Addressing the Role of Sustainable Public Procurement as a Panacea for Sustainable Development in the Local Government Areas: The Episode of Nigeria

The coronavirus has displaced local communities across the nation as their livelihood is compromised. This study explores extensively the challenges confronting sustainable public procurement in the local government areas that bothers sustainable development amid COVID-19. This study conducted semi-structured interviews with eight procurement experts from eight leading local government areas with documented evidence of extensive procurement activity across four geopolitical zones of Nigeria to obtain primary data. Findings from this study suggest a tremendous decline in the livelihood of the rural communities amid the pandemic and ridicule of local government procurement practice across the region. The study also finds a significant level of interference by the state government that continually denies the local government administration from attaining sustainable development compared to their counterparts in the developed societies. Keywords: Sustainable public procurement, Sustainable development, Local government areas, COVID-19, Sub-Saharan Africa – Nigeria DOI: 10.7176/JESD/12-8-01 Publication date: April 30th 202

Assessing sustainability performance of high-tech firms through a hybrid approach

Purpose: In light of the lack of subjective criteria and scientific rationality in current sustainability performance assessment, the purpose of this paper is conducted to improve the sustainability performance assessment of high-tech firms by developing a hybrid approach that integrates quantitative and qualitative research methods. Design/methodology/approach: This study proposed a hybrid approach that integrates word frequency analysis, cluster analysis, grey theory and the decision-making and trial evaluation laboratory (DEMATEL) method. Specifically, this study identifies useful criteria using quantitative word frequency analysis as well as qualitative literature research. Then, cluster analysis is used to divide these criteria into different categories. Subsequently, this study applies the grey theory associated with the DEMATEL method to assess the sustainability performance of high-tech firms. Findings: The results reveal that the socio-environment is an important aspect underlying the corporate sustainability performance of high-tech firms. Therefore, high-tech firms should enhance their pollution emission control capabilities and increase investment in energy-conservation and emission-reduction technologies to drive sustainable development. In addition, increasing green product sales revenue and improving the guiding capability of green consumption are core issues that firms must address. Originality/value: This study assesses the sustainability performance of high-tech firms by applying a hybrid method. This method can be used to construct a framework for scientific sustainability performance assessment and to provide a clear direction for the sustainable development of firms

