Resiliency cube

Author(s):  
Amirpurya Chavoshy ◽  
Kambod Amini Hosseini ◽  
Mahmood Hosseini

Purpose This study aims to provide resiliency against earthquakes to the framework of an urban road network and to construct a comprehensive model with sufficient computational detail to assist metropolitan managers as a decision support tool in emergency situations via parametric analysis (model behaviour analysis with parameter changes) to quantify the consequences of decisions. Design/methodology/approach Performed stages are: developing existing resilience assessment frameworks for use against earthquakes in urban road networks, identifying earthquake scenarios and estimating the weight of components using AHP, including an example modelling of Tehran; and developing modelling software (using Matlab®). Findings This study produced a software that performs three-dimensional (3D) graphical modelling, resiliency index measurements and its parametric analyses for the road networks against earthquakes. Based on this model, a prioritized list of upgrades is also introduced. The developed tool also addresses issues regarding the allocation of limited resources between the network components. Research limitations/implications Because of the novelty of the study, there is limited literature on this topic. Practical implications The developed model provides urban managers with a comprehensive list of upgrades and empowering them to graphically and numerically evaluate the resiliency changes as they alter the parameters of these measures and balance their decisions based on available funding. Originality/value In contrast to previous studies, this study has focused on all of these three keywords: resiliency, earthquake and road networks, and not only two of them.

Author(s):  
Tullia Bonomi ◽  
Letizia Fumagalli ◽  
Valeria Benastini ◽  
Marco Rotiroti ◽  
Pietro Capodaglio ◽  
...  

The study is developed through scientific cooperation between the University of Milano-Bicocca and the Regional Agency for Environmental Protection (ARPA) of the Valle d’Aosta Region. Its aim is to produce a decision-support tool to help the Public Administration’manage groundwater and public water supply. The study area is the plain of Aosta, between the cities of Aymavilles and Brissogne; in this area groundwater represents the main source of public water supply. The valley is oriented east-west, along the Baltea for a length of 13.1 km and a width of 4.6 km. The textural and hydrogeological properties of the deposits are strictly connected to glacial deposition and to the subsequent sedimentary processes which took place in glacial, lacustrine and fluvial systems. The study is based on available well information in the Aosta plain - including water wells (133) and piezometers (121) - which have been coded and stored in the well database TANGRAM,. The database facilitates interpretation of the well data, and it allows three-dimensional mapping of subsurface hydrogeological characteristics through database codification and ordinary kriging interpolation. The study is designed to achieve two objectives. The first is to provide the Aosta Public Authorities with a well database in order to simplify groundwater management. The second is to provide Public Authorities with a groundwater flow model of the local aquifer. The model integrates surface and subsurface flows in order to fully account for all important stresses, both natural and anthropogenic, on the groundwater system. It provides a tool for testing hypotheses (such as the impact of new wells) and thereby allows science-based management of the aquifer resource.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ajay Jha ◽  
Rohit Sindhwani ◽  
Ashish Dwivedi ◽  
Venkataramanaiah Saddikuti

Purpose The purpose of this study is to identify important criteria for sustainable recovery of digital entrepreneurship from distress situation using shared resources. During pandemic disruption, the importance of sharing economy in managing business efficiency is reflected through this research. Design/methodology/approach The present study advances the knowledge on shared resources in business by integrating case study approach with multi criteria decision-making (MCDM) model. A fuzzy analytic hierarchy process approach is adopted to compute criteria weights, and a fuzzy technique for order performance by similarity to ideal solution (TOPSIS) technique is used to rank the sharing economy entrepreneurial ventures during COVID-19 pandemic in the context of emerging economy. Findings The present study identified five most important enablers (technological innovation, technology expertise, convergence of virtual and physical spaces, collaboration rather than competition, and benefits to underserved groups through transparency) for sustainable recovery of sharing economy ventures in emerging economy. For example, the study highlights online tutoring through shared intellect as the most sought after sharing economy venture during pandemic disruption, which fulfills the identified enablers. Practical implications The proposed framework provides an accurate decision support tool to rank the various identified potential enablers of sharing economy during disruptions. Further, the approach is practically relevant to sharing economy entrepreneurs in selecting the best approach to recover sustainability during pandemic. Originality/value The study is unique in addressing the need of sustainability for digital ventures via sharing economy approach in emerging economy (India). To develop a conceptual framework, the present study incorporates a case based approach together with the hybrid MCDM model. Further, the extant literature on disruptions is enhanced by prioritizing the enablers for sharing economy during pandemic.


