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This paper aims to present a new method to circumvent the limitations of current schedule compression methods which reduce schedule crashing to the traditional time-cost trade-off analysis, where only cost is considered.

The schedule compression process is modeled as a multi-attributed decision making problem in which different factors contribute to priority setting for activity crashing. For this purpose, a modified format of the Multiple Binary Decision Method (MBDM) along with iterative crashing process is utilized. The method is implemented in MATLAB, with a dynamic link to MS-Project to facilitate the needed iterative rescheduling. To demonstrate the use of the developed method and to present its capabilities, a numerical example drawn from literature was analysed.

When considering cost only, the generated results were in good agreement with those generated using the harmony search (HS) method, particularly in capturing the project least-cost duration. However, when other factors in addition to cost were considered, as expected, different project least-cost and associated durations were obtained.

The developed method is not applicable, in its present formulation, to what is known as “linear projects” such as construction of highways and pipeline infrastructure projects which exhibit high degree of repetitive construction.

The novelty of the developed method lies in its capacity to allow for the consideration of a number of factors in addition to cost in performing schedule compression. Also through its allowance for possible variations in the relative importance of these factors at the individual activity level, it provides contractors with flexibility to consider a number of compression execution plans and identifies the most suitable plan. Accordingly, it enables the integration of contractors' judgment and experience in the crashing process and permits consideration of different project environments and constraints.

Most projects are facing delays, and accelerating the pace of project progress is a necessity. Project managers are responsible for completing the project on time with minimum cost and with maximum quality. This study provides a trade-off between time, cost, and quality objectives to optimize project scheduling.

The current paper presents a new resource-constrained multi-mode time–cost–quality trade-off project scheduling model with lags under finish-to-start relations. To be more realistic, crashing and overlapping techniques are utilized. To handle uncertainty, which is a source of project complexity, interval-valued fuzzy sets are adopted on several parameters. In addition, a new hybrid solution approach is developed to cope with interval-valued fuzzy mathematical model that is based on different alpha-levels and compensatory methods. To find the compatible solution among conflicting objectives, an arithmetical average method is provided as a compensatory approach.

The interval-valued fuzzy sets approach proposed in this paper is denoted to be scalable, efficient, generalizable and practical in project environments. The results demonstrated that the crashing and overlapping techniques improve time–cost–quality trade-off project scheduling model. Also, interval-valued fuzzy sets can properly manage expressions of the uncertainty of projects which are realistic and practical. The proposed mathematical model is validated by solving a medium-sized dataset an adopted case study. In addition, with a sensitivity analysis approach, the solutions are compared and the model performance is confirmed.

This paper introduces a new continuous-based, resource-constrained, and multi-mode model with crashing and overlapping techniques simultaneously. In addition, a new hybrid compensatory solution approach is extended based on different alpha-levels to handle interval-valued fuzzy multi-objective mathematical model of project scheduling with influential uncertain parameters.

This paper aims to investigate the economic consequence of the tax reductive strategy on stock price. The authors’ theory, empirically reinforced, suggests managerial tax aggressiveness endangers the corporation through a heightened risk in stock price crashing. Information opacity worsens the situation by reinforcing the relationship. Policymakers should emphasize two aspects: market openness and tighter institutional monitoring. The evidence shown in this paper demonstrates that these two weaken the tax aggressiveness impact on risk of a crashing stock price.

The sample in this paper consists of 9,702 observations from listed firms from 2008 to 2013 in China. The tax rate is manually collected and all the other original data used in this study are sourced from Wind and China Capital Market and Accounting Research databases. Both logistic regression and ordinary least squares regression methods are used to test the hypothesis in this paper.

One key insight is in tax aggressiveness to be strongly correlated with a greater risk of future stock price crashing. The authors also found information opacity to exert a positive moderating effect. That is, the higher the information opacity, the stronger and more positive the correlation between tax aggression and stock price crash risk. However, the market process and an institutional investor have opposite, negative impacts. An open market environment reduces their correlativeness. Similarly, stronger institutional vigilance leads to an attenuation of such a co-relationship.

The findings of this paper have wide policy implications for management and control by authorities of listed corporations. Aggressiveness in management of corporate taxes accentuates the risks borne by stockholders. If so, internally within the corporation, such aggression shown by management, if not proscribed, could be subject to scrutiny, possibly by an independent committee. Externally, this may be countered by the authority in emphasizing three key factors: openness in information sharing, the market environment and tighter institutional monitoring.

