Literatura académica sobre el tema "Sustainability Analytics"
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Artículos de revistas sobre el tema "Sustainability Analytics"
Lv, Zhihan, Rahat Iqbal y Victor Chang. "Big data analytics for sustainability". Future Generation Computer Systems 86 (septiembre de 2018): 1238–41. http://dx.doi.org/10.1016/j.future.2018.05.020.
Texto completoLein, James. "Projecting Regional Sustainability Trends Using Geospatial Analytics". Papers in Applied Geography 1, n.º 2 (3 de abril de 2015): 119–27. http://dx.doi.org/10.1080/23754931.2015.1012428.
Texto completoKobusińska, Anna, Kamil Pawluczuk y Jerzy Brzeziński. "Big Data fingerprinting information analytics for sustainability". Future Generation Computer Systems 86 (septiembre de 2018): 1321–37. http://dx.doi.org/10.1016/j.future.2017.12.061.
Texto completoMarjaba, G. E., S. E. Chidiac y A. A. Kubursi. "Sustainability framework for buildings via data analytics". Building and Environment 172 (abril de 2020): 106730. http://dx.doi.org/10.1016/j.buildenv.2020.106730.
Texto completoAliabadi, Majid Moradi y Yinlun Huang. "Vector-Based Sustainability Analytics: A Methodological Study on System Transition toward Sustainability". Industrial & Engineering Chemistry Research 55, n.º 12 (28 de diciembre de 2015): 3239–52. http://dx.doi.org/10.1021/acs.iecr.5b03391.
Texto completoKim, Kyoung-jae, Kichun Lee y Hyunchul Ahn. "Predicting Corporate Financial Sustainability Using Novel Business Analytics". Sustainability 11, n.º 1 (22 de diciembre de 2018): 64. http://dx.doi.org/10.3390/su11010064.
Texto completoOjokoh, Bolanle A., Oluwarotimi W. Samuel, Olatunji M. Omisore, Oluwafemi A. Sarumi, Peter A. Idowu, Emile R. Chimusa, Ashraf Darwish, Adebayo F. Adekoya y Ferdinand A. Katsriku. "Big data, analytics and artificial intelligence for sustainability". Scientific African 9 (septiembre de 2020): e00551. http://dx.doi.org/10.1016/j.sciaf.2020.e00551.
Texto completoLee, Picheng, Gary Kleinman y Chu‐hua Kuei. "Using text analytics to apprehend urban sustainability development". Sustainable Development 28, n.º 4 (19 de febrero de 2020): 897–921. http://dx.doi.org/10.1002/sd.2045.
Texto completoPaz, Cristhian, Josune Sáenz y Ana Ortiz-de-Guinea. "Data analytics in organic farming: Impact on environmental sustainability". European Conference on Knowledge Management 23, n.º 2 (25 de agosto de 2022): 895–903. http://dx.doi.org/10.34190/eckm.23.2.292.
Texto completoRaghupathi, Viju, Jie Ren y Wullianallur Raghupathi. "Identifying Corporate Sustainability Issues by Analyzing Shareholder Resolutions: A Machine-Learning Text Analytics Approach". Sustainability 12, n.º 11 (10 de junio de 2020): 4753. http://dx.doi.org/10.3390/su12114753.
Texto completoTesis sobre el tema "Sustainability Analytics"
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.
Texto completoCataloged 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
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.
Texto completoScholars 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
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.
Texto completoSyfte - 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.
Erhardt, Joachim [Verfasser], Christiane [Akademischer Betreuer] Pott y 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.
Texto completoPark, Yujin. "Essays in Geospatial Modeling of Urban Green Infrastructure". The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1588547971708147.
Texto completoGalal, 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.
Texto completoKaplan, 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.
Texto completoAcosta, 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.
Texto completoManufacturing 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.
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.
Texto completoDE, 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.
Texto completoLibros sobre el tema "Sustainability Analytics"
Siew, Renard. Sustainability Analytics Toolkit for Practitioners. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8237-8.
Texto completoCarayannis, Elias G. y 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.
Texto completoHjertholm, 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.
Buscar texto completoKruseman, Gideon. Disentangling the concept of sustainability: Conceptual definitions, analytical framework and operational techniques in sustainable land use. Wageningen: Wageningen Agricultural University, 1993.
Buscar texto completoNamibia. Ministry of Environment and Tourism y 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.
Buscar texto completoNamibia. Ministry of Environment and Tourism. y 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.
Buscar texto completoNamibia. Ministry of Environment and Tourism. y 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.
Buscar texto completoPublic, 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.
Buscar texto completoPublic 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.
Buscar texto completoPublic 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.
Buscar texto completoCapítulos de libros sobre el tema "Sustainability Analytics"
Taniguchi, Eiichi, Russell G. Thompson y Ali G. Qureshi. "Environmental sustainability". En Urban Freight Analytics, 129–35. Boca Raton: CRC Press, 2023. http://dx.doi.org/10.1201/9781003261513-12.
Texto completoSiew, Renard. "Sustainability Decision Analytics". En Sustainability Analytics Toolkit for Practitioners, 59–74. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8237-8_4.
Texto completoSiew, Renard. "Sustainability Communication". En Sustainability Analytics Toolkit for Practitioners, 113–27. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8237-8_7.
Texto completoSiew, Renard. "Sustainability Ratios". En Sustainability Analytics Toolkit for Practitioners, 101–12. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8237-8_6.
