You're using an outdated browser. Please upgrade to a modern browser for the best experience.
Blockchain in Life Cycle Assessment
Edit
This entry is adapted from the peer-reviewed paper 10.3390/en14248292

Blockchain is a technology that is increasingly used in the modern world. Its creator is Satoshi Nakamoto, who in 2008 used this technology in cryptocurrencies.

life cycle assessment (LCA) blockchain management Internet of Things (IoT)

1. Blockchain

Blockchain is a technology that is increasingly used in the modern world. Its creator is Satoshi Nakamoto, who in 2008 used this technology in cryptocurrencies [1]. The idea of blockchain assumes creating data chains between any two pages and storing them in a distributed cloud environment [2]. This technology is most often associated with cryptocurrencies, financial markets, or transactions, still, it is more and more widely used in other areas of industry or economy—health care, smart energy, copyright protection [3][4][5][6][7][8]. Originally blockchain technology was used to create a peer-to peer network and focused on cryptography and smart contracts [9][10][11]. Illustrating the current, extensive range of blockchain technology use, one can use the visualization (Figure 1) developed by Casino et al. [12].
Energies 14 08292 g001 550
Figure 1. Mindmap abstraction of different types of blockchain applications. Source: Casino, F.; Dasaklis, T.K.; Patsakis, C. A systematic literature review of blockchain-based applications: Current status, classification and open issues. Telematics and Informatics 2019, 36, 62 [12].
By reviewing the literature in blockchain and the possibilities of its use, Xu et al. [12] pointed to, emphasized by many researchers [13][14][15][16][17][18][19], a feature that enables the collection and processing of vast amounts of data in real-time. It is the fundamental advantage of this technology, which implies such extensive use. Hence, the financial area has become a natural sector for using this technology [20]. Two branches of blockchain use out of the possibilities of using this technology indicated in Figure 1 [12] relate to: economy and industry, as well as data management. The organization of production processes, supply chains, and warehouse management requires processing considerable information. This is another area that is within the scope of the possibility of adopting blockchain technology [21][22]. Other areas of blockchain application are: medical sector [23][24][25][26][27][28][29][30], education [31] or management and logistics [32][33]. Since, as many researchers emphasize, blockchain is primarily a kind of database [9][34][35], which supports the reading and transmission of data (information). It is based on a decentralized structure that allows direct contact of users without the participation of an intermediary and at the same time ensures the security of event logs with the help of the use of a time stamp [36][37]. 

2. Life-Cycle Assessment

Dong et al. [38] (p. 4), while reviewing the literature, indicated the need to compare the environmental performance of buildings. The existing criteria have been developed based on: (1) the level of greenhouse gas emissions, (2) stages of the life cycle of a building, (3) absolute or relative value, (4) analysis of the entire building or its elements, and (5) top-down or bottom-up approaches (Hollbeerg et al. [39]) (see Table 1).
Table 1. Various types of benchmarks of LCA of buildings.
Table
Category Benchmarks Description
LIFE CYCLE STAGES Whole life cycle Benchmark is a value for the whole life cycle of the building.
  Life cycle phase Benchmark is a value for individual life cycle phases.
LEVELS OF VALUES Lowest acceptable value The limit value is defined as the lowest acceptable value.
  Present state of the art The average or median values of the present state of the art.
  Best-practice value The best-practice value that has been reached in building projects.
TOP-DOWN OR BOTTOM-UP Top-down Benchmarks are defined based on political targets.
  Bottom-up Most of the existing benchmarks are derived from theoretical values.
ABSOLUTE OR RELATIVE VALUES Absolute values Benchmarks are defined as fixed values.
  Relative values Internal benchmarks are defined according to a reference building.
WHOLE BUILDINGS OR BUILDING ELEMENTS Whole building Benchmarks are for the whole building.
  Building elements Benchmarks are for the individual building elements.
Source: Dong, Y.; Ng, S.T.; Liu, P. A comprehensive analysis towards benchmarking of life cycle assessment of buildings based on systematic review. Building and Environment 2021, 204, 108162, https://doi.org/10.1016/j.buildenv.2021.108162, [38] p. 4.
