A Method for an Integrated Sustainability Assessment of RFID Technology
Abstract
:1. Introduction
- What are the measures of the impact of the RFID system on the performance of the company’s processes in terms of sustainability in economic, environmental, and social dimensions;
- what is the importance of each measure of the impact of the RFID system on the performance of the company’s processes in terms of sustainability.
2. Literature Review
2.1. RFID Sustainability-Oriented Assessment
- General methods which cover the policy making level mostly;
- methods suited for specific technologies.
- What are the measures of the impact of the RFID system on the performance of the company’s processes in terms of sustainability in economic, environmental and social dimensions;
- what is the importance of each measure of the impact of the RFID system on the performance of the company’s processes in terms of sustainability.
2.2. Integrated Assessment of Techno-Organizational Ventures
- Complexity;
- relative easiness of measuring complex processes;
- sequential nature of the assessment process (three levels: holistic view—modules—measures);
- openness, allowing for including human and social factors;
- flexibility and adaptability, allowing for maintaining compatibility with other legacy assessment systems.
- It is transparent and modular, so the assessment is consistent and transparent as well;
- it is flexible and universal, so it can be adopted to almost any problem just by choosing modules and measures appropriate to its structure and assessed problem;
- it enables holistic approach and is not just reductionist, i.e., one measure can play different roles in different modules, e.g., a decrease of the carbon footprint is positive for environmental dimension, but it can have directly associated costs in an economic dimension impacting negatively on cash flow;
- it is easy in application, requires no additional training for staff, nor support from experts;
- it enables easy customization by assigning weights to modules and measures, some unimportant criteria could be skipped purposely;
- it incorporates all the TBL dimensions of sustainability;
- it could be easily supported with other methods (e.g., controlling, AHP);
- it is dynamic and the assessment could relate to different periods, as values of measures are changing.
3. Integrated Method for Sustainability Assessment of RFID Systems: Proposed IMAR Framework
3.1. Methodology
3.2. Scope and Modules in IMAR
- design and implementation of the RFID system (an analogy for joint Phase A and Phase B of IMATOV),
- exploitation of the RFID system (an analogy for joint Phase B and Phase C of IMATOV), and
- both previously mentioned (joint assessment of implementation and exploitation phases of the RFID system).
3.3. Measures in IMAR
3.3.1. Fragmented (Sectional) Simple Measures (FSM)
3.3.2. Fragmented (Sectional) Complex Measures (FCM)
3.3.3. Synthetic Measures (SM)
3.3.4. Techno-Operational Parameters (TOP)
3.3.5. Social and Environmental Parameters (SEP)
3.3.6. Other Modules
4. Results and Discussion—Validation of the IMAR Framework
- A real industrial example of RFID application was chosen to apply the IMAR framework;
- expert panels were chosen as a technique to collect opinions about the importance of modules within IMAR;
- multi-criteria decision making (i.e., AHP) was used to quantify opinions;
- criteria ranking was used for determining whether the assumed modular structure responds to the experts’ needs.
- The set of modules and measures for the assessment of the impact of the RFID system on the performance of the company’s processes in terms of sustainability economic, environmental, and social dimensions was defined (see Section 3.3) based on a literature review and participatory observations;
- the ranking of measures was developed based on expert panels and AHP pairwise comparisons; FSM and FCM modules were neglected by the experts, who pointed out that the SM module is sufficient for technical assessment, and MI, SM, and PIA modules are important from the economic perspective; the SEP module was also considered as being important, which confirms the need for holistic assessment considering all TBL pillars (the economy, environment, and society).
5. Conclusions
- companies will be able to assess the sustainability for investment in a given technology instead of a pure profitability assessment available through the use of single measures,
- technology providers will be able to work on its further development and improvement in terms of achieving sustainability, and
- companies will be aware of the benefits and technical risks of a given solution.
- analytical analysis in terms of the identification of sustainability assessment indicators system, applicable in an industrial environment,
- conducing sustainability-oriented project decision making for a greater sample size of companies,
- enabling data input for further risk simulation and modeling to monitor it in real case studies.
