Relevant bibliographies by topics / Sustainability Analytics

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Sustainability Analytics'

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Published: 6 September 2023

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Journal articles on the topic "Sustainability Analytics"

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Lv, Zhihan, Rahat Iqbal, and Victor Chang. "Big data analytics for sustainability." Future Generation Computer Systems 86 (September 2018): 1238–41. http://dx.doi.org/10.1016/j.future.2018.05.020.

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Lein, James. "Projecting Regional Sustainability Trends Using Geospatial Analytics." Papers in Applied Geography 1, no. 2 (April 3, 2015): 119–27. http://dx.doi.org/10.1080/23754931.2015.1012428.

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Kobusińska, Anna, Kamil Pawluczuk, and Jerzy Brzeziński. "Big Data fingerprinting information analytics for sustainability." Future Generation Computer Systems 86 (September 2018): 1321–37. http://dx.doi.org/10.1016/j.future.2017.12.061.

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Marjaba, G. E., S. E. Chidiac, and A. A. Kubursi. "Sustainability framework for buildings via data analytics." Building and Environment 172 (April 2020): 106730. http://dx.doi.org/10.1016/j.buildenv.2020.106730.

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Aliabadi, Majid Moradi, and Yinlun Huang. "Vector-Based Sustainability Analytics: A Methodological Study on System Transition toward Sustainability." Industrial & Engineering Chemistry Research 55, no. 12 (December 28, 2015): 3239–52. http://dx.doi.org/10.1021/acs.iecr.5b03391.

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Kim, Kyoung-jae, Kichun Lee, and Hyunchul Ahn. "Predicting Corporate Financial Sustainability Using Novel Business Analytics." Sustainability 11, no. 1 (December 22, 2018): 64. http://dx.doi.org/10.3390/su11010064.

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Measuring and managing the financial sustainability of the borrowers is crucial to financial institutions for their risk management. As a result, building an effective corporate financial distress prediction model has been an important research topic for a long time. Recently, researchers are exerting themselves to improve the accuracy of financial distress prediction models by applying various business analytics approaches including statistical and artificial intelligence methods. Among them, support vector machines (SVMs) are becoming popular. SVMs require only small training samples and have little possibility of overfitting if model parameters are properly tuned. Nonetheless, SVMs generally show high prediction accuracy since it can deal with complex nonlinear patterns. Despite of these advantages, SVMs are often criticized because their architectural factors are determined by heuristics, such as the parameters of a kernel function and the subsets of appropriate features and instances. In this study, we propose globally optimized SVMs, denoted by GOSVM, a novel hybrid SVM model designed to optimize feature selection, instance selection, and kernel parameters altogether. This study introduces genetic algorithm (GA) in order to simultaneously optimize multiple heterogeneous design factors of SVMs. Our study applies the proposed model to the real-world case for predicting financial distress. Experiments show that the proposed model significantly improves the prediction accuracy of conventional SVMs.
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Ojokoh, Bolanle A., Oluwarotimi W. Samuel, Olatunji M. Omisore, Oluwafemi A. Sarumi, Peter A. Idowu, Emile R. Chimusa, Ashraf Darwish, Adebayo F. Adekoya, and Ferdinand A. Katsriku. "Big data, analytics and artificial intelligence for sustainability." Scientific African 9 (September 2020): e00551. http://dx.doi.org/10.1016/j.sciaf.2020.e00551.

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Lee, Picheng, Gary Kleinman, and Chu‐hua Kuei. "Using text analytics to apprehend urban sustainability development." Sustainable Development 28, no. 4 (February 19, 2020): 897–921. http://dx.doi.org/10.1002/sd.2045.

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Paz, Cristhian, Josune Sáenz, and Ana Ortiz-de-Guinea. "Data analytics in organic farming: Impact on environmental sustainability." European Conference on Knowledge Management 23, no. 2 (August 25, 2022): 895–903. http://dx.doi.org/10.34190/eckm.23.2.292.

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The production of healthy food while preserving the environment constitutes one of the main challenges of the 21st century. Along these lines, organic farming has emerged as a farm management and food production system that encourages environmental sustainability. To enhance such sustainability, data analytics both as an asset and as a capability could play a substantial role. Indeed, data analytics could be used to interpret the past and predict the future and to make more timely or accurate decisions regarding the use and protection of natural resources. Using survey data from 119 Spanish organic farms whose digitization degree as reported by the farmer is above 0, and structural equation modeling based on partial least squares to test research hypotheses, we found that even though data analytics in organic farming is clearly underdeveloped, it still contributes to enhancing farms’ environmental sustainability. Thus, investments in environmental data analytics appear to pay off.
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Raghupathi, Viju, Jie Ren, and Wullianallur Raghupathi. "Identifying Corporate Sustainability Issues by Analyzing Shareholder Resolutions: A Machine-Learning Text Analytics Approach." Sustainability 12, no. 11 (June 10, 2020): 4753. http://dx.doi.org/10.3390/su12114753.