Texto completoAl Tal, Safwat. "Business Analytics and Sustainability". En Progress in IS, 33–44. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-12527-0_3.
Texto completoSiew, Renard. "Introduction to Sustainability Analytics". En Sustainability Analytics Toolkit for Practitioners, 1–6. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8237-8_1.
Texto completoSiew, Renard. "Analytics for Sustainability Issues". En Sustainability Analytics Toolkit for Practitioners, 151–204. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8237-8_9.
Texto completoSiew, Renard. "Sustainability Risks and Policies/Instruments". En Sustainability Analytics Toolkit for Practitioners, 205–16. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8237-8_10.
Texto completoSiew, Renard. "Building/Infrastructure Sustainability Analytical Tools (SATs)". En Sustainability Analytics Toolkit for Practitioners, 29–58. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8237-8_3.
Texto completoSiew, Renard. "Sustainable Development Goals (SDGs) Impact Investing Framework". En Sustainability Analytics Toolkit for Practitioners, 75–99. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8237-8_5.
Texto completoActas de conferencias sobre el tema "Sustainability Analytics"
Yan, Lixiang, Linxuan Zhao, Dragan Gasevic y Roberto Martinez-Maldonado. "Scalability, Sustainability, and Ethicality of Multimodal Learning Analytics". En LAK22: 12th International Learning Analytics and Knowledge Conference. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3506860.3506862.
Texto completoBouttell, Adam B., Sijin Lee, Carson K. Leung, Martin J. Levesque, Seunggon Son, Weihong Zhang y Alfredo Cuzzocrea. "Predictive Analytics for Supporting Environmental Sustainability and Disaster Management". En 2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC). IEEE, 2022. http://dx.doi.org/10.1109/compsac54236.2022.00198.
Texto completoJayashree, Sreenivasan, Mohammad Nurul Hassan Reza, Chinnasamy Agamudai Malarvizhi y Mazni Binti Alias. "Big Data Analytics and Educational Sustainability-A Malaysian Scenario". En 2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT). IEEE, 2023. http://dx.doi.org/10.1109/iceeict56924.2023.10157261.
Texto completoGupta, Arnav y Sujata Joshi. "Emerging Trends and Scope of Healthcare Analytics". En 2022 International Interdisciplinary Humanitarian Conference for Sustainability (IIHC). IEEE, 2022. http://dx.doi.org/10.1109/iihc55949.2022.10059883.
Texto completoShahrokni, Hossein, Bram Van der Heijde, David Lazarevic y Nils Brandt. "Big Data GIS Analytics Towards Efficient Waste Management in Stockholm". En ICT for Sustainability 2014 (ICT4S-14). Paris, France: Atlantis Press, 2014. http://dx.doi.org/10.2991/ict4s-14.2014.17.
Texto completoKosianka, Justyna, Michael A. Allen y Nicholas Rodgers. "Pre- and post-storm hurricane monitoring via data-driven SAR-based analytics". En Space, Satellites and Sustainability II, editado por Callum J. Norrie, Kristina Tamane y Mathew Williams. SPIE, 2021. http://dx.doi.org/10.1117/12.2600975.
Texto completoAguilar, Susanne, Daniel Kushner, Jim Ortega, Aleksi Paaso, Jackie Ratner y Jeff Schlegelmilch. "Using Analytics to Inform Post-Pandemic Resiliency Strategy". En 2021 IEEE Conference on Technologies for Sustainability (SusTech). IEEE, 2021. http://dx.doi.org/10.1109/sustech51236.2021.9467473.
Texto completoCetindamar, Dilek, Baraah Shdifat y Shadi Erfani. "Assessing Big Data Analytics Capability and Sustainability in Supply Chains". En Hawaii International Conference on System Sciences. Hawaii International Conference on System Sciences, 2020. http://dx.doi.org/10.24251/hicss.2020.026.
Texto completoEl-Gayar, Omar, PingSun Leung y Arno Scharl. "Introduction to Analytics, Informatics and Decision Support for Sustainability Minitrack". En 2013 46th Hawaii International Conference on System Sciences (HICSS). IEEE, 2013. http://dx.doi.org/10.1109/hicss.2013.291.
Texto completoWu, Pei-Ju y Yi-Ching Chen. "Big data analytics for transport systems to achieve environmental sustainability". En 2017 International Conference on Applied System Innovation (ICASI). IEEE, 2017. http://dx.doi.org/10.1109/icasi.2017.7988401.
Texto completoInformes sobre el tema "Sustainability Analytics"
Ke, Jian-yu, Fynnwin Prager, Jose Martinez y Chris Cagle. Achieving Excellence for California’s Freight System: Developing Competitiveness and Performance Metrics; Incorporating Sustainability, Resilience, and Workforce Development. Mineta Transportation Institute, diciembre de 2021. http://dx.doi.org/10.31979/mti.2021.2023.
Texto completoBanerjee, Onil, Martin Cicowiez y Renato Vargas. Integrating the Value of Natural Capital in Evidence-Based Policy Making. Inter-American Development Bank, diciembre de 2020. http://dx.doi.org/10.18235/0002900.
Texto completoChapagain, Saroj, Geetha Mohan y 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.
Texto completoA model of costs of a CBD programme. Population Council, 1995. http://dx.doi.org/10.31899/rh1995.1031.
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