A general outline of a sustainable supply chain 4.0

[EN] This article presents a literature review to identify the current knowledge of supply chains 4.0 from the sustainability perspective. Reviewed papers were classified in terms of objectives, results, and sustainability approaches. Additionally, a critical discussion with the main results and recommendations for further research was carried out. Manufacturing supply chains have been contemplated but agri-food supply chains and chains related to diversified cropping systems have been also considered. In this way, 54 articles were identified and revised, and were classified according to the three main aspects of sustainability: economic, social, and environmental. The classification of articles indicated that more attention has been paid to the environmental aspect in the industry 4.0 (I4.0) context in the literature, while the social aspect has been paid less attention. Finally, reference frameworks were identified, along with the I4.0 models, algorithms, heuristics, metaheuristics, and technologies, which have enabled sustainability in supply chains.This research was supported by the European Commission Horizon 2020 project entitled 'Crop diversification and low-input farming cross Europe: From practitioners' engagement and ecosystems services to increased revenues and value chain organisation' (Diverfarming), grant agreement 728003; and the Spanish Ministry of Science, Innovation, and Universities project entitled 'Optimisation of zero-defects production technologies enabling supply chains 4.0 (CADS4.0)' (RTI2018-101344-B-I00).Cañas, H.; Mula, J.; Campuzano-Bolarín, F. (2020). A general outline of a sustainable supply chain 4.0. Sustainability. 12(19):1-17. https://doi.org/10.3390/su121979781171219Design Principles for Industrie 4.0 Scenarios https://ieeexplore.ieee.org/document/7427673Liao, Y., Deschamps, F., Loures, E. de F. R., & Ramos, L. F. P. (2017). Past, present and future of Industry 4.0 - a systematic literature review and research agenda proposal. International Journal of Production Research, 55(12), 3609-3629. doi:10.1080/00207543.2017.1308576Tseng, M.-L., Zhu, Q., Sarkis, J., & Chiu, A. S. F. (2018). Responsible consumption and production (RCP) in corporate decision-making models using soft computation. Industrial Management & Data Systems, 118(2), 322-329. doi:10.1108/imds-11-2017-0507Ghadimi, P., Wang, C., Lim, M. K., & Heavey, C. (2019). Intelligent sustainable supplier selection using multi-agent technology: Theory and application for Industry 4.0 supply chains. Computers & Industrial Engineering, 127, 588-600. doi:10.1016/j.cie.2018.10.050Wang, C., Ghadimi, P., Lim, M. K., & Tseng, M.-L. (2019). A literature review of sustainable consumption and production: A comparative analysis in developed and developing economies. 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Benchmarking: An International Journal. doi:10.1108/bij-03-2018-0056Ghafoorpoor Yazdi, P., Azizi, A., & Hashemipour, M. (2018). An Empirical Investigation of the Relationship between Overall Equipment Efficiency (OEE) and Manufacturing Sustainability in Industry 4.0 with Time Study Approach. Sustainability, 10(9), 3031. doi:10.3390/su10093031Braccini, A., & Margherita, E. (2018). Exploring Organizational Sustainability of Industry 4.0 under the Triple Bottom Line: The Case of a Manufacturing Company. Sustainability, 11(1), 36. doi:10.3390/su11010036Moghaddam, M., Cadavid, M. N., Kenley, C. R., & Deshmukh, A. V. (2018). Reference architectures for smart manufacturing: A critical review. Journal of Manufacturing Systems, 49, 215-225. doi:10.1016/j.jmsy.2018.10.006Paravizo, E., Chaim, O. C., Braatz, D., Muschard, B., & Rozenfeld, H. (2018). Exploring gamification to support manufacturing education on industry 4.0 as an enabler for innovation and sustainability. Procedia Manufacturing, 21, 438-445. doi:10.1016/j.promfg.2018.02.142Müller, J. M., Kiel, D., & Voigt, K.-I. (2018). What Drives the Implementation of Industry 4.0? The Role of Opportunities and Challenges in the Context of Sustainability. Sustainability, 10(1), 247. doi:10.3390/su10010247Kamble, S. S., Gunasekaran, A., & Gawankar, S. A. (2018). Sustainable Industry 4.0 framework: A systematic literature review identifying the current trends and future perspectives. Process Safety and Environmental Protection, 117, 408-425. doi:10.1016/j.psep.2018.05.009Hidayatno, A., Destyanto, A. R., & Hulu, C. A. (2019). Industry 4.0 Technology Implementation Impact to Industrial Sustainable Energy in Indonesia: A Model Conceptualization. Energy Procedia, 156, 227-233. doi:10.1016/j.egypro.2018.11.133Sustainable Value Stream Mapping and Technologies of Industry 4.0 in Manufacturing Process Reconfiguration: A Case Study in an Apparel Company https://ieeexplore.ieee.org/document/8476750Kumar, R., Singh, S. P., & Lamba, K. (2018). Sustainable robust layout using Big Data approach: A key towards industry 4.0. Journal of Cleaner Production, 204, 643-659. doi:10.1016/j.jclepro.2018.08.327Wiśniewska-Sałek, A. (2018). Sustainable Development in Accordance With the Concept of Industry 4.0 on the Example of the Furniture Industry. MATEC Web of Conferences, 183, 04005. doi:10.1051/matecconf/201818304005Müller, J. M., & Voigt, K.