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Corporations have embraced the idea of corporate environmental, social, and governance (ESG) under the general framework of sustainability. Studies have measured and analyzed the impact of internal sustainability efforts on the performance of individual companies, policies, and projects. This exploratory study attempts to extract useful insight from shareholder sustainability resolutions using machine learning-based text analytics. Prior research has studied corporate sustainability disclosures from public reports. By studying shareholder resolutions, we gain insight into the shareholders’ perspectives and objectives. The primary source for this study is the Ceres sustainability shareholder resolution database, with 1737 records spanning 2009–2019. The study utilizes a combination of text analytic approaches (i.e., word cloud, co-occurrence, row-similarities, clustering, classification, etc.) to extract insights. These are novel methods of transforming textual data into useful knowledge about corporate sustainability endeavors. This study demonstrates that stakeholders, such as shareholders, can influence corporate sustainability via resolutions. The incorporation of text analytic techniques offers insight to researchers who study vast collections of unstructured bodies of text, improving the understanding of shareholder resolutions and reaching a wider audience.
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Dissertations / Theses on the topic "Sustainability Analytics"

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Dalmia, Nihar. "Evaluation of the business case for using analytics for corporate sustainability and overcoming the challenges in its execution." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/90235.

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Thesis: S.M. in Management Studies, Massachusetts Institute of Technology, Sloan School of Management, 2014.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 75-78).
in an age where organizations across industries and sectors are placing increasing importance on sustainability, leaders are looking for more accurate information to guide their decisions on sustainability-related issues. Analytics and big data have been recognized as valuable tools to advance sustainability efforts both at a community as well as an organizational level. In the last decade specially, tools have been adopted by many organizations to gather and analyze data relevant to sustainability, to gain insights through business intelligence tools and to extend visibility through the supply chain. However, with opportunities come challenges and questions remain about the validity of the business case for sustainability analytics. As sustainability analytics gains momentum, understanding, identifying and addressing the challenges that come along with its adoption is going to be critical for companies to be well prepared to take their sustainability efforts forward. This thesis evaluates the emergence of sustainability analytics and the business case for its adoption, identifies the challenges that hinder its success and points towards shifts in current approaches to overcome those obstacles. Further, two of the assumptions about big data are that organizations are 'swimming in a sea' of data and thus the challenges lie in finding valuable insights, and that challenges associated with big data are primarily technical in nature. This work investigates these claims from the perspective of sustainability analytics and aims to identify the opportunities and challenges that organizations must be aware of to maximize its sustainability efforts using analytics. Various cases and interviews are cited to support the analysis and arguments presented in this paper. Chapter 1 opens the paper with a discussion of the link between sustainability and analytics and the emergence of sustainability analytics. Chapter 2 investigates the expected and realized value based on the business case(s) for sustainability analytics. Chapter 3 evaluates the challenges that can lead to the failure in realization of this value and addresses common assumptions that contribute to this failure. Chapter 4 discusses and recommends a shift in the finance function as a key ingredient to the success of sustainability analytics. The paper concludes with a proposed strategic framework in Chapter 5 that organizations must consider in their pursuit of overcoming the challenges of successfully adopting sustainability analytics..
by Nihar Dalmia.
S.M. in Management Studies
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Rodriguez, Pellière Lineth Arelys. "A qualitative analysis to investigate the enablers of big data analytics that impacts sustainable supply chain." Thesis, Ecole centrale de Nantes, 2019. http://www.theses.fr/2019ECDN0019/document.

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Les académiques et les professionnels ont déjà montré que le Big Data et l'analyse prédictive, également connus dans la littérature sous le nom de BDPA, peuvent jouer un rôle fondamental dans la transformation et l'amélioration des fonctions de l'analyse de la chaîne d'approvisionnement durable (SSCA). Cependant, les connaissances sur la meilleure manière d'utiliser la BDPA pour augmenter simultanément les performances sociales, environnementale et financière. Par conséquent, avec les connaissances tirées de la littérature sur la SSCA, il semble que les entreprises peinent encore à mettre en oeuvre les pratiques de la SSCA. Les chercheursconviennent qu'il est encore nécessaire de comprendre les techniques, outils et facteurs des concepts de base de la SSCA pour adoption. C’est encore plus important d’intégrer BDPA en tant qu’atout stratégique dans les activités commerciales. Par conséquent, cette étude examine, par exemple, quels sont les facteurs de SSCA et quels sont les outils et techniques de BDPA qui permettent de mettre en évidence le 3BL (pour ses abréviations en anglais : "triple bottom line") des rendements de durabilité (environnementale, sociale et financière) via SCA.La thèse a adopté un constructionniste modéré, car elle comprend l’impact des facteurs Big Data sur les applications et les indicateurs de performance de la chaîne logistique analytique et durable. La thèse a également adopté un questionnaire et une étude de cas en tant que stratégie de recherche permettant de saisir les différentes perceptions des personnes et des entreprises dans l'application des mégadonnées sur la chaîne d'approvisionnement analytique et durable. La thèse a révélé une meilleure vision des facteurs pouvant influencer l'adoption du Big Data dans la chaîne d'approvisionnement analytique et durable. Cette recherche a permis de déterminer les facteurs en fonction des variables ayant une incidence sur l'adoption de BDPA pour SSCA, des outils et techniques permettant la prise de décision via SSCA et du coefficient de chaque facteur pour faciliter ou retarder l'adoption de la durabilité. Il n'a pas été étudié avant. Les résultats de la thèse suggèrent que les outils actuels utilisés par les entreprises ne peuvent pas analyser de grandes quantités de données par eux-mêmes. Les entreprises ont besoin d'outils plus appropriés pour effectuer ce travail
Scholars and practitioners already shown that Big Data and Predictive Analytics also known in the literature as BDPA can play a pivotal role in transforming and improving the functions of sustainable supply chain analytics (SSCA). However, there is limited knowledge about how BDPA can be best leveraged to grow social, environmental and financial performance simultaneously. Therefore, with the knowledge coming from literature around SSCA, it seems that companies still struggled to implement SSCA practices. Researchers agree that is still a need to understand the techniques, tools, and enablers of the basics SSCA for its adoption; this is even more important to integrate BDPA as a strategic asset across business activities. Hence, this study investigates, for instance, what are the enablers of SSCA, and what are the tools and techniques of BDPA that enable the triple bottom line (3BL) of sustainability performances through SCA. The thesis adopted moderate constructionism since understanding of how the enablers of big data impacts sustainable supply chain analytics applications and performances. The thesis also adopted a questionnaire and a case study as a research strategy in order to capture the different perceptions of the people and the company on big data application on sustainable supply chain analytics. The thesis revealed a better insight of the factors that can affect in the adoption of big data on sustainable supply chain analytics. This research was capable to find the factors depending on the variable loadings that impact in the adoption of BDPA for SSCA, tools and techniques that enable decision making through SSCA, and the coefficient of each factor for facilitating or delaying sustainability adoption that wasn’t investigated before. The findings of the thesis suggest that the current tools that companies are using by itself can’t analyses data. The companies need more appropriate tools for the data analysis
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Aldherwi, Aiman. "Conceptualising a Procurement 4.0 Model for a truly Data Driven Procurement." Thesis, KTH, Hållbar produktionsutveckling (ML), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-297583.

