12,328 research outputs found
A Design Science Research Approach to Smart and Collaborative Urban Supply Networks
Urban supply networks are facing increasing demands and challenges and thus constitute a relevant field for research and practical development. Supply chain management holds enormous potential and relevance for society and everyday life as the flow of goods and information are important economic functions. Being a heterogeneous field, the literature base of supply chain management research is difficult to manage and navigate. Disruptive digital technologies and the implementation of cross-network information analysis and sharing drive the need for new organisational and technological approaches. Practical issues are manifold and include mega trends such as digital transformation, urbanisation, and environmental awareness.
A promising approach to solving these problems is the realisation of smart and collaborative supply networks. The growth of artificial intelligence applications in recent years has led to a wide range of applications in a variety of domains. However, the potential of artificial intelligence utilisation in supply chain management has not yet been fully exploited. Similarly, value creation increasingly takes place in networked value creation cycles that have become continuously more collaborative, complex, and dynamic as interactions in business processes involving information technologies have become more intense.
Following a design science research approach this cumulative thesis comprises the development and discussion of four artefacts for the analysis and advancement of smart and collaborative urban supply networks. This thesis aims to highlight the potential of artificial intelligence-based supply networks, to advance data-driven inter-organisational collaboration, and to improve last mile supply network sustainability. Based on thorough machine learning and systematic literature reviews, reference and system dynamics modelling, simulation, and qualitative empirical research, the artefacts provide a valuable contribution to research and practice
Corporate Social Responsibility: the institutionalization of ESG
Understanding the impact of Corporate Social Responsibility (CSR) on firm performance as it relates to industries reliant on technological innovation is a complex and perpetually evolving challenge. To thoroughly investigate this topic, this dissertation will adopt an economics-based structure to address three primary hypotheses. This structure allows for each hypothesis to essentially be a standalone empirical paper, unified by an overall analysis of the nature of impact that ESG has on firm performance. The first hypothesis explores the evolution of CSR to the modern quantified iteration of ESG has led to the institutionalization and standardization of the CSR concept. The second hypothesis fills gaps in existing literature testing the relationship between firm performance and ESG by finding that the relationship is significantly positive in long-term, strategic metrics (ROA and ROIC) and that there is no correlation in short-term metrics (ROE and ROS). Finally, the third hypothesis states that if a firm has a long-term strategic ESG plan, as proxied by the publication of CSR reports, then it is more resilience to damage from controversies. This is supported by the finding that pro-ESG firms consistently fared better than their counterparts in both financial and ESG performance, even in the event of a controversy. However, firms with consistent reporting are also held to a higher standard than their nonreporting peers, suggesting a higher risk and higher reward dynamic. These findings support the theory of good management, in that long-term strategic planning is both immediately economically beneficial and serves as a means of risk management and social impact mitigation. Overall, this contributes to the literature by fillings gaps in the nature of impact that ESG has on firm performance, particularly from a management perspective
Assessing performance of artificial neural networks and re-sampling techniques for healthcare datasets.
Re-sampling methods to solve class imbalance problems have shown to improve classification accuracy by mitigating the bias introduced by differences in class size. However, it is possible that a model which uses a specific re-sampling technique prior to Artificial neural networks (ANN) training may not be suitable for aid in classifying varied datasets from the healthcare industry. Five healthcare-related datasets were used across three re-sampling conditions: under-sampling, over-sampling and combi-sampling. Within each condition, different algorithmic approaches were applied to the dataset and the results were statistically analysed for a significant difference in ANN performance. The combi-sampling condition showed that four out of the five datasets did not show significant consistency for the optimal re-sampling technique between the f1-score and Area Under the Receiver Operating Characteristic Curve performance evaluation methods. Contrarily, the over-sampling and under-sampling condition showed all five datasets put forward the same optimal algorithmic approach across performance evaluation methods. Furthermore, the optimal combi-sampling technique (under-, over-sampling and convergence point), were found to be consistent across evaluation measures in only two of the five datasets. This study exemplifies how discrete ANN performances on datasets from the same industry can occur in two ways: how the same re-sampling technique can generate varying ANN performance on different datasets, and how different re-sampling techniques can generate varying ANN performance on the same dataset
Statistical-dynamical analyses and modelling of multi-scale ocean variability
This thesis aims to provide a comprehensive analysis of multi-scale oceanic variabilities using various statistical and dynamical tools and explore the data-driven methods for correct statistical emulation of the oceans. We considered the classical, wind-driven, double-gyre ocean circulation model in quasi-geostrophic approximation and obtained its eddy-resolving solutions in terms of potential vorticity anomaly and geostrophic streamfunctions. The reference solutions possess two asymmetric gyres of opposite circulations and a strong meandering eastward jet separating them with rich eddy activities around it, such as the Gulf Stream in the North Atlantic and Kuroshio in the North Pacific.
