Stakeholder engagement: Defining strategic advantage for sustainable construction

This is the accepted version of the following article: Rodriguez-Melo, A. and Mansouri, S. A. (2011), Stakeholder Engagement: Defining Strategic Advantage for Sustainable Construction. Bus. Strat. Env., 20: 539–552, which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/bse.715/abstract.Although sustainable development is increasingly becoming a part of business plans, it is unclear what makes the economic, social and environmental dynamics strategically compatible. This research examines which of the following in sustainable development – government policy, managerial attitude and stakeholder engagement – is the most influential on the profitability of companies in the UK construction sector. Quantitative and qualitative analyses were rendered through a survey and semi-structured interviews. Patterns of ambiguity in legislation were discovered as an obstacle for changing the sector's mind-set. Stakeholder engagement was identified as the defining factor increasing managers' awareness, helping legislation to be effectively implemented and making sustainability highly appealing to clients. These findings indicate that to gain competitive advantage, companies should embark on long-term strategic alliances which adopt the proposals of environmental non-governmental organisations and closely follow public opinion. This, strengthens brand equity, allows for premium pricing, increases market share and maximizes profit

Bicriteria scheduling of a two-machine flowshop with sequence-dependent setup times

The official published version of the article can be found at the link below.A two-machine flowshop scheduling problem is addressed to minimize setups and makespan where each job is characterized by a pair of attributes that entail setups on each machine. The setup times are sequence-dependent on both machines. It is shown that these objectives conflict, so the Pareto optimization approach is considered. The scheduling problems considering either of these objectives are NP-hard , so exact optimization techniques are impractical for large-sized problems. We propose two multi-objective metaheurisctics based on genetic algorithms (MOGA) and simulated annealing (MOSA) to find approximations of Pareto-optimal sets. The performances of these approaches are compared with lower bounds for small problems. In larger problems, performance of the proposed algorithms are compared with each other. Experimentations revealed that both algorithms perform very similar on small problems. Moreover, it was observed that MOGA outperforms MOSA in terms of the quality of solutions on larger problems.Partial Funding from EPSRC under grant EP/D050863/1

Decision support for build-to-order supply chain management through multiobjective optimization

This is the post-print version of the final paper published in International Journal of Production Economics. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2010 Elsevier B.V.This paper aims to identify the gaps in decision-making support based on multiobjective optimization (MOO) for build-to-order supply chain management (BTO-SCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting MOO techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted. Future research directions to better exploit the decision support capabilities of MOO are proposed. These include: reformulation of the extant optimization models with a MOO perspective, development of decision supports for interfaces not involving manufacturers, development of scenarios around service-based objectives, development of efficient solution tools, considering the interests of each supply chain party as a separate objective to account for fair treatment of their requirements, and applying the existing methodologies on real-life data sets.Brunel Research Initiative and Enterprise Fund (BRIEF

Centralised Versus Market-Based Control Under Environment Uncertainty: Case of the Mobile Task Allocation Problem (MTAP)

This paper aims at comparing the centralised versus the market-based approach. This is done in the context of the mobile task allocation problem (MTAP) from the perspective of environmental uncertainty. MTAP is defined as an optimization problem for planning the assignment of service tasks to mobile workers. Environmental uncertainty is introduced through the injection of stochastic tasks and dynamic travel delays. A multi-agent simulator is employed to experiment the behaviour of each approach in reaction to different uncertainty levels. Preliminary results suggest a tentative conceptual model to evaluate the suitability of each approach to address MTAP in function of uncertainty. It is suggested that uncertainty’s effect on achieved performance is moderated by the timeliness of decision making, workers’ degree of local knowledge, and problem’s complexity and size

Speed optimization and bunkering in liner shipping in the presence of uncertain service times and time windows at ports

© 2016 The Authors. Recent studies in maritime shipping have concentrated on environmental and economic impacts of ships. In this regard, fuel is considered as one of the important factors for such impacts. In particular, the sailing speed of the vessels affects the fuel consumption directly. In this study, we consider a speed optimization problem in liner shipping, which is characterized by stochastic port times and time windows. The objective is to minimize the total fuel consumption while maintaining the schedule reliability. We develop a dynamic programming model by discretizing the port arrival times to provide approximate solutions. A deterministic model is presented to provide a lower bound on the optimal expected cost of the dynamic model. We also work on the effect of bunker prices on the liner service schedule. We propose a dynamic programming model for bunkering problem. Our numerical study using real data from a European liner shipping company indicates that the speed policy obtained by proposed dynamic model performs signi cantly better than the ones obtained by benchmark methods. Moreover, our results show that making speed decisions considering the uncertainty of port times will noticeably decrease fuel consumption cost.This research is supported in part by EU FP7 project MINI-CHIP (Minimising Carbon Footprint in Maritime Shipping) under grant number PIAP-GA-2013-611693

Collaborative relationships between logistics service providers and humanitarian organizations during disaster relief operations