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Purpose - Procurement is an integrated part of the supply chain and crucial for the success of manufacturing. Many organisations have already started the digitalisation of their manufacturing processes using Industry 4.0 technologies and consequently trying to understand how this would impact the procurement function. The research purpose is to conceptualize a procurement of 4.0 model for a truly data driven procurement. Two research questions were proposed to address the model from digital capabilities and sustainability preceptive. Design/Methodology/approach - This study is based on a systematic literature review. A method of reviewing the literature and the current research for the propose of conceptualizing a procurement 4.0 model. Findings - The findings from the literature review contributed to the development of a proposed procurement 4.0 model based on Industry 4.0 technologies, applications, mathematical algorithms and procurement processes automation. The model contributes to the research field by addressing the gap in the literature about the lack of visualization and conceptualization of procurement 4.0. Originality/Value - The current literature discusses the advantages, implementation and impact of individual or a group of industry 4.0 technologies and applications on procurement but lacks visualization of the transformation process of combining the technologies to enable a truly data driven procurement. This research supports the creation of knowledge in this area. Practical Implementation /Managerial Implications - The proposed model can support managers and digital consultants to have practical knowledge from an academic perspective in the area of procurement 4.0. The knowledge from the literature and the systematic literature review is used to create knowledge on procurement 4.0 applications and analytics taking in to consideration the importance of visibility, transparency, optimization and the automation of the procurement function and its sustainability.
Syfte - Upphandling är en integrerad del av supply chain och avgörande för tillverkningens framgång. Många organisationer har redan börjat digitalisera sina tillverkningsprocesser med hjälp av Industry 4.0-teknologier och försöker därför förstå hur detta skulle påverka upphandlingsfunktionen. Målet med studien är att konceptualisera en upphandling av 4.0-modellen för en verkligt datadriven upphandling. Två forskningsfrågor föreslogs för att ta itu med modellen från digital kapacitet och hållbarhet. Design / metod / tillvägagångssätt - Denna studie baseras på en systematisk litteraturstudie. En metod för att granska litteraturen och den aktuella forskningen för att föreslå konceptualisering av en upphandlings 4.0-modell. Resultat - Resultaten från litteraturstudien bidrog till utvecklingen av en föreslagen upphandlings 4.0-modell baserad på Industry 4.0-teknologier, applikationer, matematiska algoritmer och automatisering av upphandlingsprocesser. Modellen bidrar till forskningsområdet genom att ta itu med klyftan i litteraturen om bristen på visualisering och konceptualisering av upphandling 4.0. Originalitet / värde - Den nuvarande litteraturen diskuterar fördelarna, implementeringen och effekten av individer eller en grupp av industri 4.0-teknologier och applikationer på upphandling men saknar visualisering av transformationsprocessen för att kombinera teknologierna för att skapa en verklig datadriven upphandling. Denna forskning stöder skapandet av kunskap inom detta område. Praktisk implementering / chefsimplikationer - Den föreslagna modellen kan stödja chefer och digitala konsulter att ha praktisk kunskap ur ett akademiskt perspektiv inom området upphandling 4.0. Kunskapen från litteraturen och den systematiska litteraturstudien används för att skapa kunskap om inköp 4.0 applikationer och analyser med beaktande av vikten av synlighet, transparens, optimering och automatisering av upphandlingsfunktionen och dess hållbarhet.
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Erhardt, Joachim [Verfasser], Christiane [Akademischer Betreuer] Pott, and Andreas [Gutachter] Hoffjan. "Learning algorithms, and current developments – banking at the crossroads : Essays on Machine learning, Applied data analytics, asset encumbrance, Bail-in, sustainability and resource availability / Joachim Erhardt ; Gutachter: Andreas Hoffjan ; Betreuer: Christiane Pott." Dortmund : Universitätsbibliothek Dortmund, 2017. http://d-nb.info/116890336X/34.

