Search results

The purpose of this paper is to investigate the key productivity constraints faced by New Zealand (NZ) road pavement maintenance and rehabilitation contractors (RPMRCs) and the associated mitigation measures.

Interview-based exploratory research strategy was used to survey senior managers and directors of medium- to large-sized road contracting firms in NZ. Empirical data were analyzed using the multi-attribute analytical technique.

Results revealed 70 productivity constraints faced by the RPMRCs in NZ; in diminishing order of influence, these constraints were aggregated into eight broad categories as follows: finance, workforce, technology/process, statutory/regulatory compliance, project characteristics, project management/project team characteristics, unforeseen circumstances and other/external factors. The most important constraints in each of the eight broad categories were presented.

The key limitation of the research is that it was based on feedback from a limited number of participants which were less than the minimum required to represent the views of the potential participants in the sampling frame for the study. As a result, the findings may not be reliably generalized beyond the scope of the data used. Further research on the subject is recommended to ensure that the representation of the views of the individuals and companies that comprised the sampling frame is achieved. The current findings could be formulated as propositions or hypotheses to be tested in future confirmatory research.

At the industry level, the findings could provide the basis for the skill development programs of the NZ RPMRCs. The application of the research findings by the RPMRCs and consultants could result in significant improvement in the productivity of the NZ roading sector and the sector’s enhanced contribution to the economy.

Currently, there is little research on the priority constraints to productivity and performance in the NZ roading sector. The findings contribute to knowledge by revealing critical factors constraining productivity performance of the NZ RMRCs and the associated improvement measures. New and more enriching viewpoints were provided on how contractors could leverage their limited resources to address the identified key constraints.

Highway projects in India have a history of cost overruns and delay in project delivery, thus incurring huge losses to public funds. The study aimed to measure the extent of influence of various constraints on the overall success of highway projects (e.g. National highway project, state highway projects and major district roads). Based on the literature, various factors were grouped under three categories (a) Project Constraints, (b) Project Governance Constraints and (c) Stakeholder Induced Constraints.

A quantitative approach was adopted. A questionnaire-based survey was conducted with 435 respondents from the field of highway projects with a minimum experience of 1 year as Project Manager. The data was analyzed by partial least squares structural equation modeling technique.

It was identified that the impact of project constraints (ES = 0.313) on project success is more than that of project governance constraints (ES = 0.231) and stakeholder induced constraints. Additionally, it was found that project governance constraints have a strong impact on project constraints (ES = 0.535) and stakeholder induced constraints (ES = 0.403).

The study presented in this paper is first of its kind to measure and articulate the impact of project governance constraint, project constraint and stakeholder induced constraints on project success.

The purpose of this research is to quantify the effect of stakeholder conflicts on project constraints in the construction industry using ordinal regression analysis. For this purpose, the most significant project constraints and factors that cause stakeholder conflicts found in the literature are measured.

Factors causing stakeholder conflicts and project constraints are extracted through a content analysis of the published literature. Further, a questionnaire survey is conducted involving 170 professionals to assess the effect of conflicts on project constraints. Finally, to obtain a more objective assessment, a statistical model is developed, and to highlight the most severe factors causing conflict and impacting project constraints, ordinal regression analysis is performed.

The results show that in the construction industry, all project constraints are affected by stakeholder conflicts. Factors that result in stakeholder conflicts indicated a positive relationship with cost, time and resources. This means that any increase or decrease in the effect of stakeholder conflicts will directly influence these three project constraints. Similarly, a negative relationship was observed between stakeholder conflicts and quality, workforce productivity, protection of environment and safety regulations in the construction industry, indicating that increase in the effect of stakeholder conflicts will decrease these four project constraints and vice versa. The results for cumulative ordinal regression model highlight that lack of communication, poor quality of completed works and change orders and rework have intense effects on project constraints collectively.

A small number of studies have been undertaken to examine the emergence of project constraints in the developing countries. And even more, its relationship with stakeholder conflicts in the construction industry is limited. This research highlights the most significant project constraints and factors that result in stakeholder conflicts in the construction industry. Therefore, this study adds to the existing body of knowledge by developing an ordinal regression model that will help decision-makers and top management control this enigma of stakeholder conflicts in the construction industry.

The purpose of this paper is to present a methodology for extracting innovation constraints from building projects through stakeholder management competencies and failure mode and effect analysis (FMEA).

