Project Resource Allocation Research Articles

Participatory analytic hierarchy process for resource allocation in agricultural development projects

In the framework of 2030 Agenda sustainable agriculture plays a central role. In the field of international aid the participatory approaches to assessment, research, management and budgeting have been widely studied and applied in the last decades, mostly because international aid initiatives, in all their relevant phases from planning through implementation, monitoring and evaluation, are faced with the problem of identifying initiatives that could be successfully and sustainably implemented. The present paper investigates the use of a modified form of analytic hierarchy process, namely the participatory analytic hierarchy process, as a tool for choice criteria elicitation and resource allocation in the framework of an operational planning for agricultural development projects in the Dioceses of Goma, Nord Kivu, Democratic Republic of Congo. During our research, we were able to make use of most frequent inconsistencies in pairwise comparison matrixes in order to stimulate the debate, to adjust local preferences and to build consensus across the group. From an operational point of view, the PAHP methodology was also suited for training the project team and for identifying a shared resource allocation pattern, which matches the existing international guidelines for agricultural development in the region.

Resource Allocation and Leveling in Construction Management Projects with Resource Histogram

Resource allocation and leveling in construction management projects have been an enthusiastic subject to plenty of researchers since the advancement of the scheduling techniques. Many researchers have studied various versions of the benchmark resource leveling and allocation optimization problems using various scheduling techniques. However, in this study, a straightforward scheduling technique called resource histogram is utilized to allocate and level the available resources. Moreover, the maximum number of resources at peak time is considered as a significant aspect of the case study. Since peak demand isn’t a preferred by the contractor. The effects of resources are also examined in order to demonstrate the variation of the total duration of the project which provides flexibility to decision-makers in making intelligent decisions regarding the use of the resources. Thereby, a construction project with seven activities taken from the technical literature is examined with constrained as well as unconstrained conditions using Microsoft Excel. However, task scheduling is performed using critical path method (CPM). The results indicate that limitation on resources significantly affect the performance and cause the project to be extended beyond the scheduled duration. Moreover, besides renewable, non-renewable resources (e.g., cost demand) may also be significant parameters and this extension can be considered in future research.

Risk interval-valued three-way decisions model with regret theory and its application to project resource allocation

Psychology of regret often affects how people work in their daily lives. Due to the effects of psychology of regret, decision-makers can make irrational decisions in the face of uncertain decision risks. As a classic model, three-way decisions (TWD) are to divide a universal set into three pair-wise disjoint regions by developing an appropriate strategy and also have been widely applied in the area of risk decision-making. However, in the existing theoretical research of TWD, few studies mention the influence of psychology of regret on risk behaviours of decision-makers. In order to expand the theories of TWD and build contacts, we have introduced the influence of psychology of regret on decision-makers’ risk behaviours into TWD with decision-theoretic rough sets (DTRS). In thisarticle, we specifically adopt regret theory to depict the decision-makers’ risk behaviours on the loss function. Regret theory as one type of generalised psychology, considers the psychological comparison between the current choice and other choices made by decision-makers. In light of the Bayesian decision procedure and a basic model of interval-valued DTRS, we reinterpret TWD and construct a new risk interval-valued TWD model. At the same time, we explore the influence of the regret behaviour to TWD by using the simulation experiment and validate the effectiveness of the new risk model. Then, we further apply the risk interval-valued TWD model to support the project resource allocation. From two different viewpoints, we establish two adjustment targets to meet the actual needs of decision-makers in project allocation, which improves our decision’s flexibility in the resource restriction. Target 1 is to minimise the utility loss of the entire field. Target 2 is to maximise the utility of the positive region in each field. Finally, a case of popular entrepreneurship of online movie is used to illustrate and validate our proposed methods.

Towards modelling diffusion mechanisms for sustainable off-grid electricity planning

The electrification-based literature reports a limited knowledge about the mechanisms of evolution of electricity demand in off-grid settings, especially in remote contexts of developing countries, due to the lack of robust and appropriate modelling frameworks. Such lack of understanding and modelling endeavour contributes to an inefficient allocation of resources for electrification projects and inappropriate off-grid sizing processes. As a first step towards the development of a more appropriate electricity demand model, we present a comparative study of two approaches for modelling different diffusion mechanisms of electricity connections: system-dynamics and agent-based models. The latter includes the modelling of social network archetypes in the simulation of diffusion processes. We model different scenarios of diffusion and we use them for evaluating the impact on the sizing process of an off-grid hydroelectric system. The results suggest that the structure of the social network can represent a crucial parameter that can impact on timing needed to complete the diffusion of electricity access – from few months to even >10 years. This affects the sizing process and the long-term sustainability of the power system, leading to variation of the hydroelectric capacity and the battery size up to around 55% and 100%, respectively. Our results indicate that the agent-based approach allows a more diversified representation of diffusion processes, but the limitations and scarcity of data can be an obstacle to their prompt application for energy application in unelectrified areas. On the contrary, system-dynamics can represent a more appropriate method since it requires less quantitative data and it provides a more structural and holistic modelling framework for conceptualising and formulating in a the determinants and complexities affecting the evolution of electricity demand in unelectrified areas.

