scholarly journals When Green Procurement Meets Complexity: The Case of Sustainable Neighborhood Projects

2021 ◽  
Vol 13 (4) ◽  
pp. 2116
Author(s):  
Hasan A. M. Hamdan ◽  
Luitzen de Boer ◽  
Daniela Baer
Keyword(s):  
Structural Complexity ◽  
Poor Performance ◽  
Complex Nature ◽  
Green Procurement ◽  
Complex Projects ◽  
Wide Range ◽  
Neighborhood Scale ◽  
Scale Challenges ◽  
Sustainable Transition

In a rapidly urbanizing world, cities form the key context for a sustainable transition. The neighborhood scale is suggested as a successful scale to realize cross-sector, inter-organizational collaborations. The multifaceted goals and resulting interdependencies in sustainable neighborhood (SN) developments seem to render them complex. Neighborhood scale can be understood as a program of related projects encompassing a wide range of actors interacting in a non-simple way. The added complexity comprised at the neighborhood scale challenges the promise of sustainable transition, creating a gap between what is promised as SN and what is delivered. While filling this gap is deemed pivotal to boost the performance and success of SNs, this study focuses on the practice of procurement. Green procurement has a prominent role in fostering the sustainable transition and alleviate the projects’ poor performance in energy consumption and carbon emissions. However, green procurement is complicated and often hampered by the complex nature of the programs and projects required to realize SNs. Using an in-depth case study of an ongoing SN development in Norway, we seek to explore green procurement in SN programs. The present study has several contributions. First, we provide a fresh look at SNs using the notion of program management and the principles of nearly decomposable systems. Second, the study demonstrates that green procurement can support coordination in programs, and propose several implications for purchasers to consider when devising a green procurement strategy for SN programs, laying the groundwork for new procurement research focusing on structural complexity. Furthermore, our study encourages purchasers to think like architects to grasp the various levels and make better decisions in complex projects and programs.

Managing integration in infrastructure alliance projects

2017 ◽  
Vol 10 (1) ◽  
pp. 5-31 ◽  
Author(s):  
Anna-Maija Hietajärvi ◽  
Kirsi Aaltonen ◽  
Harri Haapasalo
Keyword(s):  
Construction Projects ◽  
Research Approach ◽  
Content Type ◽  
Complex Projects ◽  
Wide Range ◽  
Project Organizations ◽  
Integration Mechanisms ◽  
Organizational Integration ◽  
Time Critical

Purpose The effective management of inter-organizational integration is central to complex projects. Such projects pose significant challenges for integration, as organizations struggle with constantly changing inter-organizational interdependencies and must develop and adapt integration mechanisms to meet new demands. The purpose of this paper is to understand what kinds of integration mechanisms are used and how they are developed and adjusted during the infrastructure alliance projects. Design/methodology/approach This study provides empirical evidence of integration dynamics in project alliancing by analyzing two infrastructure alliance projects – a complex tunnel construction project and a railway renovation project. The research approach is an inductive case study. Findings This paper identifies integration mechanisms adopted in two case projects and three central triggers that led to changes in the integration mechanisms: project lifecycle phase, unexpected events and project team’s learning during the project. Practical implications Integration capability should be a precondition for alliance project organizations and requires the adoption of a wide range of integration mechanisms, as well as an ability to adjust those mechanisms in response to everyday dynamics and emergent situations. Originality/value Although unplanned contingencies and the responses to them represent important influences in organizations, there is limited amount of research on the dynamics of integration. The findings will be of value in supporting the management of inter-organizational integration in complex, uncertain and time-critical construction projects.

scholarly journals Sustainability in Healthcare

2018 ◽  
Author(s):  
Gülay Tamer
Keyword(s):  
Sustainable Development ◽  
Three Dimensions ◽  
Healthcare Sector ◽  
Complex Nature ◽  
Healthcare Industry ◽  
The Sustainable Development ◽  
Healthcare Facilities ◽  
Future Design ◽  
Wide Range

Sustainability, which is a multi-dimensional and popular concept today, has three dimensions that almost everyone agrees: environmental, economic and social dimensions. Due to the complex nature of the healthcare industry and the wide range of facilities, operations and activities of a typical healthcare provider, the overall social, economic and environmental impact created by the healthcare industry is enormous and closely related to the sustainable development. As in all other industries, it is also inevitable for the healthcare sector to take sustainability initiatives to the forefront. In this study, how sustainability and sustainable development can be adapted to the healthcare sector is described after definition of the concept is given. Some examples of sustainability understanding and initiatives that healthcare facilities may adopt are addressed and how quality dimensions can be used in this context is explained. And to this end, a research conducted in a hospital to contribute to improve healthcare infrastructure to create socially sustainable healthcare facilities is given as a case study at the end of this study. In the said case study, the researches suggest that evidence based design presents an adequate tool for analyzing existing and future design of healthcare facilities.