This thesis is divided into two parts. The first part discusses a novel scale-separation method based on the local spatial correlations, called correlation-based decomposition (CBD), and provides a comprehensive analysis of mesoscale eddy forcing. In particular, we analyse the instantaneous and time-lagged interactions between the diagnosed eddy forcing and the evolving large-scale PVA using the novel `product integral' characteristics. The product integral time series uncover robust causality between two drastically different yet interacting flow quantities, termed `eddy backscatter'. We also show data-driven augmentation of non-eddy-resolving ocean models by feeding them the eddy fields to restore the missing eddy-driven features, such as the merging western boundary currents, their eastward extension and low-frequency variabilities of gyres.
In the second part, we present a systematic inter-comparison of Linear Regression (LR), stochastic and deep-learning methods to build low-cost reduced-order statistical emulators of the oceans. We obtain the forecasts on seasonal and centennial timescales and assess them for their skill, cost and complexity. We found that the multi-level linear stochastic model performs the best, followed by the ``hybrid stochastically-augmented deep learning models''. The superiority of these methods underscores the importance of incorporating core dynamics, memory effects and model errors for robust emulation of multi-scale dynamical systems, such as the oceans.Open Acces
Political Islam and grassroots activism in Turkey : a study of the pro-Islamist Virtue Party's grassroots activists and their affects on the electoral outcomes
This thesis presents an analysis of the spectacular rise of political Islam in Turkey. It has two aims: first to understand the underlying causes of the rise of the Welfare Party which -later became the Virtue Party- throughout the 1990s, and second to analyse how grassroots activism influenced this process. The thesis reviews the previous literature on the Islamic fundamentalist movements, political parties, political party systems and concentrates on the local party organisations and their effects on the party's electoral performance. It questions the categorisation of Islamic fundamentalism as an appropriate label for this movement. An exploration of such movements is particularly important in light of the event of 11`x' September. After exploring existing theoretical and case studies into political Islam and party activism, I present my qualitative case study. I have used ethnographic methodology and done participatory observations among grassroots activists in Ankara's two sub-districts covering 105 neighbourhoods. I examined the Turkish party system and the reasons for its collapse. It was observed that as a result of party fragmentation, electoral volatility and organisational decline and decline in the party identification among the citizens the Turkish party system has declined. However, the WP/VP profited from this trend enormously and emerged as
the main beneficiary of this process. Empirical data is analysed in four chapters, dealing with the different aspects of the Virtue Party's local organisations and grassroots activists. They deal with change and continuity in the party, the patterns of participation, the routes and motives for becoming a party activist, the profile of party activists and the local party organisations. I explore what they do and how they do it. The analysis reveals that the categorisation of Islamic fundamentalism is misplaced and the rise of political Islam in Turkey cannot be explained as religious revivalism or the rise of Islamic fundamentalism. It is a political force that drives its strength from the urban poor which has been harshly affected by the IMF directed neoliberal economy policies. In conclusion, it is shown that the WP/VP's electoral chances were significantly improved by its very efficient and effective party organisations and highly committed grassroots activists
Omics measures of ageing and disease susceptibility
While genomics has been a major field of study for decades due to relatively inexpensive genotyping arrays, the recent advancement of technology has also allowed the measure and study of various âomicsâ. There are now numerous methods and platforms available that allow high throughput and high dimensional quantification of many types of biological molecules. Traditional genomics and transcriptomics are now joined by proteomics, metabolomics, glycomics, lipidomics and epigenomics.