In order to carry out a systematic assessment of the impact of buildings, the emission levels should be analyzed quantitatively based on the impact analysis of each of the facilities tested. Therefore, each of the tested objects will be assessed separately, and its features will be taken into account, which is necessary for the interpretation of the environmental performance of buildings. Anand and Amor [40] indicate that there is still a research gap in this area, which makes it challenging to conduct a comparative analysis of buildings using the LCA method. Many researchers focused on reviewing the literature in the area of life-cycle assessment and its impact on the environmental assessment of buildings, which undoubtedly allowed to enrich and systematize knowledge in this area, which is an important step towards the elimination of the aforementioned barriers or problems with the use of this method. Khasreen et al. 2009 highlighted the importance of LCA as a decision support tool in the construction sector [41]. Ramesh et al. [42] performed a detailed analysis of the effectiveness of applying the LCA method in the environmental assessment of buildings on a large group of 73 cases from 13 countries. A similar research area was adopted by Sharma et al. [43], who also studied the performance of the LCA in assessing buildings located in different areas, but focused in particular on energy consumption by building types and greenhouse gas emissions. Rashid and Yusoff [44], Chau et al. [14] and Islam et al. [45] reviewed the LCA, Life Cycle Energy Analysis (LCEA) and Life-cycle cost analysis (LCCA) methods to distinguish building materials that have a significant impact on the environment. The problems with using the LCA method to compare the impact of individual buildings on the environment indicated by Anand and Amor [40] were analyzed by Soust-Verdaguer et al. [16], who identified possible simplifications for each study to develop LCA. A similar research area—verifications of the application nature of the LCA method for assessing the construction sector were carried out by Saynajoki et al. [15]. The applicative nature of LCA can be found in work by Vilches et al. [46], who investigated the impact on the environmental assessment of renovations and renovations of buildings carried out using the LCA method. Further possibilities of using LCA in Building Information Modeling (BIM) were investigated by: Lu et al. [47], Llatas et al. [48] and Potrc Obrecht et al. [49]. Lu et al. [47] performed a critical analysis of BIM integrated with LCA and life-cycle costing (LCC). Llatas et al. [48] focused on the possibility of integrating the Life Cycle Sustainability Assessment (LCSA) with the process of building design and BIM. Potrc Obrecht et al. [49] analyzed the advantages and disadvantages of various methods of the BIM integration process with LCA. The construction area is extensive, hence attempts to use the LCA method also for individual construction products. Yurong Zhang et al. [50] undertook a literature review on applying the LCA method in the concrete production process with the use of ore waste recycling. Concrete is the most widely used construction product. Its annual consumption is estimated at between 13 and 21 trillion tonnes [51]. Sustainable development requirements and the considerable production needs of concrete promote the use of waste materials in its production. The use of recycled aggregate concrete (RAC) is becoming more and more common, and the LCA method allows to compare the environmental impact of concrete production using the traditional natural aggregate concrete (NAC) and RAC methods [52][53][54]. Dong et al. [38] (p. 4), while reviewing the literature, indicated the need to compare the environmental performance of buildings. The existing criteria have been developed based on: (1) the level of greenhouse gas emissions, (2) stages of the life cycle of a building, (3) absolute or relative value, (4) analysis of the entire building or its elements, and (5) top-down or bottom-up approaches (Hollbeerg et al. [39]) (see Table 1).
To answer the research question—what emission levels should a building have throughout its life cycle, for different impact categories, respectively, Dong et al. [38] applied two research methods: (1) case study selection and (2) comparative analysis using CML 2001 [55] and IMPACT 2002+ [45]. As a result of the research, the factors influencing the environment of the building’s life cycle (including three stages: (1) production, (2) use and (3) end-of-life) were identified and grouped by categories (Table 2).
Table 2. Description of the impact categories and the conversion factors.