Colloidal Plasmonic Nanostar Antennas with Wide Range Resonance Tunability

2019 ◽  
Author(s):  
Theodoros Tsoulos ◽  
Supriya Atta ◽  
Maureen Lagos ◽  
Michael Beetz ◽  
Philip Batson ◽  
...  
Keyword(s):  
Single Particle ◽  
Structural Complexity ◽  
Field Enhancement ◽  
Hot Electron ◽  
Structure Property ◽  
Plasmon Band ◽  
Gold Nanostars ◽  
Wide Range ◽  
Particle Level ◽  
Spectrally Resolved

<div>Gold nanostars display exceptional field enhancement properties and tunable resonant modes that can be leveraged to create effective imaging tags or phototherapeutic agents, or to design novel hot-electron based photocatalysts. From a fundamental standpoint, they represent important tunable platforms to study the dependence of hot carrier energy and dynamics on plasmon band intensity and position. Toward the realization of these platforms, holistic approaches taking into account both theory and experiments to study the fundamental behavior of these</div><div>particles are needed. Arguably, the intrinsic difficulties underlying this goal stem from the inability to rationally design and effectively synthesize nanoparticles that are sufficiently monodispersed to be employed for corroborations of the theoretical results without the need of single particle experiments. Herein, we report on our concerted computational and experimental effort to design, synthesize, and explain the origin and morphology-dependence of the plasmon modes of a novel gold nanostar system, with an approach that builds upon the well-known plasmon hybridization model. We have synthesized monodispersed samples of gold nanostars with finely tunable morphology employing seed-mediated colloidal protocols, and experimentally observed narrow and spectrally resolved harmonics of the primary surface plasmon resonance mode both at the single particle level (via electron energy loss spectroscopy) and in ensemble (by UV-Vis and ATR-FTIR spectroscopies). Computational results on complex anisotropic gold nanostructures are validated experimentally on samples prepared colloidally, underscoring their importance as ideal testbeds for the study of structure-property relationships in colloidal nanostructures of high structural complexity.</div>

Site specific agricultural soil management with the use of new technologies

2013 ◽  
Vol 16 (1) ◽  
pp. 59-67
Keyword(s):  
New Technologies ◽  
Digital Interface ◽  
Appropriate Treatment ◽  
Wide Range ◽  
Soil Variation ◽  
Soil Information ◽  
Remote Sensing Techniques ◽  
Agricultural Areas

<p>The Soil Science Institute of Thessaloniki produces new digitized Soil Maps that provide a useful electronic database for the spatial representation of the soil variation within a region, based on in situ soil sampling, laboratory analyses, GIS techniques and plant nutrition mathematical models, coupled with the local land cadastre. The novelty of these studies is that local agronomists have immediate access to a wide range of soil information by clicking on a field parcel shown in this digital interface and, therefore, can suggest an appropriate treatment (e.g. liming, manure incorporation, desalination, application of proper type and quantity of fertilizer) depending on the field conditions and cultivated crops. A specific case study is presented in the current work with regards to the construction of the digitized Soil Map of the regional unit of Kastoria. The potential of this map can easily be realized by the fact that the mapping of the physicochemical properties of the soils in this region provided delineation zones for differential fertilization management. An experiment was also conducted using remote sensing techniques for the enhancement of the fertilization advisory software database, which is a component of the digitized map, and the optimization of nitrogen management in agricultural areas.</p>

COVID-19 Outbreak Prediction with Machine Learning

2020 ◽  
Author(s):  
Sina Faizollahzadeh Ardabili ◽  
Amir Mosavi ◽  
Pedram Ghamisi ◽  
Filip Ferdinand ◽  
Annamaria R. Varkonyi-Koczy ◽  
...  
Keyword(s):  
Machine Learning ◽  
Prediction Models ◽  
Fuzzy Inference ◽  
Control Measures ◽  
Future Research ◽  
Complex Nature ◽  
Inference System ◽  
Wide Range ◽  
Standard Models ◽  
High Level