-I. (2018). Sustainable Industrial Value Creation in SMEs: A Comparison between Industry 4.0 and Made in China 2025. International Journal of Precision Engineering and Manufacturing-Green Technology, 5(5), 659-670. doi:10.1007/s40684-018-0056-zTsai, W.-H., & Lu, Y.-H. (2018). A Framework of Production Planning and Control with Carbon Tax under Industry 4.0. Sustainability, 10(9), 3221. doi:10.3390/su10093221Birkel, H., Veile, J., Müller, J., Hartmann, E., & Voigt, K.-I. (2019). Development of a Risk Framework for Industry 4.0 in the Context of Sustainability for Established Manufacturers. Sustainability, 11(2), 384. doi:10.3390/su11020384Roda-Sanchez, L., Garrido-Hidalgo, C., Hortelano, D., Olivares, T., & Ruiz, M. C. (2018). OperaBLE: An IoT-Based Wearable to Improve Efficiency and Smart Worker Care Services in Industry 4.0. Journal of Sensors, 2018, 1-12. doi:10.1155/2018/6272793Ardanza, A., Moreno, A., Segura, Á., de la Cruz, M., & Aguinaga, D. (2019). Sustainable and flexible industrial human machine interfaces to support adaptable applications in the Industry 4.0 paradigm. International Journal of Production Research, 57(12), 4045-4059. doi:10.1080/00207543.2019.1572932Zambon, I., Cecchini, M., Egidi, G., Saporito, M. G., & Colantoni, A. (2019). Revolution 4.0: Industry vs. Agriculture in a Future Development for SMEs. Processes, 7(1), 36. doi:10.3390/pr7010036Belaud, J.-P., Prioux, N., Vialle, C., & Sablayrolles, C. (2019). Big data for agri-food 4.0: Application to sustainability management for by-products supply chain. Computers in Industry, 111, 41-50. doi:10.1016/j.compind.2019.06.006Trivelli, L., Apicella, A., Chiarello, F., Rana, R., Fantoni, G., & Tarabella, A. (2019). From precision agriculture to Industry 4.0. British Food Journal, 121(8), 1730-1743. doi:10.1108/bfj-11-2018-0747Miranda, J., Ponce, P., Molina, A., & Wright, P. (2019). Sensing, smart and sustainable technologies for Agri-Food 4.0. Computers in Industry, 108, 21-36. doi:10.1016/j.compind.2019.02.002Stock, T., Obenaus, M., Kunz, S., & Kohl, H. (2018). Industry 4.0 as enabler for a sustainable development: A qualitative assessment of its ecological and social potential. Process Safety and Environmental Protection, 118, 254-267. doi:10.1016/j.psep.2018.06.026Chaim, O., Muschard, B., Cazarini, E., & Rozenfeld, H. (2018). Insertion of sustainability performance indicators in an industry 4.0 virtual learning environment. Procedia Manufacturing, 21, 446-453. doi:10.1016/j.promfg.2018.02.143Smart Factories in Industry 4.0: A Review of the Concept and of Energy Management Approached in Production Based on the Internet of Things Paradigm https://ieeexplore.ieee.org/document/7058728Bonilla, S., Silva, H., Terra da Silva, M., Franco Gonçalves, R., & Sacomano, J. (2018). Industry 4.0 and Sustainability Implications: A Scenario-Based Analysis of the Impacts and Challenges. Sustainability, 10(10), 3740. doi:10.3390/su10103740De Sousa Jabbour, A. B. L., Jabbour, C. J. C., Foropon, C., & Godinho Filho, M. (2018). When titans meet – Can industry 4.0 revolutionise the environmentally-sustainable manufacturing wave? The role of critical success factors. 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Sustainability, 10(12), 4511. doi:10.3390/su10124511IoT Solution for Energy Optimization in Industry 4.0: Issues of a Real-life Implementation https://ieeexplore.ieee.org/document/8534537Towards a System-of-Systems for Improved Road Construction Efficiency Using Lean and Industry 4.0 https://ieeexplore.ieee.org/document/8428698HERNANDEZ LUNA, M., ROBLEDO FAVA, R., FERNANDEZ DE CORDOBA CASTELLA, P., PAREDES, A., MICHINEL ALVAREZ, H., & ZARAGOZA FERNANDEZ, S. (2018). USE OF STATISTICAL CORRELATION FOR ENERGY MANAGEMENT IN OFFICE PREMISES ADOPTING TECHNIQUES OF THE INDUSTRY 4.0. DYNA, 93(1), 602-607. doi:10.6036/8844Energy Management in Industry 4.0 Ecosystem: A Review on Possibilities and Concerns https://www.daaam.info/Downloads/Pdfs/proceedings/proceedings_2018/097.pdfWang, X. V., & Wang, L. (2018). Digital twin-based WEEE recycling, recovery and remanufacturing in the background of Industry 4.0. 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Working Notes from the 1992 AAAI Spring Symposium on Practical Approaches to Scheduling and Planning