The methodology was an iterative grounded theory process using case studies. A literature‐based concept model was generated which mapped project procurement stages against the innovation process. Constraints and stakeholder management strategies were extracted from 30 case studies using content analysis and mapped against the procurement stages. FMEA was used to evaluate the criticality of the constraints. For the purposes of this paper, a sample case study was detailed and referred to as the pilot study. The m\ethodology was applied to all the case studies and a schedule of constraints (SoC) extracted.

This paper evidenced that it is not project constraints which require management to sustain innovation but rather failures in stakeholder competency. This study established the benefits of FMEA as a risk assessment tool for construction innovation research and generated a database of innovation constraints which can be used as a benchmarking framework for future research.

Previous construction innovation research has focused on established project management techniques to manage innovation. This study identified that rather than a process‐driven approach, a stakeholder‐centred approach is required, where successful innovation delivery is incumbent on the right stakeholder competencies being in place at the appropriate stages of the procurement process. The benefit of this contribution is an established risk assessment methodology which can be used by project stakeholders when adopting innovation into construction projects.

The purpose of this paper is cost optimization of project schedules under constrained resources and alternative production processes (APPs).

The model contains a cost objective function, generalized precedence relationship constraints, activity duration and start time constraints, lag/lead time constraints, execution mode (EM) constraints, project duration constraints, working time unit assignment constraints and resource constraints. The mixed-integer nonlinear programming (MINLP) superstructure of discrete solutions covers time–cost–resource options related to various EMs for project activities as well as variants for production process implementation.

The proposed model provides the exact optimal output data for project management, such as network diagrams, Gantt charts, histograms and S-curves. In contrast to classic scheduling approaches, here the optimal project structure is obtained as a model-endogenous decision. The project planner is thus enabled to achieve optimization of the production process simultaneously with resource-constrained scheduling of activities in discrete time units and at a minimum total cost.

A set of application examples are addressed on an actual construction project to display the advantages of proposed model.

The unique value this paper contributes to the body of knowledge reflects through the proposed MINLP model, which is capable of performing the exact cost optimization of production process (where presence and number of activities including their mutual relations are dealt as feasible alternatives, meaning not as fixed parameters) simultaneously with the associated resource-constrained project scheduling, whereby that is achieved within a uniform procedure.

In repetitive projects, repetition offers more possibilities for activity scheduling at the sub-activity level. However, existing resource-constrained repetitive scheduling problem (RCRSP) models assume that there is only one sequence in performing the sub-activities of each activity, resulting in an inefficient resource allocation. This paper proposes a novel repetitive scheduling model for solving RCRSP with soft logic.

In this paper, a constraint programming model is developed to solve the RCRSP using soft logic, aiming at the possible relationship between parallel execution, orderly execution or partial parallel and partial orderly execution of different sub activities of the same activity in repetitive projects. The proposed model integrated crew assignment strategies and allowed continuous or fragmented execution.

When solving RCRSP, it is necessary to take soft logic into account. If managers only consider the fixed logic between sub-activities, they are likely to develop a delayed schedule. The practicality and effectiveness of the model were verified by a housing project based on eight different scenarios. The results showed that the constraint programming model outperformed its equivalent mathematical model in terms of solving speed and solution quality.

Available studies assume a fixed logic between sub-activities of the same activity in repetitive projects. However, there is no fixed construction sequence between sub-activities for some projects, e.g. hotel renovation projects. Therefore, this paper considers the soft logic relationship between sub-activities and investigates how to make the objective optimal without violating the resource availability constraint.

Construction firms keep minimal resources to maintain productive working capital. Hence, resources are constrained and have to be shared among multiple projects in an organization. Optimal allocation of resources is a key challenge in such situations. Several approaches and heuristics have been proposed for this task. The purpose of this paper is to compare two approaches for multi-mode resource-constrained project scheduling in a multi-project environment. These are the single-project approach (portfolio optimization) and the multi-project approach (each project is optimized individually, and then heuristic rules are used to satisfy the portfolio constraint).

A direct search algorithm called Probabilistic Global Search Lausanne is used for schedule optimization. Multiple solutions are generated that achieve different trade-offs among the three criteria, namely, time, cost and quality. Good compromise solutions among these are identified using a multi-criteria decision making method, Relaxed Restricted Pareto Version 4. The solutions obtained using the single-project and multi-project approaches are compared in order to evaluate their advantages and disadvantages. Data from two sources are used for the evaluation: modified multi-mode resource-constrained project scheduling problem data sets from the project scheduling problem library (PSPLIB) and three real case study projects in India.