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Machado, C.G.; Winroth, M.P.; Ribeiro da Silva, E.H.D. Sustainable manufacturing in Industry 4.0: An emerging research agenda. Int. J. Prod. Res. 2020, 58, 1462–1484. [Google Scholar] [CrossRef]
- Hussain, S.; Jahanzaib, M. Sustainable manufacturing—An overview and a conceptual framework for continuous transformation and competitiveness. Adv. Prod. Eng. Manag. 2018, 13, 237–253. [Google Scholar] [CrossRef]
- Medić, N.; Anišić, Z.; Lalić, B.; Marjanović, U.; Brezocnik, M. Hybrid fuzzy multi-attribute decision making model for evaluation of advanced digital technologies in manufacturing: Industry 4.0 perspective. Adv. Prod. Eng. Manag. 2019, 14, 483–493. [Google Scholar] [CrossRef]
- Costanza, R.; Daly, L.; Fioramonti, L.; Giovannini, E.; Kubiszewskia, I.; Mortensen, L.F.; Pickett, K.E.; Ragnarsdottir, K.V.; De Vogli, R.; Wilkinson, R. Modeling and measuring sustainable wellbeing in connection with the UN Sustainable Development Goals. Ecol. Econ. 2016, 130, 350–355. [Google Scholar] [CrossRef]
- Cambridge Dictionary. Available online: https://dictionary.cambridge.org/pl/dictionary/english/sustainability (accessed on 26 August 2020).
- Sroufe, R. Integration and organizational change towards sustainability. J. Clean. Prod. 2017, 162, 315–329. [Google Scholar] [CrossRef]
- Rusinko, C.A. Green manufacturing: An evaluation of environmentally sustainable manufacturing practices and their impact on competitive outcomes. IEEE Trans. Eng. Manag. 2007, 54, 445–454. [Google Scholar] [CrossRef]
- Hacking, T.; Guthrie, P. A framework for clarifying the meaning of triple bottom-line, integrated, and sustainability assessment. Environ. Impact Assess. Rev. 2008, 28, 73–89. [Google Scholar] [CrossRef]
- Da Silva, P.R.S.; Amaral, F.G. An integrated methodology for environmental impacts and costs evaluation in industrial processes. J. Clean. Prod. 2009, 17, 1339–1350. [Google Scholar] [CrossRef]
- Finkbeiner, M.; Schau, E.M.; Lehmann, A.; Traverso, M. Towards Life Cycle Sustainability Assessment. Sustainability 2010, 2, 3309–3322. [Google Scholar] [CrossRef] [Green Version]
- Glavič, P.; Lukman, R. Review of sustainability terms and their definitions. J. Clean. Prod. 2007, 15, 1875–1885. [Google Scholar] [CrossRef]
- Ocampo, L.A.; Himang, C.M.; Kumar, A.; Brezocnik, M. A novel multiple criteria decision-making approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy AHP for mapping collection and distribution centers in reverse logistics. Adv. Prod. Eng. Manag. 2019, 14, 297–322. [Google Scholar] [CrossRef] [Green Version]
- Gladysz, B.; Kluczek, A. An indicators framework for sustainability assessment of RFID systems in manufacturing. In Advances in Manufacturing II: Vol. 1—Solutions for Industry 4.0, LNME.; Trojanowska, J., Ciszak, O., Machado, J.M., Pavlenko, I., Eds.; Springer: Cham, Switzerland, 2019; pp. 274–286. [Google Scholar] [CrossRef]
- Fescioglu-Unver, N.; Choi, S.H.; Sheen, D.; Kumara, S. RFID in production and service systems: Technology, applications and issues. Inform. Syst. Front. 2015, 17, 1369–1380. [Google Scholar] [CrossRef]
- Finkenzeller, K. RFID Handbook: Fundamentals and Applications in Contactless Smart Cards, Radio Frequency Identification and Near-Field Communication, 3rd ed.; John Wiley & Sons: New York, NY, USA, 2010. [Google Scholar] [CrossRef]
- Wang, K.-S. Intelligent and integrated RFID (II-RFID) system for improving traceability in manufacturing. Adv. Manuf. 2014, 2, 106–120. [Google Scholar] [CrossRef] [Green Version]