Human Resource allocation in projects: A systematic mapping Study

The effective use of human resource and time management in projects can bring huge benefits to the companies' performance. Based on this point of view, a systematic mapping study was performed about research papers related to human allocation in projects. The purpose of this paper was to understand the used techniques to allocate human resources in projects and show gaps for further works. After performing the researches, an initial set of 7,894 articles was obtained. The application of selection criteria allowed the choice of 27 articles. These works were classified considering their relevance and contribution to the resource allocation area. Among the articles selected, two gaps were noticed: companies cannot change their strategic objectives once the project is started; the memory of previous allocations could not be used for future allocations. The results of this study are expected to help project managers improve their human resource allocations.

Dynamic modelling of human resource allocation in construction projects

Success of construction projects depends heavily on correct management of human resources. One of the most important effective processes in the management of human resources is the allocation of labour to the project. Allocation of human resources as an effective managerial tool and improvement factor in the progress of performing a project can strongly influence project performance in terms of cost and time. Therefore, allocation process can be improved by the estimation of labour need and assessment of different human resources allocation strategies. Labour allocation is laborious due to the existence of dynamics, complex relations and feedback in the project. A dynamic model is proposed to effectively allocate workforce using system dynamics approach. The presented model in the current research, however, enables the project to accurately estimate the labour need and its effective allocation. Using this model, required planning for on-time supply and allocation of project labour can be done before and through the course of the project. These trends can further see development using the proper policies.

Analysis of the Formation and Allocation of Resources Directed at Funding Environmental Projects and Programmes (EPP)

After signing the Treaty of Accession to the European Union (2005), Romania has enforced the obligations assumed as concerns the environment, all the while trying to identify and attract additional sustainable funding sources in order to develop wide scope projects and programmes. Therefore, the Romanian legal system has instituted a special mechanism for the formation and allocation of resources for funding environmental projects and programmes (EPP), by applying the “the polluter pays” and “extended producer responsibility” principles. We are here referring to the Environment Fund Budget, regulated since 2005 and the focus of the present endeavour. In this respect, we will resort to the most recent professional literature available in the field and to the current regulatory framework, in order to conduct certain relevant analyses related to the mentioned mechanism, all the while bringing forward the issue of the recent financial developments, based on the officially confirmed data and indicators. Also, we indicate the current (minimum) objectives of recovery / incineration in incineration plants with energy recovery and recovery through recycling, global and by type of packaging materials. In the last part of the paper, we offer the formulas used in establishing the taxes and contributions due to the Environmental Fund, striving to make a presentation as unified and documented as possible.

SEET

Software development effort estimation (SDEE) is a significant activity in project management and serves as the basis for project bidding, planning, staffing, resource allocation, scheduling, and cost estimation. The accuracy of SDEE techniques varies from project to project, which makes them rather unreliable. In this backdrop, we propose a foundation centered ensemble-based SDEE approach. The primary goal of this approach is to design an ensemble consisting of different machine learning methods for improving the prediction accuracy of SDEE. In recent times, several research results have been reported on machine learning based ensemble design, but extreme learning machine (ELM) and least square support vector regression (LSSVR) have not been used to develop an ensemble. We chose three machine learning techniques, namely ELM, LSSVR, and multilayer perceptron (MLP) as the base techniques to build an ensemble. We investigated the performance of a homogeneous ensemble design using a linear combination rule with standardized accuracy as a weight factor. The performance of the ensemble model is validated and compared with root mean square error (RMSE) based weighted average ensemble model with equivalent configuration. The experimental study was conducted using publicly available PROMISE repository test suite. We achieved promising results for SEET model compared to base learners and RMSE ensemble model.