Table
Impact Category Indicator Unit Referecne Method Conversion Factors
CLIMATE CHANGE Global warming potential for time horizon 100 years kg CO2 eq CML Non Specified: 1
TRACI:1.012
IMPACT
2002+: 1.048
ReCiPe: 0.983
ENERGY DEPLETION Abiotic depletion of fossil fuel related to the lower heating value MJ CML Non specified: 1
TRACI:
12.672
IMPACT
2002+: 0.958
ReCiPe:
42.748
EUTROPHICATION Eutrophication potential of emission of nutrients kg PO4 eq CML Non specified: 1 TRACI: 0.471 IMPACT 2002+: 10.397 ReCiPe: 3.951
ACIDIFICATION Acidification potential kg SO2 eq CML Non specified: 1
TRACI: 1.061
IMPACT
2002+: 1.058
ReCiPe: 1.227
OZONE DEPLETION Ozone depletion
potential of different
gases		 kg CFC-11 eq CML Non specified: 1 TRACI: 0.770 IMPACT 2002+: 1 ReCiPe: 0.159
PARTICULATE MATTER Fine particulate matter equivalent for respiratory inorganics kg PM2.5 eq IMPACT 2002+ Non specified: 1 TRACI: 0.942 ReCiPe: 0.659
HUMAN TOXICITY Human toxicity potential describing fate, exposure and effects of toxic substances kg 1,4-DB eq CML Non specified: 1 TRACI: N.A. IMPACT 2002+: N.A. ReCiPe: N.A.
Note: N.A.—not available. Source: Dong, Y.; Ng, S.T.; Liu, P. A comprehensive analysis towards benchmarking of life cycle assessment of buildings based on systematic review. Building and Environment 2021, 204, 108162, https://doi.org/10.1016/j.buildenv.2021.108162, [38] p. 6.
Dong et al. [38] indicated a correlation between the suggested categories, but two of them deserve special attention: climate change and energy depletion. Comparing types based on different units of measurement requires their prior normalization (Figure 2).
Energies 14 08292 g002 550
Figure 2. Normalized medians of impact categories for the entire life cycle of buildings (50-years’ service life). Source: Dong, Y.; Ng, S.T.; Liu, P. A comprehensive analysis towards benchmarking of life cycle assessment of buildings based on systematic review. Building and Environment 2021, 204, 108162, https://doi.org/10.1016/j.buildenv.2021.108162, [56] p. 12.

3. Life-Cycle Assessment Based on Blockchain Technology

The research question posed in this article regarding the possibility of supporting the use of blockchain technology in the LCA method requires illustrating its impact on the traditional structure of the LCA model [53] (Figure 3). It is worth recalling that blockchain technology allows: (1) to ensure traceability and transparency of the goal and scope definition, (2) at the inventory analysis level—by using the Internet of Things (IoT) concept, collecting and integrating data collected in real-time, and (3) at the level of impact assessment—create analytical forms [57] (Figure 4).
Energies 14 08292 g003 550
Figure 3. Life Cycle Assessment Framework. Source: ISO. Environmental management—Life Cycle Assessment—Principles and Framework. International Organization for Standardization 2011, 3, 20. https://doi.org/10.1016/j.ecolind.2011.01.007 [53].
Energies 14 08292 g004 550
Figure 4. Blockchain-based LCA Framework. Source: Zhang, A. et al. Blockchain-based life cycle assessment: An implementation framework and system architecture, Resources, Conservation and Recycling. Volume 152, January 2020, https://doi.org/10.1016/j.resconrec.2019.104512, [57] p. 4.
The four phases (levels) of the LCA method defined by the ISO standard are supported by blockchain allowing operational excellence at all levels. The problem of the analysis and comparability of a large number of data in the LCA method, indicated in the literature on the subject, appears at its first stage. According to the assumption, LCA should comprehensively examine the product life cycle, from obtaining raw materials, production, use of the product, its reuse, maintenance, recycling, and finally its disposal [58]. The time constraints mentioned by the researchers, data availability, and financial resources will have the final impact on the effectiveness of the LCA method [22]. Genovese et al. [59] indicate that the use of blockchain solves other LCA problems of quantitative data regarding material and energy consumption in production processes, which are diagnosed by Rebitzer et al. [60] on the second level. The use of blockchain and IoT technologies at the third level of the LCA—impact assessment allows for much more detailed analyzes. The IoT technology is supported by sensors and devices that generate a huge amount of data in real-time, which allows for a more precise determination of the potential influence of the discussed impact categories, e.g., energy consumption or climate change [56][61][62]. The use of blockchain in the three phases of the LCA method allows, in the last, fourth—interpretative stage, to properly assess the product life cycle based only on relevant data. Moreover, the mentioned collection of vast amounts of data in real-time significantly increases the possibilities and functionalities of the LCA method: better use of production resources [63][64], more efficient management of supply chains [65], reduction of production time [66], and consequently gaining a competitive advantage by enterprises [67].