- Aliaga, C.; Ferreira, B.; Hortal, M.; Pancorbo, M.Á.; López, J.M.; Navas, F.J. Influence of RFID tags on recyclability of plastic packaging. Waste Manag. 2011, 31, 1133–1138. [Google Scholar] [CrossRef]
- Fonseca, L.M.; Domingues, J.P.; Pereira, M.T.; Figueiredo Martins, F.; Zimon, D. Assessment of Circular Economy within Portuguese Organizations. Sustainability 2018, 10, 2521. [Google Scholar] [CrossRef] [Green Version]
- Santoyo-Castelazo, E.; Azapagic, A. Sustainability assessment of energy systems: Integrating environmental, economic and social aspects. J. Clean. Prod. 2014, 80, 119–138. [Google Scholar] [CrossRef]
- Jeswani, H.K.; Azapagic, A.; Schepelmann, P.; Ritthoff, M. Options for broadening and deepening the LCA approaches. J. Clean. Prod. 2010, 18, 120–127. [Google Scholar] [CrossRef]
- Jeswani, H.K.; Azapagic, A. Water footprint: Methodologies and a case study for assessing the impacts of water use. J. Clean. Prod. 2011, 19, 1288–1299. [Google Scholar] [CrossRef]
- Bertoni, M.; Hallstedt, S.; Ola, I. A model-based approach for sustainability and value assessment in the aerospace value chain. Adv. Mech. Eng. 2015, 7. [Google Scholar] [CrossRef]
- Finnveden, G.; Nilsson, M.; Johansson, J.; Persson, Å.; Moberg, Å.; Carlsson, T. Strategic environmental assessment methodologies–Applications within the energy sector. Environ. Impact Assess. Rev. 2003, 23, 91–123. [Google Scholar] [CrossRef]
- Leach, M.; Scoones, I.; Stirling, A. Pathways to Sustainability: An Overview of the STEPS Centre Approach; STEPS Centre: Brighton, UK, 2007. [Google Scholar]
- Kluczek, A. A conceptual framework for sustainability assessment for technology. Sci. Papers Sil. Uni. Technol. Organ. Manag. Ser. 2018, 115, 173–212. [Google Scholar]
- Lawrence, D.P. PROFILE: Integrating Sustainability and Environmental Impact Assessment. Environ. Manag. 1997, 21, 23–42. [Google Scholar] [CrossRef] [PubMed]
- Wu, R.; Yang, D.; Chen, J. Social Life Cycle Assessment Revisited. Sustainability 2014, 6, 4200–4226. [Google Scholar] [CrossRef] [Green Version]
- Kluczek, A. An energy-led sustainability assessment of production systems—An approach for improving energy efficiency performance. Int. J. Prod Econ. 2019, 216, 190–203. [Google Scholar] [CrossRef]
- Höjer, M.; Ahlroth, S.; Dreborg, K.H.; Ekvall, T.; Finnveden, G.; Hjelm, O.; Hochschorner, E.; Nilsson, M.; Palm, V. Scenarios in selected tools for environmental systems analysis. J. Clean. Prod. 2008, 16, 1958–1970. [Google Scholar] [CrossRef]
- Sendra, C.; Gabarrell, X.; Vicent, T. Material flow analysis adapted to an industrial area. J. Clean. Prod. 2007, 15, 1875–1885. [Google Scholar] [CrossRef]
- Musango, J.K.; Brent, A.C.; Amigun, B.; Pretorius, L.; Müller, H. A system dynamics approach to technology sustainability assessment: The case of biodiesel developments in South Africa. Technovation 2012, 32, 639–651. [Google Scholar] [CrossRef] [Green Version]
- Turri, A.M.; Smith, R.J.; Kopp, S.W. Privacy and RFID technology: A review of regulatory efforts. J. Consum. Aff. 2017, 51, 329–354. [Google Scholar] [CrossRef]
- Denuwara, N.; Maijala, J.; Hakovirta, M. Sustainability benefits of RFID technology in the apparel industry. Sustainability 2019, 11, 6477. [Google Scholar] [CrossRef] [Green Version]
- Kanth, R.K.; Liljeberg, P.; Tenhunen, H.; Wan, Q.; Amin, Y.; Shao, B.; Chen, Q.; Zheng, L.; Kumar, H. Evaluating sustainability, environmental assessment and toxic emissions during manufacturing process of RFID based systems. In Proceedings of the 2011 IEEE Ninth International Conference on Dependable, Autonomic and Secure Computing; IEEE Computer Society: Washington, DC, USA, 2011; pp. 1066–1071. [Google Scholar] [CrossRef]