This study provides a consequential theory of aggressive management of tax, rigorously analyzed and strongly, empirically supported. Overall, aggressiveness in tax management is related with assumption of higher risks in the crashing of stock price. The relationship is enhanced through information opacity, but reduced via market environment and institutional monitoring.

Exact solution of time–cost trade-off problem (TCTP) by the state-of-the-art meta-heuristic algorithms can be obtained for small- and medium-scale problems, while satisfactory results cannot be obtained for large construction projects. In this study, a hybrid heuristic meta-heuristic algorithm that adapts the search domain is developed to solve the large-scale discrete TCTP more efficiently.

Minimum cost slope–based heuristic network analysis algorithm (NAA), which eliminates the unfeasible search domain, is embedded into differential evolution meta-heuristic algorithm. Heuristic NAA narrows the search domain at the initial phase of the optimization. Moreover, activities with float durations higher than the predetermined threshold value are eliminated and then the meta-heuristic algorithm starts and searches the global optimum through the narrowed search space. However, narrowing the search space may increase the probability of obtaining a local optimum. Therefore, adaptive search domain approach is employed to make reintroduction of the eliminated activities to the design variable set possible, which reduces the possibility of converging into local minima.

The developed algorithm is compared with plain meta-heuristic algorithm with two separate analyses. In the first analysis, both algorithms have the same computational demand, and in the latter analysis, the meta-heuristic algorithm has fivefold computational demand. The tests on case study problems reveal that the developed algorithm presents lower total project costs according to the dependent t-test for paired samples with α = 0.0005.

In this study, TCTP is solved without considering quality or restrictions on the resources.

The proposed method enables to adapt the number of parameters, that is, the search domain and provides the opportunity of obtaining significant improvements on the meta-heuristic algorithms for other engineering optimization problems, which is the theoretical contribution of this study. The proposed approach reduces the total construction cost of the large-scale projects, which can be the practical benefit of this study.

The purpose of this paper is to examine projects crashing based on the factors including cost, time, quality, risk and the law of diminishing returns.

The paper first investigated effective factors on project crashing then proposed a grey linear programming model. In the proposed grey linear programming model, the costs of quality of works that include the cost of conformance and non-conformance of deliverables in the project were studied. The results are presented for considering the existing uncertainties using positioned programming under the sensitivity analysis table and graphs.

The lack of consideration of project risks will reduce the project success probability in future. The proposed model reduces the existing uncertainties to a significant extent by covering the project risks completely. Based on the law of diminishing returns, after a certain point technically known as saturation point, the increase of resources does not lead to the reduction of time and may even have negative impacts. Finding the saturation point for each activity prevents the excessive allocation of resources that can lead to reduction of productivity.

The main duty of each project manager is finishing the project in the framework of the determined objectives. In most of the cases, after the preparation of the initial project schedule by the project team, it is seen that there is a need for the time reduction. This study has used a grey linear programming model for optimum crashing of project activities. In order to make the model more realistic and applicable, the authors endeavoured to consider most of the factors that are involved in doing a project.

In the present study, to the best of the authors’ knowledge the factors of time, cost, quality, risk and the law of diminishing returns are simultaneously considered in project crashing for the first time and the grey theory was used for considering the uncertainties of project parameters. Also, “the law of diminishing returns” has not been considered during crashing in the studies conducted so far.

Managers often face the problem of making project decisions that involve a large number of interrelated activities – the planning and scheduling of which is project management. These problems often arise in areas such as product development, production planning and control and setting up of production facilities. One important aspect of project management is activity crashing, i.e. reducing activity time by adding more resources such as workers, overtime and so on. It is important to decide the optimal crash plan to complete the project within the desired time period. The usual practice is to use a linear programming (LP) approach. Finds that the solution obtained from LP is not always effective and shows that a goal‐programming approach can be used efficiently in such decision‐making problems.

The purpose of this paper is to help project management (PM) game designers and educators in simulating complexity in PM games and in assessing the effect of simulated project complexity levels on students’ learning experience. To achieve this aim, the authors attempt to design and evaluate two computer-based project crashing games (PCGs) with different complexity levels, namely project crashing game (PCG) and program crashing game (PgCG).

A literature review is conducted to identify serious games design principles. These principles are then manifested in the design of PCG and PgCG. The latter is a more complex version of the first. Students’ reaction after playing both games are then analyzed quantitatively.