2020 ◽  
Vol 26 (9) ◽  
pp. 1579-1591
Author(s):  
Sang-Woo Baek ◽  
Nahm-Gyoo Cho ◽  
Dong-Hyeok Lee

Purpose This paper aims to propose a method for manufacturing multi-material monolithic structures with flexible materials to construct the elastic body by using a dual-nozzle three-dimensional printer to develop a piezoelectric (PZT)-driven micropositioning stage with three degrees of freedom (3-DOF) and flexure hinges. Design/methodology/approach Polylactic acid (PLA) and nylon were used for the lever structure’s frame and flexure hinge, respectively. Additionally, the stage consisted of three PZT actuators for fine movement in the nanometer scale in 3-DOF (x, y and θ-directions). For the design of the stage, the kinematic analysis model and the finite element method (FEM) analysis was undertaken for comparing between PLA with nylon (multi-material), PLA (single material) and aluminum (conventional-material). In addition, two verification experiments were implemented for the fabricated prototype stage. First, to evaluate various assessments (lever ratio, hysteresis, coupling error and resolution), a measurement is carried out using the three capacitive sensors. Then, a two-camera-vision measurement experiment was performed to verify the displacement and lever ratio over the full-scale working range of the fabricated positioning stage, and the results from the experimentation and the FEM analysis were compared. Findings The authors confirmed enhancements in the properties of the lever structure frame, which requires stiffness and of the hinge, which requires flexibility for elastic deformation. Comparing FEM analysis and experimental results, although the performance as shown by experimental results was lower: the maximum difference being 3.4% within the end-point working range; this difference was sufficient to be a plausible alternative for the aluminum-based stage. Originality/value Multi-material monolithic-structure fabrication has an effective advantage in improving the performance of the stage, by using a combination of materials capable of reinforcing the desired characteristics in the necessary parts. It was verified that the fabricated stage can substitute the aluminum-based stage and can achieve a higher performance than single-material stages. Thus, precise-positioning stages can be manufactured in many kinds of structures with various properties and contribute to weight reduction and low costs for application equipment.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Serhat Simsek ◽  
Abdullah Albizri ◽  
Marina Johnson ◽  
Tyler Custis ◽  
Stephan Weikert

PurposePredictive analytics and artificial intelligence are perceived as significant drivers to improve organizational performance and managerial decision-making. Hiring employees and contract renewals are instances of managerial decision-making problems that can incur high financial costs and long-term impacts on organizational performance. The primary goal of this study is to identify the Major League Baseball (MLB) free agents who are likely to receive a contract.Design/methodology/approachThis study used the design science research paradigm and the cognitive analytics management (CAM) theory to develop the research framework. A dataset on MLB's free agents between 2013 and 2017 was collected. A decision support tool was built using artificial neural networks.FindingsThere are clear links between a player's statistical performance and the decision of the player to sign a new offered contract. “Age,” “Wins above Replacement” and “the team on which a player last played” are the most significant factors in determining if a player signs a new contract.Originality/valueThis paper applied analytical modeling to personnel decision-making using the design science paradigm and guided by CAM as the kernel theory. The study employed machine learning techniques, producing a model that predicts the probability of free agents signing a new contract. Also, a web-based tool was developed to help decision-makers in baseball front offices so they can determine which available free agents to offer contracts.