References

  1. Nakamoto, S. Bitcoin: A Peer-to-Peer Electronic Cash System. 2008. Available online: https://bitcoin.org/bitcoin.pdf (accessed on 17 October 2021).
  2. Iansiti, M.; Lakhani, K.R. The truth about blockchain. Harv. Bus. Rev. 2017, 95, 118–127.
  3. Engelhardt, M.A. Hitching Healthcare to the Chain: An Introduction to Blockchain Technology in the Healthcare Sector. Technol. Innov. Manag. Rev. 2017, 7, 22–34.
  4. Hyvarinen, H.; Risius, M.; Friis, G. A Blockchain-based approach towards overcoming financial fraud in public sector services. Bus. Inf. Syst. Eng. 2017, 59, 441–456.
  5. Kim, H.M.; Laskowski, M. Toward an ontology-driven blockchain design for supply-chain provenance. Intell. Syst. Account. Financ. Manag. 2018, 25, 18–27.
  6. O’Dair, M.; Beaven, Z. The networked record industry: How blockchain technology could transform the record industry. Strateg. Chang. 2017, 26, 471–480.
  7. Radanovic, I.; Likić, R. Opportunities for Use of Blockchain Technology in Medicine. Appl. Health Econ. Health Policy 2018, 16, 583–590.
  8. Savelyev, A. Copyright in the blockchain era: Promises and challenges. Comput. Law Secur. Rev. 2018, 34, 550–561.
  9. Christidis, K.; Devetsikiotis, M. Blockchains and smart contracts for the internet of things. IEEE Access 2016, 4, 2292–2303. Available online: https://people.cs.pitt.edu/~mosse/courses/cs3720/blockchain-iot.pdf (accessed on 12 October 2021).
  10. Cruz, J.P.; Kaji, Y.; Yanai, N. RBAC-SC: Role-based access control using smart contract. IEEE Access 2016, 6, 12240–12251. Available online: https://ieeexplore.ieee.org/document/8307397 (accessed on 14 October 2021).
  11. Kraft, D. Difficulty control for blockchain-based consensus systems. Peer-Peer Netw. Appl. 2015, 9, 397–413.
  12. Xu, M.; Chen, X.; Kou, G. A systematic review of blockchain. Financ. Innov. 2019, 5, 27.
  13. World Energy Council. The Developing Role of Blockchain White Paper; World Energy Council: London, UK, 2017.
  14. Chau, C.K.; Leung, T.M.; Ng, W.Y. A review on life cycle assessment, life cycle energy assessment and life cycle carbon emis-sions assessment on buildings. Appl. Energy 2015, 143, 395–413.
  15. Säynäjoki, A.; Heinonen, J.; Junnila, S.; Horvath, A. Can life-cycle assessment produce reliable policy guidelines in the building sector? Environ. Res. Lett. 2017, 12, 13001.
  16. Soust-Verdaguer, B.; Llatas, C.; García-Martínez, A. Simplification in life cycle assessment of single-family houses: A review of recent developments. Build. Environ. 2016, 103, 215–227.
  17. Swan, M. Anticipating the Economic Benefits of Blockchain. Technol. Innov. Manag. Rev. 2017, 7, 6–13.
  18. Tapscott, D.; Tapscott, A. Blockchain Revolution: How the Technology behind Bitcoin Is Changing Money, Business, and the World; Portfolio: New York, NY, USA, 2016; 368p.
  19. Zadorozhnyi, Z.-M.V.; Muravskyi, V.; Shevchuk, O.A. Management accounting of electronic transactions with the use of cryptocurrencies. Financ. Credit Act. Probl. Theory Pract. 2018, 3, 169–177.