Several outbreak prediction models for COVID-19 are being used by officials around the world to make informed-decisions and enforce relevant control measures. Among the standard models for COVID-19 global pandemic prediction, simple epidemiological and statistical models have received more attention by authorities, and they are popular in the media. Due to a high level of uncertainty and lack of essential data, standard models have shown low accuracy for long-term prediction. Although the literature includes several attempts to address this issue, the essential generalization and robustness abilities of existing models needs to be improved. This paper presents a comparative analysis of machine learning and soft computing models to predict the COVID-19 outbreak as an alternative to SIR and SEIR models. Among a wide range of machine learning models investigated, two models showed promising results (i.e., multi-layered perceptron, MLP, and adaptive network-based fuzzy inference system, ANFIS). Based on the results reported here, and due to the highly complex nature of the COVID-19 outbreak and variation in its behavior from nation-to-nation, this study suggests machine learning as an effective tool to model the outbreak. This paper provides an initial benchmarking to demonstrate the potential of machine learning for future research. Paper further suggests that real novelty in outbreak prediction can be realized through integrating machine learning and SEIR models.

Oxford Studies in Ancient Philosophy, Volume 55

2018 ◽  
Keyword(s):  
Middle Ages ◽  
Ancient Philosophy ◽  
Recent Book ◽  
Loss Of Control ◽  
Ancient Greek ◽  
Original Essays ◽  
Constant Change ◽  
Wide Range ◽  
Metaphysical Principle

Oxford Studies in Ancient Philosophy provides, twice each year, a collection of the best current work in the field of ancient philosophy. Each volume features original essays that contribute to an understanding of a wide range of themes and problems in all periods of ancient Greek and Roman philosophy, from the beginnings to the threshold of the Middle Ages. From its first volume in 1983, OSAP has been a highly influential venue for work in the field, and has often featured essays of substantial length as well as critical essays on books of distinctive importance. Volume LV contains: a methodological examination on how the evidence for Presocratic thought is shaped through its reception by later thinkers, using discussions of a world soul as a case study; an article on Plato’s conception of flux and the way in which sensible particulars maintain a kind of continuity while undergoing constant change; a discussion of J. L. Austin’s unpublished lecture notes on Aristotle’s Nicomachean Ethics and his treatment of loss of control (akrasia); an article on the Stoics’ theory of time and in particular Chrysippus’ conception of the present and of events; and two articles on Plotinus, one that identifies a distinct argument to show that there is a single, ultimate metaphysical principle; and a review essay discussing E. K. Emilsson’s recent book, Plotinus.

scholarly journals Consumer Neuroscience Techniques in Advertising Research: A Bibliometric Citation Analysis

2021 ◽  
Vol 13 (3) ◽  
pp. 1589
Author(s):  
Juan Sánchez-Fernández ◽  
Luis-Alberto Casado-Aranda ◽  
Ana-Belén Bastidas-Manzano
Keyword(s):  
Self Report ◽  
Future Research ◽  
Complex Nature ◽  
Clear Understanding ◽  
Continuous Growth ◽  
Main Research ◽  
Consumer Neuroscience ◽  
Starting Point ◽  
Wide Range ◽  
Performance Analysis Tools

The limitations of self-report techniques (i.e., questionnaires or surveys) in measuring consumer response to advertising stimuli have necessitated more objective and accurate tools from the fields of neuroscience and psychology for the study of consumer behavior, resulting in the creation of consumer neuroscience. This recent marketing sub-field stems from a wide range of disciplines and applies multiple types of techniques to diverse advertising subdomains (e.g., advertising constructs, media elements, or prediction strategies). Due to its complex nature and continuous growth, this area of research calls for a clear understanding of its evolution, current scope, and potential domains in the field of advertising. Thus, this current research is among the first to apply a bibliometric approach to clarify the main research streams analyzing advertising persuasion using neuroimaging. Particularly, this paper combines a comprehensive review with performance analysis tools of 203 papers published between 1986 and 2019 in outlets indexed by the ISI Web of Science database. Our findings describe the research tools, journals, and themes that are worth considering in future research. The current study also provides an agenda for future research and therefore constitutes a starting point for advertising academics and professionals intending to use neuroimaging techniques.

scholarly journals Assessing the Relation between Mud Components and Rheology for Loss Circulation Prevention Using Polymeric Gels: A Machine Learning Approach