Purpose: this study explores barriers and benefits of establishing relationships between humanitarian organizations (HOs) and logistics service providers (LSPs) in order to improve humanitarian disaster relief operations (DROs). the perceptions of a variety of actors are explored to determine key factors which influence collaboration. Design/ methodology/ approach: This study comprises of quantitative methodological approaches. a comprehensive literature review was undertaken alongside an online survey with a variety of respondents. descriptive statistics, data visualization and qualitative data analysis were implemented to analyse survey results. a follow-up survey and interviews with LSPs validated the results. Findings, the research presents the opinions of a variety of actors involved in DROs and reveals barriers which affect HO/LSP collaboration. explanations for these barriers and possible solutions to mitigate them are disclosed. the findings also uncover gaps between research and practice; providing new insights into behaviour in the humanitarian field. Practical implications: We provide an in-depth understanding of the barriers and challenges faced in this field and suggest a revaluation of corporate decision making in order to increase trust between LSPs and HOs. We identify future research topics including the impact of donors and military organisations on HO decision making, and analysis of variables which may affect the formation of collaborative partnerships. Originality/value: We introduce a unique empirical insight into the perspective of HOs, LSPs and academics and offers suggestions for mitigating the numerous barriers associated with successful collaborative partnerships between HOs and LSPs

Integrated business continuity and disaster recovery planning: Towards organizational resilience

Businesses are increasingly subject to disruptions. It is almost impossible to predict their nature, time and extent. Therefore, organizations need a proactive approach equipped with a decision support framework to protect themselves against the outcomes of disruptive events. In this paper, a novel framework is proposed for Integrated Business Continuity and Disaster Recovery Planning for efficient and effective resuming and recovering of critical operations after being disrupted. The proposed model addresses decision problems at all strategic, tactical and operational levels. At the strategic level, the context of the organization is first explored and the main features of the organizational resiliency are recognized. Then, a new multi-objective mixed integer linear programming model is formulated to allocate internal and external resources to both resuming and recovery plans simultaneously. The model aims to control the loss of resiliency by maximizing recovery point and minimizing recovery time objectives. Finally, at the operational level, hypothetical disruptive events are examined to evaluate the applicability of the plans. We also develop a novel interactive augmented ε-constraint method to find the final preferred compromise solution. The proposed model and solution method are finally validated through a real case study

A hybrid decision support system for managing humanitarian relief chains

Decisions regarding location, allocation and distribution of relief items are among the main concerns of the Humanitarian Relief Chain (HRC) managers in response to no-notice large-scale disasters such as earthquakes. In this paper, a Hybrid Decision Support System (HDSS) consisting of a simulator, a rule-based inference engine, and a knowledge-based system (KBS) is developed to configure a three level HRC. Three main performance measures including the coverage, total cost, and response time are considered to make an explicit trade-off analysis between cost efficiency and responsiveness of the designed HRC. In the first step, the simulator calculates the performance measures of the different configurations of the HRC under generated number of disaster scenarios. Then, the rule-based inference engine attempts to build the best configuration of the HRC including facilities’ locations, relief items’ allocation and distribution plan of the scenario under investigation based on calculated performance measures. Finally, the best configuration for each scenario is stored in the KBS as the extracted knowledge from the above analyses. In this way, the HRC managers can retrieve the most appropriate HRC configuration in accordance with the realized post-disaster scenario in an effective and timely manner. The results of a real case study in Tehran demonstrate that the developed HDSS is an effective tool for fast configuration of HRCs using stochastic data

The lean-performance relationship in services: A theoretical model

A successful software project is the result of a complex process involving, above all, people. Developers are the key factors for the success of a software development process, not merely as executors of tasks, but as protagonists and core of the whole development process. This paper investigates social aspects among developers working on software projects developed with the support of Agile tools. We studied 22 open-source software projects developed using the Agile board of the JIRA repository. All comments committed by developers involved in the projects were analyzed and we explored whether the politeness of comments affected the number of developers involved and the time required to fix any given issue. Our results showed that the level of politeness in the communication process among developers does have an effect on the time required to fix issues and, in the majority of the analysed projects, it had a positive correlation with attractiveness of the project to both active and potential developers. The more polite developers were, the less time it took to fix an issue.UK Engineering and Physical Sciences Research Counci

From disaster to development: A systematic review of community-driven humanitarian logistics

There remains a plethora of untapped resources which exist within disaster affected communities, able to address both relief and development concerns. A systematic review of the literature revealed that communities are able to form ad hoc networks which have the capabilities to address a wide range of disaster management needs. These networks, known as Collaborative Aid Networks (CANs), have demonstrated efficient logistical capabilities exclusive of humanitarian organisations (HOs). We propose CANs offer alternative solutions to traditional humanitarian approaches to logistics, whilst also mitigating the challenges commonly faced by traditional HOs. Furthermore, the impact that CANs have on development as a result of their involvement in humanitarian logistics, highlights a more holistic, long-term approach to disaster management. This research provides the foundation for further theoretical exploration of effective and efficient disaster management, and opportunities for policy and practice