  20. Gomber, P.; Kauffman, R.J.; Parker, C.; Weber, B.W. On the Fintech Revolution: Interpreting the Forces of Innovation, Disruption, and Transformation in Financial Services. J. Manag. Inf. Syst. 2018, 35, 220–265.
  21. Ashta, A.; Biot-Paquerot, G. FinTech evolution: Strategic value management issues in a fast changing industry. Strateg. Chang. 2018, 27, 301–311.
  22. Matos, S.; Hall, J. Integrating sustainable development in the supply chain: The case of life cycle assessment in oil and gas and agricultural biotechnology. J. Oper. Manag. 2007, 25, 1083–1102.
  23. Brogan, J.; Baskaran, I.; Ramachandran, N. Authenticating Health Activity Data Using Distributed Ledger Technologies. Comput. Struct. Biotechnol. J. 2018, 16, 257–266.
  24. Manion, S.T.; Bizouati-Kennedy, Y. Blockchain for Medical Research: Accelerating Trust in Healthcare; Taylor & Francis: Boca Raton, FL, USA, 2020; p. 150.
  25. Ramzi Abujamra, D. Blockchain Applications in Healthcare and the Opportunities and the Advancements due to the New Information Technology Framework, in Advance in Computers. In Role of Blockchain Technology in IoT Applications; Shiho-Kim, G.C.D., Zhang, P., Eds.; Academic Press: Cambridge, MA, USA, 2019; Volume 115, Chapter 5; pp. 141–154.
  26. Randall, D.; Goel, P.; Abujamra, R. Blockchain Applications and Use Cases in Health Information Technology. J. Health Med. Inform. 2017, 8, 1–4.
  27. Shae, Z.; Tsai, J.J. On the Design of a Blockchain Platform for Clinical Trial and Precision Medicine. In Proceedings of the 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS), Atlanta, GA, USA, 5–8 June 2017; pp. 1972–1980.
  28. Shetty, S.; Liang, X.; Bowden, D.; Zhao, J.; Zhang, L. Blockchain-Based Decentralized Accountability and Self-Sovereignty in Healthcare Systems. In Business Transformation through Blockchain; Treiblmaier, H., Beck, R., Eds.; Springer International Publishing: Cham, Switzerland, 2019; Volume 2, pp. 119–149.
  29. Wang, X.; Shi, H. Research on Container Transportation Application Based on Blockchain Technology. In Proceedings of the Asia-Pacific Conference on Intelligent Medical 2018 & International Conference on Transportation and Traffic Engineering, Beijing, China, 21–23 December 2018; pp. 277–281.
  30. Wutthikarn, R.; Hui, Y.G. Prototype of blockchain in dental care service application based on hyperledger composer in hyperledger fabric framework. In Proceedings of the 2018 22nd International Computer Science and Engineering Conference (ICSEC), Chiang Mai, Thailand, 21–24 November 2018; pp. 1–4.
  31. Mehendale, M.S.; Kamble, A. Trust the system–blockchain technology and its application in education. J. Xian Univ. Archit. Technol. 2019. Available online: http://www.xajzkjdx.cn/gallery/128-dec2019.pdf (accessed on 21 November 2021).
  32. Álvarez-Díaz, N.; Herrera-Joancomartí, J.; Caballero-Gil, P. Smart contracts based on blockchain for logistics management. In Proceedings of the 1st International Conference on Medical and Health Informatics, Taichung, Taiwan, 20–22 May 2017; pp. 1–8.
  33. Polishchuk, A.I.Y.; Dyba, O. SMART-contracts via blockchain as the innovation tool for SMEs development. Econ. Stud. J. 2019, 39–53. Available online: https://www.ceeol.com/search/article-detail?id=831391 (accessed on 29 October 2021).
  34. Catalini, C.S.; Gans, J.S. Some Simple Economics of the Blockchain. 2016. Available online: https://ssrn.com/abstract=2887234 (accessed on 28 October 2021).
  35. Hofmann, A. Building Scalable Blockchain Applications—A Decision Process. In Designing for Digital Transformation. Co-Creating Services with Citizens and Industry; Springer International Publishing: Cham, Switzerland, 2020; pp. 309–320.