The authors discover that students’ learning experience is affected by how complex the simulated project is. The more complex the project is (i.e. as in the PgCG), the more realistic the game is perceived. Nevertheless, the authors also discover that the less complex game (PCG) offers significant value to students, particularly to teach basic PM principles to those with minimum or no practical experience. This game is perceived as better in increasing students’ learning confidence as its content is perceived as more relevant to their existing knowledge.

The authors adopt a project complexity perspective when designing and evaluating the games.

To meet the rapidly increasing demand for medical treatment during the outbreak of COVID-19, Huoshengshan and Leishenshan Hospital are rapidly built (9–12 days) in Wuhan. These two urgent emergency projects are unprecedented. In general, substantial literature suggests that the possibility of shortening a schedule by more than a quarter of its original duration is implausible. By contrast, the two projects had successfully compressed the schedules from months and years to about ten days. This study aims to investigate how this was done and provide references for future projects.

The study uses qualitative case study techniques to analyze the project practices in two urgent emergency projects. Data were gathered through semi-structured interviews and archival research. During interviews, interviewees were asked to describe the project practices adopted to overcome the challenges and freely share their experiences and knowledge.

The results illustrate that a high degree of schedule compression is achievable through tactful crashing, substitution and overlapping applications. The successful practices heavily rely on the high capacity of participants and necessary organization, management and technology innovations, such as three-level matrix organizational structure, reverse design method, site partition, mock-up room first strategies and prefabricated construction technology. For instance, the reverse design method is one of the most significant innovations to project simplification and accelerate and worthy of promotion for future emergency projects.

The empirical findings are significant as they evoke new thinking and direction for addressing the main challenges of sharp schedule compression and provide valuable references for future emergency projects, including selecting high-capacity contractors and replacing the conventional design methods with reverse design.

Substantial studies indicate that the maximum degree of schedule compression is highly unlikely to exceed 25%, but this study suggests that sharp compression is possible. Although with flaws in its beauty (i.e. compressing schedule at the expense of construction cost and quality), it is also a breakthrough. It provides the building block for future research in this fertile and unexplored area.

Previous research regarding shaping factors and major causes behind accidents in the construction field is reviewed. In particular, a hypothetical model is established to correlate activity time, cost and safety in the context of construction activity acceleration planning. Two demonstration cases are presented to illustrate the proposed theoretical model in the context of critical activity expedition planning. Further, a third case uses a 100-activity project to perform the global level total project time and cost analysis, identifying specific activity acceleration plans that would materialize the shortened total project time at the lowest total project cost.

This research proposes a safety-centric application framework to guide construction acceleration planning at both activity and project levels while taking sufficient preventive measures against safety hazards and accidents. As planning construction acceleration by factoring in safety constraints inevitably drives up cost, it is imperative to control increases in activity costs at the local level in connection with schedule acceleration planning while at the same time not compromising on safety. This research also addresses this critical question through performing global level total project time and cost analysis.

An application framework is proposed for guiding a planner through identifying accident shaping factors, obeying schedule acceleration rules and accounting for safety-related costs in attempts to mitigate hazardous situations on-site at both activity level (local) and project level (global), resulting in (1) minimizing the increase of total project cost in schedule acceleration while at the same time not compromising on safety at individual activities; (2) producing specific execution plans on each individual activity in terms of the amount of time to crash and the associated activity cost.

This study is original in developing theories and methods for evaluating the impact of safety constraints upon construction time and cost in activity acceleration planning and project time-cost analysis. The research fills a gap in knowledge in terms of how to factor in sufficient safety constraints while achieving project time and cost objectives on construction acceleration planning at both activity and project levels.

The purpose of this paper is to propose a new framework for time–cost trade-off. The new framework provides the optimum time–cost value taking into account the float loss impact.

The stochastic framework uses Monte Carlo Simulation to calculate the effect of float loss on risk. This is later translated into an added cost to the trade-off problem. Five examples, from literature, are solved using the proposed framework to test the applicability of the developed framework.

The results confirmed the research hypothesis that the new optimum solution will be at a higher duration and cost but at a lower risk compared to traditional methods. The probabilities of finishing the project on time using the developed framework in all five cases were better than those using the classical deterministic optimization technique.

The objective of time–cost trade-off is to determine the optimum project duration corresponding to the minimum total cost. Time–cost trade-off techniques result in reducing the available float for noncritical activities and thus increasing the schedule risks. Existing deterministic optimization technique does not consider the impact of the float loss within the noncritical activities when the project duration is being crashed. The new framework allows project managers to exercise new trade-offs between time, cost and risk which will ultimately improve the chances of achieving project objectives.