- Elkington, J. Accounting for the triple bottom line. Meas. Bus. Excell. 1998, 2, 18–22. [Google Scholar] [CrossRef]
- Van der Togt, R.; Bakker, P.J.M.; Jaspers, M.W.M. A framework for performance and data quality assessment of radio frequency identification (RFID) systems in health care settings. J. Biomed. Inform. 2011, 44, 372–383. [Google Scholar] [CrossRef] [PubMed]
- Fisher, J.A.; Monahan, T. Tracking the social dimensions of RFID systems in hospitals. Int. J. Med. Inform. 2008, 77, 176–183. [Google Scholar] [CrossRef]
- Grandinetti, J.J. Welcome to a new generation of entertainment: Amazon web services and the normalization of Big Data analytics and RFID tracking. Surveill. Soc. 2019, 17, 169–175. [Google Scholar] [CrossRef]
- Gasparatos, A.; Scolobig, A. Choosing the most appropriate sustainability assessment tool. Ecol. Econ. 2012, 80, 1–7. [Google Scholar] [CrossRef]
- Marciniak, S. Zespolona metoda oceny efektywności przedsięwzięć techniczno-organizacyjnych; Warsaw University of Technology Publishing House: Warsaw, Poland, 1989. [Google Scholar]
- Marciniak, S. Technology evaluation using modified integrated method of technical project assessment. In Advances in Production Management Systems: Innovative Production Management Towards Sustainable Growth, IFIPAICT.; Umeda, S., Nakano, M., Mizuyama, H., Hibino, H., Kiritsis, D., von Cieminski, G., Eds.; Springer: Cham, Switzerland, 2015; pp. 493–501. [Google Scholar] [CrossRef]
- Ejsmont, K. Holistic assessment method of intelligent technologies used in production processes. Procedia Eng. 2017, 182, 189–197. [Google Scholar] [CrossRef]
- Ejsmont, K. Holistic assessment of intelligent technologies: Top management’s perceptions. In Proceedings of the 9th International Conference on Engineering, Project, and Production Management (EPPM2018), MATEC Web Conference, Cape Town, South Africa, 24–26 September 2018; Volume 312, p. 05002. [Google Scholar] [CrossRef] [Green Version]
- Mehrjerdi, Y.Z. RFID and its benefits: A multiple case analysis. Assem. Autom. 2011, 31, 251–262. [Google Scholar] [CrossRef]
- Sari, K. Exploring the impacts of radio frequency identification (RFID) technology on supply chain performance. Eur. J. Oper. Res. 2010, 207, 174–183. [Google Scholar] [CrossRef]
- Baysan, S.; Ustundag, A. The cost–benefit models for RFID investments. In The Value of RFID; Ustundag, A., Ed.; Springer: London, UK, 2013; pp. 13–22. [Google Scholar] [CrossRef]
- Marciniak, S.; Ejsmont, K. Ocena przedsięwzięć techniczno-organizacyjnych typu eScop [Assessment of technical and organizational project eScop]. Econ. Organ. Enterp. 2015, 12, 17–32. [Google Scholar]
- Gladysz, B.; Santarek, K.; Lysiak, C. Dynamic spaghetti diagrams. A case study of pilot RTLS implementation. In Intelligent Systems in Production Engineering and Maintenance—ISPEM 2017, AISC; Burduk, A., Mazurkiewicz, D., Eds.; Springer: Cham, Switzerland, 2018; pp. 238–248. [Google Scholar] [CrossRef]
- Saaty, T.L. Fundamentals of Decision Making and Priority Theory with the Analytic Hierarchy Process; RWS Publications: Pittsburgh, PA, USA, 1994. [Google Scholar]
- Goepel, K.D. Implementation of an online software tool for the analytic hierarchy process (AHP-OS). Int. J. Anal. Hierarchy Process 2018, 10, 469–487. [Google Scholar] [CrossRef] [Green Version]
- Gladysz, B.; Santarek, K. An approach to RTLS selection. DEStech Trans. Eng. Technol. Res. 2018, 13–18. [Google Scholar] [CrossRef] [Green Version]
