterprise’s strategic objectives deviate(s), and can facilitate managers in undertaking targeted remedial measures as soon as possible.

Currently, construction enterprises urgently need this method to manage PPs effectively. The implementation of construction PPs is highly affected by the external environment. The turbulence of the external environment can interrupt or delay the PP implementation, resulting in the deviation of the PP from the enterprise’s strategic objectives. Managers can regularly monitor the implementation of a construction PP by calculating the strategic alignment of each sub-strategic objective. The analysis of the calculated results can grasp the achievement of the enterprise’s strategic objectives and clarify the deviation, providing a reference for managers to carry out subsequent remedial measures.

(2)

The new project selection procedure provides an effective tool for managers to solve the problem of PPs’ deviation from the enterprise’s strategic objectives. When deviation occurs, adding new projects is a significant remedial measure, and managers are faced with the dilemma of how to select from multiple possible new projects to compensate for deviation. The new project selection procedure proposed in this study takes whether candidate new projects can compensate for the deviation as the selection criterion. By utilizing this procedure, the alignment between new projects and strategies, the capital constraints of the enterprise, and the synergy between new projects and the PP can be considered simultaneously to screen out feasible and optimal new projects that can best compensate for the deviation to improve management efficiency.

Particularly for construction enterprises, the implementation of PPs is inevitably impacted by the COVID-19 pandemic, leading to severe project delays, which causes great deviation of the PP from the enterprise’s strategic objective. This procedure alleviates the crisis faced by construction enterprises to a certain extent. When the deviation occurs, the manager can use this procedure to quickly evaluate multiple alternative construction projects in the face of limited enterprise capital, preventing the continued spread of deviations. The new project selection procedure can effectively reduce the management pressure of construction enterprises.

6. Conclusions

For many industries, including the construction industry, in the past three years, the PP interruptions or delays caused by the uncertainty of the external environment have led to many deviations from enterprises’ strategic objectives. To implement organizational strategy and strengthen an organization’s competitive advantage, managers must pay attention to the divergence between the PP and the enterprise’s strategic objectives, and implement remedial measures if necessary.

Adding new projects can be an effective remedy. To help select new projects to remedy the deviation between the PP and the enterprise’s strategic objectives, this paper proposes a three-phase procedure considering the synergistic relationships in the PP. In the first phase, the deviation between the PP and the enterprise’s strategic objectives is analyzed by calculating the strategic alignment. Then, in the second phase, candidate new projects are screened twice through capital constraints and strategic alignment to identify a set of feasible new projects. In the third phase, by analyzing the synergistic relationships in the PP, a model of new project selection is established and used to determine the optimal new projects. To validate the practicability and effectiveness of this procedure, a numerical example of building and real estate is provided. The results show that adding new projects can compensate for deviation. Compared with the previous research on construction projects focused on the internal aspects of a single project, this paper studies the effects evaluation and remedial measures during the PP implementation from the perspective of synergy under the background of multiple projects in construction enterprises. This procedure is conducive to promoting the achievement of construction enterprises’ strategic objectives, and provides new ideas for construction project management. In sum, this study extends existing research on PPC, and offers managerial insights into the practice of PP management.