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Park, Yujin. "Essays in Geospatial Modeling of Urban Green Infrastructure." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1588547971708147.

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Galal, Hana Sherin. "Integrating sustainability in municipal wastewater infrastructure decision-analysis using the analytic hierarchy process." Thesis, University of British Columbia, 2013. http://hdl.handle.net/2429/44590.

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New regulations from the Canadian Council of Ministers of Environment, released in 2009, require all wastewater treatment plants in Canada to produce effluent of secondary treatment levels. To comply with the new law, many Canadian municipalities using primary treatment plants must retrofit or renew their old systems. There is an increasing pressure from stakeholder groups and policy makers to select new infrastructure using triple-bottom-line (economic, environmental and social) analyses. The present study aims to illuminate how differing preferences among experts from different stakeholder groups influence what is considered to be the ‘most sustainable' wastewater treatment system. Through the use of policy documents, academic literature, and the use of AHP (a decision support tool: Analytic Hierarchy Process) an objectives hierarchy was constructed. The objectives hierarchy was made up of four criteria and 13 indicators. Five wastewater experts were asked to use pair-wise comparisons to score the indicators and criteria of the constructed objectives hierarchy and provide their opinions on the same. In addition, four low foot-print wastewater treatment alternatives were selected for review. One of the participants was asked to rank the four alternatives with regards to their performance on the selected indicators. This ranking, in combination with the rankings of the indicators and criteria, previously made by the five experts, were used to indicate the preferred alternatives for each of the separate participants. Then, the overall prioritization of the alternatives was used to carry out a sensitivity analysis. In terms of results, this study of sustainability indicators for wastewater treatment selection showed that the most contentious indicators among those studied were Initial Costs and Long Term Costs, Effluent Quality and Aesthetics. Additionally, the study showed that the Sequencing Batch Reactor was identified as the ‘most sustainable’ alternative by the average scores of all five participants and separately by four of the five participants.
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Kaplan, Samuel. "DEVELOPING A METHOD FOR THE ELECTROCEHMICAL CHARACTERIZATION OF NOVELNITROGEN-DOPED CARBONACEOUS CATALYSTS FOR CARBON DIOXIDE REDUCTION." Case Western Reserve University School of Graduate Studies / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=case1626451551046237.

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Acosta, Andino Byron Fabrício. "Proposta de uma estrutura analítica para a identificação do perfil de sustentabilidade de cadeias de suprimentos." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2011. http://hdl.handle.net/10183/32474.