2014 ◽  
Vol 25 (4) ◽  
pp. 510-527 ◽  
Author(s):  
Zineb Simeu-Abazi ◽  
Maria Di Mascolo ◽  
Eric Gascard

Purpose – In this paper, the authors are concerned with a maintenance workshop (MW) centralizing all corrective maintenance activities. The purpose of this paper is to propose a methodology for designing a central maintenance workshop, enabling the evaluation of performance in terms of cost and sojourn time, for a given budget. Design/methodology/approach – The authors propose a modeling framework based on queuing networks. The aim is to maximize operational availability of the production workshop, by reducing the sojourn time of failed equipment in the MW. Findings – The proposed methodology leads to a maintenance decision support tool enabling to give the structure of the MW, performing at a higher level, but at a reasonable configuration cost. Simulation results illustrate the influence of different parameters, such as the number of stations and the level of spare parts in the MW, on the sojourn time of the equipment. Research limitations/implications – Only corrective maintenance is taken into account and only equipment that can be taken out of the production workshop are considered. The preventive replacement of some equipment items can be taken into account by the repair process by considering them as failed. Originality/value – The work falls within a more general framework for optimizing maintenance costs, in the context of integration of multi-site services in a distributed context. The paper is concerned with centralized maintenance, and proposes to integrate the so-called repair by replacement technique in a MW, used for a multi-site production workshop.


2020 ◽  
Vol 25 (2) ◽  
pp. 183-199 ◽  
Author(s):  
Zhe Zhang ◽  
Zhi Ye Koh ◽  
Florence Ling

Purpose This study aims to develop benchmarks of the financial performance of contractors and a decision support tool for evaluation, selection and appointment of contractors. The financial benchmarks allow contractors to know where they are relative to the best-performing contractors, and they can then take steps to improve their own performance. The decision support tool helps clients to decide which contractor should be awarded the project. Design/methodology/approach Financial data between 2013 and 2015 of 44 Singapore-based contractors were acquired from a Singaporean public agency. Benchmarks for Z-score and financial ratios were developed. A decision tree for evaluating contractors was constructed. Findings This study found that between 57% and 64% of contractors stayed in the financially healthy zone from 2013 to 2015. Ratios related to financial liabilities are relatively bad compared with international standards. Research limitations/implications The limitation is that the data is obtained from a cross-sectional survey of contractors’ financial performance in Singapore over a three-year period. Regarding the finding that ratios relating to financial liabilities are weak, the implication is that contractors need to reduce their financial liabilities to achieve a good solvency profile. Contractors may use the benchmarks to check their financial performances relative to that of their competitors. To reduce financial risks, project clients may use these benchmarks to examine contractors’ financial performance. Originality/value This study provides benchmarks for contractors and clients to examine the financial performance of contractors in Singapore. A decision tree is provided to aid clients in making decisions on which contractors to appoint.


2016 ◽  
Vol 27 (7) ◽  
pp. 898-914 ◽  
Author(s):  
Nicholas A. Meisel ◽  
Christopher B. Williams ◽  
Kimberly P. Ellis ◽  
Don Taylor

Purpose Additive manufacturing (AM) can reduce the process supply chain and encourage manufacturing innovation in remote or austere environments by producing an array of replacement/spare parts from a single raw material source. The wide variety of AM technologies, materials, and potential use cases necessitates decision support that addresses the diverse considerations of deployable manufacturing. The paper aims to discuss these issues. Design/methodology/approach Semi-structured interviews with potential users are conducted in order to establish a general deployable AM framework. This framework then forms the basis for a decision support tool to help users determine appropriate machines and materials for their desired deployable context. Findings User constraints are separated into process, machine, part, material, environmental, and logistical categories to form a deployable AM framework. These inform a “tiered funnel” selection tool, where each stage requires increased user knowledge of AM and the deployable context. The tool can help users narrow a database of candidate machines and materials to those appropriate for their deployable context. Research limitations/implications Future work will focus on expanding the environments covered by the decision support tool and expanding the user needs pool to incorporate private sector users and users less familiar with AM processes. Practical implications The framework in this paper can influence the growth of existing deployable manufacturing endeavors (e.g. Rapid Equipping Force Expeditionary Lab – Mobile, Army’s Mobile Parts Hospital, etc.) and considerations for future deployable AM systems. Originality/value This work represents novel research to develop both a framework for deployable AM and a user-driven decision support tool to select a process and material for the deployable context.