- Podsakoff, P.M.; MacKenzie, S.B.; Podsakoff, N.P. Sources of method bias in social science research and recommendations on how to control it. Annu. Rev. Psychol. 2012, 63, 539–569. [Google Scholar] [CrossRef] [PubMed] [Green Version]
FSM1: IT hardware | FSM1.1: fixed readers FSM1.1.1: pieces; FSM1.1.2: monetized value |
FSM1.2: antennas FSM1.2.1: pieces; FSM1.2.2: monetized value | |
FSM1.3: cabling FSM1.3.1: length; FSM1.3.2: monetized value | |
FSM1.4: mounting and fixtures FSM1.4.1: pieces; FSM1.4.2: monetized value | |
FSM1.5: mobile readers FSM1.5.1: pieces; FSM1.5.2: monetized value; FSM1.5.3: lifecycle | |
FSM1.6: tags FSM1.6.1: pieces; FSM1.6.2: monetized value; FSM1.6.3: lifecycle (not durability) | |
FSM1.7: tagging levels FSM1.7.1: number of levels used; FSM1.7.2: names of levels: unit, containers, returnable assets, etc. according with GS1 standards | |
FSM1.8: employed standards and frequencies | |
FSM1.9: servers | |
FSM1.10: desktops FSM1.10.1: pieces; FSM1.10.2: monetized value | |
FSM1.11: value of hardware | |
FSM1.12: number of operations | |
FSM1.13: operational time for equipment |
FCM1: work intensity and equipment utilization | FCM1.1: coverage and scope of the system (percentage of units tagged) |
FCM1.2: manual scans per day per worker | |
FCM1.3: automated scans per day per reader | |
FCM1.4: scans per day per tag FCM1.4.1: manual scans; FCM1.4.2: automated scans | |
FCM1.5: fraction of automated scans in the total number of scans | |
FCM1.6: number of handheld readers per worker | |
FCM1.7: utilization time for equipment type (operational time per total available time) | |
FCM1.8: no. of devices per tagged objects tags in circulation) FCM1.8.x: per specific equipment type | |
FCM1.9: fraction of identification unit times in total lead time | |
FCM2: experience | FCM2.1: RFID experience per worker in calendar units |
FCM2.2: trainings per workers FCM2.2.1: in events; FCM2.2.2: in hours |
SM1: cost measures | SM1.1: operating costs: SM1.1.1: in total; SM1.1.2: hardware in total; SM1.1.3: for category x; SM1.1.4: of waste treatment |
SM1.2: maintenance costs SM1.2.1: in total; SM1.2.2: hardware in total; SM1.2.3: for category x | |
SM1.3: cost of resources SM1.3.1: cost of electric energy; SM1.3.2: cost of resource x | |
SM1.4: unit cost of system exploitation SM1.4.1: per tagged object; SM1.4.2: per scan operation; SM1.4.3: per tagged object; SM1.4.4: per worker | |
SM1.5: costs of disposed hardware SM1.5.1: readers; SM1.5.2: tags; SM1.5.3: others | |
SM2: benefit measures | SM2.1: decrease in cost of working capital’s freezing SM2.1.1: monetized decrease of inventory levels; SM2.1.2: monetized decrease of lead times |
SM2.2: monetized decrease of inventory handling costs | |
SM2.3: monetized decrease of out of stock values | |
SM2.4: decrease costs in actions (e.g., incorrect deliveries effected from incorrect identification) | |
SM2.5: unit monetized benefits SM2.5.1: per tagged object; SM2.5.2: per tag in circulation; SM2.5.3: per reader; SM2.5.4: per worker | |
SM3: effectiveness measures | SM3.1: cost/benefit related measures SM3.1.1: unit benefits minus unit costs (unit profit); SM3.1.2: unit profit per tagged object; SM3.1.3: unit profit per identification operation; SM3.1.4: unit profit per reader; |
SM3.2: profitability measures SM3.2.1: return on assets; SM3.2.2: return on investment (and/or IRR, NPW, payback period) |
Level 1 | Level 2 | Level 3 | Level 4 | Level 5 | Global Priority |
---|---|---|---|---|---|