  36. Gipp, B.; Meuschke, N.; Gernandt, A. Decentralized Trusted Timestamping using the Crypto Currency Bitcoin. In Proceedings of the iConference 2015 (to Appear), Newport Beach, CA, USA, 24–27 March 2015; Available online: http://ischools.org/the-iconference/ (accessed on 15 September 2021).
  37. Zyskind, G.; Nathan, O.; Pentland, A. Decentralizing Privacy: Using Blockchain to Protect Personal Data. In Proceedings of the 2015 IEEE Security and Privacy Workshops, San Jose, CA, USA, 21–22 May 2015; pp. 180–184.
  38. Dong, Y.; Ng, S.T.; Liu, P. A comprehensive analysis towards benchmarking of life cycle assessment of buildings based on systematic review. Build. Environ. 2021, 204, 108162.
  39. Hollberg, A.; Lützkendorf, T.; Habert, G. Top-down or bottom-up?—How environmental benchmarks can support the design process. Build. Environ. 2019, 153, 148–157.
  40. Anand, C.K.; Amor, B. Recent developments, future challenges and new research directions in LCA of buildings: A critical review. Renew. Sustain. Energy Rev. 2017, 67, 408–416.
  41. Khasreen, M.M.; Banfill, P.F.G.; Menzies, G.F. Life-Cycle Assessment and the Environmental Impact of Buildings: A Review. Sustainability 2009, 1, 674–701.
  42. Ramesh, T.; Prakash, R.; Shukla, K.K. Life cycle energy analysis of buildings: An overview. Energy Build. 2010, 42, 1592–1600.
  43. Sharma, A.; Saxena, A.; Sethi, M.; Shree, V. Varun Life cycle assessment of buildings: A review. Renew. Sustain. Energy Rev. 2011, 15, 871–875.
  44. Rashid, A.F.A.; Yusoff, S. A review of life cycle assessment method for building industry. Renew. Sustain. Energy Rev. 2015, 45, 244–248.
  45. Islam, H.; Jollands, M.; Setunge, S. Life cycle assessment and life cycle cost implication of residential buildings—A review. Renew. Sustain. Energy Rev. 2015, 42, 129–140.
  46. Vilches, A.; Garcia-Martinez, A.; Sanchez-Montanes, B. Life cycle assessment (LCA) of building refurbishment: A literature review. Energy Build. 2017, 135, 286–301.
  47. Lu, K.; Jiang, X.; Yu, J.; Tam, V.W.; Skitmore, M. Integration of life cycle assessment and life cycle cost using building information modeling: A critical review. J. Clean. Prod. 2021, 285, 125438.
  48. Llatas, C.; Soust-Verdaguer, B.; Passer, A. Implementing Life Cycle Sustainability Assessment during design stages in Building Information Modelling: From systematic literature review to a methodological approach. Build. Environ. 2020, 182, 107164.
  49. Obrecht, T.P.; Röck, M.; Hoxha, E.; Passer, A. BIM and LCA Integration: A Systematic Literature Review. Sustainability 2020, 12, 5534.
  50. Zhang, Y.; Luo, W.; Wang, J.; Wang, Y.; Xu, Y.; Xiao, J. A review of life cycle assessment of recycled aggregate concrete. Constr. Build. Mater. 2019, 209, 115–125.
  51. World Business Council for Sustainable Development (WBCSD). The Cement Sustainability Initiative; World Business Council for Sustainable Development: Geneva, Switzerland, 2009.
  52. International Organization for Standardization Website. ISO 14001:2015. Environmental Management Systems—Requirements with Guidance for Use. Available online: https://www.iso.org/standard/60857.html (accessed on 8 October 2021).
  53. Singh, R.K.; Murty, H.; Gupta, S.; Dikshit, A.K. An overview of sustainability assessment methodologies. Ecol. Indic. 2012, 15, 281–299.
  54. Yang, J.; Du, Q.; Bao, Y. Concrete with recycled concrete aggregate and crushed clay bricks. Constr. Build. Mater. 2011, 25, 1935–1945.