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1377
Author(s):  
Musaab I. Magzoub ◽  
Raj Kiran ◽  
Saeed Salehi ◽  
Ibnelwaleed A. Hussein ◽  
Mustafa S. Nasser
Keyword(s):  
Machine Learning ◽  
Rheological Properties ◽  
Nearest Neighbor ◽  
Drilling Fluid ◽  
Gradient Boosting ◽  
K Nearest Neighbor ◽  
Wide Range ◽  
Machine Learning Approach ◽  
Drilling Operations

The traditional way to mitigate loss circulation in drilling operations is to use preventative and curative materials. However, it is difficult to quantify the amount of materials from every possible combination to produce customized rheological properties. In this study, machine learning (ML) is used to develop a framework to identify material composition for loss circulation applications based on the desired rheological characteristics. The relation between the rheological properties and the mud components for polyacrylamide/polyethyleneimine (PAM/PEI)-based mud is assessed experimentally. Four different ML algorithms were implemented to model the rheological data for various mud components at different concentrations and testing conditions. These four algorithms include (a) k-Nearest Neighbor, (b) Random Forest, (c) Gradient Boosting, and (d) AdaBoosting. The Gradient Boosting model showed the highest accuracy (91 and 74% for plastic and apparent viscosity, respectively), which can be further used for hydraulic calculations. Overall, the experimental study presented in this paper, together with the proposed ML-based framework, adds valuable information to the design of PAM/PEI-based mud. The ML models allowed a wide range of rheology assessments for various drilling fluid formulations with a mean accuracy of up to 91%. The case study has shown that with the appropriate combination of materials, reasonable rheological properties could be achieved to prevent loss circulation by managing the equivalent circulating density (ECD).

scholarly journals The Supportive Care Needs of Cancer Patients: a Systematic Review

2021 ◽  
Author(s):  
Madeleine Evans Webb ◽  
Elizabeth Murray ◽  
Zane William Younger ◽  
Henry Goodfellow ◽  
Jamie Ross
Keyword(s):  
Cancer Patients ◽  
Healthcare Professionals ◽  
Treatment Options ◽  
Complex Nature ◽  
Narrative Synthesis ◽  
Care Needs ◽  
Wide Range ◽  
Need Support ◽  
Lack Of Control ◽  
Everyday Work

AbstractCancer, and the complex nature of treatment, has a profound impact on lives of patients and their families. Subsequently, cancer patients have a wide range of needs. This study aims to identify and synthesise cancer patients’ views about areas where they need support throughout their care. A systematic  search of the literature from PsycInfo, Embase and Medline databases was conducted, and a narrative. Synthesis of results was carried out using the Corbin & Strauss “3 lines of work” framework. For each line of work, a group of key common needs were identified. For illness-work, the key needs idenitified were; understanding their illness and treatment options, knowing what to expect, communication with healthcare professionals, and staying well. In regards to everyday work, patients wanted to maintain a sense of normalcy and look after their loved ones. For biographical work, patients commonly struggled with the emotion impact of illness and a lack of control over their lives. Spiritual, sexual and financial problems were less universal. For some types of support, demographic factors influenced the level of need reported. While all patients are unique, there are a clear set of issues that are common to a majority of cancer journeys. To improve care, these needs should be prioritised by healthcare practitioners.

scholarly journals Using citizen science data to monitor the Sustainable Development Goals: a bottom-up analysis

2021 ◽  
Author(s):  
Laura Ballerini ◽  
Sylvia I. Bergh
Keyword(s):  
Sustainable Development ◽  
Citizen Science ◽  
Sustainable Development Goals ◽  
Comparative Case Study ◽  
Science Data ◽  
The Sustainable Development ◽  
Case Study Analysis ◽  
Wide Range ◽  
Development Goals

AbstractOfficial data are not sufficient for monitoring the United Nations Sustainable Development Goals (SDGs): they do not reach remote locations or marginalized populations and can be manipulated by governments. Citizen science data (CSD), defined as data that citizens voluntarily gather by employing a wide range of technologies and methodologies, could help to tackle these problems and ultimately improve SDG monitoring. However, the link between CSD and the SDGs is still understudied. This article aims to develop an empirical understanding of the CSD-SDG link by focusing on the perspective of projects which employ CSD. Specifically, the article presents primary and secondary qualitative data collected on 30 of these projects and an explorative comparative case study analysis. It finds that projects which use CSD recognize that the SDGs can provide a valuable framework and legitimacy, as well as attract funding, visibility, and partnerships. But, at the same time, the article reveals that these projects also encounter several barriers with respect to the SDGs: a widespread lack of knowledge of the goals, combined with frustration and political resistance towards the UN, may deter these projects from contributing their data to the SDG monitoring apparatus.

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