An Optimal Portfolio Selection based on a Hybrid Approach to improve Projects Oriented Organizations

Nowadays, managing and allocating resources to the project portfolio is one of the most critical decision-making processes in project-oriented organizations. To achieve the most value in terms of profitability, these companies should consider taking advantage of ongoing projects and optimal management of their resources allocated to the most optimal project portfolio. Project Portfolio Selection (PPS) and resource allocation are critical problems in project portfolio based companies. These organizations are required to evaluate, prioritize and select their projects in accordance with the strategic and operational mission and objectives. In this study, we propose a three-stage hybrid approach for prioritizing and selecting an optimal project portfolio. We obtain the maximum economic contribution (maximum fitness) between the final PPS and the projects initial prioritizing while considering various organizational criteria and objectives. The proposed approach is composed of three stages with several steps. We use information entropy for the initial prioritizing, the branch and bound algorithm for generating combination of project portfolios and Integer Linear Programming (ILP) for selecting the most suitable project portfolio according to strategic and operational objectives. At the end, a case study is used to demonstrate the applicability and the merits of the proposed approach.

The Influence of Project Resource Allocation on the Resource Capacity of the Business Processes

In small and medium enterprises, resources from within the company are often used to fulfil small-scale projects. This paper discusses the influence of project resource allocation on the operational workflow of small and medium enterprises based on a case study. More precisely, the capacity of certain business operations will be lowered due to the allocation of scarce resources to projects. Subsequently, this might result in a temporarily lower throughput in the business processes and thus a potential loss of profitability. As a result, project scheduling and resource management have a clear impact on the planning and execution of the daily operations. In case that the deterministic estimates of project durations and costs are used, without accounting for risk and uncertainty, project delays are highly likely. Given the relation between project and business resource allocation, project delays might lead to difficulties in meeting targets in the daily operations. This paper presents an approach to incorporate the above effect in the decision-making process of portfolio management, i.e. the choice to initiate a project given the negative impact on the business processes. The decision-making process that results from this fundamental trade-off is demonstrated using a real-life project, which could provide valuable insights to project managers in small and medium enterprises.

Threats to validity in search‐based predictive modelling for software engineering

A number of studies in the literature have developed effective models to address prediction tasks related to a software product such as estimating its development effort, or its change/defect proneness. These predictions are critical as they help in identifying weak areas of a software product and thus guide software project managers in effective allocation of project resources to these weak parts. Such practices assure good quality software products. Recently, the use of search-based approaches (SBAs) for developing software prediction models (SPMs) has been successfully explored by a number of researchers. However, in order to develop effective and practical SPMs it is imperative to analyse various sources of threats. This study extensively reviews 93 primary studies, which use SBAs for developing SPMs of four commonly used software attributes (effort, defect-proneness, maintainability and change-proneness) in order to discuss and identify the various sources of threats while using these approaches for SPMs. The study also lists various actions that may be taken in order to minimise these threats. Furthermore, best practice examples in literature and the year-wise trends of threats indicating the most common threats missed by researchers are provided to help academicians and practitioners in designing effective studies for developing SPMs using SBAs.

Client Deadline Concentration in Audit Offices and Audit Quality

This research investigates the effect on audit quality of concentrated public company financial statement filing deadlines in audit offices. Audit offices must effectively manage their resources to meet their clients’ audit service demands. For audit offices with clients that have filing deadlines concentrated in time, resource management is of greater importance because, when constrained or not managed effectively, resources can impair audit quality. We draw on the resource constraints and multiple project resource allocation literatures in auditing and management, respectively, to hypothesize that audit quality is lower when an audit office’s clients’ financial statement deadlines concentrate in time, which we term client deadline concentration. Using multiple proxies for audit quality, we find an economically significant negative association between an audit office’s client deadline concentration and audit quality. This significant effect is incremental to the effects of other resource-based constraints from the prior literature and to controls for unobservable differences in audit offices that explain a significant amount of the variation in audit quality outcomes. In light of our findings, audit offices might more carefully consider the relative timing of client deadlines when accepting or continuing client engagements and when making resource-related decisions.