  55. Guinée, J.B.; Gorrée, M.; Heijungs, R.; Huppes, G.; Kleijn, R.; de Koning, A.; van Oers, L.; Sleeswijk, A.W.; Suh, S.; de Haes, H.A.; et al. Handbook on Life Cycle Assessment. Operational Guide to the ISO Standards. I: LCA in Perspective. IIa: Guide. IIb: Operational Annex. III: Scientific Background; Kluwer Academic Publishers: Dordrecht, The Netherlands, 2002; p. 692. ISBN 1-4020-0228-9.
  56. Kouhizadeh, M.; Sarkis, J. Blockchain Practices, Potentials, and Perspectives in Greening Supply Chains. Sustainability 2018, 10, 3652.
  57. Zhang, A.; Zhong, R.Y.; Farooque, M.; Kang, K.; Venkatesh, V.G. Blockchain-based life cycle assessment: An implementation framework and system architecture. Resour. Conserv. Recycl. 2020, 152, 104512.
  58. Christensen, T.H.; Bhander, G.; Lindvall, H.; Larsen, A.W.; Fruergaard, T.; Damgaard, A.; Manfredi, S.; Boldrin, A.; Riber, C.; Hauschild, M. Experience with the use of LCA-modelling (EASEWASTE) in waste management. Waste Manag. Res. 2007, 25, 257–262.
  59. Genovese, A.; Acquaye, A.A.; Figueroa, A.; Koh, S.L. Sustainable supply chain management and the transition towards a circular economy: Evidence and some applications. Omega 2017, 66, 344–357.
  60. Rebitzer, G.; Ekvall, T.; Frischknecht, R.; Hunkeler, D.; Norris, G.; Rydberg, T.; Schmidt, W.-P.; Suh, S.; Weidema, B.P.; Pennington, D.W. Life cycle assessment: Part 1: Framework, goal and scope definition, inventory analysis, and applications. Environ. Int. 2004, 30, 701–720.
  61. Jolliet, O.; Dubreuil, A.; Gloria, T.; Hauschild, M.Z. Progresses in Life Cycle Impact Assessment within the UNEP/SETAC Life Cycle Initiative. Int. J. Life Cycle Assess. 2005, 10, 447–448.
  62. Krishna, I.M.; Manickam, V.; Shah, A.; Davergave, N. Chapter Five—Life Cycle Assessment. In Environmental Management: Science and Engineering for Industry; Butterworth Henneman Elsevier: Oxford, UK, 2017; pp. 57–75.
  63. Cai, Y.; Zhu, D. Fraud detections for online businesses: A perspective from block chain technology. Financ. Innov. 2016, 2, 20.
  64. Tao, F.; Zuo, Y.; Xu, L.D.; Zhang, L. IoT-based intelligent perception and access of manufacturing resource toward cloud manufacturing. IEEE Trans. Ind. Inform. 2014, 10, 1547–1557.
  65. Zhong, R.Y.; Huang, G.Q.; Lan, S.; Dai, Q.Y.; Chen, X.; Zhang, T. A big data ap proach for logistics trajectory discovery from RFID-enabled production data. Int. J. Prod. Econ. 2015, 165, 260–272.
  66. Zhong, R.Y.; Huang, G.Q.; Dai, Q.Y.; Zhang, T. Mining SOTs and dispatching rules from RFID-enabled real-time shopfloor production data. J. Intell. Manuf. 2012, 25, 825–843.
  67. Galletti, A.; Papadimitriou, D.-C. How Big Data Analytics Are Perceived as a Driver for Competitive Advantage: A Qualitative Study on Food Retailers; Uppsala University Department of Business Studies: Uppsala, Sweden, 2013; p. 53. Available online: http://www.diva-portal.org/smash/get/diva2:641706/FULLTEXT01.pdf (accessed on 12 October 2021).
More
© Text is available under the terms and conditions of the Creative Commons Attribution (CC BY) license; additional terms may apply. By using this site, you agree to the Terms and Conditions and Privacy Policy.
Upload a video for this entry
Information
Subjects: Management
Contributor MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register :
Jacek Wójcik
View Times: 2.2K
Revisions: 3 times (View History)
Update Date: 30 Dec 2021
Table of Contents
Academic Video Service
Feedback