Computational results prove the superiority of the single-project approach over heuristic priority rules (multi-project approach). The single-project approach identifies better solutions compared to the multi-project approach. However, the multi-project approach involves fewer optimization variables and is faster in execution.

It is feasible to adopt the single-project approach in practice; realistic resource constraints can be incorporated in a multi-objective optimization formulation; and good compromise solutions that achieve acceptable trade-offs among the conflicting objectives can be identified.

An integer programming model was developed in this research to optimize the multiple objectives in a multi-project environment considering explicit resource constraints and maximum daily costs constraints. This model was used to compare the performance of the two multi-project environment approaches. Unlike existing work in this area, the model used to predict the quality of activity execution modes is based on data collected from real construction projects.

This paper proposes an innovative intelligent simulation-based construction planning framework that introduces a new approach to simulation-based construction planning.

In this approach, the authors developed an ontological inference engine as an integrated part of a constraint-based simulation system that configures the construction processes, defines activities and manages resources considering a variety of requirements and constraints during the simulation. It allows for the incorporation of the latest project information and a deep level of construction planning knowledge in the planning. The construction planning knowledge is represented by an ontology and several semantic rules. Also, the proposed framework uses the project building information model (BIM) to extract information regarding the construction product and the relations between elements. The extracted information is then converted to an ontological format to be useable by the framework.

The authors implemented the framework in a case study project and tested its usefulness and capabilities. It successfully generated the construction processes, activities and required resources based on the construction product, available resources and the planning rules. It also allowed for a variety of analyses regarding different construction strategies and resource planning. Moreover, 4D BIM models that provide a very good understanding of the construction plan can be automatically generated using the proposed framework.

The active integration between BIM, discrete-event simulation (DES) and ontological knowledge base and inference engine defines a new class of construction simulation with expandable applications.

The purpose of this paper is to explore the benefits of integrating the theory of constraints (TOC), resources-based theory (RBT), resource advantage theory (RAT), with a structured project-based methodology e.g., Project Management Body of Knowledge. This paper describes each theory and explores what benefits a unified model would bring to project management. This paper represents the conceptual development of an integrated framework that will be tested in a range of project management scenarios in various industrial sectors.

Extant literature is used to develop a conceptual framework of an integrated model that will be tested in the field for robustness. The model has been applied to published projects to identify its strengths and weaknesses.

The work shows important implications for improved success of projects from the use of TOC, RAT and resource dependence theory (RDT). Specifically, it emphasizes the need for application of strategic theories to project management.

While TOC, RAT and RDT are well established in the context of organization theory, there is limited application in project management. Moreover, the model has yet to be applied in the field. The hypotheses identified in this research are currently being tested using field-based surveys.

The research falls short in addressing some resources, e.g. innovation, tacit knowledge and decision making methods in traditional project management context. Therefore, identifying these critical resources in future work and exploiting them as the means of improving project performance would enhance the success of project-based management.

Project management is an emergent discipline and a project is temporary in nature. Therefore, new ideas and development of theories for project management practices are required. This innovative research, for example, may change the way projects are executed in future.

This paper examines the components of a successful project according to the iron triangle, i.e. scope, quality, time and cost. However, through the application of TOC, RAT and RDT into an integrated project-based management framework gives new insights to resources management.

The purpose of this research is to develop a time-cost optimization model to schedule repetitive projects while considering limited resource availability.

The model is based on the constraint programming (CP) framework; it integrates multiple scheduling characteristics of repetitive activities such as continuous or fragmented execution, atypical activities and coexistence of different modes in an activity. To improve project performance while avoiding inefficient hiring and firing conditions, the strategy of bidirectional acceleration is presented and implemented, which requires keeping regular changes in the execution modes between successive subactivities in the same activity.

Two case studies involving a real residential building construction project and a hotel refurbishing project are used to demonstrate the application of the proposed model based on four different scenarios. The results show that (1) the CP model has great advantages in terms of solving speed and solution quality than its equivalent mathematical model, (2) higher project performance can be obtained compared to using previously developed models and (3) the model can be easily replicated or even modified to enable multicrew implementation.

The original contribution of this research is presenting a novel CP-based repetitive scheduling optimization model to solve the multimode resource-constrained time-cost tradeoff problem of repetitive projects. The model has the capability of minimizing the project total cost that is composed of direct costs, indirect costs, early completion incentives and late completion penalties.