7,531 research outputs found

    A Decision Support System for Economic Viability and Environmental Impact Assessment of Vertical Farms

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    Vertical farming (VF) is the practice of growing crops or animals using the vertical dimension via multi-tier racks or vertically inclined surfaces. In this thesis, I focus on the emerging industry of plant-specific VF. Vertical plant farming (VPF) is a promising and relatively novel practice that can be conducted in buildings with environmental control and artificial lighting. However, the nascent sector has experienced challenges in economic viability, standardisation, and environmental sustainability. Practitioners and academics call for a comprehensive financial analysis of VPF, but efforts are stifled by a lack of valid and available data. A review of economic estimation and horticultural software identifies a need for a decision support system (DSS) that facilitates risk-empowered business planning for vertical farmers. This thesis proposes an open-source DSS framework to evaluate business sustainability through financial risk and environmental impact assessments. Data from the literature, alongside lessons learned from industry practitioners, would be centralised in the proposed DSS using imprecise data techniques. These techniques have been applied in engineering but are seldom used in financial forecasting. This could benefit complex sectors which only have scarce data to predict business viability. To begin the execution of the DSS framework, VPF practitioners were interviewed using a mixed-methods approach. Learnings from over 19 shuttered and operational VPF projects provide insights into the barriers inhibiting scalability and identifying risks to form a risk taxonomy. Labour was the most commonly reported top challenge. Therefore, research was conducted to explore lean principles to improve productivity. A probabilistic model representing a spectrum of variables and their associated uncertainty was built according to the DSS framework to evaluate the financial risk for VF projects. This enabled flexible computation without precise production or financial data to improve economic estimation accuracy. The model assessed two VPF cases (one in the UK and another in Japan), demonstrating the first risk and uncertainty quantification of VPF business models in the literature. The results highlighted measures to improve economic viability and the viability of the UK and Japan case. The environmental impact assessment model was developed, allowing VPF operators to evaluate their carbon footprint compared to traditional agriculture using life-cycle assessment. I explore strategies for net-zero carbon production through sensitivity analysis. Renewable energies, especially solar, geothermal, and tidal power, show promise for reducing the carbon emissions of indoor VPF. Results show that renewably-powered VPF can reduce carbon emissions compared to field-based agriculture when considering the land-use change. The drivers for DSS adoption have been researched, showing a pathway of compliance and design thinking to overcome the ‘problem of implementation’ and enable commercialisation. Further work is suggested to standardise VF equipment, collect benchmarking data, and characterise risks. This work will reduce risk and uncertainty and accelerate the sector’s emergence

    A Comparative Study on Students’ Learning Expectations of Entrepreneurship Education in the UK and China

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    Entrepreneurship education has become a critical subject in academic research and educational policy design, occupying a central role in contemporary education globally. However, a review of the literature indicates that research on entrepreneurship education is still in a relatively early stage. Little is known about how entrepreneurship education learning is affected by the environmental context to date. Therefore, combining the institutional context and focusing on students’ learning expectations as a novel perspective, the main aim of the thesis is to address the knowledge gap by developing an original conceptual framework to advance understanding of the dynamic learning process of entrepreneurship education through the lens of self-determination theory, thereby providing a basis for advancing understanding of entrepreneurship education. The author adopted an epistemological positivism philosophy and a deductive approach. This study gathered 247 valid questionnaires from the UK (84) and China (163). It requested students to recall their learning expectations before attending their entrepreneurship courses and to assess their perceptions of learning outcomes after taking the entrepreneurship courses. It was found that entrepreneurship education policy is an antecedent that influences students' learning expectations, which is represented in the difference in student autonomy. British students in active learning under a voluntary education policy have higher autonomy than Chinese students in passive learning under a compulsory education policy, thus having higher learning expectations, leading to higher satisfaction. The positive relationship between autonomy and learning expectations is established, which adds a new dimension to self-determination theory. Furthermore, it is also revealed that the change in students’ entrepreneurial intentions before and after their entrepreneurship courses is explained by understanding the process of a business start-up (positive), hands-on business start-up opportunities (positive), students’ actual input (positive) and tutors’ academic qualification (negative). The thesis makes contributions to both theory and practice. The findings have far reaching implications for different parties, including policymakers, educators, practitioners and researchers. Understanding and shaping students' learning expectations is a critical first step in optimising entrepreneurship education teaching and learning. On the one hand, understanding students' learning expectations of entrepreneurship and entrepreneurship education can help the government with educational interventions and policy reform, as well as improving the quality and delivery of university-based entrepreneurship education. On the other hand, entrepreneurship education can assist students in establishing correct and realistic learning expectations and entrepreneurial conceptions, which will benefit their future entrepreneurial activities and/or employment. An important implication is that this study connects multiple stakeholders by bridging the national-level institutional context, organisational-level university entrepreneurship education, and individual level entrepreneurial learning to promote student autonomy based on an understanding of students' learning expectations. This can help develop graduates with their ability for autonomous learning and autonomous entrepreneurial behaviour. The results of this study help to remind students that it is them, the learners, their expectations and input that can make the difference between the success or failure of their study. This would not only apply to entrepreneurship education but also to other fields of study. One key message from this study is that education can be encouraged and supported but cannot be “forced”. Mandatory entrepreneurship education is not a quick fix for the lack of university students’ innovation and entrepreneurship. More resources must be invested in enhancing the enterprise culture, thus making entrepreneurship education desirable for students