The symposium presented issues involved in the development of scheduling systems that can deal with resource and time limitations. To qualify, a system must be implemented and tested to some degree on non-trivial problems (ideally, on real-world problems). However, a system need not be fully deployed to qualify. Systems that schedule actions in terms of metric time constraints typically represent and reason about an external numeric clock or calendar and can be contrasted with those systems that represent time purely symbolically. The following topics are discussed: integrating planning and scheduling; integrating symbolic goals and numerical utilities; managing uncertainty; incremental rescheduling; managing limited computation time; anytime scheduling and planning algorithms, systems; dependency analysis and schedule reuse; management of schedule and plan execution; and incorporation of discrete event techniques

Artificial Intelligence in the Capitalist University

Using Marxist critique, this book explores manifestations of Artificial Intelligence (AI) in Higher Education and demonstrates how it contributes to the functioning and existence of the capitalist university. Challenging the idea that AI is a break from previous capitalist technologies, the book offers nuanced examination of the impacts of AI on the control and regulation of academic work and labour, on digital learning and remote teaching, and on the value of learning and knowledge. Applying a Marxist perspective, Preston argues that commodity fetishism, surveillance, and increasing productivity ushered in by the growth of AI, further alienates and exploits academic labour and commodifies learning and research. The text puts forward a solid theoretical framework and methodology for thinking about AI to inform critical and revolutionary pedagogies. Offering an impactful and timely analysis, this book provides a critical engagement and application of key Marxist concepts in the study of AI’s role in Higher Education. It will be of interest to those working or researching in Higher Education

Application of Business Analytics Approaches to Address Climate-Change-Related Challenges

Climate change is an existential threat facing humanity, civilization, and the natural world. It poses many multi-layered challenges that call for enhanced data-driven decision support methods to help inform society of ways to address the deep uncertainty and incomplete knowledge on climate change issues. This research primarily aims to apply management, decision, information, and data science theories and techniques to propose, build, and evaluate novel data-driven methodologies to improve understanding of climate-change-related challenges. Given that we pursue this work in the College of Management, each essay applies one or more of the three distinct business analytics approaches (i.e., descriptive, prescriptive, and predictive analysis) to aid in developing decision support capabilities. Given the rapid growth in data availability, we evaluate important data characteristics for each analysis, focusing on the data source, granularity, volume, structure, and quality. The final analysis consideration is the methods used on the data output to help coalesce the various model outputs into understandable visualizations, tables, and takeaways. We pursue three distinct business analytics challenges. First, we start with a natural language processing analysis to gain insights into the evolving climate change adaptation discussion in the scientific literature. We then create a stochastic network optimization model with recourse to provide coastal decision-makers with a cost-benefit analysis tool to simultaneously assess risks and costs to protect their community against rising seas. Finally, we create a decision support tool for helping organizations reduce greenhouse gas emissions through strategic sustainable energy purchasing. Although the three essays vary on their specific business analysis approaches, they all have a common theme of applying business analytics techniques to analyze, evaluate, visualize, and understand different facets of the climate change threat