2020 ◽  
Vol 5 (1) ◽  
pp. 121-136
Author(s):  
Christos Papaleonidas ◽  
Dimitrios V. Lyridis ◽  
Alexios Papakostas ◽  
Dimitris Antonis Konstantinidis

Purpose The purpose of this paper is to improve the tactical planning of the stakeholders of the midstream liquefied natural gas (LNG) supply chain, using an optimisation approach. The results can contribute to enhance the proactivity on significant investment decisions. Design/methodology/approach A decision support tool (DST) is proposed to minimise the operational cost of a fleet of vessels. Mixed integer linear programming (MILP) used to perform contract assignment combined with a genetic algorithm solution are the foundations of the DST. The aforementioned methods present a formulation of the maritime transportation problem from the scope of tramp shipping companies. Findings The validation of the DST through a realistic case study illustrates its potential in generating quantitative data about the cost of the midstream LNG supply chain and the annual operations schedule for a fleet of LNG vessels. Research limitations/implications The LNG transportation scenarios included assumptions, which were required for resource reasons, such as omission of stochasticity. Notwithstanding the assumptions made, it is to the authors’ belief that the paper meets its objectives as described above. Practical implications Potential practitioners may exploit the results to make informed decisions on the operation of LNG vessels, charter rate quotes and/or redeployment of existing fleet. Originality/value The research has a novel approach as it combines the creation of practical management tool, with a comprehensive mathematical modelling, for the midstream LNG supply chain. Quantifying future fleet costs is an alternative approach, which may improve the planning procedure of a tramp shipping company.


2018 ◽  
Vol 30 (5) ◽  
pp. 591-606 ◽  
Author(s):  
Thierry Houé ◽  
Eileen Murphy

Purpose Faced with increasing competition, the ability to secure and optimise global logistics operations should be regarded as a competitive advantage. In the context of the hitherto little explored field of security and safety programmes, the purpose of this paper is to examine how an Authorised Economic Operator (AEO) certificate may affect the creation of a competitive edge for a freight forwarder. Design/methodology/approach By using the resource-based view as a theoretical background and a qualitative analysis using an interview grid inspired by the balanced scorecard, this research identifies resources and capabilities linked to the AEO certification. Findings The findings show two specific groups of resources that contribute to the creation of a competitive advantage. The first category is a process-type resource obtained through the AEO certification, which leads to more formalised and better-executed processes. The second relates to the freight forwarder’s knowledge, know-how and relational skills. Research limitations/implications This research is developed in a logistics service provider context. It should be equally applied in other contexts and with other methods to provide generalisability. Practical implications Considering its contribution to an area of study currently under research, the findings may be useful to practitioners as a decision support tool to assess the value of the AEO certification. Originality/value This paper comes in the context of a yet little explored field, despite practitioners’ questions about custom certifications.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Emmelie Gustafsson ◽  
Patrik Jonsson ◽  
Jan Holmström

PurposeThis paper investigate how fit uncertainty impacts product return costs in online retailing and how digital product fitting, a pre-sales fitting practice, can reduce fit uncertainty.Design/methodology/approachThe paper analyzes the current performance of a retailer's e-commerce and return operations by estimating costs generated by product returns, including product handling costs, tied-up capital, inventory holding costs, transportation costs, and order-picking costs. The estimated costs were built on 2,229 return transactions from a Scandinavian fashion footwear retailer. A digital product fitting technology was tested with the retailer’s products and resulted in estimations on how such technology could affect product returns.FindingsThe cost of a return is approximately 17% of the prime cost. The major cost elements are product handling costs and transportation costs, which together amount to 72% of the total costs. If well calibrated, the fitting technology can cut fit-related return costs by up to 80%. The findings show how customers reacted to the fitting technology: it was unable to verify fit every time, but it serves as a useful and effective support tool for customers when placing orders.Research limitations/implicationsVirtual fit verification using digital product fitting is key to retailers to reduce fit-related returns. Digital product fitting using three-dimensional scanning is more appropriate for some products, but it is unsuitable for products that are difficult to measure and scan.Originality/valueThe paper contributes an empirical estimate of retail supply chain costs associated with fit uncertainty, as well as theoretical understanding of the role of pre-sales fit verification in avoiding product returns.


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