ME 11.5% | Labor efficiency: 50.0% | Decrease of cycle times (average): 6.5% | 0.4% | ||
Lead time (average) decrease: 33.6% | 1.9% | ||||
Increase of worker productivity: 19.9% | 1.1% | ||||
Decrease of errors: 40.0% | 2.3% | ||||
Inventory accuracy: 50.0% | Decrease of costs of frozen stocks: 20.0% | 1.2% | |||
Decrease of stocks in monetary values: 20.0% | 1.2% | ||||
Decrease of costs of inventory handling: 20.0% | 1.2% | ||||
Decrease of shrinkage in monetary values: 20.0% | 1.2% | ||||
Decrease of costs of shrinkage handling: 20.0% | 1.2% | ||||
MI 13.1% | Software investment costs: 25.0% | 3.3% | |||
Hardware investment: 75.0% | 9.8% | ||||
SM 16.8% | MRO costs: 66.7% | 11.2% | |||
Disposed hardware yearly costs: 33.3% | 5.6% | ||||
PIA 42.9% | ROI: 20.0% | 8.6% | |||
Payback period: 80.0% | 34.3% | ||||
SEP 15.7% | Environmental: 50.0% | Waste generation: 50.0% | Amount of waste: 75.0% | No. of tags disposed completely: 18.6% | 0.5% |
No. of tags circulating in the system: 8.4% | 0.2% | ||||
Electronic devices disposed: 53.4% | 1.6% | ||||
Electronic devices installed: 19.7% | 0.6% | ||||
Lifecycle & supply chain integration: 25.0% | Tags lifecycle duration in supply chain: 43.1% | 0.4% | |||
No. of tags reads in its lifecycle: 32.3% | 0.3% | ||||
No. of reading points in a supply chain: 15.9% | 0.2% | ||||
No. of supply chain echelons benefiting RFID: 8.6% | 0.1% | ||||
Waste reduction: 50.0% | Inventory accuracy: 50.0% | Decrease of stocks in units: 75.0% | 1.5% | ||
Decrease of shrinkage in units: 25.0% | 0.5% | ||||
Assets utilization: 50.0% | Decrease of paper documents: 8.3% | 0.2% | |||
Decrease of printing accessories: 4.4% | 0.1% | ||||
Decrease of number of assets: 8.2% | 0.2% | ||||
Decrease of the total value of assets: 14.1% | 0.3% | ||||
Decrease of fuel consumption in liters: 28.3% | 0.6% | ||||
Decrease of electricity consump. in kWh: 36.6% | 0.7% | ||||
Social: 50.0% | Public acceptability: 33.3% | Qualitative assessment of customers’ choice: 13.0% | 0.3% | ||
TEM in place: 6.9% | 0.2% | ||||
Qualitative assessment of threats by users: 22.6% | 0.6% | ||||
Additional staff: 39.8% | 1.0% | ||||
Relations improvement: 17.8% | 0.5% | ||||
Safety & health: 66.7% | No. of occupational accidents: 50.0% | 2.6% | |||
Air pollutant: 50.0% | 2.6% |
Scale | Group Results | CRMAX | ||
---|---|---|---|---|
Alt1 | Alt2 | Alt3 | ||
Standard linear | 20.0% | 25.7% | 54.3% | 9.0% |
Logarithmic | 3.9% | 30.2% | 46.0% | 4.1% |
Root square | 24.7% | 31.0% | 44.3% | 2.2% |
Inverse linear | 24.2% | 31.2% | 44.6% | 17.0% |
Balanced | 22.4% | 30.1% | 47.5% | 6.2% |
Balanced generalized | 21.6% | 29.3% | 49.1% | 2.3% |
Adaptive balanced | 20.2% | 27.9% | 51.9% | 8.3% |
Adaptive | 18.7% | 22.1% | 59.1% | 13.0% |
Power | 18.4% | 15.6% | 66.0% | 30.3% |
Geometric linear | 16.4% | 18.2% | 65.4% | 5.6% |
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Gladysz, B.; Ejsmont, K.; Kluczek, A.; Corti, D.; Marciniak, S. A Method for an Integrated Sustainability Assessment of RFID Technology. Resources 2020, 9, 107. https://doi.org/10.3390/resources9090107
Gladysz B, Ejsmont K, Kluczek A, Corti D, Marciniak S. A Method for an Integrated Sustainability Assessment of RFID Technology. Resources. 2020; 9(9):107. https://doi.org/10.3390/resources9090107
Chicago/Turabian StyleGladysz, Bartlomiej, Krzysztof Ejsmont, Aldona Kluczek, Donatella Corti, and Stanislaw Marciniak. 2020. "A Method for an Integrated Sustainability Assessment of RFID Technology" Resources 9, no. 9: 107. https://doi.org/10.3390/resources9090107