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A produção de um bem é responsabilidade de todas as empresas que integram a cadeia de suprimentos, por conseguinte, as implicações socioambientais que esses produtos geram são também de responsabilidade de cada uma das empresas que integram essa cadeia. Assim, o comportamento socioambiental nas empresas precisa ser considerado ao longo da cadeia de suprimentos. Embora existam estudos relacionando sustentabilidade e cadeia de suprimentos, as pesquisas têm-se focado principalmente na dimensão ambiental e econômica. Os aspectos relacionados com as três dimensões da sustentabilidade de forma conjunta têm recebido pouca atenção na pesquisa. Além disso, os estudos têm considerado somente a empresa focal como unidade de análise e, raramente, essas pesquisas abrangem todos os membros que compõem a cadeia. Nesse contexto, a presente tese propõe desenvolver uma estrutura analítica para identificar o perfil de sustentabilidade de cadeias de suprimentos. No referencial teórico discute-se a dinâmica da sustentabilidade sob a visão das dimensões econômica, social e ambiental. Em seguida, apresentam-se os fundamentos da gestão da cadeia de suprimentos, identificando seus elementos-chave (estrutura, processos, e componentes). Posteriormente, relaciona-se a sustentabilidade com os elementos-chave de gestão por meio da cadeia de suprimentos sustentável. Por fim, o referencial teórico propõe a estrutura analítica de pesquisa, integrando parâmetros sustentáveis em cada elemento-chave da gestão da cadeia de suprimentos, objetivando a construção do perfil de sustentabilidade. Referente aos procedimentos metodológicos, a estrutura analítica foi testada em quatorze cadeias de suprimentos de rosas do Equador. Nesse tipo de cadeia, o produtor de rosas é considerado a empresa focal. As cadeias de suprimentos estão compostas por oito membros: a empresa focal e os sete fornecedores de primeiro nível. Os dados foram coletados com o uso de um questionário estruturado. Para estruturação das cadeias foi utilizada uma amostra de 312 empresas. Dessas, 42 responderam o questionário, ou seja, 13% do total. Foram usadas para a configuração das cadeias apenas 26 empresas. Com os dados obtidos foram construídos quatorze perfis, os quais descrevem a posição de sustentabilidade da cada empresa e da cadeia como se fosse uma única empresa. Adicionalmente, a forma em que o perfil é apresentado permite desdobrar as posições obtidas de cada empresa nas dimensões social, ambiental e econômica. Esse desdobramento possibilita identificar qual empresa obteve a maior ou a menor posição de forma global e por dimensão. A partir desses perfis, apresentam-se três tipos de análise: entre cadeias, entre os membros da cadeia, e entre as empresas que ocupam a mesma posição nas cadeias. Os resultados que a estrutura analítica gerou possibilitaram traçar perfis de sustentabilidade em cadeias de suprimentos de acordo com o objetivo proposto. O perfil caracteriza de forma simples a posição de sustentabilidade de uma cadeia, usando os mesmos parâmetros de mensuração em todos seus membros. Além disso, a forma como o perfil foi construído permite analisar a cadeia e seus membros nas dimensões social, ambiental e econômica, separadamente. Esse desdobramento facilita a identificação de brechas entre as dimensões e entre as empresas.
Manufacturing a good is a responsibility shared by all the enterprises integrating the supply chain; therefore, each enterprise of the chain should be held responsible for the socioenvironmental implications generated by these products. That being said, enterprises’ socioenvironmental behavior is an aspect to be taken into consideration along all the supply chain. Although there are studies relating sustainability and supply chain, researches have focused mainly on the environmental and economic dimensions. The aspects related to the three sustainability dimensions combined have received little research attention. Furthermore, studies have considered only the focal enterprise as an analysis unit, and these studies hardly ever encompass all the members composing the chain. In this context, this study attempts to develop an analytical structure in order to identify the sustainability profile of supply chains. In the theoretical background it is discussed the sustainability dynamics under the light of the economic, social and environmental dimensions. Afterwards, supply chain management basis are presented, identifying their key elements (structure, processes and components). Subsequently, sustainability is related to management key elements through a sustainable supply chain. The theoretical background proposes the research analytical structure, integrating sustainable parameters into each key element of the supply chain management, so as to build a sustainability profile. Regarding the methodological procedures, the analytical structure has been tested in fourteen rose supply chains in Ecuador. In this kind of chain, the rose grower is considered as the focal enterprise. The supply chains are composed of eight elements: the focal enterprise and seven first level suppliers. Data has been collected through a structured questionnaire. For the chain structuring a sample of 312 enterprises has been used. Out of these, 42 answered the questionnaire, that is, 13% of the total. Only 26 enterprises have been used to outline the chains. Fourteen profiles have been made with the data collected, describing the sustainability position of each enterprise and that of the chain, as if they were unique enterprises. Moreover, the way the profile is presented allows for the unfolding of the positions obtained by each enterprise in the social, environmental and economic dimensions. Such unfolding enables us to identify which enterprise has had the highest or lowest position globally or per dimension. Based on these profiles, three kinds of analysis have been presented: among chains, among chain members, and among enterprises occupying the same position in the chains. The outcomes from this analytical structure have enabled us to outline the sustainability profiles in supply chains according to the proposed aim. This profile characterizes in a simple way the sustainability position of a chain, applying the same measurement parameters to all its members. Furthermore, the way this profile has been built enables us to analyze the chain and its members in the social, environmental and economic dimensions separately. This unfolding makes it easier to identify gaps among the dimensions and the enterprises.
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Bohjort, Emelie. "Method verification for homocysteine and a sustainability study on glucose, homocysteine and lactate in different sampling tubes." Thesis, Uppsala universitet, Institutionen för kvinnors och barns hälsa, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-296043.

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The pre-analytical phase is known for being the most important step in the laboratory process to reach reliable test results. If handling, transport or preparation of the sample is performed incorrectly the results can deviate from the true value. Today, sampling tubes contains various additives to stabilize concentration levels. The aim of this study was to test a new sampling tube containing fluoride/citrate for glucose, lactate and homocysteine. It was also of interest to evaluate the stability of those three analytes in lithium-heparin, sodium-fluoride/potassium oxalate and fluoride/citrate tubes. To perform the sustainability study, a method verification was done for homocysteine in plasma. The study was performed in a hospital laboratory on the routine instrument Roche Cobas 6000 analyzer. Blood was drawn from 20 patients and was analyzed at the hospital laboratory in Gävle. The blood samples were transported frozen to the laboratory in Hudiksvall and were used in the method verification. For the sustainability study, blood was drawn from 10 healthy volunteers in lithium-heparin, sodium-fluoride/potassium oxalate and fluoride/citrate tubes. The method verification was approved. The results showed that glucose was stable for up to 72 hours in Vacuette Glycaemia tube with fluoride/citrate and this tube also gave more accurate results. Lactate and homocysteine were also stable in fluoride/citrate, but needs further studies. All three analytes were more stable if the sample tubes were centrifuged as soon as possible after blood collection. Fluoride/citrate tubes were stable without centrifugation directly.
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DE, MARINIS PIETRO. "PARTICIPATORY EVALUATION OF AGRICULTURAL DEVELOPMENT PROGRAMS AS A TOOL FOR IMPROVED SUSTAINABILITY IN DEVELOPMENT COOPERATION." Doctoral thesis, Università degli Studi di Milano, 2020. http://hdl.handle.net/2434/703261.