    Consolidation of Urban Freight Transport – Models and Algorithms

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    Urban freight transport is an indispensable component of economic and social life in cities. Compared to other types of transport, however, it contributes disproportionately to the negative impacts of traffic. As a result, urban freight transport is closely linked to social, environmental, and economic challenges. Managing urban freight transport and addressing these issues poses challenges not only for local city administrations but also for companies, such as logistics service providers (LSPs). Numerous policy measures and company-driven initiatives exist in the area of urban freight transport to overcome these challenges. One central approach is the consolidation of urban freight transport. This dissertation focuses on urban consolidation centers (UCCs) which are a widely studied and applied measure in urban freight transport. The fundamental idea of UCCs is to consolidate freight transport across companies in logistics facilities close to an urban area in order to increase the efficiency of vehicles delivering goods within the urban area. Although the concept has been researched and tested for several decades and it was shown that it can reduce the negative externalities of freight transport in cities, in practice many UCCs struggle with a lack of business participation and financial difficulties. This dissertation is primarily focused on the costs and savings associated with the use of UCCs from the perspective of LSPs. The cost-effectiveness of UCC use, which is also referred to as cost attractiveness, can be seen as a crucial condition for LSPs to be interested in using UCC systems. The overall objective of this dissertation is two-fold. First, it aims to develop models to provide decision support for evaluating the cost-effectiveness of using UCCs. Second, it aims to analyze the impacts of urban freight transport regulations and operational characteristics on the cost attractiveness of using UCCs from the perspective of LSPs. In this context, a distinction is made between UCCs that are jointly operated by a group of LSPs and UCCs that are operated by third parties who offer their urban transport service for a fee. The main body of this dissertation is based on three research papers. The first paper focuses on jointly-operated UCCs that are operated by a group of cooperating LSPs. It presents a simulation model to analyze the financial impacts on LSPs participating in such a scheme. In doing so, a particular focus is placed on urban freight transport regulations. A case study is used to analyze the operation of a jointly-operated UCC for scenarios involving three freight transport regulations. The second and third papers take on a different perspective on UCCs by focusing on third-party operated UCCs. In contrast to the first paper, the second and third papers present an evaluation approach in which the decision to use UCCs is integrated with the vehicle route planning of LSPs. In addition to addressing the basic version of this integrated routing problem, known as the vehicle routing problem with transshipment facilities (VRPTF), the second paper presents problem extensions that incorporate time windows, fleet size and mix decisions, and refined objective functions. To heuristically solve the basic problem and the new problem variants, an adaptive large neighborhood search (ALNS) heuristic with embedded local search heuristic and set partitioning problem (SPP) is presented. Furthermore, various factors influencing the cost attractiveness of UCCs, including time windows and usage fees, are analyzed using a real-world case study. The third paper extends the work of the second paper and incorporates daily and entrance-based city toll schemes and enables multi-trip routing. A mixed-integer linear programming (MILP) formulation of the resulting problem is proposed, as well as an ALNS solution heuristic. Moreover, a real-world case study with three European cities is used to analyze the impact of the two city toll systems in different operational contexts