Allocating human resources to projects and services in dynamic project environments

PurposeResource allocation is challenged by dynamic environments where changes are frequent. The purpose of this paper is to identify resource allocation challenges and practices in service units that perform both project and non-project activities in dynamic environments. Its goal is to show that top-down mechanisms of project resource allocation need to be replaced by or supplemented with mechanisms that are more flexible.Design/methodology/approachA qualitative comparative case study was conducted in two service units of two project-based firms. The main source of data consisted of semi-structured interviews with 17 service managers and staff members.FindingsThis study shows that resource allocation is not necessarily a top-down process at all, and the practices are context-dependent. Two more flexible approaches are revealed – hybrid resource allocation and bottom-up resource allocation – as examples of managing resource allocation in service units that engage in projects under uncertain conditions. The results of the analysis highlight prioritisation and adapting to change and delay as the main issues that managers face in allocating resources to different types of projects and service activities in dynamic environments.Research limitations/implicationsThe two target companies chosen for the qualitative research design limit the analysis to project-based firms in a business-to-business context. Further, the viewpoint of the service unit is central to the study. Studying project resource allocation in different organisational contexts and uncovering the perspectives of product development and delivery units would offer promising directions for future research.Practical implicationsThe study reveals that in dynamic project settings such as service organisations, top-down mechanisms of resource allocation need to be accompanied by other, more flexible approaches to ensure the sufficient resourcing of projects and related services in dynamic environments. Companies need to establish practices for resource allocation changes that are caused by re-prioritising tasks and accommodating changes and delays in their project and service activities.Originality/valueCompared to a top-down perspective taken in previous research, the study proposes a more flexible approach for resource allocation in constantly changing environments with different project and service activities. Previous studies have focussed on resource competition between projects, placing project managers in the central role for resource allocation. By contrast, this study discusses hybrid and bottom-up resource allocation, both of which involve broader personnel engagement in resource allocation tasks, drawing on the experience of all employees.

Quantifying cost-effectiveness of subsurface strata exploration in excavation projects through geostatistics and spatial tessellation

Abstract A major source of uncertainty in civil engineering projects arises from the geological and geotechnical variability at the project site. This paper presents an approach to quantify such uncertainty, and to rationally incorporate them into estimates of cost contingency. Contrary to the conventional approaches that rely on individual expert's opinion or data from past projects, the proposed approach allows site-specific assessments of the intrinsic geotechnical variability through geostatistical techniques. Such uncertainty can be reduced through geotechnical investigation, and spatial tessellation techniques are proposed to facilitate determination of the optimal locations of new boreholes. Cost-effectiveness of the boreholes can be evaluated based on the corresponding reductions in geotechnical uncertainty and their influence on the budget. The approach is illustrated using a hypothetical excavation scenario, where the project costs are affected by uncertainty in the subsurface strata, particularly the rockhead level across the site. Under the specific site conditions, a Pareto frontier is developed to reveal the relationship between the number of boreholes to be drilled and potential savings in contingency budget. Through this approach, the study promotes better utilization of geotechnical information and rational assessments of project risks associated with their variability, which may lead to improved project planning and resource allocation.

Detection of Resource Overload in Conditions of Project Ambiguity

The planning of project resource allocation is an important part of project management, but it often suffers from uncertainty and ambiguity. Ambiguity conditions can be described and simulated by the theory of fuzzy sets and fuzzy quantities. The fuzzy approach to project planning is usually applied in critical path setting and project duration monitoring. In this article, we show a new application of the fuzzy set theory that involves planning project resource allocation and monitoring resource workloads. We derive the theoretical relations for the membership functions of the corresponding fuzzy quantities and demonstrate their application by taking a simple project as an example. The derived methods were used in planning a real project whose purpose was to analyze the possible resource workload. As a result, it was possible to recognize the serious risk of resource overload, which is not possible with the deterministic approach. They contributed to the success of the project.

Project Screening and Resource Allocation in Boss-less Organizations

A boss-less organization, where employees self-select to projects, have been an emerging phenomenon that has attracted attention of both scholars and practitioners. The proponents of this new form argue that it offers considerable advantages over the more traditional hierarchical approach. The empirical evidence, however, offers mixed results. This paper develops a simple agent- based model of open and hierarchical allocation to determine the mechanisms and boundary conditions of application of the two opposing modes of project selection and asset allocation. Our results suggest that the relative balance between the resources of the organization and number of opportunities it faces play a critical role in determining the efficacy of the two forms. We provide a detailed analysis of the mechanism and discuss potential applications of our findings to studies of industry evolution and firm size.