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‘Every human conduct that is not totally impulsive or just routine mechanics seems to be guided by an evaluation process’ (Dewey, 1939). Switching away from this individual definition of evaluation, the thesis acknowledges the definition given by OECD-DAC and focus the experimentation of well-known multicriteria decision aiding methodologies for ex-ante assessment in a specific development cooperation case study. Chapters 1 and 2, resume the structured bibliographic that has been conducted in order to identify an updated sample of literature about evaluation in development cooperation. During the evolution of the sector, several approaches and methodologies have been conceived and are continuously developing in order to match the variety of evaluanda and contexts. So, three main approaches can be defined, still keeping in mind that they are interlaced in their mutual evolution: the “Positivist-Experimental”, the “Pragmatist-Quality” and the “Constructive-Social Process” approaches group the contributions of several authors, ranging from the more theoretical philosophical basis to the development of specific methodologies and practical techniques. The reality of human development today, as defined by UN through SDGs, requests a multifaceted approach that is capable of mixing the existing approaches, methodologies and techniques. Pluralism of values and focus on the real use of evaluation results through participatory knowledge management are the key elements of the “Constructivist-Social Process approach” which is gaining attention in development cooperation evaluation systems. The literature review took in consideration the state of art of governmental and non-governmental organizations for worldwide and brought to the conclusion that ESs are nowadays in the middle of a renovation process which is far from being concluded. For this reason, we worked in order to provide new insights about sound methodologies able to integrate the different paradigms and methodologies in order to keep methodological robustness and allow a transformative evaluation process to take place in a specific case study. Chapter 3 frames our case study that is located in the Diocese of Goma, Nord Kivu, Democratic Republic of Congo. The framework for this case study is provided by a 3-year EU-funded project called ARDST ‘Appui au retour de réfugiés et déplacés par le biais de la sécurisation de terres en Diocèse de Goma’, led by Caritas Development Goma NGO. The project started in February 2016 and ended in June 2019. In this context our research group was asked to lead a strategic sectoral evaluation. The aim of the evaluation was to inform the choice of interventions meant to trigger sustainable agricultural development in the Diocese of Goma. Chapters 4 to 6 report the pre-print version of three scientific papers issued from the research. Chapter 4 deals with the sketching of a spatial decision support system aimed at Multi-Criteria Evaluation of potential pilot sites for agricultural development and refugees’ resettlement. Land disputes are considered both key sources and perpetuating factors of conflict in the eastern Democratic Republic of the Congo. Existing literature demonstrates that remote sensing is a useful tool for systematically monitor the spatial-temporal land use/land cover dynamics in many regions of the world. For this reason, in this Chapter we propose a methodology for the integration of different sources of information, namely satellite imagery and census information, in order to set up multi-method approach for evidence-based decision-making in development cooperation. Chapter 5 deals with the use of a simplified multicriteria decision-making methodology and namely the application of a simplified form of pairwise ranking (SPWR). International Aid initiatives involve complex real-world decision-making problems in all their relevant phases. Agri-environmental and generally landscape-scale issues are the typical target of participative decision-making procedures as they involve community resources planning. To successfully solve the complex real-world problems multi-criteria group decision-making approaches are recognized as reliable and effective. Main research questions are : What are the priorities for intervention in order to achieve sustainable development of the agricultural sector in the case study? Is SPWR a sound technique to prioritize different alternatives for intervention while improving group consensus in real-world complex cases? SPWR was found to be a useful technique for eliciting discussion among a multidisciplinary group for pointing out and discuss inconsistencies in decision makers’ preferences. Moreover, the final group ranking matches the existing guidelines for sustainable agricultural development in the region demonstrating that SPWR is a sound technique for prioritization of alternatives in the fields of agricultural development and international aid. Chapter 6 deals with the use of a modified form of analytic hierarchy process, namely the participatory analytic hierarchy process (PAHP), as a tool for choice criteria elicitation and resource allocation in the framework of our case study. 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. 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. Finally, in Chapter 7, we use the results of our research to support the proposal of the wider use of the experimented evaluation approaches and methodologies as tools for fostering the diffusion of evaluation culture in development cooperation, which in turns is a key objective to foster the impact of interventions aiming sustainability. In fact, in development cooperation, the dissemination at all levels of a culture of evaluation and the construction of solid, adaptive and inclusive feedback and decision-making systems are seen as possible solutions to the everlasting doubt about development cooperation impact. In our research, we experimented a methodological approach and some specific multicriteria participatory techniques that should be taken into account when trying to link in a completely interconnected chain, the cooperation results on different scales and to evaluate, both ex-ante and ex-post, its overall contribution towards the SDGs.
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Books on the topic "Sustainability Analytics"

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Siew, Renard. Sustainability Analytics Toolkit for Practitioners. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8237-8.

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Carayannis, Elias G., and Stavros Sindakis, eds. Analytics, Innovation, and Excellence-Driven Enterprise Sustainability. New York: Palgrave Macmillan US, 2017. http://dx.doi.org/10.1057/978-1-137-37879-8.

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Hjertholm, Peter. Debt relief and the rule of thumb: Analytical history of HIPC debt sustainability targets. Helsinki: United Nations University, World Institute for Development Economics Research, 2001.

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Kruseman, Gideon. Disentangling the concept of sustainability: Conceptual definitions, analytical framework and operational techniques in sustainable land use. Wageningen: Wageningen Agricultural University, 1993.

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Namibia. Ministry of Environment and Tourism and Namibia. Ministry of Lands and Resettlement, eds. Namibia: Land use planning and environmental sustainability : contributions to an analytical framework for sustainable land management. Windhoek: Directorate of Environmental Affairs, Ministry of Environment and Tourism, 2007.