    Industry 4.0: product digital twins for remanufacturing decision-making

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    Currently there is a desire to reduce natural resource consumption and expand circular business principles whilst Industry 4.0 (I4.0) is regarded as the evolutionary and potentially disruptive movement of technology, automation, digitalisation, and data manipulation into the industrial sector. The remanufacturing industry is recognised as being vital to the circular economy (CE) as it extends the in-use life of products, but its synergy with I4.0 has had little attention thus far. This thesis documents the first investigating into I4.0 in remanufacturing for a CE contributing a design and demonstration of a model that optimises remanufacturing planning using data from different instances in a product’s life cycle. The initial aim of this work was to identify the I4.0 technology that would enhance the stability in remanufacturing with a view to reducing resource consumption. As the project progressed it narrowed to focus on the development of a product digital twin (DT) model to support data-driven decision making for operations planning. The model’s architecture was derived using a bottom-up approach where requirements were extracted from the identified complications in production planning and control that differentiate remanufacturing from manufacturing. Simultaneously, the benefits of enabling visibility of an asset’s through-life health were obtained using a DT as the modus operandi. A product simulator and DT prototype was designed to use Internet of Things (IoT) components, a neural network for remaining life estimations and a search algorithm for operational planning optimisation. The DT was iteratively developed using case studies to validate and examine the real opportunities that exist in deploying a business model that harnesses, and commodifies, early life product data for end-of-life processing optimisation. Findings suggest that using intelligent programming networks and algorithms, a DT can enhance decision-making if it has visibility of the product and access to reliable remanufacturing process information, whilst existing IoT components provide rudimentary “smart” capabilities, but their integration is complex, and the durability of the systems over extended product life cycles needs to be further explored

    Developing a Decision Support System for Integrated Decision-Making in Purchasing and Scheduling under Lead Time Uncertainty

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    Decision-making in supply chain management is complex because of the relations between planning tasks from different stages and planning levels. Uncertainties such as unpredictable supplier lead times and supply chain disruptions further complicate decision-making. Considering the case study of a company in printed circuit board assembly, a three-level concept is proposed that includes a decision support system. The global single-source supply network is characterized by highly variable lead times. Hence, the company maintains high inventory levels to prevent running out of stock. The decision support system considers the purchasing and scheduling decision problems in an integrated way. The prototypical implementation of the purchasing algorithm uses a genetic algorithm that recommends reorder days and order quantities using a simulation model. In addition, it evaluates the risks of the recommended solution by calculating the probability of stockouts for each order cycle

    Flexographic printed nanogranular LBZA derived ZnO gas sensors: Synthesis, printing and processing

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    Within this document, investigations of the processes towards the production of a flexographic printed ZnO gas sensor for breath H2 analysis are presented. Initially, a hexamethylenetetramine (HMTA) based, microwave assisted, synthesis method of layered basic zinc acetate (LBZA) nanomaterials was investigated. Using the synthesised LBZA, a dropcast nanogranular ZnO gas sensor was produced. The testing of the sensor showed high sensitivity towards hydrogen with response (Resistanceair/ Resistancegas) to 200 ppm H2 at 328 °C of 7.27. The sensor is highly competitive with non-catalyst surface decorated sensors and sensitive enough to measure current H2 guideline thresholds for carbohydrate malabsorption (Positive test threshold: 20 ppm H2, Predicted response: 1.34). Secondly, a novel LBZA synthesis method was developed, replacing the HMTA by NaOH. This resulted in a large yield improvement, from a [OH-] conversion of 4.08 at% to 71.2 at%. The effects of [OH-]/[Zn2+] ratio, microwave exposure and transport to nucleation rate ratio on purity, length, aspect ratio and polydispersity were investigated in detail. Using classical nucleation theory, analysis of the basal layer charge symmetries, and oriented attachment theory, a dipole-oriented attachment reaction mechanism is presented. The mechanism is the first theory in literature capable of describing all observed morphological features along length scales. The importance of transport to nucleation rate ratio as the defining property that controls purity and polydispersity is then shown. Using the NaOH derived LBZA, a flexographic printing ink was developed, and proof-of-concept sensors printed. Gas sensing results showed a high response to 200 ppm H2 at 300 °C of 60.2. Through IV measurements and SEM analysis this was shown to be a result of transfer of silver between the electrode and the sensing layer during the printing process. Finally, Investigations into the intense pulsed light treatment of LBZA were conducted. The results show that dehydration at 150 °C prior to exposure is a requirement for successful calcination, producing ZnO quantum dots (QDs) in the process. SEM measurements show mean radii of 1.77-2.02 nm. The QDs show size confinement effects with the exciton blue shifting by 0.105 eV, and exceptionally low defect emission in photoluminescence spectra, indicative of high crystalline quality, and high conductivity. Due to the high crystalline quality and amenity to printing, the IPL ZnO QDs have numerous potential uses ranging from sensing to opto-electronic devices

    Impacts of clear-cutting on soil fungal communities and their activities in boreal forests - A metatranscriptomic approach