Beyond Related Experience: Upstream vs. Downstream Experience in Innovation Contest Platforms with Interdependent Problem Domains

Problem definition: Innovation contest platforms are often organized around specific fields and host contests that span a variety of interdependent problem domains. Whereas contestants may benefit from related experience in contests whose problem domains share an interdependency with the focal problem domain, it is unclear whether the benefits of related experience arise symmetrically from upstream experience (i.e., experience in problem domains that provide input information to the focal problem domain) and downstream experience (i.e., experience in problem domains that use output information from the focal problem domain) or differ among them. Academic/practical relevance: Given that innovation contest platforms serve to effectively match contest problem requirements with contestants’ skills, it is important to understand how a contestant’s prior experience on a platform contributes to her problem-solving performance. Our research provides a more granular examination of the benefits of related experience than what has been examined in prior studies on individual learning or innovation contests. Methodology: We collected detailed archival data from TopCoder, a leading innovation contest platform that hosts contests across multiple interdependent software development problem domains, from its launch in 2001 to September 2013. Our data set comprises detailed participation histories of 821 contestants in 3,274 contests across eight interdependent problem domains involving 8,985 observations. Results: Whereas a contestant’s related experience on the innovation contest platform is more positively associated with her focal contest performance compared with unrelated experience, the benefits of related experience arise only from downstream experience. That is, there are no significant performance benefits of upstream experience. Furthermore, the performance benefits of downstream experience are greater when the contest duration is shorter, highlighting its role in enabling more efficient search and problem solving in innovation contest platforms with interdependent problem domains. Managerial implications: Contrary to the notion of “hyperspecialization,” our findings suggest that contestants can reap benefits from diversifying their experience into downstream problem domains on innovation contest platforms. Furthermore, innovation contest platforms could facilitate such targeted diversification of contestant experience by developing more granular metrics of contestant experience across problem domains. Our findings also have implications for resource allocation and job rotation decisions in software development projects within firms.

A CASE Study on Software Project Development Cost, Schedule & Effort Estimation

This paper theme is to provide a case study of Software Project Development cost, effort, and schedule estimation. From recent past, a remarkable research takes place in developing different techniques on software effort and cost estimation. Making estimation before start of any project is necessary to be able to plan and manage any project. The estimate is an intelligent guess for the project resources. Nowadays, software has become a major contributor to economic growth for any nation. Making an estimate before starting any software project is vital for the project managers and key stakeholders. Major project milestones such as project schedules, budgeting, resource allocation, and project delivery dates are set on theeffort and cost estimates. Thus, the reliability of the estimation leads any project success or otherwise fail. In this article, author’s idea is to work with function point analysis and include the concept of workforce scheduling in a better way while taking the decision in the contract phase. That leads to strengthening the relations between the developer and the customer. Basically, size is a main measured unit of the software project. Based on the size and other functionalities, the software managers estimate the total effort required to develop the project. From the effort and work schedule, the total cost can be estimated.

Software Cost Estimation Approaches: A Survey

The software cost estimation aims to predict the most realistic effort that is required to finish a software project and so it is critical to the success of a software project management. A Software Cost Estimation affects nearly all management activities, including project bidding, resource allocation and project planning. It is affected by a number of factors, such as implementation efficiency, as well as how much the various reviews and studies completed prior to the software development stage cost. Accurate cost estimation will help us to complete the project on time and within budget. Accurate estimation is important because it has led to extensive research into the methods of software cost estimation. Some important software cost estimation methods have been studied in this research work. In addition, we have set out own criteria, which has been used to compare all the different selected methods. We have also given a score for each evaluation criteria, so that we can compare the different methods numerically for cost estimation. Our observations have shown that it is best to use a number of different estimating techniques or cost models, and then compare the results before determining the reasons for any of the large variations. None of the methods are necessarily better or worse than the others. We found, in fact, that their strengths and weaknesses often complement each other. Therefore, the main conclusion is that there is no one single technique that is best for every situation, and the results of a number of different approaches need to be carefully considered to discover what is the most likely to produce estimates that are realistic.

Toward Project Complexity Evaluation: A Structural Perspective

Complexity is often quoted as an independent variable that challenges the utility of traditional project management tools and techniques. A large body of work has been devoted in exposing its numerous aspects, yet means for quantitatively assessing it have been scarce. Part of the challenge lies in the absence of hard evidence supporting the hypothesis that projects can be considered as complex systems, where techniques for measuring such complexity are better established. In response, this study uses empirical activity networks to account for the technological aspect of five projects. By doing so, the contribution of this study is twofold. First, a procedure for the quantitative assessment of an aspect of project complexity is presented; namely, structural complexity. Second, results of the analysis are used to highlight qualitatively similar behavior with a well-known complex system, the Internet. As such, it suggests a transition from the current, metaphorical view of projects being complex systems to a literal one.From a practical point of view, this study uses readily captured and widely used data, enabling practitioners to evaluate the structural complexity of their projects to explore system pathologies and, hence, improve the decision-making process around project bidding, resource allocation, and risk management.