I was lucky to have access to a unique resource in the Orkney Complex Disease Study (ORCADES), a cohort of individuals from the Orkney Islands that are extremely deeply annotated. Approximately 1000 individuals in ORCADES have genomics, proteomics, lipidomics, glycomics, metabolomics, epigenomics, clinical risk factors and disease phenotypes, as well as body composition measurements from whole body scans. In addition to these cross-sectional omics and health related measures, these individuals also have linked electronic health records (EHR) available, allowing the assessment of the effect of these omics measures on incident disease over a ~10-year follow up period. In this thesis I use this phenotype rich resource to investigate the relationship between multiple types of omics measures and both ageing and health outcomes.
First, I used the ORCADES data to construct measures of biological age (BA). The idea that there is an underlying rate at which the body deteriorates with age that varies between individuals of the same chronological age, this biological age, would be more indicative of health status, functional capacity and risk of age-related diseases than chronological age. Previous models estimating BA (ageing clocks) have predominantly been built using a single type of omics assay and comparison between different omics ageing clocks has been limited. I performed the most exhaustive comparison of different omics ageing clocks yet, with eleven clocks spanning nine different omics assays. I show that different omics clocks overlap in the information they provide about age, that some omics clocks track more generalised ageing while others track specific disease risk factors and that omics ageing clocks are prognostic of incident disease over and above chronological age.
Second, I assessed whether individually or in multivariable models, omics measures are associated with health-related risk factors or prognostic of incident disease over 10 years post-assessment. I show that 2,686 single omics biomarkers are associated with 10 risk factors and 44 subsequent incident diseases. I also show that models built using multiple biomarkers from whole body scans, metabolomics, proteomics and clinical risk factors are prognostic of subsequent diabetes mellitus and that clinical risk factors are prognostic of incident hypertensive disorders, obesity, ischaemic heart disease and Framingham risk score.
Third, I investigated the genetic architecture of a subset of the proteomics measures available in ORCADES, specifically 184 cardiovascular-related proteins. Combining genome-wide association (GWAS) summary statistics from ORCADES and 17 other cohorts from the SCALLOP Consortium, giving a maximum sample size of 26,494 individuals, I performed 184 genome-wide association meta-analyses (GWAMAs) on the levels of these proteins circulating in plasma. I discovered 592 independent significant loci associated with the levels of at least one protein. I found that between 8-37% of these significant loci colocalise with known expression quantitative trait loci (eQTL). I also find evidence of causal associations between 11 plasma protein levels and disease susceptibility using Mendelian randomisation, highlighting potential candidate drug targets
Management controls, government regulations, customer involvement: Evidence from a Chinese family-owned business
This research reports on a case study of a family-owned elevator manufacturing company in China, where management control was sandwiched between the state policies and global customer production requirements. By analysing the role of government and customer, this thesis aimed to illustrate how management control operated in a family-owned business and to see how and why they do management control differently. In particular, it focused on how international production standards and existing Chinese industry policies translated into a set of the management control practices through a local network within the family-owned business I studied.
Based on an ethnographic approach to research, I spent six months in the field, conducted over 30 interviews, several conservations, and reviewed relevant internal documents to understand how management control (MC) techniques with humans cooperated in the company. I also understood how two layers of pressure have shaped company behaviour, and how a company located in a developing country is connecting with global network. I also found there is considerable tension among key actors and investigated how the company responded and managed it.
Drawing on Actor Network Theory (ANT), I analysed the interviews from key actors, examined the role of government regulations and customer requirements to see how management control being managed under two layers of pressure, i.e., the government regulations (e.g., labour, tax, environment control) and customer requirement (e.g., quality and production control). Management controls were an obligatory passage point (OPP), and transformation of those elements of Western production requirements and government requirements arrived at the Chinese local factory and influenced management control and budgeting.
The findings suggest that management control systems are not only a set of technical procedures, but it is also about managing tensions. This understanding shows a linear perspective on MC practices rather than a social perspective. However, when we use ANT as a theoretical perspective, we see those actors who, being obliged and sandwiched, and controlled by external forces for them to follow. Consequently, human actors must work in an unavoidable OPP. This is the tension they face which constructed mundane practices of MC. Hence, MCs are managing such tensions. This study contributes to management control research by analysing management controls in terms of OPP, extends our understanding by illustrating the role of the government and customers, and our understanding of family-owned business from a management controls perspective in a developing country
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