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Namibia. Ministry of Environment and Tourism. and Namibia. Ministry of Lands and Resettlement., eds. Namibia: Land use planning and environmental sustainability : contributions to an analytical framework for sustainable land management. Windhoek, Namibia: Directorate of Environmental Affairs, Ministry of Environment and Tourism, 2007.

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Namibia. Ministry of Environment and Tourism. and Namibia. Ministry of Lands and Resettlement., eds. Namibia: Land use planning and environmental sustainability : contributions to an analytical framework for sustainable land management. Windhoek, Namibia: Directorate of Environmental Affairs, Ministry of Environment and Tourism, 2007.

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Public, Finance Workshop (2008 Perugia Italy). Fiscal sustainability: Analytical developments and emerging policy issues : papers presented at the Banca d'Italia workshop held in Perugia, 3-5 April, 2008. Roma, Italy: Banca d'Italia, 2008.

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Public Finance Workshop (2008 Perugia, Italy). Fiscal sustainability: Analytical developments and emerging policy issues : papers presented at the Banca d'Italia workshop held in Perugia, 3-5 April, 2008. Roma, Italy: Banca d'Italia, 2008.

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Public Finance Workshop (2008 Perugia, Italy). Fiscal sustainability: Analytical developments and emerging policy issues : papers presented at the Banca d'Italia workshop held in Perugia, 3-5 April, 2008. Roma, Italy: Banca d'Italia, 2008.

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Book chapters on the topic "Sustainability Analytics"

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Taniguchi, Eiichi, Russell G. Thompson, and Ali G. Qureshi. "Environmental sustainability." In Urban Freight Analytics, 129–35. Boca Raton: CRC Press, 2023. http://dx.doi.org/10.1201/9781003261513-12.

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Siew, Renard. "Sustainability Decision Analytics." In Sustainability Analytics Toolkit for Practitioners, 59–74. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8237-8_4.

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Siew, Renard. "Sustainability Communication." In Sustainability Analytics Toolkit for Practitioners, 113–27. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8237-8_7.

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Siew, Renard. "Sustainability Ratios." In Sustainability Analytics Toolkit for Practitioners, 101–12. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8237-8_6.

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Al Tal, Safwat. "Business Analytics and Sustainability." In Progress in IS, 33–44. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-12527-0_3.

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Siew, Renard. "Introduction to Sustainability Analytics." In Sustainability Analytics Toolkit for Practitioners, 1–6. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8237-8_1.

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Siew, Renard. "Analytics for Sustainability Issues." In Sustainability Analytics Toolkit for Practitioners, 151–204. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8237-8_9.

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Siew, Renard. "Sustainability Risks and Policies/Instruments." In Sustainability Analytics Toolkit for Practitioners, 205–16. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8237-8_10.

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Siew, Renard. "Building/Infrastructure Sustainability Analytical Tools (SATs)." In Sustainability Analytics Toolkit for Practitioners, 29–58. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8237-8_3.

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Siew, Renard. "Sustainable Development Goals (SDGs) Impact Investing Framework." In Sustainability Analytics Toolkit for Practitioners, 75–99. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8237-8_5.

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Conference papers on the topic "Sustainability Analytics"

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Yan, Lixiang, Linxuan Zhao, Dragan Gasevic, and Roberto Martinez-Maldonado. "Scalability, Sustainability, and Ethicality of Multimodal Learning Analytics." In LAK22: 12th International Learning Analytics and Knowledge Conference. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3506860.3506862.

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Bouttell, Adam B., Sijin Lee, Carson K. Leung, Martin J. Levesque, Seunggon Son, Weihong Zhang, and Alfredo Cuzzocrea. "Predictive Analytics for Supporting Environmental Sustainability and Disaster Management." In 2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC). IEEE, 2022. http://dx.doi.org/10.1109/compsac54236.2022.00198.

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Jayashree, Sreenivasan, Mohammad Nurul Hassan Reza, Chinnasamy Agamudai Malarvizhi, and Mazni Binti Alias. "Big Data Analytics and Educational Sustainability-A Malaysian Scenario." In 2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT). IEEE, 2023. http://dx.doi.org/10.1109/iceeict56924.2023.10157261.

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Gupta, Arnav, and Sujata Joshi. "Emerging Trends and Scope of Healthcare Analytics." In 2022 International Interdisciplinary Humanitarian Conference for Sustainability (IIHC). IEEE, 2022. http://dx.doi.org/10.1109/iihc55949.2022.10059883.

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Shahrokni, Hossein, Bram Van der Heijde, David Lazarevic, and Nils Brandt. "Big Data GIS Analytics Towards Efficient Waste Management in Stockholm." In ICT for Sustainability 2014 (ICT4S-14). Paris, France: Atlantis Press, 2014. http://dx.doi.org/10.2991/ict4s-14.2014.17.

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Kosianka, Justyna, Michael A. Allen, and Nicholas Rodgers. "Pre- and post-storm hurricane monitoring via data-driven SAR-based analytics." In Space, Satellites and Sustainability II, edited by Callum J. Norrie, Kristina Tamane, and Mathew Williams. SPIE, 2021. http://dx.doi.org/10.1117/12.2600975.

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Aguilar, Susanne, Daniel Kushner, Jim Ortega, Aleksi Paaso, Jackie Ratner, and Jeff Schlegelmilch. "Using Analytics to Inform Post-Pandemic Resiliency Strategy." In 2021 IEEE Conference on Technologies for Sustainability (SusTech). IEEE, 2021. http://dx.doi.org/10.1109/sustech51236.2021.9467473.