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    Large-scale forestry has reduced and fragmented the area of primary forest and greatly impacted communities of organisms, above and below ground. Fungal com-munities, which are pivotal in boreal forest soil functions, are vulnerable to tree har-vesting. Changes in their community composition may be followed by loss of key functions and ultimately affect carbon and nutrient cycling. By using various molec-ular approaches, such as metabarcoding, transcriptomics and metatranscriptomics, this thesis aims to investigate how clear-cut forestry affects the composition and traits of soil fungal communities. In a shorter time perspective, clear-cutting eliminate ectomycorrhizal fungi but stimulates growth of saprotrophic fungi. Clear-cutting also enhanced cellulose and lignin decomposition, which may reduce soil carbon stocks in the short-term and potentially cause eutrophication in the mid-term. After 35 years, the ectomycorrhizal fungal community composition in re-established secondary forest was still not re-stored to the same composition as in forest with longer continuity, although its bio-mass had recovered. Particularly Cortinarius, a genus with a key functional role in lignin decomposition, was largely missing in secondary forest. Ectomycorrhizal Cortinarius species accounted for a large fraction of gene transcription of ligninolytic peroxidases in forests with long continuity, and loss of this function could impair long-term nitrogen cycling and soil fertility. Overall, this thesis presents evidence that clear-cutting forestry has extensive ef-fects on fungal biodiversity, with major short-term consequences for soil fungi and their facilitation of decomposition and nutrient cycling, but also long-term effects on ectomycorrhizal communities that should be considered in further evaluation of management practices

    Infrastructure for the Circular Economy: The Role of Policy in System Change

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    The concept of a Circular Economy has gained policy traction as a mainstream solution for preserving and renewing. This work sought to understand which policy instruments have been successful, might still be necessary, and are most likely in the future to deliver a high penetration Circular Economy for materials, wastes and associated energy. Waste related policy decisions in England over the past 20 years were reviewed, exploring the regulatory means that had achieved the current 44% diversion of municipal wastes from landfill. The hypothesis is that to achieve a far-reaching Circular Economy, at a greater scale, across different sectors and for a wider product range, suitable physical infrastructure (waste treatment assets) must be available to circulate those materials in the economy. Furthermore, the study set out to value financially and in terms of social and economic benefits that could be derived from a circular approach across the whole economy. We found the financial value to be significant at circa 1.5% of English GDP or  32bn and 72,000-175,000 jobs. It was demonstrated by calculation that DEFRA analysis (for England) underestimated the capacity gap for infrastructure by 11.3 million tonnes per annum in 2014. The policy findings were that the early implementation of blunt instruments such as a landfill tax and separate collection of recyclables did allow for diversion performance of approximately 45-50% recycling and composting, the remaining 50% of which was progressively treated by energy from waste rather than landfill. It is apparent that policies that drive system changes are effective in bringing about ecological transformations of how societies, economies, and governments operate at all levels. This ecological transformation is undoubtedly difficult to achieve since it will require consumers, manufacturers, regulators, policymakers, media, and business all to move differently and together, but nevertheless it is critical at a global scale.Open Acces

    Coping with the postponement boundary problem: an empirical investigation in global food supply chains

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    Purpose – The postponement boundary problem entails that duties and cross-border trade complexity can lead companies to geographically postpone operations to downstream global facilities. The present study aims at investigating the problem to provide insights into the drivers behind the choice of different postponement strategies for global food supply chains. Design/methodology/approach – A single case study was conducted considering an Italian company exporting olive oil toward the United States. Two global postponement strategies, previously formalized in the literature, were tailored for food supply chains. A multi-methodological approach was adopted, combining data obtained through exploratory case research with empirically-grounded analytical modeling. A sensitivity analysis was also performed, to investigate outcomes related to the considered problem when changing key parameters. Findings – Bulky and heavy packing materials account for a big percentage of finished products’ volume and weight, and this can deeply affect strategies’ cost-effectiveness. Postponing packaging operations could allow for taking advantage of lower tariffs levied on bulk goods, contributing to significantly lower duties to be paid. However, important trade-offs could arise related to the required investments, and the fiscal regulatory frameworks must be carefully examined. Originality/value – This study offers an empirical investigation of the postponement boundary problem, which is largely unexplored in the current literature. It also tackles an understudied empirical context as global food supply chains. It summarizes the drivers behind and explores the costs related to the implementation of different strategies, offering an original quantitative approach that could support practitioners’ decision-making. Lastly, it formalizes five propositions that could pave the way for further research inquiries
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