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Cetindamar, Dilek, Baraah Shdifat, and Shadi Erfani. "Assessing Big Data Analytics Capability and Sustainability in Supply Chains." In Hawaii International Conference on System Sciences. Hawaii International Conference on System Sciences, 2020. http://dx.doi.org/10.24251/hicss.2020.026.

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El-Gayar, Omar, PingSun Leung, and Arno Scharl. "Introduction to Analytics, Informatics and Decision Support for Sustainability Minitrack." In 2013 46th Hawaii International Conference on System Sciences (HICSS). IEEE, 2013. http://dx.doi.org/10.1109/hicss.2013.291.

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Wu, Pei-Ju, and Yi-Ching Chen. "Big data analytics for transport systems to achieve environmental sustainability." In 2017 International Conference on Applied System Innovation (ICASI). IEEE, 2017. http://dx.doi.org/10.1109/icasi.2017.7988401.

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Reports on the topic "Sustainability Analytics"

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Ke, Jian-yu, Fynnwin Prager, Jose Martinez, and Chris Cagle. Achieving Excellence for California’s Freight System: Developing Competitiveness and Performance Metrics; Incorporating Sustainability, Resilience, and Workforce Development. Mineta Transportation Institute, December 2021. http://dx.doi.org/10.31979/mti.2021.2023.

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This study explores the question of whether California's freight system is staying competitive with other US regions. A novel analytical framework compares supply chain performance metrics across multiple US states and regions for seaports, airports, highways, freight rail service, and distribution centers by combining the Performance Evaluation Matrix (PEM), Competitive Position Matrix (CPM), and Business Process Management (BPM) approaches. Analysis of industry data and responses from structured interviews with 30 freight industry experts across 5 transportation sectors suggests that California's freight system is competitive for seaports, airports, and freight rail; however, highways and distribution centers have room for improvement with respect to travel time reliability and operation costs, and California should prioritize infrastructure investments here. To stay competitive with the Texas and North East regions, state investments could also expand seaport container terminals and air cargo handling facilities, improve intermodal port connections and management of flows of chassis, container trucks, empty containers to ameliorate cargo backlogs and congestion on highways, at the ports, and at warehouses. The state could also invest in inland ports, transporting goods by rail directly from seaports to the Inland Empire or Central Valley.
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Banerjee, Onil, Martin Cicowiez, and Renato Vargas. Integrating the Value of Natural Capital in Evidence-Based Policy Making. Inter-American Development Bank, December 2020. http://dx.doi.org/10.18235/0002900.

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This paper describes how Natural Capital Accounting (NCA) can be integrated into economy wide analytical frameworks to enhance evidence based decision making. Examples from applications of the Integrated Environmental Economic Modelling (IEEM) Platform show how explicitly accounting for the contributions of the environment to the economy in economic forecasting can lead to substantially different policy recommendations, overcoming some of the scope limitations of traditional economic performance analysis. Furthermore, the paper describes how NCA can be integrated into more traditional economic performance measurements, such as the System of National Accounts and their indicators such as adjusted Gross Domestic Product and Genuine Savings. Integration of natural capital into economy-wide analytical frameworks leads to better policy uptake of research findings and it empowers policymakers to avoid short-sighted decisions, which, although they can generate short-term economic gain, can have adverse consequences for economic, social, and environmental sustainability in the long run.
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Chapagain, Saroj, Geetha Mohan, and Kensuke Fukushi. Water for Sustainable Development Casebook: Recognising the Value of Water for Sustainable Development. United Nations University Institute for the Advanced Study of Sustainability, 2022. http://dx.doi.org/10.53326/pznf3984.

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This casebook presents the outcomes of the Water for Sustainable Development (WSD) research project implemented by the United Nations University Institute for the Advanced Study of Sustainability (UNU-IAS) to improve regional environmental and economic policies in the case study countries. The project investigated the role of water in the sustainable development of four locations in Asia: Bali Province, Indonesia; Kaski District, Nepal; Visakhapatnam City, India; and Rayong Province, Thailand. Based on an Input-Output (IO) analysis, the research findings provide a comprehensive matrix of intersectoral dependence, in terms of economy, water consumption, and pollution loads, and offer policy directives for controlling water pollution. The publication is aimed at policymakers, water practitioners, researchers, and students interested in learning and utilising the analytical framework developed by WSD.
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A model of costs of a CBD programme. Population Council, 1995. http://dx.doi.org/10.31899/rh1995.1031.

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This study is a collaborative effort of the Population Council, New Delhi, and the Centre for Development and Population Activities, New Delhi. Cost analysis is an analytical tool that provides program managers and planners with information about existing and potential programs. Existing programs can be evaluated for efficiency and effectiveness, while the resource requirements of future programs can be estimated. In the context of family planning (FP) programs, cost analysis provides policymakers and program managers with sufficient data on efficient ways to meet the demand for FP services with available resources. As FP programs mature and requirements for the resources expands, research is required to shed light on such issues as cost effectiveness and program sustainability. A community-based distribution project in Samastipur district in Northern Bihar was effective in increasing the contraceptive prevalence rate by 3.6 percentage points. As noted in this report, the results of the cost analysis has been useful for expansion and replication of the model in Uttar Pradesh.
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